FSL in Review 2002 - 2003

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Acronyms and Terms


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Nita Fullerton


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FIR 2002 - 2003 FRD MastHead
Steven E. Koch, Chief
(303-497-5487)

Web Homepage: http://www-frd.fsl.noaa.gov/

Steven C. Albers, Senior Meteorologist, 303-497-6057
Robert L. Anderson, Research Associate, 303-497-6876
Dr. Stanley G. Benjamin, Chief, RAPB, 303-497-6387
Dr. Ligia R. Bernardet, Meteorologist, 303-497-4315
Dr. Daniel L. Birkenheuer, Meteorologist, 303-497-5584
Dr. John M. Brown, Meteorologist, 303-497-6867
Dr. Gerald L. Browning, Mathematician, 303-497-6772
Kevin J. Brundage, Computer Specialist, 303-497-7246
Scott D. Buennemeyer, Systems Admin,. 303-497-6894
Dr. Fernando Caracena, Meteorologist, 303-497-6269
Susan C. Carsten, Secretary OA, 303-497-6779
Randall S. Collander, Meteorologist, 303-497-5960
Dr. Dezso Devenyi, Meteorologist, 303-497-6827
Gary Fisher, Systems Admin., 303-497-6754
Nita B. Fullerton, Writer/Editor, 303-497-6995
Dr. Georg A. Grell, Meteorologist, 303-497-6924
Thomas D. Helman, STEP Student, 303-497-7263
Brian D. Jamison, Meteorologist, 303-497-6079
Bernadette M. Johnson, Secretary OA, 303-497-7260
Dr. Dongsoo Kim, Research Associate, 303-497-6725
Dr. Chungu (Dan) Lu, Meteorologist, 303-497-6776
Dr. Adrian Marroquin, Meteorologist, 303-497-6202
Paula T. McCaslin, Computer Analyst, 303-497-3187
Dr. John A. McGinley, Chief, LAPB, 303-497-6161
Dr. William R. Moninger, Physicist, 303-497-6435
Dr. Mariusz Pagowski, Guest Researcher, 303-497-6443
Dr. Steven E. Peckham, Meteorologist, 303-497-7978
Paul J. Schultz, Meteorologist, 303-497-6997
Barry E. Schwartz, Meteorologist, 303-497-6481
Jared R. Seehafer, STEP Student, 303-497-4554
Brent Shaw, Meteorologist, 303-497-6100
Thomas W. Shilling, Electronics Engineer, 303-497-6876
John R. Smart, Meteorologist, 303-497-6590
Tanya G. Smirnova, Meteorologist, 303-497-6253
Tracy Lorraine Smith, Meteorologist, 303-497-6727
Edward J. Szoke, Meteorologist, 303-497-7395
Dr. Edward I. Tollerud, Meteorologist, 303-497-6127
Diane I. Vinaske, Secretary OA, 303-497-6629
Dr. Steven S. Weygandt, Meteorologist, 303-497-5529
Linda S. Wharton, Computer Specialist, 303-497-7239
Dr. Yuanfu Xie, Computer Scientist, 303-497-6846

(The above roster, current when document is published, includes
government, cooperative agreement, and commercial affiliate staff.)

Address: NOAA Forecast Systems Laboratory – Mail Code: FS1
David Skaggs Research Center
325 Broadway
Boulder, Colorado 80305-3328


Objectives

The Forecast Research Division (FRD) is home to most of the research in FSL on short-range numerical weather prediction (NWP), development of advanced modeling and data assimilation techniques, diagnostic studies of mesoscale weather phenomena, and applications of NWP to nonmeteorological uses. A major emphasis involves the assimilation of operational, research, and future meteorological observations for analyzing current atmospheric conditions and the subsequent generation of short-range numerical forecasts. Produced in real time at frequent intervals on national and local scales, these analyses and forecasts are valuable to commercial aviation, civilian and military weather forecasting, the energy industry, regional air pollution prediction, and emergency preparedness. FRD also has supported several large meteorological field experiments and continues to perform this service to the community.

The Forecast Research Division comprises three branches:

The Regional Analysis and Prediction Branch supports the following research programs:

    Rapid Update Cycle (RUC) – A complete analysis/forecast system for hourly assimilation of meteorological observations over the United States into a numerical prediction model, the RUC has been implemented as an operational forecast system at the National Centers for Environmental Prediction (NCEP). The branch develops and tests improvements to the RUC and its research counterpart, the Mesoscale Analysis and Prediction System (MAPS), in the following areas:
    • Data Assimilation – Improved techniques for estimating meteorological parameters on a regular grid, combining information from in situ and remote observations with that from a forecast model, and investigation of uses for new data sources, such as rapid updating using Geostationary Operational Environmental Satellite (GOES) raw radiances and derived products. The latter task is being performed partly in collaboration with other members of the Joint Center for Satellite Data Assimilation, National Envirionmental Satellite, Data, and Information Service (NESDIS); National Aeronautics and Space Administration (NASA); and National Centers for Environmental Protection (NCEP).
    • Numerical Prediction – Design, testing, and implementation of improvements to the RUC/MAPS numerical prediction model, with a major emphasis on improving representation of processes near the surface and in clouds, which exert a strong control on mesoscale forecasts.
    • Analysis and Model Verification – Statistical and subjective evaluations of RUC/MAPS analysis and forecast products for standard atmospheric variables, surface conditions, aviation-impact variables, clouds, and precipitation.
    • Data Sensitivity Studies – Using the RUC, conducted studies to determine the effects of different types of observations on short-range numerical forecasts, including wind profilers, GPS, and space wind lidar systems of the future.

    RUC Applications – Development of coupled atmospheric/land surface model capability in support of the Global Energy and Water Cycle Experiment (GEWEX) programs and the NCEP implementation of the RUC, forecasting of aviation impact variables (icing, turbulence, ceiling, and visibility) in support of the Federal Aviation Administration (FAA), wind forecasting applied to wind energy utilization, and real-time support for field projects in which NOAA is engaged.

    Collaborative Modeling Projects – Lead role in the development and evaluation of the coupled MM5/Air Chemistry model (Figure 16) and the WRF/Air Chemistry model, continued collaboration with NCAR in the advancement of the science of modeling precipitation physics, participation in the development of the Weather Research and Forecasting (WRF) model system and nonhydrostatic generalized vertical coordinate model, and, finally, development of a RUC Short-Range Ensemble Forecast (SREF) system in collaboration with NCEP.

Figure 16 - NETAQ Domains

Figure 16. Domains over which air quality and weather forecasts were produced in real time – using the MM5/chem model – during the 2002 New England Temperature and Air Quality (TAQ) pilot experiment.

The Local Analysis and Prediction Branch is engaged in the following efforts:

    Local Analysis and Prediction System (LAPS) – Incorporation of local datasets into numerical models (e.g., MM5, RAMS, WRF) for the production of very detailed analyses of local weather conditions and short-range forecasts. The model is updated using variational methods and Kalman filtering techniques with new observations at least hourly. A diabatic initialization procedure known as the “hot start” has been developed for reducing the problem of cloud and precipitation “spinup” in the early hours of model integration. LAPS supports a broad clientele of mostly government and military entities, including the the National Weather Service (NWS), Federal Aviation Administration (FAA), Federal High Ways Administration (FHWA), U.S. Air Force Weather Agency (AFWA), Department of Defense (DOD/Army, Lockheed Martin, the Central Weather Bureau of Taiwan, and the Korean Meteorological Administration.

    LAPS Observation Simulation System (OSS) – Evaluation of new observation technology or siting of existing observational systems. This system has been employed to assess the potential of new satellite systems for instrument placement around eastern and western space centers of the U.S. Air Force and spaceborne wind lidar systems for NOAA.

    Satellite Products – Utilization and evaluation of raw radiances and products derived from GOES atmospheric soundings, for the purpose of developing a complete national-scale moisture analysis useful for high-resolution model initialization. The branch also participates in the Joint Center for Satellite Data Assimilation.

    Weather Research and Forecasting (WRF) Model Support – Development of a Standard Initialization procedure for community use in initializing the WRF model with background fields obtained from other models and static data defining the surface properties. High-resolution local applications of WRF are being developed and tested, including evaluation during the International H2O (IHOP-2002) field experiment in the Southern Plains and application for the Coastal Storms Initiative.

    WFO-Advanced Support – Full support of an operational version of LAPS on the WFO-Advanced workstation, including both analysis and prediction. The WFO-Advanced forecaster workstation is used to demonstrate Advanced Weather Interactive Processing System (AWIPS) functions in support of future Weather Forecast Office (WFO) operations.

    Local Model Implementations and Demonstrations – Configuring and installing modeling systems that take advantage of local datasets, advancements in affordable parallel computing, and the results of weather modeling research and developments from FSL and elsewhere. Current and upcoming applications of various models on different computing platforms all take advantage of LAPS initialization. Ensembles of local models will be an increasingly useful approach to numerical weather forecasting problems and applications to a broad spectrum of uses ranging from fire weather prediction to ground transportation needs.

Research efforts in the Meteorological Applications Branch consist of the following:

    GAINS Project – The Global Air-Ocean IN-situ System (GAINS) program is developing a proof of concept for routinely sounding the Earth's atmosphere, ocean, and in situ air chemistry over oceanic areas.

    Diagnostic Turbulence Forecasting – Development, testing, and verification of diagnostic tools using the RUC model for forecasting turbulence in support of the Aviation Weather Research Program.

    Mesoscale Diagnostic Studies – Research performed to increase the understanding of weather systems, improve conceptual and diagnostic models of the atmosphere using data from conventional instruments and new state-of-the-art sensors, and investigate mesoscale dynamical processes. Current studies include potential vorticity streamers, the structure and dynamics of the low-level jet and its role in moisture transport, and the role of gravity waves in turbulence generation and convection initiation.

    Research Quality Datasets – Production of quality-controlled hourly precipitation data, meteorological data from commercial aircraft (ACARS and AMDAR), and North American radiosonde data for access on CD-ROMs and the Web. Assessments of and improvements to the set of hourly precipitation measurements are utilized for verification purposes by the Real-Time Verification System (RTVS).

    Websites for FSL Data – Development of Websites for GAINS, the NOAA Chemical Weather Research and Development program (with information such as the MM5/Chem model domain in Figure 16), national precipitation data, ACARS data, interactive soundings, national mesonetwork data, and FSL publications.


Regional Analysis and Prediction Branch
Stanley G. Benjamin, Chief

Objectives

The primary focus of the Regional Analysis and Prediction (RAP) Branch is research for and development of the Rapid Update Cycle (RUC), which provides high frequency, hourly analyses of conventional and new data sources over the contiguous United States, and short range numerical forecasts in support of aviation and severe storm forecasting and other mesoscale forecast users. The RUC runs operationally at the National Centers for Environmental Prediction (NCEP) at the highest frequency among its suite of operational models. The branch works closely with NCEP in developing, implementing, and testing RUC improvements at FSL, and transferring them to NCEP. A variety of model and assimilation development, verification, and observational data investigation activities are carried out under the RUC focus. Applications of the RUC include contributions to the GEWEX (Global Energy and Water Cycle Experiment) program toward improved climate forecasting (GEWEX Americas Prediction Project, GAPP), forecasting detailed wind fields in collaboration with the National Renewable Energy Laboratory, support for a number of field experiments, and the Short-Range Ensemble Forecast system being developed at NCEP. The RUC has a unique role within the NWS in that it is the only operational system that provides updated national scale numerical analyses and forecasts more often than once every 6 hours. It was developed in response to the needs of the aviation community and other forecast users for high frequency, mesoscale analyses and short range forecasts covering the conterminous United States. It is widely used in NWS Forecast Offices, NWS centers for aviation weather and storm prediction, the FAA, and other facilities. Evaluations of the RUC have clearly demonstrated its advantage in providing high frequency, recently initialized forecasts based on the latest observations. The RUC is a key part of the FAA Aviation Weather Program, since commercial and general aviation are both critically dependent on accurate short range forecasts. The RUC will continue to improve over the next few years, perpetuating the successful collaboration between FSL and NCEP, but a shift in primary focus will be to develop a rapid update component to the WRF model by 2006.

In collaboration with other government agencies (e.g., NCAR, NCEP, NESDIS) and universities (e.g., University of Miami, University of Oklahoma), RAP branch scientists develop improved data assimilation and modeling methods for use in the RUC. Techniques for assimilating new observational datasets are developed toward the goal of the best possible estimate of current atmospheric and surface conditions, as well as the best possible short-range forecast. The branch also interacts with other FSL staff in implementing optimal computing methods with RUC software, making the model as efficient as possible on modern computing platforms.

A second primary focus of the branch is the development, real-time implementation, and evaluation of a fully coupled atmospheric/air chemistry mesoscale model prediction system. An MM5-based, fully coupled system has been run in support of the 2002 NOAA Temperature and Air Quality (TAQ) Pilot Project in New England (and other previous experiments). An increasingly important focus of research involves regional air pollution studies.

Accomplishments

Development and Implementation of the 20-kilometer RUC

NCEP Implementation – Culminating a four-year development and testing activity, a major revision to the RUC system including 20-km horizontal resolution was implemented at NCEP on 17 April 2002. This new version has four key aspects: finer (20-km) horizontal and vertical (50 levels) resolution (requiring about 10 times the computations of the 40-km version for the forecast model), an improved version of the RUC forecast model, assimilation of GOES-based cloud-top pressure to improve the initial RUC cloud and precipitation fields for each forecast, and use of an improved version of the RUC optimal interpolation analysis. Performance of the 20-km RUC has shown significant improvement over the previous 40-km RUC running at NCEP from 1998 – 2002. Verification against rawinsonde observations over a period of almost 4 months in late 2002 showed that the RUC is successful in producing shorter-range forecasts that are more accurate than those of longer durations. This is most true for wind forecasts, as shown in Figure 17, where improved skill is found all the way down to 1-hour forecasts. This same verification showed that RUC short-range forecasts generally improve on persistence forecasts. The RUC is also able to produce short-range forecasts at the surface that are more accurate than longer-range forecasts valid at the same time, and again, improve on persistence forecasts at 1- and 3-hour projections (Figure 18).

Figure 17 - RUC Winds Verification

Figure 17. Verification of RUC wind forecasts against rawinsonde observations over entire RUC domain for 11 September – 31 December 2002. RMS vector difference (m s-1) between observations and forecasts is shown for forecasts of 1-, 3-, 6-, 9-, and 12-hour duration and for the analysis, all valid at rawinsonde observation times (0000 UTC and 1200 UTC).

Figure 18 - RUC Temperature Verification

Figure 18. Verification of RUC 2-meter temperature forecasts against METAR (meteorological aviation report) observations over the full RUC domain. Value is standard deviation of observation-forecast difference in degrees C. Two seasons are shown: 17 April – 27 September 2002 and 1 October – 26 December 2002. Values are shown for RUC forecasts of 1-, 3-, 6-, 9-, and 12-hour duration. Open squares are RMS differences for 1-hour and 3-hour persistence forecasts using RUC analysis for each season.

The following improvements have been made to the RUC20 since its implementation at NCEP.

3D Variational Analysis – A 3D variational (3DVAR) analysis has been developed for the 20-km RUC 1-hour cycle and is now being tested at NCEP for an implementation in 2003. The RUC 3DVAR analysis is configured in a generalized vertical coordinate set, which in this case is the RUC hybrid isentropic-sigma coordinate. The use of this coordinate provides an adaptive analysis space, with sloping of background error covariances in the proximity of baroclinic systems, and a stability-dependence for vertical error covariances. The RUC 3DVAR analysis has been shown to give equal or improved forecast skill to those from the current optimal interpolation analysis for forecast projections from 3 – 12 hours. The RUC 3DVAR analysis also assimilates the following new observational datasets:

  • GPS ground-based precipitable water values (now over 180 in the United States)
  • 915 MHz boundary-layer profilers (about 25 in the RUC domain)
  • RASS temperature low-level virtual temperature profiles from selected 405-MHz and 915 MHz profilers
  • Mesonet surface observations

Assimilation of Radar Reflectivity – An initial technique has been developed for assimilation of radar reflectivity and lightning data into the hydrometeor and water vapor fields in the RUC analysis to improve short-range precipitation and cloud forecasts. This technique can modify both rain and snow mixing ratios (Figure 19), accounting for the observed reflectivity in the column. National 2-km resolution reflectivity mosaic fields and 10-km Radar Coded Message fields are being inserted into the RUC20, since the former provides higher resolution but the latter provides beam blockage information to help differentiate "no echo" from "no coverage." Lightning data are used as an indication of convection. Verification of precipitation forecasts made in a parallel cycle using this technique have shown a significant improvement in skill.

Figure 19 - ARM/CART Site Profiles

Figure 19. Vertical profiles of 20-km RUC rain and snow mixing ratio before
and after assimilation of radar reflectivity for 2200 UTC 11 December 2001
at the ARM/CART site in Lamont, Oklahoma. Also a time series from a
cloud-profiling radar at the same location around the same period shows
the vertical profile of precipitation.

Improved Version of the Grell-Devenyi Convective Parameterization – The RUC20 includes improved convective (subgrid-scale) precipitation from an ensemble closure/feedback convective parameterization by Grell and Devenyi. Additional research is being carried out to optimize the closure weighting and even to develop data assimilation techniques for probabilistic convective forecasts. An example of the difference in convective forecasts from the RUC is shown in Figure 20.

Figure 20 - RUC Forecasts - Grell-Devenyi

Figure 20. 13-hour forecasts of subgrid-scale precipitation from versions of the RUC using 1 ensemble closure and 144 closures in the Grell-Devenyi scheme, valid 0100 UTC 13 June 2002 (during the IHOP field program). Infrared and visible satellite images valid at the same time are also shown.

Support of the Operational RUC at NCEP – FSL monitors performance of the RUC running operationally at NCEP and works with NCEP to make necessary modifications. As part of this work, FSL must maintain expertise on the IBM SP computing system at NCEP and maintain a close, long-term collaboration with many groups in NCEP.

FSL also supports a related major ongoing task, that of running in real time a backup version of the 20-km RUC in a "hardened" computer environment on the FSL Jet supercomputer to assure high-level reliability. During NCEP outages, RUC grids from FSL are substituted through NWS distribution channels to support all real-time RUC users. This task involves both the RAP Branch and FSL's Information Technology Services, along with NCEP and other organizations of the National Weather Service. A backup for the RUC20 was developed and implemented during 2002. Ongoing enhancements continue on the RUC Website, http://ruc.noaa.gov, including products from the test version of the 20-km RUC, and the use of the 20-km RUC grids in the FSL Interactive Sounding program.

Applications of the RUC

Development of Improved Atmospheric/Land-Surface Coupled Model Capability and Production of Integrated Datasets for GEWEX/GCIP/GAPP – FSL continues to participate in the multiyear GEWEX and the GEWEX American Prediction Project (GAPP) by providing data from the RUC/MAPS model/assimilation system to the GCIP (GEWEX Continental-scale International Project) archive of gridded datasets. The goal of GCIP is improved understanding of the continental scale hydrological cycle components, and ultimately, improved climate prediction capability. Ongoing improvements to all aspects of RUC/MAPS, especially to its land-surface component, contribute toward meeting this goal.

The RUC/MAPS system was the first regional model to cycle its multilevel soil moisture and soil temperature fields, and continues to be the only one to cycle snow water equivalent depth and multilevel snow temperature. This cycling of snow cover has proven beneficial in short-range surface forecasts in which there is change of snow cover over a 24-hour period, as shown in Figure 21, with snow melted over Wisconsin. In this case, the RUC was able to produce more accurate surface temperature forecasts than other models due to its cycling of snow variable in its 1-hour cycle. Paradoxically, although the RUC is used primarily as very short-range forecast guidance, the cycling of these surface fields requires considerable robustness from the land-surface model for what is, in effect, a simulation spanning months to years. In turn, the cycling of soil moisture and snow water equivalent in the RUC leads to improved short-range forecasts. The RUC research for the GEWEX/GAPP project is aimed at using cycling of surface variables combined with data assimilation of radar reflectivity and other cloud/precipitation observations to provide improved land-surface fields which can result in improved seasonal and interannual climate forecasts.

Figure 21 - RUC/NESDIS Snow Cover

Figure 21. Observed snow cover from 2200 UTC 7 and 8 January 2002
NESDIS analyses and RUC cycled snow cover valid at 2100 UTC 8 January.

Use of RUC Wind Forecasts for Estimated Wind Power Potential – FSL continues a collaborative wind energy study with the National Renewable Energy Laboratory (NREL, Department of Energy) now using 20-km RUC/MAPS forecasts. Time-lagged ensembles produced from 20-km RUC forecasts out to 48 hours are used to estimate near-surface wind power potential, while variance among forecast ensemble members provides a measure of uncertainty in those forecasts. The high vertical resolution in the RUC near the surface and frequent update cycling makes it well suited to wind energy forecasting.

Special High-Resolution RUC Forecasts for NOAA Experiments (PACJET, IHOP, and TAQ) – FSL ran a special high-resolution version of the RUC model for three different special experiments over the last year (Figure 22). First, FSL distributed forecast fields to t he NWS Western Region Headquarters for real-time AWIPS display at local offices in support of the PACJET 2002 (Pacific Landfalling Jets) experiment. The special PACRUC configuration consisted of a 10-km grid covering all of the NWS Western Region, nested within the CONUS 20-km RUC domain. The 20-km RUC utilized a 1-hour assimilation cycle to ingest all conventional observations. PACRUC 24-hour, 10-km forecasts were produced every 6 hours, and AWIPS files containing selected surface fields were transferred to NWS via automated LDM scripts. Additional RUC fields were provided to the forecasters through a Webpage, and a Web-based forecast evaluation form was used to obtain forecaster feedback. Special 10-km RUC forecasts were also produced for the May – June 2002 Central Plains International H2O Project (IHOP-2002) to the NWS Storm Prediction Center in Norman, Oklahoma. Finally, the 10-km RUC was moved to a domain covering the northeastern United States in support of the Temperature and Air Quality (TAQ) experiment in summer 2002. Again, AWIPS-compatible NetCDF files were provided to the NWS, this time through the Eastern and Central Regions. The 10-km RUC TAQ runs were continued through the fall and into winter 2002 – 2003. An example of a lake effect snow band forecast from the 10-km TAQ RUC is shown in Figure 23.

Figure 22 - RUC Runs for Experiments

Figure 22. Special 10-km RUC domains run in support of NOAA
experiments for PACJET, IHOP, and TAQ programs during 2002.

Figure 23 - RUC Lake Effect Snow

Figure 23. 10-km RUC 12-hour forecast of lake-effect snow band from Lake
Huron across Ontario and Lake Ontario into New York. Also shown is
observed radar reflectivity at the valid time of 1030 UTC 11 January 2003.

Profiler Impact Experiments with RUC – An assessment of the value of data from the NOAA Profiler Network (NPN) on weather forecasting has been completed. A series of experiments were conducted using the RUC20 model in which various data sources were denied to assess the relative importance of the profiler data for short-range wind forecasts. Average verification statistics from a 13-day test period indicate that the profiler data have a positive impact on short-range (3 – 6 hour) forecasts over a central United States subdomain that includes most of the profiler sites as well as immediately downwind of the profiler observations (Figure 24). Averaged over time of day, the profiler data most strongly reduce the overall vector error in the troposphere below 300 hPa where there are relatively few automated aircraft observations. At night when fewer commercial aircraft are flying, profiler data also contribute strongly to more accurate 3-hour forecasts at jet levels. For the test period, the profiler data contributed 20–30% (at 70 hPa) of the overall reduction of 3-hour wind forecast error by all data sources combined.

Figure 24 - RUC Wind Forecasts with/without Profiler Data

Figure 24. Effects of profiler data denial (no profiler – control with profiler) on RUC wind
forecasts. Average RMS vector errors against rawinsonde data for 4 – 16 February 2001
over an area in the central United States with 22 rawinsonde sites. Positive difference
indicates that the control (cntl) experiment with profiler data had lower rms vector
error than the no-profiler experiment.

Several case studies were examined in detail to illustrate the value of the profiler observations for improving weather forecasts. One of the case studies indicated that inclusion of profiler data in the RUC model runs for the 3 May 1999 Oklahoma tornado outbreak improved model guidance of convective available potential energy (CAPE), 850–300 hPa wind shear 0–3 km helicity, and precipitation in southwestern Oklahoma prior to the outbreak of the severe weather. In another case study, inclusion of profiler data improved RUC precipitation forecasts associated with a severe snow and ice storm that occurred over Kansas. Summaries of NWS forecaster use of profiler data in daily operations support the results from these case studies and the statistical forecast model impact study that profiler data contribute significantly to improved forecasts over the central United States, where these observations currently exist. The results of this profiler impact study have been submitted for publication.

Observation Sensitivity Experiments Using RUC to Examine the Impact of GPS Precipitable Water Observations – In collaboration with the Demonstration Division, the RAP Branch continued 60-km RUC parallel cycle experiments with and without assimilation of GPS precipitable water observations. Positive impact (leading to more accurate forecasts) of GPS precipitable water observations on short-range relative humidity forecasts seen in earlier sensitivity experiments has continued to increase as more stations have been added to the network. Results from a new set of 2-week retrospective experiments for both cold and warm season periods with the 20-km version of the RUC show still greater impact from the addition of GPS precipitable water observations than with the 60-km RUC model.

Collaborative Modeling Projects

Regional Lidar OSSE Experiments with RUC – FSL has completed a series of regional observing system simulation experiments (OSSEs) designed to test the potential impact of a space-based Doppler lidar wind profiling system on regional-scale numerical weather predictions. OSSEs utilize a numerical prediction model to mimic a typical atmospheric evolution, and provide a cost-effective method for evaluating the forecast improvement from potential new observing systems. As shown by Figure 25, the regional OSSE experiments were run in conjunction with a series of global OSSE experiments conducted by NCEP. Lateral boundary conditions needed for the regional OSSE experiments run with the RUC were obtained from matched global lidar OSSE experiments, while simulated observations, assimilated into the RUC, were obtained from the MM5 regional nature run completed by the Local Analysis and Prediction Branch. Conventional observations (rawinsonde, profiler, VAD, ACARS, METAR, buoy) and simulated lidar observations were computed directly from the regional nature run. The assumed characteristics of the lidar observations were produced by the NOAA Environmental Technology Laboratory. Calibration of the MM5 regional nature run was performed using the European Centre for Medium-Range Weather Forecasts global nature run, and coding of the regional verification software was completed by NCAR — thus a truly collaborative, multiyear effort.

Figure 25 - Flow-Chart - OSSE

Figure 25. Flow-chart depicting the relationship between the regional and global lidar OSSE experiments. The global nature run (ECMWF model) supplies lateral boundary conditions to the regional nature run (MM5 model) and simulated observations to the global assimilation runs (MRF model). The regional assimilation runs (RUC model) receive boundary conditions from the global assimilation runs and simulated observations from the regional nature run.

Regional forecast improvements due to the lidar observations can come from three sources: 1) direct assimilation of the lidar observations on the regional domain 2) improved lateral boundary conditions due to the assimilation of lidar observations on the regional domain and 3) improved lateral boundary conditions due to the assimilation of lidar observations from the global model. As expected, results from this study indicate forecast improvement from all sources. Improvement from the direct assimilation of lidar observations is greatest at the analysis time, then slowly diminishes with forecast length, while improvements from the lateral boundary conditions increase with forecast length. Initial OSSE experiments focused on a best-case scenario, in which no lidar observations were lost due to cloud attenuation and no errors were added to the lidar observations. In these experiments, lidar wind observations produce modest short-range (0 – 12-hour) forecast improvements over the data-rich RUC domain. Midlevel wind forecasts benefit the most, with 6-hour forecast error reductions of up to 10% (Figure 26) from the assimilation of lidar observations. Other experiments which accounted for the loss of lidar observations due to clouds and the existence of random errors in the lidar observations, have shown only a slight reduction in the forecast improvement compared to the best-case experiments. As part of this project, the formulation of the RUC 3DVAR was modified to facilitate the direct assimilation of lidar line-of-site wind observations. This modification also allows for the future direct assimilation of Doppler radar radial velocity observations, in accordance with planned RUC analysis enhancements.

Figure 26 - RUC Errors

Figure 26. Vertical profile of the percent improvement (reduction in error) in vector wind root mean square error for 6-hour RUC forecasts due to the assimilation of idealized simulated lidar observations. The impact for forecasts initialized at the rawinsonde observation times (0000, 1200 UTC) is less than that for forecasts initialized at nonrawinsonde observation times (0600, 1800 UTC).

Air Quality Forecasts from a Coupled Weather/Air Chemistry Prediction Model – FSL is developing and applying a next-generation coupled weather/air quality numerical prediction system. This system is capable of forecasting ambient ozone concentrations over regional to urban scales and includes the MM5 meteorological model with "online" chemical capability. In this system the chemical kinetic mechansm is embedded within the meteorological model structure, and thus the integration of the chemistry is performed as part of MM5 (MM5/Chem). Biogenic emissions are also integrated online since they are strongly modulated by meteorology. A second coupled modeling system, led by FSL, is based on the Weather Research and Forecasting (WRF) numerical model and uses the same chemical modules as MM5/Chem.

During the summer of 2002, MM5/chem was run in real time at FSL in support of the New England Temperature and Air Quality (TAQ) pilot experiment. The domains for which forecasts were produced were shown in Figure 16, and Table 2 summarizes each of the runs. In addition, during 5 July – 30 August 2002, data from the model forecasts were provided in real time to several OAR laboratories via the Web. NOAA/ETL received data from the numerical forecasts for verification with meteorological observations at profiler locations, and with surface observations at special high energy usage sites. (Figure 27 shows an example of a meteorological comparison that was displayed in real time.) Scientists at the National Severe Storms Laboratory (NSSL) received meteorological data on a common three-dimensional grid for ensemble predictions. Special three-dimensional chemical and meteorological datasets were also provided to the NOAA Aeronomy Laboratory (AL) for verification as well as for real-time forecasting aboard the Ron Brown. An example of a comparison of ozone forecasts with measurements from the Ron Brown as seen in real time on 24 July is shown in Figure 28. Note that for this particular case the model did exceptionally well in predicting the ozone concentrations, especially for the highest resolution forecasts. Finally, the Air Resources Laboratory (ARL) received surface chemistry and meteorology datasets for verification. The completion rate of the model forecast run on the Jet supercomputer at FSL was greater than 95%.

Table 2.
Real-time Model Runs at NOAA/FSL



Domain/
Horizontal
Resolution
Meteorological
Input
Boundary
Conditions


Simulation
Length


How
Often

Initial
Chemistry
Fields

Chemistry
Boundary
Conditions

Anthropogenic
Emissions
Input
DO1/
21 km
RUC20/Eta 60 Hours
(12 Hours
FDDA +
48-Hour
Forecasts)
Twice
Daily
FDDA Background
Soundings
EPA NET95
DO2
9 km
MM5/Chem -
DO1
24 Hours Twice
Daily
12-Hour
Forecasts
M5/Chem -
DO1
EPA NET95
DO3
3 km
MM5/Chem -
DO2
24 Hours Twice
Daily
12-Hour
Forecasts
MM5/Chem -
DO2
EPA NET95

Figure 27 - Time Series - Schenactady

Figure 27. Time series of predicted (symbols) versus observed (dots) wind speed (a, blue) and wind direction (a, green), 2-m temperature (b, red), and relative humidity (b, blue) for the Schenectady profiler site as seen at 1200 UTC 10 August. Time starts on the right side of the graph 1200 UTC 8 August.

Figure 28 - Ron Brown Measurements

Figure 28. Observed (thick black line) and predicted (color lines) ozone concentrations as measured on the Ron Brown for predictions using MM5 9-km horizontal resolution (middle panel) and 3-km horizontal resolution (bottom panel). Displayed are results from model runs starting at 1200 UTC 22 July (red lines), 0000 UTC 23 July (purple lines), and 1200 UTC 23 July (blue lines).

In addition, data from July and August 2002 have since been rerun to create a complete testbed dataset. A statistical comparison with observations over this time period was performed by AL and is now available as a baseline dataset to compare against. (See Figure 29 for an example of a comparison of ozone forecasts and observations at one particular station.) Development of this type of testbed dataset is a powerful tool in model development to aid the assesment and understanding of currently available atmospheric numerical modeling systems, and point to areas where further development is needed as we work toward production of reliable air quality forecasts.

Figure 29 - Harvard Forest Ozone Concentrations

Figure 29. Correlation coefficients of observed versus predicted ozone
concentrations at Harvard Forest, averaged over 120 runs (July and
August 2002). Displayed are the r2 for different model resolutions
and different forecast times for the day times.

In addition, FSL is taking the lead in developing the next-generation air quality forecast model, WRF/chem. The first version of this model already exists and includes all chemical modules that are a part of MM5/Chem (grid-scale and subgrid-scale transport, biogenic emissions, deposition, photolysis, and the RADM2 chemical mechanism). Evaluation of this model is currently in progress, and it will probably be run in real time during the summer of 2003.

Participation in Development of the Weather Research and Forecast (WRF) Model System – The overall goal of the WRF model project is to develop a next-generation mesoscale forecast model and assimilation system that will advance both the understanding and prediction of important mesoscale weather, and promote closer ties between the research and operational forecasting communities. The model and associated system are being developed as a collaborative effort among NCAR, NCEP, FSL, the Center for the Analysis and Prediction of Storms (CAPS), and other research institutions together with the participation of a number of university scientists.

In collaboration with NCAR, FSL has worked on the development of physics packages and a three-dimensional (3DVAR) analysis system. FSL has contributed two physics components to the WRF forecast model — an alternative land-surface model based on the RUC land-surface model and the Grell-Devenyi ensemble convective parameterization. Both of these schemes have been fully implemented and tested in the WRF model. FSL has also developed the standard initialization package for the WRF model, and has worked with the University of Miami on development of a quasi-isentropic variant of the WRF nonhydrostatic model.

The WRF model is being tested with RUC initial conditions for two different domains, the 20-km CONUS RUC domain; and the 10-km TAQ New England domain. The WRF standard initialization (SI) procedure was modified to fully use RUC native-coordinate initial conditions, including hydrometeor and land-surface fields. In addition, a post-processor was developed from the WRF model to produce RUC-like GRIB output files, facilitating comparisons with RUC model forecasts. FSL will adapt WRF assimilation and model systems over the next several years to include an advanced rapid update capability for operational implementation at NCEP. It is planned that the WRF model will supplant the current RUC forecast model in the Rapid Update Cycle by 2006.

Projections

The Regional Analysis and Prediction Branch will continue to work with scientists at NCEP, NCAR, and other organizations to improve the RUC and WRF models over the next few years. An overview of the primary near-term tasks follows.

Implementation of Three-Dimensional Variational (3DVAR) Analysis in the 20-kilometer RUC – With tuning to ensure sufficient accuracy for short-range wind forecasts, the RUC 3DVAR analysis will be added to the 20-km RUC running at NCEP. The 3DVAR implementation will provide smoother analyses, more accurate forecasts, and a framework for assimilation of radial wind observations from radar in the future. Development and real-time testing will continue on the 3DVAR analysis, both for incorporation into the RUC and toward the development of the 3DVAR analysis for the WRF model.

Continued Development of a National-Scale Cloud/Hydrometeor Analysis – Development and real-time testing will continue for further improvements to the RUC national-scale cloud analysis, with the addition of radar, lightning, and surface observations to satellite cloud-top data. Experiments will be carried out testing assimilation of a GOES imager-based multilevel cloud product, as described below under the JCSDA plans.

Refinement and Testing of Improved Physical Parameterizations for Soil/Vegetation Processes, Turbulence, Convective Clouds, and Cloud Microphysics – Some of this work will be done in collaboration with NCAR, since the RUC model uses some of the MM5 parameterizations, which will be options for the WRF model.

National Observing System – FSL will continue its efforts with a team working toward an initiative to develop a national mesoscale observing system consisting of tropospheric and boundary layer profilers, ground GPS receivers, and radiosondes with ground tracking systems. This is an initiative with great potential impact for mesoscale forecasting. Also under development is an observation system simulation experiment (OSSE) with a practical observation network design and numerical model to verify the budgets and applicability.

Data Assimilation – Work will commence to test the WRF 3DVAR system within the RUC assimilation cycle.

High-Resolution Experiments Using RUC for the New England Temperature Air Quality Experiments – RUC forecasts will continue to be made at 10-km resolution in support of this experiment. In addition, the WRF model will be run over the same domain, also at 10-km resolution, initialized from the RUC. This will allow initial intercomparisons between the current RUC hydrostatic model and the WRF nonhydrostatic model including RUC physical parameterizations, the RUC land-surface model, and the Grell/Devenyi ensemble-closure cumulus parameterization. Objective verification of the model forecasts will be performed as part of these studies.

Participation in GEWEX – Collaboration will continue on the GEWEX/GAPP program, with the focus on development of a coupled atmospheric/land-surface assimilation system that uses an optimal combination of radar and satellite observations to modify clouds and precipitation along with model forecasts in regions where observations are unavailable.

Contribution of RUC Forecasts to the NCEP Short-Range Ensemble Forecast System – As part of an expansion to NCEP's Short-Range Ensemble Forecast (SREF) project, FSL will complete its effort begun this last year to set up an ensemble version of the RUC model running out to 63 hours on a 48-km grid over the Eta domain. The RUC SREF is spawned from a set of five members bred from the NCEP Eta model, and is a candidate for inclusion in the NCEP SREF set currently composed only of Eta and Regional Spectral Model bred members. Tentative results from the RUC SREF show substantial spread in the ensemble, but it needs to be determined whether the forecast skill for the ensemble mean exceeds that of the operational RUC20 model, and statistical techniques must be developed to assess the results.

Joint Center for Satellite Data Assimilation Activities – Future work will first involve running and testing the Optical Test Transmittance (OPTRAN) radiative transfer model to replace the European Centre for Medium-Range Weather Forecasts' RTTOV code that has been used in all RUC forward model calculations thus far. OPTRAN has been chosen as the community radiative transfer model by the Joint Center for Satellite Data Assimilation. Outgoing radiances from the RUC will then be subjected to OPTRAN forward model calculations to compare with the GOES radiances. The imager data will be used to determine clear-air radiances with greater resolution than using the sounder estimates. Eventually, the goal is to incorporate the adjoint of the forward calculations into the RUC three-dimensional variational (3DVAR) analysis and to begin using this to rapidly update the radiance data in the RUC and, later, the WRF models.

Return to Top of Forecast Research Division Section


Local Analysis and Prediction Branch
John A. McGinley, Chief

Objectives

The Local Analysis and Prediction (LAP) Branch responds to the needs of many government agencies and the private sector in the areas of local and mesoscale data analysis, data fusion, data assimilation, quality control, three-dimensional display and visualization, and numerical modeling. The branch carries out the research and development of the Local Analysis and Prediction System (LAPS) and the implementation of mesoscale forecast models. The primary objective is to provide real-time, three-dimensional, local-scale analyses and short-range forecasts (0 – 24 hours) for operational weather offices, facilities, or field operations. Activities cover four broad areas:
    Data Acquisition – Includes identifying, collecting, and quality-controlling any kind of atmospheric or earth surface measurement, such as those provided by satellites, radars, mesonets, aircraft, GPS, balloons, and profilers. This activity also includes developing interfaces to “national” datasets, such as the gridded data services provided via the Satellite Broadcast Network (SBN) data feed and similar military systems. LAPS is coupled with the Local Data Acquisition and Dissemination (LDAD) system, which stores portable applications that retrieve and render AWIPS weather data into images and graphical displays for dissemination.

    Data Analysis – Accomplished using an integrated software package containing well-documented objective analysis schemes that apply quality control criteria to the data, spatially represent atmospheric conditions, perform spectral filtering, and ensure vertical consistency. The data analysis system is running within AWIPS in National Weather Service (NWS) forecast offices, at the eastern and western space ranges at Cape Canaveral, Florida, and Vandenberg Air Force Base (AFB), California, for the National Ocean Service for Chesapeake and Naragansett Bays, for the U.S. Forest Service (USFS) in support of fire mitigation and firefighting, and for the U.S. Army in support of precision parachute airdrop activities.

    Mesoscale Model Implementation – Accomplished using an expanding variety of mature nonhydrostatic modeling systems, such as the Regional Atmospheric Modeling System (RAMS) developed at Colorado State University, MM5 developed jointly by NCAR and Pennsylvania State University, the hydrostatic version of Eta developed at NCEP, and the Weather Research and Forecast (WRF) model under joint development by FSL, NCAR, and NCEP. These models have been configured to be initialized by LAPS analyses and with time-dependent boundary conditions furnished by all operationally available gridded datasets (RUC, Eta, Aviation, and the U.S. Navy Operational Global Atmospheric Prediction System). Implementation of the LAPS system at some NWS forecast offices has demonstrated the portability and effectiveness of running models locally. One such demonstration, sponsored by NWS, tests the feasibility of local modeling in NWS WFOs. The collocation of FSL with the Denver-Boulder NWS Forecast Office has demonstrated the effectiveness of locally run models during the past few years, as LAPS-initialized mesoscale models have been run on their local AWIPS hardware and on FSL's High-Performance Computing System for operational evaluation. Models have the option of being initialized using the LAPS diabatic analysis that allows a full representation of clouds and vertical motion in the initial state. A unique ensemble of mesoscale models (RAMS, MM5, and WRF) is currently supporting the weather forecast input to a road maintenance decision support system demonstration for the Federal Highway Administration.

    Dissemination – Includes delivery of weather products and basic fields developed from LAPS to users in operational forecast offices and state and local government agencies, including emergency managers and other users specializing in fields such as winter highways operations, fire weather, aviation and space operations, and military operations such as those mentioned later. LAPS fields are compatible with AWIPS file formats and appear in a number of dedicated Webpages for specified customers. For fire weather support, LAPS analysis and model fields can be dynamically located to specific fire locations. This text format for 24-hour point forecasts proved to be popular with USFS personnel.

LAPS can be displayed in three dimensions using the experimental D3D (Display Three-Dimensional) add-on to AWIPS. Figure 30 illustrates an end product of the LAPS effort, namely to completely define the local meteorological environment using this D3D display (in the form of isosurfaces). Such three-dimensional displays can help forecasters achieve a better conceptual view of complex meteorological processes. The LAP Branch, along with some NWS Forecast Offices, continues to explore the potential of three-dimensional displays for operational use, perhaps eventually as a part of AWIPS within the NWS as well as within other operational environments.

Figure 30 - Vis 5-D LAPS

Figure 30. Three-dimensional Vis 5-D image of forecast LAPS fields including clouds (white/grey material surfaces), horizontal reflectivity at 675 meters (blue lines), vertical cross section of reflectivity (yellow lines), pressure (millibars, black lines in diagonal cross-section plane). Back graphic plane shows vertical motion (blue upward; red downward).

Accomplishments

Basic Analysis System Development

Three-Dimensional Variational Methods – LAPS applies variational methods at various stages in its analysis. The variational approach to the LAPS moisture analysis remains the method of choice to integrate GOES sounder radiances, GOES-derived products, GPS, boundary layer moisture, cloud information, radiosonde, and profiler data. In LAPS the variational step was previously used only with GOES sounder radiances. The variational adjustment using GOES radiances includes GOES three-layer precipitable water vapor, GPS total column water vapor, and cloud information from the LAPS cloud analysis in one variational formulation.

An ongoing data denial experiment provides insight into the impacts of the various data sources on the analysis. In addition, this assessment tool can be used to gauge the strength and weakness of the different data sources, in order to optimize their respective weights in the variational equation. The statistics used in this study are a comparison of analysis output to radiosonde data (taken as referenced truth). This is possible since radiosonde data are not typically used in the operational LAPS system due to their latency (poor timeliness). The goal of the moisture variational application is to provide a complete product that describes the atmospheric water distribution from vapor to cloud droplets to precipitation, both liquid and frozen. This analysis has been used to improve model initialization. This analysis utilizes all conventional data, along with satellite, radar, and GPS data. The routine is based on the LAPS cloud analysis, but then seeks to quantify all water substance. Variational methods are used to impose dynamic balance and continuity on the first-stage analyzed fields to accommodate the "Hot Start" analysis described below.

LAPS Advanced Quality Control – Quality control of observations is a continuing focus of LAPS analysis development. A Kalman filtering scheme is used to improve the quality and timeliness of surface observations. The method allows users to optimally exploit local model output and past station trends and buddy trends to produce check values for surface stations. In conjunction with LAPS support of a three-dimensional 30-minute analysis cycle, the Kalman scheme allows the merging of mesonetworks with varying cycle times. Working exclusively in data space, the Kalman filter scheme is economical for use in the local computing environment and provides a continuously updated and accurate set of observations where all stations appear at each cycle. This is an appropriate approach for instances when a user requires good product time continuity, but has high variability in observation count from cycle to cycle. Since the Kalman scheme still requires more computer storage than is currently available in the local weather office, it has not been widely used.

LAPS "Hot Start" Procedure – The LAP Branch continues to improve the Hot Start procedure for diabatic initialization of mesoscale models. The Hot Start initialization scheme is designed to develop initial conditions for mesoscale models such as the MM5, RAMS, and the mass-coordinate version of the (WRF) model. This scheme is unique in that it runs on small PC clusters with Linux operating systems and is ideal for applications in local weather offices where accurate short-term cloud and precipitation forecasts are needed. This system depends greatly on the accuracy of the background modeling system, currently the NCEP versions of the RUC and Eta models. The Hot Start scheme uses estimates of vertical motion and cloud water and ice mixing ratios from the LAPS cloud analysis. A variational analysis that applies both mass continuity and mass-momentum balance makes small adjustments to the wind and temperature field to accommodate and sustain the clouds in the first few time steps of the model integration. The cloud retrieval algorithm includes a broad range of microphysical species, cloud-type dependent estimates of cloud vertical motion, and saturation of the cloud environment.

Verification with MM5 during the 6-week International H2O Project showed that the Hot Start outperforms other initialization techniques in the 0 – 6-hour time frame in forecasts of precipitation, most state variables, and 3-D cloud and radar fields. Figure 31 shows equitable threat scores for precipitation for the entire experiment. Note that the bias for the LAPS Hot Start 3-hour forecasts is nearly 1.0 across all precipitation categories (i.e. it is nearly unbiased), whereas the other models characteristically overforecast very light precipitation amounts and display a large dry bias for precipitation amounts >0.25 inch. The Hot Start method is used to initialize MM5 over a variety of domains including the local Denver forecast area, where forecasters use it as an operational tool; the U.S. Air Force Western Range at Vandenberg Air Force Base as part of the Range Standardization and Automation (RSA) implementation discussed below, and IHOP field operational areas at 12- and 4-km grid resolution. The Hot Start system has been coupled to the WRF-mass coordinate model for testing in a local weather service office in conjunction with the Coastal Storms Initiative carried out with the National Weather Service and National Ocean Service. It is also under evaluation as part of the MM5 modeling system at the Central Weather Bureau of Taiwan.

Figure 31a - ETSs for 3 Hour Precip

Figure 31b - ETSs for 3 Hour Precip
Figure 31. (a, top) Equitable threat score (ETS) and frequency bias for various
precipitation categories (x-axis) for 3-hour precipitation forecasts from the
12-km LAPS Hot Start MM5 (pink), the 10-km WRF (green), the 12-km Eta
(orange), and the 10-km RUC (blue) models; (b, bottom) Same results for the
6-hour forecast period.

GOES Improved Measurements and Product Assurance Plan – The GOES Improved Measurements and Product Assurance Plan (GIMPAP) project has been a key part of the LAPS moisture algorithm development for integrating the high spatial structure of GOES imagery and sounder data into the LAPS system. GIMPAP includes NESDIS cloud-top pressure and layer-precipitable water products.

The total precipitable water analysis over the IHOP domain as generated by the LAPS analysis system incorporated real-time NESDIS product data with greatly reduced latency (a 30-minute cycle instead of the customary 60-minute cycle) and experimental GOES-11 single field-of-view (unsmoothed) radiance data. It also used indirect NESDIS cloud-top product data via the LAPS cloud analysis. The IHOP product stream was accurate and timely throughout the 6-week field project.

Joint Center for Satellite Data Assimilation (JCSDA) – The latest OPTRAN code was obtained from NCEP, compiled and tested, and made to run under IBM AIX, Linux Dec Alpha and Linux PC, and Sun OS. Current work involves writing the interface between OPTRAN and LAPS, and exploring the mesoscale nature of the background and observed error covariances for moisture analyses.

Applications of LAPS

LAPS in AWIPS – The LAPS package has long been an integral element of the WFO-Advanced workstation, running as an application within AWIPS to produce a variety of gridded fields that may be combined with satellite imagery and radar on state- and local-scale displays. The LAPS in AWIPS serves the LDAD system operating outside the AWIPS network. The independent LAPS quality control system will supplement the LDAD quality control system to ensure that local data are monitored and properly employed. The LAPS group continues to support new AWIPS builds and updates the software as needed.

The WFO-Advanced workstation in Boulder receives 10-km resolution MM5 model output from twice daily model runs on exactly the same grid and projection as the LAPS analysis. This permits the display of mesoscale model output in a fully integrated fashion, along with radar, satellite, and surface data. Forecasters can check the quality of a model run by directly comparing model output with observations. The model is running experimentally in the Denver-Boulder NWS Forecast Office on a system within the AWIPS application hardware suite. The model runs in automated mode with little intervention required, and is diabatically initialized using the Hot Start procedure discussed above. Another onsite model implementation is now in progress for the Jacksonville, Florida, WFO under the Coastal Storms Initiative. This model is being established to test short-term forecast capabililty and application of high-resolution wind forecasts to improve estuarine water flow for harbor operations.

U.S. Army Precision Air Drop Project – In 2002, the LAP Branch became involved with a U.S. Army-sponsored development to improve the accuracy of middle-level and high-level parachute delivery of logistical material to military units (Precision Air Drop Systems, PADS). Because of the complexity of wind profiles and air channeling terrain, computed air drop release points (CARP) were often inaccurate, resulting in cargo being substantially off target. In regions of Bosnia, for example, the errors were often whole valleys off target, resulting in long excursions to recover the needed material. In conjunction with Planning Systems Inc., of Reston, Virginia, the LAPS group was asked to port the LAPS analysis onto a laptop that would be taken on drop missions. The concept of operations is for the aircraft to make a close proximity pass over the drop zone, release a dropsonde, process and assimilate the dropsonde with model background fields, and create a high-resolution profile that accommodates time and space displacements from the dropsonde to cargo release time, while accounting for flow channeling over rugged terrain. The laptop computes an updated CARP, within minutes, reducing the threat period for the aircraft. LAPS was ported into the PADS and is now undergoing testing at an Arizona drop range. LAPS is able to ingest the data quickly and provide the wind data to recompute the CARP in less than 3 minutes. Tests so far have been good for mid-level drops, but less so for high-level drops.

Participation in IHOP – FSL participated in the International H2O project (IHOP) in May and June 2002. Different versions of mesoscale models — run in real time — were used to aid in the nowcasting and forecasting effort to support IHOP operations. Formal real-time evaluation and documentation of the model forecasts were part of the IHOP effort, using online forms to record forecaster assessment of the quality and usefulness of the models. A more formal evaluation is taking place after the end of the IHOP field phase, in coordination with researchers at NCAR and at the Storm Prediction Center (SPC). Figure 32 shows example forecasts from three of the models for a rather subtle dryline situation during a very dynamic convective event and a comparison of the composite radar imagery over the IHOP region to a forecast from the 4-km MM5 model showing a pronounced bow echo forming along a developing squall line.

Figure 32a - IHOP Model Runs

Figure 32b - IHOP Radar and MM5 Model Run

Figure 32. (a, top) 6-hour surface temperature and wind forecasts valid at
2100 UTC 15 June 2002 from three experimental mesoscale models run by
FSL during IHOP for a rather subtle dryline situation during a very dynamic
convective event and (b, bottom) composite radar imagery over the IHOP
region at 0000 UTC 16 June and a 6-hour forecast from the 4-km MM5 model.

The Range Standardization and Automation (RSA) Project – Several years ago, the Air Force initiated the Range Standardization and Automation (RSA) program to modernize and standardize the command and control infrastructure of the two U.S. Space Launch facilities (ranges), located at Vandenberg Air Force Base, California, and Cape Canaveral Air Station, Florida. During this past year in cooperation with Lockheed Martin Mission Systems, an integrated local data assimilation and forecasting system was installed at both ranges. The RSA system runs on Linux "Beowulf" clusters from IBM at each range and a test cluster at FSL for use in system development. The clusters consist of 8 dual-processor Pentium III nodes and 1 dual-processor front-end node, totaling 18 processors. A Myrinet interconnect is used for high-speed message passing between nodes.

The first version of the RSA Data Assimilation and Forecast System, based on LAPS coupled with the NCAR fifth-generation Mesoscale Model (MM5), is in testing mode. The system produces hourly LAPS analyses and a new MM5 forecast run every 6 hours on a triple-nested domain with 10-km, 3.3-km, and 1.1 km grid spacing, respectively. These analyses make use of the AWIPS Local Data Acquisition and Dissemination (LDAD) interface to incorporate data sources unique to the launch facilities in addition to the radar, satellite, and other datasets available via the AWIPS data feed. Every 6 hours, these analyses are used to perform a diabatic initialization of an MM5 forecast run. The forecast model outputs hourly forecast fields out to 14, 12, and 9 hours for the 10-km, 3.3-km, and 1.1-km grids, respectively, using 2-way nested feedback. The entire system is integrated with the Linux version of AWIPS installed at the Air Force ranges. Figure 33 shows an example of a product on the interior (1-km mesh) of forecast surface wind and temperature, verifying surface plots, and comparative wind forecasts from the MesoEta model over the local area surrounding Vandenberg AFB.

Figure 33 - LAPS/MM5 Surface Forecast

Figure 33. 5-hour surface forecast for 1700 UTC 11 January 2002
from LAPS/MM5 of isotherms (red contours), wind barbs (tan), and
6-hour MesoEta wind forecasts (green), all valid at 1800 UTC, and
verifying surface observations (cyan).

The RSA and projects spurred numerous improvements to the LAPS/MM5 prediction system. First, the cloud analysis was adapted to ingest and use narrowband radar reflectivity from multiple WSR-88D sites, available via the Satellite Broadcast Network (SBN) feed into AWIPS. This provides better coverage over the entire domain of the grid used for the RSA, which is spatially larger than a typical NWS Forecast Office domain. Second, the cloud analysis was modified to use a climatological albedo field to increase the utility of the visible satellite imagery. This, combined with the recent integration of the GOES 3.9 micron channel, has greatly improved the system's ability to detect low stratus clouds over the ocean surrounding the Western Range. Third, for the purposes of initializing a numerical weather prediction model, the final three-dimensional concentrations of the hydrometeor species are scaled as a function of horizontal grid spacing. Finally, to ensure compatibility with current numerical weather prediction model microphysics schemes, any grid box volume containing cloud liquid or ice is raised to its saturation level with respect to the phase of the cloud species. This prevents rapid evaporation of the cloud and the concomitant spurious generation of cool downdrafts within the first few time steps of model integration.

These RSA capabilities together represent the first operational installation of a local modeling system completely integrated with AWIPS in a WFO-like environment, the first operational installation of the LAPS diabatic initialization-Hot Start method, and the first operational use of a Linux-based AWIPS system. Ongoing FSL work includes ingesting and optimizing the use of all local meteorological datasets, incorporating new capabilities such as online verification of the forecast grids, enhancing utilization of the satellite data to improve cloud analyses, and improving the LAPS diababic initialization method.

High Performance Computing – The FSL High-Performance Computing System (HPCS) has been a critical resource for all of the numerical modeling activity in the branch, including the unique mesoscale model ensemble used for the Federal Highways Project described below. This experience continues to provide important feedback to the system developers and computer specialists regarding configuration issues and future upgrade plans.

Collaborative Modeling Projects

International Collaborations – Scientists continue an active collaboration with the Central Weather Bureau (CWB) of Taiwan. The branch hosts long-term visitors from Taiwan, forming working relationships that are very beneficial in improving the real-time data preprocessing for LAPS, the analyses, and the modeling components. Software has been enhanced for ingest of a large variety of surface and upper-air data, including rawinsonde, mesonet, cloud drift wind, METAR, ACARS, synoptic observations, and necessary adaptations to changing satellite data. LAPS now runs with data ingest from a CWB model background, hundreds of mesonet surface stations, and four radars covering each of the four U.S. Coasts.

The CWB-LAPS products feed into CWB's Weather Information and Nowcasting System workstation. The onsite and "shadow systems" (running at FSL) were improved to completely mimic the CWB system. The surface analyses were upgraded to handle analysis of variables in the coastal zones by increasing correlation over similar earth surface characteristics. Use of model backgrounds into LAPS was improved and coupled to bogussing techniques for tropical cyclone positioning. Satellite imagery for infrared and visible bands are ingested in the cloud analysis scheme.

The CWB MM5 modeling effort was the focus of a visiting scientist at FSL who worked with the group to configure a multinested modeling domain, a LAPS Hot Start initialization capabililty, inclusion of bogussing, and a precipitation verification system. Results indicated that the Hot Start scheme helped to better define tropical rainbands leading to improved 0 – 9 hour forecasts. As an example, Figure 34 shows forecasts of Typhoon Rammasun, which skirted the islands to the northeast of Taiwan. Experiments were run with cold start, hot start only, and hot start with bogussing. Three 6-hour forecasts are shown along with comparative track forecasts out to 24 hours for each realization. The Taiwan MM5 system is being implemented at the CWB.

Figure 34a - Three LAPS Model Runs

Figure 34b - Forecast Tracks

Figure 34. MM5 simulated radar 6-hour forecasts for three scenarios:
(a, top panels, left) cold start (model initialized with background only),
(center) LAPS Hot Start with data and background, and (right) LAPS
Hot Start using a background bogussed position of storm in the back-
ground fields. The latter method produces the best analysis, although
rainbands are more mature in the hot start versus the cold start.
(b, bottom) shows the comparative track forecasts: red is actual track
with southern dots showing initial positions and northern dots showing
forecast position at 24 hours; blue is cold start forecast; brown is hot
start; yellow is hot start with bogussed initial position.

Branch staff visited with Central Weather Bureau forecasters and researchers in Taipei to conduct training on the potential use of LAPS in operational forecasting and discuss ideas for nowcasting. A Webpage...

was created to display the training sessions online and provide a subjective evaluation of the LAPS performance at the Taiwan CWB.

Additional collaboration with the Korean Meteorological Agency (KMA) and Hong Kong Observatory (HKO) has been less formal but ongoing. Both agencies are interested in developing a high-resolution modeling and analysis capability. KMA has already developed a prototype LAPS/MM5 system, which is being tested, and HKO is working on a LAPS development.

Ensemble Modeling of Winter Road Conditions – In collaboration with NCAR, LAP Branch scientists began designing an ensemble of mesoscale models to support a Federal Highways Administration (FHWA) road weather project. The ensemble includes multiple models (MM5, RAMS, and WRF) with lateral boundaries provided by multiple large-scale models (AVN, Eta, and RUC) that run at relatively high spatial resolution. Although ensemble techniques have been applied before on grids with approximately 25-km resolution, runs for this experiment were performed on 12-km grids and were used to make site-specific (road) probabilistic forecasts. The need for quantitative precipitation forecasts early (0–3 hours) in the forecast cycle necessitated the use of the LAPS hot start for all model runs. Cold started model runs were attempted, but these were of little value. Grids from the 9-member ensemble were fed into the NCAR Maintenance Decision Support system where the weather probabilities were used to make road maintenance decisions (mobilization of trucks, routes, types of chemicals, duration, etc). The system has been tested during the 2003 winter. Figure 35 shows four ensemble members and forecasts centered over the Iowa test area.

Figure 35a - MM5/Upper Midwest/Eta Boundary

Figure 35b - MM5/Upper Midwest/AVN Boundary

Figure 35c - RAMS/Upper Midwest/Eta Boundary

Figure 35d - WRF/Upper Midwest/AVN Boundary/Hot Start

Figure 35. 24-hour forecasts on 29 October 2002 showing precipitation
accumulation for the upper Midwest (centered over Iowa). (a, top) MM5
with Eta boundary condition; (b, second from top) MM5 with the AVN
boundary conditions; (c, second from bottom) RAMS with Eta boundary
conditions; and (d, bottom) WRF with AVN boundary conditions using
models initialized with LAPS/Hot Start.

Developments for the Weather Research and Forecast Model – The branch is involved in three key areas of the WRF modeling system. The Standard Initialization (SI) software creates model start-up grids from the NCEP national AVN, RUC, or Eta models. The land-surface module (LSM) of WRF uses "static" fields (such as vegetation greenness, albedo, land use, terrain height, land fraction) that have been assembled and reformatted, along with efficient interface software. The third area is a graphical user interface (GUI) for the localization of the WRF to be used by the WRF community. The initial version of the GUI was released to the WRF user community in early 2003. These software components — developed by the LAP Branch and sponsored jointly by the Air Force Weather Agency, FHWA, and FAA — are released routinely with the WRF model itself.

Lidar OSSE Studies – A strong interest has evolved over the last 20 years in the possibility of inferring atmospheric winds from Doppler lidar measurements aboard a polar orbiting satellite. Two satellites in appropriate orbits could provide daily global wind coverage, at least where the pulses of energy from the lidar are not blocked by clouds. Cost is not the only issue with this observing system. The technology for obtaining radial wind velocities with good signal-to-noise ratio is still being perfected, and more than one lidar has been proposed to do the job. For this reason, FSL cooperated with the Environmental Technology Laboratory (ETL), NCEP, and NCAR to study the impact of Doppler wind lidar data on numerical models. FSL was responsible for studying the impact of the data on forecasts over the U.S. using a regional observing systems simulation experiment (OSSE).

For the case study, a long-duration, pure forecast from February 1993 was generated using the global model developed at the European Center for Medium-Range Weather Forecasts (ECMWF). LAP Branch ran the Regional Nature Run (RNR) using the PSU/NCAR mesoscale model (MM5) initialized from the ECMWF Nature Run to simulate onboard lidar data (clouds, winds, vertical velocity). The huge MM5 domain of the RNR covered most of North America with a 10-km horizontal (740 x 520) grid spacing and 43 vertical levels. This domain was tailored to include the present domain of the RUC model. Simulated observations were extracted from the RNR over an 11-day period for inclusion into the RUC data assimilation system. The simulated data included the entire suite of operational and future lidar observations; thus, synthesized rawinsonde, ACARS/MDCRS, surface, METAR, wind profiler, and VAD winds were all extracted from the RNR fields with appropriate error characteristics. The lidar line-of-sight winds from the satellite positions in four-dimensional space were determined by ETL from the Cartesian winds and cloud hydrometeor fields provided from the RNR. The last remaining task was to conduct a variety of sensitivity experiments with the mesoscale data assimilation system (RUC) with and without the lidar data, with various combinations of boundary conditions, and with and without liquid and/or ice clouds present. Results from this experiment can be found in the section on the Regional Analysis and Prediction Branch.

NOAA Coastal Storms Initiative – With the cooperation of the NOAA National Ocean Service, the NWS embarked on a project to test and evaluate locally produced, high-resolution grids derived from an onsite, high-resolution mesoscale model, driving an estuary flow model that predicts harbor and river depths for safe navigation. A secondary purpose is to test the model for forecasting marine hazards like thunderstorms, winds, and heavy precipitation events. LAP Branch's role in this is to bring to bear the experience gained from other deployments (such as RSA), link the LAPS analysis to the new WRF model, and set up the system at the Jacksonville, Florida WFO. Jacksonville is uniquely qualified for the test with a busy harbor, two major estuaries (St. Mary and St. John rivers), and frequent occurrence of thunderstorms and tropical weather. The sea and river breezes make for a complex land/water interaction and justifies the high-resolution modeling approach. The system runs on a 9 dual processor linux cluster and ingests all local data. The 24-hour forecasts (4 times a day, both cold and hot start) run in about 3 hours. The grid is a single nest of 5-km resolution and uses the Eta model as background and boundary conditions. The need for short range quantitative precipitation forecasts necessitates the use of the LAPS diabatic initialization scheme. Adjusting the scheme for the sub-tropics will be a major challenge. This demonstration will be an important consideration for the NWS in the decision to support local modeling in weather offices.

U.S. Forest Service Fire Consortia for Advanced Modeling of Meteorology and Smoke (FCAMMS) – In 2002 the LAP Branch became involved in a project to develop an FCAMMS for the Rocky Mountain Research Station in Ft. Collins, Colorado. The goal of this project was to develop an analysis and modeling capability that encompassed needed fire-specific (both planning and incident) support products. The MM5 model was used to develop 12-km and 4-km nests for large sections of Arizona and New Mexico (the Southwest Area Coordination Center) and Colorado and Wyoming (the Rocky Mountain Area Coordination Center). These models and analyses were run over the newsworthy 2002 fire season. Products were disseminated using a Webpage. The fire manager/user had the option of initiating specific point forecasts for new fire locations by simply entering the latitude and longitude. During the next model cycle (4 times per day) a test product was generated with weather for the next 24 hours. Development is continuing to add new products, increase resolution, and improve existing products and the appearance and utility of the Webpage. Once the initial capability is completed, new members of the consortium will be sought. State and federal agencies with a need for high resolution weather support are likely candidates.

Projections

During 2003, the Local Analysis and Prediction Branch plans to:
  • Continue to support LAPS in AWIPS, interacting with the AWIPS contractor, Litton PRC Inc., and the NWS to achieve this goal.
  • Support the U.S. Army Precision Air Drop System (PADS) by improving and expanding sources of data, ingest and use of climatology, and improved estimates of model error and variance.
  • Continue the cooperative effort with Lockheed-Martin in developing the RSA weather support systems for the Space Flight Centers at Cape Kennedy and Vandenberg Air Force Base. Help with expanding the customer base for RSA-like systems. Investigate whether improvements to the background error term specifications and new methods to deal with spurious convection in the model forecast can result in replacement of the current system with a fully cycled, rapidly updated four-dimensional data assimilation system.
  • Complete the evaluation of the FSL special model runs from IHOP with the goal of improving operational model prediction of convection initiation, evolution, and quantitative precipitation forecasts (QPFs). Strive for further improvements in short-range QPFs using an optimized diabatic initialization technique applied to the MM5, WRF, and RUC models. Determine how forecast mesoscale convective systems compare with the type observed, including an analysis of the relative contributions of forecast displacement, intensity, and shape errors to the total error. Publish the results.
  • Demonstrate LAPS capabilities on the new high-performance multiprocessor, continue investigating Hot Start techniques, and perform an assessment on the use of 3DVAR for local analysis in the context of the WRF model.
  • Continue development of the multimodel ensemble methodology; determine the optimum configuration for best forecasts and user-friendly products. Improve the postprocessing to develop optimum ways to provide consensus forecasts and statistically based products. Seek new applications and projects for a mesoscale model approach.
  • Complete the WRF Standard Initialization and graphical user interface and distribute the model to the community. Complete range of land surface fields for ingest into the land-surface model subsystem.
  • Support the U.S. Forest Service FCAMMS project by improving the local model runs and analyses, and improving dissemination via the Web. Provide training to USFS personnel on model configuration and management.
  • Set up, install, and tune the LAPS/WRF modeling system for the CSI project. Support product cycles and grid outputs for independent verification. Support NWS/OST in presenting results to the NWS Corporate Board.

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Meteorological Applications Branch
Steve Koch, Acting Chief

Objectives

The Meteorological Applications Branch performs diagnostic studies of weather-related phenomena, including mesoscale convective systems and clear-air turbulence. A springboard of these studies is the development of diagnostic tools that are applicable to routine observations, data from experimental networks or model grid-point data, and that utilize statistical methods, fundamental dynamical relationships, and derived parameters relating to unobserved variables. These studies often result in products of value to forecasters and are transferred to the National Weather Service (NWS). Research quality datasets of operational sounding and precipitation data and of commercial aircraft atmospheric data are assembled to support FSL modeling and diagnostic activities, and are shared with other NOAA laboratories and NWS research groups. The branch also conducts field tests and computer simulations to study the impact of balloon-based, in situ observing systems on atmospheric and oceanic monitoring for environmental prediction and climate observations.

Accomplishments

Global Air-ocean IN-situ System (GAINS)

The Global Air-ocean IN-situ System (GAINS) is an Earth observing system of 400 regularly spaced platforms from which in-situ sounding of the atmosphere and ocean, and in-situ collection of air chemistry samples can be performed. It is anticipated that several kinds of vehicles, operating between 18 and 23 km, will make up the GAINS low-Earth-orbit constellation. Superpressurized, shear-directed balloons and remotely operated aircraft (ROA) are presently under consideration. GAINS vehicle development currently emphasizes the superpressure balloon and appropriate altitude control mechanisms. A number of forecast tools have been refined for planning and support of GAINS field tests. Execution of a major milestone in the development of the GAINS brought the concept one step closer to fruition.

GAINS PIII Flight – The maiden flight of the 60-ft diameter GAINS Prototype III (PIII) balloon occurred on 21 June 2002. This flight met several development objectives, including launching the PIII balloon, floating it at altitude for more than eight hours, transforming the balloon envelope into a deceleration device, achieving a safe descent rate, tracking the balloon from an aircraft; forecasting balloon trajectory before launch, updating balloon landing position during flight, and recovering the balloon and payload.

Manufactured by GSSL, Inc., of Hillsboro, Oregon, and launched from their Small Balloon Facility at Tillamook, Oregon, the 500-pound balloon carried a 325-pound payload containing packages from four organizations. The FSL payload included GPS for locating the system, two independent radio- and software-controlled termination methods, and environmental sensors to monitor balloon performance. The payload also contained a GPS reflection experiment from NASA/Langley, redundant locating capability based on a design adapted from the Edge of Space Science (EOSS) of Denver, Colorado, and backup location and termination units from the Physical Science Laboratory of New Mexico State University and from GSSL.

Nominal float altitude of 54,000 ft was achieved after reaching a maximum altitude of 57,000 ft. A tracking aircraft kept the balloon within radio line of sight at all times during the 225-mile flight, and personnel on board coordinated the flight with FAA Air Traffic Control. Two additional vehicles tracked the balloon from the ground and recovered the payload. The balloon's descent was slowed by the GSSL BERSTM (Balloon Envelope Recovery System), in which the balloon envelope transformed to a parachute and the system descended at about 500 ft per minute. The soft landing caused no damage to the payload capsule, and minimal damage to the wheat field south of The Dalles, Oregon, where it landed. The entire system was removed from the landing site and returned to Tillamook within 24 hours of landing. Figure 36 shows the actual flight path and the path predicted using winds from the global AVN numerical model.

Figure 36 - GAINS Balloon Flight Path

Figure 36. Flight path taken by the GAINS PIII balloon and the path predicted
using winds from the global aviation (AVN) numerical weather prediction model.

GAINS Pump Test Flight – On 17 August 2002 a flight was launched from Meadow Lake Airport, northeast of Colorado Springs in a cooperative effort between the GAINS and EOSS groups. The main objective of the flight was to test the operation of the turbine developed by Advanced Engineering at GAINS operational altitudes. Results from laboratory experiments indicated that the turbine met the requirements for flow rate, power needs, and weight; this experimental flight was intended to affirm these results under true atmospheric conditions. Turbine electronics and control software algorithms were also tested. A 19,000 cubic-ft polyethylene balloon was used for lift, and a 500-gram latex balloon in a GAINS P-I 8-ft nylon shell used as a ballast balloon. The plan was for the turbine to pump ambient air into the ballast balloon until the desired super pressure was achieved. For this experiment, the turbine was to be tested at 50,000, 60,000, and 70,000 ft, with inflation continuing until a super pressure of ambient plus 15% was achieved. The payload, consisting of all control and communication electronics, was located in an insulated ring that encircled the turbine on a lightweight disc with three supporting legs, known as the "lander" (Figure 37).

Figure 37 - GAINS Payload Lander Package

Figure 37. The GAINS payload lander package prior to launch.

The gusty nature of the surface winds prior to launch made for complications, the most significant being the introduction of small holes in the polyethylene lift balloon from contact with the ground. Most, but not all, of these were repaired prior to launch, resulting in a flight duration shorter than expected. The balloon reached a maximum altitude of 32,000 ft before descending back to earth. Unfortunately, this altitude was not sufficient to allow testing of the GAINS pump. Although the pump performance could not be tested, the setup and launch procedures as well as tracking and recovery were successful. This will enhance the ability to achieve the goals when the test is repeated later.

Evaluation of Balloon Trajectory Forecast Routines – Software has been developed that uses observations and model wind data for prediction of balloon trajectories for GAINS. A fifth version of the software, utilizing output from the U.S. Navy NOGAPS model, was added to the four other versions that currently use rawinsonde data, global AVN model winds and RUC-2 model winds. Each version produces predicted balloon positions in 1-minute increments, and these are available to FSL personnel and collaborators in textual and graphical form at the GAINS Website, http://www-frd.fsl.noaa.gov/mab/sdb/overview.htm.

A verification study was performed on the predictions made for the period 1 March 2001 – 31 August 2001, building upon a 1-month study performed in 2001. Prior to that initial study, comparisons were limited to examination of experimental flight data on a case-by-case basis. Since resource constraints have not permitted twice daily balloon launches (from which actual balloon trajectories can be obtained), a verification system was developed using predictions from hourly analyses from the MAPS RUC-2 model as a baseline to examine differences between baseline and predicted trajectories from the rawinsonde and AVN model-based predicted trajectories. When segregated by season (spring and summer), the comparisons show a significant decrease in correlation of longitudinal errors from spring to summer. Median values appear to indicate stronger zonal winds in the RUC data in comparison to the values obtained from the AVN-based predictions. Further study is planned, including comparison with GAINS and other actual balloon flights.

Support of NCAR Dropsonde Experimental Flight – The InterContinental Radiosonde Sounding System (ICARUSS), also called Driftsonde, is a proposed new atmospheric sounding system for use during the upcoming THORpex (THe Observing-system Research and predictability experiment) field projects in 2003 or 2004. The ICARUSS concept uses a thin polyethylene balloon (0.35 mm) with a volume of 268 cubic meters to lift a payload (up to 40 kg) of 24 dropsondes or modified radiosondes to an altitude of about 100 – 75 mb (53,000 – 60,000 ft) and maintain that altitude for 5 or 6 days. The altitude of the balloon can be adjusted over a limited range to take advantage of the most favorable upper-level westerly wind flow.

Simulations using 1999 wind data over the Atlantic and Pacific oceans show that balloons launched from coastal radiosonde sites (in the eastern United States or Asia) will travel across the oceans in approximately 5 or 6 days. The dropsonde would telemeter the measured profile data back to the balloon where it would be received, processed, and stored. A compressed dataset (e.g., WMO message or 10-second data) would be sent through a Low Earth Orbiting Satellite (e.g., ORBCOM) to a ground station and on to the THORpex control center for further processing and/or input into the Global Telecommunications System (GTS).

A 2-hour experimental flight was launched from Tillamook, Oregon, on 28 February 2002. Software written for GAINS balloon trajectory prediction was modified to use flight parameters appropriate for the Dropsonde flight, and these changes were provided to NCAR personnel at Tillamook. Through use of these predictions, NCAR was able to make a prelaunch assessment of the expected flight path, and recovery personnel were positioned in the proper area.

Station-keeping Balloon Concept – A cursory examination of the technical feasibility/capabilities of a self-propelled Aerodynamic Canopied Balloon Cluster (ACBC) was prepared, and a rudimentary model was constructed and demonstrated. This concept evaluation was toward a buoyant craft that could float (rather than fly) to high altitudes where the air is thin enough so that aerodynamic streamlining and solar powered turbines could allow the craft to fly against the prevailing wind with enough speed to remain fixed in space at altitudes exceeding 70,000 ft. As envisioned, the systems onboard an ACBC craft might include:

  • Standard lifting balloons
  • GBP-033 altitude ballast control pumps (GAINS pump)
  • Aerodynamic canopy structure
  • Solar cell panels with manipulators
  • Propulsion pods with ducted fan units/motors controllers
  • Battery charging system with lithium ion polymer batteries
  • Programmed module for GPS location capability
  • Radio communications module
  • Cargo gondola and load lines

The overall ACBC concept suggested here is radical, but the various components exist and in some cases are "off the shelf." The net payloads may be substantial, as balloon technologies allow for payloads into the thousands of kilograms at relatively low cost.

Forecasting Clear-Air Turbulence

Field Studies – Funded in part by the FAA's Aviation Weather Research Program and operating in the Pacific Ocean in collaboration with NOAA's Winter Storms Reconnaissance Program, the SCATCAT (Severe Clear-Air Turbulence Colliding with Aircraft Traffic) experiment was conducted in 2001. Scientists in the Meteorological Applications Branch collaborated with NCAR, the Aeronomy Laboratory, and NASA to test the performance of RUC model predictors of turbulence and to better understand turbulence generation mechanisms. These forecasts are used to construct the Integrated Turbulence Forecast Algorithm (ITFA) appearing on the Aviation Digital Data Service (ADDS), http://adds.aviationweather.gov/, at the Aviation Weather Center.

FSL scientists have analyzed data collected by the NOAA Gulfstream-IV (G-IV) aircraft from one of the SCATCAT missions. In-flight observations were made at several altitudes and dropsondes were launched from the 41,000-ft level along a track perpendicular to the core of an upper-level jet streak. The aircraft encountered moderate-or-greater (MOG) turbulence on three legs of the stack, highlighted in yellow in Figure 38. This figure is a cross-section analysis of wind speed, potential temperature, and DTF3-diagnosed Turbulent Kinetic Energy (TKE) fields computed from the dropsonde data. Regions of strong vertical wind shear are evident above and below the level of the jet core. There is also a strong suggestion of vertically propagating gravity waves above the jet core and to its cyclonic side in the lower stratosphere (in the 260 – 176-mb layer). Coherent streaks of MOG turbulence are predicted by the DTF3 (Diagnostic Turbulence Flux Algorithm) field primarily in the layers of strong shear just above and below the jet core and within the warm front stable layer. These layers of high DTF3 correspond well to the observed in-flight turbulent regions.

Figure 38 - Vertical Cross Section 1

Figure 38. Vertical cross section of wind magnitude (blue lines, 5 m s-1 isotachs), potential temperature (black lines, 2K isentropes), and DTF3 turbulence diagnostic computed from dropsondes (note release times at bottom of display) from 2300, 2600, and 0600 UTC 17 February through 0000, 2400, 0200 UTC 18 February 2001. Jet core is highlighted by winds in excess of 80 m s-1 (maximum of 100 m s-1), and DTF3 values are contoured at 0.6 and 1.0 m2 s-3 (yellow and red areas, respectively). Also shown are the stacked legs of the G-IV tracks (black lines with arrows depicting sense of aircraft travel), and those segments of the legs (yellow highlighting) for which moderate-or-greater turbulence was diagnosed in the flight-level data (see text). Note distance scale at top of display.

The RUC20 model was run for this SCATCAT case, representing the first time that the RUC had ever been positioned to run entirely over the Pacific Ocean. The AVN model was also used for the first time instead of the Eta model for specification of the RUC boundary conditions. Figure 39 shows a cross section of isentropes and isopleths of isentropic potential vorticity taken perpendicular to the jet core but over a longer length than the dropsonde cross section in Figure 38. These model predictions were compared to fields of winds, potential temperature, and ozone (potential vorticity is taken as a surrogate for ozone) measured by the aircraft. This comparison revealed very similar features, including the warm frontal zone, the upper-tropospheric front/jet system zone, and regions of strong vertical wind shear and associated large DTF within these zones. A deep tropopause fold is present along the warm frontal zone down to almost 700 hPa, but of greater interest are multiple tropopause "undulations" in the upper-level front of the model. Also of interest are mesoscale gravity waves in the lower stratosphere directly above the jet core, with vertically varying horizontal wavelengths of ~100 – 160 km. Similar waves in the dropsonde analyses in the lower stratosphere directly above the jet core displayed wavelengths of ~80 km. A higher-resolution version of the RUC, of course, might have produced shorter wavelength features.

Figure 39 - Vertical Cross Section 2

Figure 39. Vertical cross section of potential temperature (black lines, 2K
isentropes) and isentropic potential vorticity (colored shading, in units of
PVU) produced from a 6-hour forecast by the RUC20 model valid at
0300 UTC 18 February. A pronounced tropopause fold is shown at the
upper reaches of the warm front, which is marked by strong static stability
from 500 hPa to 900 hPa in the center of the domain. The upper-level jet
core occurs in the vicinity of several "tropopause undulations." Notice the
presence of mesoscale gravity waves in the lower stratosphere above the
jet core. Also shown is that part of the cross section sampled by the G-IV
aircraft (black vertical lines). Distance scale appears at bottom of display.

Wild fluctuations in ozone measurements from the NOAA/ARL experimental instrument were measured at the 41,000-ft level, but fluctuations in the potential temperature and wind in-flight observations did not correlate highly with the ozone data, nor was much turbulence reported on this flight leg. It was concluded that these rapid fluctuations in ozone at this level represented "fossil turbulence" or remnants of earlier stratosphere-troposphere turbulent exchange processes. By contrast, the correlation between the ozone and in-flight variables, as well as with the RUC model potential vorticity variations, was very high at the 33,000-ft altitude. Also, moderate turbulence was reported at this flight altitude, as the G-IV was penetrating a rather pronounced gravity wave within the upper-tropospheric frontal zone. Thus, active turbulence was occurring in association with gravity wave activity at this altitude, but not at the higher level.

Time series and spectral analyses were performed for each of these flight legs in an attempt to relate the appearance of turbulence to mesoscale gravity wave activity. Potential temperature and longitudinal wind exhibited a high degree of cross correlation, as did the potential temperature and ozone data at the 33,000-ft level. Such a strong "in-phase covariance" is expected of either deep propagating gravity waves or, more likely, decaying (evanescent) waves.

The SCATCAT research revealed that MOG turbulence occurred in conjunction with gravity waves shed within an upper-level fractured front on the cyclonic shear side of the jet core. Besides this major finding, it was concluded that RUC-forecast DTF is a useful diagnostic of turbulence, whereas ozone is not, and that both the MOG turbulence and the high DTF regions occurred in the vicinity of the strongest mesoscale gravity wave activity in both the model forecasts and the aircraft observations.

Diagnostic Algorithm Development – The forecast skill of Integrated Turbulence Forecasting Algorithm (ITFA) and its component algorithms has been evaluated both objectively and by forecasters. These studies show that the best of the algorithms display similar probability of detection (POD) curves, and that there is considerable room for improvement. Research conducted at FSL indicates that these algorithms also typically predict patterns that are similar to one another, and that MOG pilot reports (PIREPs) of turbulence often fall in the margins of the predicted ITFA regions. The best of these algorithms are fundamentally based on the destabilizing dynamics of vertical wind shear.

FSL developed an experimental turbulence prediction scheme based on a radically different dynamical concept, namely that turbulence is generated as mesoscale gravity waves are shed when an unbalanced jet streak propagates toward an inflection axis in the upper-level height field (the SCATCAT analyses discussed above lend additional support to this contention). Diagnosed gravity waves and model flow imbalance have been shown in detailed case studies by Forecast Research Division scientists to relate strongly, not only to each other, but also to MOG turbulence reports. The flow is considered to be unbalanced when there is a pronounced residual in the computed sum of the terms in the nonlinear balance equation from the RUC model. Imbalance typically occurs in essentially the same region as where mesoscale gravity waves develop and upstream of where the turbulence is reported, as demonstrated in one case shown in Figure 40. Note in this example that the imbalance is occurring precisely at the tip of the dry air stream associated with subsidence within a pronounced jet streak (or "potential vorticity streamer," discussed below). The conventional turbulence diagnostic DTF3, which is a major contributor to the ITFA, fails to predict the swath of turbulence reports in the Ohio River Valley region, whereas the imbalance indicator field successfully captures this event. On the other hand, DTF3 does a credible job at delineating the other swath of turbulence reports in the Great Lakes region, not captured by the imbalance field. This complementary nature of the imbalance indicator fields and DTF/ITFA is typically observed to occur.

Figure 40a - RUC Forecast Diagnostics and Analyses 1

Figure 40b - RUC Forecast Diagnostics and Analyses 2

Figure 40c - RUC Forecast Diagnostics and Analyses 3

Figure 40d - RUC Forecast Diagnostics and Analyses 4

Figure 40. Analyses and 3-hour RUC forecast diagnostics valid at 1200 UTC 7 February 1999: (a) enhanced water vapor imagery and time-space converted MOG PIREPs over a ±2-hour interval, (b) heights and wind at 300 hPa, ridge axis (thick curve), and jet isotachs (kt), (c) DTF3 prediction of turbulence and MOG PIREPs overlay, and (d) unit streamwise advection of the residual of the nonlinear balance equation (the imbalance indicator field).

A Webpage was created this past year to examine the relationships between diagnosed flow imbalance from the RUC20 model and MOG turbulence reports on a daily basis. This more thorough investigation has shown that mountain waves generated by strong flow over rough terrain like the Rocky Mountains are even more highly correlated with turbulence and flow imbalance than are the imbalances associated with the jet stream and cyclonic storm systems. While mesoscale models like RUC can be useful for diagnosing the flow imbalance regions and where generally gravity waves are likely to form, they do not reliably predict the details of the gravity waves themselves, such as their wavelength, phase speeds, and so forth. The new predictive scheme being developed at FSL not only produces patterns systematically different from the current ITFA algorithms but also predicts turbulence regions missed by those methods. Further refinement of forecast turbulence regions might be obtained by adding the requirement that an efficient wave duct must be present downstream of the region of diagnosed flow imbalance to retard the vertical leakage of wave energy, thus allowing coherent waves to persist. The optimum amount of smoothing of the imbalance fields, the proper thresholds, and other numerical issues must all be resolved, before the new imbalance indicator field can be incorporated into ITFA to increase its utility.

Mesoscale Diagnostic Studies

Moisture Transport by the Low-level Jet (LLJ) – The Central Plains Low-Level Jet (LLJ) is a warm-season phenomenon that transports large amounts of moisture northward into the center of the U.S., thereby playing a critical role in the location and intensity of precipitation. Unfortunately, the existing observational network is not well designed to describe the LLJ. The radiosonde network, for instance, often misses the period of maximum jet intensity in very early morning (to say nothing of its spatial dimensions or substructures), and wind profilers often cannot observe low enough to capture the LLJ core. Perhaps even more critically, neither radiosondes nor profilers can adequately observe the detailed boundary layer moisture distribution. As a result, numerical initialization fields do not accurately represent transport of moisture by the LLJ, with inevitable negative implications for quantitative precipitation forecasting.

The IHOP project offered a unique opportunity to carry out two aircraft missions (led by the Forecast Research Division Chief) to observe the morning LLJ over Oklahoma and Kansas. Each mission utilized airborne dropsonde data, Differential Absorption Lidar (DIAL) data flown on the German Falcon, High-Resolution Doppler Lidar (HRDL) data from NOAA/ETL also flown on the Falcon, and in one of the cases, hyperspectral radiometric data from the NASA Proteus aircraft, to observe a strong LLJ in good atmospheric conditions (i.e., substantially free of clouds). These observations offer an excellent opportunity to prepare detailed three-dimensional meteorological fields of moisture and winds at a multitude of scales and the possibility to compute a moisture budget. The objective is to examine these data to determine the impact of fine-scale moisture observations on the numerical prediction of precipitation. Another ongoing task is combining datasets obtained from the two aircraft missions to compute moisture budgets and perform diagnostic and numerical modeling studies of these cases to test the hypothesis that warm-season QPF skill can be significantly improved by better characterization of the transport of water vapor by the LLJ.

Structure and Dynamics of Gravity Currents and Undular Bores – The IHOP field phase collected a surprisingly large number of events in which either a thunderstorm outflow boundary or cold front, acting as an atmospheric gravity current, intruded into a stably-stratified boundary layer and generated an undular bore (a kind of hydraulic jump) on the top of the inversion. In some cases, deep convection appeared to have been generated by the vertical motions attending this phenomenon, which are quite strong (updrafts of several meters per second magnitude). An unprecedented number of ground-based and airborne remote sensing systems observed the passage and evolution of bores in IHOP, including FM-CW radar, the NCAR Multiple Antenna Profiler (MAPR), Raman lidar, the NASA GLOW and HARLIE aerosol backscatter lidars, refractivity fields obtained from the NCAR S-POL radar, an Atmospheric Emitted Radiance Interferometer (AERI) system, the French Leandre-II DIAL system aboard the NRL P-3 aircraft, and the University of Wyoming King Air aircraft. FSL is collaborating with a team of international scientists to analyze these data. Also, very high-resolution numerical simulations of two bore events are underway to better understand the origin, dynamics, entrainment mechanisms, and influence on convection initiation by undular bores. Much more will be reported on these studies in the next issue of FSL in Review.

Potential Vorticity Streamers – Researchers in Europe and the United States have noted the frequent occurrence on water vapor satellite imagery (GOES and METEOSAT) of pronounced dark filaments, which are mesoscale in width and varying in length up to the largest scales of atmospheric motion (see Figure 41). The most pronounced of these dry filaments have a parallel jet stream immediately to the south, and according to recent studies conducted at FSL, a similarly shaped band of collocated, enhanced potential vorticity (a "PV streamer"). Another satellite-observed feature — enhanced ozone — suggests that a PV streamer is a downward intrusion of stratospheric air along an upper-level front.

Figure 41 - Central US Spec Humidity

Figure 41. Mid-to-upper tropospheric specific humidity at 0000 UTC
22 April 2001 displayed using an altered water vapor product. Note
that the dry filament in the Central U.S. is an extension of a much
larger feature of the large-scale flow pattern.

Monitoring PV streamers has prognostic value. In Europe, PV streamers have been identified as precursors to flooding along the Mediterranean slopes of the Alpine piedmont. In the United States a number of case studies have documented MCS development near a preexisting PV streamer. Some of these MCSs were accompanied by severe weather and flash flooding, as was the case with one occurring 28 June 1999 over Kansas (described in the 2002 FSL In Review). This storm was one in a series of four MCSs that occurred along a PV streamer that persisted six days over the central and southeastern United States. The total precipitation from these four MCSs produced a significant fraction of the area's annual precipitation.

In addition to being a valuable forecasting ingredient to organized convection and heavy precipitation, the PV streamer is a fascinating phenomenon, rich in dynamical and thermodynamic implications deserving of serious scientific study. It combines upper-level jet stream dynamics with the flow of midtropospheric, dry, potentially cold air having a low static stability. Some researchers have suggested that the exit region of an upper-level jet streak enhances a transverse low-level jet as a result of mass balance. Others have suggested that upper-level PV passing over a low-level front can organize a developing cyclonic circulation. With the addition of moisture to the low-level jet, the mechanisms for producing organized convection are all present. The details of how the ingredients combine to shape an MCS await results of field experiments (such as BAMEX) and those of mesoscale modeling at FSL.

Research Quality Datasets

Climate Station Monitoring Project – As part of the USWRP- (U.S. Weather Research Program) funded Health of the Network Project at the National Climate Data Center, a system to assure precipitation observation homogeneity in the climate data record has been devised and partially tested. Magnitude, frequency bias, and Equitable Threat Score have been chosen as measures of correlation between measurement sites because they implicitly compensate for the highly variable and binary (on-off) character of precipitation. In this application, scores are computed between sets of observation pairs made at individual target stations and a set of their neighbors. Comparison of results between winter and spring in Iowa illustrate that seasonal variability caused by instrumentation response to frozen precipitation may not be as significant a problem as feared. Computations of longer-term precipitation totals (3 – 7 days) have revealed no advantage to homogeneity tests performed over periods longer than one day.

NCEP Gauge Quality Control Project – A system for the automated screening of hourly gage precipitation observations has been designed to find failing gauges in the Hydrometeorological Automated Data System (HADS). Funded by the USWRP, this system was solicited by National Centers for Environmental Prediction (NCEP) to provide more timely gauge quality indicators to prevent the use of faulty gauges in analyses used to initialize model runs. Following the identification of several characteristic failure types (e.g., gauges that jam on or off for long periods), tests for these failures on individual gauges have been devised. Several of these tests are based on the most recent 30-day distributions of precipitation characteristics such as daily and hourly rainfall frequency. Gauges that fail these tests can then be entered on a reject list to eliminate them from precipitation analyses and model verification. Because old or inaccurate station metadata have often been a weak link, procedures to automatically update relevant station lists have been introduced. An automated procedure for gauge quality control and rejection will be completed during 2003 and delivered to NCEP for implementation.

Assessing the Quality of Real-Time Precipitation Gauge Observations – An ongoing collaboration with the Real-Time Verification System project group seeks to improve verification procedures for model-based precipitation forecasts. Over the past year, this verification effort concentrated on the use of hourly point precipitation observations at sites to which model fields were interpolated. Of major concern was the determination of the quality of hourly observations in order to screen out unsatisfactory observing sites and to reincorporate sites with good observations that in the past have not been included in the set of stations presented in near real time by River Forecast Centers.

ACARS/AMDAR Quality Control System – A computer program to flag and in some cases correct weather data from automated sensors on commercial aircraft (called ACARS in the U.S. and AMDAR in the rest of the world) was upgraded. The quality control system uses temporal and spatial consistency checks along each flight track and altitude-adjusted climatological consistency checks to discover errors. It also interpolates locations and times for high-resolution observations taken during ascent and descent enabling these data to be used in numerical weather prediction model research and weather forecasting. The quality control system was upgraded to ingest and display data from the MDCRS (Meteorological Data Collection and Reporting System) data stream, produced by Aeronautical Radio, Inc. MDCRS data are largely the same as data provided by airlines directly to FSL, and decoded here, but have some differences. Because MDCRS feeds numerical weather prediction models run by NCEP, it is important to understand these differences. The QC system attempts to match each MDCRS observation with one decoded directly by FSL, and report the differences. The QC system was also upgraded to process experimental icing data from Delta Airlines, in support of a research effort led by the National Center for Atmospheric Research and funded by the FAA.

ACARS-RUC Intercomparison Database – A database has been developed that compares ACARS data with 1-hour RUC forecasts. RUC data are interpolated to the location of each ACARS observation. This database, with 9 months accumulated data, is used to develop error statistics for longitudinal and transverse winds, and for other RUC and aircraft error analyses.

North American Radiosonde Dataset – For years FSL has been providing a CD-ROM archive of quality-controlled radiosonde data for use by the research community. During 2002, updates were made to the global and North American station history files to reflect changes in the network sites, including moves, station identification changes, and addition of new stations. The Website was modified to correct problems in the generation of duplicate skew-T plots for different stations, and software was incorporated to handle the change to a new year without interrupting service.

FSL Websites

GAINS Website
(http://www-frd.fsl.noaa.gov/mab/sdb/gains_rt.htm)
– This GAINS field briefing Webpage is accessible to crews in the field wherever a phone line exists. Updated hourly, this page contains the current surface observation and upper-air winds for Tillamook, Oregon, the location of annual test flights, as well as links to satellite, radar, numerical model, and surface and upper-air charts and other data. Upper-air charts for mandatory pressure levels above the height of 100 mb covering the continental U.S., Pacific Northwest, and Colorado regions are generated in-house and added to the briefing Webpage.

Chemical Weather Research and Development Website
(http://www-frd.fsl.noaa.gov/aq)
– In support of a major NOAA initiative to improve temperature and air quality forecasting, a Website was developed that that will present real-time and retrospective results from air quality models. The region of interest is primarily New England, the location of the Temperature and Air Quality (TAQ) project conducted in 2002. A related site on high-resolution temperature forecasting may be found at http://www.temp-aq.org.

National Hourly/Daily Precipitation Website
(http://esrl.noaa.gov/precip/hourly_precip.html)
– Development work continued on a Website that displays hourly and daily precipitation data from NCEP. Data are displayed on a national map that optionally shows rivers and county boundaries. Moving the cursor across the map reveals the available data, and a mouse click provides a daily time series of the data. Users can zoom and roam on the map for detailed local structure of precipitation events. Years of precipitation observations are available at the site. Significant improvements have been made to this Website as part of a USWRP-funded project with NCEP to improve screening of the operational network of real-time hourly precipitation observations. Included in the set of new features are a utility to locate individual stations on the display, extension of the geographical display to a global domain, incorporation of standardized Java code from several FSL Websites to simplify site maintenance, and improved ability to distinguish stations that are in very close geographical proximity.

ACARS/AMDAR Website
(http://amdar.noaa.gov/)
– Many upgrades were made to this site, which displays weather data from automated sensors on commercial aircraft. Air Route Traffic Control Center boundaries were added to aid users working at Center Weather Service Units (CUSUs). Additional North American VOR stations were added, primarily at the request of users at CWSUs. Experimental icing data from Delta airlines can now be displayed. Data can be selectively displayed based on data source: either ACARS (decoded at FSL), MDCRS (decoded at ARINC and ingested into NCEP models), or AMDAR (non-U.S. data). Observations with missing or bad wind and temperature data can be excluded from the display. Additional statistics (such as number of observations in a particular geographic region) are displayed. Data reporting wind speeds in excess of 200 kts are now displayed. Data downloads may now be restricted to specific types of data (such as ACARS or AMDAR) and data in specific geographic regions, thereby potentially speeding up data loading. Java code was upgraded to be consistent with the latest versions of Java, such as those used by Netscape version. Several audiovisual tutorials were created and made available on the Web; these show in detail how to use the various options available on the Web display.

Recently, 86 sites (such as participating airlines, United States and foreign forecast offices, and research institutions) accessed the site, which is restricted to specific users at the request of the airlines providing the data. These sites requested more than 2,500 data loads and looked at more than 4,100 soundings. Figure 42 shows the upgraded display.

Figure 42 - ACARS/AMDAR Website

Figure 42. ACARS/AMDAR Website display of aircraft
tracks worldwide for a 1-h period on 11 March 2003.

Interactive Soundings Website
(http://www-frd.fsl.noaa.gov/mab/soundings/java/)
– This Website interactively displays past and forecasted soundings from two versions of the RUC model, as well as from wind profilers, radiosondes, and aircraft. This page is becoming increasingly popular, with more than 56,000 accesses from over 450 major domains (such as "noaa.gov" or "delta.com") — nearly twice as many as in January 2002. The easily adaptable Java code that runs this site has been requested by more than 80 organizations, and has been released to them under FSL's open-source software license/disclaimer. The site was upgraded to display worldwide radiosonde data. Also, the latest available data from any radiosonde site are listed, to save users the trouble of seeking data from sites that have not reported recently.

National Mesonet Website
(http://madis.noaa.gov/sfc_display/)
– Using Java, a national mesonet Website was developed to interactively display observations from 22 mesonetworks (up from 17 a year ago), maritime buoys, and the METAR network, with typically more than 7,000 stations from around the world (up from 3,200 a year ago). The site displays weather data and quality control information from FSL's Meteorological Assimilation Data Ingest System (MADIS). The Java code has been modularized into packages, which are shared with other FSL Websites to allow easier code maintenance, and upgraded to be consistent with the latest versions of Java, while remaining compatible with earlier versions. Recently, North American highways were added as an overlay, thereby helping to put site locations in perspective, particularly when the map is zoomed in to a local region. The site, previously restricted, is now publicly available. During January 2003 it was accessed more than 2,900 times from 525 unique domains. Figure 43 shows mesonet data for a region centered on Washington, D.C.

Figure 43 - Mesonet Data - Washington, DC

Figure 43. Surface mesonet data for a small region centered on
Washington, D.C., for a 76-minute period on 12 March 2003.
The temperature coding range has been adjusted so the cooler
stations, toward the west, are shown in blue, and the warmer
stations, in the east, are shown in red. Washington National
Airport is shown at the cursor location. The beltway and
other highways are shown in brown.

RUC-ACARS Website
(http://amdar.noaa.gov/ruc_acars/)
– This page is similar to the ACARS/ AMDAR Website (above), and similarly restricted. It displays ACARS data along with RUC 1-hour forecasts interpolated to the location of the ACARS data. Standard meteorological variables (wind and temperature) from either the aircraft or the RUC model may selectively be displayed, along with ACARS-RUC differences in vector wind, wind speed, and temperature. The site is used primarily within FSL, and is useful for identifying aircraft wind and temperature biases, and RUC errors. The page displays data from the ACARS-RUC intercomparison database, and as of this writing, 9 months of data are available for display.

PIREPs-AIRMETs Website
(http://www-ad.fsl.noaa.gov/fvb/rtvs/turb/2003/interrogation_tool/)
– This page displays pilot reports (PIREPs) and AIRMETS (warnings issued by the Aviation Weather Center). Currently it displays only AIRMETs and PIREPs related to turbulence. Raw PIREPs along with their decoded values are displayed when the cursor is moved over a data point. AIRMET skill statistics may be generated for each AIRMET, and for each Aviation Weather Center region, including Alaska. This site has been useful for understanding more deeply AIRMET turbulence skill statistics generated by FSL's RTVS project. Also, because this site allows displays of turbulence PIREPs reported since 21 January 2002, it has been useful in verifying turbulent events identified by other means, such as infrasound.

North American Radiosonde Database Website
(http://esrl.noaa.gov/raobs/)
– This site provides access to the most recent years of global radiosonde data. Upgrades last year included updates to the global station history and provisions to accommodate the change over to the most recent year without service interruption or loss of data. The FSL format was slightly changed to show north or south latitudes and east or west longitudes to avoid confusion. Problems with duplicate skew-T images being generated for different stations were resolved.

Projections

During 2003, the Meteorological Applications Branch will be involved in the following activities and studies.

Forecasting Clear-Air Turbulence

Field Studies – Analysis of the SCATCAT cases will be completed with the objective of deriving a comprehensive picture of the atmosphere producing turbulence. This interpretation will be built using the dropsonde data, meteorological data from aircraft flight level, ozone data from the Aeronomy Laboratory's experimental sensor flown during SCATCAT, and model analyses. In addition to the case study analyses, modeling studies will be completed with a 10-km version of the RUC to determine whether mesoscale features captured in the aircraft data are resolved in the model, where and with what intensity the model develops turbulence from both diagnostic and prognostic routines, how this model turbulence compares with that measured by the aircraft, and how tropopause folding in the RUC compares with the onboard ozone measurements.

Diagnostic Algorithm Development – The residual of the nonlinear balance equation and other methods will be further investigated to arrive at the optimum method for diagnosing imbalance and for determining the appropriate threshold values. Real-time evaluation of these approaches will continue to be performed in preparation for planned implementation and full evaluation within ITFA in the next year. Idealized modeling studies will be performed to develop a basic understanding of the nonlinear-scale contraction process by which mesoscale gravity waves may steepen and saturate, leading to turbulence production at smaller scales.

Mesoscale Diagnostic Studies

Moisture Transport by the Low-level Jet (LLJ) – The aircraft data will be processed and analyzed to determine the impact of fine-scale moisture observations on the numerical prediction of precipitation. The combined datasets obtained from the two aircraft missions will be used to compute moisture budgets and diagnostic and numerical modeling studies of these cases will be performed in order to test the hypothesis that warm-season QPF skill can be significantly improved by better characterization of the transport of water vapor by the LLJ.

Structure and Dynamics of Gravity Currents and Undular Bores – The remote sensing data observing bores in IHOP will be analyzed in collaboration with a team of international scientists. Very high-resolution numerical simulations of two bore events, possibly to include Large-Eddy Simulation (LES) studies with specialized treatment of the boundary layer, will be conducted to increase understanding of the origin, dynamics, entrainment mechanisms, and influence on convection initiation by undular bores.

Potential Vorticity Streamers – FSL plans to participate in the BAMEX field experiment and complete its mesoscale modeling of PV streamer interactions with mesoscale convective systems, and to publish the results within the year.

Research Quality Datasets

NCDC Climate Station Monitoring – A prototype monitoring system utilizing algorithms based on precipitation verification scores will be completed and forwarded to NCDC for installation and testing. Prior to project completion, the scheme will be tested on selected states and on stations with identified historical inhomogeneities. The results of statistical simulations done at NCAR intended to determine the required duration of precipitation analysis periods for different regions of the United States will be applied to the system when completed.

NCEP Gauge Quality Control Project – Software to apply a set of retrospective checks on distributions of key precipitation characteristics (e.g., frequency of hourly and daily precipitation intended to determine, respectively, gauges that stick on or off and observing sites that report only non-zero precipitation amounts) will be completed and forwarded to the Environmental Modeling Center of NCEP for installation. A period of monitoring system performance at FSL (via the RTVS, where the system will also be installed) and at EMC will be instigated prior to final application at EMC. Also during this period, a daily automated procedure to update and collate daily and hourly reporting stations and produce a reduced station list will be written and installed. There are no firm plans for additional improvements to the Real-Time Precipitation Website.

ACARS/AMDAR Quality Control – This system will be fully documented and passed on to a group of programmers at FSL so that there is no single point of failure for the system. Data from additional airlines, will be integrated into the system, and the error characteristics of these data will be investigated.

ACARS-RUC Intercomparison Database – Once an entire year of data have been accumulated, detailed ACARS-RUC statistics will be generated and stratified by season.

North American Radiosonde Dataset – Plans to continue with upgrades to this dataset are pending sufficient funding.

FSL Websites

Chemical Weather Research and Development Website – Development of this Website depends upon new directions taken in the NOAA Chemical Weather program.

National Hourly Precipitation Website – The collaborative project with NCEP to improve rain gauge QC and assess the Stage IV precipitation product involves further improvements to this Website, to be completed over the next year.

ACARS/AMDAR Website – This system will be fully documented and passed on to a group of programmers for several points of failure for the system. Data from additional airlines and additional sensors will be integrated into the system.

Interactive Soundings – This site will continue to be maintained and data flow into it monitored, but it will probably not be upgraded, because the early version Java code used in it is useable on a wider variety of computers that cannot run newer versions of Java. Pending identification of resources, scripts will be written to ease the reloading of past data cases upon request.

National METAR Website – New mesonets will be added as they become available, and data loading will be speeded up. Pending identification of additional resources, wind gust and precipitation amounts will be shown for those sites that support them.

RUC-ACARS Website – Pending identification of resources, this site will be expanded to include additional RUC forecasts longer than 1 hour, such as 3-, 6-, and 12-hour forecasts. Skill statistics will be generated.

PIREPs-AIRMETs Website – This page is designed primarily to provide feedback for forecasters at the Aviation Weather Center. Feedback will be gathered, and future upgrades will be tailored to the forecasters' needs.

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