Assessing climate boundary shifting under climate change scenarios across Nepal.

Abstract

This study assesses the climate boundary shifts from the historical time to near/mid future by using a slightly modified Köppen-Geiger (KG) classification scheme and presents comprehensive pictures of historical (1960-1990) and projected near/mid future (1950s: 2040-2060/1970s: 2060-2080) climate classes across Nepal. Ensembles of three selected general circulation models (GCMs) under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5) were used for projected future analysis. During the 1950s, annual average temperature is expected to increase by 2.5°C under RCP 8.5. Similarly, during the 1970s, it is even anticipated to rise by 3.6°C under RCP 8.5. The rate of temperature rise is higher in the non-monsoon period than in monsoon period. During the 1970s, annual precipitation is projected to increase by 8.1% under RCP 8.5. Even though the precipitation is anticipated to increase in the future in annual scale, winter seasons are estimated to be drier by more than 15%. This study shows significant increments of tropical (Am and Aw) and arid (BSk) climate types and reductions of temperate (Cwa and Cwb) and polar (ET and EF). Noticeably, the reduction of the areal coverage of polar frost (EF) is considerably high. In general, about 50% of the country's area is covered by the temperate climate (Cwa and Cwb) in baseline scenario and it is expected to reduce to 45% under RCP 4.5 and 42.5% under RCP 8.5 during the 1950s, and 42% under RCP 4.5 and 39% under RCP 8.5 during the 1970s. Importantly, the degree of climate boundary shifts is quite higher under RCP 8.5 than RCP 4.5, and likewise, the degree is higher during the 1970s than the 1950s. We believe this study to facilitate the identification of regions in which impacts of climate change are notable for crop production, soil management, and disaster risk reduction, requiring a more detailed assessment of adaptation measures. The assessment of climate boundary shifting can serve as valuable information for stakeholders of many disciplines like water, climate, transport, energy, environment, disaster, development, agriculture, and tourism.