4.5 Review

Intercomparison review of IPWV retrieved from INSAT-3DR sounder, GNSS and CAMS reanalysis data

Journal

ATMOSPHERIC MEASUREMENT TECHNIQUES
Volume 14, Issue 7, Pages 4857-4877

Publisher

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/amt-14-4857-2021

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The study examined the spatiotemporal variations of integrated precipitable water vapor (IPWV) using satellite and Copernicus Atmosphere Meteorological Service (CAMS) retrievals in the Indian region. Differences in performance were found between INSAT-3DR and CAMS with respect to GNSS IPWV across seasons and locations, providing valuable insights for forecasting applications.
The spatiotemporal variations of integrated precipitable water vapor (IPWV) are very important in understanding the regional variability of water vapor. Traditional in situ measurements of IPWV in the Indian region are limited, and therefore the performance of satellite and Copernicus Atmosphere Meteorological Service (CAMS) retrievals with the Indian Global Navigation Satellite System (GNSS) as reference were analyzed. In this study the CAMS reanalysis data of 1 year (2018) and the Indian GNSS and INSAT3DR sounder retrieval data for 1.5 years (January 2017 to June 2018) were utilized, and statistics were computed. It is noticed that seasonal correlation coefficient (CC) values between INSAT-3DR and Indian GNSS data mainly lie within the range of 0.50 to 0.98 for all the selected 19 stations except Thiruvananthapuram (0.1), Kanyakumari (0.31) and Karaikal (0.15) during the monsoon season and Panjim (0.2) during the post-monsoon season. The seasonal CC values between CAMS and GNSS IPWV range from 0.73 to.99 except for Jaipur (0.16) and Bhubaneswar (0.29) during the pre-monsoon season, Panjim (0.38) during the monsoon season, Nagpur (0.50) during the post-monsoon season, and Dibrugarh (0.49) Jaipur (0.58) and Bhubaneswar (0.16) during the winter season. The root mean square error (RMSE) values are higher under the wet conditions (pre-monsoon and monsoon season) than under dry conditions (post-monsoon and winter season), and we found differences in magnitude and sign of bias for INSAT-3DR and CAMS with respect to GNSS IPWV from station to station and season to season. This study will help to improve understanding and utilization of CAMS and INSAT-3DR data more effectively along with GNSS data over land, coastal and desert locations in terms of the seasonal flow of IPWV, which is an essential integrated variable in forecasting applications.

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