Open AccessThe global relocatable regional weather prediction model of the German Military Geophysical Office
Author(s) -
Prenosil Thomas,
Amtmann Richard,
Derichs Heinz
Publication year - 1999
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1017/s1350482799001152
Subject(s) - stereographic projection , mercator projection , geographic coordinate system , meteorology , grid , coordinate system , computer science , trajectory , numerical weather prediction , domain (mathematical analysis) , latitude , data assimilation , longitude , map projection , geology , geodesy , geography , artificial intelligence , mathematics , geometry , mathematical analysis , physics , astronomy
A regional numerical weather prediction system, consisting of an analysis scheme, a forecast model and a variety of interpretation, visualization and military application tools, named ‘BLM’ has been routinely operating at the German Military Geophysical Office (GMGO) since 1984. At that time, the grid domain was confined to Central Europe and parts of the North Atlantic, where a polar stereographic map projection was appropriate. Owing to increasing user demands, the system had to be made relocatable to provide numerical forecasts at any location of the globe. The relocatable version, called ‘RBL’, is still formulated on a stereographic plane, which is now defined using a rotated geographical system with an artificial north pole right in the middle of the domain. This approach is well known. However, most of the current numerical weather prediction systems are defined on a horizontal latitude–longitude grid, so that the equator in rotated coordinates runs through the centre of the forecast area. The main advantages of the horizontal coordinate transformation used by the ‘RBL’ are numerical stability for a large and economical time step, which enables the model to be run on a computer with limited power, and an invariant map factor all over the globe, which eases the interpretation of the model results for different locations. Copyright © 1999 Royal Meteorological Society