Code to compare the mass and energy balance of five Peruvian glaciers, based on outputs from the energy balance model Tethys-Chloris. Also includes code to compare the results of climate sensitivity experiments (where the air temperature and precipitation were varied). The main outputs of the analysis at each of the sites are also stored. Full details about this dataset can be found at https://doi.org/10.5285/5f6661e4-1d34-4b01-8f3a-9fc86c546f73

Weather station data at five on-glacier stations in Peru and the ecohydrological model Tethys-Chloris. Data includes: - Hourly weather station data from Shallap Glacier, Artesonraju Glacier, Cuchillacocha Glacier, Quisoquipina Glacier and Quelccaya Ice Cap. Given as .csv files and as model input files. - The model code used to input the data and set the correct parameters for these sites. - The model code for the point version of Tethys-Chloris, an ecohydrological model which is used in this case to calculate glacier melt and mass balance. Full details about this dataset can be found at https://doi.org/10.5285/b69b8849-6897-47eb-a820-f488f8bca437

Averaged outputs from the WRF (Weather Research and Forecasting) model for the Rio Santa and Vilcanota, Urubamba and Vilcabamba catchments in Peru. Averaging was applied over the entire model period from 1980 to 2018. Data includes: - Averaged precipitation and air temperature records and the related standard deviation at a 4km resolution (annually and for each season) for each catchment. Monthly averaged and monthly totals of air temperature and precipitation (averaged over each catchment). - WRF model input elevation for each catchment. - WRF total precipitation and maximum/minimum air temperature at the location of five on-glacier weather stations (Artesonraju Glacier, Shallap Glacier, Cuchillacocha Glacier, Quisoquipina Glacier and Quelccaya Ice Cap) at a daily resolution from 1980 to 2018. Full details about this dataset can be found at https://doi.org/10.5285/7dbb2d72-7032-4cfa-bc9b-aa02bebe8df5

[This dataset is embargoed until February 28, 2025]. The Reference Observatory of Basins for INternational hydrological climate change detection (ROBIN) dataset is a global hydrological dataset containing publicly available daily flow data for 2,418 gauging stations across the globe which have natural or near-natural catchments. Metadata is also provided alongside these stations for the Full ROBIN Dataset consisting of 3,060 gauging stations. Data were quality controlled by the central ROBIN team before being added to the dataset, and two levels of data quality are applied to guide users towards appropriate the data usage. Most records have data of at least 40 years with minimal missing data with data records starting in the late 19th Century for some sites through to 2022. ROBIN represents a significant advance in global-scale, accessible streamflow data. The project was funded the UK Natural Environment Research Council Global Partnership Seedcorn Fund - NE/W004038/1 and the NC-International programme [NE/X006247/1] delivering National Capability Full details about this dataset can be found at https://doi.org/10.5285/3b077711-f183-42f1-bac6-c892922c81f4