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Assessing the performance of GPS radio occultation measurements in retrieving tropospheric humidity in cloudiness: A comparison study with radiosondes, ERA‐Interim, and AIRS data sets
Author(s) -
Vergados Panagiotis,
Mannucci Anthony J.,
Ao Chi O.
Publication year - 2014
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2013jd021398
Subject(s) - radiosonde , troposphere , environmental science , humidity , atmospheric infrared sounder , meteorology , climatology , radio occultation , atmosphere (unit) , atmospheric sciences , latitude , ionosphere , geography , geology , geodesy , geophysics
We assess the impact that the Global Positioning System radio occultations (GPSRO) measurements have on complementing different data sets in characterizing the lower‐to‐middle tropospheric humidity in cloudy conditions over both land and oceans using data from 1 August 2006 to 31 October 2006. We use observations from rawinsondes, Global Positioning System radio occultations (GPSRO), Atmospheric Infrared Sounder (AIRS), and the European Center for Medium‐Range Weather Forecasts Reanalysis Interim (ERA‐Interim). During the selected time period, Constellation Observing System for Meteorology, Ionosphere, and Climate data were not assimilated in ERA‐Interim. From each data set, we estimate a zonally averaged tropospheric specific humidity profile at tropical, middle, and high latitudes. Over land, we use rawinsondes as the ground truth and quantify the specific humidity differences and root‐mean‐square‐errors (RMSEs) of the GPSRO, AIRS, and ERA‐Interim profiles. GPSRO are beneficial in retrieving lower tropospheric humidity than upper tropospheric profiles, due to their loss of sensitivity at high altitudes. Blending GPSRO with ERA‐Interim produces profiles with smaller humidity biases outside the tropics, but GPSRO data do not improve the humidity RMSE when compared to rawinsondes. Combining GPSRO with AIRS leads to smaller humidity bias at the tropics and high latitudes, while reducing humidity's RMSEs. Over oceans, no rawinsonde information is available, and we use ERA‐Interim as a reference. Combining GPSRO with AIRS leads to smaller humidity RMSEs than AIRS. We conclude that cross‐comparisons and synergies among multi‐instrument observations are promising in advancing our knowledge of the tropospheric humidity in cloudy conditions. GPSRO data can contribute to improving humidity retrievals over cloud‐covered regions, especially over land and within the boundary layer.