Current Browsing: Snow

Data set of spatial and temporal distribution of water resources in Indus from 1998 to 2017

This data is a 5km monthly hydrological data set, including grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation), simulated and output through the WEB-DHM distributed hydrological model of the Indus River basin, with temperature, precipitation, barometric pressure, etc. as input data.


Global average annual snow cover proportion data (2000-2021)

The fractional snow cover (FSC) is the ratio of snow cover area (SCA) to unit pixel area. The data set is made by bv-blrm snow area proportional linear regression empirical model; The source data used are mod09ga 500m global daily surface reflectance products and mod09a1 500m 8-day synthetic global surface reflectance products; The production platform uses Google Earth engine; The data range is global, the data preparation time is from 2000 to 2021, the spatial resolution is 500 meters, and the temporal resolution is year by year. This set of data can provide quantitative information of snow cover distribution for regional climate simulation and hydrological models.


30km Gridded dataset of Snowline altitude in High Mountain Asia (2001-2019)

High Mountain Asia is the third largest cryosphere on earth other than the Antarctic and Arctic regions. The large amounts of glaciers and snow over the High Mountain Asia play an important role not only on global water cycle but also on water resources and ecology of the arid regions of central Asia. The snowline, as the lower boundary of the snow covered area at the end of melting season, its altitude changes can directly reflect the changes in snow and glaciers. The snowline altitude provides a possibility to rapidly obtain a proxy for their equilibrium line altitude (ELA) which in turn is an indicator for the glacier mass balance. In this dataset, the daily MODIS snow cover products from 2001 to 2019 are used as the main data source. The cloud removal of the daily MODIS snow cover products was firstly carried out based on the developed cubic spline interpolation cloud-removel method, and snow covered days (SCD) are extracted using the cloud-removed MODIS snow cover products. In addition, the MODIS SCD threshold for estimating perennial snow cover is calibrated using the observed data of glacier annual mass balance and Landsat data at the end of melting season. The altitude value of the snowline at the end of melting season is determined by combining the perennial snow cover area and the hypsometric (area-elevation) curve. Finally, the 30km gridded dataset of snowline altitude in the High Mountain Asia during 2001-2019 is generated. This dataset can provide data support for the study of cryosphere and climate change over the High Mountain Asia.


A daily, 0.05° Snow depth dataset for Tibetan Plateau (2000-2018)

Under the funding of the first project (Development of Multi-scale Observation and Data Products of Key Cryosphere Parameters) of the National Key Research and Development Program of China-"The Observation and Inversion of Key Parameters of Cryosphere and Polar Environmental Changes", the research group of Zhang, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, developed the snow depth downscaling product in the Qinghai-Tibet Plateau. The snow depth downscaling data set for the Tibetan Plateau is derived from the fusion of snow cover probability dataset and Long-term snow depth dataset in China. The sub-pixel spatio-temporal downscaling algorithm is developed to downscale the original 0.25° snow depth dataset, and the 0.05° daily snow depth product is obtained. By comparing the accuracy evaluation of the snow depth product before and after downscaling, it is found that the root mean square error of the snow depth downscaling product is 0.61 cm less than the original product. The details of the product information of the Downscaling of Snow Depth Dataset for the Tibetan Plateau (2000-2018) are as follows. The projection is longitude and latitude, the spatial resolution is 0.05° (about 5km), and the time is from September 1, 2000 to September 1, 2018. It is a TIF format file. The naming rule is SD_yyyyddd.tif, where yyyy represents year and DDD represents Julian day (001-365). Snow depth (SD), unit: centimeter (cm). The spatial resolution is 0.05°. The time resolution is day by day.


Meteorological, albedo and evapotranspiration data set of hulugou shrub experimental area in the upper reaches of Heihe River (2012-2014)

The data set is the meteorological and observational data of hulugou shrub experimental area in the upper reaches of Heihe River, including meteorological data, albedo data and evapotranspiration data under shrubs. 1. Meteorological data: Qilian station longitude: 99 ° 52 ′ E; latitude: 38 ° 15 ′ n; altitude: 3232.3m, scale meteorological data from January 1, 2012 to December 31, 2013. Observation items include: temperature, humidity, vapor pressure, net radiation, four component radiation, etc. The data are daily scale data, and the calculation period is 0:00-24:00 2. Albedo: daily surface albedo data from January 1, 2012 to July 3, 2014, including snow and non snow periods. The measuring instrument is the radiation instrument on the 10m gradient tower in hulugou watershed. Among them, the data from August 4 to October 2, 2012 was missing due to instrument circuit problems, and the rest data quality was good 3. Evapotranspiration: surface evapotranspiration data of Four Typical Shrub Communities in hulugou watershed. The observation period is from July 18 to August 5, 2014, which is the daily scale data. The data include precipitation data, evaporation and infiltration data observed by lysimeter. The data set can be used to analyze the evapotranspiration data of alpine shrubs and forests. The evapotranspiration of grassland under canopy was measured by a small lysimeter with a diameter of 25 cm and a depth of 30 cm. Two lysimeters were set up in each shrub plot, and one lysimeter was set for each shrub in transplanting experiment. The undisturbed undisturbed soil column with the same height as the barrel is placed in the inner bucket, and the outer bucket is buried in the soil. During the embedding, the outer bucket shall be 0.5-1.0 cm higher than the ground, and the outer edge of the inner barrel shall be designed with a rainproof board about 2.0 cm wide to prevent surface runoff from entering the lysimeter. Lysimeter was set up in the nearby meteorological stations to measure grassland evapotranspiration, and a small lysimeter with an inner diameter of 25 cm and a depth of 30 cm was also set up in the sample plot of Picea crassifolia forest to measure the evaporation under the forest. All lysimeters are weighed at 20:00 every day (the electronic balance has a sensing capacity of 1.0 g, which is equivalent to 0.013 mm evaporation). Wind proof treatment should be taken to ensure the accuracy of measurement. Data processing method: evapotranspiration is mainly calculated by mass conservation in lysimeter method. According to the design principle of lysimeter lysimeter, evapotranspiration is mainly determined by the quality difference in two consecutive days. Since it is weighed every day, it is calculated by water balance.


Wind snow data of dadongshuyakou observation station in Heihe River basin (2014)

This data includes the distribution along the height of the blowing snow flux collected during the wind-blown snow event at the big winter tree pass observation station (longitude 100 degrees 14 minutes 28 seconds east and latitude 38 degrees 00 minutes 58 seconds north) on December 17, 2013 at solstice on July 9, 2014.


Daily cloudless MODIS snow albedo dataset of Babaohe River basin (2008-2014)

The proportion data set of daily cloudless MODIS snow cover area in babaohe river basin (2008.1.1-2014.6.1) was obtained after cloud removal processing using a cloud removal algorithm based on cubic spline function interpolation on the basis of daily cloudless MODIS snow cover product-mod10a1 (tang zhiguang, 2013). This data set adopts the projection method of UTM (horizontal axis isometric cutting cylinder), with a spatial resolution of 500m, and provides Daily Snow Albedo daily-sad results for the babao river basin.The data set is a daily file from January 1, 2008 to June 1, 2014.Each file is the snow albedo result of the day, with a value of 0-100 (%), is the ENVI standard file, and the naming rule is: mod10a1.ayyyyddd_h25v05_snow_sad_grid_2d_reproj_babaohe_nocloud.img, where YYYY represents the year, DDD stands for Julian day (001-365/366).The file can be opened directly with ENVI or ARCMAP software. The original MODIS snow cover data products processed by declouding are derived from MOD10A1 products processed by the us national snow and ice data center (NSIDC). This data set is in HDF format and USES sinusoidal projection. The attributes of the cloud-free MODIS albedo data set (2008.1.1-2014.1.1) in babaohe river basin are composed of the spatial and temporal resolution, projection information and data format of the dataset.


WATER: Dataset of intensive snow parameter measurements in the Binggou watershed foci experimental area on Mar. 11, 2008

The dataset of intensive snow parameter measurements was obtained in the Binggou watershed foci experimental area on Mar. 11, 2008. Those provide reliable data for retrieval of snow parameters from remote sensing approaches. Observation items included the snow layer temperature by the probe thermometer, the snow grain size by the handheld microscope, snow density by the aluminum case, the snow surface temperature by the handheld infrared thermometer, and the snow-soil interface temperature by the handheld infrared thermometer in three plots in BG-Z. 4 points were selected and measured 4 times in each plot. Two files including raw data and preprocessed data (3 subfolders enclosed) on snow properties were archived; besides, profile pictures of each point were also included.