Studies of the suitability of drought indices for different applications indicate that a thorough depiction of drought events requires joint analysis of the covariation of multiple indicators such as rainfall, runoff and soil moisture conditions. However, current approaches do not objectively combine separate indicators into an overall assessment of drought for managing water resources and assessing impacts of climate variability. To address this need, we propose to:
– Expand, test and implement a multivariate drought analysis framework for combining multiple drought indicators probabilistically to improve the understanding of drought onset, development and termination. Indicators include precipitation, soil moisture and runoff, which are used in describing multiple drought aspects (meteorological, agricultural, hydrological).
– Assess the proposed multi-index approach as applied to the detection of drought characteristics such as onset, development and termination, and contrast performance with univariate approaches or subjective combinations.
– Diagnose physical underpinnings of variations in multivariate index performance for different droughts, with emphasis on the MAPP Drought Task Force (DTF) case studies. The index responds to covariation in water stress for multiple indices, and thus distinguishes false wet/dry signals by individual drought indicators.
– Use the proposed multivariate multi-index approach to assess 1-9 months drought predictions using seasonal forecast datasets (primarily from CFSv2 and NMME).
– Support the National Integrated Drought Information System (NIDIS) and the United States Drought Monitor (USDM), focusing both nationwide and with emphasis on prediction of severe droughts in the southwestern U.S. and associated decision support.
The proposed project coordinates with the National Drought Mitigation Center and the California Dept. of Water Resources, and with technical linkages to the NOAA/NCEP and the DTF. The proposed work follows the capability assessment protocol introduced by the DTF, and addresses two primary objectives of the MAPP-Drought program: (a) improving methodologies for global to regional-scale analysis and predictions and (b) developing integrated assessment and prediction capabilities relevant to decision makers, and particularly the opportunity to integrate diverse data sources. The project goals also support NOAA’s strategic objectives in the climate area, namely, “to identify causes and effects of [changes in climate variability and their impacts], produce accurate predictions, identify risks and vulnerabilities, and inform decisions”.