China meteorological forcing dataset (1979-2018)

The China Meteorological Forcing Dataset (CMFD) is a high spatial-temporal resolution gridded near-surface meteorological dataset that was developed specifically for studies of land surface processes in China. The dataset was made through fusion of remote sensing products, reanalysis dataset and in-situ observation data at weather stations. Its record starts from January 1979 and keeps extending (currently up to December 2018) with a temporal resolution of three hours and a spatial resolution of 0.1°. Seven near-surface meteorological elements are provided in CMFD, including 2-meter air temperature, surface pressure, specific humidity, 10-meter wind speed, downward shortwave radiation, downward longwave radiation and precipitation rate.

0 2019-11-19

A monthly air temperature and precipitation gridded dataset on 0.025° spatial resolution in China during(1951-2011)

Gridded climatic datasets with fine spatial resolution can potentially be used to depict the climatic characteristics across the complex topography of China. In this study we collected records of monthly temperature at 1153 stations and precipitation at 1202 stations in China and neighboring countries to construct a monthly climate dataset in China with a 0.025° resolution (~2.5 km). The dataset, named LZU0025, was designed by Lanzhou University and used a partial thin plate smoothing method embedded in the ANUSPLIN software. The accuracy of LZU0025 was evaluated based on three aspects: (1) Diagnostic statistics from the surface fitting model during 1951–2011. The results indicate a low mean square root of generalized cross validation (RTGCV) for the monthly air temperature surface (1.06 °C) and monthly precipitation surface (1.97 mm1/2). (2) Error statistics of comparisons between interpolated monthly LZU0025 with the withholding of climatic data from 265 stations during 1951–2011. The results show that the predicted values closely tracked the real true values with values of mean absolute error (MAE) of 0.59 °C and 70.5 mm, and standard deviation of the mean error (STD) of 1.27 °C and 122.6 mm. In addition, the monthly STDs exhibited a consistent pattern of variation with RTGCV. (3) Comparison with other datasets. This was done in two ways. The first was via comparison of standard deviation, mean and time trend derived from all datasets to a reference dataset released by the China Meteorological Administration (CMA), using Taylor diagrams. The second was to compare LZU0025 with the station dataset in the Tibetan Plateau. Taylor diagrams show that the standard deviation, mean and time trend derived from LZU had a higher correlation with that produced by the CMA, and the centered normalized root-mean-square difference for this index derived from LZU and CMA was lower. LZU0025 had high correlation with the Coordinated Energy and Water Cycle Observation Project (CEOP) - Asian Monsoon Project, (CAMP) Tibet surface meteorology station dataset for air temperature, despite a non-significant correlation for precipitation at a few stations. Based on this comprehensive analysis, we conclude that LZU0025 is a reliable dataset. LZU0025, which has a fine resolution, can be used to identify a greater number of climate types, such as tundra and subpolar continental, along the Himalayan Mountain. We anticipate that LZU0025 can be used for the monitoring of regional climate change and precision agriculture modulation under global climate change.

0 2019-11-18

Precipitation observation data of the east bank of Selincuo Lake (2016-2017)

This is the precipitation observation data set of the east bank of Selincuo Lake. It can be used in Glaciology, Climatology, Environmental Change, Hydrologic Process in Cold Regions and other disciplinary areas. The data is observed from September 1, 2016 to August 17, 2017. It is measured by automatic rain gauge and a piece of data is recorded every 60 minutes. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The original data meets the accuracy requirements of China Meteorological Administration (CMA) and the World Meteorological Organization (WMO) for meteorological observation. Quality control includes eliminating the systematic error caused by the missing point data and sensor failure. The data is stored as an excel file.

0 2019-11-18

Precipitation observation data on Taerma Township (2016-2017)

This is the precipitation observation data of the observation point in Taerma Township. It can be used in Glaciology, Climatology, Environmental Change, Hydrologic Process in Cold Regions and other disciplinary areas. The data is observed from September 15, 2016 to August 17, 2017. It is measured by automatic rain gauge and a piece of data is recorded every 60 minutes. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The original data meets the accuracy requirements of China Meteorological Administration (CMA) and the World Meteorological Organization (WMO) for meteorological observation. Quality control includes eliminating the systematic error caused by the missing point data and sensor failure. The data is stored as an excel file.

0 2019-11-18

Meteorological observation data of Selincuo Lake camp (2017)

This is the meteorological observation data of Selincuo Lake Camp. It includes the radiosonde data, turbulent flux, radiation observation data, general meteorologrical elements near the surface layer and others. The radiosonde data is observed separately at 14:00 and 18:00 July 2, at 8:00, 12:00, 16:00 and 20:00 July 3, at 8:00, 12:00, 16:00, 20:00, and 23:00 July 4, at 6:00 July 5, 2017. The observation time of turbulent flux and radiation observation data is from 17:30 June 29 to 10:00 July 6, 2017. The observation time of general meteorologrical elements near the surface layer is from 18:30 June 29 to 10:10 July 6, 2017. The wind lidar observation time is from 2:24 June 30 to 3:49 July 6, 2017. The data is stored as an excel file.

0 2019-11-18

Slopes-Runoff observation dataset of Selincuo Basin (2017)

This is the slopes-runoff observation data set in typical underlying surface runoff fields of Selincuo Basin. It can be used in Hydrologic Process in Cold Regions, Geocryology and other disciplinary areas. The underlying surface of the observation point is the typical alpine steppe. The data is observed on July 2, August 10, August 17, August 26, August 30, September 1, September 2, September 3, and September 4, 2017. The observation includes the rainfall time, rainfall duration, rainfall, average rainfall, runoff, and the runoff coefficient. The precipitation duration is accurate to minute, the precipitation observation is accurate to 0.1mm, and the runoff observation is converted to mm, which is accurate to 0.01mm.The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The data is stored as an excel file.

0 2019-11-18

Sounding observation dataset of Ali Station (2017)

This is the sounding observation data set measured by the sounding instrument. It is released by Ali Station, Institute of Tibetan Plateau Research, Chinese Academy of Sciences. The observation time is separately at 12:00, 16:00, 20:00 September 2, 2017, at 16:00, 20:00 September 3, 2017, at 8:00, 12:00, 16:00, 20:00, September 4,2017, at 0:00, 4 :00, 8:00, 12:00, 16:00, 20 :00 September 5, 2017, at 0:00, 4 :00, 8:00, September 6,2017. The original data accuracy is as follows. The data accurate to the integer position are logarithmic pressure, relative humidity, altitude, horizontal wind direction, azimuth, and elevation. The data accurate to one decimal place are temperature, air pressure, dew-point temperature, horizontal wind speed, and longitude. And the data accurate to two decimal places are meridional wind velocity, zonal wind velocity, vapor-to-liquid ratio and latitude. Quality control includes eliminating the missing data and the empty data. The data is stored as an excel file.

0 2019-11-18

Meteorological observation data of Kongque River Source (2012-2017)

This data set includes the temperature, precipitation, relative humidity, wind speed, wind direction and other daily values in the observation point of Kongque River Source. The data is observed from July 2, 2012 to September 15, 2017. It is measured by automatic meteorological station (Onset Company) and a piece of data is recorded every 2 hours. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The original data meets the accuracy requirements of China Meteorological Administration (CMA) and the World Meteorological Organization (WMO) for meteorological observation. Quality control includes eliminating the systematic error caused by the missing point data and sensor failure.

0 2019-11-18

Meteorological observation dataset of Shiquan River Source (2012-2015)

This dataset includes the temperature, precipitation, relative humidity, wind speed, wind direction and other daily values in the observation point of Shiquan River Source. The data is observed from July 2, 2012 to August 5, 2014, and from September 30, 2015 to December 25, 2015. It is measured by automatic meteorological station (Onset Company) and a piece of data is recorded every 2 hours. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The original data meets the accuracy requirements of China Meteorological Administration (CMA) and the World Meteorological Organization (WMO) for meteorological observation. Quality control includes eliminating the systematic error caused by the missing point data and sensor failure. The data is stored as an excel file.

0 2019-11-17

The precipitation from May to September on the Tibetan Plateau and surrounding areas (1957-2015)

The data set contains annual precipitation from May to September on the Tibetan Plateau and surrounding areas during 1957 to 2015, with a data resolution of one year. The raw data were obtained from the National Meteorological Information Center of the China Meteorological Administration (https://data.cma.cn). The default data were replaced with multiyear average values. The data are in two columns: The first column is the year; The second column is precipitation, unit: millimeters.

0 2019-11-13