Geophysical Research Letters · 2016 · 163 citations · 21 references
Natural SciencesEarth SciencesMeteorologyAtmospheric ScienceAtmospheric ThermodynamicsTropical MeteorologyData AssimilationInfrared Remote SensingSatellite SensorsTropical ConvectionTropical Cyclone ForecastingTropical CyclonesAll-sky Radiance AssimilationCyclone Data AssimilationEnsemble Kalman FilterObserving System Simulation ExperimentsSatellite Radiance AssimilationState VariablesTropical Cyclone ClimatologyTropical Cyclone Remote Sensing
Abstract The potential impacts of GOES‐R satellite radiances on tropical cyclone analysis and prediction were examined through ensemble correlations between simulated infrared brightness temperatures and various model state variables. The impacts of assimilating GOES‐R all‐sky infrared brightness temperatures on tropical cyclone analysis and prediction were further demonstrated through a series of convection‐permitting observing system simulation experiments using an ensemble Kalman filter under both perfect and imperfect model scenarios. Assimilation of the high temporal and spatial resolution infrared radiances not only constrained well the thermodynamic variables, including temperature, moisture, and hydrometeors, but also considerably reduced analysis and forecast errors in the wind fields. The potential of all‐sky radiances is further demonstrated through an additional proof‐of‐concept experiment assimilating real‐data infrared brightness temperatures from GOES 13 satellite which was operational in an enhanced scanning mode during Hurricane Karl (2010).
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