The data set is the monthly average temperature data of China's multi scenario and multi-mode, with a spatial resolution of 0.0083333 ° (about 1km) from January 2021 to December 2100. The data is in NetCDF format. The data is generated in China through the delta spatial downscaling scheme according to the global > 100 km climate model data set released in the sixth phase of the IPCC coupled model comparison program (cmip6) and the global high-resolution climate data set released by worldclim. The data adopts the latest SSP scenarios (ssp119, ssp245, ssp585) released by IPCC. Each scenario contains three GCMS (ec-earth3, gfdl-esm4, mri-esm2-0) climate data. The geospatial range contained in the dataset is China's main land, excluding islands and reefs in the South China Sea. The unit is 0.1 ℃. The file name is GCM_ SSP_ Tmp-30s-serial number NC, 30s, i.e. 0.0083333 °, serial number from 1-40, serial number 1 represents 2021.1-2022.12, and represents the year in turn; Based on ec-earth3_ ssp119_ tmp-30s-1. NC file, for example, represents the monthly average temperature data of ec-earth3 climate model with 1km resolution from 2021.1 to 2022.12 under ssp119 scenario, including 24 layers. For a deeper understanding of the data, please refer to the data cited in the literature and the published papers of the authors.

The data set mainly includes the ice observation frequency (ICO) of north temperate lakes in four periods from 1985 to 2020, as well as the location, area and elevation of the lakes. Among them, the four time periods are 1985-1998 (P1), 1999-2006 (P2), 2007-2014 (P3) and 2015-2020 (P4) respectively, in order to improve the "valid observation" times in the calculation period and improve the accuracy. The ICO of the four periods is calculated by the ratio of "icing" times and "valid observation" times counted by all Landsat images in each period. Other lake information corresponds to the HydroLAKEs data set through the "hylak_id" column in the table. In addition, the data only retains about 30000 lakes with an area of more than 1 square kilometer, which are valid for P1-P4 observation. The data set can reflect the response of Lake icing to climate change in recent decades.

The recent glacial changes in the third polar region have become the focus of the governments of the surrounding countries because of their important significance to the downstream water supply. Based on SRTM acquired in 2000 and aster stereo image pairs before and after 2015, more than 40 Typical Glaciers in the third polar region were selected to estimate the glacial surface elevation in corresponding period. This product estimates the surface elevation changes of more than 14000 glaciers in the third polar region in 2000-2015s, and the investigated area accounts for about 25% of the total glaciers in the third polar region. The data covers the whole third pole area except Altai mountain, with a spatial resolution of 30m.

Glacier thickness is the vertical distance between the glacier surface and the glacier bottom. The distribution of glacier thickness is not only controlled by glacier scale and subglacial topography, but also varies with different stages of glacier response to climate. The data include longitude and latitude, elevation, single point thickness, total ice reserves and instrument type of glacier survey line. The glacier thickness mainly comes from drilling and ground penetrating radar (GPR). The drilling method is to drill holes on the ice surface to the bedrock under the ice, so as to obtain the thickness of the glacier at a single point; Glacier radar thickness measurement technology can accurately measure the continuous distribution of glacier thickness on the survey line, and obtain the topographic characteristics of subglacial bedrock, so as to provide necessary parameters for the estimation of glacier reserves and the study of glacier dynamics The accuracy of glacier drilling data reaches decimeter level. The accuracy of thickness measurement by GPR radar is between 5% and 15% in theory due to the difference of glacier properties and radar signal strength of bottom interface. Glacier thickness is a prerequisite for obtaining information of subglacial topography and glacier reserves. In the numerical simulation and model study of glacier dynamics, glacier thickness is an important basic input parameter. At the same time, glacier reserve is the most direct parameter to characterize glacier scale and glacier water resources. It is not only very important for accurate assessment, reasonable planning and effective utilization of glacier water resources, but also has important and far-reaching significance for regional socio-economic development and ecological security.

Qiangyong glacier: 90.23 °E, 28.88° N, 4898 m asl. The surface is bedrock. The record contains data of absolute pressure and water temperature. Data from the automatic water gauge was collected using USB equipment at 12:00 on June 15, 2021, with a recording interval of one hour, and data was downloaded at 12:00 on Nov. 2, 2021. There is no missing data. Jiagang glacier: 88.69°E, 30.82°N, 5362 m asl. The surface is rubble and weeds. The record contains data of absolute pressure and water temperature. Data from the automatic water gauge was collected using USB equipment at 20:00 on June 19, 2021, with a recording interval of one hour, and data was downloaded at 11:00 onSept 18 , 2021. There is no missing data.

Qiangyong glacier: 90.23 °E, 28.88° N, 4898 m asl. The surface is bedrock. The record contains data of 1.5 m temperature, 1.5 m humidity, 2 m wind speed, 2 m wind orientation, surface temperature, etc. Data from the automated weather station was collected using USB equipment at 19:10 on August 6, 2019, with a recording interval of 10 minutes, and data was downloaded on December 20, 2020. There is no missing data but a problem with the wind speed data after 9:30 on July 14, 2020 (most likely due to damage to the wind vane). Jiagang glacier: 88.69°E, 30.82°N, 5362 m asl. The surface is rubble and weeds. The records include 1.5 meters of temperature, 1.5 meters of humidity, 2 meters of wind speed, 2 meters of wind direction, surface temperature, etc. The initial recording time is 15:00 on August 9, 2019, and the recording interval is 1 minute. The power supply is mainly maintained by batteries and solar panels. The automatic weather station has no internal storage. The data is uploaded to the Hobo website via GPRS every hour and downloaded regularly. At 23:34 on January 5, 2020, the 1.5 meter temperature and humidity sensor was abnormal, and the temperature and humidity data were lost. The data acquisition instrument will be retrieved on December 19, 2020 and downloaded to 19:43 on June 23, 2020 and 3:36 on September 25, 2020. Then the temperature and humidity sensors were replaced, and the observations resumed at 12:27 on December 21. The current data consists of three segments (2019.8.9-2020.6.30; 2020.6.23-2020.9.25; 2020.12.19-2020.12.29), Some data are missing after inspection. Some data are duplicated in time due to recording battery voltage, which needs to be checked. The meteorological observation data at the front end of Jiagang mountain glacier are collected by the automatic weather station Hobo rx3004-00-01 of onset company. The model of temperature and humidity probe is s-thb-m002, the model of wind speed and direction sensor is s-wset-b, and the model of ground temperature sensor is s-tmb-m006. The meteorological observation data at the front end of Jianyong glacier are collected by the US onset Hobo u21-usb automatic weather station. The temperature and humidity probe model is s-thb-m002, the wind speed and direction sensor model is s-wset-b, and the ground temperature sensor model is s-tmb-m006.

The data in the form of .xlsx store the meteorological varialbes observed on the East Rongbuk glacier from May to July. Two sheets, named "Surface_energy_budget" and "Cycle", respectivley, are included. In the sheet of "surface_energy_budget", the meteorological variables are as follows: Four-component radiations (incident solar radiation, reflected shortwave radiation, incoming longwave radiation, outgoing longwave radiation)、wind speed and direction, air temperature and relative humidity, cloud index, south Asian summer monsoon and albedo. In addition, net shortwave radiation, net longwave radiation, net radiation, sensible heat, latent heat and subsurface heat are also included. Energy fluxes are in unit of W m-2. The sheet of "Cycle" stores the diurnal cycle of the meteorological variables mentioned above. In the first line, the prefixes of "1"、"2" and “3” indicate three observational periods, i.e., "1" represents days from 1 - 28 May, "2" represents the period between 29 May 16 June and "3" indicates time episode from 17 June to 22 July.

The RCM employed is the International Center for Theoretical Physics (ICTP) Regional Climate Model version 4 (RegCM4, Giorgi et al., 2012). The domain used is the Coordinated Regional Climate Downscaling Experiment (CORDEX) Phase II East Asia domain, covering whole of China and its surrounding East Asia areas. The model is run at 25 km gird spacing, with its standard configuration of 18 vertical sigma layers with a model top at 10 hPa. Configuration of the model follows Gao et al. (2016, 2017), with land cover data over China was updated as reported by Han et al. (2015) to better represent the realistic vegetation. The initial and lateral boundary conditions needed to drive RegCM4 are derived from the CMIP5 models of HadGEM2-ES (RCP4.5 pathways), and the data set include temperature and precipitation.

Based on the field survey, the aboveground and underground biomass of vegetation, and soil carbon and nitrogen contents in Nagqu， in the north of Zoige, eastern of Tibet plateau and the wind vacanofrom 2015 to 2017 were collected, and the data were collated and preliminarily analyzed. Dataset consists both of the aboveground and underground biomass of vegetation and soil carbon and nitrogen contents in different elevation gradient (subalpine meadow, alpine meadow, alpine shrub meadow), different moisture gradient (wetland, degraded swamp, swamp meadow, wet meadow, dry meadow and degraded meadow) and the different desertification degree (mild desertification, moderate desertification, severe desertification, desertification). The differences and trends of vegetation biomass and soil carbon and nitrogen contents under different gradients were analyzed. This dataset provides a theoretical basis for understanding and rational utilization of grassland resources, and also provides strong support for exploring the prediction of alpine grassland productivity under the global climate change.

Radar penetration correction is essential for accurately estimating glacier mass balance when using the geodetic methods based on the radar-derived Digital Elevation Model (DEM). Due to heterogeneous snow distribution and snowpack properties, the radar penetration depth varies by region and is basically dependent on the altitudes. Therefore, this data set gives the result of the penetration depth difference of SRTM C/X-band radar on 1°×1° grid of High Mountain Asia Glaciers. The data set contains 214 1°×1° grids SRTM X-band and C-band penetration depth difference in HMA, and a linear fitting expression for each grid. According to the geodetic method, the 30 m SRTM X-band and C-band DEM are used to obtain the results of the penetration depth difference between the SRTM X-band and C-band of the 1°×1° high grid in HMA, and obtain the relationship between the SRTM X-C-band penetration depth difference and the elevation in the glacier area (for specific methods, please refer to references). The data is stored in excel files. Observational data can provide important basic data for studying the glacier mass balance in HMA, and can be used by scientific researchers studying climate, hydrology and glaciers.

High Asia is very sensitive to climate change, and is a hot area of global change research. The changes of temperature and precipitation will be reflected in the freezing and thawing time of ice and snow. Satellite microwave remote sensing can provide continuous monitoring ability of ice and snow surface state in time and space. When a small part of ice and snow begins to melt, micro liquid water will also be reflected in active and passive microwave remote sensing signals. In the microwave band, the dielectric constant of ice and liquid water is very different, so it provides a basic theory for the microwave remote sensing monitoring of ice and snow melting. In the case of passive microwave, when ice and snow begin to melt and liquid water appears, its absorption and emissivity increase rapidly, so its emissivity, brightness temperature and backscatter coefficient will also change rapidly. This data set is the initial time of ice and snow melting in the high Asia region retrieved by using the satellite microwave radiometer and scatterometer observations from 1979 to 2018. The passive microwave remote sensing data are SMMR on satellite (1979-1987) and SSM / i-ssmis radiometer on DMSP (1988 present). The active microwave remote sensing data is the QuikSCAT satellite scatterometer (2000-2009).

The melting observation of Hengduan Moutain glacier is mainly carried out on Hailuogou Glacier on the east slope of Gongga and the large and small Gongba glacier on the west slope of Gongga. In addition, some ablation observations have been made on Baishui 1 glacier on the east slope of Yulong. According to the melting observation of the four glaciers in the above two mountains, there are some regional representativeness, which makes them reflect the basic situation of melting glaciers in Hengduan Mountain. This data set records the glacier ablation data of different time and different places: from June to August 1982, the Glacier No. 1 in Baishui on the east slope of Yulong mountain was observed at the altitude of 4200m, 4600m and 4800m. From August 27, 1982 to the end of August 1983, the annual measured data of different heights of Hailuogou Glacier tongue on the east slope of Gongga Mountain were collected. From July 12, 1982 to August 6, 1983, the observation data of Gongba glacier melting on the west slope of Gongga Mountain were recorded.