- Improved accuracy in the monitoring of ongoing drought conditions
- Better predictions to prepare for the development of drought conditions
- Further understanding of drought causes and behavior
Research to meet these needs:
- Accurate soil moisture data, useful for understanding monitoring, and for modeling drought
- Examination of computer model biases and understanding the role and influence of model input from the North American Land Data Assimilation System
- Utilizing data from satellites to improve drought modeling and understanding
- Harnessing model predictions of precipitation to improve indices that describe drought
- Utilizing multiple independent computer models to further improve seasonal and sub-seasonal drought prediction
Having the capacity to monitor droughts in near real time and to provide accurate drought prediction from weeks to seasons can greatly reduce the severity of social and economic damage caused by drought. Drought indices are used to monitor and predict many aspects of drought. For meteorological drought (lack of precipitation), the Standardized Precipitation Indices (SPI) have been recommended for use. Soil moisture (SM) levels are used as indicators of agricultural drought (lack of water impacting agricultural productivity). Runoff or streamflow anomalies are used to monitor hydrological drought (lack of water supply). The official U.S. Drought Monitor and the Seasonal Drought Outlook are the leading operational national drought products, and are major contributors to the National Integrated Drought Information System (NIDIS). The Drought Monitor, Seasonal Drought Outlook, and NIDIS integrate a diverse set of drought indicators from numerous sources. To support this integration, NOAA-funded research is targeted to improving drought monitoring and prediction systems, resulting in improvements in the U.S. Drought Monitor, Drought Outlook, and NIDIS capabilities. For example, NOAA's National Centers for Environmental Prediction (NCEP) Climate Prediction Center (CPC) issues several operational drought monitoring and prediction products, many of which are used in the preparation of the U.S. Drought Monitor and Drought Outlook as well as to inform NIDIS. NCEP's Climate Test Bed (CTB) is a mechanism that aims at accelerating advances in NCEP's drought operational products. Advances in drought monitoring and prediction systems are sought as the result of MAPP grant-funded collaborative research projects involving academia, NOAA research laboratories and other research labs, as part of the Drought Task Force research efforts. A few examples of how NOAA MAPP research investments are delivering improved drought operational products are given below.
A. Advances in Drought Monitoring (click here for more info) --- Content provided by Kingtse Mo, NCEP/CPC ---
a. Developing the North American Land Data Assimilation System for drought monitoring
b. Advancing drought monitoring using remote sensed data
B. Drought Prediction (click here for more info)
a. Drought prediction based on forecasted Standardized Precipitation Indices
b. National Multi-Model Prediction Experiment for drought prediction.