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Predictability of the Moisture Regime During the Pre-onset Period of Sahelian Rains

Predictability of the Moisture Regime During the Pre-onset Period of Sahelian Rains. Robert J. Mera Marine, Earth and Atmospheric Sciences North Carolina State University Seminar, April 3rd 2009. Motivation. Why is the moisture regime important?. Prediction of Monsoon rainfall.

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Predictability of the Moisture Regime During the Pre-onset Period of Sahelian Rains

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  1. Predictability of the Moisture Regime During the Pre-onset Period of Sahelian Rains Robert J. Mera Marine, Earth and Atmospheric Sciences North Carolina State University Seminar, April 3rd 2009

  2. Motivation • Why is the moisture regime important? Prediction of Monsoon rainfall African Easterly Waves Agriculture Public health: Meningitis Outbreaks

  3. Outline • The Application • Background • Health-climate link • Our Study • Importance of Downscaling • Predictability of Pre-onset Conditions • Ensemble Prediction and Evaluation of Model Skill

  4. The Application • Meningitis is a serious infectious disease affecting 21 countries • 300 million people at risk across the Sahel • 700,000 cases in the past 10 years • 10-50 % fatality rate • 256,000 people lost to the disease in 1996 SAHEL

  5. Meningitis-Climate link • Outbreaks coincide with dry, dusty conditions over the Sahel due to the Harmattan winds flowing south from the Sahara (Jan-May) • Largest correlation occurs between low humidity and disease outbreaks (Molesworth et al., 2006) • Disease occurrence drops dramatically with the onset of humidity SH SHL Harmattan ITCZ Moisture ITCZ January July

  6. Meningitis-Climate link • The most actionable case involves the link between humidity onset and cessation of disease 1998 2004 Pink: # of cases Orange: Relative Humidity (%)

  7. Current Efforts • University Corporation for Atmospheric Research (UCAR) and the Google Foundation are funding efforts to explore climate-meningitis dynamics • Global scale models will be employed for operational purposes

  8. Our study: Importance of Downscaling 65 60 55 50 45 40 35 Ghana Ghana 30 25 20 WRF at 30km resolution NCEP/NCAR Reanalysis at 2.5° Relative Humidity (%)

  9. The Scientific Question: Predictability of Moisture • What are the dynamics governing the northward progression of the moisture regime? • How well does the model represent the physical processes? • What is the skill of the model in predicting the dynamics and statistics of the physical processes?

  10. In the literature • The West Africa summer monsoon is characterized by two steps: preonset and onset(Sultan and Janicot, 2003) • The preonset stage corresponds to the arrival of the Inter Tropical Front (ITF) at 15°N ITF Rain (mm/day) From Sultan and Janicot (2003)

  11. Schematic Cross Section of the West African Monsoon 200 hPa Deep moist convection AEJ 600 hPa Deep dry convection 1000 hPa 10 N 20 N Equator ITCZ Sahel Sahara Slide from John Marsham, U. of Leeds

  12. Our Study • The northward progression of moisture is related to the preonset stage of the monsoon and the position of the ITF • Two important factors at work: • Interannual variability is dictated by fluxes in sea surface temperatures (SST), interaction with mid-latitude systems (teleconnections) • Intraseasonal variability is related to east-west transient disturbances, African Easterly Jet

  13. Data and Methods • NCEP/NCAR, ECMWF Reanalysis, In-situ observations & satellite data: Statistics of Relative Humidity, etc • We use the Advanced Research WRF (WRF-ARW) Model for downscaling of reanalysis and operational forecasts, sensitivity analyses *NCEP: National Centers for Environmental Prediction *NCAR: National Center for Atmospheric Research *WRF: Weather Research and Forecasting Model *ECMWF: European Centre for Medium-Range Weather Forecasts

  14. Preliminary analysis and results

  15. Historical Data: Reanalysis JUN 24 • Mean 2000–2008 relative humidity time series (%) computed on the grid points located between 10°W and 10°E longitude, 14.5°N and 15.5°N latitude JUN 14 APR 15 Two distinct slopes

  16. Model simulations April 1, 2006 relative humidity (%) at the surface, 925mb winds and u component at 0 to delineate ITF 700 mb AEJ Cross section along the prime meridian from 0° to 20 °N: Relative humidity (shaded) and u component at 0 20N EQ

  17. Ensemble Prediction • We will use the ensemble prediction approach to generate probabilistic forecasts that will also allow us to analyze model skill

  18. An ensemble forecast run was tested against interpolated observations Interpolated Observations Ensemble Simulation

  19. An ensemble forecast run was tested against interpolated observations -10 -8 -6 -4 -2 2 4 6 8 10 Relative Humidity Anomaly (%) The error (anomaly) is much smaller than the signal

  20. Analyzing Model Skill Observations EPS Forecast

  21. The Relative Operating Characteristic (ROC) • The ROC method is widely used for estimating the skill of ensemble prediction systems (EPS)(Marzban, 2004) • A perfect forecast system would have a ROC area (ROCA) of 1

  22. An Extended ROC Procedure • ROC plots model skill only for an optimum user • We developed an extended (EROC) procedure that caters to a particular user’s needs: Shift in baselines According to user Semazzi & Mera, 2006

  23. Model Skill for End-user • Additional analysis through EROC can help with current health efforts and the incurred costs: • Transportation of Supplies • Inoculation • Personnel

  24. Looking Forward • Understanding the moisture regime statistics: variance of 40% RH date and changes in slope of humidity trends • Sensitivity studies using SSTs, land cover, meridional transient distrubances, teleconnections with mid-latitude systems • Application of EROC for surface conditions pertinent to health efforts

  25. Acknowledgements • Dr Semazzi • CML crew • Google/UCAR group • NOAA ISET • Dr Arlene Laing, Dr Tom Hopson

  26. Questions?

  27. Auxiliary slides

  28. Historical Data: Reanalysis • Mean 2000–2008 relative humidity time series (%) computed on the grid points located between 10°W and 10°E longitude, 14.5°N and 15.5°N latitude

  29. Large scale Climatology

  30. Large Scale Climatology

  31. Decision to issue a forecast of an event (E) to occur is probabilistically based on the criteria: Criteria for Issuing a forecast Where: (N): size of the ensemble (n): number of the runs in the ensemble for which (E) actually occurs (p): probability given by the ratio (n/N) This is the threshold fraction above which the event (E) is predicted to occur based on the model forecast

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