Abstract

AbstractStatistical 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.

Highlights

  • Altimeter satellite mission data are widely used to monitor sea level and are necessary for understanding the impact of climate change on mean sea level

  • wet tropospheric correction (WTC) is generally derived from brightness temperature (TB) measurements from a nadir-viewing radiometer on board an altimeter mission at two or three dedicated frequencies, one of them being located around the 22.235 GHz water vapor absorption line

  • The aim of this study is to explore the potential benefits and limits of a one-dimensional variational method to retrieve clear-sky WTC over global ocean

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Summary

Introduction

Altimeter satellite mission data are widely used to monitor sea level and are necessary for understanding the impact of climate change on mean sea level. Since altimeters measure the altitude of the satellite above Earth’s surface, retrieving sea level from these measurements requires data processing including instrument/platform corrections, accurate orbit determination, as well as accounting for atmospheric delay and surface effects. With such considerations, global and regional mean sea level (MSL) error budget from 1993 to 2012 range under 0.5 and 3 mm yr, respectively Ablain et al (2012). The atmospheric propagation delay is mainly caused by water vapor in the lower-tropospheric layers and dry a Current affiliation: Laboratoire d’Océanographie et du Climat, OSU ECCE-TERRA, Paris, France. Lower constraints are needed on retrieved humidity around these pressure levels, which implies higher

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