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Algorithms proposed to retrieve water vapor are usually developed using statistical regression. Recent results have shown that this global statistical approach creates systematic geographical errors implying systematic biases. In the particular case of the wet tropospheric correction for altimetry missions, these biases directly distort the sea level estimation. After an in-depth analysis of the retrieval errors, we propose a new approach that significantly improves the quality of the retrieval algorithm.