The dataset is a 34-year (1983.7-2017.6) high-resolution (3 h, 10 km) global SSR (surface solar radiation) dataset, which can be used for hydrological modeling, land surface modeling and engineering application. The dataset was produced based on ISCCP-HXG cloud products, ERA5 reanalysis data, and MODIS aerosol and albedo products with an improved physical parameterization scheme. Validation and comparisons with other global satellite radiation products indicate that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). This SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future. The unit is W/㎡, instantaneous value.
The near surface atmospheric forcing and surface state dataset of the Tibetan Plateau was yielded by WRF model, time range: 2000-2010, space range: 25-40 °N, 75-105 °E, time resolution: hourly, space resolution: 10 km, grid number: 150 * 300. There are 33 variables in total, including 11 near surface atmospheric variables: temperature at 2m height on the ground, specific humidity at 2m height on the ground, surface pressure, latitudinal component of 10m wind field on the ground, longitudinal component of 10m wind field on the ground, proportion of solid precipitation, cumulative cumulus convective precipitation, cumulative grid precipitation, downward shortwave radiation flux at the surface, downward length at the surface Wave radiation flux, cumulative potential evaporation. There are 19 surface state variables: soil temperature in each layer, soil moisture in each layer, liquid water content in each layer, heat flux of snow phase change, soil bottom temperature, surface runoff, underground runoff, vegetation proportion, surface heat flux, snow water equivalent, actual snow thickness, snow density, water in the canopy, surface temperature, albedo, background albedo, lower boundary Soil temperature, upward heat flux (sensible heat flux) at the surface and upward water flux (sensible heat flux) at the surface. There are three other variables: longitude, latitude and planetary boundary layer height.
一. Data overview In the heihe river basin simulation model development and environment construction of cross integration research, project support, ren-sheng Chen (RReDC) in the center of the renewable energy data provided by the model, on the basis of considering the data of heihe river and other radiation model parameterization scheme, by 1 km resolution DEM, heihe surface weather observation data and NECP reanalysis data, the preparation of total radiation, direct radiation and scattering radiation three data sets. 二, data processing process 1) data source Watershed basic data mainly include DEM data, as well as slope and slope direction data generated thereby.The model adopts Alberts equal area conic projection), the grid size is 1km*1km, a total of 411×562 grids, that is, the actual calculated area is about 23*10^4 km^2.The calculated year is 2002, and the temporal resolution is 1h. Two sets of NCEP/NCAR reanalysis data were used, one set was instantaneous data of 1°*1° per 6h, mainly ozone and precipitable data.The other set is based on the assimilation data of 4 times a day of 192*94 grid (which is the average value per 6h), mainly the data of total cloud cover and precipitation rate.The main reason for applying the two sets of data is that the total cloud cover changes dramatically with time, and the instantaneous data cannot control the overall change of the weather.However, it is impossible to control the weather change within 6 hours by using the average data of 6 hours. 2) method A. Short-wave solar incident radiation model in clear sky horizontal plane.Rayleigh scattering, aerosol absorption, water vapor absorption, ozone absorption and heterogeneous mixed gases (O2, CO2, etc.) are mainly considered in the calculation of direct radiation from clear sky. B. Short-wave radiation model of clear-sky solar incidence under arbitrary topographic conditions.According to the principle of solid geometry and the algorithm of the short-wave radiation of horizontal plane, a simple algorithm of the short-wave radiation considering the self-masking effect of mountain slopes is designed. C. Calculation of solar incident short-wave radiation under arbitrary terrain conditions in actual weather.Based on the Ver4Fortran source code provided by Dr. Harry d. K of the Greek institute of meteorology and atmospheric physics. D. Spatial interpolation adopts the three-dimensional interpolation method based on triangular grid. The time interpolation of the first set of data adopts linear interpolation. For specific algorithm description, please refer to: Chen rensheng, kang ersi, et al. (2006). "model of hourly incident short-wave radiation under arbitrary terrain and actual weather conditions -- a case study of heihe river basin." Chinese desert (05). 3) data verification The simulation results were verified by using the total radiation observation data of three automatic meteorological stations located in the mountainous area, xishui, linze in the middle reaches and ejinaqi in the lower reaches. The calculated results of the total radiation of xishui were relatively poor, with R2 = 0.71.The measured and calculated results of total radiation of linze and ejin flags are better, with R2 of 0.90 and 0.91, respectively. 4) conclusion It is a feasible method to calculate the solar incident short-wave radiation with large range, long time and high spatial and temporal resolution under any terrain and actual weather conditions by combining the radiation transmission parameterization scheme and remote sensing information, especially in the northwest arid region.The established model only USES DEM data of the basin and the slope and slope direction data generated thereby, while other data are reanalysis data, so it is easy to be popularized and applied.The weather changes at any time in high mountain areas. The main reason for the poor calculation effect of the model in high mountain areas is still the low spatial and temporal resolution of the total cloud cover data. Meanwhile, the inconsistency between the calculated value and the measured value partly leads to the poor comparison results.
This dataset is the spatial distribution map of the marshes in the source area of the Yellow River near the Zaling Lake-Eling Lake, covering an area of about 21,000 square kilometers. The data set is classified by the Landsat 8 image through an expert decision tree and corrected by manual visual interpretation. The spatial resolution of the image is 30m, using the WGS 1984 UTM projected coordinate system, and the data format is grid format. The image is divided into five types of land, the land type 1 is “water body”, the land type 2 is “high-cover vegetation”, the land type 3 is “naked land”, and the land type 4 is “low-cover vegetation”, and the land type 5 is For "marsh", low-coverage vegetation and high-coverage vegetation are distinguished by vegetation coverage. The threshold is 0.1 to 0.4 for low-cover vegetation and 0.4 to 1 for high-cover vegetation.