Product User Manual for SAFNWC/MSG “Precipitating
Contents
1. Code SAF NWC CDOP SMHI SCUPUM A Product User Manual for issue 1 5 1 Date 25 May 2010 APA p A Cloud pile SAF NWC CDOP SMHI SCI PUM NWC SAF Page 1 18 The EUMETSAT Network ol 4 Sate ie Application Facilhes p Support lo Nowi asting ond Vory Short Range Forecasting Product User Manual for SAFNWC MSG Precipitating Cloud PC PGE04 v1 5 1 SAF NWC CDOP SMHI SCI PUM 4 Issue 1 Document Revision 5 1 25 May 2010 Applicable to SAFNWC MSG version 2010 Applicable to the following PGE s PGE Acronym Product ID Product name Version number PGEO4 PC SAFNWC MSG PGE04 Precipitating Clouds 15 1 Prepared by SMHI Product User Manual for SAFNWC MSG Precipitating Cloud SMHI PC PGE04 v1 5 1 NWC SAF Code SAF NWC CDOP SMHI SCI PUM 4 Issue 1 5 1 Date 25 May 2010 File SAF NWC CDOP SMHI SCI PUM 4_v1_5_1 DOC Manager Page 2 18 REPORT SIGNATURE TABLE Function Name Signature Date Prepared by SMHI Anke Thoss 25 May 2010 Reviewed by Pilar Fernandez Authorised by AEMET NWCSAF Product User Manual for SAFNWC MSG Precipitating Cloud SMHI PC PGE04 v1 5 1 NWC SAF Code SAF NWC CDOP SMHI SCI PUM 4 Issue 1 5 1 Date 25 May 2010 File SAF NWC CDOP SMHI SCI PUM 4_v1_5_1 DOC Page 3 18 DOCUMENT CHANGE RECORD Date Pages 23 January 2009 New Document for v2009 1 5 2 March 2009 17 Changes a2. e NWP surface temperature Product User Manual for CodeSAF NWC CDOP SMHI SCI PUM 4 SAFNWC MSG Precipitating Issue 1 5 1 Date 25 May 2010 Cloud PC PGE04 v1 5 1 File S AF NWC CDOP SMHI SCI PUM NWC SAF SMHI 1 v1 5 I DOC Page 10 18 2 2 3 Graphical overview of the Precipitating Clouds product PGE04 Sevin NWP Tsurface Cloud Type HRIT data on region PGE02 PGE04 Read prepare input data For each pixel Region configuration PGE04 model config Algorithm configuration Likelihood tables for day and night 2 per day Write output product Calculate global statistics and write to file Free memory PC product Likelihood rain Statistics file Processing flags Figure 1 schematic overview over the Precipitating Clouds product Product User Manual for CodeSAF NWC CDOP SMHI SCI PUM 4 SAFNWC MSG Precipitating Issue 1 5 1 Date 25 May 2010 Cloud PC PGE04 v1 5 1 File SAF NWC CDOP SMHI SCI PUM NWC SAF Page 11 18 2 2 4 Description of the output The precipitating clouds product gives the likelihood of precipitation e Class 1 total precipitation likelihood for rain gt 0 1 mm h e Class2 obsolete set to 0 The likelihood is given in intervals of 10 0 to 5 0 gt 5 to 15 10 gt 15 to 25 20 gt 25 to 35 30 gt 35 to 45 40 gt 45 to 55 50 gt 55 to 65
3. French gauge data set 2004 verified against 30 min averages in gauge data Blue high and very high clouds red medium level clouds green thick cirrus cyan cirrus over lower clouds 13 Figure 4 Likelihood of rain versus observed rain frequency Same as Figure 3 but for night time 13 Figure 5 Example of the precipitating clouds product with a change from day to night algorithm diagonally over the British isles northward night algorithm south day algorithm Please note typical features precipitation area more spread out for night time algorithm less detailed features and no high precipitation likelihood At high satellite viewing angles the product becomes unreliable as seen by high precipitation likelihood at the rim of the Meteosat disk do not use for satellite viewing angles exceeding 60 degrees 13 Code SAF NWC CDOP SMHI SCI PUM 4 Product User Manual for Issue 1 5 1 Date 25 May 2010 SAFNWC MSG Precipitating Cloud File SAF NWC CDOP SMHI SCI PUM SMHI PC PGE04 v1 5 1 4_v1_5_1 DOC NWCSAE Page 6 18 1 INTRODUCTION The Eumetsat Satellite Application Facilities SAF are dedicated centres of excellence for processing satellite data and form an integral part of the distributed EUMETSAT Application Ground Segment http www eumetsat int This documentation is provided by the SAF on Support to Nowcasting and Very Short Range Forecasting SAFNWC The main objective of SAFNWC is to provide further devel
4. NWC CDOP SMHI SCI PUM 4 SAFNWC MSG Precipitating Issue 1 5 1 Date 25 May 2010 Cloud PC PGE04 v1 5 1 File S AF NWC CDOP SMHI SCI PUM NWC SAF Page 18 18 7 EXAMPLE OF PRODUCT VISUALISATION MODERATE PREC PROBABILITY 65 100 j SRFNHC PGEO4 Figure 5 Example of the precipitating clouds product with a change from day to night algorithm diagonally over the British isles northward night algorithm south day algorithm Please note typical features precipitation area more spread out for night time algorithm less detailed features and no high precipitation likelihood At high satellite viewing angles the product becomes unreliable as seen by high precipitation likelihood at the rim of the Meteosat disk do not use for satellite viewing angles exceeding 60 degrees
5. simple way to convert likelihood estimates into easily verifiable estimates of precipitation is to set a threshold for rain according to algorithm performance Which threshold of total precipitation likelihood does best divide the precipitating from the non precipitating events Usually 20 or 30 of total precipitation likelihood The performance of this hard clustering is verified using contingency tables Evaluating the performance at different threshold levels gives also an overview of how closely assigned probability values match real occurrence of rain as illustrated in Figure 3 and Figure 4 Hungarian dataset French dataset Cloud type dependent tuning Cloud type dependent tuning Day algorithm Day algorithm 80 70 X 70 X 60 g 60 E 50 kg g 40 a 9 30 g 3o z P 20 8 20 2 10 10 0 0 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 Likelihood of rain Likelihood of rain CT 11 44 CT 9 10 _CT 11 14 CT 9 10 Gl 17 CI 18 tj 1 CT 18 Figure 3 Likelihood of rain from PC product versus observed rain frequency Cloud type dependent tuning on French gauge data Left independent validation against Hungarian gauge data 2004 right performance on dependent French gauge data set 2004 verified against 30 min averages in gauge data Blue high and very high clouds red medium level clouds green thick cirrus cyan cirrus over lower clouds Product User S
6. 60 gt 65 to 75 70 gt 75 to 85 80 gt 85 to 95 90 gt 95 to 100 100 Please pay attention to that the value in the HDF5 dataset has to be multiplied by the scaling factor 10 as specified in the HDF file to arrive at the correct likelihood The product is supplied in HDF5 format and has the same resolution as in the original SEVIRI image Special count 152 150 used when no data value is available The forecaster is likely to receive the product displayed as an image similar to Figure 2 Using the 20 class as a threshold for precipitation detection gives a fairly save estimate of possible precipitation although some light to moderate precipitation migh be missed deep green in Figure 2 Using 30 as theshold light green in Figure 2 provides usually a subjectively better fit to radar data but more real precipitation remains undetected while there is still a slight overestimation of precipitation area 2 2 4 1 Flags The product contains also quality information in a separate field The quality information is indicating under which circumstances the PC product was derived Except for the field indicating whether solar channels were used it should not be of much interest to the forecaster and most likely it will not be required to visualize this information Product User Manual for CodeSAF NWC CDOP SMHI SCI PUM 4 SAFNWC MSG Precipitating Issue 1 5 1 Date 25 May 2010 Cloud PC PGE04
7. AFNWC MSG NWC SAF SMHI Manual for CodeSAF NWC CDOP SMHI SCI PUM 4 Precipitating Issue 1 5 1 Cloud PC PGE04 v1 5 1 Date 25 May 2010 File SAF NWC CDOP SMHI SCI PUM 4 v1 5 I DOC Page 16 18 Hungarian dataset Night algorithm dispersed on cloud type Observed rain freq 0 10 20 30 40 50 60 70 Likelihood of rain CT 11 14 CT 9 10 CT 18 53 French dataset Night algorithm dispersed on cloud type y o o mco RB Oo O O O eo Observed rain freq 96 k o 0 0 10 20 30 40 50 60 70 Likelihood of rain CT 11 14 CT 9 10 CT 17 CT 18 Figure 4 Likelihood of rain versus observed rain frequency Same as Figure 3 but for night time Algorithm performance can be summarized as follows e At the 20 detection threshold day and night algorithms perform almost equally well whereas the day algorithm clearly exhibits more skill at the 30 threshold than the night algorithm 20 can be used as a kind of hardclustering threshold for precipitation but thresholding at 30 generally gives a better subjective fit to radar precipitation areas e Day and nighttime algorithms exhibit different characteristics and discontinuities at the day night deliminator are apparent see Figure 5 With just using IR channels at night there are less areas assigned high precipitation likelihood and the precipitation areas are less defi
8. WC Product Requirements Document SAF NWC INM MGT PRD Table 2 List of Referenced Documents 28 07 2009 Product User Manual for CodeSAF NWC CDOP SMHI SCI PUM A SAFNWC MSG Precipitating Issue 1 5 1 Date 25 May 2010 Cloud PC PGE04 v1 5 1 File SAF NWC CDOP SMHI SCI PUM NWC SAF Page 8 18 1 7 SCIENTIFIC UPDATES SINCE MSG VERSION 2009 No scientific updates have been implemented since product version 1 3 released spring 2007 Product User Manual for CodeSAF NWC CDOP SMHI SCI PUM 4 SAFNWC MSG Precipitating Issue 1 5 1 Date 25 May 2010 Cloud PC PGE04 v1 5 1 File SAF NWC CDOP SMHI SCI PUM NWC SAF Page 9 18 2 DESCRIPTION OF THE PRODUCT 2 1 GOAL OF THE PC PRODUCT Goal of the PC product is to give a first guideline to the forecaster where to expect precipitation especially for areas where no radar data is available The product provides the probability of precipitation for each Meteosat pixel Since the coupling of radiances from visible and infrared channels with precipitation is rather weak large areas are marked as potentially precipitating more than 1046 precipitation likelihood The skill the derive stratiform precipitation is limited and potential precipitation area is overestimated but indicating low likelihood Strong convective precipitation can be better estimated from METEOSAT data than rain from stratiform precipitation and the NWCSAF convective rain rate product
9. and MSG Meteosat second generation Hydrological Institute NIR Near Infrared SW SoftWare NORDRAD Nordic Weather Radar Network TOA Top Of Atmosphere NWP Numerical Weather Prediction USGS U S Geological Survey PC Precipitating Cloud also VIS Visible PGE04 For a list of SAF acronyms see also RD 1 1 6 REFERENCES 1 6 1 Applicable Documents Reference Title Code Vers Date AD 1 Validation Report for Precipitating Clouds PC SAF NWC CDOP SMHI SCI VR 01 1 4 19 11 07 PGEO04v1 4 AD 2 Software User Manual for the SAFNWC MSG SAF NWC CDOP INM SW SUM 2 4 0 16 02 2009 Application Software Part AD 3 Interface Control Document for the External SAF NWC CDOP INM SW ICD 1 4 0 2010 and Internal Interfaces of the SAFNWC MSG AD 4 SAFNWC MSG Output Product Format SAF NWC CDOP INM SW ICD 3 4 0 2010 Definition AD 5 Architectural Design Document for the SAF NWC CDOP INM SW AD 1 4 0 2010 SAFNWC AD 6 Algorithm Theoretical Basis Document for SAF NWC CDOP SMHI SCI ATBD 1 5 1 25 05 2010 Precipitating Clouds PC PGE04 v1 5 1 04 AD 7 Cross Verification of the Rapid Visiting scientist report by 15 11 2009 Development Thunderstorm and the Eszter L b Maria Putsay Precipitation Products of the Zs fia Kocsis and lldik Nowcastion and Vert Short Range Szenyan Forecasting SAF Table 1 List of Applicable Documents 1 6 2 Reference Documents RD 1 The Nowcasting SAF Glossary SAF NWC CDOP INM MGT GLO 10 11 2009 RD 2 SAFN
10. and the rapidly developing thunderstorm product can be consulted for more detailed analysis of severe convection 2 2 OUTLINE OF THE PRECIPITATING CLOUD ALGORITHM 2 2 1 General algorithm design The precipitating clouds product gives the total likelihood of precipitation without attempting to estimate intensity To derive the likelihood of precipitation a precipitation Index PI is constructed from those IR and visible spectral features which are most correlated with precipitation The precipitation likelihood for each value of the PI is determined statistically by comparison with collocated precipitation measurements For the tuning of the current algorithm version French gauge network measurements for one year of data were used In the calculation of the PI special attention has been given to spectral features in the visible which implicitly contain information on cloud microphysical properties at the cloud top such as effective radius and cloud phase The algorithm employed is cloud type dependent in the sense that mapping from PI to precipitation likelihood makes use of cloud type dependent lookup tables For the PI calculation a day and a night version exists where the night version only makes use of IR channels not influenced by sunlight 2 2 2 Data sources for Precipitationg Clouds e Meteosat visible and IR channels Daytime vis0 6 NIR1 6 IR3 9 IR6 2 IR7 3 IR10 8 IR12 0 Nighttime IR6 2 IR7 3 IR10 8 IR12 0 e Cloud type product
11. avSes bande tend 13 LED VALIDATION 13 5l SUMMARY OF VALIDATION RESULTS rioei oe E EN OA EN ERR TH UR EU PIU ER E PIENO 13 6 KNOWN PROBLEM AREAS AND LIMITATIONS essesesssesesssecsscsccssoceessecescsecescoeesseceessecsssoeesscoeessocse 13 7 EXAMPLE OF PRODUCT VISUALISATION eene estne reta ntn tata stata tn sinet tassa ssa ta sins sa tassa estan 13 Code SAF NWC CDOP SMHI SCUPUM A Product User Manual for issue 1 5 1 Date 25 May 2010 SAENWC MSG Precipitating Cloud yo SAF NWC CDOP SMHI SCI PUM SMHI PC PGE04 v1 5 1 4_v1_5_1 DOC NWC SAE Page 5 18 List of Tables and Figures Table 1 Listor Applicable Documents rsrsrsr eenn reae bete erer le rr retri rhet 7 Table 2 LisEor Referenced i teint aperiret teri eei tei o pee hob e eere rrera r rE Errr e EEr etu ieee 7 Table Quahty flags ot PGEOA icenic atch eieren e erare Pepe ba ar rarere arbre r arr erinti 12 Figure 1 schematic overview over the Precipitating Clouds product 10 Figure 2 200901241200 precipitating clouds product over MSG N configured for day algorithm Dark green hues present precipitation likelihood classes 10 20 light green 30 yellow40 and orange red hues 50 and higher 12 Figure 3 Likelihood of rain from PC product versus observed rain frequency Cloud type dependent tuning on French gauge data Left independent validation against Hungarian gauge data 2004 right performance on dependent
12. dmin we refer to the Software User Manual AD 2 which will of course also be relevant for the science admin For the person interested in the algorithms in detail we refer to the Algorithm theoretical Basis Document AD 6 1 4 SOFTWARE VERSION IDENTIFICATION This document describes the algorithms implemented in the PGE04 version v1 6 of the 2010 SAFNWC MSG software package delivery 1 5 DEFINITIONS ACRONYMS AND ABBREVIATIONS Acronym Explanation Acronym Explanation CDOP Continuous Development and CM Cloud Mask also PGEOI Operational Phase CT Cloud Type also PGE02 Product User PC PGE04 v1 5 1 Manual for SAFNWC MSG Precipitating Cloud Issue File SAF NWC CDOP SMHI SCI PUM Code SAF NWC CDOP SMHI SCI PUM 4 1 5 1 Date 25 May 2010 SMHI 4_v1_5_1 DOC NWC SAF Page 7 18 Acronym Explanation Acronym Explanation CTTH Cloud Top Temperature Height PCPN Precipitation and Pressure also PGE03 PGE Process Generating Element EUMETSAT European Organisation for the PI Precipitation Index Exploitation of Meteorological POD Probability Of Detection Satellites POFD Probability Of False Detection FAR False Alarm Rate RGB Red Green Blue FOV Field Of View SAF Satellite Application Facility HDF5 Hierarchical Data format SAFNWC Satellite Application Facility version 5 for support to NoWcasting IR Infrared SEVIRI Imager onboard MSG satellites LUT Look Up Table SMHI Swedish Meteorological
13. fter DRI 2009 Corrected erroneous references and add short reference names Acronym list updated Erroneous reference to PPS in chapter 1 3 deleted Applicable documents dates and codes updated clarified reference to last scientific update in section 1 7 1 5 1d 19 April 2010 22 no scientific updates Adapted date issue and revision to v 2010 Included reference to VS report nov 2009 25 May 2010 Added the full NWCSAF logotype on first page CHANGE S Code SAF NWC CDOP SMHI SCI PUM 4 Product User Manual for Issue 1 5 1 Date 25 May 2010 SAENWC MSG Precipitating Cloud Fe SAF NWC CDOP SMHI SCI PUM SMHI PC PGE04 v1 5 1 4 v1 5 I DOC NWC SAE Page 4 18 Table of contents L INTRODUCTION eoe sces esose aeaa a O va cu cea oci NEE E 6 1 SCOPEOP THE DOCUMENT eeesaceteetsetes eco ct a e oet estet bee tee eroe chere be tree ete Rte ocu tee E EEEE eb E RETES 6 1 2 SCOPE OF OTHER DOCUMENTS 5 rote teeecott enter eere iE E EEE EENE EET e ded 6 1 3 WHO SHOULD READ THIS MANU NE 5 1 iot ote eot oet Erea eM e tote aE Pot etate e tee te eet rooted 6 1 4 SOFTWARE VERSION IDENTIEICATIQDRN cadet cette tete oett ete th t tee eroe oc a a E ERE e Po tere eco tcn rr E EEE eet Tode ied 6 1 5 DEFINITIONS ACRONYMS AND ABBREVIATIONS ccsssesececececsesseaececececsessnaececececsensaeaeeeeeesessnssaeeeeeees 6 1 6 REFERENCE c 7 LOT Apphcable DOcinertS sis
14. he forecaster is that the region is configurable However auxiliary data for a new region has to be compiled beforehand The product generation is usually scheduled automatically by the task manager Product User Manual for CodeSAF NWC CDOP SMHI SCI PUM 4 SAFNWC MSG Precipitating Issue 1 5 1 Date 25 May 2010 Cloud PC PGE04 v1 5 1 File SAF NWC CDOP SMHI SCI PUM NWC SAF Page 14 18 4 INPUTS AND CONFIGURABLE PARAMETERS 4 1 LIST OF INPUTS Please note that the precipitating cloud product PGE04 requires the cloudtype product as input PGEO2 and for that even the Cloudmask product has to be run PGEOI NWP surface temperature Sun zenith satellite view zenith and sun satellite view relative azimuth difference angle Output from Cloud Type Seviri data 4 2 CONFIGURABLE PARAMETERS The Precipitating Cloud product has been designed to allow a full configuration and flexibility to update tune the algorithm without having to modify the code However most of these configurable parameters are only of interest to the developer The only configurable parameters potentially of interest to the users are the configuration of when to switch from day to nighttime scheme and that it is in principle possible to define which cloud types are treated as potentially raining e The default configuration is that the night time algorithm is activated when the sun zenith angle is greater than 80 degrees It is possible to conf
15. iane aniran P STI E EAE Fe Eee Dy ETERN deans E 7d 4 0 2 Reference Documents uitiis er iiz i UE OUR MEE FIR ACH BELA E RIR RU QUEM UTI GEL HRS ERE RI ERI MIR tesatioee 7 17 SCIENTIFIC UPDATES SINCE MSG VERSION 2000 ccccccscsssssssscsssssssssssscsscscecscssscscsessscsesensssnsseseseseses 8 2 DESCRIPTION OF THE PRODUCT wisssisccsscscssssesssscssccsenessssssscasccsencsvadaoncsseasebeasssnesssed edessusaasecensssnessessses 9 2 1 GONIDOPTHEPC PRODUCTS tnt RI HEN MIEL LE EUM 9 22 QUTLINE OF THE PRECIPITATING CLOUD ALGORITHM ciat eas vedusys ate aa vate Ug sadn sas vade o UY vete eon CR Deo Eq UE UOTE 9 224 JGeneyabulsop hin dete stes DNUS HA RAO RE DURA CAPRA FAM MAR DU MU DIE A IUE 9 2 2 2 JDat sources Jor Precipitationg C lauds oerte erts S A PETR CREAR ATEUNEAR ce XR ERA SYUA EN OEO 9 2 2 3 Graphical overview of the Precipitating Clouds product PGEOA4 eee 10 2 24 Description of Ihe oWIpUE sees esee RS IET EN SENS A denen ERES TUNSAR S ANERTSR AEO 1I RI SAUSNCS JUE ar n EN EER OEE RO AAA ORAE EN 12 IMPLEMENTATION OF THE PRODUCT beissssssssccsssscassesssssaveasssssveseseessecesvnesssavenssosevansssvavessasscsssasnsees 13 INPUTS AND CONFIGURABLE PARAMETERS 0 sscccsssssccssssccesssccccssscccscssccesssnacccesscsecessscecesssees 13 4 1 LISTOPTNPUTS ete te HEIN te UE Ue eae e Net rettet paste rd eere eet edo 13 4 2 CONFIGURABLE PARAMETERS concorrono oss tite oett eet a vet ion eec Ee Past ee buen voe bapbvstiods
16. igure the product to only use the night algorithm by setting the sun zenith angle threshold to 0 in the algorithm configuration file This would avoid discontinuities in the product at the day night deliminator on the cost of degrading performance during day time e n principle it is possible to configure which cloud classes are treated as potentially raining Please consult the NWCSAF helpdesk before changing the validated default configuration The possible configurable parameters are described in the Software User Manual AD 2 Product User Manual for CodeSAF NWC CDOP SMHI SCI PUM A SAFNWC MSG Precipitating Issue 1 5 1 Date 25 May 2010 Cloud PC PGE04 v1 5 1 File SAF NWC CDOP SMHI SCI PUM NWC SAF Page 15 18 5 VALIDATION 5 1 SUMMARY OF VALIDATION RESULTS The PC product can be validated against co located radar data synop current weather observations or rain gauge data For more information on product validation see validation reports AD 1 and AD 6 When verifying likelihood results of the PC product it is important to somehow quantify the algorithm performance and give guidance to answer the question whether it is raining or not It is important to understand that a simplified categorical estimate which has been derived from the likelihood distribution degrades the product on the one hand no fair comparison but on the other hand makes it more practical to use for the forecaster A
17. ned at night time For the night time algorithm precipitation occurrence is more strongly overestimated in winter in summer more actual precipitation is missed Both at 20 and 30 threshold precipitation occurrence is overestimated e The work with separating cloud types has shown that gt Cloud type class 9 10 medium level cloud precipitation is overestimated at 20 percent detection level gt Cloud type class 17 and 18 thick cirrus and cirrus over lower cloud give bad results overall gt Cloud type class 11 14 high and very high cloud seems to be the easiest to handle gt Considering cloud low clouds CT 8 as possibly precipitating might be considered in the following versions NWC SAF SMHI Product User Manual for SAFNWC MSG Precipitating Cloud PC PGE04 v1 5 1 CodeS AF NWC CDOP SMHI SCI PUM 4 Issue 1 5 1 Date 25 May 2010 File SAF NWC CDOP SMHI SCI PUM 4 v1 5 I DOC Page 17 18 6 KNOWN PROBLEM AREAS AND LIMITATIONS e The current version of the product contains a certain dependence on sun zenith angle e There is also a clear jump in algorithm performance between day and night algorithm which cannot be totally avoided e The product degrades considerably at high viewing angles and use for viewing angles greater than 60 degrees is not recommended e The algorithm does currently not detect any precipitation from low clouds Product User Manual for CodeSAF
18. op and maintain software packages to be used for Nowcasting applications of operational meteorological satellite data by National Meteorological Services More information can be found at the SAFNWC webpage http www nwcsaf org This document is applicable to the SAFNWC processing package for Meteosat satellites meteorological satellites SAFNWC MSG 1 1 SCOPE OF THE DOCUMENT This document is the Product User Manual for the SAFNWC MSG Precipitating Clouds product The document describes how to use the product after installation It is meant to support the interpretation as well as describe the possibilities and limitations 1 2 SCOPE OF OTHER DOCUMENTS The algorithm used in the Precipitating Clouds Product is described in more detail in the corresponding Algorithm Theoretical Basis document AD 6 Validation of the algorithm is detailed in the Validation report for Precipitating Clouds AD 1 Instructions how to install configure and execute the software are given in the Software User Manual for NWCSAF MSG Package AD 2 The Interface Control Documents AD 3 for the External and Internal Interfaces of the SAFNWC MSG and AD 4 MSG Output Product Format Definition detail the input and output data format for the SAFNWC MSG software 1 3 WHO SHOULD READ THIS MANUAL This document is intended for the end user i e the forecaster For the person in charge of building and installing the MSG software package thus the sys a
19. v1 5 1 File S AF NWC CDOP SMHI SCI PUM NWC SAF Page 12 18 Bit Meaning of he bit 1 0 O0 Processed non processed 1 MSG channels missing not missin CT used not used MSG land no land High terrain no high terrain 6 NWP data missing not missing 7 MSG cloud mask low quality no low quality Table 3 Quality flags of PGEO4 2 3 MSG solar channels used not used 4 5 The quality information is indicating under which circumstances the PC product was derived 2 2 5 Statistics file The statistics file is an ASCII file summarising the distribution of probabilities over the complete region It can be easily used for verification whether 2 runs are identical Files may also be used to easily accumulate statistics on general algorithm performance MODERATE PREC PROBABILITY 65 100 copuriaht 2009 EUMETSAT SAFNWC PC1 24 JAN O9 12 00 Figure 2 200901241200 precipitating clouds product over MSG N configured for day algorithm Dark green hues present precipitation likelihood classes 10 20 light green 30 yellow40 and orange red hues 50 and higher NWC SAF SMHI Product User Manual for SAFNWC MSG _ Precipitating Cloud PC PGE04 v1 5 1 CodeSAF NWC CDOP SMHI SCI PUM 4 Issue 1 5 1 Date 25 May 2010 File SAF NWC CDOP SMHI SCI PUM 4 vl_5_1 DOC Page 13 18 3 IMPLEMENTATION OF THE PRODUCT The implementation is described in Software User Manual AD 2 Interesting for t
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