The basic data for the accounting of ice and snow ecological product value in Hulunbuir City in 2024

During data processing, all original raster data were geometrically co-registered and resampled to a unified spatial reference, then masked to the administrative boundary of Hulunbuir City. Monthly indicators such as snow cover fraction, mean snow depth, and mean snow depth over farmland were derived through zonal statistics; monthly precipitation, runoff, and evapotranspiration were obtained by averaging the corresponding monthly raster values over each region.

Snow cover duration was calculated as the cumulative number of snow-covered days per pixel, then averaged regionally; sunshine intensity was converted from shortwave radiation totals to hourly averages. Finally, all indicators were compiled into a structured table by region, forming a quantifiable basis for accounting purposes.In terms of spatiotemporal coverage, the dataset spans 14 banner- and county-level administrative divisions within Hulunbuir City, namely: Hailar District, Zalainuoer District, Arun Banner, Morin Dawa Daur Autonomous Banner, Oroqen Autonomous Banner, Ewenki Autonomous Banner, New Barag Right Banner, New Barag Left Banner, Chen Barag Banner, Manzhouli City, Yakeshi City, Zhalantun City, Ergun City, and Genhe City.

The temporal coverage is the full year of 2024, with particular focus on the critical snow season months (January–April and October–December), at a monthly temporal resolution. The data table comprises 14 records corresponding to the 14 administrative regions. Each row represents the annual aggregated indicators for a given banner/county/district.

The columns fall into three categories: (1) regional identifiers, area (km²), and annual tourism revenue (100 million RMB); (2) monthly hydrological and snow parameters, including precipitation, surface runoff, evapotranspiration, snow cover fraction (%), snow cover duration (days), mean snow depth (cm), and mean snow depth over farmland (cm) for each month, with snow-season sunshine intensity (hours/day) additionally provided only for October and December; and (3) annual summary statistics, including mean snow cover fraction, total snow cover duration, mean snow depth, and mean snow depth over farmland.

All numerical indicators are reported in metric units: precipitation, runoff, and evapotranspiration are in millimetres (monthly means), snow depth in centimetres, snow cover fraction in percentage, duration in days, and tourism revenue in 100 million RMB.Regarding data quality, it should be clearly noted that certain fields are missing for specific regions. Specifically, "mean snow depth over farmland" is not recorded (indicated by "–") for Zalainuoer District, Morin Dawa Daur Autonomous Banner, and Manzhouli City across all months and in the annual summary, due to the very limited extent of farmland in these areas or the lack of reliable remotely sensed snow depth signals over agricultural land.

In addition, a small number of monthly records for snow cover fraction or snow depth are missing for Oroqen Autonomous Banner, New Barag Right Banner, New Barag Left Banner, and Ergun City, likely due to cloud cover affecting MODIS snow product retrievals or invalid ERA5-Land pixels. Missing values have been estimated and filled using regional averages; however, users are advised to be aware of their potential influence on regional summary statistics.

The primary sources of error inherent in this dataset stem from the uncertainty in original retrieval algorithms, the smoothing effects introduced by spatial resampling, and cumulative biases when converting hourly snow cover duration and shortwave radiation into monthly indicators. In particular, MODIS snow products have relatively limited accuracy over forested areas, and ERA5-Land reanalysis data exhibit root-mean-square errors of approximately 5–15 cm for snow depth at local scales.

However, after regional multi-pixel averaging, these errors are substantially mitigated for accounting purposes at the banner/county level.The final data file is a single Excel workbook (.xlsx format) containing one worksheet, which is the integrated indicator matrix with 14 rows and 58 columns described above. This file format is a common office format and can be opened and edited directly with mainstream spreadsheet software such as Microsoft Excel (2016 or later), WPS Office, or LibreOffice Calc, requiring no specialised software.

Users are encouraged to cross-validate this dataset against local in-situ snow depth measurements and meteorological observations when applying it to ecological product value accounting, and to carefully distinguish between snow depth over farmland and non-farmland areas, so as to ensure the accuracy and regional comparability of the accounting results.