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Potential impacts of assimilating all‐sky infrared satellite radiances from GOES‐R on convection‐permitting analysis and prediction of tropical cyclones
Author(s) -
Zhang Fuqing,
Minamide Masashi,
Clothiaux Eugene E.
Publication year - 2016
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2016gl068468
Subject(s) - data assimilation , environmental science , tropical cyclone , satellite , meteorology , sky , brightness , ensemble kalman filter , brightness temperature , infrared , atmospheric infrared sounder , remote sensing , kalman filter , geology , troposphere , computer science , physics , extended kalman filter , astronomy , artificial intelligence , optics
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).