The data set is a numerical simulation data set based on CESM2.1.3 mode. The data set is global multi scenario monthly climate data. The spatial resolution is f19_ G17 atmosphere/land is 1.9x2.5 degrees, from January 2015 to December 2010, and the data is in NETCDF format. The data set includes historical data from 1850-2014 (referred to as Hist for short) and SSP scenarios (SSP126, SSP245, SSP370, SSP585). Each scenario includes three sets of climate data (default emission data CMIP6 (referred to as CMIP6 for short), China's carbon neutral CNCN (referred to as CNCN for short) CO2 emissions, and China's CH4 and N2O changes with CNCN, which are further used to drive the CESM (referred to as CNCNext for short)), The data set contains a geospatial range of - 90 ° N – 90 ° N and - 180 ° E – 180 ° E.
LI Longhui
1) Data content: the observation data of atmospheric oxidation related parameters in Namuco from April to July 2019, including O3, H2O, CO2, NO2, VOCs, wind direction and wind speed. The coordinates of the observation points are 90.96 ° e, 30.77 ° n, 4730m above sea level, and the underlying surface is alpine grassland. (2) Data source and processing method: the original observation data shall be processed and quality controlled by special personnel according to the observation records. (3) Data quality description: due to the problem of instrument status, the data is missing and discontinuous in some periods. (4) Application prospect of data: the data can be applied to plateau atmospheric chemical analysis and other fields.
YE Chunxiang YE Chunxiang
This dataset contains the flux measurements from the Guazhou station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to December 27 in 2021. The site (102.73E, 36.692N) was located in a desert in Liuyuan Guazhou, which is near Jiuquan city in Gansu Province. The elevation is 2903 m. The EC was installed at a height of 4.0 m, 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 (CSAT3&Li7500A) was 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: data/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). 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Guazhou station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to December 27 in 2021. The site (95.673E, 41.405N) was located in a desert in Liuyuan Guazhou, which is near Jiuquan city in Gansu Province. The elevation is 2016 m. The EC was installed at a height of 4.0 m, 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 (CSAT3&Li7500A) was 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: data/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). 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Suganhu station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to December 27 in 2021. The site (94.12E, 38.99N was located in a desert in Suganhu, which is in Gansu Province. The elevation is 2823 m. The EC was installed at a height of 4.0 m, 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 (CSAT3&Li7500A) was 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. Suspicious data were marked in red. The released data contained the following variables: data/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). 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Sidalong station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to Dec 19 in 2021. The site (99.926E, 38.428N) was located on a forest in the Kangle Sunan, which is near Zhangye city, Gansu Province. The elevation is 3146 m. The EC was installed at a height of 4.0 m above the canopy , 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 (CSAT3&Li7500A) was 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. Suspicious data were marked in red. The released data contained the following variables: data/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). 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Xiyinghe station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to December 27 in 2021. The site (101.853E, 37.561N) was located on a alpine meadow in the Menyuan, Qinghai Province. The elevation is 3639 m. The EC was installed at a height of 4.0 m, 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 (CSAT3&Li7500A) was 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. Suspicious data were marked in red. The released data contained the following variables: data/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). 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Minqin station eddy covariance system (EC) in the middle reaches of the Shiyanghe integrated observatory network from January 1 to December 27 in 2021. The site (103.668E, 39.208N) was located on a alpine meadow in the Wuwei, Gansu Province. The elevation is 1020 m. The EC was installed at a height of 4.0 m, 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 (CSAT3&Li7500A) was 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) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and 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. Suspicious data were marked in red. The released data contained the following variables: data/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). 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.
ZHAO Changming, ZHANG Renyi
The GHG emission reduction resilience of the countries along the Belt and Road reflects the level of GHG emission reduction resilience of the countries along the Belt and Road, and the higher the value of the data, the stronger the GHG emission reduction resilience of the countries along the Belt and Road. The Emissions Database for Global Atmospheric Research (EDGAR) for 2000-2020 was used to prepare the GHG resilience data. The product was prepared based on a sensitivity and adaptation analysis, using year-by-year data of total GHG emissions of countries along the Belt and Road from 2000 to 2020, and a comprehensive diagnosis based on year-by-year changes. The GHG emission reduction resilience dataset for countries along the Belt and Road is an important reference for analyzing and comparing the current GHG emission reduction resilience of each country.
XU Xinliang
The CO2 emission reduction resilience per unit GDP of countries along the Belt and Road reflects the level of CO2 emission reduction resilience per unit GDP of the countries along the Belt and Road, and the higher the value of the data, the stronger the CO2 emission reduction resilience per unit GDP of the countries along the Belt and Road. The CO2 emission reduction resilience per unit of GDP was prepared by referring to the Emissions Database for Global Atmospheric Research (EDGAR) for 2000-2020, using the 2000-2020 data for the period 2000-2020. The CO2 emission reduction resilience products per unit GDP of countries along the "Belt and Road" were prepared based on sensitivity and adaptation analyses, taking into account the year-to-year changes, and through comprehensive diagnosis. The CO2 emission reduction resilience per unit GDP of countries along the "Belt and Road" is an important reference for analyzing and comparing the current CO2 emission reduction resilience per unit GDP of each country.
XU Xinliang
The CO2 emission reduction resilience of the countries along the "Belt and Road" reflects the level of CO2 emission reduction resilience of the countries along the Belt and Road, and the higher the value of the data, the stronger the CO2 emission reduction resilience of the countries along the Belt and Road. The Emissions Database for Global Atmospheric Research (EDGAR) was used to prepare data on the total CO2 emissions of the countries along the "Belt and Road" from 2000 to 2020, taking into account the year-on-year changes. Based on the sensitivity and adaptation analysis, a comprehensive diagnosis was made based on the annual data of the total CO2 emissions of the countries along the "Belt and Road" from 2000 to 2020, and a resilience product for CO2 emission reduction was prepared. "The data set of CO2 emission reduction resilience of countries along the Belt and Road is an important reference for the analysis and comparison of the current CO2 emission reduction resilience of countries.
XU Xinliang
Based on the meteorological data of 105 meteorological stations in and around the Qinghai Tibet Plateau from 1980 to 2019 (data from China Meteorological Administration and National Meteorological Science Data Center), the oxygen content was calculated. It was found that there was a significant linear correlation between oxygen content and altitude, y = -0.0263x + 283.8, R2 = 0.9819. Therefore, the oxygen content distribution map can be calculated based on DEM data grid. Due to the limitation of the natural environment in the Qinghai Tibet Plateau, there are few related fixed-point observation institutions. This data can reflect the distribution of oxygen content in the Qinghai Tibet Plateau to a certain extent, and has certain reference significance for the research of human living environment in the Qinghai Tibet Plateau.
The dataset of eddy covariance observations was obtained at the Dayekou Guantan forest station (E100°15′/N38°32′, 2835m), south of Zhangye city, Gansu province, from Dec. 27, 2007 to Dec. 31, 2009. Guantan forest station was dominated by the spruce 15-20m high and the surface was covered by moss 10cm deep. All the vegetation was in good condition. The original observation items included the latitudinal wind speed Ux (m/s), the latitudinal wind speed Uy (m/s), the longitudinal wind speed Uz (m/s), the ultrasonic temperature Ts (°C), co2 consistency (mg/m^3), h2o consistency (g/m^3), air pressure (KPa) and the abnormal ultrasonic signal (diag_csat). The instrument mount-height was 20.02m, the ultrasound direction was at an azimuth angle of 74°, the distance between Li7500 and CSAT3 was 30cm and sampling frequency was 10HZ. The dataset was distributed at three levels: Level0 were the raw data acquired by instruments; Level1, including the sensible heat flux (Hs), the latent heat flux (LE_wpl), and co2 flux (Fc_wpl), were real-time eddy covariance output data and stored in .csv month by month; Level2 were processed data in a 30-minute cycle after outliers elimination, coordinates rotation, frequency response correction, WPL correction and initial quality control. The data were named as follows: station name +data level+data acquisition date. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide and Eddy Covariance Observation Manual.
LI Xin, MA Mingguo, Wang Weizhen, HUANG Guanghui, TAN Junlei, Zhang Zhihui
The dataset of eddy covariance observations was obtained at the Yingke Oasis station from 27 Dec. 2007 to 31 Dec. 2009. The observation site is located in an irrigation farmland in Yingke (E100°24′37.2″/N38°51′25.7″, 1519.1m), Zhangye city, Gansu province. The experimental area, situated in the middle stream Heihe river basin and with windbreaks space of 500m from east to west and 300m from south to north, is an ideal choice for its flat and open terrain. The original observation items included the latitudinal wind speed Ux (m/s), the latitudinal wind speed Uy (m/s), the longitudinal wind speed Uz (m/s), the ultrasonic temperature Ts (°C), co2 consistency (mg/m^3), h2o consistency (g/m^3), air pressure (KPa) and the abnormal ultrasonic signal (diag_csat). The instrument mount was 2.81m, the ultrasound direction was at an azimuth angle of 0°, the distance between Li7500 and CSAT3 was 30cm and the sampling frequency was 10HZ/s. The dataset was distributed at three levels: Level0 were the raw data acquired by instruments; Level1, including the sensible heat flux (Hs), the latent heat flux (LE_wpl), and co2 flux (Fc_wpl), were real-time eddy covariance output data and stored in .csv month by month; Level2 were processed data in a 30-minute cycle after outliers elimination, coordinates rotation, frequency response correction, WPL correction and initial quality control. The data files were named as follows: station name +data level+data acquisition date. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide and Eddy Covariance Observation Manual.
Liu Qiang, LIU Qinhuo, MA Mingguo, Wang Weizhen, HUANG Guanghui, Zhang Zhihui, TAN Junlei
The dataset of eddy covariance observations was obtained at the A'rou freeze/thaw observation station from Jul. 14, 2008 to Dec. 31, 2010, in Wawangtan pasture (E100°28′/N38°03′, 3032.8m), Daban, A'rou. The experimental area with a flat and open terrain slightly sloping from southeast to northwest and hills and mountains stretching outwards is an ideal horizontal homogeneous underlying surface. The original observation items included the latitudinal wind speed Ux (m/s), the latitudinal wind speed Uy (m/s), the longitudinal wind speed Uz (m/s), the ultrasonic temperature Ts (°C), co2 consistency (mg/m^3), h2o consistency (g/m^3), air pressure (KPa) and the abnormal ultrasonic signal (diag_csat). The instrument height was 2.81m, the ultrasound direction was at an azimuth angle of 0°, the distance between Li7500 and CSAT3 was 30m and sampling frequency was 10HZ/s. The instrument mount was 3.15m, the ultrasound direction was at an azimuth angle of 86°, the distance between Li7500 and CSAT3 was 22cm and sampling frequency was 10HZ/s. The dataset was released at three levels: Level0 were the raw data acquired by instruments; Level1, including the sensible heat flux (Hs), the latent heat flux (LE_wpl), and co2 flux (Fc_wpl), were real-time eddy covariance output data and stored in .csv month by month; Level2 were processed data in a 30-minute cycle after outliers elimination, coordinates rotation, frequency response correction, WPL correction and initial quality control. The data were named as follows: station name +data level+data acquisition date. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide and Eddy Covariance Observation Manual.
Wang Weizhen, MA Mingguo, LI Xin, HUANG Guanghui, Zhang Zhihui, TAN Junlei
This data set contains the eddy related data of Zhangye National Climate Observatory from 2008 to 2009. The station is located in Zhangye, Gansu Province, with longitude and latitude of 100 ° 17 ′ e, 39 ° 05 ′ N and altitude of 1456m. For more information, see the documentation that came with the data.
Zhangye city meteorological bureau
Interaction "heihe region in field observation experiment (HEIFE)", is in the heihe river basin in hexi corridor in the middle of a 70 km by 90 km range of experimental zone for the center with water and heat exchange of a very comprehensive experiment, the interaction is the current international field the longest continuous observation on the land surface process experiment, has obtained the Eurasia hinterland typical in heihe river basin, gobi desert and oasis in arid regions different underlaying surface, such as solar radiation, atmospheric boundary layer meteorological data and oasis of meteorological data, and collect the conventional meteorological and hydrological data in the region,It has laid the foundation of observation experiment for theoretical study of land surface processes in arid areas. The heihe experimental database (HDB) (tao zehong and zuo hongchao, 1994a) comprehensively collected and systematically integrated the field observation data of heihe experiment.In the database, all observation data are divided into three categories according to the nature and purpose of observation: Category 1: normal observation period (FOP) data.It includes :(1) observation data of 5 micrometeorological stations and 5 automatic meteorological stations;(2) groundwater level data observed at four well stations;(3) distribution of blowing sand and dust and ozone observation data;(4) conventional observation data of 3 upper-air weather stations, 3 surface weather stations, 4 hydrology stations, some rain measuring stations and downhole water stations. The second category: enhanced observation period (IOP) data.It includes: observations of turbulence, tethered balloons, Sodar, Lidar, soil moisture content and composition during each strengthening period (PlOP, IOP-1, lop-2, IOP-3, IOP-4). The third category is special observation period data, which includes: biological meteorological observation (BOP), precipitation mechanism observation (iop-r) in arid areas, turbulence contrast observation (iop-c), supplementary observation data of deserts far from the oasis (iop-da) and observation data of sand sample experiment.Please refer to HEIFE database user manual for more detailed information (tao zehong et al., 1994b).
LI Xin, RAN Youhua
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