Paper
8 December 1999 Comparing SSM/I and TMI for the estimation of atmospheric water vapor and cloud liquid water over the Mediterranean Sea
Stefano Nativi, Stefano Migliorini, Dino Giuli
Author Affiliations +
Abstract
Knowledge of water cycle in the atmosphere: that is the amount of water in its three phases is very useful for several applications, such as: weather forecasting, latent heat flux estimation, sea-atmosphere interaction. The present work showed a comparison of total precipitable water and cloud liquid water content retrievals from the well-known SSM/I and the new TMI radiometers, utilizing a physical-based inversion scheme -- developed at the PIN of the University of Florence. The estimations obtained through the physical-based inversion scheme are compared against those worked out thorough well- accepted empirical scheme based on SSM/I data. Hence, a validation of the physical-based inversion scheme, was achieved. For this purpose, a specific data-set was collected and analyzed, obtaining near-coincident crossing of the two radiometers over the Mediterranean sea. This is a contribution to understand the applicability of algorithms developed for the SSM/I towards the TMI, and to assess the improvement due to this new instrument (i.e. TMI). The statistical results show the goodness at utilizing the physical inversion model to estimate useful parameters such as atmosphere total precipitable water distribution over the Mediterranean area, from both the SSM/I and the TMI radiometers, and demonstrate a good retrieval accuracy. That is important especially for data-assimilation applications.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stefano Nativi, Stefano Migliorini, and Dino Giuli "Comparing SSM/I and TMI for the estimation of atmospheric water vapor and cloud liquid water over the Mediterranean Sea", Proc. SPIE 3867, Satellite Remote Sensing of Clouds and the Atmosphere IV, (8 December 1999); https://doi.org/10.1117/12.373075
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KEYWORDS
Radiometry

Liquids

Clouds

Atmospheric modeling

Atmospheric physics

Algorithm development

Statistical analysis

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