Storm Warning System Barcelona, November 7-9-, 2007

Transcription

1 WMO/GEO Expert Meeting on an Internacional Sand and Dust Storm Warning System Barcelona, November 7-9-, 2007 The WMO Sand and Dust Storm Warning System (SDS-WS) for Europe, Africa and Middle East: a GEO-oriented System Emilio Cuevas 1, José María Baldasano 2,3,Carlos Pérez 2, Xavier Querol 4, Sara Basart 1,2, Miguel Ángel Martínez 1, Oriol Jorba 2, Pedro Jiménez 2, Len Barrie 4,Slobodan Nickovic 4 1 National Institute of Meteorology (INM; Spain) 2 Earth Sciences Department. Barcelona Supercomputing Center (BSC; Spain) 3 Laboratory of Environmental Modeling. Universitat Politècnica de Catalunya (UPC, Spain) 4 Earth Sciences Institute Jaume Almera (IJA-CSIC; Spain) 5 AREP, World Meteorological Organization (WMO; Switzerland) ecuevas@inm.es

2 Outline 1. Motivation 2. Domain 3. The Consortium 4. Main Objectives of the Regional SDS WS 5. Current and potential users

3 The World Meteorological Organization (WMO) Scientific Steering Committee meeting for Sand and Dust Storm (SDS) Project (November 2006 Shanghai, China): establishment of a WMO-coordinated global network of SDS forecasting Centers delivering products useful to a wide range of users for reducing the impacts of SDS Spain is currently implementing a WMO Regional SDS WS Centre for Europe, Africa and Middle East

4 Motivation The Saharan sources are considered by far the most active ones in the world. Recent estimations of annual Saharan dust emission range from 1000 to 1600 Tg yr Annual value in μg/m Daily value in μg/m Nº of allowed exceedances Long-term simulations ( ) of Saharan dust over the Mediterranean and the Eastern North Atlantic with the DREAM regional dust model C. Pérez, P. Jiménez-Guerrero, O. Jorba, J. M. Baldasano, E. Cuevas, S. Nickovic, X. Querol Limit values for PM 10 in the European Directive

5 Motivation

6 The consortium + partners of the region Why? Spain is seriously affected by SDS Partnership among a NMS, a Supercomputing facility and a Research Council Commitment of the consortium to fund a long-term and stable operational SDS WS Cooperation with African NHMNs in coordination with WMO and supported by the Government of Spain

7 Domain Sahara and Arabia deserts

8 Objectives 1) provide real-time information from a long-term maintained core-operational operational and quality controlled dust monitoring and forecasting system; 2) maintain an open web portal with both research and near-real real time information, and links to available dust forecasting and monitoring systems within the region; 3) implement a web-oriented modelling and observational historical SDS WS products archive for case-study study and climatological analysis.

9 Objective #1 (Operational Dust forecasting) Dust forecasting with BSC-DREAM model 50x50 km 2 20x20 km h 3h step Vertical till 10 km Pérez et al., this meeting

10 Objective #1 (Operational Satellite dust surveillance) Dust monitoring SAF_NowCasting with MSG satellite 3x3 km 2 15 min step (day and night) SeaWifs, Modis, OMI CALIPSO Nowcast concept Small area dust source determination Martínez et al., Use of SEVIRI images and derived products in a WMO Sand and Dust Storm Warning System

11 Objective #1 (dust monitoring and forecasting)

12 Objective #1 Products Operational model: - Horizontal distribution PM2.5, PM10, TSP at surface and height/pressure levels Total column mass (dust load) Dust aerosol optical depth at 550 nm Wet, dry, total deposition Visibility Meteorological variables (cloudiness, precipitation, wind, temperature) - Vertical distribution Cross sections Fixed point/time concentration vertical profiles - Fixed point (selected sites/cities) Dustgrams - Other additional products Total PM10, PM2.5 in Europe (dust+antropogenic aerosols) Satellite near-real time surveillance: -RGB dust from Meteosat Second Generation (MSG) every 15 minutes for the whole geographical area of responsibility. - AOD from Seawifs, Modis, AVHRR (over limited areas) - AI from OMI - Vegetation Index, Cloud masks and other auxiliary products.

13 Objective #1 (ground-based dust monitoring and validation) Sun photometers (AOD) AERONET-NASA PHOTONS-CNRS (France) RIMA (Spain) hhtp://aeronet.gsfc.nasa.gov

14 Objective #1 (dust vertical distribution monitoring and validation) Lidars MPLNet-NASA (Tenerife) Airlinet (Europe) Earlinet database in BSC Marenostrum

15 Objective #1 (ground-dust conc. monitoring and validation) In-situ PM10/PM2.5 On-line stations EMEP National and regional air-quality networks Seasonal Dust Concentration (μg m -3 ) nm IZAÑA Observations DJF (Izaña) Model DJF (DREAM) YEAR R=0.79

16 Provide real-time information from a long-term maintained core-operational and quality controlled dust monitoring and forecasting system Objective #1: ongoing activities - Real-time model validation (point-aod, point surface PM) - Real time model-satellite qualitative comparison (MSG-RGB) - Off-line model-satellite quantitative validation over the ocean (Seawifs( and Modis AOT) Implementation of MSG-AOD (PROMOTE; SAF NowCasting) ) for quantitative model-msg comparison (only over ocean?) Implementation of the DREAM model into the most recent parallelized and non-hydrostatic version of the NMM/NCEP model, with possible application either as a limited area (regional) or global model Improvement of the current parameterizations for several physical processes such as dust emission, dust particle size physics, wet deposition n and dust radiative effects

17 Provide real-time information from a long-term maintained core-operational and quality controlled dust monitoring and forecasting system Objective #1: Challenges; next activities - Visibility-range (Metar( and Synop convention) forecasts for airports - Data dissemination: real-time dust alerts (WIS-GTS); GeoNetCast - Temperature and radiative forcing forecasts over dusty regions - Implementation of satellite Outgoing Longwave Radiation (OLR) and comparison with model outputs. - Support to chlorophyll forecasting systems for fishing activities - Provide information to the meningitis issue in the Sahel - PROMOTE BUILDING CAPACITY IN AFRICA (DUST SOURCE REGIONS) - Dry and wet deposition validation - Real time dust assimilation (Experience from the Asian SDS WS) - Harmonized forecasting (DREAM, SKIRON, CHIMERE, ECMWF-MACC, MACC, MOCACHE, TAU, HYSPLiT )

18 Objective #2 (Web page) Maintain a web portal with both research and near-real time information, and links to available dust forecasting and monitoring systems within the region

19 Maintain a web portal with both research and near-real information and links to available dust forecasting and monitoring systems within the region Objective #2: Challenges; ongoing activities - Implement and maintain a WMO SDS WS web portal within WMO domain - Develop user-friendly model (DREAM) forecast maps - Links to other dust forecast products within the region - Real time data access for on-line validation service facilities

20 Maintain a web portal with both research and near-real information and links to available dust forecasting and monitoring systems within the region Objective #2: Challenges; next activities - Model homogenization to compare results: - Geographical domain - Projection - Space and time resolution - Output parameters (Surface concentration, dry, wet deposition; AOD) - Color palette homogenization - Potential operational run of other dust forecast models at the BSC B Marenostrum supercomputer - Promote joint dust model validation exercises and joint developments (data assimilation, dust sources developments) within EC Framework Programme

21 Objective #3: Challenges; ongoing activities Implement a web- oriented modelling and observational historical data base available for case-study study and climatological analysis Long-term Saharan dust simulations with DREAM (under progress): Dust and chlorophyll: long-term analysis of Atlantic Ocean eutrophization (PI: A. González lez; ; University of Las Palmas) Dust and NAO (PI: C. Pérez,, BSC) Dust trends over different regions (Canary Islands, North Atlantic, tic, Mediterranean basin) Weather patterns associated to SDS

22 Objective #3: Challenges; next activities Implement a web-oriented modelling and observational historical data base available for case-study and climatological analysis - Dust model data inventory: - Model reanalysis -AOD - Surface concentration - Dry and wet deposition - point-vertical dust distribution - Score reports (validation) - Dust information from satellites - Satellite imagery bank -AOD -AI - Dust data from ground stations Dust data from ground stations - Visibility range series (from Metar and Synop) -PM series - Lidar data base (Earlinet) - Sunphotometer data base (link to Aeronet?) Dust climatololy Case-study analysis

23 Current and potential users of the SDS WS - European and African NHNMs and Administrations: early warnings to population - European and African air quality managers - WHO; Health community (asthma and meningitis) - Airport authorities - Oceanographic centers (Marine Biology Departments) -Scientific community - Observational Networks: Earlinet (European Lidar Network), AERONET and in-situ observations (EMEP, national and regional air quality networks) - Satellite community (ESA, Eumetsat, NASA) - Experimental campaigns (TROMPETA, SAMUM, )

24 The WMO Regional Sand and Dust Storm (SDS) Warning System (WS) for Europe, Africa and Middle East: A harmonized atmospheric dust focal point within the Region and link to others WMO SDS WS Regional SDS WS Steering Committee with annual expert Conferences

25 Thank you Gracias Emilio Cuevas 1, José María Baldasano 2,3,Carlos Pérez 2, Xavier Querol 4, Sara Basart 1,2, Miguel Ángel Martínez 1, Oriol Jorba 2, Pedro Jiménez 2, Len Barrie 4,Slobodan Nickovic 4 1 National Institute of Meteorology (INM; Spain) 2 Earth Sciences Department. Barcelona Supercomputing Center (BSC; Spain) 3 Laboratory of Environmental Modeling. Universitat Politècnica de Catalunya (UPC, Spain) 4 Earth Sciences Institute Jaume Almera (IJA-CSIC; Spain) 5 AREP, World Meteorological Organization (WMO; Switzerland)