The global typhoon path data set contains the data of 29 typhoon path points in the Northwest Pacific in 2018, including time, longitude and latitude, central air pressure, wind speed and wind force, future direction, future speed, wind force level and other indicators; the data comes from the typhoon network of the Central Meteorological Station (http://typhone.nmc.cn/web.html), using Python to grab the typhoon path data published on the web page, In addition, the captured Excel data table is sorted into ShapeFile form, and each path point is given wind power level according to the wind power rating standard of typhoon; It can be applied to the analysis of the characteristics and influence of the movement of typhoon path points, wind speed and wind force.
CHEN Yiting, YANG Hua, WU Jianjun, ZHOU Hongmin
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
The data set analyzes the spatial and temporal distribution, impact and loss of typical global flood disasters from 2018 to 2019. In 2018, there were 109 flood disasters in the world, with a death toll of 1995. The total number of people affected was 12.62 million. The direct economic loss was about 4.5 billion US dollars, which was at a low level in the past 30 years. The number of global flood incidents in 2018 was higher in the first half of the year than in the second half of the year, and the frequency of occurrence was higher from May to July. Therefore, based on three typical disaster events such as the hurricane flood in Florence in the United States in 2018, the flooding of the Niger River in Nigeria in 2018, and the Shouguang flood in Shandong Province in 2018, the disaster background, hazard factors, and disaster situation were analyzed. .
JIANG Zijie, JIANG Weiguo, WU Jianjun, ZHOU Hongmin
A gridded ocean temperature dataset with complete global ocean coverage is a highly valuable resource for the understanding of climate change and climate variability. The Institute of Atmospheric Physics (IAP) provides a new objective analysis of historical ocean subsurface temperature since 1990 for the upper 2000m through several innovative steps. The first was to use an updated set of past observations that had been newly corrected for biases (e.g., in XBTs). The XBT bias was corrected by CH14 scheme, which is recommended by the XBT community. The second was to use co-variability between values at different places in the ocean and background information from a number of climate models that included a comprehensive ocean model. The third was to extend the influence of each observation over larger areas, recognizing the relative homogeneity of the vast open expanses of the southern oceans. Then the observations were also used to provide finer scale detail. Finally, the new analysis was carefully evaluated by using the knowledge of recent well-observed ocean states, but subsampled using the sparse distribution of observations in the more distant past to show that the method produces unbiased historical reconstruction. The ocean wind data set is constructed using RSS Version-7 microwave radiometer wind speed data. The input microwave data are processed by Remote Sensing Systems with funding from the NASA MEaSUREs Program and from the NASA Earth Science Physical Oceanography Program. This wind speed product is intended for climate study as the input data have been carefully intercalibrated and consistently processed. Each netCDF file contains: 1) monthly means of wind speed, grid size 360x180xnumber of all months since Jan 1988(increases over time) 2) a 12-month set of climatology wind speed, grid size 360x180, the climatology is an average calculated over the 20-year period 1988-2007 3) monthly anomalies of wind speed derived by subtracting the above climatology maps from the monthly means, grid size 360x180x#months since Jan 1988 (increases over time) 4) a wind speed trend map, grid size 360x180, the trend is calculated from 1988-01-01 to the latest complete calendar year 5) a time-latitude plot (a minimum of 10% of latitude cells is required for valid data), grid size 180x#months since Jan 1988 (increases over time).
GE Yong, LI Qiangzi, DONG Wen
This data set contains information on natural disasters in Qinghai over nearly 50 years, including the times, places and the consequences of natural disasters such as droughts, floods, hail, continuous rain, snow disasters, cold waves and strong temperature drops, low temperature freezing injuries, gales and sandstorms, pest plagues, rats, and geological disasters. Qinghai Province is located in the northeastern part of the Tibetan Plateau and has a total area of 720,000 square kilometers. Numerous rivers, glaciers and lakes lie in the province. Because two mother rivers of the Chinese nation, the Yangtze River and the Yellow River, and the famous international river—the Lancang River—originated here, it is known as the "Chinese Water Tower"; there are 335,000 square meters of available grasslands in the province, and the natural pasture area ranks fourth in the country after those of Inner Mongolia, Tibet and Xinjiang. There are various types of grasslands, abundant grassland resources, and 113 families, 564 genera and 2100 species of vascular plants, which grow and develop under the unique climatic condition of the Tibetan Plateau and strongly represent the characteristics of the plateau ecological environment. As the main part of the Tibetan Plateau, Qinghai Province is one of the centers of the formation and evolution of biological species in China. It is also a sensitive area and fragile zone for the study of climate and ecological environment in the international field of sciences and technology. The terrain and land-forms in Qinghai are complex, with interlaced mountains, valleys and basins, widely distributed snow and glaciers, the Gobi and other deserts and grassland. Complex terrain conditions, high altitudes and harsh climatic conditions make Qinghai a province with frequent meteorological disasters. The main meteorological disasters include droughts, floods, hail, continuous rain, snow disasters, cold waves and strong temperature drops, low temperature freezing injuries, gales and sandstorms. The data are extracted from the Qinghai Volume of Chinese Meteorological Disaster Dictionary, with manual entry, summarizing and proofreading.
Qinghai Provincial Bureau of Statistics
The UHSLC offers tide gauge data with two levels of quality-control (QC). Fast Delivery (FD) data are released within 1-2 months of data collection and receive only basic QC focused on large level shifts and obvious outliers. The GLOSS/CLIVAR (formerly known as the WOCE) "fast" sea level data is distributed as hourly, daily, and monthly values. This project is supported by the NOAA Climate and Global Change program, and is one of the activities of the University of Hawaii Sea Level Center. Each file is given a name "h###.dat" where "h" denotes hourly sea level data and "###" denotes the station number. A file exists for every station with hourly data. The UHSLC datasets are GLOSS data streams (read more here). There are many tide gauge records in the UHSLC database, but the backbone is the GLOSS Core Network (GCN) – a global set of ~300 tide gauge stations that serve as the foundation of the global in situ sea level network. The network is designed to provide evenly distributed sampling of global coastal sea level variation at a variety of time-scales.
DONG Wen, University of hawaii sealevel center （UHSLC）
1)The data content includes three stages of soil erosion intensity in Qinghai-Tibet Plateau in 1992, 2005 and 2015, and the grid resolution is 300m. 2) China soil erosion prediction model (CSLE) was used to calculate the soil erosion amount of more than 4,000 investigation units on the Qinghai-Tibet Plateau. Soil erosion was interpolated according to land use on Qinghai-Tibet Plateau. According to the soil erosion classification standard, the soil erosion intensity map of Qinghai-Tibet Plateau was obtained. 3) By comparing the differences of three-stage soil erosion intensity data, it conforms to the actual change law and the data quality is good. 4) The data of soil erosion intensity are of great significance to the study of soil erosion in the Qinghai-Tibet Plateau and the sustainable development of local ecosystems. In the attribute table, "Value" represents the erosion intensity level, from 1 to 6, the value represents slight, mild, moderate, intense, extremely intense and severe. "BL" represents the percentage of echa erosion intensity in the total area.
ZHANG Wenbo
This data is digitized from the `` Map of Desertification Types of Naiman Banner, Kulun Banner, and Horqin Left-wing Rear Banner '' on the drawing.The specific information of this map is as follows: * Chief Editor: Zhu Zhenda * Deputy editors: Liu Shu and Qiu Xingmin * Edit: Feng Yukun * Mapping: Feng Yudi, Zhao Yanhua, Wang Jianhua * Double photo: Li Weimin * Field trip: Zhu Zhenda, Qiu Xingmin, Liu Shu, Shen Jingqi, Feng Yudi, Wang Yimou, Yang Youlin, Yang Taiyun, Wen Zixiang, Liu Yangxuan * Mapping unit: Prepared by Desert Research Office, Chinese Academy of Sciences * Publisher: No * Scale: 1: 300000 * Publication time: No * Legend: undulating undulating sandy loess plain, non-desertified land, grassland, saline-alkali land, woods and shrubs, arable land, mountains, sand dunes File format and naming The data is stored in ESRI Shapefile format, including the following layers: Naiman Banner, Kubian Banner, Kezuohou Banner Desertification Type Map, River, Road, Lake, Railway, Well Spring, Residential Area Data attributes Desertification Grade Vegetation Background Desertified land under development Saline-alkali land Heavily desertified land Woods and shrubs Mountain Strongly developed desertified land Potentially desertified land Lake Non-desertified land Undulating sandy loess plain 2. Projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
WANG Jianhua, ZHU Zhenda
Water scarcity，food crises and ecological deterioration caused by drought disasters are a direct threat to food security and socio-economic development. Improvement of drought disaster risk assessment and emergency management is now urgently required. This article describes major scientific and technological progress in the field of drought disaster risk assessment. Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Soil relative humidity index is one of the indicators to characterize soil drought and can directly reflect the status of crops' available water.
GE Yong, WU Hua
The dataset contains all individual glacial storage (unit: km3) over the Qinghai-Tibetan Plateau in 1970s and 2000s. It is sourced from the resultant data of the paper entitled "Consolidating the Randolph Glacier Inventory and the Glacier Inventory of China over the Qinghai-Tibetan Plateau and Investigating Glacier Changes Since the mid-20th Century". The first draft of this paper has been completed and is planned to be submitted to Earth System Science Data journal. The baseline glacier inventories in 1970s and 2000s are the Randolph Glacier Inventory 4.0 dataset, and the Glacier Inventory of China, respectively. Based on the individual glacial boundaries extracted from the above-mentioned two datasets, the grid-based bedrock elevation dataset (https://www.ngdc.noaa.gov/mgg/global/global.html, DOI: 10.7289/v5c8276m), and the glacier surface elevation obtained by a slope-dependent method, the individual glacier volumes in 1970s and 2000s are then calculated. In addition, the calculated results of individual glacier volumes in this study have been compared and verified with the existent results of several glacier volumes, relevant remote sensing datasets, and the global glacier thickness dataset based on the average of multiple glacier model outputs (https://www.research-collection.ethz.ch/handle/20.500.11850/315707, doi:10.3929/ethz-b-000315707), and the errors in the calculations have also been quantified. The established dataset in this study is expected to provide the data basis for the future regional water resources estimation and glacier ablation-involved researches. Moreover, the acquisition of the data also provides a new idea for the future glacier storage estimation.
WANG Jianhua, ZHU Zhenda, FENG Yusun, YAO Fafen
The data is digitized from a drawing, the map of developmental degree of desertification in Daqinggou, Keerqin (HORQIN) Steppe (1975). The specific information of this map is as follows: * Chief Editor: Zhu Zhenda * Editor: Feng Yusun * Drawer: Feng Yusun, Yao Fafen, Wang Jianhua, Zhao Yanhua, Li Weimin * Mapping unit: Prepared by Desert Research Office, Chinese Academy of Sciences * Publisher: No * Scale: 1: 50000 * Publication time: No * Legend: Gully Dense Forest, Sparse Woods, Brush, Artificial Woodland, Nursery and Vegetable Garden, Grass Land, Dry Farmland (Dry Farmland), Rejected Farmland, Marsh Land, Shifting Snad-Dunes, Semi-Shifting Sand-Dunes, Semi-Fixed Sand-Dunes ), Fixed Sand-Dunes, Water Area, Rice, Residential, Highway 1. File format and naming The data is stored in ESRI Shapefile format, including the following layers: Desertification map of Daqinggou area in Horqin steppe, rivers, swamps, roads, lakes, residential areas 2. Data desertification attribute fields: Type of desertification (Shape), Grassland (Grassland), Woodland (Woodland), Woodland Density (W_density), Farmland (Farmland) 3. Projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
WANG Jianhua, ZHU Zhenda, FENG Yusun, YAO Fafen
1) The data content includes three stages of soil erosion intensity in Qinghai-Tibet Plateau in 1992, 2005 and 2015m the grid resolution is 300m.2) The data of soil erosion intensity are obtained by using the Chinese soil erosion prediction model (CSLE). The formula of soil erosion prediction model includes rainfall erosivity factor, soil erodibility factor, slope length factor, slope factor, vegetation cover and biological measure factor, engineering measure factor and tillage measure factor. Rainfall erodibility factors are calculated from the daily rainfall data by the US Climate Prdiction Center (CPC); soil erodibility factors, engineering measures factors and tillage measures factors are obtained from the first water conservancy census data; slope length factors and slope factors are obtained by resampling after calculating 30 m elevation data; vegetation coverage and biological measures factors are obtained by combining fractional vegetation cover with land use data and rainfall erodibility proportionometer. The fractional vegetation cover is calculated by MODIS vegetation index products through pixel dichotomy. 3) Compared with the data of soil erosion intensity in the same region in the same year, there is no significant difference and the data quality is good.4) the data of soil erosion intensity is of great significance for studying the present situation of soil erosion in Pan third polar 65 countries and better carrying out the development policy of the area along the way.
ZHANG Wenbo
This data set contains 2018 global forest fire case data for the whole year and 2019, including the forest fire in California in November 2018, the forest fire in Attica, Greece in July 2018, and the forest fire in Shanxi Province in March 2019. Case data. Specific data include: fire intensity data of the monitoring range and data of vegetation index changes before and after the disaster. The data set is mainly used to describe the occurrence, development, impact and recovery of major global forest fire events in the first half of 2018-2019. The data mainly comes from NASA official website and EM-DAT database, it was processed by statistical and spatial analysis methods using EXCEL and ArcGIS tools. The data source is reliable, the processing method is scientific and rigorous, and it can be effectively applied to global (forest fire) disaster case analysis research.
YANG Yuqing, GONG Adu, WU Jianjun, ZHOU Hongmin
The research project on the function and mechanism of sand-fixing afforestation of waste lignin from straw pulp and paper making belongs to the national natural science foundation of China "environment and ecological science in western China" major research program, led by wang hanjie, a researcher of the institute of aviation meteorology and chemical protection, air force equipment research institute. The project ran from January 2004 to December 2006 Remittance data of the project: 1. 2005-08-10 - sand lake - jinsha wan test site image (JPG) 2.2006 field picture of fixed sand test (JPG) 3. Meteorological data of ningxia jinshawan meteorological station (TXT text) Observation data including dry bulb temperature, wet bulb temperature, 0, 5, 10, 15, 20cm ground temperature, evaporation and air temperature were observed at 8:00,14:00 and 20:00 on August 13, 2005 4. Growth data of jinshawan community in ningxia (TXT text) The data of crown diameter and height of four samples are included. 5. Soil water data of jinshawan, ningxia (excel) Soil moisture data of 16 samples at depths of 20CM and 12CM in clear water control area and lignin spraying area by 2 hours in the daytime on August 19, 2005. 6. Soil water data of shahu lake in ningxia (excel) On August 10,11, 2005, soil moisture data of various depths of 10CM,12CM and 20CM were obtained 7. Plant growth data of sand fixation community in shahu, ningxia (excel) Plant growth statistics of 5 sample plots: species name,x,y, base, crown, height, number of plants.
WANG Hanjie
Data from EM-DAT. EM-DAT is a global database on natural and technological disasters, containing essential core data on the occurrence and effects of more than 21,000 disasters in the world, from 1900 to present. EM-DAT is maintained by the Centre for Research on the Epidemiology of Disasters (CRED) at the School of Public Health of the Université catholique de Louvain located in Brussels, Belgium.The main objective of the database is to serve the purposes of humanitarian action at national and international levels. The initiative aims to rationalise decision making for disaster preparedness, as well as provide an objective base for vulnerability assessment and priority setting.The database is made up of information from various sources, including UN agencies, non-governmental organizations, insurance companies, research institutes and press agencies. Priority is given to data from UN agencies, governments, and the International Federation of Red Cross and Red Crescent Societies. This prioritization is not only a reflection of the quality or value of the data, it also reflects the fact that most reporting sources do not cover all disasters or have political limitations that could affect the figures. The entries are constantly reviewed for inconsistencies, redundancy, and incompleteness. CRED consolidates and updates data on a daily basis. A further check is made at monthly intervals, and revisions are made at the end of each calendar year.
GE Yong, LI Qiangzi, DONG Wen
The data is digitized from a drawing, the map of developmental degree of desertification in Daqinggou, Keerqin (HORQIN) Steppe (1981). The specific information of this map is as follows: * Chief Editor: Zhu Zhenda * Editor: Feng Yusun * Drawer: Feng Yusun, Yao Fafen, Wang Jianhua, Zhao Yanhua, Li Weimin * Mapping unit: Prepared by Desert Research Office, Chinese Academy of Sciences * Publisher: No * Scale: 1: 50000 * Publication time: No * Legend: Gully Dense Forest, Sparse Woods, Brush, Artificial Woodland, Nursery and Vegetable Garden, Grass Land, Dry Farmland (Dry Farmland), Rejected Farmland, Marsh Land, Shifting Snad-Dunes, Semi-Shifting Sand-Dunes, Semi-Fixed Sand-Dunes ), Fixed Sand-Dunes, Water Area, Rice, Residential, Highway 1. File format and naming The data is stored in ESRI Shapefile format, including the following layers: Desertification map of Daqinggou area in Horqin steppe, rivers, swamps, roads, lakes, residential areas 2. Data desertification attribute fields: Type of desertification (Shape), Grassland (Grassland), Woodland (Woodland), Woodland Density (W_density), Farmland (Farmland) 3. Projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
WANG Jianhua, ZHU Zhenda, YAO Fafen, FENG Yusun
Global Tropical cyclone (TC) best track data already exist as individual storm tracks at other agencies. The intent of the IBTrACS project is to overcome data availability issues. This was achieved by working directly with all the Regional Specialized Meteorological Centers and other international centers and individuals to create a global best track dataset, merging storm information from multiple centers into one product and archiving the data for public use. The World Meteorological Organization Tropical Cyclone Programme has endorsed IBTrACS as an official archiving and distribution resource for tropical cyclone best track data. The IBTrACS project: contains the most complete global set of historical tropical cyclones available, combines information from numerous tropical cyclone datasets, simplifies inter-agency comparisons by providing storm data from multiple sources in one place, provides data in popular formats to facilitate analysis and checks the quality of storm inventories, positions, pressures, and wind speeds, passing the information on to the user. The primary intent of IBTrACS is to support scientific research efforts.
GE Yong, LI Qiangzi, DONG Wen
This dataset mainly includes the spatial distribution of global SPEI in 1218 in 2018, the global drought intensity in 2018, and the anomalies of precipitation, land surface temperature, 0-10 cm soil moisture and the past 10 years (2009-2018); The flat index method, the maximum value synthesis method and the trend analysis method calculate the global drought intensity and the main meteorological factor anomaly data for 2018. The data time scale is 2018-01-01 to 2018-12-31, and the spatial resolution is 0.5 degree. The data can provide a scientific reference for the analysis of global drought distribution and drought assessment in 2018.
TIAN Feng, WU Jianjun, ZHOU Hongmin
The China-Pakistan Economic Corridor, north from Kashgar of China and south to the Gwadar seaport of Pakistan, with a total length of 000 km, is the key to linking the north and south Silk Road. Due to the complex geology, landform, climate, hydrology conditions, landslides and debris flows are very active in this area. Through the combination of field investigation and image interpretation, the symbols of typical landslide and debris flow images were established. Based on interactive interpretation and field investigation verification, the spatial distribution of landslides and debris flows within the scope of CPEC was identified, which provides important data support for risk analysis of landslide and debris flow disasters in CPEC and disaster prevention and reduction.
ZOU Qiang
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