Variability of integrated precipitable water over India in a warming climate

Abstract

Changes in precipitation patterns as a result of increased atmospheric water vapour in a warming environment over the Indian region have been reported in the past few decades. However, these studies have not focused much on exploring the changes in atmospheric water vapour in a changing climate. The present study focuses on examining the variability of integrated precipitable water (IPW) over the Indian region derived from the Modern Era Retrospective‐Analysis for Research and Application (MERRA 2) model in a warming environment. The results suggest that the IPW has increased significantly in recent decades. Changes in the IPW are consistent with changes in regional warming over India. The results also point out an increase of about 4.98% ± 1.26% in the IPW for a 1°C increase in regional warming. The variability of IPW has been examined in a warming climate. An increase in regional temperature shows coherent variation with IPW. A decadal increase of about 1.69% has been reported in the IPW.

Long-term changes in precipitable water vapour over India derived from satellite and reanalysis data for the past four decades (1980–2020)

“…For example, Jade et al (2019) 19 showed that the interannual variation of PWV is about 9–22% for southern India, 9–19% for Himalaya and about 3–10% for northeast India. Mishra (2019) 20 showed a positive trend of about 1.69% dec −1 in PWV for the period 1980–2018 in India. Similarly, Jindal et al (2020) 21 found positive trends in PWV at different locations in India (about 1.663% per year and 0.580% per year over Hyderabad and Delhi, respectively) during the period 2003–2011.…”

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Third Edition

“…Another source of data is provided by reanalysis models, such as CAMS or MERRA-2 (Gueymard and Yang 2020; Kosmopoulos et al 2018). Similarly, water vapor information can be retrieved from the Global Ozone Monitoring Experiment-2 (GOME-2), the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), and MODIS spaceborne instruments (Beirle et al 2018;, or from reanalysis models (Mishra 2019). Although AOD and PW are derived mostly from polar-orbiting satellites, several retrievals are developed with geostationary satellites, such as Himawari-8, the Geostationary Operational Environmental Satellite (GOES), and Meteosat (Kaufman, Tanré, and Boucher 2002).…”

Developing a Web Application-Based Water Budget Calculator: Attaining Water Security in Rural-Nashik, India

“…The WBC estimates evapotranspiration using the Blaney-Criddle formula [8]. This empirical formula is based on data from the arid climatic conditions of the United States and takes into account the sunshine hours and temperature.…”

“…[5][6][7]. The interference to the hydrological cycle at one stage can lead to serious consequences at some other stage due to the strong interdependency between the stages of the cycle [8]. India, having predominantly the rural and agricultural society, is no more exempted from the issue of water scarcity, security, and spatial non-uniformity in the water distribution [9][10][11].…”