Understanding the Role of Water Vapor Transport Anomalies in Asian and African Monsoon Droughts Using New Satellite Observations
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1 Understanding the Role of Water Vapor Transport Anomalies in Asian and African Monsoon Droughts Using New Satellite Observations Chris Funk, USGS EROS, UCSB CHG NASA PMM meeting, Salt Lake City, Oct
2 UCSB/USGS/NASA Collaboration & the USAID Famine Early Warning System Network An elderly woman is given water in the Turkana region of Kenya. Many of the elderly are too weak and sick to feed themselves or drink. NYT Oct The aid community in Kenya has been predicting a disaster for months, saying this could be the worst drought in more than a decade.
3 Integrated Drought Monitoring? History QPE Seasonal Prediction Decadal Prediction Moisture Transports
4 Monitoring and assessing El Niño s possible food security impacts House Foreign Affairs Committee October 2, 2009 Gary Eilerts, USAID FEWS NET 4
5 So, how should we plan for El Niño in the Horn of Africa? Plan for a bigger problem. Rains have already been poor in most of 2009 Poor rains, March May 2009 Poor rains, June July Source: USGS EWX
6 So, how should we plan for El Niño in the Horn of Africa? Understanding that it s not only El Niño; climate change is also present Last 4 rainy seasons are worst since Main season rainfall decreasing, while second season is increasing Almost 20% drop in main season rainfall since 1980 C. Funk/USGS Real-time Decision Support Systems: The Famine Early Warning System Network Chapter 17 for: Satellite Rainfall Applications for Surface Hydrology, by Springer-Verlag
7 So, how should we plan for El Niño in the Horn of Africa? Looking at all info; in any year, a warmer Indian Ocean may impede rains C. Funk/USGS
8 ocean warming also contributes to drier main seasons in Southern Africa A warming Indian Ocean threatens Eastern and Southern Africa, Proceeding of the Nat. Academy of Science, 2008 C. Funk/USGS
9 So, how should we plan for El Niño in the Horn of Africa? Even more concern as anomalous rainfall IS ALREADY occuring USGS and NASA CauKon: Might El Niño instead bring a poor season to the Horn?
10 Water Vapor Transports Anomalies Account for a large fraction of the anomalous energy transports in the tropics Conv(Moist Static Energy) Changes in moist entropy in PBL Transport Water Persist Predictability Comprehension Can help us understand decadal variability
11 Indian Ocean Monsoonal Circulation Summer Winter Eq High Pressure Low Pressure
12 Indian Ocean Monsoonal Walker Circulation Walker Cell 90E 120E High Pressure No Rain Low Pressure Heavy Rain
13 Seasonal Rainfall and Moisture Transports: JFM Data: The Passive Microwave Water Cycle Product, Hillburn, Remote Sensing Systems high pressure low pressure
14 Seasonal Rainfall and Moisture Transports: AMJ Data: The Passive Microwave Water Cycle Product, Hillburn, REMSS low pressure high pressure trough trough
15 Seasonal Rainfall and Moisture Transports: JAS Data: The Passive Microwave Water Cycle Product, Hillburn, REMSS low pressure high pressure
16 Seasonal Rainfall and Moisture Transports: OND Data: The Passive Microwave Water Cycle Product, Hillburn, REMSS low pressure high pressure
17 Seasonal Differences: JFM and AMJ low pressure high pressure
18 Correlation with Kenya AMJ Rainfall
19 EOF1 of AMJ Precipitation and Transports
20 Time series of Kenyan October-November forecasts and observations 4 Kenyan Oct November rainfall Kme series 3 Oct Nov Rainfall Index [sigma] Cross validated Forecasts Eth Oct Nov Rainfall Index Fcast 1 Standard Error Fcast +1 Standard Error normal forecast 3
21 Correlation with JAS Indian Rainfall Northward Transports Indian Rainfall
22 Warming Indian/Pacific Oceans linked to drought? Science, 2008 (CMIP3 TS) T B(obs) Indian Ocean + Western Pacific SST Anomalies
23 Thanks! Moisture transport anomalies appear linked to the seasonal Indian Ocean monsoon cycle For Kenya AMJ Low at equator drives NH easterlies, increases rainfall Opposite seasonality For India JAS High at equator drives NH westerlies, increases rainfall Similar to seasonality Results may lead to better predicatibility Integrated DSS Historic Obs + RT QPE + forecasts + decadal variability analysis
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