Selection of climate models for developing representative climate projections for the Hindu Kush Himalayan Region

Abstract

In HI-AWARE, both statistical and dynamical downscaling techniques will be used to downscale and bias correct climate model data to higher spatial resolutions. For both approaches, General Circulation Models (GCMs) and Regional Climate Models (RCMs) must be selected to either be statistically downscaled or used as boundary and forcing for dynamical downscaling. This report discusses the statistical downscaling component. There are two fundamentally different methods for selecting appropriate GCMs/RCMs. The first approach aims to cover the full envelope of possible futures ranging from dry and cold projections to wet and warm projections, while the second approach selects GCMs/RCMs on the basis of indicators of past performance. Both approaches have their pros and cons, but in the case of the Hindu Kush Himalayas (HKH) the first approach may be preferable as climate models have considerable difficulty in simulating past climate (Turner and Annamalai 2012). In this study, we develop a new method that combines the two existing methods. We aim to select a set of climate models that both cover a wide range of possible futures, but are also able to reproduce the most important processes in the region.

Description

This series is based on the work of the Himalayan Adaptation, Water and Resilience (HI-AWARE) consortium under the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA) with financial support from the UK Government’s Department for International Development and the International Development Research Centre, Ottawa, Canada. CARIAA aims to build the resilience of vulnerable populations and their livelihoods in three climate change hot spots in Africa and Asia. The programme supports collaborative research to inform adaptation policy and practice.

Keywords

STATISTICAL DOWNSCALING TECHNIQUES, DYNAMICAL DOWNSCALING TECHNIQUES, GENERAL CIRCULATION MODELS (GCMs), REGIONAL CLIMATE MODELS (RCMs), HINDU KUSH HIMALAYAS (HKH), MODELLING, CLIMATE, BANGLADESH, INDIA, NETHERLANDS, NEPAL, PAKISTAN, BASINS

Citation

Lutz, A; Immerzeel, W; Biemans, H; Maat, H; Veldore, V; Shrestha, A (2016) Selection of climate models for developing representative climate projections for the Hindu Himalayan region. HI-AWARE Working Paper 1. Kathmandu: HI-AWARE.

DOI