Meteorological data of the integrated observation and research station of Ngari for desert environment (2009-2017)

The data set includes meteorological data from the Ngari Desert Observation and Research Station from 2009 to 2017. It includes the following basic meteorological parameters: temperature (1.5 m from the ground, once every half hour, unit: Celsius), relative humidity (1.5 m from the ground, once every half hour, unit: %), wind speed (1.5 m from the ground, once every half hour, unit: m/s), wind direction (1.5 m from the ground, once every half hour, unit: degrees), atmospheric pressure (1.5 m from the ground, once every half hour, unit: hPa), precipitation (once every 24 hours, unit: mm), water vapour pressure (unit: kPa), evaporation (unit: mm), downward shortwave radiation (unit: W/m2), upward shortwave radiation (unit: W/m2), downward longwave radiation (unit: W/m2), upward longwave radiation (unit: W/m2), net radiation (unit: W/m2), surface albedo (unit: %). The temporal resolution of the data is one day. The data were directly downloaded from the Ngari automatic weather station. The precipitation data represent daily precipitation measured by the automatic rain and snow gauge and corrected based on manual observations. The other observation data are the daily mean value of the measurements taken every half hour. Instrument models of different observations: temperature and humidity: HMP45C air temperature and humidity probe; precipitation: T200-B rain and snow gauge sensor; wind speed and direction: Vaisala 05013 wind speed and direction sensor; net radiation: Kipp Zonen NR01 net radiation sensor; atmospheric pressure: Vaisala PTB210 atmospheric pressure sensor; collector model: CR 1000; acquisition interval: 30 minutes. The data table is processed and quality controlled by a particular person based on observation records. Observations and data acquisition are carried out in strict accordance with the instrument operating specifications, and some data with obvious errors are removed when processing the data table.

0 2020-01-13

Meteorological observation data from the integrated observation and research station of the alpine environment in Southeast Tibet (2007-2017)

This data set includes daily average data of atmospheric temperature, relative humidity, precipitation, wind speed, wind direction, net radiance, and atmospheric pressure from 1 January 2007 to 31 December 2016 derived from the Integrated Observation and Research Station of the Alpine Environment in Southeast Tibet. The data set has been used by students and researchers in the fields of meteorology, atmospheric environment and ecological research. The units of the various meteorological elements are as follows: temperature °C; precipitation mm; relative humidity %; wind speed m/s; wind direction °; net radiance W/m2; pressure hPa; and particulate matter with aerodynamic diameter less than 2.5 μm μg/m3. All the data are the daily averages calculated from the raw observations. Observations and data collection were carried out in strict accordance with the instrument operating specifications and the guidelines published in relevant academic journals; data with obvious errors were eliminated during processing, and null values were used to represent the missing data. In 2015, due to issues related to the age of the observation probe at the station, only the wind speed data for the last 8 months were retained.

0 2020-01-10

Shergyla Mountain meteorological data (2005-2017)

Shergyla Mountain meteorological data, Record the surface near Linzhi(1.2-1.5m) conventional meteorological observation.The dataset records the meteorological data at the eastern slope of Shergyla Mountain from 2005 to 2016, and North-facing slope from 2005 to 2012.Including daily average data of temperature, relative humidity, precipitation. Data collected near the eastern slope timberline of Shergyla Mountain, Latitude:29°39′25.2″N; Longitude:94°42′25.62″E; Altitude:4390m, and collected near the north-facing slope of Shergyla Mountain, Latitude:29°35′50.9″N; Longitude:94°36′42.7″E; Altitude:4390m. Collector: Campbell Co CR1000. Collection time interval:30min. Digital automatic data collection, daily average value of artificial calculation. It includes the following basic meteorological parameters: North-facing slope data: Wind speed,Unit m/s Temperature,Unit ℃ Relative Humidity,Unit % Atmospheric pressure,Unit hPa Global radiation,Unit w/m2 Soil heat flux,Unit w/m2 Soil temperature,Unit ℃ Soil moisture,Unit % Precipitation,Unit mm Thickness of snow, Unit cm Ecology station data: Temperature,Unit ℃ Relative Humidity,Unit % Atmospheric pressure,Unit hPa Wind speed,Unit m/s Precipitation,Unit mm Snow Depth,Unit cm Radiation,Unit w/m2 Soil moisture content,Unit % Soil heat flux,Unit w/m2

0 2020-01-10

Observation data set of field weather stations in Central Asia (2018-2019)

The observation data set of Central Asia field meteorological station includes the field observation data of temperature, precipitation, wind direction and speed, relative humidity, air pressure, radiation, soil heat flux, sunshine time and soil temperature of 10 Central Asia field meteorological stations. 10 field stations cover farmland, forest, grassland, desert, desert, wetland, plateau, mountain and other ecosystem types. The original meteorological data collected by the ground meteorological observation station is obtained after screening and review, and format conversion. Data quality is good. Central Asia has a variety of climate types, fragile ecological environment and frequent meteorological disasters. The establishment of this data set provides data support for long-term research in the fields of Central Asia ecological environment monitoring, disaster prevention and mitigation, climate change and ecological environment in Central Asia, and has been applied in the research of Central Asia ecological environment monitoring.

0 2019-12-16

Monthly dataset of ERA-Interim based on pressure levels from 1979 to 2018 released from ECMWF

This dataset is derived from the global atmospheric reanalysis dataset, ERA-Interim, based on the 4-dimensional variational analysis (4D-Var) released by the European Centre for Medium-Range Weather Forecasts (ECMWF). ERA-Interim represents a major undertaking by ECMWF (European Centre for Medium-Range Weather Forecasts) to produce a reanalysis with an improved atmospheric model and assimilation system which replaces those used in ERA-40, particularly for the data-rich 1990s and 2000s, and to be continued as an ECMWF Climate Data Assimilation System (ECDAS) until superseded by a new reanalysis. Through systematic increases in computing power, 4-dimensional variational assimilation (4D-Var) became feasible and part of ECMWF operations since 1997. Enhanced computing power also allowed horizontal resolution to be increased from T159 to T255, and the latest Integrated Forecasting System(IFS CY31r1 and CY31r2) to be used, taking advantage of improved model physics. ERA-interim retains the same 60 model levels used for ERA-40 with the highest level being 0.1 hPa. Besides, data assimilation of ERA-Interim also benefits from quality control that draws on experience from ERA-40 and JRA-25, variational bias correction of satellite radiance data, and more extensive use of radiances with an improved fast radiative transfer model. In addition, ERA-Interim uses the new ERS (European Remote Sensing Satellite) altimeter wave heights, EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) reprocessed winds and clear-sky radiances, GOME (Global Ozone Monitoring Experiment) ozone data from the Rutherford Appleton Laboratory, and CHAMP (CHAllenging Minisatellite Payload), GRACE (Gravity Recovery and Climate Experiment), and COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) GPS radio occultation measurements processed and archived by UCAR (University Corporation for Atmospheric Research).

0 2019-12-05

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

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

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 Kunsha Glacier (2015-2017)

This data set includes the temperature, precipitation, relative humidity, wind speed, wind direction and other daily values in the observation point of Kunsha Glacier. The data is observed from October 3, 2015 to September 19, 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. The data is stored as an excel file.

0 2019-11-17

Yulong snow mountain glacier No.1, 4 506 m altitude the daily average meteorological observation dataset (2014-2018)

1. Data content: air temperature, relative humidity, precipitation, air pressure, wind speed, average total radiation, total net radiation value and daily average water vapor pressure data. 2. Data source and processing method: Observed by American campel high-altitude automatic weather station, air temperature and humidity sensor model HMP155A; wind speed and wind direction model: 05103-45; net radiometer: CNR 4 Net Radiometer four component; atmospheric pressure sensor: CS106; Rain gauge: TE525MM. The automatic weather station automatically collects data every 10 minutes, and collects daily statistical data to obtain daily average weather data. 3. Data quality description: Data is automatically acquired continuously. 4. Data application results and prospects: The weather station is located in the middle of the glacier, and the meteorological data can provide data guarantee for simulating the response of oceanic glacier changes to global climate change in the context of future climate change.

0 2019-11-12