Documentation

1. Overview of Methods and Data

Calculating Drought Indices

This tool evaluates drought severity by analyzing hydroclimate observations (such as precipitation, evapotranspiration, and soil moisture). A statistical distribution is fit to these observations over a specific "reference period"—typically a 30-year span. We then estimate the probability of accumulated precipitation (or moisture deficits) for a given time period based on that fitted distribution.

Addressing a Non-Stationary Climate

Non-stationarity broadly describes a changing of a region's hydrometeorological distribution, which can be caused by trends in the climate system such as rising temperatures, changing evaporative demand, or changing precipitation. This tool is designed to allow users to explore how a non-stationary climate impacts currently implemented metrics for estimating drought severity.

By allowing the selection of different reference periods, the tool demonstrates how these baselines alter our perspective on the severity and extent of a drought. Users can view drought conditions across the CONUS domain relative to two reference periods: the Period of Record (1951–2023) and the Climate Normal (1990–2020).

Supported Indices

The tool currently allows users to explore three standardized indices:

• SPI (Standardized Precipitation Index)
• SPEI (Standardized Precipitation-Evapotranspiration Index)
• SSMI (Standardized Soil Moisture Index)

Methods for calculating these indices are derived from:

• World Meteorological Organization, 2012: Standardized Precipitation Index User Guide (M. Svoboda, M. Hayes and D. Wood). (WMO-No. 1090), Geneva. View Guide
• Vicente-Serrano et al., 2010. DOI: 10.1175/2009JCLI2909.1
• AghaKouchak, A., 2013. DOI: 10.1016/j.advwatres.2013.03.009

Differences Maps

The main dashboard provides two maps to compare indices estimated using alternate reference periods:

• Continuous Difference Map: Displays the continuous difference between the values of the indices. This provides perspective on the magnitude of the difference in the estimated likelihood of the drought event in normalized space.
• Drought Monitor Category Difference: Displays categorical differences estimated using guidance from the Drought Monitor classification system. This highlights how differently the exact same conditions would be classified and communicated from a national drought monitoring perspective depending on the chosen baseline.

Dataset Information

ERA5-Land dataset variables act as the primary inputs for estimating the SPI, SPEI, and SSMI. Hourly fluxes are converted into monthly frequencies (precipitation and evapotranspiration are summed; soil moisture is averaged) to calculate the 1, 2, 3, 6, and 12-month drought conditions.

Evapotranspiration was estimated using the FAO-56 Penman-Monteith approach utilizing tools from the PET GitHub repository. Multiple layers of soil moisture were used to estimate the weighted average of the 1-meter depth soil moisture content to calculate the SSMI.

2. Resources & Code Repositories

• Input Data ERA5-Land (Copernicus Climate Data Store)
• Drought Resources Drought.gov | U.S. Drought Monitor
• Index Calculation Scripts Python Analysis Scripts (Placeholder Link) | Adapted from the Climate Indices for Drought Monitoring Toolbox.
• Partners Western Water Assessment

3. Contact & Acknowledgements

Acknowledgements

Thank you to the National Centers for Environmental Information for supporting the assessment of the impacts of non-stationarity on drought and the generation of this tool. This work was supported by NOAA/NCEI Grant# NA22OAR4320151 - Drought products that address non-stationarity.

Thank you to the Western Water Assessment team and the network of drought experts who helped advise in the development of this tool, with express thanks to Elizabeth Payton, Matthew Sabin, Ben Livneh, and Benet Duncan for their efforts on this project.