Abstract
We have developed a new algorithm to estimate the surface air specific humidity over the ocean from AMSR-E data. It should be noted that remarkably reduced random errors of the estimated surface air specific humidity result from using the surface air specific humidity provided by reanalysis data. We validated our new algorithm using independent ship and buoy data. The bias, RMS error, and correlation coefficient of the products obtained using our algorithm for global buoys are 0.38 g/kg, 0.61 g/kg and 0.99, respectively. It should be noted that surface specific humidity having similar accuracy to the reanalysis data near in situ data could be derived from AMSR-E data by the present algorithm.
Highlights
Latent heat flux (LHF) is considered to be the most important constituent of ocean surface heat flux, which comprises shortwave radiation, longwave radiation, latent heat flux, and sensible heat flux
The global LHF is estimated by using data from several satellites and the following bulk formula: LHF a LvCEU Qs Qa, where a is the density of air, Lv is the latent heat of vaporization, U is the near-surface wind speed relative to the surface current speed, Qs and Qa are the surface and saturated specific humidity, respectively, and CE is the turbulent exchange coefficient for moisture
We developed a new algorithm to determine the surface air specific humidity from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E)
Summary
Latent heat flux (LHF) is considered to be the most important constituent of ocean surface heat flux, which comprises shortwave radiation, longwave radiation, latent heat flux, and sensible heat flux. Several studies have been performed on the development of algorithms for the estimation of specific humidity, e.g.; [1,2,3] Most of these algorithms were developed for application to the data of the Defense Meteorological Satellite Program (DMSP)/ Special Sensor. To date, only [7] has developed an algorithm for estimation of specific humidity using AMSR-E data. It is necessary to evaluate the accuracy of the air specific humidity derived from AMSR-E data using [7]‘s algorithm, by comparing with ocean observation data. We have used the in situ surface air specific humidity data, which is observed by ships and buoys, of the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) for the construction of the new algorithm. We used the data for the year 2004 for analysis, except in the case of the KEO buoy because the KEO has only been carrying out observations since June 2004
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