About
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.
Acknowledgements
The development of LERI was supported in part by the grant from DOI's North Central Climate Adaptation Science Center (NC CASC) for the project (Grant # G17AP00096) titled "Evaporative Demand, Drought Monitoring and Assessment Across Timescales." The continued development and maintenance of LERI is managed through a joint collaboration effort between NOAA PSL and NC CASC.
Any issues with accessing the plots and other information on this page are welcome and should be sent to psl.data@noaa.gov. Any issues or questions related to the content on these pages are welcome and should be sent to mike.hobbins@noaa.gov.
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LERI Maps (Monthly)
Description of Maps and Underlying Data
The Landscape Evaporative Response Index (LERI) maps archived here show anomalies in the actual evapotranspiration from the land-surface (ETa, which is the sum of transpiration from vegetation and evaporation from soil and water bodies) at a 1-km spatial resolution for a particular period of accumulation (1 month, 3 months, growing season {April-October}, and the calendar and water years) between January 2000 and the present.
At any given time, LERI maps signify the relative evaporative response of a landscape as a result of the state of land-surface moisture (i.e., soil moisture) that is readily accessible to plants (for transpiration) and the atmosphere (for evaporation). Hence, it works as a remotely observed proxy for anomalies in the upper layers of soil moisture. The different map colors indicate the frequency at which the observed ETa anomaly has occurred in the period of record, with warm colors indicating land-surface moisture conditions that are drier than normal, and cool colors wetter than normal. For drier-than-normal categories (i.e., LD0-LD3), the binning is analogous to the US Drought Monitor (USDM) categories (i.e., D0-D3) using the same percentile breaks that USDM considers for soil moisture. For example, the LD3 category indicates that the ETa anomaly has only been observed less than 5% of the time for the period of interest between year 2000 and the present, which represents the most severe drought conditions based on the period of record (2000-present). Caution should be exercised in the interpretation of the LD categories as drought because the LERI percentiles are based on a relatively short period of record, and only represent the anomalous dryness or wetness for that period.
The data underlying these maps is the actual evapotranspiration (ETa) data estimated using the operational Simplified Surface Energy Balance (SSEBop) model that incorporates remotely sensed MODIS thermal imagery and climatological reference evapotranspiration based on the methodology described in Senay et al., 2013. For a given time period of accumulation, LERI is calculated by computing percentiles in SSEBop ETa data using a rank-based, non-parametric (Tukey) method.
LERI data (in NetCDF) and maps can also be accessed here.
Please contact Mike.Hobbins@noaa.gov for technical questions about LERI maps.
This is a Research and Development Application
LERI Maps (8-day)
Description of Maps and Underlying Data
The Landscape Evaporative Response Index (LERI) maps archived here show anomalies in the actual evapotranspiration from the land-surface (ETa, which is the sum of transpiration from vegetation and evaporation from soil and water bodies) at a 1-km spatial resolution for both discrete and accumulated 8-day periods during the growing season (April-October) between 2000 and the present.
At any given time, LERI maps signify the relative evaporative response of a landscape as a result of the state of land-surface moisture (i.e., soil moisture) that is readily accessible to plants (for transpiration) and the atmosphere (for evaporation). Hence, it works as a remotely observed proxy for anomalies in the upper layers of soil moisture. The different map colors indicate the frequency at which the observed ETa anomaly has occurred in the period of record, with warm colors indicating land-surface moisture conditions that are drier than normal, and cool colors wetter than normal. For drier-than-normal categories (i.e., LD0-LD3), the binning is analogous to the US Drought Monitor (USDM) categories (i.e., D0-D3) using the same percentile breaks that USDM considers for soil moisture. For example, the LD3 category indicates that the ETa anomaly has only been observed less than 5% of the time for the period of interest between year 2000 and the present, which represents the most severe drought conditions based on the period of record (2000-present). Caution should be exercised in the interpretation of the LD categories as drought because the LERI percentiles are based on a relatively short period of record, and only represent the anomalous dryness or wetness for that period.
The data underlying these maps is the actual evapotranspiration (ETa) data estimated using the operational Simplified Surface Energy Balance (SSEBop) model that incorporates remotely sensed MODIS thermal imagery and climatological reference evapotranspiration based on the methodology described in Senay et al., 2013. For a given time period of accumulation, LERI is calculated by computing percentiles in SSEBop ETa data using a rank-based, non-parametric (Tukey) method.
LERI data (in NetCDF) and maps can also be accessed here.
Please contact Mike.Hobbins@noaa.gov for technical questions about LERI maps.
This is a Research and Development Application
Plot LERI Time Series
Description of Time-Series Data and Plot
This page generates the LERI time-series using monthly actual evapotranspiration data from January 2000 to latest complete year, across a user-selected region and timescale. You can select your region as a rectangular area by directly entering latitude and longitude values or by selecting the area in the adjacent map. The main output is a table with LERI time series for timescales of 1 to 12 months. A plot will also be generated with user- (or default-) entered month and averaging period, which will accompany another table showing the time-series data with user-defined specifications. On the output page, you will have an option to readily replot LERI time series with different specifications.
At any given time, there can be large spatial variability in LERI. For generating these time series for meaningful assessment, we generally recommend that users select as small an area as possible (e.g., county, climate division, small watersheds), including point locations (i.e., by using a single latitude value in both the N and S boxes, and a single longitude value in both E and W boxes for bounding the region, thereby getting the time series for just a single representative 1km x 1km pixel). The time-series tool does not accept a region with area greater than 4° lat x 7° lon.
The main output table also includes the actual evapotranspiration value (in mm) for each month used to calculate LERI. The absolute values of the actual evapotranspiration are highest during the warm season, during which there is also a heightened risk of water stress on the land surfaces. For drought-related impacts, users can use time series of different LERI timescales to compare with their own historical impacts data.
For further assistance or technical advice on the use of these timeseries data for research applications please contact Imtiaz.Rangwala@colorado.edu and Mike.Hobbins@noaa.gov.
This is a Research and Development Application
LERI Project Team
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Imtiaz Rangwala • imtiaz.rangwala@colorado.edu • 732-277-8231Imtiaz is a research scientist at CIRES at the University of Colorado Boulder and works closely with NOAA's Physical Sciences Laboratory. 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. |
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Mike Hobbins • mike.hobbins@noaa.gov • 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 Laboratory 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. |
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Gabriel Senay • senay@usgs.gov • 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. |
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Lesley Smith • lesley.l.smith@colorado.edu • 303-497-6172Lesley Smith is a physicist with the University of Colorado's Cooperative Institute for Research in Environmental Sciences and NOAA's Earth System Research Lab Physical Science Division. |
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Joe Barsugli • joeseph.barsugli@noaa.gov • 303-497-6042Joe is a Research Scientist at CIRES and NOAA's Physical Sciences Laboratory. 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. |
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Stefanie Kagone • skagone@contractor.usgs.gov • 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. |
Resources
Links
- LERI Data and Maps
- LERI Poster — Presented at CPASW 2018 (May 23, 2018)
- LERI Slides — Presentation to the NIDIS staff (September 24, 2018)
- US SSEBop Evapotranspiration Maps and Data
- Drought monitoring and Impact Assessment Using Satellite-derived Evapotranspiration
- R-utility to extract LERI data
References
- Rangwala, I., Smith, L.L., Senay, G., Barsugli, J., Kagone, S., and Hobbins, M. (2019). Landscape Evaporative Response Index (LERI): A high resolution monitoring and assessment of evapotranspiration across the Contiguous United States. U.S. Geological Survey ScienceBase, https://doi.org/10.21429/43r4-3q68.
- 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