Agricultural irrigation consumes a large amount of available freshwater resources and is the most immediate human disturbance to the natural water cycle process, with accelerated regional water cycles accompanied by cooling effects. Therefore, estimating irrigation water use (IWU) is important for exploring the impact of human activities on the natural water cycle, quantifying water resources budget, and optimizing agricultural water management. However, the current irrigation data are mainly based on the survey statistics, which is scattered and lacks uniformity, and cannot meet the demand for estimating the spatial and temporal changes of IWU. The Global Irrigation Water Use Estimation Dataset (2011-2018) is calculated by the satellite soil moisture, precipitation, vegetation index, and meteorological data (such as incoming radiation and temperature) based on the principle of soil water balance. The framework of IWU estimation in this study coupled the remotely sensed evapotranspiration process module and the data-model fusion algorithm based on differential evolution. The IWU estimates provided from this dataset have small bias at different spatial scales (e.g., regional, state/province and national) compared to traditional discrete survey statistics, such as at Chinese provinces for 2015 (bias = −3.10 km^3), at U.S. states for 2013 (bias = −0.42 km^3), and at various FAO countries (bias = −10.84 km^3). Also, the ensemble IWU estimates show lower uncertainty compared to the results derived from individual precipitation and soil moisture satellite products. The dataset is unified using a global geographic latitude and longitude grid, with associated metadata stored in corresponding NetCDF file. The spatial resolution is about 25 km, the time resolution is monthly, and the time span is 2011-2018. This dataset will help to quantitatively assess the spatial and temporal patterns of agricultural irrigation water use during the historical period and support scientific agricultural water management.
ZHANG Kun, LI Xin, ZHENG Donghai, ZHANG Ling, ZHU Gaofeng
The data set is a sub data set of the comprehensive observation data set of cloud precipitation process, which is derived from the comprehensive investigation and test carried out in Liupanshan area during 2021. Liupanshan scientific research is carried out in Dawan station, Jingyuan station, Liupanshan station, Longde station, etc. Dawan station is mainly equipped with cfl-06 wind profile radar, ht101 cloud radar, mrr-2 micro rain radar, dsg5 raindrop spectrometer, three-dimensional anemometer, C12 laser cloud altimeter. Jingyuan station is mainly equipped with qfw-6000 microwave radiometer, hmb-kps cloud radar, dsg5 raindrop spectrometer Cl51 laser cloud altimeter. Liupanshan station is mainly equipped with ht101 cloud radar, mrr-2 micro rain radar, Ott laser raindrop spectrometer, cloud condensation nodule (CCN) counter, three-dimensional anemometer, FM120 droplet spectrometer and C12 laser cloud altimeter. Longde station is mainly equipped with rpg-hatpro-g4 microwave radiometer, cfl-06 wind profile radar, ht101 Cloud Radar, mrr-2 micro rain radar Ott laser raindrop spectrometer, C12 laser cloud altimeter. Meanwhile automatic weather station, iron tower (Shangpu), X-band all solid-state dual polarization Doppler Weather Radar (Pengyang County), gradient station and other observations were done. It can be used to study the impact of the eastward movement of the plateau system on the downstream, and to reveal the impact of the atmospheric boundary layer and free atmospheric exchange process on aerosols, clouds Fog and precipitation and their interaction.
FU Danhong
The data set is a sub data set of the comprehensive observation data set of cloud precipitation process, which is derived from the comprehensive investigation and test carried out in Sanjiangyuan area during 2021. The scientific research of Sanjiangyuan mainly focuses on Advanced Air King aircraft observation. The airborne observation system includes aerosol, cloud particle spectrometer and imager observation. The observation elements include precipitation particle concentration and image of IP probe, cloud particle concentration and image of CIP probe, cloud and aerosol particle data of CAS probe and Hotwire_ LWC probe liquid water data, CAPS Summary aerosol, cloud and precipitation comprehensive data, AIMMS probe conventional meteorological elements, PCASP -100 probe aerosol particle data. Ground observation includes raindrop spectrometer, microwave radiometer and X-band radar. Raindrop spectrometer mainly observes equivalent volume diameter and particle falling speed. Microwave radiometer mainly observes temperature, humidity, water vapor and liquid water. And X-band radar mainly observes intensity, velocity and spectral width. It can provide data support for the study of the impact of westerly monsoon synergy on the cloud precipitation process of Sanjiang source.
FU Danhong
This data set is a sub data set of the comprehensive observation data set of cloud precipitation process, which is derived from the field observation test of cloud precipitation physical process carried out in Nyingchi area from 2019 to 2021. The observation instruments include Ka band millimeter wave cloud radar, micro rain radar and raindrop spectrometer. The observation elements of Ka band milliwave Cloud Radar include fixed-point vertical observation, RHI scanning observation and volume scanning observation data, The observation elements of micro rain radar include particle spectrum, liquid water content and precipitation intensity. The observation elements of raindrop spectrometer include particle spectrum and precipitation intensity. This data set can provide data support for the study of the formation mechanism and change trend of cloud precipitation physical process in Southeast Tibet and the response mechanism to westerly monsoon change.
FU Danhong
This data includes the image data of the second comprehensive field scientific investigation of the Qinghai Tibet Plateau. The image data includes the sample plot photos of the quadrats collected in the nature reserve during the scientific research, the images of forest ecosystem, grassland ecosystem and lake ecosystem in the nature reserve in Northwest Yunnan and Western Sichuan, the vegetation situation, wildlife habitat, and the data of animals, plants and fungi in the reserve. In addition, the image data also includes the sample collection process of the scientific research, the household survey of the scientific research team in the community survey and the image data of the interview with the local protection department. The data comes from UAV and camera shooting, which can provide evidence and reference for scientific research.
SU Xukun
The dataset of the truck-mounted dual polarized doppler radar observations (time-continuous 10-minute on the 250m×250m horizontal grid) was obtained in the arid region hydrology experiment area from May 20 to Jul. 5, 2008. The observation site (38.73°N, 100.45°E, 1668m) was typical of complex underlying surface and transit zone landscapes. The aim was to explore and retrieve precipitation type and intensity by radar in cold regions, with the precipitation particle drop size analyzer and ground intensive measurements occurring simultaneously, thus making it possible to produce a high resolution precipitation dataset. The 714XDP X-band dual-linear polarization Doppler weather radar was with a horizontal resolution of 150 m, an azimuth resolution of 1, VCP from 10-22 layers and the scanning cycle 10 minutes. ZH, ZDR and KDP could be acquired together. For more details, please refer to Readme file.
CHU Rongzhong, ZHAO Guo, HU Zeyong, ZHANG Tong, JIA Wei
Data content: precipitation data of the Aral Sea basin from 2015 to 2018. Data sources and processing methods: from the new generation of global precipitation measurement (GPM) of NASA, the daily rainfall can be obtained by adding the three-hour rainfall data, and then the eight day rainfall can be obtained. Data quality: the spatial resolution is 0.1 ° x 0.1 ° and the temporal resolution is 8 days. The value of each pixel is the sum of rainfall in 8 days. Data application results: under the background of climate change, it can be used to analyze the correlation between meteorological elements and vegetation characteristics.
LIU Tie
The dataset of the truck-mounted dual polarized doppler radar observations (time-continuous 10-minute on the 250m×250m horizontal grid) was obtained in A'rou (39.06°N, 100.44°E, 3002m, typical of complex terrain in high altitude), Qilian county in the upper stream of Heihe river from Mar. 14 to Apr. 14, 2008. The aim was to explore and retrieve precipitation type and intensity by radar in cold regions, with the precipitation particle drop size analyzer and ground intensive measurements occurring simultaneously, thus making it possible to produce a high resolution precipitation dataset. The 714XDP X-band dual-linear polarization Doppler weather radar was with a horizontal resolution of 150 m, an azimuth resolution of 1, VCP from 10-22 layers and the scanning cycle 10 minutes. ZH, ZDR and KDP could be acquired together. For more details, please refer to Readme file.
CHU Rongzhong, ZHAO Guo, HU Zeyong, ZHANG Tong, JIA Wei
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