Journal of Geophysical Research Atmospheres · 2005 · 246 citations · 36 references
Natural SciencesEarth SciencesMeteorologyAtmospheric RadiationAtmospheric ScienceNumerical Weather PredictionAerosol Radiative EffectsAerosol Remote SensingCloud Radiative EffectsRadiation BalanceRadiative ForcingSurface Radiation BudgetDust Radiative EffectsLongwave Radiation FluxLongwave Radiative FluxesLongwave Radiative ForcingLongwave Radiative TransferMineral Dust AerosolsOutgoing Longwave RadiationSatellite Remote Sensing Data
Measurements of the top‐of‐the‐atmosphere outgoing longwave radiation (OLR) for July 2003 from Meteosat‐7 are used to assess the performance of the numerical weather prediction version of the Met Office Unified Model. A significant difference is found over desert regions of northern Africa where the model emits too much OLR by up to 35 Wm −2 in the monthly mean. By cloud‐screening the data we find an error of up to 50 Wm −2 associated with cloud‐free areas, which suggests an error in the model surface temperature, surface emissivity, or atmospheric transmission. By building up a physical model of the radiative properties of mineral dust based on in situ, and surface‐based and satellite remote sensing observations we show that the most plausible explanation for the discrepancy in OLR is due to the neglect of mineral dust in the model. The calculations suggest that mineral dust can exert a longwave radiative forcing by as much as 50 Wm −2 in the monthly mean for 1200 UTC in cloud‐free regions, which accounts for the discrepancy between the model and the Meteosat‐7 observations. This suggests that inclusion of the radiative effects of mineral dust will lead to a significant improvement in the radiation balance of numerical weather prediction models with subsequent improvements in performance.
36
AERONET—A Federated Instrument Network and Data Archive for Aerosol Characterization
B. N. Holben, T. F. Eck, I. Slutsker et al. · Remote Sensing of Environment · 1998 · 8.5K citations · Full text