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PACJET Projects
HMT 2004
PACJET 2003
PACJET 2002
PACJET 2001
CALJET 1998
Resources
GPS Realtime Water Vapor
GWINDEX
West Coast RUC
ETL Profiler Network
Press Materials
Background
About Pacjet
CALJET Summary
Societal Impacts and User Input
Linkages to National Priorities
USWRP
  Data Assimilation Implementation Plan
March 2001 Program Status Report
PACJET 2001 Poster NSSL Briefing
Program Documents
PACJET and a Long-term Effort to Improve 0-24 h West Coast Forecasts
Overview Poster
Research Participants
NOAA Research
  ETL,   NSSL,   FSL,   AL,   CDC
National Weather Service Western Region
  Eureka,   Hanford,   Medford,   Monterey,   Oxnard,   Portland,   Reno,   Sacramento,   San Diego,   Seattle,   CNFRC
Office of Marine and Aviation Operations
  AOC
Naval Postgradute School
DRI CIASTA
CIRES
SUNY Stony Brook
National Centers for Environmental Prediction
  EMC,   HPC,   MPC
National Environmental Satellite, Data and Information Service
  CIMSS,   CIRA
Operational Forecasting Components
COMET Presentation
West Coast RUC Aircraft Obs via AWIPS
GWINDEX Poster
Applications Development
Research Components
Modeling Research Components
Related Experiments
Winter Storm Reconnaissance (Central Pac.)
CRPAQS (CA Air Quality)
IMPROVE (Microphysics)
THORPEX (Synoptic Targeting)
Observing Systems
AEROSONDE
NOAA P-3
Wind Profiler Network
Satellite Products
NOAA S-band Radar
Contacts
Program
Media Contacts
Webmaster
Workshops
2001 - Monterey, CA
July 13-14 2000 (Boulder, CO)
July Workshop Agenda
September 1999 - Monterey, CA
1999 Planning Workshop Figures
June 1998 - CALJET

OPERATIONAL APPLICATIONS DEVELOPMENT

Real-time Assimilation of Experimental Data

Real-time assimilation of experimental data for operational NWP, such as an operational global scale model (MRF) and an experimental version of the RUC. For more information and program data see http://maps.fsl.noaa.gov/pacjet_am.cgi.

Extended RUC domain
Extended RUC Domain

Forecast Tools

PACJET will aid in the creation of forecast tools centering around new instruments and observing strategies. Data dissemination pathways will be developed for visual and quantitative experimental data. Visualization products will be designed for optimal use of data for specific forecast problems. Alerts will be sent to forecast offices indicating that experimental data will be available. Real-time verification tools will be developed around special PACJET observations.

Real-time GOES winds

Specialized GOES wind products based on a feature tracking technique were produced by CIMSS as part of the CALJET experiment in 1998. A unique component of this data set is the availability of super-rapid-scan (1-min sampling) GOES images. These data were used to assess the impact of shortening the time between images used in feature tracking. Standard approaches used 30-min between samples, but tests in tropical storms had suggested more frequent sampling could improve areal coverage in regions where cloud features had a shorter lifetime than 30 min. The figures shown here represent the results of this test using a 5-min lag between images for both IR and visible channels. These are compared to results using 30 min lag, and confirm that the areal data coverage increases significantly. Using statistical internal consistency checks it was determined that the optimal time lag was about 5-min. Wind vectors calculated using shorter lags had higher internal variance that resulted from the increased influence of satellite pointing uncertainty as the distance between features decreased, i.e., with shorter time lags. Based on these results, a new GOES scan pattern is being developed that should provide a set of 3 consecutive 5-minute interval images, once every hour around the clock during PACJET over the domain shown here. In addition to the GOES wind products, GOES sounder moisture products (total precipitable water vapor, and cloud-top pressure) will be available at 3-hourly intervals.

Monitoring Impact

The impact of experimental data on NWP and on issuance of warnings will be assessed. Forecasters and key forecast users will be trained on new data and concepts before PACJET. The direct use of new data by forecasters and users will be tracked during the experiment.
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