SWECA: High-resolution daily Snow Water Equivalent estimates for Mountainous Central Asia (1979–2016)
Description
The dataset provides daily estimates of snow water equivalent (SWE) for Central Asia, at a spatial resolution of 1km, covering the period from 1979 to 2016. The dataset were generated within the SWECA project, supported by GEO Mountains under the Adaptation at Altitude Programme (Swiss Agency for Development and Cooperation Project Number: 7F-10208.01.02).
Spatial Domain:
The dataset encompasses the Central Asian region within the bounding coordinates 61W, 81E, 44N, 34S, which covers the Tian-Shan and Pamir mountains, a larger extent of the Hindukush mountains, and the northern part of the Karakoram mountains.
Data Generation and Validation:
The SWE data was generated using the GEMS snow model (Umirbekov, Essery, and Müller, 2024), forced by CHELSA-W5E5 daily climate data (Karger et al., 2023). Simulated SWE was validated using historical records of SWE from 1980 to 1992 from Central Asian Snow Survey database (Bedford and Tsarev, 2001), and by comparing extent of the modelled SWE with MODIS derived snowcover for two consecutive hydrological years (2015-2016). Data generation procedures and validation results will be provided in upcoming data description paper (TBD).
File Descriptions:
The daily SWE estimates (in millimeters) are compiled into 37 GeoTIFF files, each corresponding to a hydrological year from 1979 to 2016. The hydrological year begins on October 1st and concludes on September 30th of next year. To avoid the need for auxiliary files, the corresponding date of each layer in the GeoTIFF file is incorporated as a layer`s name.
References:
- Bedford, D. and Tsarev, B. (2001) ‘Central Asian Snow Cover from Hydrometeorological Surveys, Version 1 [Dataset]’. Boulder, Colorado USA.: National Snow and Ice Data Center. doi: 10.7265/N51Z4291.
- Karger, D. N. et al. (2023) ‘CHELSA-W5E5: daily 1km meteorological forcing data for climate impact studies’, Earth System Science Data, 15(6), pp. 2445–2464. doi: 10.5194/essd-15-2445-2023.
- Riggs, G., Hall, D. and Salomonson, V. (2019) ‘MODIS snow products user guide to collection 6.1: MODIS-derived snow cover retrievals using the cloud-gap-filled MOD10A1F product’.
- Umirbekov, A., Essery, R. and Müller, D. (2024) ‘GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers’, Geoscientific Model Development, 17(2), pp. 911–929. doi: 10.5194/gmd-17-911-2024.
Files
SWECA_v01_19791001_19800930.tif
Files
(38.7 GB)
Name | Size | Download all |
---|---|---|
md5:2040d4441bce914c60b942bfd5817417
|
1.0 GB | Preview Download |
md5:4db0e308bc67b23626ce716519242b28
|
1.1 GB | Preview Download |
md5:c51173789dbd0c7c7dec17194731d4ca
|
969.3 MB | Preview Download |
md5:2e379c35db6978fb271bdfc53bdc19df
|
1.1 GB | Preview Download |
md5:861cde139224fe1d5af3ea019868d705
|
965.1 MB | Preview Download |
md5:dacae40b008218241a51e47f31cd6565
|
1.1 GB | Preview Download |
md5:6f976af8ce54a5ffcaacc461c9e23598
|
1.0 GB | Preview Download |
md5:3a6ac8660a2625b426db4834557f83ba
|
1.1 GB | Preview Download |
md5:74fe1e2849636a382abbafd9eb4ee34c
|
1.2 GB | Preview Download |
md5:972ba3351ba6f4c4a06a6e86303467ef
|
1.0 GB | Preview Download |
md5:d640cb6f04168e6b4742bab9150d2fe0
|
1.1 GB | Preview Download |
md5:5bb4fcac02a5bcfdde37aca81b479cfc
|
1.1 GB | Preview Download |
md5:42451311c770b846fe2b18db21ac8ac9
|
1.1 GB | Preview Download |
md5:ba5714b1bd64e714f6ef5b4e5b237413
|
1.1 GB | Preview Download |
md5:8bc1e4fc9e679799ddc1a60942013ff8
|
1.2 GB | Preview Download |
md5:5fcd5af87df1f3d01cb78cc5ce4eb743
|
1.0 GB | Preview Download |
md5:a61f1c3c0f9ab98aa6a8618e1f7fd6e5
|
1.1 GB | Preview Download |
md5:2d12fdac1feef113890a91757a1cbd3f
|
903.8 MB | Preview Download |
md5:f0bb1c9310d2904b9544ab21cae1ce35
|
1.2 GB | Preview Download |
md5:eb7bb35f1b516540b76b4bd34d07d73a
|
767.2 MB | Preview Download |
md5:4dde9c199ac69e8227ad3172a007f1df
|
739.9 MB | Preview Download |
md5:4c2e04d044ba6d9d5c947668fad3391e
|
1.2 GB | Preview Download |
md5:77a67ee6be5a30d13b78b9d286e931e9
|
1.5 GB | Preview Download |
md5:c54f26a5ce8d6aa719740491bf16a7ef
|
1.1 GB | Preview Download |
md5:aa78422c25f1874488dbe7afdfbc24b5
|
978.8 MB | Preview Download |
md5:0d033d8a13808cea07f086310d4feed5
|
1.1 GB | Preview Download |
md5:b1aa555ca6ed09eeef3e5227b4aee8cc
|
963.9 MB | Preview Download |
md5:461d0765d940d4a0111c9e1be2c97a57
|
902.4 MB | Preview Download |
md5:e08eb52ebc439704628ab07c55a9b3e0
|
940.8 MB | Preview Download |
md5:d4d29b620069ebe2783414bd4cffc2c9
|
991.8 MB | Preview Download |
md5:9b34e90ad7c2e71f7172439cfba46371
|
1.0 GB | Preview Download |
md5:a80af22da75891c1ac3df666d18eb726
|
859.8 MB | Preview Download |
md5:5f7a9c896551431a590b14a3399c3deb
|
1.2 GB | Preview Download |
md5:069226b0dcee7ecaf572b780239d3d77
|
982.5 MB | Preview Download |
md5:15dad06e280198f9c103f2eab48c68c0
|
958.5 MB | Preview Download |
md5:984893ebd12c4ebc547e67fc8545d1ba
|
1.0 GB | Preview Download |
md5:10ac96d8b4b3986b6fd90dfe63fd5da6
|
919.8 MB | Preview Download |