1 / 28

Custom Seasonal Forecasts for The Eastern Horn

Custom Seasonal Forecasts for The Eastern Horn. Chris Funk & Gideon Galu. Context: In Jan 2011 FEWS NET issued an accurate projection of food insecurity if the long rains failed, how predictable might the long rains be?.

stuart
Télécharger la présentation

Custom Seasonal Forecasts for The Eastern Horn

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Custom Seasonal Forecasts for The Eastern Horn Chris Funk & Gideon Galu

  2. Context: In Jan 2011 FEWS NET issuedan accurate projection of food insecurity if the long rains failed, how predictable might the long rains be?

  3. This study analyzes January and MAM climate fields for 8 recent drought years Outlier MAM SPI time-series for high-risk region in southern Ethiopia, central-eastern Kenya and Southern Somalia. Boxes show drought years (those with SPI <-0.5). While 1992 was an outlier, all the other years exhibited similar SST gradients, and large scale atmospheric responses. Data: GPCP topped with RFE2 for 2011

  4. Modeling Experiment – Lyon & DeWitt Multi-model ensemble mean (72 members) MAM RR anomaly (mm/day) from simulations using observed SSTs, averaged over 1999-2009. SST Anomalies used to drive the model Side shows research by Bradfield Lyon (IRI) presented by TufaDinku (IRI) at the CRAM3

  5. MERRA MAM SST Z-scores Brown = Hot Blue =Cold While the positions vary, in all dry seasons, an SST gradient existed across the western-central Pacific. The role of the Indian Ocean is less clear. MAM climate seems similar to January climate in the Pacific, supporting prediction.

  6. 1984 Wet Wet Warm

  7. 2000 Wet Wet Warm

  8. 2004 Warm Wet Wet 2004 seems more influenced by Indian Ocean Dipole

  9. 2007 Wet Wet Warm

  10. 2008 Wet Wet Warm

  11. 2009 Wet Wet Warm

  12. 2011 Warm Wet Wet

  13. Wet, Dry and Normal Year SST transects Key Points : 1) Note that SST relationship across the Pac is uncorrelated, wet and dry years cool! 2) Nonetheless, 7 of 8 dry years have SST gradient 3) Even with low grid cell correlations, the GFS might capture the impact of the SST gradients

  14. Fig. 3 Transects forwet, dry and normal seasons A. Standardized equatorial (-20S to 20N) SST transects for dry, wet, and normal eastern equatorial east African MAM rainy seasons. Shading along the bottom shows the average terrain elevation. B. Similar transects for vertically integrated air temperatures. C and D - transects of zonal and vertical wind speeds at several vertical levels for dry and wet years. E-G - Transects of vertically integrated moisture transports, total precipitable water, precipitation and evaporation.

  15. MAM SLP and surface wind anomalies for dry years

  16. Rainfall Anomalies Jan 1 – Feb 11 2012

  17. Reanalysis Jan/Feb Temp Anomalies

  18. March 2012 SPI and Population

  19. March 2011 NDVI Anomalies

  20. SST based Analog Analysis

  21. CCA(Forecast SSTs MAM) Figure x. Relative forecast probabilities of below normal rainfall, based on ECHAM4.5 and CCM3.6 models driven with forecast sea surface temperatures. The probability of below normal rainfall in 2012 appears broadly similar to these analog years. Analysis provided by Bradfield Lyon, International Research Institute for Climate and Society.

  22. Analog years analysis for April & May Chris Funk: 2000, 2008 & 2011 KMD: 2001 & 2009 Key messages: Consistent observations of increased likelihood for poor rainfall performance over northern and central Tanzania, southern, central, eastern and northern Kenya, together with Somali and Afar regions of Ethiopia (<75% of normal) . Emerging areas of concern in Rwanda and Burundi during the months of April and May, with mixed rainfall performance likely in south and central Somalia.

  23. Analog years analysis for Maize WRSI/EoS 2011 2008 2000 Key messages: Increased likelihood (80% chance ) for crop failure in SE and coastal strip of Kenya, S. Somalia and N. Tanzania. 100% likelihood for near normal cropping conditions for key agric areas of Kenya and Uganda. About 60% likelihood for normal cropping conditions in Rwanda and Burundi. Mixed crop performance for Meher/Belg cropping areas despite delayed onset(?) 2001 2009

  24. Analog years analysis for Rangelands WRSI/EoS 2011 2008 2000 2001 2009 Key messages: Mixed performance in rangeland conditions in the region, due to expected poor rainfall distribution in space and time over the key pastoral areas. Increased likelihood for poor rangeland conditions over N. and S. Kenya, Somali region of Ethiopia and parts of Somaliland, Djibouti and S. Eritrea.

  25. Forecast Communication

  26. Kenya 2012 – Food Security Outlook Rainfall anomalies based on KMD Analogs (2001,2009)

  27. Proposed Climate Projection/Forecast System Winds Rainfall Temperature Observed & predicted SSTs Climate Models Hoerling/Hurrel Decadal SST predictions PET z ObsRainfallTS CA CCA MFR ... T z PETobsm,s Additional (Filtered CMIP5)SST predictions GHGs Tobsm,s FutureRainfallTS Probs Future TempTS Probs Future PETTS Probs SPI FLDAS WRSI

  28. Thursday A.M. Forecasting Discussion • Presentations • W. Thiaw - 30 minutes • M. Hoerling/Brant Liebmann – 30 minutes • J. Michaelsen – 15 minutes • G. Husak – 15 minutes • C. Funk – 15 minutes • Discussion Topics • Monthly FEWS NET climate telecon? • Integrated FEWS NET monitoring/forecast system?

More Related