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Meteorological dissemination prieto@eumetsat.de

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  1. Meteorological dissemination prieto@eumetsat.de

  2. HRI A and B Format

  3. Meteosat Image 11 Mai 2001 / Europe

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

  5. WEFAX CnD, D and E Format

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

  7. Spin-scan acquisition

  8. Meteosat pictures Visible Infra-red Water vapour

  9. What is rectification? Raw Nominal • Deformation-Matrix • Horizontal - Vertical • ( 105 x 105 )

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

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

  15. 240 250 260 270 280290 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 IR window channel (10.8 m) Water vapour channel 6.5 m 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. Cloud Analysis • level (3 heights) • phase • fraction • top temperature • 10 cloud types. If (clear) surface type

  19. Spatial coherence

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

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

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

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

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

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

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

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

  33. Validation efforts: Africa

  34. Validation efforts: Elbe

  35. Calibration Monitoring • 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

  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. 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 SW Packages for Users 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 ServicesMSGEPSMulti-Mission • 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 • Surface Albedo • Aerosol • Scattered Radiance Field • Surface Short-wave Fluxes • Land Surface Temperature • Surface Emissivity • Surface Long-wave Fluxes • Soil Moisture • Evapotranspiration Rate SAF OSI SAF O3M SAF CLM SAF GRM SAF LSA

  40. Off-Line Product ServicesMSGEPSMulti-Mission • 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] • Surface Albedo & Aerosol • Scattered Radiance Field • Surface Short-wave Fluxes • Land Surface Temperature • Surface Emissivity • Surface Long-wave Fluxes SAF OSI SAF O3M SAF CLM SAF GRM SAF LSA

  41. 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” SAF Visiting Scientists

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