edu.ucar.opensky::articles:26207 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T19:37:59.830623 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7377dnm https://doi.org/10.17632/gw7c3yjhyp.2 https Related Dataset #1 High Resolution Ensemble Forecasting of Summer Drought in the Western United States with Statistical Models https://doi.org/10.5066/P9PHPK4F https Related Dataset #2 Four-kilometer long-term regional hydroclimate reanalysis over the conterminous United States (CONUS), 1979-2020 https://doi.org/10.5067/0GGPB220EX6A https Related Dataset #3 Daily 4 km Gridded SWE and Snow Depth from Assimilated In-Situ and Modeled Data over the Conterminous US, Version 1 High resolution forecasting of summer drought in the Western United States 2023-03-01T00:00:00Z publication https://n2t.org/ark:/85065/d7377dnm https://doi.org/10.1029/2022WR033734 Abolafia-Rosenzweig, Ronnie author He, Cenlin author Chen, Fei author Ikeda, Kyoko author Schneider, Timothy author Rasmussen, Roy M. author UCAR/NCAR - Library publisher Drought monitoring and forecasting systems are used in the United States (U.S.) to inform drought management decisions. Drought forecasting efforts have often been conducted and evaluated at coarse spatial resolutions (i.e., > 10-km), which miss key local drought information at higher resolutions. Addressing the importance of forecasting drought at high resolutions, this study develops statistical models to evaluate 1- to 3-month lead time predictability of meteorological and agricultural summer drought across the western U.S. at a 4-km resolution. Our high-resolution drought predictions have statistically significant skill (p <= 0.05) across 70%-100% of the western U.S., varying by evaluation metric and lead time. 1- to 3-month lead time drought forecasts accurately represent monitored summer drought spatial patterns during major drought events, the interannual variability of drought area from 1982 to 2020 (r = 0.84-0.93), and drought trends (r = 0.94-0.97). 71% of western U.S summer drought area interannual variability can be explained by cold-season (November-February) climate conditions alone allowing skillful 3-month lead time predictions. Pre-summer drought conditions (represented by drought indices) are the most important predictors for summer drought. Thus, the statistical models developed in this study heavily rely on the autocorrelation of chosen agricultural and meteorological drought indices which estimate land surface moisture memory. Indeed, prediction skill strongly correlates with persistence of drought conditions (r >= 0.73). This study is intended to support future development of operational drought early warning systems that inform drought management. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. None eng geoscientificInformation