Retrieval of sea surface specific humidity based on AMSR-E satellite data

A new algorithm using a multivariate regression technique for retrieving sea surface specific humidity (Q) from remote sensing data from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) is proposed. Daily and monthly specific humidity data from the National Center for Environmental Prediction (NCEP) reanalysis dataset and data of sea surface temperature, atmospheric total water vapor, and wind speed from AMSR-E oceanographic products were used to derive the regression coefficients of the algorithm, and all the data for derivation are from the year 2003. An F-test was applied to the regression, and small P-values indicate that the regressions are significant to a high level of confidence. The derived coefficients have been validated using similar data from the year 2004. The root mean square (rms) error of the algorithm for daily retrieved Q over the global oceans is 1.05 g kg−1, and the rms error for monthly retrieved Q is 0.61 g kg−1.