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Mineral Dust Impacts

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

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Mineral Dust Impacts

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  1. 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 • Earth Sciences Department. Barcelona Supercomputing Center (BSC; Spain) • Laboratory of Environmental Modeling. Universitat Politècnica de Catalunya (UPC, Spain) • National Institute of Meteorology (INM; Spain) • AREP, World Meteorological Organization (WMO; Switzerland) • Earth Sciences Institute ‘Jaume Almera’ (IJA-CSIC; Spain) • carlos.perez@bsc.es • GEO Meningitis Environmental Risk Consultative Meeting, Geneva, 26-27 September 2007

  2. Mineral Dust Impacts

  3. 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

  4. ? Districts crossing the Alert and Epidemic thresholds in African countries under enhanced surveillance 2006 Dust from MODIS Dust and meningitis epidemics - 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).

  5. How can we contribute to improving the knowledge on environmental risk indicators of 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 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

  6. 1- Refined short-term dust forecasts and dust surveillance in the Sahel region 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 mm) • 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 (http://www.cgd.ucar.edu/tss/staff/mahowald/dust.html)

  7. http://www.bsc.es/projects/earthscience/DREAM/ 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

  8. 1- Refined short-term dust forecasts and dust surveillance in the Sahel region SDS WS Operational products • 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

  9. 1- Refined short-term dust forecasts and dust surveillance in the Sahel region Operational verification 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 ….) Meteosat Second Generation SeaWIFS Lidars - EARLINET AERONET - ONLINE

  10. 1- Refined short-term dust forecasts and dust surveillance in the Sahel region

  11. Long term Saharan dust simulations 1958 – 2006 (under progress) Reanalysis data: NCEP/NCAR 1958-2006 • 3D fields of dust and meterology • - Validated with observations !! Complementing and, at least, partially overcoming Satellite data (AI) limitations 2- Retrospective analysis of dust and opportunities for meningitis studies MareNostrum- Peak performance of 94,21 Teraflops - 10240 IBM Power PC 970MP processors WHAT CAN WE PROVIDE TO THE HEALTH COMMUNITY ???

  12. 2- Retrospective analysis of dust and opportunities for meningitis studies Seasonal Average 1959-2006: surface dust concentration

  13. 2- Retrospective analysis of dust and opportunities for meningitis studies Seasonal Average 1959-2006 Wet dust deposition

  14. 2- Retrospective analysis of dust and opportunities for meningitis studies Izaña Station (Tenerife) dust record 1987-1999Model 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.

  15. 2- Retrospective analysis of dust and opportunities for meningitis studies

  16. IZAÑA R=0.79 AVHRR 10-30W 15-30N R=0.62 Evan et al., 2006 2- Retrospective analysis of dust and opportunities for meningitis studies Winter

  17. + + - - - - + - + - - - + + - + + - - - + + + 3- Link between dust, meningitis and large scale climate indexes Correlations DJF NAO vs. DJF averages 1981-2006 DJF NAO vs. DJF concentration DJF NAO vs. DJF AOD DJF NAO vs. DJF Dry Dep DJF NAO vs. DJF Wet Dep

  18. 3- Link between dust, meningitis and large scale climate indexes Winter monthly correlations NOV NAO – NOV dust DEC NAO – DEC dust JAN NAO – JAN dust Other possible indexes to look at: - TNA (Tropical Northern Atlantic Index) - NTA (North Tropical Atlantic SST Index) - Atlantic Tripole SST - Sahel Standardized Rainfall FEB NAO – FEB dust

  19. Final aspects and further steps • 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

  20. THANKS CONTACT carlos.perez@bsc.es Barcelona Supercomputing Center-Centro Nacional de Supercomputación Earth Sciences Department. Barcelona. GEO Meningitis Environmental Risk Consultative Meeting, Geneva, 26-27 September 2007

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