By Singay Dorji, Ph.D. candidate UNU-IAS

The year 2016 marked the third consecutive hottest on record according to the National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA). The fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) concludes that the warming in the climate system is unequivocal. In the Conference of Parties (COP21), the Paris summit in Dec 2015 agreed to limit the rise in global temperature below 2°C above the pre-industrial level. Climate change is a significant challenge to achieving the sustainable development goals. Global average temperature anomaly and trend by the Japan Meteorological Agency (JMA) is shown in Figure attached.

Climate change is projected to increase temperature, rainfall, extreme events and the non-rainy days. This study focuses on understanding the climate impacts at a regional or catchment scale. The aim of the research is to predict temperature and rainfall for impact assessment studies and forecasting applications. The three main objectives of the study are to study climate change trends, downscaling and seasonal forecasting. The study area is based on Sri Lanka and Bhutan. A variety of tools and methods are used in the research. Several tests and validation using observed data, reanalysis, global forecasts and other statistics are applied.

Downscaling is required to extract the sub-grid and local scale information from the course resolution Global Climate Model (GCM). The study uses the Canadian Earth System Model (CanESM2) GCM, the National Center for Environmental Prediction (NCEP) reanalysis data and the Asian Precipitation Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE) observation data. Downscaling is done with the statistical downscaling model (SDSM) and artificial neural networks. The result provides daily temperature and rainfall at a point location for applications like hydrology models.

Climate change trends and future projections will be made based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) of the World Climate Research Programme (WCRP). Observation data from the Climatic Research Unit (CRU) and the Global Precipitation Climatology Centre (GPCC) will be used to study the past climate. The study will include projections of future climate under various Representative Concentration Pathway (RCP) scenarios.

The study is developed within the framework of the International Network for Advancing Transdisciplinary Education (INATE) launched at the UN World Conference on Disaster Risk Reduction in Sendai, Japan in March 2015 of the UN Climate and Ecosystem Change Adaptation Research (UN-CECAR). Important elements of INATE include identification of critical societal needs, customizing global knowledge to local conditions, active stakeholder participation, leadership, and sustainability. The outputs from this research will directly benefit the study countries for climate studies and applications in operational forecasting.