Clear Sky Radiance: Product Guide

Similar documents
Volcanic Ash Monitoring: Product Guide

Active Fire Monitoring: Product Guide

Clear Sky Radiance (CSR) Product from MTSAT-1R. UESAWA Daisaku* Abstract

MSG MPEF Products focus on GII Simon Elliott Meteorological Operations Division

EUMETSAT Satellite Programmes

Sentinel-3 Marine Test Data Set processed at EUMETSAT

Overview of the IR channels and their applications

The APOLLO cloud product statistics Web service The APOLLO cloud product statistics Web service

Best practices for RGB compositing of multi-spectral imagery

Authors: Thierry Phulpin, CNES Lydie Lavanant, Meteo France Claude Camy-Peyret, LPMAA/CNRS. Date: 15 June 2005

THE USE OF THE HIGH RESOLUTION VISIBLE IN SAFNWC/MSG CLOUD MASK

An Introduction to the MTG-IRS Mission

The APOLLO cloud product statistics Web service

Improved diagnosis of low-level cloud from MSG SEVIRI data for assimilation into Met Office limited area models

VIIRS-CrIS mapping. NWP SAF AAPP VIIRS-CrIS Mapping

GOES-R AWG Cloud Team: ABI Cloud Height

NCDC s SATELLITE DATA, PRODUCTS, and SERVICES

A FOG DETECTING RGB COMPOSITE TECHNIQUE BASED ON THERMAL BANDS OF THE SEVIRI INSTRUMENT

The impact of window size on AMV

The Sentinel-4/UVN instrument on-board MTG-S

Studying cloud properties from space using sounder data: A preparatory study for INSAT-3D

Synoptic assessment of AMV errors

CALCULATION OF CLOUD MOTION WIND WITH GMS-5 IMAGES IN CHINA. Satellite Meteorological Center Beijing , China ABSTRACT

Obtaining and Processing MODIS Data

RESULTS FROM A SIMPLE INFRARED CLOUD DETECTOR

ECMWF Aerosol and Cloud Detection Software. User Guide. version /01/2015. Reima Eresmaa ECMWF

Satellite remote sensing using AVHRR, ATSR, MODIS, METEOSAT, MSG

Solar Irradiance Forecasting Using Multi-layer Cloud Tracking and Numerical Weather Prediction

Validation of SEVIRI cloud-top height retrievals from A-Train data

Suman Goyal Sc E /In-charge SYNOPTIC Application Unit Satellite Meteorology Davison

Outline of RGB Composite Imagery

McIDAS-V Tutorial Displaying Polar Satellite Imagery updated September 2015 (software version 1.5)

FRESCO. Product Specification Document FRESCO. Authors : P. Wang, R.J. van der A (KNMI) REF : TEM/PSD2/003 ISSUE : 3.0 DATE :

GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document For Low Cloud and Fog

METEOSAT. Europe s geostationary

Solarstromprognosen für Übertragungsnetzbetreiber

Estimating Firn Emissivity, from 1994 to1998, at the Ski Hi Automatic Weather Station on the West Antarctic Ice Sheet Using Passive Microwave Data

VALIDATION OF SAFNWC / MSG CLOUD PRODUCTS WITH ONE YEAR OF SEVIRI DATA

Update on EUMETSAT ocean colour services. Ewa J. Kwiatkowska

RPG MWR PRO TN Page 1 / 12 physics.de Radiometer Physics GmbH

USING THE GOES 3.9 µm SHORTWAVE INFRARED CHANNEL TO TRACK LOW-LEVEL CLOUD-DRIFT WINDS ABSTRACT

NOAA NESDIS CENTER for SATELLITE APPLICATIONS and RESEARCH ALGORITHM THEORETICAL BASIS DOCUMENT. ABI Cloud Mask

Product Navigator User Guide

Comparison of NOAA's Operational AVHRR Derived Cloud Amount to other Satellite Derived Cloud Climatologies.

SMOS NRT BUFR specification

High Resolution Information from Seven Years of ASTER Data

Precipitation Remote Sensing

2.3 Spatial Resolution, Pixel Size, and Scale

Cloud detection and clearing for the MOPITT instrument

P1.21 GOES CLOUD DETECTION AT THE GLOBAL HYDROLOGY AND CLIMATE CENTER

Meteorological Forecasting of DNI, clouds and aerosols

SYNERGISTIC USE OF IMAGER WINDOW OBSERVATIONS FOR CLOUD- CLEARING OF SOUNDER OBSERVATION FOR INSAT-3D

Definition of KOMPSAT-3 Product Quality

Cloud Masking and Cloud Products

Satellite Remote Sensing of Volcanic Ash

Hyperspectral Satellite Imaging Planning a Mission

Options for filling the LEO-GEO AMV Coverage Gap Francis Warrick Met Office, UK

2002 A. Werkmeister et al.: Comparing cloud coverage a case study

How to calculate reflectance and temperature using ASTER data

Evaluations of the CALIPSO Cloud Optical Depth Algorithm Through Comparisons with a GOES Derived Cloud Analysis

Files Used in this Tutorial

The Centre for Australian Weather and Climate Research. A partnership between CSIRO and the Bureau of Meteorology

User Perspectives on Project Feasibility Data

3.4 Cryosphere-related Algorithms

IRS Level 2 Processing Concept Status

TI GPS PPS Timing Application Note

Assessing Cloud Spatial and Vertical Distribution with Infrared Cloud Analyzer

CLOUD CLASSIFICATION EXTRACTED FROM AVHRR AND GOES IMAGERY. M.Derrien, H.Le Gléau

Forest fire detection for near real-time monitoring using geostationary satellites

Temporal variation in snow cover over sea ice in Antarctica using AMSR-E data product

Information Contents of High Resolution Satellite Images

ADAGUC & PyTROLL. Maarten Plieger Ernst de Vreede. Application of polar orbiter products in weather forecasting Using open source tools and standards

SEVIRI Fire Radiative Power and the MACC Atmospheric Services

Evaluation of the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius

STAR Algorithm and Data Products (ADP) Beta Review. Suomi NPP Surface Reflectance IP ARP Product

COMPUTING CLOUD MOTION USING A CORRELATION RELAXATION ALGORITHM Improving Estimation by Exploiting Problem Knowledge Q. X. WU

Spectral Response for DigitalGlobe Earth Imaging Instruments

AATSR Technical Note. Improvements to the AATSR IPF relating to Land Surface Temperature Retrieval and Cloud Clearing over Land

Night Microphysics RGB Nephanalysis in night time

A system of direct radiation forecasting based on numerical weather predictions, satellite image and machine learning.

Lake Monitoring in Wisconsin using Satellite Remote Sensing

163 ANALYSIS OF THE URBAN HEAT ISLAND EFFECT COMPARISON OF GROUND-BASED AND REMOTELY SENSED TEMPERATURE OBSERVATIONS

SAFNWC/MSG Cloud type/height. Application for fog/low cloud situations

MODIS Collection-6 Standard Snow-Cover Products

VISUAL INSPECTION OF EO DATA AND PRODUCTS - OVERVIEW

A remote sensing instrument collects information about an object or phenomenon within the

Solar and PV forecasting in Canada

TerraColor White Paper

SATELLITE IMAGES IN ENVIRONMENTAL DATA PROCESSING

DISCRIMINATING CLEAR-SKY FROM CLOUD WITH MODIS ALGORITHM THEORETICAL BASIS DOCUMENT (MOD35) MODIS Cloud Mask Team

GEOMETRIC ACCURACY ASSESSMENT OF MSG-SEVIRI LEVEL 1.5 IMAGERY

Remote sensing of precipitable water vapour and cloud cover for site selection of the European Extremely Large Telescope (E-ELT) using MERIS

Towards agreed data quality layers for airborne hyperspectral imagery

Sky Monitoring Techniques using Thermal Infrared Sensors. sabino piazzolla Optical Communications Group JPL

LSA SAF products: files and formats

IMPROVING THE PERFORMANCE OF SATELLITE-TO-IRRADIANCE MODELS USING THE SATELLITE S INFRARED SENSORS

Final report on RAD service chain evolution

Data Processing Flow Chart

Definition of the community standard for skyglow observations

Basic Climatological Station Metadata Current status. Metadata compiled: 30 JAN Synoptic Network, Reference Climate Stations

Transcription:

Doc.No. Issue : : EUM/TSS/MAN/14/786411 v1a e-signed EUMETSAT Eumetsat-Allee 1, D-64295 Darmstadt, Germany Tel: +49 6151 807-7 Fax: +49 6151 807 555 Date : 2 September 2015 http://www.eumetsat.int WBS : EUMETSAT The copyright of this document is the property of EUMETSAT.

Document Change Record Issue / Revision Date DCN. No Summary of Changes 1 6 October 2010 Initial release of Document 1A 2 September 2015 Added the following content: Product description, content to specify product output and specifications for GRIB-2 Encoded Product. Table of Contents 1 PRODUCT DESCRIPTION... 3 2 PRODUCT SPECIFICATIONS... 4 2.1 Product history... 4 2.2 Known Operations Limitations... 4 3 PRODUCT ILLUSTRATION... 5 4 ALGORITHM COMPONENTS... 7 4.1 Inputs/Dynamic Application Data... 7 4.2 Outputs... 7 4.3 Essential Quality Flags... 8 5 REFERENCES AND LINKS... 9 Reference Documents... 9 Online Resources and Assistance... 9 Page 2 of 9

1 PRODUCT DESCRIPTION The Clear Sky Radiance (CSR) product is a subset of the information derived during the Scenes and Cloud Analysis processing. The product contains information on mean brightness temperatures and radiances from all thermal (infrared and water vapour) channels, for regions containing no or only low-level clouds. The product provides the radiances for a subset of the MSG channels averaged over all pixels identified as clear within a processing segment. This is carried out for all channels except WV6.2, where the CSR is also derived for areas containing low-level clouds. The accuracy of the product depends on the accuracy of the calibrated image data and the accuracy of the scenes analysis processing. The product provides valuable input to numerical weather prediction models. The horizontal resolution is on synoptic scale, 100 km or better. The CSR uses averaging segments of 16 16 pixels about 80 80 km 2 at the sub-satellite point. The product provides valuable input to numerical weather prediction models. The horizontal resolution is on synoptic scale (100 km or better). Example of CSR product on full-disk image. Page 3 of 9

2 PRODUCT SPECIFICATIONS Category Applications and users Product Distribution Product Area Product Resolution Product Distribution Frequency Product Format Product Size Specification Numerical weather prediction GTS EUMETCast EUMETSAT Data Centre FES (Full Earth Scan) Area RSS (Rapid Scanning Service) Area FES: 16 16 pixels RSS: Variable FES Area GTS: hourly for the 00:45, 01:45, 02:45, 23:45 UTC products EUMETCast: hourly for the 00:45, 01:45, 02:45, 23:45 UTC products EUMETSAT Data Centre: hourly for the 00:45, 01:45, 02:45, 23:45 UTC products RSS Area GTS: every 15 minutes for the 00:00, 00:15, 00:30, 23:45 UTC products EUMETCast: every 15 minutes for the 00:00, 00:15, 00:30, 23:45 UTC products EUMETSAT Data Centre: every 15 minutes for the 00:00, 00:15, 00:30, 23:45 UTC products BUFR format FES Area: about 3 MB (variable) RSS Area: about 320 KB (variable) 2.1 Product history Initial development and baseline: Operational start Substantial Revision Substantial gaps in coverage 1997 1998 2001 product upgraded to replace single quality flag with quality index. none 2.2 Known Operations Limitations None Page 4 of 9

3 PRODUCT ILLUSTRATION Figure 1: Full disk scan for channel IR6.2. Colour scheme (at right) shows brightness temperatures in K. Page 5 of 9

Channel: IR7.3 Channel: IR10.8 Page 6 of 9

4 ALGORITHM COMPONENTS 4.1 Inputs/Dynamic Application Data As an input, level 1.5 image data of all channels for every repeat cycle is available for the CSR processing in the form of radiances, or reflectances and brightness temperatures. Also, the CSR product results from the previous repeat cycle and the scenes type information from the Scenes Analysis of the current repeat cycle is available. The visible channels are not processed and the CSR product provides missing values instead. The output for the infrared channels provide brightness temperatures (K) and the eadiance values are also set to missing. Note: The complete algorithm specification is in the ATBD for this product. See the document reference section in Section 5 for the document reference number. Parameter Units Resolution Source Scenes type - pixel CLA int Radiances/reflectances/ brightness temperatures from all channels CSR from previous repeat cycle mwm -2 sr -1 (cm -1 ) -1 % K pixel Derived from Level 1.5 image data mwm -2 sr -1 (cm -1 ) -1 % K CSR processing segment CSR prev Solar Zenith angle pixel Derived from level 1.5 image header data 4.2 Outputs Table 1: Dynamic Application Data required for CSR Product. The following list of output parameters are generated per CSR processing segment for both the final and the intermediate CSR products. CSR channel_1 CSR channel_2 CSR channel_n Parameter Units To mwm -2 sr -1 (cm -1 ) -1, %, K CSR final & intermediate products Location of the CSR for the solar channels (latitude /longitude) Location of the CSR for channel WV6.2 (latitude /longitude) mwm -2 sr -1 (cm -1 ) -1, %, K mwm -2 sr -1 (cm -1 ) -1, %, K CSR final & intermediate products CSR final & intermediate products Location of the CSR for the IR CSR final & intermediate products channels (latitude /longitude) Quality flag - CSR final & intermediate products Page 7 of 9

Parameter Units To Percentage of clear pixels contributing to the CSR for each segment for each channel % CSR final & intermediate products Standard Deviation of clear pixels contributing to CSR for each segment for each channel mwm -2 sr -1 (cm -1 ) -1, %, K CSR final & intermediate products Table 2: Output parameters per CSR Processing Segment for both final and intermediate CSR products. 4.3 Essential Quality Flags Parameter Value Meaning CSR_quality_flag Bit 0: 1 No CSR derived for VIS channels, insufficient number of clear day pixels Bit 1: 1 Bit 2: 1 Bit 3: 1 Bit 4: 1 Bit 5: 1 Bit 6: 1 Bit 7: 1 Bit 8: 1 No CSR derived for WV channels, insufficient number of pixels No CSR derived for IR channels, insufficient number of pixels AQC Temporal Check failed for VIS channels AQC Temporal Check failed for WV channels AQC Temporal Check failed for IR channels AQC Spatial Check failed AQC SD Check failed for VIS channels AQC SD Check failed for WV channels Bit 9: 1 AQC SD Check failed for IR channels Table 3: CSR Quality Flags and Bit breakdown Page 8 of 9

5 REFERENCES AND LINKS Reference Documents Type Detailed Algorithm Validation Document Name MSG Meteorological Products ATBD MSG-3 System Commissioning Product Validation Test Report Reference EUM/MSG/SPE/022 EUM/MSG/REP/12/0190 Online Resources and Assistance All of the reference documents listed above are in the EUMETSAT Technical Documents page. www.eumetsat.int > Satellites > Technical Documents > Meteosat Services > 0 Meteosat Meteorological Products To register for data delivery from this product, go to the Data Registration page on the EUMETSAT web page: www.eumetsat.int > Data > Data Delivery > Data Registration To get answers to any of your questions about data delivery, registration or documentation, contact the EUMETSAT User Service Help Desk: Telephone: +49 6151 807 3660/3770 e-mail: ops@eumetsat.int Page 9 of 9