Title:	Dynamic downscaling for assessment of regional water cycle
DNr:	SNIC 2021/22-277
Project Type:	SNIC Small Compute
Principal Investigator:	Tinghai Ou <tinghai.ou@gu.se>
Affiliation:	Göteborgs universitet
Duration:	2021-05-01 – 2021-08-01
Classification:	10501
Keywords:

Abstract

Variations in the water cycle are one of the key factors which directly affect the living environment of human beings. It is of great importance to assess the changes in the water cycle in relation to global warming. High-resolution data sets are needed in order to carry out the work on a regional scale, i.e. for Tibetan Plateau. In this project, a mesoscale numerical model will be used to dynamically downscale the ERA5 reanalysis data sets (horizontal resolution: 0.25ox0.25o (Lon x Lat)) to high-resolution regional data sets (horizontal resolution: 2-9 km). Successfully carry out this project will provide high-resolution data sets for assessing the changes in the water cycle over southern Sweden in response the climate change.