Meteorological dissemination

HRI A and B Format

Meteosat Image 11 Mai 2001 / Europe

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)

WEFAX CnD, D and E Format

Meteorological Products Extraction Facility

Spin-scan acquisition

Meteosat pictures Water vapour Infra-redVisible

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

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

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

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

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

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

IR window channel (10.8  m)Water vapour channel 6.5  m K 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

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

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

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

Spatial coherence

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

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

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

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

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

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

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

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

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

MSG AMV

Meteosat Winds (transition programme)

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

 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)

Validation efforts: Africa

Validation efforts: Elbe

 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

Satellite Application Facilities (SAFs)

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

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

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

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

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”

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  m spectral band data for the SAFNWC Convective Rainfall Rate product

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