Present and future capabilities of the Sand and Dust Storm Warning System for North Africa to provide knowledge on environmental risk indicators of meningitis epidemics Carlos Pérez 1 José M. Baldasano 1,2, Emilio Cuevas 3, Slobodan Nickovic 4, Len Barrie 4, Xavier Querol 5 (1) Earth Sciences Department. Barcelona Supercomputing Center (BSC; Spain) (2) Laboratory of Environmental Modeling. Universitat Politècnica de Catalunya (UPC, Spain) (3) National Institute of Meteorology (INM; Spain) (4) AREP, World Meteorological Organization (WMO; Switzerland) (5) Earth Sciences Institute Jaume Almera (IJA-CSIC; Spain) GEO Meningitis Environmental Risk Consultative Meeting, Geneva, September 2007

Mineral Dust Impacts

Sand and Dust Storm Warning System for North Africa, Europe and Middle East PURPOSE : - Achieve comprehensive, coordinated and sustained observations and modelling capabilities of the sand and dust storm - Increase the understanding of its formation processes - Enhance and provide operational prediction capabilities and dust-related data

- Epidemics start during the dry season - Certain environmental factors, such as low absolute humidity, land cover types and dusty atmospheric conditions, may play an important role (Lapeyssonnie, 1963; Cheesbrough et al., 1995; Greenwood, 1999; Molesworth et al., 2003; Thomson et al., 2006). Districts crossing the Alert and Epidemic thresholds in African countries under enhanced surveillance 2006 Dust from MODIS ? Dust and meningitis epidemics

Health-related GEMS-MACC project proposal work package: Sand and Dust forecasting to prevent meningitis epidemics Objectives: Gain scientific knowledge about the relationship between atmospheric mineral dust, general atmospheric conditions and meningitis in the Sahel region Improve environmental prediction models for meningitis prevention How can we contribute to improving the knowledge on environmental risk indicators of meningitis epidemics? Activities: 1- Refined short-term dust forecasts and dust surveillance in the Sahel region 2- Retrospective analysis of dust with model and available satellites and its relationship with meningitis in the Sahel 3- Explore links between dust, meningitis and large scale climate indexes

Dust REgional Atmospheric Model (DREAM) (Nickovic et al., 2001) Simulates all major processes of the atmospheric dust cycle. Fully embedded as one of the governing prognostic equations in the atmospheric NCEP/Eta atmospheric model (Janjic 1994, 1996a,b, Janjic 1997) 4 transport particle sizes (0.73, 6.1, 18, 36 m) Dust production scheme with introduced viscous sublayer (Shao 1993; Janjic 1994). Particle size distribution effects. Soil wetness effects on dust production (Fecan et al, 1999). Dry (Georgi, 1986) and wet deposition. Developed and operated at University of Athens, ICOD Malta and Barcelona Supercomputing Center ( 1- Refined short-term dust forecasts and dust surveillance in the Sahel region

SDS WS Operational products Model predictions (72-h): Horizontal distribution PM2.5, PM10, TSP at surface and height Total column mass (dust load) Dust aerosol optical depth Wet, dry, total deposition Visibility (soon available) Meteorological variables Vertical distribution Cross sections Fixed point/time profiles Fixed point (selected sites/cities) Dustgrams Meteograms Request-only basis: Numerical data Climatology 1- Refined short-term dust forecasts and dust surveillance in the Sahel region

Observations real time or near real time: 15-minute RGB dust from Meteosat Second Generation (MSG) Seviri channels for North Africa Weekly maps of Normalized Difference Vegetation Index (NDVI) obtained from 15-minute Seviri MSG channels (3km resolution) Dust from MODIS, SeaWIFS, OMI AERONET and Visibility data Vegetation index derived from SEVIRI/MSG data over West Africa SDS WS Operational products 1- Refined short-term dust forecasts and dust surveillance in the Sahel region

Meteosat Second Generation Model has shown very good agreement with observations in a number of studies of single events (e.g., Ansmann et al., 2003, Papayannis et al., 2005; Pérez et al., 2006a;b; Jiménez et al, 2006 ….) SeaWIFS Lidars - EARLINET AERONET - ONLINE Operational verification 1- Refined short-term dust forecasts and dust surveillance in the Sahel region

MareNostrum - Peak performance of 94,21 Teraflops IBM Power PC 970MP processors 2- Retrospective analysis of dust and opportunities for meningitis studies Long term Saharan dust simulations 1958 – 2006 (under progress) WHAT CAN WE PROVIDE TO THE HEALTH COMMUNITY ??? - 3D fields of dust and meterology - Validated with observations !! Reanalysis data: NCEP/NCAR Complementing and, at least, partially overcoming Satellite data (AI) limitations

Seasonal Average : surface dust concentration 2- Retrospective analysis of dust and opportunities for meningitis studies

Seasonal Average Wet dust deposition 2- Retrospective analysis of dust and opportunities for meningitis studies

Izaña Station (Tenerife) dust record Model Validation – 12 h average total dust concentration Izaña Station (Tenerife) 28° 18' N, 16° 29' W, elevation 2367 meters a.s.l. 350 km west of Africa. A trade wind inversion layer is usually present below 1800 meters a.s.l. avoiding the arrival of polluted air from the surrounding lowland areas. 2- Retrospective analysis of dust and opportunities for meningitis studies

Winter R=0.79 IZAÑA R=0.62 AVHRR 10-30W 15-30N Evan et al., Retrospective analysis of dust and opportunities for meningitis studies

Correlations DJF NAO vs. DJF averages DJF NAO vs. DJF concentration DJF NAO vs. DJF AOD DJF NAO vs. DJF Dry Dep DJF NAO vs. DJF Wet Dep Link between dust, meningitis and large scale climate indexes

NOV NAO – NOV dust DEC NAO – DEC dust JAN NAO – JAN dust FEB NAO – FEB dust Winter monthly correlations 3- Link between dust, meningitis and large scale climate indexes Other possible indexes to look at: - TNA (Tropical Northern Atlantic Index) - NTA (North Tropical Atlantic SST Index) - Atlantic Tripole SST - Sahel Standardized Rainfall

- Dust forecasting and observations available for the health community through the SDS WS Regional Center - Dust model retrospective analysis available for research - More refined simulations and forecasts are planned - Need for collaboration and feedback between atmospheric and health community within GEMS-MACC and other projects Final aspects and further steps

CONTACT Barcelona Supercomputing Center-Centro Nacional de Supercomputación Earth Sciences Department. Barcelona. GEO Meningitis Environmental Risk Consultative Meeting, Geneva, September 2007