Climate Modeling LaboratoryMEASNC State University Predictability of the Moisture Regime Associated with the Pre-onset of Sahelian Rainfall Roberto J

Climate Modeling LaboratoryMEASNC State University

Predictability of the Moisture Regime

Associated with the Pre-onset of Sahelian Rainfall

Roberto J. Mera* and Fred H.M. Semazzi

Marine, Earth and Atmospheric Sciences

North Carolina State University AMS Annual Meeting January 19th, 2010


A broader context: Predictability of the

Moisture Regime During the Boreal Spring in West Africa and its

Implications on Meningitis Mitigation


Our Motivation• Why is the moisture regime important?

Prediction of Monsoon rainfall

AgricultureAfrican Easterly Waves

Public health: Meningitis Outbreaks


Outline

• The Application– Background– Current efforts

• Our Study– Relevant Variables– Sources of Moisture– Importance of Downscaling– Intraseasonal prediction


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


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

January July

SHLSHL

Har

mat

tan

Moi

sture


Current Efforts

• UCAR, in conjunction with IRI, NCSU, Navrongo (Ghana) Health Research Center are working on a prototype Earth-gauging system integrating weather and health data to manage meningitis

• The latest research was presented at the World Health Organization (WHO) Meningitis Environmental Risk Information Technologies (MERIT) project meeting in Niamey, Niger in 2009


Google/UCAR Project at NCSU

• Recent work for the MERIT project has been aimed at constructing a decision tree on “action threshold” for vaccine implementation

• This decision tree, however, does not include climate information at this point


Google/UCAR Project at NCSU

• Our aim is to address the climate factors pertinent to meningitis mitigation at the appropriate time scales

• We present preliminary results on seasonal and intraseasonal scales


Our Study: Predictability of Atmospheric Moisture

• What are the variables important for the prediction of the moisture regime?

• What are the sources of moisture in West Africa during the Boreal Spring?

• Can regional climate models forecast moisture transport dynamics?


The VariablesVariables related to the West Africa monsoon have the highest correlation with meningitisWe use relative humidity (RH) as an indicator in our study

From Yaka et al (2008)


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

*NCEP: National Centers for Environmental Prediction*NCAR: National Center for Atmospheric Research


• Three different time periods to analyze conditions: early spring (P1, Jan 27 – Feb 15), mid-spring (P2, Apr 15 – May 4) & late spring (P3 Jun 11-30)

• We use Relative Humidity derived from NCEP/NCAR reanalysis at 40% as a divider between dry and moist conditions

P1 P2 P3

April 20, 2000


Source Regions

66.7%

15.9%

16.7%

0.8%

NW SaharaNE Sahara

Europe

NE Tropical Atlantic

0.7%7.8%1.4%

14.2%

19.9%

7.8%

2.8%

0.7%

44.7%

NW Sahara

NE Sahara

Europe

North Atlantic

Gulf of Guinea

NE Tropical Atlantic

Guinea Coast

Sahel

South Atlantic20.0%

73.6%

1.6%

4.8%

Gulf of Guinea

Guinea Coast

Sahel

South Atlantic

P1

P3

P2


Implications

• Role of large scale forcing: NAO, ENSO• Other factors:

• Sea Surface Temperature anomalies (SSTA) in the Gulf of Guinea and Northeast Tropical Atlantic

• Global teleconnections


• Analysis of added value of dynamical downscaling• We use the Weather Research and Forecasting WRF Model

as both a predictive and analytical tool for• High resolution reanalysis• Real-time forecasts• Sensitivity experiments• Comparison with large-scale models

Dynamical Downscaling

Scale of relevance


Advantages of Dynamical Downscaling

WRF at 30km resolution NCEP/NCAR Reanalysis at 2.5°

Ghana Ghana


Attack rates and reanalysis


Advantages of Dynamical Downscaling

Kano


0

40

80

3-Mar 13-Mar 23-Mar 2-Apr 12-Apr 22-Apr 2-May 12-May 22-May

Ob

se

rve

d R

H (

%)

Intraseasonal Variability

KanoShort-term events


WRF captures intraseasonal events (westwatd-propagating disturbances)

Domains


Implications

• Short-term phenomena:• Westward-propagating systems• Dynamics of Saharan Heat Low• Incursions from mid-latitudes• SST anomalies• Diurnal variability• Walker circulation


Summary

Back‐trajectory analysis has determined that the sources of air mass during the onset of higher moisture into the region are highly variable in horizontal and vertical scales. Further attention needs to be directed towards the variance of large scale patterns that dictate the state of the atmosphere in these source regions. WRF can be used as a tool to diagnose the moisture regime preceding the West African Monsoon for health efforts in the region


Future Work

• Data assimilation of satellite and in-situ information for further analysis of the meningitis-climate interface

• Integration of WRF into meningitis prediction• Simulations using spectral nudging to retain large

scale information from the air mass source regions

• Stratification of predictive model skill for different modes of variability


Communication

Updates on our work: http://climlab.meas.ncsu.edu/googleucar

twitter.com/climlab


Acknowledgements


Questions?

Documents

Climate Modeling LaboratoryMEASNC State University Predictability of the Moisture Regime Associated with the Pre-onset of Sahelian Rainfall Roberto J