The aerosol optical thickness data of the Arctic Alaska station is formed based on the observation data products of the US Department of Energy's atmospheric radiation observation program at the Arctic Alaska station. The data coverage time is from 1998 to 2020, the time resolution is hourly, the coverage site is the Arctic Alaska station, and the longitude and latitude coordinates are (71 ° 19 ′ 22.8 ″ N, 156 ° 36 ′ 32.4 ″ W). The observation data is obtained from the inversion of the radiation data observed by MFRSR instrument. The optical characteristic variable is aerosol optical thickness, and the observation inversion error range is about 15%. The data format is nc format.
ZHAO Chuanfeng
The triple pole aerosol type data product is an aerosol type result obtained through a series of data pre-processing, quality control, statistical analysis and comparative analysis processes by comprehensively using MEERA 2 assimilation data and active satellite CALIPSO products. The key of the aerosol type fusion algorithm is to judge the aerosol type of CALIPSO. During the data fusion of aerosol type, the final aerosol type data (12 types in total) and quality control results in the three polar regions are obtained according to the types and quality control of CALIPSO aerosol types and referring to MERRA 2 aerosol types. The data product fully considers the vertical and spatial distribution of aerosols, and has a high spatial resolution (0.625 ° × 0.5 °) and time resolution (month).
ZHAO Chuanfeng
The 0.1 º aerosol optical thickness dataset (also known as the "Poles AOD Collection 1.0" aerosol optical thickness (AOD) dataset) in the polar regions from 2000 to 2020 was produced by combining Merra-2 mode data and MODIS satellite sensor AOD. The data covers the period from 2000 to 2020, with a daily time resolution, covering the "tri polar" (Antarctic, Arctic and Qinghai Tibet Plateau) region, and a spatial resolution of 0.1 degree. The verification of the measured stations shows that the relative deviation of the data is within 35%, which can effectively improve the coverage and accuracy of AOD in the polar region.
GUANG Jie GUANG Jie
Global solar radiation and diffuse horizontal solar radiation at Dome C (Antarctica) are measured by radiation sensors (pyranometers CM22, Kipp & Zonen Inc., The Netherlands), and water vapor pressure (hPa) at the ground are obtained from the IPEV/PNRA Project “Routine Meteorological Observation at Station Concordia”, http://www.climantartide.it. This dataset includes hourly solar radiation and its absorbing and scattering losses caused by the absorbing and scattering atmospheric substances (MJ m-2, 200-3600 nm), and the albedos at the top of the atmosphere and the surface. The above solar radiations are calculated by using an empirical model of global solar radiation (Bai, J.; Zong, X.; Lanconelli, C.; Lupi, A.; Driemel, A.; Vitale, V.; Li, K.; Song, T. 2022. Long-Term Variations of Global Solar Radiation and Its Potential Effects at Dome C (Antarctica). Int. J. Environ. Res. Public Health, 19, 3084. https://doi.org/10.3390/ijerph19053084). The observed global solar radiation and meteorological parameters are available at https://doi.org/10.1594/PANGAEA.935421. The data set can be used to study solar radiation and its attenuation at Dome C, Antarctica.
BAI Jianhui
Global solar radiation at Qomolangma station (The Tibetan Plateau) is measured by radiation sensor (pyranometers CM22, Kipp & Zonen Inc., The Netherlands), and water vapor pressure (hPa) at the ground is measured by HMP45C-GM (Vaisala Inc., Vantaa, Finland). This dataset includes hourly solar radiation and its absorbing and scattering losses caused by the absorbing and scattering atmospheric substances (MJ m-2, 200-3600 nm), and the albedos at the top of the atmosphere and the surface. The above solar radiations are calculated by using an empirical model of global solar radiation (Bai, J.; Zong, X.; Ma, Y.; Wang, B.; Zhao, C.; Yang, Y.; Guang, J.; Cong, Z.; Li, K.; Song, T. 2022. Long-Term Variations in Global Solar Radiation and Its Interaction with Atmospheric Substances at Qomolangma. Int. J. Environ. Res. Public Health, 19, 8906. https://doi.org/10.3390/ijerph19158906). The observed global solar radiation and meteorological variables are available at https://data.tpdc.ac.cn/zh-hans/data/b9ab35b2-81fb-4330-925f-4d9860ac47c3/. The data set can be used to study solar radiation and its attenuation at Qomolangma region.
BAI Jianhui
Aerosol Optical Depth (AOD) reflects the attenuation of solar radiation to the surface by aerosols. The aerosol type is calculated according to the aerosol optical thickness (AOD). This data set is derived from the latest MODIS aerosol secondary product MOD04_ L2 and MYD04_ L2, where MOD and MYD represent Terra and Aqua satellites respectively. At present, MODIS aerosol retrieval algorithms are Dark Target (DT) and Deep Blue (DB). According to the inversion accuracy of the metadata field table Quality Assurance Confidence (QAC), DT and DB algorithm products are integrated to deal with land, ocean and coast respectively. The index quality is optimal (QAF=3) or suboptimal (QAF=2) or meets the basic needs (QAF=1) to obtain high-resolution AOD products (0.1 degree, daily scale) with full coverage and long time series. According to AOD experience threshold (AOD: 0~0.2, clean type; 0.2~0.6, urban or industrial type; greater than 0.6, sand dust type) The aerosol types are classified into three types: clean type (1), urban or industrial type (2) and sand dust type (3). This dataset provides MOD, MYD and fusion products based on transit time.
YE Aizhong
This data set contains the high-resolution tropospheric nitrogen dioxide vertical column concentration pomino v2.1 data in East Asia from 2012 to 2020. It is a new version of the data after bug fix of v2.0.1, which provides an important data basis for studying the spatial distribution characteristics and temporal change trend of tropospheric nitrogen dioxide in China. Based on the tropospheric nitrogen dioxide slant column concentration provided by KNMI, the pomino tropospheric nitrogen dioxide vertical column concentration is calculated through the tropospheric AMF retrieval algorithm developed by ourselves. The comparison with the ground-based observation data shows that the tropospheric nitrogen dioxide column concentration of pomino can better capture the day-to-day variation trend, and has better correlation with the ground-based observation data. At present, the data has been used for scientific research by many universities and scientific research institutions at home and abroad. In the future, the data set will provide more comprehensive data support for scientific research projects on the Qinghai Tibet Plateau.
LIN Jintai
Surface solar irradiance (SSI) is one of the products of FY-4A L2 quantitative inversion. It covers a full disk without projection, with a spatial resolution of 4km and a temporal resolution of 15min (there are 40 observation times in the whole day since 20180921, except for the observation of each hour, there is one observation every 3hr before and after the hour）, and the spectral range is 0.2µ m～5.0 µ m. The output elements of the product include total irradiance, direct irradiance on horizontal plane and scattered irradiance, the effective measurement ranges between 0-1500 w / m2. The qualitative improvement of FY-4A SSI products in coverage, spatial resolution, time continuity, output elements and other aspects makes it possible to further carry out its fine application in solar energy, agriculture, ecology, transportation and other professional meteorological services. The current research results show that the overall correlation of FY-4A SSI product in China is more than 0.75 compared with ground-based observation, which can be used for solar energy resource assessment in China.
SHEN Yanbo, HU Yueming, HU Xiuqing
The global monthly all-sky land surface temperature (2000-2020) is produced by the method from Chen et al. 2017 JHM.
CHEN Xuelong, BOB Su, MA Yaoming
This data set is a national high-resolution solar radiation data set covering 34 years (1983.7-2017.6), with a resolution of 10 km. The data unit is W / m2. The data set is developed by merging the global high-resolution (3 hours, 10 km) surface solar radiation data set (1983-2017) with isccp-hxg cloud products as the main input, with ground based sunshine duration derived surface solar raidation data from 2261 meteorological stations in China by using the geographic weighted regression method. The validation results show that this dataset can provide more accurate simulation of long-term variability of surface solar radiation than that of gewex-srb, cmsaf-clara-a2 and the isccp-hxg based surface solar radiation product. This data can provide favorable data support for the application and research of long-term change of hydrology in land surface process simulation.
FENG Fei, WANG Kaicun
Land surface temperature (LST) is a key variable for high temperature and drought monitoring and climate and ecological environment research. Due to the sparse distribution of ground observation stations, thermal infrared remote sensing technology has become an important means of quickly obtaining ground temperature over large areas. However, there are many missing and low-quality values in satellite-based LST data because clouds cover more than 60% of the global surface every day. This article presents a unique LST dataset with a monthly temporal resolution for China from 2003 to 2017 that makes full use of the advantages of MODIS data and meteorological station data to overcome the defects of cloud influence via a reconstruction model. We specifically describe the reconstruction model, which uses a combination of MODIS daily data, monthly data and meteorological station data to reconstruct the LST in areas with cloud coverage and for grid cells with elevated LST error, and the data performance is then further improved by establishing a regression analysis model. The validation indicates that the new LST dataset is highly consistent with in situ observations. For the six natural subregions with different climatic conditions in China, verification using ground observation data shows that the root mean square error (RMSE) ranges from 1.24 to 1.58 K, the mean absolute error (MAE) varies from 1.23 to 1.37 K and the Pearson coefficient (R2) ranges from 0.93 to 0.99. The new dataset adequately captures the spatiotemporal variations in LST at annual, seasonal and monthly scales. From 2003 to 2017, the overall annual mean LST in China showed a weak increase. Moreover, the positive trend was remarkably unevenly distributed across China. The most significant warming occurred in the central and western areas of the Inner Mongolia Plateau in the Northwest Region, and the average annual temperature change is greater than 0.1K (R>0:71, P<0:05), and a strong negative trend was observed in some parts of the Northeast Region and South China Region. Seasonally, there was significant warming in western China in winter, which was most pronounced in December. The reconstructed dataset exhibits significant improvements and can be used for the spatiotemporal evaluation of LST in high-temperature and drought-monitoring studies. More detail please refer to Zhao et al (2020). doi.org/10.5281/zenodo.3528024
MAO Kebiao
The Land Surface Temperature in China dataset contains land surface temperature data for China (about 9.6 million square kilometers of land) during the period of 2003-2017, in Celsius, in monthly temporal and 5600 m spatial resolution. It is produced by combing MODIS daily data(MOD11C1 and MYD11C1), monthly data(MOD11C3 and MYD11C3) and meteorological station data to reconstruct real LST under cloud coverage in monthly LST images, and then a regression analysis model is constructed to further improve accuracy in six natural subregions with different climatic conditions.
MAO Kebiao
This dataset is land surface phenology estimated from 16 days composite MODIS NDVI product (MOD13Q1 collection6) in the Three-River-Source National Park from 2001 to 2020. The spatial resolution is 250m. The variables include Start of Season (SOS) and End of Season (EOS). Two phenology estimating methods were used to MOD13Q1, polynomial fitting based threshold method and double logistic function based inflection method. There are 4 folders in the dataset. CJYYQ_phen is data folder for source region of the Yangtze River in the national park. HHYYQ_phen is data folder for source region of Yellow River in the national park. LCJYYQ_phen is data folder for source region of Lancang River in the national park. SJY_phen is data folder for the whole Three-River-Source region. Data format is geotif. Arcmap or Python+GDAL are recommended to open and process the data.
WANG Xufeng
The dataset was produced based on MODIS data. Parameters and algorithm were revised to be suitable for the land cover type in the Three-River-Source Regions. By using the Markov de-cloud algorithm, SSM/I snow water equivalent data was fused to the result. Finally, high accuracy daily de-cloud snow cover data was produced. The data value is 0(no snow) or 1(snow). The spatial resolution is 500m, the time period is from 2000-2-24 to 2019-12-31. Data format is geotiff, Arcmap or python+GDAL were recommended to open and process the data.
HAO Xiaohua
The dataset is a nearly 36-year (1983.7-2018.12) 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.
TANG Wenjun
This dataset includes the ground surface temperature in the Qilian Mountains on the Qinghai-Tibet Plateau during 1980-2013. This dataset was obtained from the ERA-interim reanalysis product. The ERA-interim system includes a 4-dimensional variational analysis (4D-Var). The quality of the data has been improved using the bias correction of satellite data. The spatial resolution of the dataset is 0.125°. The dataset includes the grid data of the ground surface temperature in the Qilian Mountains during the past 30 years, and may provide a basic data for relevant studies such as climatic change, ecosystem succession, and earth system models.
WU Xiaodong
Photosynthetic effective radiation absorption coefficient photosynthetically active radiation component is an important biophysical parameter. It is an important land characteristic parameter of ecosystem function model, crop growth model, net primary productivity model, atmosphere model, biogeochemical model and ecological model, and is an ideal parameter for estimating vegetation biomass. The data set contains the data of photosynthetically active radiation absorption coefficient in Qinghai Tibet Plateau, with spatial resolution of 500m, temporal resolution of 8D, and time coverage of 2000, 2005, 2010 and 2015. The data source is MODIS Lai / FPAR product data mod15a2h (C6) on NASA website. The data are of great significance to the analysis of vegetation ecological environment in the Qinghai Tibet Plateau.
FANG Huajun, Ranga Myneni
The data set of ERA-Interim global surface air temperature reanalysis (1979-2016) was obtained from the European Center for Medium-Range Weather Forecasts (ECMWF) by adopting the ECMWF IFS forecasting system (T255, 60 layers) and using the four-dimensional variational assimilation system (8DVAR) with an analysis window of 12 hours to assimilate satellite remote sensing data (TOVS, GOES, Meteosat, etc.) and regular observations of the surface and upper atmosphere in different regions of the world and from different sources. The surface air temperature (2 m air temperature) data span the time range from January 1979 to December 2016 and cover the whole world with the projection of equal latitude and longitude, a temporal resolution of six hours, and a horizontal resolution of 0.75. The data were stored as a NetCDF format file once a month and included longitude, latitude, time, and temperature (t2m, unit: K), with 241 latitudinal grid points and 480 longitudinal grid points.
LI Fei
This data set of cloud observations at a site in Arctic Alaska is based on the fusion of five cloud inversion products that are well known worldwide. The temporal coverage of the data is from 1999 to 2009, the temporal resolution is one hour, and there are 512 layers vertically with a vertical resolution of 45 m. The spatial coverage is one site in Arctic Alaska, with latitude and longitude coordinates of 71°19′22.8′′N, 156°36′32.4′′ W. The remote sensing cloud inversion data products include the following official products: the all-phase cloud characteristic products produced by the Atmospheric Radiation Measurement Program of the US Department of Energy adopting a parametric method for remote sensing inversion, the ice cloud and hybrid cloud feature products obtained from the US NOAA researchers Matt Shupe and Dave Turner based on cooperative remote sensing inversion (optimization method + parametric method), the hybrid cloud feature (optimization method) products produced by Zhien Wang of the University of Wyoming, USA, the ice cloud feature (parametric method) products produced by Min Deng of the University of Wyoming, USA, and the cloud optical thickness products produced by Qilong Min of the State University of New York at Albany adopting remote sensing inversion (optimization method). The variables of the remote sensing products include cloud water effective radius, cloud water content, cloud ice effective radius, cloud ice content, cloud optical thickness, and cloud water column content; the corresponding observed inversion error ranges are approximately 10-30%, 30-60%, 10-30%, 30-60%, 10-30% and 10-20%. The data files are in the NC format, and an NC file is stored every month.
ZHAO Chuanfeng
This data set was derived from MODIS version 005 and the IMS data set. It is a daily cloudless snow area product processed by cloud removal. Value range: 0%-100%. 200: snow; 100: lake ice; 25: land; 37: sea. The spatial resolution is 0.005 degrees (approximately 500 m), and the temporal coverage is from July 5, 2002, to December 31, 2014.
HAO Xiaohua
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