Current Browsing: Cloud Microphysics


Human activity data in key areas of Qilian Mountains in 2019

This dataset contains the flux measurements from the Subalpine shrub eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from April 28 to December 31 in 2019. The site (100°6'3.62"E, 37°31'15.67" N ) was located near Dasi, Shaliuhe Town, Gangcha County, Qinghai Province. The elevation is 3495m. The EC was installed at a height of 2.5m, and the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (Gill&Li7500A) was about 0.17 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. The observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC): class 1-3 (high quality), class 4-6 (good), class 7-8 (poor, better than gap filling data), class9 (rejected). In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data collected before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day, and the missing data were replaced with -6999. The released data contained the following variables: DATE/TIME, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xls format. Detailed information can be found in the suggested references.

2020-07-28

Watershed allied telemetry experimental research,WATER: The doppler weather radar observation dataset of Zhangye National climate observatory from Mar to Jun, 2008

This dataset contains Doppler Weather Radar data from the Zhangye National Climate Observatory during the Watershed Allied Telemetry Experimental Research from 2008-03-08 to 2008-06-30. The latitude and longitude of the observation point are 100°16.8'E, 39°05.094'N; the altitude is 1378m. The main observation items are: rainfall, cloud physics, weather radar, etc.

2019-09-15

Dataset of cloud observations in Arctic Alaska (1999-2009)

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.

2019-09-12