The role of land surface feedbacks in drought monitoring and forecasting
Abstract
Drought, a hydrometeorological extreme, causes substantial socio-economic losses globally. Mitigation of the losses can be facilitated by a proactive approach based on real-time drought monitoring and forecasting systems. This invited talk will focus on two ongoing efforts to provide real-time drought monitoring and forecasting (i) over CONUS as part of the North American Land Data Assimilation System (NLDAS) and (ii) over Africa and the Middle East and Central Asia through USAID's Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). Primary focus will be on (i) the role of dynamic vegetation in representing the feedbacks during drought periods over CONUS (ii) the role of precipitation quality and the ability of FLDAS to simulate water availability during long term (hydrological) droughts over Africa.
The talk will also focus on recent efforts at developing a seasonal scale drought forecasting system for Africa and the Middle East. Seasonal drought forecasts derive skill from a combination of initial hydrologic state and seasonal climate forecasts. We use NASA's Land Information System (LIS) to assimilate satellite datasets to provide initial estimates of hydrologic state. These states are then used to generate subseasonal to seasonal scale drought forecasts using LIS and downscaled inputs from NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) climate forecasts. Results suggest that improved land surface initial conditions can extend the value of low-skill precipitation forecasts under certain conditions.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A33M..01P
- Keywords:
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- 0399 General or miscellaneous;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 3399 General or miscellaneous;
- ATMOSPHERIC PROCESSES