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Explore the Data: Drought Indicator Relevance by Region and Season

Explore the Data from This NASA-Led Research

Explore the Data

Map of the regions included in this study.Below, you can view the 15 indicators and timescales with the highest fractional information ("drought explainability" with respect to the U.S. Drought Monitor) from this study for different regions and seasons. 

This NASA-led study analyzed 113 indicators of drought across a variety of timescales (from 1 week to 72 months). Using an information theoretic measure, mutual information, the researchers compared these 113 indicators to U.S. Drought Monitor data from 2006-2019, with results broken down by region and season.

The researchers used historical percentiles for each of the indicators to calculate their mutual information with the U.S. Drought Monitor, then normalized these values to allow comparison across different locations. The resulting normalized mutual information is called fractional information. They used climate division–resolution data to calculate the fractional information for six U.S. regions that largely align with NOAA's Regional Climate Centers: High Plains, Midwest, Northeast, South, Southeast, and West.

Notes for Interpretation

Please note that many indicators were not included in this research, and that there may be overlap in certain indicators (e.g., precipitation, SPI, and SPEI all use precipitation as an input). View a full list of the indicators included in this analysis.

In addition, some regions/seasons may have a shorter or longer list of indicators since each timescale is counted as one indicator (e.g., 3-month vs. 6-month precipitation). In addition, some indicators in the study were calculated using multiple underlying datasets; if the same indicator had high fractional information across multiple datasets, each was counted as a separate indicator (e.g., total column soil moisture from NLDAS-2 Noah and NLDAS-2 Mosaic).

Learn more about this research and how it can be used, read the publication in the Journal of Hydrometeorology, or download a CSV file with all of the regional results.

Indicator *What Is This, and How Do I Use It?Datasets In StudyAdditional Datasets
Total Column Soil MoistureSoil moisture—the amount of water held in the pores of the soil—is a key variable for monitoring drought. Soil moisture can be observed (through monitoring stations), modeled, or remotely sensed and can be measured at a variety of depths.NLDAS-2 Noah (Model-based), NLDAS-2 Mosaic (Model-based), NLDAS-2 VIC (Model-based), NLDAS-2 SAC (Model-based)

NASA Short-term Prediction and Transition Center – Land Information System (SPoRT-LIS) (conditions compared to 1981-2013)

Crop Condition and Soil Moisture Analytics Tool (Crop-CASMA) (compared to 2015–present)

NASA GRACE Data Assimilation (compared to 1948-2012)

NOAA's Climate Prediction Center (compared to 1991-2020)

9-Month, 12-Month Standardized Precipitation Index (SPI)SPI is a drought index that captures how observed precipitation deviates from the climatological average over a given time period. Looking at multiple timescales can show short- and long-term precipitation deficits.NOAA's nClimGrid-Monthly (Observation-based)

NOAA's nClimGrid-Daily

High Plains Regional Climate Center ACIS Maps

Southern Regional Climate Center Integrated Water Portal

Climate Engine (create SPI using different underlying datasets)

9-Month, 12-Month PrecipitationPrecipitation is a key variable for monitoring drought that can be observed, modeled, or remotely sensed. Looking at multiple timescales can show short- and long-term precipitation deficits.NOAA's nClimGrid-Monthly (Observation-based)

NOAA's National Water Prediction Service

NOAA's nClimGrid-Daily

Applied Climate Information System (ACIS)

Gridded Surface Meteorological Dataset (GridMET)

IMERG (Integrated Multi-satellitE Retrievals for GPM)

1-Meter Soil MoistureSoil moisture—the amount of water held in the pores of the soil—is a key variable for monitoring drought. Soil moisture can be observed (through monitoring stations), modeled, or remotely sensed and can be measured at a variety of depths.NLDAS-2 Noah (Model-based), NLDAS-2 VIC (Model-based), NLDAS-2 SAC (Model-based)

NASA Short-term Prediction and Transition Center – Land Information System (SPoRT-LIS) (conditions compared to 1981-2013)

Crop Condition and Soil Moisture Analytics Tool (Crop-CASMA) (compared to 2015–present)

NASA GRACE Data Assimilation (compared to 1948-2012)

NOAA's Climate Prediction Center (compared to 1991-2020)

Palmer Hydrological Drought Index (PHDI)PHDI is a long-term drought index that that incorporates temperature and precipitation data and a physical water balance model to estimate relative dryness. The PHDI was designed to capture hydrological impacts (e.g., water storage, streamflow, and groundwater).NOAA's nClimDiv-Monthly (Observation-based)NOAA Historical Palmer Drought Indices
Palmer Modified Drought Index (PMDI)PMDI is a standardized drought index that incorporates temperature and precipitation data and a physical water balance model to estimate relative dryness.NOAA's nClimDiv-Monthly (Observation-based)

NOAA Historical Palmer Drought Indices

NOAA Estimated PMDI Using Paleoclimate Data

9-Month, 12-Month Standardized Precipitation-Evapotranspiration Index (SPEI)SPEI is a drought index that takes into account both water supply (precipitation) and water demand (potential evapotranspiration, calculated using temperature). Warmer temperatures tend to increase evapotranspiration, which can dry the landscape.NOAA's nClimGrid-Monthly (Observation-based)

NOAA's nClimGrid-Daily

High Plains Regional Climate Center ACIS Maps

Climate Engine (create SPEI using different underlying datasets)

* The indicators were processed to the same time resolution and week definition as the U.S. Drought Monitor (USDM) maps by interpolating when the native resolution is weekly (for week ending-day definitions different from that of a USDM week) or coarser, else accumulating/averaging when it is finer.