Data set of soil freezing depth in the future scenario of Qinghai Tibet Plateau Based on Stefan equation (2007-2017,2046-2065)

Soil freezing depth (SFD) is necessary to evaluate the balance of water resources, surface energy exchange and biogeochemical cycle change in frozen soil area. It is an important indicator of climate change in the cryosphere and is very important to seasonal frozen soil and permafrost. This data is based on Stefan equation, using the daily temperature prediction data and E-factor data of canems2 (rcp45 and rcp85), gfdl-esm2m (rcp26, rcp45, rcp60 and rcp85), hadgem2-es (rcp26, rcp45 and rcp85), ipsl-cm5a-lr (rcp26, rcp45, rcp60 and rcp85), miroc5 (rcp26, rcp45, rcp60 and rcp85) and noresm1-m (rcp26, rcp45, rcp60 and rcp85), The data set of annual average soil freezing depth in the Qinghai Tibet Plateau with a spatial resolution of 0.25 degrees from 2007 to 2065 was obtained.

0 2022-07-22

Occurence records of birds of the fieldwork in winter Tibet, 2020

This database includes the occurrence records of birds in Qinghai-Tibet Plateau produced during the fieldtrip in December 2020 to January 2021. The geographical area mainly covers the middle-down stream of the Yarlung Zangbo River and eastern coast of Namtso lake, covering mang vallies, villiages and wetlands of Lhasa, Linzhi, Shannan, Rikaze. The information of each record is composed of species name, coordinates, date of field observation and observers.

0 2022-07-22

Aboveground biomass and vegetation cover data of Qinghai-Tibet Plateau (1990-2020)

The data set product contains the aboveground biomass and vegetation coverage data products of the Qinghai-Tibet Plateau every five years from 1990 to 2020 (1990, 1995, 2000, 2005, 2010, 2015 and 2020).The aboveground biomass of the Qinghai-Tibet Plateau is the remote sensing inversion product of above-ground biomass inversion models based on different land cover types including grassland, forest, etc. Vegetation coverage data of the Qinghai-Tibet Plateau is inversed using remote sensing by the dimidiate pixel model. Among them, the aboveground biomass and vegetation coverage data from 2000 to 2020 were estimated based on MODIS data, the spatial resolution was 250 m; the aboveground biomass and vegetation coverage data of 1990 and 1995 were estimated based on NOAA AVHRR data, the spatial resolution after resampling process is 250 m. This dataset can provide basic data for revealing the temporal and spatial pattern of land cover areas and quality on the Qinghai-Tibet Plateau and supporting the assessment of ecosystems, ecological assets and ecological security.

0 2022-07-20

Land cover data of Qinghai Tibet Plateau in 1995, 2005 and 2015

The data is the land cover data of the Qinghai Tibet Plateau, with a spatial resolution of 300 meters and a temporal resolution of years. The data includes three periods of 1995, 2005 and 2015. The data is in grid format (TIFF), using the 2000 national geodetic coordinate system, and can be opened using software tools such as ArcGIS and envi. The original data comes from the European Copernicus climate change service data center. With reference to the "land cover classification system" developed by the food and Agriculture Organization of the United Nations, the global land cover types are divided into 22 categories. Because of its high accuracy, consistency and annual update, this data has been widely used in the fields of land use and human activity change monitoring worldwide. Based on the original data, this data is obtained in ArcGIS through clipping, projection, accuracy verification, and quality audit by a second person. The data quality is reliable.

0 2022-07-18

Dataset of Qinghai Lake integrated observatory network (Phenology camera observation data set of Alpine meadow and grassland ecosystem Superstation, 2021)

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from phenology camera observation data of the Alpine meadow and grassland ecosystem Superstation from January 1 in 2021 to December 31 in 2021. Data of January 31 to April 14 is missing due to the spilled storage. The site (98°35′41.62″E, 37°42′11.47″N) was located in the alpine meadow and alpine grassland ecosystem, near the SuGe Road in Tianjun County, Qinghai Province. The elevation is 3718m. The phenology camera adopts a vertical downward method to collect data, with the resolution of 2592*1944. Phenology photos in this data set were taken at 12:10 a day, which has a time error of ±10 min. The image is named as BSDCJZ BEIJING_IR_Year_Month_Day_Time.

0 2022-07-07

Glacier runoff segmentation data set in the five river source areas of the Qinghai Tibet Plateau (1971-2015)

The Qinghai Tibet Plateau is known as the "Asian water tower", and its runoff, as an important and easily accessible water resource, supports the production and life of billions of people around, and supports the diversity of ecosystems. Accurately estimating the runoff of the Qinghai Tibet Plateau and revealing the variation law of runoff are conducive to water resources management and disaster risk avoidance in the plateau and its surrounding areas. The glacier runoff segmentation data set covers the five river source areas of the Qinghai Tibet Plateau from 1971 to 2015, with a time resolution of year by year, covering the five river source areas of the Qinghai Tibet Plateau (the source of the Yellow River, the source of the Yangtze River, the source of the Lancang River, the source of the Nujiang River, and the source of the Yarlung Zangbo River), and the spatial resolution is the watershed. Based on multi-source remote sensing and measured data, it is simulated using the distributed hydrological model vic-cas coupled with the glacier module, The simulation results are verified with the measured data of the station, and all the data are subject to quality control.

0 2022-07-06

Types of surface vegetation within 500m of China Pakistan Economic Corridor and Tianshan Mountains (2020)

This data set collates and collects the surface vegetation type data with 500m spatial resolution in the Qinghai Tibet Plateau and its surrounding areas. The data source is from the official website of the United States Geological Survey (USGS)( https://lpdaac.usgs.gov/products/mod12q1v006/ )This data is the land use and cover product of MODIS level III data, with a spatial resolution of 500m. By using supervised classification of Terra and aqua reflectance data. By applying smoothing splines to the bottom bidirectional reflectance distribution function (BRDF) - adjusted reflectance (nbar) time series, the 6th mcd1201 product developed a new notch filling spectral time feature. In addition, the 6th edition also uses hidden Markov model (HMM) to reduce false changes in category labels. The data set contains 17 major land cover types, including 11 natural vegetation types, 3 land types for land development and mosaic and 3 non vegetation land type definition types according to the international geosphere biosphere program (IGBP). They are: 1-evergreen coniferous forest; 2-evergreen broad-leaved forest; 3-deciduous coniferous forest; 4-deciduous broad-leaved forest; 5-mixed forest; 6-dense shrub; 7- sparse shrub; 8- woody savanna; 9- savanna; 10- grassland; 11- permanent wetlands; 12- agricultural land; 13- cities and construction areas; 14- agricultural land / natural vegetation splicing; 15- snow and ice; 16- bare ground; 17- water.

0 2022-07-01

30 m land cover classification product data set of Qilian Mountain Area in 2021 (V3.0)

This data set is a 30m land cover classification product in the Qilian Mountains in 2021. This product is based on the land cover classification product in 2021, based on the Landsat series data and strong geodetic data processing capability of Google Earth engine platform, and is produced by using the ideas and methods of change detection. The overall accuracy is better than 85%. This product is the continuation of land cover classification products from 1985 to 2020. Land cover classification products from 1985 to 2020 can also be downloaded from this website. Among them, the land use products from 1985 to 2015 are five years and one period, and the land use products from 2015 to 2021 are one year and one period.

0 2022-06-30

Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of Meteorological elements gradient of Yulei station on Qinghai lake, 2021)

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of Yulei station on Qinghai lake from Janurary 1 to December 31, 2021. The site (100° 29' 59.726'' E, 36° 35' 27.337'' N) was located on the Yulei Platform in Erlangjian scenic area, Qinghai Province. The elevation is 3209m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 12 and 12.5 m above the water surface, towards north), wind speed and direction profile (windsonic; 14 m above the water surface, towards north) , rain gauge (TE525M; 10m above the water surface in the eastern part of the Yulei platform ), four-component radiometer (NR01; 10 m above the water surface, towards south), one infrared temperature sensors (SI-111; 10 m above the water surface, towards south, vertically downward), photosynthetically active radiation (LI190SB; 10 m above the water surface, towards south), water temperature profile (109, -0.2, -0.5, -1.0, -2.0, and -3.0 m). The observations included the following: air temperature and humidity (Ta_12 m, Ta_12.5 m; RH_12 m, RH_12.5 m) (℃ and %, respectively), wind speed (Ws_14 m) (m/s), wind direction (WD_14 m) (°) , precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT_1) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), water temperature (Tw_20cm、Tw_50cm、Tw_100cm、Tw_200cm、Tw_300cm) (℃). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. As the lake water freezes in winter, the water temperature probe is withdrawn, so there is no water temperature data record during October 19, 2020 to December 31, 2020. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018-1-1 10:30. Moreover, suspicious data were marked in red.

0 2022-06-30

Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of Meteorological elements gradient of Alpine meadow and grassland ecosystem Superstation, 2021)

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of the Alpine meadow and grassland ecosystem Superstation from January 1 to October 9 in 2021. The site (98°35′41.62″E, 37°42′11.47″N) was located in the alpine meadow and alpine grassland ecosystem, near the SuGe Road in Tianjun County, Qinghai Province. The elevation is 3718m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (PTB110; 3 m), rain gauge (TE525M; 10m of the platform in west by north of tower), four-component radiometer (CNR4; 6m, towards south), two infrared temperature sensors (SI-111; 6 m, towards south, vertically downward), photosynthetically active radiation (PQS1; 6 m, towards south, each with one vertically downward and one vertically upward, soil heat flux (HFP01; 3 duplicates below the vegetation; -0.06 m), soil temperature profile (109; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m), soil moisture profile (CS616; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m, Ta_15 m, Ta_20 m, Ta_30 m, and Ta_40 m; RH_3 m, RH_5 m, RH_10 m, RH_15 m, RH_20 m, RH_30 m, and RH_40 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30m, and WD_40 m) (°), precipitation (rain) (mm), air pressure (press) (hpa), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m-2)), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), soil heat flux (Gs_1, Gs_2, and Gs_3) (W/m^2), soil temperature (Ts_5cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_80cm、Ts_120cm、Ts_200cm、Ts_300cm、Ts_400cm) (℃), soil moisture (Ms_5cm、Ms_10cm、Ms_20cm、Ms_40cm、Ms_80cm、Ms_120cm、Ms_200cm、Ms_300cm、Ms_400cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018/8/31 10:30. Moreover, suspicious data were marked in red.

0 2022-06-29