MSG validation: An Ongoing Process
Paul de Valk(KNMI), Catherine Naud(UCL),
Marcel Derrien, Herve LeGleau(CMS), Tim Smyth (PML), Elizabeth Slack, Charles Wrench (RAL)
Royal Netherlands Meteorological Institute [email protected]
Contents
Introduction Data: Cloud Top Height SAF-
NWC Results Conclusions
CLOUDMAP2 (funded till January 2004)
Production and exploitation of value-added
remote sensing data products on cloud properties and water vapour distributions to characterise sub-grid scale processes within Numerical Weather Prediction Models (NWP)
through validation and data assimilation.
www.cloudmap.org
Data for validation of Cloud Top Height CTH
SAF-NWC products based on MSG (cloud type, coverage, CTH) 11 and 12 hr
MODIS products produced PML (coverage, CTP)
Chilbolton 94 GHz Radar products (CTH)
Problems encountered Collocation, spatial and temporal Slanted views (polar vs
geostationary) Different pixel size dimensions Different volume sampling Conversion CTP to CTH (HiRLAM)A solution: consider only high coverage
MODIS PML vs SAF-NWC MSG(red line)
Sept 2003 Oct Nov
CTH
Latitudinal dependency, MODIS vs MSG [RED]
< 40 degree 40-45degree > 70 degree
September
Low Medium
High
SemitransparentOver lower
Cloud type dependency of CTH for OctoberMODIS vs MSG [RED]
94 GHz RADAR vs SAF-NWC MSG(red line)
CTH
Sep-Dec2003
RADARVs MSGaverage
BoxesIndicate Max min
Statistics of CTH comparison
Modis vs MSG Bias[m] Std dev [m]
Number
Sept -210 2025 1947574
Oct -200 2261 1523472
Nov -386 2319 2567726
Dec -1080 2649 532402
Radar vs MSG -502 2659 33
Only < 10 km 190 1913 28
Conclusions Good agreement both with MODIS
and Radar, especially high clouds Indication of overestimation of CTH
for low clouds by SAF-NWC but… Latitudinal dependency and Cloud
type dependency of MSG CTH. MODIS PML CTH frequency low at
4000 m