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Evaluation of the Met Office global forecast model using Geostationary Earth Radiation Budget (GERB) data
Author(s) -
Allan Richard P.,
Slingo Anthony,
Milton Sean F.,
Brooks Malcolm E.
Publication year - 2007
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.166
Subject(s) - environmental science , geostationary orbit , parametrization (atmospheric modeling) , meteorology , earth's energy budget , convection , satellite , cloud cover , geostationary operational environmental satellite , outflow , cloud top , energy budget , climatology , outgoing longwave radiation , atmospheric sciences , radiative transfer , cloud computing , geology , radiation , geography , physics , quantum mechanics , astronomy , computer science , thermodynamics , operating system
Simulations of the top‐of‐atmosphere radiative‐energy budget from the Met Office global numerical weather‐prediction model are evaluated using new data from the Geostationary Earth Radiation Budget (GERB) instrument on board the Meteosat‐8 satellite. Systematic discrepancies between the model simulations and GERB measurements greater than 20 Wm −2 in outgoing long‐wave radiation (OLR) and greater than 60 Wm −2 in reflected short‐wave radiation (RSR) are identified over the period April–September 2006 using 12 UTC data. Convective cloud over equatorial Africa is spatially less organized and less reflective than in the GERB data. This bias depends strongly on convective‐cloud cover, which is highly sensitive to changes in the model convective parametrization. Underestimates in model OLR over the Gulf of Guinea coincide with unrealistic southerly cloud outflow from convective centres to the north. Large overestimates in model RSR over the subtropical ocean, greater than 50 Wm −2 at 12 UTC, are explained by unrealistic radiative properties of low‐level cloud relating to overestimation of cloud liquid water compared with independent satellite measurements. The results of this analysis contribute to the development and improvement of parametrizations in the global forecast model. Copyright © 2007 Royal Meteorological Society