What is LERI?
The Landscape Evaporative Response Index (LERI) is an experimental drought-monitoring and early warning guidance tool that measures the anomaly in the actual evapotranspiration (ETa) from the land surface. This webpage provides LERI plots based on accumulated 8-day, monthly, seasonal, growing season, and annual ETa for the contiguous United States and northern Mexico at a 1-km spatial resolution. LERI data are available from January 2000 to the present — a period that corresponds to the availability of MODIS satellite data on which it depends.
ETa is the sum of transpiration from vegetation and evaporation from soil (and water bodies), and is accumulated over a given time period for a given location. The ETa data on which LERI is based are produced by the U. S. Geological Survey using the operational Simplified Surface Energy Balance (SSEBop) model (Senay et al., 2013). SSEBop combines evapotranspiration fraction (i.e., the ability of the land surface to meet the atmospheric demand for water vapor, expressed as a proportion of that demand) generated from remotely sensed MODIS thermal imagery, acquired every 8 days, with climatological atmospheric evaporative demand as represented by reference evapotranspiration derived using the Penman-Montieth formulation and driven by from University of Idaho's Gridded Surface Meteorological Data for that period.
LERI uses a rank-based, non-parametric (Tukey) method to estimate percentiles of the SSEBop ETa data compared to the available period of record (January 2000 to present). LERI percentiles are binned into four drought categories (LD0 - LD3) analogous to the US Drought Monitor (USDM) categories (i.e., D0 - D3) and using the same percentile breaks that USDM considers for soil moisture. LERI does not have an LD4 category (i.e., the 2nd -percentile break) because of the short period of the record.
This webpage provides current and historic (starting Jan 2000) maps of LERI; a time-series tool to generate historical times-series of LERI for a user-defined region; introductions to the LERI team; and a list of resources for users to explore LERI and its applications further.
Why use LERI?
At any given time, LERI provides a high spatial resolution assessment of the landscape evaporative response to land-surface moisture and evaporative demand. It represents the anomalous state of land-surface moisture (i.e., soil moisture) that is readily accessible to plants (for transpiration) and the atmosphere (for evaporation). LERI can complement other drought-monitoring indices, such as SPI, SPEI, PDSI, and EDDI, and modeled soil moisture products. Work is ongoing to evaluate the early warning potential for agricultural and ecological droughts, flash drought and wildfire risk.
How often is LERI updated?
The LERI plots and data are kept updated to the latest completed week.
This work is supported in part by grant(s) from (i) DOI's North Central Climate Science Center for the project (Grant # G17AP00096) titled "Evaporative Demand, Drought Monitoring and Assessment Across Timescales."
Any issues with accessing the plots and other information on this page are welcome and should be sent to firstname.lastname@example.org. Any issues or questions related to the content on these pages are welcome and should be sent to email@example.com.
LERI Project Team
Imtiaz Rangwala • firstname.lastname@example.org • 303-497-6544Imtiaz is a research scientist at CIRES at the University of Colorado Boulder and works closely with NOAA's Physical Sciences Division. He is a climate scientist with training in assessing and diagnosing regional scale climate change. Using climate observations and models, he works to understand and quantify climate processes relevant to regional warming trends and hydrological processes changes. This specifically ties into understanding climate extremes and changes in water balance in the western U.S., including the Great Plains region, and the how these extremes affect ecosystem response. Other work includes developing approaches to addressing and incorporating future climate change uncertainty into decision making and climate adaptation.
Joe Barsugli • email@example.com • 303-497-6042Joe is a Research Scientist at CIRES and NOAA's Physical Sciences Division. Trained in climate theory and modeling, he works at the technical interface connecting climate science with the practitioners and technical staff who are informing planning for water and land management in the Colorado region, and connecting researchers to the problems faced by managers.
Lesley L. Smith • firstname.lastname@example.org • 303-497-6172Lesley is a research associate at CIRES at the University of Colorado Boulder and NOAA's Physical Sciences Division. Her research interests include drought, climate diagnostics and variability on seasonal to centennial time scales, ENSO impacts, attribution of weather and climate-related extremes.
Gabriel Senay • email@example.com • 605-594-2758Gabriel Senay is a Research Physical Scientist with the U.S. Geological Survey Earth Resources Observation and Science (USGS EROS) Center. Senay is co-located with the North Central Climate Science Center in Fort Collins, Colorado and is a faculty affiliate with the Ecosystem Science and Sustainability, Colorado State University. He conducts applied research on water use and availability assessment and drought monitoring using satellite-derived data and hydrologic modeling. His research contributes to the development and dissemination of a suite of drought monitoring and early warning products through the Famine Early Warning Systems Network (FEWS NET) for Africa, Central America, and parts of Asia (https://earlywarning.usgs.gov/fews). Similarly, through the USGS Water Census program, he works on the estimation and mapping of landscape water use dynamics and trends for the United States.
Mike Hobbins • firstname.lastname@example.org • 303-497-3092Since obtaining his Ph.D. in Hydrologic Science and Engineering from Colorado State University in 2004, Mike has worked in research into evapotranspiration, evaporative demand, and drought. As a Research Scientist for NOAA's Physical Sciences Division and the Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado in Boulder, CO, his recent work supports drought early warning across the US for the National Integrated Drought Information Systems (NIDIS) and famine early warning across the globe for the Famine Early Warning Systems Network (FEWS NET), including the development and dissemination of reanalyses of evaporative demand; the development of the Forecast Reference Evapotranspiration (FRET) product for daily and weekly evaporative demand forecasts across the US; and the development of the LERI.
Stefanie Kagone • email@example.com • 605-594-2862Stefanie is a Geospatial Information Scientist as a contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, SD. She supports the efforts of the USGS Famine Early Warning Systems Network (FEWS NET) and WaterSMART projects, including the development and dissemination of satellite-derived multi-scale SSEBop evapotranspiration products for early warning purposes. Her research interests include applied hydrology, GIS, ET modeling, virtual water, and remote sensing.
- LERI Data and Maps (FTP)
- LERI Poster — Presented at CPASW 2018 (May 23, 2018)
- US SSEBop Evapotranspiration Maps and Data
- Drought monitoring and Impact Assessment Using Satellite-derived Evapotranspiration
- Savoca, M.E., Senay, G.B., Maupin, M.A., Kenny, J.F., and Perry, C.A., 2013, Actual evapotranspiration modeling using the operational Simplified Surface Energy Balance (SSEBop) approach: U.S. Geological Survey Scientific Investigations Report 2013-5126, 16 p., http://pubs.usgs.gov/sir/2013/5126.
- Senay, Gabriel B., Stefanie Bohms, Ramesh K. Singh, Prasanna H. Gowda, Naga M. Velpuri, Henok Alemu, James P. Verdin, 2013b. Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: A New Parameterization for the SSEB Approach. Journal of the American Water Resources Association (JAWRA). 49(3):577-591. http://onlinelibrary.wiley.com/doi/10.1111/jawr.12057/full