Pre-processed input data for large-scale High Mountain Asia snow model

Open data API in a single place

Provided by Zenodo

Get early access to Pre-processed input data for large-scale High Mountain Asia snow model API!

Let us know and we will figure it out for you.

Dataset information

Country of origin
Updated
2024.07.19 00:00
Created
2021.01.01
Available languages
English
Keywords
High Mountain Asia, Snow water equivalent, Snow
Quality scoring

Dataset description

Input datasets necessary to run the snow model of Kraaijenbrink et al. (2021) for the High Mountain Asia region in the same setup as the study. For more information on this data, pre-processing and the exact source datasets used, please refer to the original paper and its methods section. Model code is available here.   File descriptions basin_mask.tif Grid with mask of major basins at 0.05° grid. cmip6_deltas_ensmeans.tar Archive holding grids of climatological deltas between the reference period (2000–2019) and end of century (2081–2100) for precipitation (factor) and temperature (K) for all CMIP6 RCP-SSP ensemble means (SSP119, SSP126, SSP245, SSP370, SSP434, SSP460, SSP585).  era5_2m-temperature_3h_1979-2019.nc ERA5 2m air temperature at 0.25° grid for the period 1979-2019, aggregated to 3-hourly resolution. era5_cellaverage_srtm.tif Shuttle Radar Topography Mission elevation data, spatially averaged at the ERA5 0.25° grid. era5_total-precipitation_3h_1979-2019.nc ERA5 total precipitation at 0.25° grid for the period 1979-2019, aggregated to 3-hourly resolution. LST_monclim_1km.nc Monthly climatologies of MODIS land surface temperature for the period 2000–2019. snowpersistence_ndsi10_monclim.nc Monthly climatologies of MODIS-derived snow persistence for the period 2000–2019. snowpersistence_ndsi10_monclim_mean.nc Average MODIS-derived snow persistence over the period 2000–2019. srtm_elevation_1000m.nc Shuttle Radar Topography Mission elevation data, spatially averaged to ~0.009° grid. srtm_elevation_500m.nc Shuttle Radar Topography Mission elevation data, spatially averaged to ~0.0045° grid tbias_005dd.tif Temperature biases on 0.05° model grid at standard settings.   Model output Daily output time series and climatological future projections of snow water equivalent and snow melt presented in Kraaijenbrink et al. (2021) are available here.   References Kraaijenbrink, P. D. A., Stigter, E. E., Yao, T., and Immerzeel, W. W. (2021). Climate change decisive for Asia’s snow meltwater supply. Nature Climate Change. doi:10.1038/s41558-021-01074-x.      
European data infrastructure with broad catalog discovery, free evaluation access and production-grade API options.
190K+
indexed dataset pages
32
countries and EU institutions
2019
API-first since
Free API quota
for evaluation and prototypes
SLA
history and push on production APIs
FAQ

Questions before production use

Practical answers on evaluation, licensing, freshness, versioning and support.

api.store is built and operated by Apitalks s.r.o. Company details and a direct contact path are linked in the footer for vendor checks and procurement review.
Yes. Selected APIs include a free API quota, so your team can validate coverage, freshness, response shape and workflow fit before asking for a production plan.
Often yes, but usage rights depend on the source license and dataset. We surface source, license and update metadata where available, and can help review terms before a production integration.
Maintained APIs include update metadata where available. For production integrations, we can add history, monitoring and push updates so changes are easier to detect and act on.
Production APIs can add SLA, stable identifiers, versioning support, history, push updates and direct support around the data your product or AI workflow depends on.

Didn't find the API you need?

Let us know and we will figure it out for you.

European data discovery with free evaluation access and production-grade API options.

Copyright © 2026. Made by Apitalks