1. Meteorological dissemination prieto@eumetsat.de

2. HRI A and B Format

3. Meteosat Image 11 Mai 2001 / Europe

4. HRI X Format E_X format (for GOES-E) W_X format (for GOES-W) J_X format (for GMS) I_X format (for INDOEX)

5. WEFAX CnD, D and E Format

6. Meteorological Products Extraction Facility (MPEF)prieto@eumetsat.de

7. Spin-scan acquisition

8. Meteosat pictures Water vapour Infra-redVisible

9. What is rectification?  Deformation-Matrix  Horizontal - Vertical  ( 105 x 105 ) RawNominal

10. MARF = Meteorological Archive & Retrieval Facility MPEF = Meteorological Products Extraction Facility MDD = Meteorological Data Distribution PDUS = Primary Data User Station SDUS = Secondary Data User Station DRS = DCP Retransmission System

11. MSG MPEF  Based on calibrated data (level 1.5):  Scenes Analysis  Cloud Analysis and Cloud Top Height  Atmospheric Motion Vectors (AMV)  Clear Sky Radiance (CSR)  Calibration monitoring

12. MSG MPEF Scenes Analysis (SCE)  Derives a pixel cloud mask  Scene type  Radiances at the top of the atmosphere  Threshold tests  Quality indices

13. Algorithm applied to data of the current Meteosat (3 channels) high, medium, low clouds Scenes Analysis MSG SEVIRI Improvement: Scenes identification / cloud heights with higher accuracy sea land

14. Cloud mask: Cloud coverage over 100 km * 100 km areas, shown as a colour coded image Scenes Analysis MSG SEVIRI Improvement: Clouds coverage will be derived with higher accuracy

15. IR window channel (10.8  m)Water vapour channel 6.5  m 240 250 260 270 280 290 300 310 320 330 K 215 220 225 230 235 240 245 250 255 260 265 K Clear Sky Radiance over 100 km * 100 km areas, example of Meteosat-7 MSG SEVIRI Improvement: Clear Sky Radiance in all channels except HRV

16. Tropospheric Humidity over 100 km * 100 km areas, example for the current Meteosat Humidity values are representative for an atmospheric layer in ~ 5-7 km height MSG SEVIRI improvement: A second water vapour channel will additionally provide the humidity field in ~3-5 km height

17. Tropospheric Humidity Total Precipitable Water Content: Example for a GOES image. SEVIRI will be global

18.  level (3 heights)  phase  fraction  top temperature  10 cloud types. If (clear) surface type Cloud Analysis

19. Spatial coherence

20.  aviation  3 x 3 pixel segment  Vertical resolution: 300 metres  fog indicator Cloud Top Height (CTH)

21. Meteosat “winds” IR: any level, cloud tracers WV: high level (300-600 Hpa), but uncertain –humidity or cloud tracers, dry zones VIS: low level –cloud/ocean contrast –not on land (orography, contrast) –better resolution

22. -cumulus -transparent cirrus -tropical storms at low level -WV winds: height assignment Winds: problem areas

23. Atmospheric Motion Vectors (AMV)  Extracted from the channels:  VIS (0.6 or 0.8 µm)  IR (10.8 µm)  WV (6.2 and 7.3 µm)  Ozone (9.7 µm)  IR (8.7 µm)  HRV (0.75 µm)  Speed, direction, position, level (P,T), quality, method

24.  Tracer, rather than fixed grid  Level of the tracer, for example by Spatial Coherence Method  Correlation, gradient or texture methods Atmospheric Motion Vectors (AMV)

25. height assignment  Brightness temperature  Semi-transparency correction  Cloud base height (low clouds)  Height assignment  Ozone winds? Atmospheric Motion Vectors

26. lowmediumhigh Atmospheric Motion Vectors Analysed wind field from 3 consecutive Meteosat 10.8  m images

27. Atmospheric Motion Vectors Selection of appropriate “targets” for the tracking: These are typically regions of high image contrasts

28. Example of automatic quality control for a wind field derived from Meteosat VIS data: spatial and temporal consistency determine quality low quality index Atmospheric Motion Vectors: Quality Control

29. MSG AMV

30. Meteosat Winds (transition programme)

31. Atmospheric Instability Example of an instability retrieval (over cloudfree areas), data of GOES satellite (USA) Instability analysis: red areas mark storm potential IR image taken 10 hours later shows storm activity MSG SEVIRI improvement: Instability information retrieved on a global scale

32.  physical and neural network methods  Operational SAF processing method  Little information on atmospheric vertical structure from SEVIRI  Ancillary data from soundings or NWP Global Instability Index (GII)

33. Validation efforts: Africa

34. Validation efforts: Elbe

35.  solar and IR radiances from radiative transfer models are compared with radiances from level 1.5 images  Monitoring by NWP centres  Satellite cross-calibration  Calibration campaigns, in-situ data Calibration Monitoring

36. Satellite Application Facilities (SAFs)

37. SAF Network  EUMETSAT Application Ground Segment –Services: -up to level 2 products -user software packages -data management and user services -co-ordination of research and development –Focus: operational meteorology and climate monitoring  Two phases: Development / Operations –with EUMETSAT financial contribution for travel costs and per diem for visiting scientists

38. SW Packages for Users SEVIRI  Cloud Mask  Cloud Type  Cloud Top Temp. & Height  Precipitating Clouds  Convective Rainfall Rate  Total Precipitable Water  Layer Precipitable Water  Stability Analysis Imagery  High Resolution Winds  Aut. Sat. Image Interpr.  Rapid Dev. Thunderstorms  Air Mass Analysis  Improved Obs. Operators (for AMVs)  Geostationary Rad. Assimilation AVHRR/AMSU/MHS/HIRS  Cloud Mask  Cloud Type  Cloud Top Temp. & Height  Precipitating Clouds  Improved & Extended RTMs IASI  Fast RTM & Obs. Operators GOME  Obs. Operators ASCAT/SeaWinds  Improved Obs. Operators SSM/I  1DVar Retrieval System (for wind speed, cloud water etc.)  Fast RTM SSMIS  1DVar Retrieval System (for wind speed, cloud water etc.)  Fast RTM AIRS  1DVAR Retrieval System AAPP  Improved and extended versions for annual distribution (e.g. updated ingest function, updated cloud detection, added ICI retrieval module etc.)  Extension to processing IASI+AMSU+AVHRR SAF NWC SAF NWP

39. Real Time Product Services MSG EPS Multi-Mission  Surface Albedo  Aerosol  Scattered Radiance Field  Surface Short-wave Fluxes  Land Surface Temperature  Surface Emissivity  Surface Long-wave Fluxes  Soil Moisture  Evapotranspiration Rate  Near Surface Wind Vector  Regional SST  Atlantic High Latitude Rad. Fluxes  Total Ozone  Ozone Profiles  Aerosol Indicator  Surface Albedo & Aerosol  Scattered Rad. Field  Surface Short-wave Fluxes  Land Surface Temperature  Surface Emissivity  Surface Long-wave Fluxes  Evapotranspiration Rate  N. Europe Snow Cover  Refractivity Profiles  Temp., Hum. & Pressure Profiles  Integrated Water Vapour  Atlantic SST  Atlantic Surf. Rad. Fluxes  Sea Ice Edge  Sea Ice Cover  Sea Ice Type  Clear-Sky UV Fields  Land Surface Temperature  Surface Emissivity  Surface Long-wave Fluxes  S. & C. Europe Snow Cover SAF OSI SAF O3M SAF CLM SAF GRM SAF LSA

40. Off-Line Product Services MSG EPS Multi-Mission  Surface Albedo & Aerosol  Scattered Radiance Field  Surface Short-wave Fluxes  Land Surface Temperature  Surface Emissivity  Surface Long-wave Fluxes  Total Ozone  Trace Gases  Ozone Profiles  UV Fields with Clouds & Albedo  Surface Albedo & Aerosol  Scattered Radiance Field  Surface Short-wave Fluxes  Land Surface Temperature  Surface Emissivity  Surface Long-wave Fluxes  Refractivity Profiles  Temperature, Humidity and Pressure Profiles  Integrated Water Vapour  Land Surface Temperature  Surface Emissivity  Surface Long-wave Fluxes  NDVI, FGV, fPAR, LAI  Fractional Cloud Cover  Cloud Classification  Cloud Top Temp. & Height  Cloud Optical Thickness  Cloud Phase  Cloud Water Path  Surface Rad. Budget  Surface Albedo  Rad. Budget at TOA  Sea Surface Temperature  Sea Ice Cover  Humidity Profile [TBC] SAF OSI SAF O3M SAF CLM SAF GRM SAF LSA

41. SAF Visiting Scientists Objectives to allow scientists from other institutes to acquire expertise in the field of the SAF activities/products to allow scientists from other institutes to contribute to algorithm development and product verification/validation Types VISITING SCIENTISTS, which participate in the development activities by spending a certain time interval at one of the SAF Institutes ASSOCIATED SCIENTISTS, which participate in the development activities but stay “at home”

42. SAF Visiting Scientists - Examples of topics - >Monthly Arctic sea ice signatures for use in passive microwave algorithms >Precipitation analysis from AMSU >Evaluation of skin-bulk sea surface temperature difference models >Cloud classifications in cold winter situations in Northern Europe >Investigations of NOAA AVHRR/3 1.6  m imagery for snow, cloud and sunglint discrimination >Compensating for atmospheric effects on passive radiometry at 85.5 GHz using a radiative transfer model and NWP model data >Tests of the the radiance ratioing method with HIRS data >Cloud height determination using GOES water vapour and infrared window channel imagery >Evaluation of applicability of the 3.6 - 4.0  m spectral band data for the SAFNWC Convective Rainfall Rate product

43. Nowcasting Ocean and sea ice Ozone Climate Numerical weather prediction GRAS meteorology Land surface Hydrology SAF Themes