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• W2045407218 abstract "Abstract A comparison of the impact of infrared (IR), microwave (MW), and radio occultation (RO) observations on NCEP’s operational global forecast model over the month of March 2013 is presented. Analyses and forecasts with only IR, MW, and RO observations are compared with analyses and forecasts with no satellite data and with each other. Overall, the patterns of the impact of the different satellite systems are similar, with the MW observations producing the largest impact on the analyses and RO producing the smallest. Without RO observations, satellite radiances are over– or under–bias corrected and RO acts as an anchor observation, reducing the forecast biases globally. Positive correlation coefficients of temperature impacts are generally found between the different satellite observation analyses, indicating that the three satellite systems are affecting the global temperatures in a similar way. However, the correlation in the lower troposphere among all three systems is surprisingly small. Correlations for the moisture field tend to be small in the lower troposphere between the different satellite analyses. The impact of the satellite observations on the 500-hPa geopotential height forecasts is much different in the Northern and Southern Hemispheres. In the Northern Hemisphere, all the satellite observations together make a small positive impact compared to the base (no satellite) forecasts. The IR and MW, but not the RO, make a small positive impact when assimilated alone. The situation is considerably different in the Southern Hemisphere, where all the satellite observations together make a much larger positive impact, and all three observation types (IR, MW, and RO) make similar and significant impacts." @default.
• W2045407218 created "2016-06-24" @default.
• W2045407218 creator A5047639348 @default.
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• W2045407218 date "2014-10-24" @default.
• W2045407218 modified "2023-10-13" @default.
• W2045407218 title "Impact of Infrared, Microwave, and Radio Occultation Satellite Observations on Operational Numerical Weather Prediction" @default.
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• W2045407218 doi "https://doi.org/10.1175/mwr-d-14-00101.1" @default.
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