Improvement of precipitable water vapour and water vapour mixing ratio profile in atmospheric infrared sounder retrievals: differential linear adjustment model

ABSTRACT

Knowledge of both the horizontal and vertical distributions of atmospheric water vapour is pivotal to understand the Earth’s radiative balance. The Atmospheric Infrared Sounder (AIRS) provides an opportunity to monitor both precipitable water vapour (PWV) measurements and water vapour mixing ratio (MR) profiles. In this study, we incorporate a differential linear adjust model (DLAM) by using the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim) to adjust the AIRS water vapour retrievals. The performance of the differential linear adjustment model (DLAM) is assessed by comparing AIRS water vapour retrievals with spatio-temporally synchronized radiosonde (RS) observations. Taking RS data as the reference, RMS of the DLAM-adjusted PWV is reduced by about 16%, and that of water vapour MR is decreased by 17% to 8% from 1000 to 500 hPa. We also find that the DLAM appears to be affected by the generally larger uncertainties of the a priori water vapour MR at upper tropospheric levels, and the DLAM-derived water vapour MR improvement is generally greater from 1000 to 850 hPa than 700 to 500 hPa. Moreover, the potential reason for the effectiveness of the DLAM on AIRS water vapour retrievals adjustment may be the deviation of the differential water vapour information derived by the differential process is significantly reduced in the incorporated model.

Acknowledgements

This work was funded by the National Natural Science Foundation of China (41506211 and 41606208), the Shanghai Pujiang Program (19PJ1404300), the National Key Research & Development Program of China (2019YFD0901404), the open fund of State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources (MNR) (QNHX1909), the open fund of the Key Laboratory for Polar Science, Polar Research Institute of China, MNR (KP201701), and the open fund of the Key Laboratory for Information Science of Electromagnetic Waves, Fudan University (EMW201909). Liang Chang appreciates the kind helps and constructive discussion from Dr. Abhnil A. Prasad (the University of New South Wales (UNSW)). We are grateful to the National Aeronautics and Space Administration (NASA) Goddard Earth Sciences (GES) Data and Information Services Center (DISC), the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Integrated Global Radiosonde Archive (IGRA) for providing their data.

Disclosure statement

No potential conflict of interest was reported by the authors.