Local projections of future sea-level change are important for understanding climate change risks and informing coastal management decisions. Reliable and relevant coastal risk information is especially important in South Asia, where large populations live in low-lying areas and are at risk from coastal inundation. A new set of local sea-level projections for selected tide gauge locations in South Asia have been produced over the 21st century under the RCP2.6, RCP4.5 and RCP8.5 scenarios by the UK Met Office for the Asia Regional Resilience to a Changing Climate Programme.

This is the ensemble average annual precipitation sum data from 1981 to 2100 for 77 districts of Nepal. This data was prepared using four RCP4.5 and four RCP8.5 models with spatial coverage of whole Nepal at 10 km by 10 km resolution. It also contains the standard deviation to show the variability among the models in each RCP.

This is the ensemble average annual mean temperature data from 1981 to 2100 for 77 districts of Nepal. This data was prepared using four RCP4.5 and four RCP8.5 models with spatial coverage of whole Nepal at 10 km by 10 km resolution. It also contains the standard deviation to show the variability among the models in each RCP.

A comparison between male and female population residing in the Koshi Basin Districts in various parameters shows more male population who have higher literacy rate, higher rate of land and house ownership, involved in higher income generating jobs as well as 76% of men are also head of household compared to female despite the fact that there are equal population women and men.

A comparison between male and female population residing in the Koshi Basin Districts in various parameters revealing the trends in marriage, population, life expectancy, migration, ethnicity and other parameters.

Resilient Mountain Solution (RMS) and RMS Poverty and Vulnerability Assessment (PVA) is a ward level household survey to have get a deeper understanding of Dadeldhura site. The survey was a part of the case study at covering multiple issues focusing on agricultural and animal husbandry practices, energy use, environmental and socioeconomic changes faced, their impact and coping to identify emerging issues, determinants of vulnerability and develop solution to improve their resilience for enhanced livelihoods. The survey covers 110 households across the 5 wards of Bhageswor rural municipality in Dadeldhura which was purposively selected. Household selection for the survey was done following random sampling method within the wards.

Poverty and Vulnerability Assessment (PVA) is a district level household survey to understand vulnerability of households to environmental and socioeconomic changes with focus on mountain specificity as well as their coping strategies and adaptive capacity. Under the Adaptation to Change program, the Himalaya Climate Change Adaptation Programme (HICAP) initiative have conducted the survey among 2647 households across 7 districts in states of Assam and Arunanchal Pradesh in the Eastern Brahmaputra sub-basin in India. The households were selected following a probability based multi-stage cluster sampling approach.

Precipitaton(%) and temperature(delta T(K)) for RCP4.5 and RCP 8.5 for 4 GCM, monthly change grids at a resolution of 25km covering the whole model domain, grids showing the average monthly value during 2021-2050 relative to the average monthly value during 1961-1990.

NorESM climate scenario data of 4.5 and 8.5 W/m2 of daily rainfall Tmin and Tmax.

As part of climate change impact monitoring program on biodiversity, Ugyen Wangchuck Institute for Conservation and Environment Research (UWICER) has initiated HEROES program in 2015. 17 schools covering different altitudinal gradient and geographic region were selected as monitoring sites. In each school, weather station was installed that logs weather data such as temperature, precipitation, solar radiation, soil moisture, wind speed and wind direction every 10 minutes. Also, at the same location, the project monitor and records phenological events and its timing such as budburst, flowering and fruiting on an yearly basis. This dataset consists of daily and monthly temperature and precipitation data for 2015-2020 period derived from weather station data collected at 10 minute interval at Khasadrapchu School in Thimphu, Bhutan.