Estimating small-scale and robust future climate extremes greatly depends on finer resolution of both reference (observation) and model data. The statistical and dynamical downscaling scientific communities try to produce reliable data at local scale, reduce the uncertainty and establish the confidence of policy makers over future climate extremes by improving reference and model data. Despite of continuous improvement of climate extremes, there are critical gaps exist in finer resolution, observation is not sufficient and scaling issues between reference and models data over South Asia. There is an urgent need for high resolution regional/local future climate extremes information for impact adaptation and vulnerability studies. The aim of this project to: (i) prepare local scales (5 km) reference data using statistical (long-term trend preserving bias correction methods) and dynamical downscaling approaches; (iii) produce local information of climate extremes and identify the vulnerable regions over South Asia; (iv) recommend adaptation measures at local, national and regional levels; (v) capacity building of researchers, students and policy makers in the field of climate extremes in the developing countries involved in the project; and (vi) develop a portal for reporting/recording information on current and future climate extremes.
Project leader
Project publications
Selecting the best CMIP6 GCMs for application and downscaling studies over Pakistan, Nepal and Bangladesh
Climate change research, capacity building and communication on climate extremes over South Asia
A 5-km gridded product development of daily temperature and precipitation for Bangladesh, Nepal, and Pakistan from 1981 to 2016
Project final report: CRRP2018-04MY-Ali
Modelling the impact of climate change on dengue outbreaks and future spatiotemporal shift in Pakistan
