The dataset of automatic meteorological observations was obtained at the Dayekou Maliantan grassland station (E100°18′/N38°33′, 2817m) from Nov. 2, 2007 to Dec. 31, 2009. The experimental area with a flat and open terrain was slightly sloping from southeast to northwest. The landscape was mainly grassland, with vegetation 0.2-0.5m high. Observation items were multilayer gradient (2m and 10m) of the wind speed, the air temperature and air humidity, the air pressure, precipitation, four components of radiation, the multilayer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm, and 120cm), soil moisture (5cm, 10cm, 20cm, 40cm, 80cm, and 120cm), and soil heat flux (5cm & 15cm). The raw data were level0 and the data after basic processes were level1, in which ambiguous ones were marked; the data after strict quality control were defined as Level2. The data files were named as follows: station+datalevel+AMS+datadate. Level2 or above were strongly recommended to domestic users. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
0 2019-09-15
This data is based on the 1:50,000 and 1:100,000 base maps of hexi and ejin by lanzhou institute of desert research, Chinese academy of sciences, and compiled by supplementary investigation.(1) land type map of zhangye region of gansu province and alashan right banner of Inner Mongolia (Chen longheng, 1:250,000);(2) soil map of beidahe river basin (li fuxing, Yang constituent system, 1:100,000);(3) land type map of ejin banner delta in Inner Mongolia (ejin banner delta research team, lanzhou desert research institute, Chinese academy of sciences, 1:250,000).The drawing USES the basic map data, the field route investigation mainly, the aerial photograph, the guardian photograph interpretation combination method.This chart by li fuxing, qiu baoming compilation, zhang ziyu participated in the work;Drawing for peng shilong, wang xizhang, guo yingsheng.The soil classification research group of nanjing institute of soil research, Chinese academy of sciences and li jin provided the classification and mapping specifications.According to the Chinese soil classification system and the field conditions, the soil in heihe river basin is divided into 8 soil classes, 12 subclasses, 23 soil classes and 60 subclasses.Its purpose is to reflect the main soil types, combinations and distribution rules of the region, and reflect the regional characteristics of the soil, comprehensively demonstrate the generalization of soil resources, and provide the basic scientific basis for the estimation and evaluation of the quantity and quality of land resources, the rational utilization of land resources and the rational redistribution of water resources basins.See attachment for soil data type attributes.
0 2020-06-05
We produced surface photosynthetic effective radiation (PAR), solar radiation (SSR) and net radiation (NR) products with 1KM resolution in the heihe basin in 2012.The temporal resolution ranges from instantaneous to hourly and daily.Day-by-day ancillary data were also produced, including aerosol optical thickness, moisture content, NDVI, snow cover, and surface albedo.Among them, PAR and SSR use the method of lookup table to directly invert by combining the stationary weather satellite and polar orbit satellite MODIS product.NR was calculated by analyzing the relationship between net short-wave and net surface radiation.Hourly instantaneous products are weighted by average and integral to obtain hourly and daily cumulative products.
0 2020-03-15
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.
0 2019-05-23
Global warming and human activities have led to the degradation of permafrost and the collapse of permafrost, which have seriously affected the construction of permafrost projects and the ecological environment. Based on high-resolution satellite images, the permafrost of oboling in Heihe River Basin of Qinghai Tibet Plateau is taken as the research area, and the object-oriented classification technology of machine learning is used to extract the thermal collapse information in the research area. The results show that from 2009 to 2019, the number of thermal collapse increased from 12 to 16, and the total area increased from 14718.9 square meters to 28579.5 square meters, nearly twice. The combination of high spatial resolution remote sensing and object-oriented classification method has a broad application prospect in the monitoring of thermal thawing and collapse of frozen soil.
0 2020-03-14
The dataset of airborne WiDAS mission was obtained in the A'rou flight zone on Jul. 7, 2008. Due to cloud/cloud shadow influence, atmospheric correction could not be performed, and geometric registration was performed manually instead of automatic matching. Level-2B (after radiometric and manual geometric corrections) and mosaic images were available for users. For the visible near infrared band the resolution is 1.25m, Radiance was recorded (W/ (sr•m^2•nm);DN=Radiance*100000); for TIR band, the brightness temperature was recorded (℃; DN=Brightness_Temperature*100) . The flying time of each route was as follows: {| ! id ! flight ! relative height ! starttime ! endtime ! data size ! data state ! data quality ! ground targets |- | 1 || 6#1 || 1500m || 13:43:18 || 13:46:26 || 48 || incomplete || incomplete |- | 2 || 6#3 || 1500m || 13:52:26 || 13:55:18 || 43 || incomplete || incomplete |- | 3 || 6#5 || 1500m || 13:59:30 || 14:02:38 || 48 || incomplete || incomplete || A’rou freeze/thaw observation station |- | 4 || 6#7 || 1500m || 14:08:02 || 14:11:02 || 46 || incomplete || incomplete |}
0 2019-05-23
The aerosol optical thickness data of the Arctic Alaska station is based on the observation data products of the atmospheric radiation observation plan of the U.S. Department of energy at the Arctic Alaska station. The data coverage time is from 1998 to 2016, and the time resolution is hour by hour. The coverage site is the Arctic Alaska station, with the longitude and latitude coordinates of (71 ° 19 ′ 22.8 ″ n, 156 ° 36 ′ 32.4 ″ w). The source of the observed data is retrieved from the radiation data observed by mfrsr instrument. The optical characteristic variable is aerosol optical thickness, and the error range of the observed inversion is about 15%. The data format is NC format.
0 2020-01-12
The dataset of ground truth measurements synchronizing with airborne WiDAS mission was obtained in the Linze grassland foci experimental area on Jun. 29, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data were mainly the land surface temperature measured by the hand-held infrared thermometer in the reed plot A, the saline plots B and C and the barley plot E, the maximum of which were 120m×120m and the minimum were 30m×30m. Data were archived in Excel file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
0 2019-05-23
The data is clipped from "1: 1 million wetland data of China". "1: 1 million wetland data of China" mainly reflects the national marsh wetland information in the 2000s. It is expressed in geographic coordinates using the decimal degree. The main contents include: marsh wetland types, wetland water supply types, soil types, main vegetation types, geographical area, etc. Implemented the "Standard for Information Classification and Coding of Sustainable Development Information Sharing System of China". Data source of this database: 1:20 swamp map (internal version), Tibetan Plateau 1: 500,000 swamp map (internal version), swamp survey data 1: 1 million and national 1: 4 million swamp map; processing steps are: data source selection, preprocessing, digitization and encoding of marsh wetland elements, data editing processing, establishing topological relationships, edge processing, projection conversion, linking with attribute databases such as place names and obtaining attribute data.
0 2020-06-08
CMADS V1.0(The China Meteorological Assimilation Driving Datasets for the SWAT model Version 1.0)Version of the data set introduces the technology of STMAS assimilation algorithm . It was constructed using multiple technologies and scientific methods, including loop nesting of data, projection of resampling models, and bilinear interpolation. The CMADS series of datasets can be used to drive various hydrological models, such as SWAT, the Variable Infiltration Capacity (VIC) model, and the Storm Water Management model (SWMM). It also allows users to conveniently extract a wide range of meteorological elements for detailed climatic analyses. Data sources for the CMADS series include nearly 40,000 regional automatic stations under China’s 2,421 national automatic and business assessment centres. This ensures that the CMADS datasets have wide applicability within the country, and that data accuracy was vastly improved. The CMADS series of datasets has undergone finishing and correction to match the specific format of input and driving data of SWAT models. This reduces the volume of complex work that model builders have to deal with. An index table of the various elements encompassing all of East Asia was also established for SWAT models. This allows the models to utilize the datasets directly, thus eliminating the need for any format conversion or calculations using weather generators. Consequently, significant improvements to the modelling speed and output accuracy of SWAT models were achieved. Most of the source data in the CMADS datasets are derived from CLDAS in China and other reanalysis data in the world. The integration of air temperature, air pressure, humidity, and wind velocity data was mainly achieved through the LAPS/STMAS system. Precipitation data were stitched using CMORPH’s global precipitation products and the National Meteorological Information Center’s data of China (which is based on CMORPH’s integrated precipitation products). The latter contains daily precipitation records observed at 2,400 national meteorological stations and the CMORPH satellite’s inversion precipitation products.The inversion algorithm for incoming solar radiation at the ground surface makes use of the discrete longitudinal method by Stamnes et al.(1988)to calculate radiation transmission. The resolutions for CMADS V1.0, V1.1, V1.2, and V1.3 were 1/3°, 1/4°, 1/8°, and 1/16°, respectively. In CMADS V1.0 (at a spatial resolution of 1/3°), East Asia was spatially divided into 195 × 300 grid points containing 58,500 stations. Despite being at the same spatial resolution as CMADS V1.0, CMADS V1.1 contains more data, with 260 × 400 grid points containing 104,000 stations. For both versions, the stations’ daily data include average solar radiation, average temperature, average pressure, maximum and minimum temperature, specific humidity, cumulative precipitation, and average wind velocity. The CMADS comprises other variables for any hydrological model（under 'For-other-model' folder ）: Daily Average Temperature, Daily Maximum Temperature, Daily Minimum Temperature, Daily cumulative precipitation (20-20h), Daily average Relative Humidity, Daily average Specific Humidity, Daily average Solar Radiation, Daily average Wind, and Daily average Atmospheric Pressure. Introduction to metadata of CMADS CMADS storage path description:(CMADS was divided into two datesets) 1.CMADS-V1.0\For-swat\ --specifically driving the SWAT model 2.CMADS-V1.0\For-other-model\ --specifically driving the other hydrological model(VIC,SWMM,etc.) CMADS--\For-swat-2009\ folder contain:(Station\ and Fork\) 1).Station\ Relative-Humidity-58500\ Daily average relative humidity(fraction) Precipitation-58500\ Daily accumulated 24-hour precipitation(mm) Solar radiation-58500\ Daily average solar radiation(MJ/m2) Tmperature-58500\ Daily maximum and minimum temperature(℃) Wind-58500\ Daily average wind speed(m/s) Where R, P, S, T, W+ dimensional grid number - the number of longitude grid is the station in the above five folders respectively.(Where R,P,S,T,W respective Daily average relative humidity,Daily cumulative precipitation(24h),Daily mean solar radiation(MJ/m2),Daily maximum and minimum temperature(℃) and Daily mean wind speed (m/s)) respectively.Data format is (.dbf) 2).Fork\ (Station index table over East Asia) PCPFORK.txt (Precipitation index table) RHFORK.txt (Relative humidity index table) SORFORK.txt (Solar radiation index table) TMPFORK.txt (Temperature index table) WINDFORK.txt (Wind speed index) CMADS--\For-swat-2012\ folder contain:(Station\ and Fork\) Storage structure is consistency with \For-swat- 2009\.However, all the data in this directory are only available in TXT format and can be readed by SWAT2012. 3)\For-other-model\ (Includes all weather input data required by the any hydrologic model (daily).) Atmospheric-Pressure-txt\ Daily average atmospheric pressure(hPa) Average-Temperature-txt\ Daily average temperature(℃) Maximum-Temperature-txt\ Daily maximum temperature(℃) Minimum-Temperature-txt\ Daily minimum temperature(℃) Precipitation-txt\ Daily accumulated 24-hour precipitation (mm) Relative-Humidity-txt\ Daily average relative humidity(fraction) Solar-Radiation-txt\ Daily average solar radiation(MJ/m2) Specific-Humidity-txt\ Daily average Specific Humidity(g/kg) Wind-txt\ Daily average wind speed(m/s) Data storage information: data set storage format is .dbf and .txt Other data information: Total data: 33.6GB Occupied space: 35.2GB Time: From year 2008 to year 2016 Time resolution: Daily Geographical scope description: East Asia Longitude: 60°E The most east longitude: 160°E North latitude: 65°N Most southern latitude: 0°N Number of stations: 58500 stations Spatial resolution: 1/3 * 1/3 * grid points Vertical range: None
0 2020-06-23
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