Eddy Covariance Data for an Alpine Marshland in Shenzha

(1) This data set is the carbon flux data set of Shenzha alpine wetland from 2016 to 2019, including air temperature, soil temperature, precipitation, ecosystem productivity and other parameters. (2) The data set is based on the field measured data of vorticity, and adopts the internationally recognized standard processing method of vorticity related data. The basic process includes: outlier elimination coordinate rotation WPL correction storage item calculation precipitation synchronization data elimination threshold elimination outlier elimination U * correction missing data interpolation flux decomposition and statistics. This data set also contains the model simulation data calibrated based on the vorticity correlation data set. (3) the data set has been under data quality control, and the data missing rate is 37.3%, and the missing data has been supplemented by interpolation. (4) The data set has scientific value for understanding carbon sink function of alpine wetland, and can also be used for correction and verification of mechanism model.

0 2020-07-22

NPP dataset in the Heihe River Basin (1998-2002)

The annual total net primary productivity (NPP) and average productivity of different ecosystems in heihe river basin from 1998 to 2002 were estimated by using the light energy utilization model c-fix, high spatial and temporal resolution remote sensing data of SPOT/VEGETATION, global grid meteorological reanalysis data and land use map of heihe river basin. From 1998 to 2002, the 10-day 1-km resolution SPOT VEGETATATION NDVI (10-day maximum synthesis) data product in the heihe basin, provided by the image processing and archiving center (CTIV) of VITO institute, Belgium, was used to calculate the key parameters fAPAR required by the c-fix model. The daily temperature and total radiation of heihe river basin from 1998 to 2002 were obtained using a global 1.5 °× 1.5 ° grid meteorological data product from MeteoFrance. It contains the spatial distribution pattern of annual accumulation of NPP in heihe basin and the seasonal dynamic map of NPP.The spatial resolution of this data is 1km.

0 2020-03-07

Validation dataset of ecological model in the Heihe River Basin (2018)

This data set is collected according to the output results of tesim ecological process model, including biomass, plant N and P content, evapotranspiration, NPP and other model output results. Some of the results are obtained by field measurement, some by laboratory analysis of field samples, some by literature.

0 2020-03-02

Global vegetation productivity monthly data obtained by CNRM-CM6-1 mode of CMIP6 (1850-2014)

The data set is the global vegetation productivity data, including Gross Primary Productivity(GPP) and Net Primary Productivity (NPP). It was obtained by the CNRM-CM6-1 mode simulation of CMIP6 under the Historical scenario. The time range of the data covers from 1850 to 2014, the time resolution is a month, and the spatial resolution is about 1.406°×1.389°. For the simulated data details, please go to the following link: http://www.umr-cnrm.fr/cmip6/spip.php?article11.

0 2019-09-15

The NPP spatio-temporal dataset of the Tibetan Plateau (1982-2006)

This data set contains the results of the calculation of Net Primary Productivity (NPP) on the Tibetan Plateau based on ecological models and remote sensing data from 1982 to 2006. Ecosystem NPP of the Tibetan Plateau was generated based on the remote sensing Advanced Very High Resolution Radiometer (AVHRR) data and the Carnegie-Ames-Stanford Approach (CASA) model(1982-2006), the soil carbon content was generated based on the second soil census data, and the biomass carbon data were generated based on the High Resolution Biosphere Model (HRBM) model. Forest ecosystem NPP of the Tibetan Plateau (1982-2006): npp_forest82.e00,npp_forest83.e00,npp_forest84.e00,npp_forest85.e00,npp_forest86.e00, npp_forest87.e00,npp_forest88.e00,npp_forest89.e00,npp_forest90.e00,npp_forest91.e00, npp_forest92.e00,npp_forest93.e00,npp_forest94.e00,npp_forest95.e00,npp_forest96.e00, npp_forest97.e00,npp_forest98.e00,npp_forest99.e00,npp_forest00.e00,npp_forest01.e00, npp_forest02.e00,npp_forest03.e00,npp_forest04.e00,npp_forest05.e00,npp_forest06.e00 Grassland ecosystem NPP of the Tibetan Plateau(1982-2006): npp_grass82.e00,npp_grass83.e00,npp_grass84.e00,npp_grass85.e00,npp_grass86.e00, npp_grass87.e00,npp_grass88.e00,npp_grass89.e00,npp_grass90.e00,npp_grass91.e00, npp_grass92.e00,npp_grass93.e00,npp_grass94.e00,npp_grass95.e00,npp_grass96.e00, npp_grass97.e00,npp_grass98.e00,npp_grass99.e00,npp_grass00.e00,npp_grass01.e00,npp_grass02.e00,npp_grass03.e00,npp_grass04.e00,npp_grass05.e00,npp_grass06.e00. Biomass carbon and soil carbon of the Tibetan Plateau: Biomass.e00,Socd.e00. The soil carbon content data (Socd) are generated based on data of the second soil census of China and Soil Map of China (1:1,000,000) by soil subclass interpolation. The NPP data are generated from the CASA model and AVHRR data simulation: Potter CS, Randerson JT, Field CB et al. Terrestrial ecosystem production: a process model based on global satellite and surface data. Global Biogeochemical Cycles, 1993, 7: 811–841. The biomass carbon data are generated via HRBM model simulation: McGuire AD, Sitch S, et al. Carbon balance of the terrestrial biosphere in the twentieth century: Analyses of CO2, climate and land use effects with four process-based ecosystem models. Global Biogeochem. Cycles, 2001, 15 (1), 183-206. The raw data are mainly remote sensing data and field observation data with high accuracy; the verification and adjustment of the measured data in the field during the production were undertaken to maintain the error of the simulation results and the field measured data within the acceptable range as much as possible; the verification results of the NPP data and the field measured data show that the error remains within 15%. The spatial resolution is 0.05°×0.05° (longitude×latitude).

0 2019-09-12