Crop phenology refers to the date when a crop reaches a critical growth period. The main planting pattern in the North China Plain (NCP) is the rotation system of winter wheat and summer maize. Changes in the key phenological periods of winter wheat and summer maize reflect the response and adaptability of them to climatic conditions and production management measures. And the critical phenology dates are important parameters for evaluating crop growth status and irrigation water consumption in the NCP This study selected the winter wheat-summer maize stable planting area in the NCP. The GIMMS3g NDVI data from 1982 to 2015 was used. Multiple characteristis such as the maximum value, minimum value, slope, and percentage value of the curve were combined to extract phenology of winter wheat and summer maize: SOS (start of the season), PEAK (peak of the season), and EOS (end of the season). The extracted phenology was compared with the phenological records from the agro-meteorological stations. The R² was above 0.9, which was with high accuracy. (Details can be found in the reference) The phenological dataset can be applied to related researches about calculating the productivity of winter wheat and summer maize, evaluating the response of crops to climate change, and estimating irrigation water consumption in this region.
The North China Plain is an important food production area in China, with a large area of cropland and a complex planting structure. Accurately identifying the distribution of typical crops in this area and tracking the dynamic changes of planting structure are fundamental for detecting crop growth, evaluating crop irrigation water consumption and optimizing agricultural water resources allocation. This study used Fourier transform to obtatin the amplitudes and phases of the 0-5 harmonics of the MOD13Q1 NDVI data. Based on the field sample points and maximum likelihood supervised classification, the planting area of 6 typical crops (winter wheat-summer maize; winter wheat-rice; other double cropping systems; spring maize; cotton; other single cropping systems) in the North China Plain from 2001 to 2018 was identified. The identification results accuracy were evaluated through confusion matrix, comparison with the winter wheat planting area in the county-level statistical yearbook, and comparison with the proportion of winter wheat extracted by Landsat images, all of which showed good performance and high accuracy. The data can be applied to related research and analysis on crop production, irrigation water consumption estimation, and groundwater protection in the North China Plain.
Snow cover is an important component of the cryosphere and an indispensable variable in the scientific research of global change and Earth system. The distribution range and phenological information of snow cover are important indicators to measure the variation characteristics of snow cover, and also important parameters for snow melting runoff simulation in the hydrological model of cold regions. The High Mountain Asia is the source of many international rivers, and also the hot spot of global climate change research; The ecological and environmental problems caused by the change of ice and snow in the region, such as the reduction of water resources, the increase of extreme weather events, and the frequent occurrence of disasters, have attracted extensive attention from all countries. Therefore, it is very important for climate change research, water resources management, disaster early warning and prevention to accurately obtain long-term snow distribution and snow phenology data in High Mountain Asia . The daily cloudless MODIS normalized snow cover index (NDSI) product (2000-2021500 m) in the High Mountain Asia is based on the MODIS daily snow cover product (including Terra Morning Star data product MOD10A1 and Aqua Afternoon Star data product MYD10A1, C6 versions), and is processed by the same day afternoon star data fusion and cubic spline interpolation cloud removal algorithm; Among them, when there was only Morningstar data product MOD10A1 from 2000 to 2002, the cubic spline interpolation algorithm was directly used for cloud removal. The snow cover phenological data set for hydrological years 2002-2020 is prepared based on cloudless MODIS NDSI products in hydrological years, including three parameters: snow onset date (SOD), snow end date (SED) and snow duration days (SDD). This data set has reliable accuracy.
TANG Zhiguang , DENG Gang
The surface PM2.5 concentration data of Tibet Plateau is named by date (YYYYMMDD). Each NC file contains one day's data, which is composed of PM2.5 concentration, longitude, latitude, and time information of the area (the corresponding variables in the data are named with PM2.5, lon, lat, time). The data inversion relies on the reanalysis data MERRA-2 released by NASA and the AOD product of Multi-angle Imaging SpectroRadiometer (MISR). MERRA-2 is mainly based on NASA GMAO Earth system model version 5 (GEOS 5). The algorithm is able to assimilate all the in-situ and re- motely-sensed atmospheric data. This dataset mainly focuses on the aerosol field of MERRA-2. This is the first multi-decadal reanalysis within which meteorological and aerosol observations are jointly assimilated into a global assimilation system. MISR views Earth with cameras pointed in 9 different directions， which can help us know the amount of sunlight that is scattered in different directions under natural conditions. The main data products used in this data algorithm are MERRA-2 aerosol analysis product (M2T1NXAER) and MISR Level 3 version 4 global aerosol products (MIL3DAEN_4). Firstly, the ratio of PM2.5 to AOD in each grid was calculated by using the aerosol information provided by MERRA-2. Second, the PM2.5 concentration of the grid was calculated by multiplying the AOD of MISR by the ratio. The mean prediction error of PM2.5 concentration obtained by this method is within 20 μg/m3. The corresponding PM2.5 products can be used for the assessment of particulate pollution in the Tibet Plateau.
The data set is the original repeated GPS observation data along Paizhen - Motuo active deformation Himalayan orogenic belt in Southeast Tibetan Plateau. The data are measured in 2021, including the data of 18 stations, and the data quality is good. Through the observation data of these observation points, we can reveal the horizontal and vertical distribution characteristics of the northward converging strain of the Indian continent in the key parts of the Himalayan orogenic belt. And we can understand the current uplift state of the Himalayan orogenic belt and its correlation with horizontal movement, and combine with the active faults. Based on the theory of motion dislocation, the quantitative distribution of strain between earthquakes could be studied, as well as the strain accumulation characteristics, fault locking range and fault locking level between earthquakes, which provide important constraints for evaluating the seismic risk of active faults in the study area.
We compiled the Seismotectonic Map and Seismic Hazard Zonation Map of South Asia using the ArcGIS platform through data collecting and digitization. The seismotectonic map of South Asia covers India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka. The seismotectonic map is replenished with tremendous amount published data and depicts the location, character and name of the seismogenic faults or active faults and the epicenter of earthquakes with M ≥ 5 from 1960 to 2021. The zonation map shows the mean values of peak ground acceleration (PGA) with 10% probability of being exceeded in 50 years. The two maps can not only be used in the research of active faults and seismic risks in South Asia, but also will be applied to the seismic safety evaluation for infrastructure construction.
The Tibetan Plateau region has strong seismic activity, which is driven by the subduction collision between the Indian plate and the Eurasian plate and the internal deformation of the plateau. A total of 5030 earthquakes of magnitude M≥5.0 have occurred on the Tibetan Plateau and surrounding areas (20-40°N, 70-105°E) . Historical records since the present ( December 2021), including 20 earthquakes of magnitude M≥8, 154 earthquakes of magnitude M=7.0-7.9, 913 earthquakes of magnitude M=6.0-6.9, and 3943 earthquakes of magnitude M=5.0-5.9. The earthquakes occurred mainly along the large faults zones around and within the Tibetan Plateau.
Atmospheric water vapor is an important parameter for studying the water cycle. In the context of global warming, in order to better study the impact of atmospheric water vapor on the water cycle, a global daily scale AMSR-E/AMSR2 all-weather atmospheric precipitable water (TPW) dataset with a spatial resolution of 0.25 ° was constructed. In the data set, the TPW over land is mainly obtained by our newly developed 18.7 and 23.8 GHz brightness temperature data inversion algorithm based on AMSR-E and AMSR2; The ocean sky TPW data integrates AMSR-E/AMSR2 official TPW products. As a post-processing, in order to eliminate the systematic deviation between AMSR-E TPW and AMSR2 TPW, using AIRX2RET TPW as the benchmark, the histogram matching method was used to correct the systematic deviation of AMSR-E and AMSR2 TPW data on a global scale, to ensure the continuity of the data, and finally the global daily scale AMSR-E and AMSR2 TPW all-weather data sets were obtained. Among them, the time range of AMSR-E data is from July 8, 2002 to September 27, 2011, and the time range of AMSR-2 data is from January 1, 2013 to August 31, 2017. Each date contains two files: orbit raising and orbit lowering. The data format is Geotiff. The number of data layers is 2. The first layer is TPW data, with the unit of mm. The second layer is time information, which represents the number of seconds elapsed between the pixel observation time with UTC as the time base and 0:00:00 of the current day. The data set has reliable quality. Through verification and analysis with the global SuomiNET GPS TPW, the root mean square error of the data set is 3.5-5.2mm. As atmospheric precipitable water is an important geophysical parameter affecting surface remote sensing and also has an important impact on the earth's climate change, this data can be used for research on the impact of atmospheric water vapor on the water cycle, the assessment of atmospheric water resources and atmospheric correction in the context of climate warming.
JI Dabin, SHI Jiancheng, HUSI Letu, LI Wei , ZHANG Hongxing , SHANG Huazhe
The annual emission data of conventional air pollutants (PM2.5, SO2, NH3, NOX) under different carbon neutralization technologies and air pollutant end treatment scenario combinations from 2017 to 2060, generated based on the computable general equilibrium model and the base year emission inventory, are used for the policy scenario analysis of the future coordinated treatment of carbon dioxide and air pollution in China. This data has been applied to the evaluation of the health synergy benefits of the carbon neutral technology path, as the data input of the health impact assessment model, to estimate the premature death, incidence rate and the resulting life expectancy loss, and to monetize these health impacts. The health common interests of monetization are compared with the corresponding emission reduction costs to explore the cost-effectiveness of different carbon neutral technology combinations.
WANG Can , ZHANG Shihui
This data integrates a variety of current natural geographic map data, and combines land suitability evaluation, crop growth model, scenario analysis and other methods to generate China's biomass resources and energy technology potential on a 1km grid scale from 2015 to 2100, with a temporal resolution of 5 years and a spatial resolution of 1km. The data set includes 3 categories and 11 types of biomass resources (the residues include dry land agricultural residues, paddy field agricultural residues, forest residues, shrub residues, orchard residues and grassland residues, the wastes include livestock manure, MSW and COD, and the energy crops include sweet sorghum and switchgrass), fully covering the types of biomass that can be used as resources. The data format is raster data (. tiff), which can be opened using ArcGIS, R/Python and other programming languages. Biomass is a dependent resource for negative carbon technology in China's carbon neutral technology system in the future. The biomass data developed in this research has three advantages: wide coverage (nationwide), fine spatial resolution (1km grid), and wide time span (2015-2100). It can provide detailed quantitative data for China to formulate low-carbon emission reduction strategies and deploy biomass energy technology strategies.
CAI Wenjia , NIE Yaoyu , WANG Rui
Provide detailed spatial distribution of land cover types in China from 1990 to 2015, with spatial accuracy of 0.25 ° and geographic coordinate system of WGS84. Each grid shows the ratio of land use type to grid area (0-1). The data comes from the global land use spatial distribution map of the University of Maryland. The historical homogenized land use data of China is obtained by linear interpolation of the original data, extraction of Chinese regional mask and transformation of coordinate system, and saved in geotiff file format. The methods and standards of data over the years are consistent, the coverage is complete, and the collection and processing process is traceable and reliable. It has realized the homogenization of existing population data products, providing a basis for analyzing the laws of human elements, the interaction mechanism of human elements and natural elements.
WANG Can , WANG Jiachen
Provide detailed spatial distribution of population data in China from 1990 to 2015 year by year. The data is 1km grid data, with population pop as the indicator. The grid data comprehensively considers multiple factors for weight distribution to realize the spatialization of population, which is convenient for data sharing and spatial statistical analysis. The data comes from the Resource and Environmental Science and Data Center of the Institute of Geographic Science and Resources, Chinese Academy of Sciences. The annual data is obtained by linear interpolation of the original data, and saved in geotiff file format. The methods and standards of data over the years are consistent, the coverage is complete, and the collection and processing process is traceable and reliable.
WANG Can , WANG Jiachen
Provide the spatial distribution of water intake in six departments of agricultural irrigation, municipal administration, industrial production, animal husbandry, primary energy exploitation and power generation in China from 1990 to 2015, with a spatial accuracy of 0.5 °, and a geographic coordinate system of WGS84. The data comes from the data set of jgcri papers. The historical uniform water intake data of China is obtained after linear interpolation of the original data, mask extraction in China and coordinate system conversion, and is saved in GeoTIFF file format. The methods and standards of data over the years are consistent, the coverage is complete, and the collection and processing process is traceable and reliable. This data realizes the homogenization of existing data products and provides a basis for analyzing the laws of human factors and the interaction mechanism between human factors and natural factors.
WANG Can , WANG Jiachen
Provide the spatial distribution of the annual emissions of BC, CH4, CO2, CO, NH3, NMVOC, NOx, OC and SO2 from agriculture, energy exploitation, industrial and fuel combustion, surface transportation, residential and commercial housing, solvent production, waste disposal and international shipping in China from 1990 to 2015, in kg/m2/yr. The spatial precision is 0.5 °, and the geographic coordinate system is WGS84. The data comes from the CEDs data set. The historical homogenized land use data of China is obtained by linear time interpolation, Chinese regional mask extraction and coordinate system transformation of the original data, and saved in geotiff file format. The methods and standards of data over the years are consistent, the coverage is complete, and the collection and processing process is traceable and reliable.
WANG Can , WANG Jiachen
Terrestrial actual evapotranspiration (ET) is an essential ecohydrological process linking the land surface energy, water and carbon cycles, and plays a critical role in the earth system. This global ET dataset is obtained based on ETMonitor model, which combines parameterizations for different processes and land cover types, with multi-source satellite data as input. Several open accessed remote sensing variables, e.g., LAI, FVC, albedo, surface soil moisture, dynamic surface water cover and snow/ice cover, were used as input to estimate daily ET. The meteorological variables from ERA5 reanalysis dataset were also adopted. The ETMonitor model is applied at daily scale to estimate the ET components at 1-km resolution, including vegetation transpiration, soil evaporation, canopy precipitation interception loss, water surface evaporation and snow/ice sublimation on daily step, and the total actual ET is estimated as the sum of these components. Overall, the actual ET estimated by ETMonitor agreed well with ground measurements from 251 flux towers across various ecosystems and climate zones globally, with high correlation (0.75), low bias (0.08mm/d), and low root mean square error (0.93 mm/d). The estimated ET showed reasonable spatial patterns, and superior in presenting the spatial variation of ET especially in the mountain regions and in the arid irrigated cropland regions. The ET estimation is conducted at daily temporal step and 1km spatial resolution. For easier publication, the daily/1-km ET from ETMonitor (https://doi.org//10.12237/casearth.6253cddc819aec49731a4bc2) was summed to obtain monthly ET in this dataset. The data type is 16-bit signed integer, the scale factor is 0.1, and the unit is mm/month. The missing values were filled by -1.
ZHENG Chaolei , JIA Li , HU Guangcheng
The reconstruction of sunshine hours can better reflect the long-term change trend of surface solar radiation, but only the station data. Therefore, in order to obtain high-resolution grid point data and ensure its accuracy in long-term changes, it is necessary to fuse a variety of surface solar radiation related data. Using the geographic weighted regression (GWR) method, the MODIS 0.1 ° resolution cloud and aerosol retrieval and the surface sunshine hours are combined to reconstruct the surface solar radiation station data. By adding the combination judgment of adjacent point schemes, the accuracy of downscaling results of geographical weighted regression is effectively improved, and the multi-year average value and long-term trend of China are basically consistent with the observation and satellite remote sensing inversion results. Using geographic weighted regression and other methods, the surface wind speed and relative humidity data of 0.1 degree grid are generated; The improved Penman formula is used to calculate the land surface evapotranspiration data.
The change of observation environment and instruments may affect the observation results, that is, the heterogeneity of climate observation data. Instrument replacement and station migration can bring about relatively large changes in observation results, which are relatively easy to detect and correct, and have been solved relatively well. However, the instrument sensitivity drift and the observation environment change slowly, so it is more difficult to detect and correct because of its relatively small amplitude, but its impact gradually accumulates, so it is more important to study the long-term change trend. A detection metho was proposed for gradual inhomogeneity of surface solar radiation, ground temperature, air temperature, wind speed, precipitation and other observation data in China, and realizes the inspection / correction of gradual inhomogeneity of these data. We use sunshine hours to calculate solar radiation, and perform homogenization and accuracy calibration to prepare high-quality solar radiation data sets; Using four times a day and hourly air temperature and ground temperature observations, a new data set of daily average land surface temperature and ground temperature is prepared; The geostrophic wind and reanalysis wind speed calculated from the atmospheric pressure observation are used to homogenize the wind speed observation; The observed precipitation is corrected by using the observed wind speed and precipitation type discrimination results. The surface solar radiation, ground temperature, air temperature and precipitation have been in the past 60 years, and the surface wind speed has been in 1972.
Continued global warming and degradation of the cryosphere are raising concerns about adaptation to environmental instability in mountain areas. In recent decades, glacier-related slope failures, such as ice avalanches and rock avalanches on glaciers, have been frequently documented. In this study, we create a global inventory of glacier-related landslides to examine their distribution, trends, fractures, and relationship to climate change. During the period 1901-2019, 737 glacier-related landslides were recorded, including 156 ice avalanches, 89 ice-rock avalanches, 26 glacier slides, and 466 supraglacial rock avalanches. The Pacific Northwest had the most recorded cases (N = 440, 60%), with supraglacial rockfalls being the most dominant. In addition, the currently published list of glacial lake outburst floods of regional or global nature is integrated and refined, and moraine lake outburst flood events are separated separately. 380 moraine lake outburst flood events were counted between 1901 and 2020, making it the most complete list available on a global scale.
ZHANG Taigang, WANG Weicai
Clouds cover 70% of the earth's surface and are one of the important factors affecting the balance of atmospheric radiation and climate change. They are also an important part of the global water cycle. Considering the lack of reliable cloud parameter data with high temporal and spatial resolutions in the East Asia-Pacific (EAP) region, the 2016 data were developed using the next-generation geostationary satellite Himawari-8 with a temporal resolution of 1h and spatial resolutions of 0.1° and 0.25°. , 1° cloud parameters datasets. The cloud products include macro- and micro parameters. The macro parameters include: cloud cover (CF), cloud detection (CM), cloud phase detection (CP), cloud top pressure (CTP), cloud top height (CTH) ), cloud top temperature (CTT), cloud type (CT), supercooled water detection (SWC); micro parameters include cloud optical depth (COT), cloud particle effective radius (CER). These cloud parameters produced have reached the international advanced level in terms of precision.
Water cover is one of the basic parameters of water cycle and energy balance. Based on the AVHRR daily reflectance time series from 1982 to 2020, this data set has produced 39 year long-term daily water body mapping products (including water body icing information) on the Qinghai Tibet Plateau. This dataset contains 39 folders, named after the year (from 1982 to 2020). Each folder contains 365 / 366 GeoTIFF files, and each file contains two bands: (1) water mapping band (waterlayer); (2) Quality control information band (QC). This product provides data support for remote sensing monitoring of water bodies in the Qinghai Tibet Plateau.