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A 1D-Var Approach to Retrieve Clear-Sky Wet Tropospheric Correction from Current and Future Altimetry Missions

Abstract : Abstract Statistical methods are usually used to provide estimations of the wet tropospheric correction (WTC), necessary to correct altimetry measurements for atmospheric path delays, using brightness temperatures measured at two or three low frequencies from a passive microwave radiometer on board the altimeter mission. Despite their overall accuracy over oceanic surfaces, uncertainties still remain in specific regions of complex atmospheric stratification. Thus, there is still a need to improve the methods currently used by taking into account the frequency-dependent information content of the observations and the atmospheric and surface variations in the surroundings of the observations. In this article we focus on the assimilation of relevant passive microwave observations to retrieve the WTC over ocean using different altimeter mission contexts (current and future, providing brightness temperature measurements at higher frequencies in addition to classical low frequencies). Data assimilation is performed using a one-dimensional variational data assimilation (1D-Var) method. The behavior of the 1D-Var is evaluated by verifying its physical consistency when using pseudo- and real observations. Several observing-system simulation experiments are run and their results are analyzed to evaluate global and regional WTC retrievals. Comparisons of 1D-Var-based TWC retrieval and reference products from classical WTC retrieval algorithms or radio-occultation data are also performed to assess the 1D-Var performances.
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https://hal-meteofrance.archives-ouvertes.fr/meteo-03657912
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Submitted on : Tuesday, May 3, 2022 - 3:47:15 PM
Last modification on : Monday, May 16, 2022 - 8:20:22 AM

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Laura Hermozo, Laurence Eymard, Fatima Karbou, Bruno Picard, Mickael Pardé. A 1D-Var Approach to Retrieve Clear-Sky Wet Tropospheric Correction from Current and Future Altimetry Missions. Journal of Atmospheric and Oceanic Technology, American Meteorological Society, 2019, 36 (3), pp.473-489. ⟨10.1175/JTECH-D-17-0133.1⟩. ⟨meteo-03657912⟩

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