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An Objective Seasonal Drought Outlook for the Conterminous United States

The goal of this proposal is to develop an objective drought seasonal outlook (ODSO) over
the Conterminous United States (CONUS) for agricultural and hydrological users. The ODSO
will utilize both statistical and dynamical forecasts, and will include estimates of their
uncertainties. The idea is that forecasters can use the ODSO as their ‘first guess’ for the NOAA
Drought Outlook. The proposed project will advance CPC/NOAA operational capabilities for
prediction of drought by incorporating the results of past NOAA/MAPP-funded (and other)
drought research. To achieve our goal, we plan (1) to better understand drought evolution from

onset to demise based on observations of precipitation (P) and temperature (Tair), and model-
reconstructed soil moisture (SM), snow water equivalent (SWE, where applicable),

evapotranspiration (ET) and runoff (RO) using a suite of land surface models (LSMs) that
comprise an updated NLDAS system from 1916-near present; (2) to examine forcings
associated with drought and to test statistical tools such as ensemble canonical correlation
analysis (ECCA) for forecasting of drought indices; (3) to evaluate the ability of an ensemble of
global forecast and land surface models (GCM_LSM) to predict drought development by
diagnosing sources of model errors, with global forecasts taken from the North American Multi
Model Ensemble (NMME) archive, (4) to utilize the ECCA to optimally combine statistical
forecasts and error-corrected dynamical forecasts into an ODSO. The proposed work will
directly contribute to the MAPP objectives of advancing drought understanding and prediction.
The proposed research will also contribute to the NIDIS objectives of (1) improving drought
prediction skill and (2) improving drought information systems. The PI and co-PI will continue
to contribute to NOAA’s Drought Task Force (DTF) research to better understand the physical
mechanisms and advance the ability to predict various aspects of drought including onset,
duration and recovery. The work we propose will be readily transferrable to operations, and in
fact we propose to implement a prototype system at CPC that will draw from the operational
North American Land Data Assimilation System (NLDAS) and will produce information for
CPC Drought Outlook forecasters in near real-time. The TRL level of the proposed project is
TR5 (System/subsystem/component validation in relevant environment).

Climate Risk Area: Water Resources

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