1. WMO SDS-WAS Regional Center for Northern Africa, Middle East and Europe. Dust models intercomparison Sara Basart (BSC-CNS), Enric Terradellas (AEMET), José M. Baldasano (BSC-CNS) and Francesco Benincasa (BSC-CNS) 4th. ICAP Workshop. Frascati, 14-17 May 2012

2. WMO SDS-WAS Mission The WMO SDS-WAS mission is to enhance the ability of countries to deliver timely and quality dust forecasts, observations, information and knowledge to users through an international partnership of research and operational communities. Photo: Steve & Jemma Copley, 15-2-2008 Severe sand storm in Salmiya, Hawalli, Kuwait http://www.wmo.int/pages/prog/arep/wwrp/new/Sand_and_Dust_Storm.html

3. The Regional Center for Northern Africa, Middle East and Europe The Regional Center is jointly managed by AEMET and the BSC-CNS. It is located in Barcelona, at BSC- CNS premises

4. Objectives of the Regional Center Identify and improve monitoring and forecast products of atmospheric dust, through consultation and cooperation with research, operational and user communities Facilitate user access to information Build capacity of countries to use observations, analysis and forecasts provided by the WMO SDS-WAS programme. MODIS Terra 22 June 2009. MODIS Rapid Response Team:

5. sds-was.aemet.es HOME ABOUT US FORECAST & PRODUCTS PROJECTS & RESEARCH MATERIALS NEWS EVENTS CONTACT US sdswas@aemet.es

6. Dust models Data exchange Joint visualization Common forecast evaluation Generation of multimodel products Calculation of monthly evaluation metrics New sources of data for model evaluation Sharing model output data files Time-averaged products

7. Data exchange MODELINSTITUTIONRUN TIMECONTACT BSC-DREAM8bBSC-CNS12J. M. Baldasano CHIMERELMD00L. Menut LMDzT-INCALSCE00M. Schulz MACC-ECMWFECMWF00J. J. Morcrette A.Benedetti DREAM-NMME- MACC SEEVCC12G. Pejanovic NMMB/BSC- Dust BSC-CNS12J. M. Baldasano UMU. K. Met OfficeD. Walters

8. Joint visualization of dust models Model outputs (dust optical depth and dust surface concentration) are represented using a common geographical framework and colour palette.

9. Forecast evaluation using AERONET data

10. Generation of multimodel products CENTRALITY: Mean - Median SPREAD: Standard deviation - Realtive st. dev. (  / (x+k)

11. Calculation of monthly evaluation metrics Besides dust, there might be other aerosol types (anthropogenic, biomass burning, etc.). Then, a small BE could be expected. Scores for individual sites can be little significant for being calculated from a small number of data. The RMSE is strongly dominated by the largest values. Especially in cases where prominent outliers occur, the usefulness of the RMSE is questionable and the interpretation becomes more difficult

12. Future: New sources of data for model evaluation

13. Sharing model output data files Daily forecasts of dust surface concentration and dust optical depth will be displayed on a page together with a menu to allow visualization of the archived products and/or download of the numerical files for a selected range of dates. Access to the download pages shall be restricted to those groups that authorize the exchange of their own data.

14. Time-averaged products To be extended to other models.

15. II Lectures on Atmospheric Mineral Dust. Barcelona, 5-9 Nov. 2012 Scope: The event is targeted to operational meteorologists as well as to early career scientists (advanced students, PhD candidates and postdoctoral researchers) with a background in the Earth system sciences. Scientific Committee: José María Baldasano (BSC-CNS) Emilio Cuevas Agulló (AEMET) Santiago Gassó (UPC) Slobodan Nickovic (WMO) José Prieto (EUMETSAT) Coordination: WMO SDS-WAS. Regional Center for Northern Africa, Middle East and Europe Information and online registration: sdswas@aemet.eshttp://sds-was.aemet.eshttp://sds-was.aemet.es

16. WMO SDS-WAS programme Regional Center for Northern Africa, Middle East and Europe http://sds-was.aemet.es sdswas@aemet.es http://sds-was.aemet.es sdswas@aemet.es