Vorhersage atmosphärischer Prozesse und Partikel: Regionale Skala (CAMS 50)

Transcription

1 Vorhersage atmosphärischer Prozesse und Partikel: Regionale Skala (CAMS 50) H. Elbern, E. Friese Rheinisches Institut für Umweltforschung an der Universität zu Köln, und IEK 8-FZ Jülich

2 Contents 1. Introduction and legacy 2. Scope of CAMS 3. Regional air quality monitoring and forecast services 4. EURAD-IM CAMS implementation with downstream extensions

3 CAMS - Aufbauentwicklung > 10a GMES CAMS

4 background requirements All the individual assimilation and forecast systems must be mature, well validated and operated by their main developers. a group of organisations with proven operational capabilities and track record in air quality assimilation and forecasting

5 Model characteristics on contract inception

6 Description of individual productions GRIB2 data format, eight vertical levels (surface, 50m, 250m, 500m, 1000m, 2000m, 3000m, and 5000m above ground), parameters provided : O 3, NO 2, NO, PM 10, PM 2.5, SO 2, CO, NH 3, PANs, NMVOC and birch pollen for almost all models, olive and grass pollen will be provided at phase 2 and ragweed pollen is planned for phase 3.

7 Data flow of the daily regional production

8 Aerosol Dynamic in EURAD-IM

9 Secondary Organic Aerosols in EURAD-IM ROG + oxidant (O 3, NO 3, OH) photo-chemistry low volatility condensable products anthropogenic biogenic CVARO1 CVALK1 CVAPI1 CVLIM1 CVISO1 CVARO2 CVOLE1 CVAPI2 CVLIM2 CVISO2 SORGAM production of semivolatile condensable products (gas phase) P B P i = X i P i 0 1 X A P A gas/particle-partitioning thermodynamic equilibrium Temperature dependent (Li et al., 2013) secondary organic aerosol SOAARO1 SOAALK1 SOAAPI1 SOALIM1 SOAISO1 SOAARO2 SOAOLE1 SOAAPI2 SOALIM2 SOAISO2 anthropogenic biogenic secondary organic aerosol (aerosol phase)

10 Web based product publication example: ensemble O 3

11 Analyses data provided to users and availability times Forecast ensemble data provided to users and availability times

12 Products available to users: Website and data server

13 EURAD-IM production stream 1. ECMWF-based implementation Global production IFS meteorological forecast/analysis GFAS wildfire emission data Global AQ forecast/analysis EURAD-IM regional production AQ analysis AQ forecast Data archive, Dissemination Ensemble production Validation

14 Use of In Situ and Remote Sensing Data AIRBASE routine measurement sites METOP IASI A train In Situ Further remote sensing data AERONET lidars EBAS special stations: Jungfraujoch NO2 column data assimilation modules IASI O3 and CO data assimilation module integration of novel satellite observation operators,: IASI-GOME, SLSTR, Remote Sensing Terra/MOPPIT Sentinels 1, 4, 5, 5p, METOP/GOME-2 VIIRS, OMPS MODIS, SEVIRI AOD data assimilation module IAGOS Terra/MODIS

15 Example: August 2016 ozone episode Observations Forecast Analysis

16 Forecast skills: impact of national emission inventories? Typical NO 2 example compare Germany- The Netherlands Lower Saxony Netherlands Schleswig-Holsatia

17 EURAD-IM MACC 3d-var EVA Re-Analysis for 2013 OMI NO 2 Column Retrievals for 9. July Analysis - background Observations, y Background, H(x) Analysis, H(x)

18 3d-var Assimilation of IASI Ozone Columns MACC-III GA Reading

19 3d-var Assimilation of IASI Ozone Columns Validation by Ozone Radio Sondes

20 Fire Radiative Power Analysis from GFAS GFAS CO Emissions Example: Russian peat fires 2010 CO Impact on PM 10 PM 10 Observations EURAD-IM without GFAS emissions EURAD-IM with GFAS emissions

21 Incorporation of the MODIS 8-day Leaf Area Index Product (Sentinel 2 in preparation) January July

22 EURAD-IM Downstream AQ Services Central Europe, 5 km resolution

23 Further CAMS regional ITTs CAMS 61 Model development CAMS 62 Chemical data assimiltion CAMS 63 ensemble modelling

24 CAMS 50 Services RIU extended services incl. regional downscaling EURAD-IM surface NO 2 forecast, , 15:00 UTC VIELEN DANK FÜR IHRE AUFMERKSAMKEIT