1 / 32

Variability of Atmospheric Moisture During the Boreal Spring in West Africa

Variability of Atmospheric Moisture During the Boreal Spring in West Africa. Roberto J. Mera 1 , Arlene Laing 2 , and Fred H.M. Semazzi 1 1 Dept. of Marine, Earth and Atmospheric Sciences, North Carolina State University 2 National Center for Atmospheric Research

akasma
Télécharger la présentation

Variability of Atmospheric Moisture During the Boreal Spring in West Africa

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. Variability of Atmospheric Moisture During the Boreal Spring in West Africa Roberto J. Mera1, Arlene Laing2, and Fred H.M. Semazzi1 1Dept. of Marine, Earth and Atmospheric Sciences, North Carolina State University 2National Center for Atmospheric Research AMS Hurricanes & Tropical Meteorology Conference May11th, 2010 climlab.meas.ncsu.edu

  2. Outline • Motivation • Societal impacts • Boreal Spring • Conceptual Model • Sources of Moisture • Data & Methods • Dynamics • Short-term events • Convectively-coupled Equatorial Waves • Regional Model Simulations • Conclusions, Future Work & Acknowledgements climlab.meas.ncsu.edu

  3. Our Motivation • Why is the moisture during the boreal spring important? Prediction of Monsoon rainfall African Easterly Waves Agriculture Public health: Meningitis Outbreaks climlab.meas.ncsu.edu

  4. The Application • Meningitis is a serious infectious disease affecting 21 countries • 300 million people at risk • 700,000 cases in the past 10 years • 10-50 % case fatality rates Source: AP Based on Molesworth (2002) and references therein climlab.meas.ncsu.edu

  5. Meningitis-Climate link • Outbreaks coincide with dry, dusty conditions over the Sahel due to the Harmattan winds • Largest correlation occurs between humidity and disease outbreaks (Molesworth et al., 2003)‏ • Disease occurrence drops dramatically with the onset of humidity 2 Contrasting months SHL Harmattan Moisture January July climlab.meas.ncsu.edu

  6. A Case study: Kano, Nigeria 2009 District in Epidemic District in Alert Number of cases / 100000 per week Source: Multi-disease Control Center, Ouagadougou, Burkina-Faso, World Health Organization 40% Threshold based on Besancenot (1998) climlab.meas.ncsu.edu

  7. What happened in Kano? Kano Short-term events New moisture regime climlab.meas.ncsu.edu

  8. Simplified Conceptual Model of the Boreal Spring Equatorial Waves climlab.meas.ncsu.edu

  9. Orographic Features climlab.meas.ncsu.edu

  10. Sources of Moisture • We employ a parcel back-trajectory analysis utilizing u and v wind components from the NCEP/NCAR reanalysis for 2000-2008 • The end points surface is set at 925mb DRY MOIST *NCEP: National Centers for Environmental Prediction *NCAR: National Center for Atmospheric Research climlab.meas.ncsu.edu

  11. Data & Methods • Parcel Back-trajectory analysis & Synoptic Environment • NCEP/NCAR u & v wind components • NCEP/NCAR geopotential, total column precipitable water (mm) • Space-time filtering • Television Infrared Observation Satellite–National Oceanic and Atmospheric Administration (TIROS–NOAA), twice-daily outgoing longwave radiation (OLR), resolution of 2.5 (Gruber and Krueger 1974) • Modeling • WRF-ARW Version 3.0 season simulations 2006 & 2009 climlab.meas.ncsu.edu

  12. Model Customization • Trial-and-error approach for customization during the AMMA period of 2006 • 26 Physics parameter ensemble tests for WRF2, 19 for WRF3, numerous domain setups and relaxation zones • KF Cumulus physics, YSU PBL, Noah Land Surface Model, CAM Radiation Domains climlab.meas.ncsu.edu

  13. Short-term events propagate westward climlab.meas.ncsu.edu

  14. SHL SHL Westward-propagating moist event Synoptic Situation mid-May, 2009 event Shaded: Precipitable Water Contoured: 925mb Geopotential Vectors: 925mb winds SHL climlab.meas.ncsu.edu

  15. Diagnosing short-term Events • Are these events early-season African Easterly Waves? • What is their climatology (frequency per season)? • What synoptic factors are involved? • Saharan Heat Low • Mid-Latitude Systems • Sea surface temperatures (SSTs) • Convectively-coupled Equatorial Waves climlab.meas.ncsu.edu

  16. Two Contrasting years: 2006 & 2009 • 2006 (AMMA, late monsoon), 2009 (Meningitis reports, real-time forecasts) • Unfiltered daily NCEP OLR 2009 MJO May MJO April climlab.meas.ncsu.edu

  17. 15N has a cleaner signal of the mid-May event 2006 2009 June April climlab.meas.ncsu.edu

  18. Unfiltered analysis: OLR & precipitable water time MJO Kelvin? climlab.meas.ncsu.edu

  19. Contrasting years: 2006 & 2009 2006 2009 Less activity in 2006 climlab.meas.ncsu.edu

  20. Kelvin Filtered TB Variance climlab.meas.ncsu.edu

  21. Seasonally, 2006 & 2009 did not differ much • April had important differences climlab.meas.ncsu.edu

  22. Correlations: 2000-2009 Sahel East Sahel West climlab.meas.ncsu.edu

  23. Advantages of Dynamical Downscaling Ghana Ghana WRF at 30km resolution NCEP/NCAR Reanalysis at 2.5° climlab.meas.ncsu.edu

  24. Kano climlab.meas.ncsu.edu

  25. 12z is slightly different, closer to obs AIRS, 1:30 AM LST WRF, 00z climlab.meas.ncsu.edu

  26. TRMM (daily) April 29 – May 5 Week average Increasing precip (Chad) Increasing precip (Chad) WRF (daily) Week average climlab.meas.ncsu.edu

  27. May 20 20E TRMM Hovmoller, April 11 – May 20, 20W-20E, at 10N May 1 Westward propagation April 11 20W 20E Westward propagation May 1 WRF Hovmoller, April 11 – May 20, 20W-20E, At 10N April 11 20W climlab.meas.ncsu.edu

  28. WRF captures intraseasonal events time climlab.meas.ncsu.edu

  29. Concluding Remarks & Future Work • Convectively-coupled Equatorial Waves constitute an important source of variability for Sahelian moisture during the boreal spring • TD-Type systems modulate the moisture in the atmosphere • TD-Type systems tend to occur with higher Kelvin wave variance • Filtering of WRF simulations, spectral nudging climlab.meas.ncsu.edu

  30. Updates on our work: http://climlab.meas.ncsu.edu/googleucar • twitter.com/climlab • Facebook.com/climlab climlab.meas.ncsu.edu

  31. Acknowledgements Special thanks: Arlene Laing, George Kiladis, Stefan Tulich, Fred Semazzi, Anantha Aiyyer, Liang Xie, Matt Norman Google/UCAR team: Mary Hayden, Abraham Hodgson, Thomas Hopson, Benjamin Lamptey, Jeff Lazo, Raj Pandya, Jennie Rice, Madeleine Thomson, Sylwia Trazka, Tom Warner, Tom Yoksas climlab.meas.ncsu.edu

  32. Questions? climlab.meas.ncsu.edu

More Related