Introduction to Qingtu Lake

What is/are Qingtu Lake?

Qingtu Lake - In this study, long time series normalized difference vegetation index (NDVI) was used to extract the restored vegetation area in Qingtu Lake area, a terminal lake in inland Shiyang River basin, northwestern China. ^[1] The theory is validated by the data obtained at Kansas and also at Qingtu Lake Observation Array in Northern China for a variety of heat flux conditions. ^[2] Here we provide a high frequency observation in the Qingtu Lake Observation Array (QLOA), China. ^[3] Qingtu Lake is located between Tengger Desert and Badain Jilin Desert, Gansu Province, Northwest China. ^[4] The quadrant and octant analysis methods are used to investigate the characteristic of the atmospheric surface layer (ASL) turbulent flow based on the field observation data obtained from the Qingtu Lake Observation Array (QLOA). ^[5] After ecological water conveyance, the ion concentration of water in Qingtu Lake was higher overall, and ion concentration of water in the unstable catchment was higher than that of the stable catchment. ^[6] In this study, Qingtu Lake, the terminal lake of Shiyang River, was selected to analyze the ecological effects of water transport by means of remote sensing interpretations and current year field investigations. ^[7] Based on the field observation data in the near-neutral atmospheric surface layer (ASL) at the Qingtu Lake Observation Array, a new experimental data processing of the second-order statistic distribution of the high Reynolds number wall turbulence was presented which considered the influence of the intense thermal convection events (ITCEs). ^[8] 7 m above the ground during a dust storm are measured at Qingtu Lake Observation Array site. ^[9] Long-term measurements were performed at the Qingtu Lake Observation Array site to obtain high-Reynolds-number atmospheric surface layer flow data ( $Re_{\unicode[STIX]{x1D70F}}\sim O(10^{6})$ ). ^[10]

atmospheric surface layer

The quadrant and octant analysis methods are used to investigate the characteristic of the atmospheric surface layer (ASL) turbulent flow based on the field observation data obtained from the Qingtu Lake Observation Array (QLOA). ^[1] Based on the field observation data in the near-neutral atmospheric surface layer (ASL) at the Qingtu Lake Observation Array, a new experimental data processing of the second-order statistic distribution of the high Reynolds number wall turbulence was presented which considered the influence of the intense thermal convection events (ITCEs). ^[2] Long-term measurements were performed at the Qingtu Lake Observation Array site to obtain high-Reynolds-number atmospheric surface layer flow data ( $Re_{\unicode[STIX]{x1D70F}}\sim O(10^{6})$ ). ^[3]

qingtu lake observation

The theory is validated by the data obtained at Kansas and also at Qingtu Lake Observation Array in Northern China for a variety of heat flux conditions. ^[1] Here we provide a high frequency observation in the Qingtu Lake Observation Array (QLOA), China. ^[2] The quadrant and octant analysis methods are used to investigate the characteristic of the atmospheric surface layer (ASL) turbulent flow based on the field observation data obtained from the Qingtu Lake Observation Array (QLOA). ^[3] Based on the field observation data in the near-neutral atmospheric surface layer (ASL) at the Qingtu Lake Observation Array, a new experimental data processing of the second-order statistic distribution of the high Reynolds number wall turbulence was presented which considered the influence of the intense thermal convection events (ITCEs). ^[4] 7 m above the ground during a dust storm are measured at Qingtu Lake Observation Array site. ^[5] Long-term measurements were performed at the Qingtu Lake Observation Array site to obtain high-Reynolds-number atmospheric surface layer flow data ( $Re_{\unicode[STIX]{x1D70F}}\sim O(10^{6})$ ). ^[6]