Retrieving Layer-Averaged Tropospheric Humidity from Advanced Technology Microwave Sounder Water Vapor Channels
Journal article, 2015

A method is presented to calculate layer-averaged tropospheric humidity (LAH) from the observations of the Advanced Technology Microwave Sounder (ATMS) water vapor channels. The method is based on a linear relation between the satellite brightness temperatures (Tb) and natural logarithm of Jacobian weighted humidity. The empirical coefficients of this linear relation were calculated using different data sets, as well as a fast and a line-by-line radiative transfer (RT) model. It was found that the coefficients do not significantly depend on the data set or the RT model. This Tb to the LAH transformation method can be applied to either original or limb-corrected ATMS Tb's. The method was validated using both simulated and observed ATMS Tb's. The systematic difference between the estimated and calculated LAH values was less than 10% in most cases. We also tested the transformation method using a fixed Jacobian for each channel. The bias generally increases when fixed Jacobians are used, but there is still a satisfactory agreement between estimated and calculated LAH values. In addition, the spatial distribution of the bias was investigated using the European Center for Medium-Range Weather Forecasting (ECMWF) Interim Reanalysis (ERA-interim) and collocated ATMS observations. The bias did not indicate any significant regional dependence when actual Jacobians were used, but in the case of fixed Jacobians, the bias generally increased from middle latitude toward the poles.

Climate change

remote sensing

water vapor

hydrology

joint polar satellite system (JPSS)

microwave

Author

I. Moradi

University of Maryland

National Oceanic and Atmospheric Administration

R. R. Ferraro

National Oceanic and Atmospheric Administration

B. J. Soden

University of Miami

Patrick Eriksson

Chalmers, Earth and Space Sciences, Global Environmental Measurements and Modelling

P. Arkin

University of Maryland

IEEE Transactions on Geoscience and Remote Sensing

0196-2892 (ISSN) 15580644 (eISSN)

Vol. 53 12 6675-6688 7150548

Subject Categories

Remote Sensing

Meteorology and Atmospheric Sciences

DOI

10.1109/TGRS.2015.2445832

More information

Latest update

4/27/2021