• Energy Research

AbstractRunoff from glacierised Andean river basins is essential for sustaining the livelihoods of millions of people. By running a high-resolution climate model over the two most glacierised regions of Peru we unravel past climatic trends in precipitation and temperature. Future changes are determined from an ensemble of statistically downscaled global climate models. Projections under the high emissions scenario suggest substantial increases in temperature of 3.6 °C and 4.1 °C in the two regions, accompanied by a 12% precipitation increase by the late 21st century. Crucially, significant increases in precipitation extremes (around 75% for total precipitation on very wet days) occur together with an intensification of meteorological droughts caused by increased evapotranspiration. Despite higher precipitation, glacier mass losses are enhanced under both the highest emission and stabilization emission scenarios. Our modelling provides a new projection of combined and contrasting risks, in a region already experiencing rapid environmental change.

AbstractPeruvian glaciers are important contributors to dry season runoff for agriculture and hydropower, but they are at risk of disappearing due to climate change. We applied a physically based, energy balance melt model at five on‐glacier sites within the Peruvian Cordilleras Blanca and Vilcanota. Net shortwave radiation dominates the energy balance, and despite this flux being higher in the dry season, melt rates are lower due to losses from net longwave radiation and the latent heat flux. The sensible heat flux is a relatively small contributor to melt energy. At three of the sites the wet season snowpack was discontinuous, forming and melting within a daily to weekly timescale, and resulting in highly variable melt rates closely related to precipitation dynamics. Cold air temperatures due to a strong La Niña year at Shallap Glacier (Cordillera Blanca) resulted in a continuous wet season snowpack, significantly reducing wet season ablation. Sublimation was most important at the highest site in the accumulation zone of the Quelccaya Ice Cap (Cordillera Vilcanota), accounting for 81% of ablation, compared to 2%–4% for the other sites. Air temperature and precipitation inputs were perturbed to investigate the climate sensitivity of the five glaciers. At the lower sites warmer air temperatures resulted in a switch from snowfall to rain, so that ablation was increased via the decrease in albedo and increase in net shortwave radiation. At the top of Quelccaya Ice Cap warming caused melting to replace sublimation so that ablation increased nonlinearly with air temperature.

ABSTRACTNear-surface air temperature is an important determinant of the surface energy balance of glaciers and is often represented by a constant linear temperature gradients (TGs) in models. Spatio-temporal variability in 2 m air temperature was measured across the debris-covered Miage Glacier, Italy, over an 89 d period during the 2014 ablation season using a network of 19 stations. Air temperature was found to be strongly dependent upon elevation for most stations, even under varying meteorological conditions and at different times of day, and its spatial variability was well explained by a locally derived mean linear TG (MG–TG) of −0.0088°C m−1. However, local temperature depressions occurred over areas of very thin or patchy debris cover. The MG–TG, together with other air TGs, extrapolated from both on- and off-glacier sites, were applied in a distributed energy-balance model. Compared with piecewise air temperature extrapolation from all on-glacier stations, modelled ablation, using the MG–TG, increased by <1%, increasing to >4% using the environmental ‘lapse rate’. Ice melt under thick debris was relatively insensitive to air temperature, while the effects of different temperature extrapolation methods were strongest at high elevation sites of thin and patchy debris cover.

AbstractDistributed energy-balance melt models have rarely been applied to glaciers with extensive supraglacial debris cover. This paper describes the development of a distributed melt model and its application to the debris-covered Miage glacier, western Italian Alps, over two summer seasons. Sub-debris melt rates are calculated using an existing debris energy-balance model (DEB-Model), and melt rates for clean ice, snow and partially debris-covered ice are calculated using standard energy-balance equations. Simulated sub-debris melt rates compare well to ablation stake observations. Melt rates are highest, and most sensitive to air temperature, on areas of dirty, crevassed ice on the middle glacier. Here melt rates are highly spatially variable because the debris thickness and surface type varies markedly. Melt rates are lowest, and least sensitive to air temperature, beneath the thickest debris on the lower glacier. Debris delays and attenuates the melt signal compared to clean ice, with peak melt occurring later in the day with increasing debris thickness. The continuously debris-covered zone consistently provides 30% of total melt throughout the ablation season, with the proportion increasing during cold weather. Sensitivity experiments show that an increase in debris thickness of 0.035 m would offset 18C of atmospheric warming.

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. The weather station data were cleaned to remove erroneous data and gaps were filled using data from nearby off-glacier stations or in some cases data from the WRF (Weather Research and Forecasting) climate model. Source data were provided by co-authors and Peruvian institutions. The Tethys-Chloris model was provided by Simone Fatichi with some modifications by the team during the project.

The inputs for the analysis code were generated by running the Tethys-Chloris energy balance melt model using weather station data from five Peruvian glaciers. These input data and code are described in the related dataset ‘The physically-based melt model Tethys-Chloris and meteorological input data for five Peruvian glaciers’. The outputs of the analysis saved in this dataset are a result of running the analysis code provided (the code can be run using the inputs provided in Main_runs_for_analysis to produce the output data). 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.