Snow Line Altitude in High mountain Asia derived from satellite imagery (LS5, LS7, LS8 & S2) between 1999 and 2019

This repository contains the data used for the study Precipitation phase drives seasonal and decadal snowline changes in high mountain Asia. This study focuses on 4776 glacierized catchments across high mountain Asia (HMA). They are numbered from 0 to 4775. This code number is then used in all the products as their unique ID. The repository contains the following data: 1-OutlinescatchmentsHMAtot.shp is a shapefile with the outline of the 4776 glacierized catchments. 2-Raw dataThe DataCover_HMA and SnowCover_HMA directories respectively contain the data maps (number of data available for each pixel) and snow maps (number of snow detections for each pixel) obtained for each catchment for each satellite (Landsat 5 = LS5, Landsat 7 = LS7, Landsat 8 = LS8 and Sentinel 2 = S2). The files are named as:SnowCover_HMA[catchment_number]_[Satellite_id].tifDataCover_HMA[catchment_number]_[Satellite_id].tif SLA_HMA_rawdata directory contains for each catchment and for each satellite the initial snow line altitude (SLA) information extracted from the snow & data maps.The files are are named as: SLA_HMA[catchment_number]_[Satellite_id].csv 3-Preprocessed data SLA_HMA_preprocessedWe preprocessed the raw SLA data to produce valid SLA data for each catchment, filtering and aggregating data from the different satellites. The files are named as: SLA_HMA[catchment_number].csv 4-DEM_HMAWe used elevation information from ALOS DEM that are available for each catchment.DEMalt_HMA[catchment_number].csv contains the elevations of the catchment binned every 10m and DEMcdistrib_HMA[catchment_number].csv the corresponding cumulative distribution. 5-RESULTS datasets (all the figures are based on these datasets)The datasets resulting from this study are divided into two groups: Data per catchment in Catchment_data directory RESULTS OVER 1999-2019 The file Catchment_data.csv contains for each catchment the following variables:> the parameters obtained from the second order harmonic regression> geographical variables> Snow Line Altitude variables> Number of observations> Temperature variables> Precipitation variables> Snowfall variables RESULTS OVER 1999-2009 AND 2009-2019For each catchment, monthly aggregated data for the two decades are available in the following files: Precipitation_monthly_1999_2009.csv and Precipitation_monthly_2009_2019.csvTemperature_monthly_1999_2009.csv and Temperature_monthly_2009_2019.csvSLA_monthly_1999_2009.csv and SLA_monthly_2009_2019.csv Data aggregated per region (from Bolch et al., 2019) in Regional_data directory Table of the correlations per region (Fig SI 8-9-10) table_correlations_per_region.csvTable of precipitation changes per region (%) table_Precipitation_changes_per_region.csvTable of temperature changes per region (°C) table_Temperature_changes_per_region.csvTable of SLA changes per region (m) table_SLA_changes_per_region.csv Acknowledgments This work was supported by the SNSF (Science and Swiss National Science Foundation)-SSSTC (Sino-Swiss Science and Technology Cooperation) Project (IZLCZ0_189890) 'Understanding snow, glacier and rivers response to climate in High Mountain Asia (ASCENT)', by the JSPS (Japan Society for the Promotion)-SNSF Bilateral Programmes project (HOPE, High-elevation precipitation in High Mountain Asia; Grant 183633), and the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (RAVEN, Rapid mass losses of debris-covered glaciers in High Mountain Asia; Grant 772751). Marin Kneib acknowledges funding from the SNSF Postdoc.Mobility program (Grant No. P500PN_210739).