We present here a new helicopter-borne glacier thickness survey in Khumbu Himal, Nepal, flown by the British Antarctic Survey in 2019. The data consist of raw and processed radio echo sounding radargrams and associated survey measurements acquired using a mono-pulse dipole radar known as 'DELORES', and geolocated glacier thickness interpreted from these radargrams. Mountain glaciers provide an important service in sustaining river flows for large populations downstream of High Mountain Asia, but these glaciers are retreating, and their future is highly uncertain. Glacier thickness measurements are vital for accurate mapping of the remaining ice reserve and for predicting where and how fast it will decline under climate change, but such measurements are severely lacking in this region due to the difficulties of surveying in remote, high-altitude settings. We report on a uniquely extensive new glacier thickness dataset for 17 glaciers in the Khumbu Himal around Everest that our team from the British Antarctic Survey collected using a novel, low-frequency helicopter-borne radar. We succeeded in mapping ice thickness with a precision of around +/-7% for thicknesses of up to 445 m and spanning a total of 119 line-km. This approximately doubles the length of previous thickness surveys in High Mountain Asia. This research is supported by the following NERC fundings: - NERC International Opportunities Fund - Bedmap Himalayas - Reconnaissance (NE/L013258/1) - Polar Expertise - Supporting Development (NE/R000107/1 and NEB1348) - The Big Thaw (NE/X005267/1 and NEB2165)

Ground-penetrating radar (GPR) was used to test glacier ice thickness/glacier bed detectability on debris-covered Himalayan glaciers at a range of frequencies in glacier long- and cross- profiles and at static points. The survey sites were of the Lirung and Langtang Glaciers in the Langtang National Park, Nepal, where debris cover thickness varied from centimetres to several metres. The radar used was the BAS DELORES dipole pulse radar system, operating at 5MHz, 10MHz, 20MHZ and 40MHz. Data were acquired as a stop-go survey at 2-4m intervals on partially snow-covered and entirely debris-covered glacier surfaces in temperatures close to freezing, with a diurnal freeze-thaw cycle. Funding was provided by the NERC grant NE/L013258/1.

The dataset is the output of a statistical model which downscales ERA5 monthly precipitation data using gauge measurements from the Upper Beas and Sutlej Basins in the Western Himalayas. Multi-Fidelity Gaussian Processes (MFGPs) are used to generate more accurate precipitation values between 1980 and 2012, including over ungauged areas of the basins. MFGPs are a probabilistic machine learning method that provides principled uncertainty estimates via the prediction of probability distributions. These predictions can therefore be used to estimate the likelihood of extreme precipitation events which have led to droughts, floods, and landslides. Funding from UK Engineering and Physical Sciences Research Council [grant number: 2270379].

This dataset contains barium concentration and stable isotope ratio measurements of the adsorbed and dissolved phases associated with batch laboratory adsorption-desorption reactions using common environmental mineral adsorbents (clay minerals: kaolinite & montmorillonite, iron-oxyhydroxides: goethite and ferrihydrite) and surface waters (river water, groundwater and seawater). The experiments systematically changed several variables (reaction duration, adsorbent concentration, water type and the pre-experiment adsorbent cleaning procedure). Barium concentration and stable isotope ratio measurements of the adsorbed and dissolved phases from two Himalayan rivers (Saptakoshi River and Sunkoshi River) are also provided. Full details about this dataset can be found at https://doi.org/10.5285/cfa9abd4-1200-47b6-9553-aa1b6e4d9ffd