Abstract
Regional precipitation feedback resulting through regional mean temperature escalation on seasonal basis has been investigated in the present study. Recently published reanalysis dataset AgMERRA has been used to cater for observational dataset requirements for analysis. Historical (1980-1998), present and near future (2007-2025), and far future (2080-2098) climate datasets of a super high resolution GCM viz. GCM20 (20Km horizontal resolution, A1B scenario), and of a high resolution RCM viz. RegCM4.3 (25Km horizontal resolution, RCP8.5 scenario) have been used to construct linear regression models based on method of least squares, to analyse possible regional precipitation responses to increase in regional temperature over Pakistan. Mean seasonal temperature have been used to predict mean seasonal precipitation feedback, both in past and future climate over the region. Results have shown that MAM precipitation has the highest cumulative response to changes in daily mean MAM temperature, irrespective of the time period, and the data used. AgMERRA reveals a 0.09 mm/day drop in MAM mean precipitation intensity for each degree Celsius rise in MAM mean temperature over the region. Under the A1B scenario, GCM20 baseline and projection analysis depicts 0.12 mm/day decrease in historical, 0.09 mm/day decrease in present and near future, and 0.12 mm/day decrease in far future MAM mean precipitation intensity for each degree Celsius rise in MAM mean temperature over the region. However under the RCP8.5 protocols, RegCM4.3 baseline and projection illustrates 0.04 mm/day decrease in historical, 0.04 mm/day decrease in present and near future, and 0.09 mm/day decrease in far future MAM mean precipitation intensity for each degree Celsius rise in MAM mean temperature over the region.
Keyword(s)
AgMERRA, GCM20, RegCM4.3, A1B scenario, RCP8.5 scenario, linear regression analysis