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| 1 | Digital Extraction of Altitudinal Belt Spectra in the West Kunlun Mountains Using SPOT-VGT NDVI and SRTM DEM显示文摘In this paper,a digital identification method for the extraction of altitudinal belt spectra of montane natural belts is presented.Acquiring the sequential spectra of digital altitudinal belts in mountains at an acceptable temporal frequency and over a large area requires extensive time and work if traditional methods of field investigation are to be used.Such being the case,often the altitudinal belts of a whole mountain or the belts at a regional scale are represented by single points.However,single points obviously cannot accurately reflect the spatial variety of altitudinal belts.In this context,a digital method was developed to extract the spectra of altitudinal belts from remote sensing data and SRTM DEM in the West Kunlun Mountains.By means of the 1km resolution SPOT-4 vegetation 10-day composite NDVI,the horizontal distribution of altitudinal belts were extracted through supervised classification,with a total classification accuracy of 72.23%.Then,a way of twice-scan was used to realize the automatic transition of horizontal maps to vertical belts.The classification results of remote-sensing data could thus be transformed automatically to sequential spectra of digital altitudinal belts.The upper and lower lines of the altitudinal belts were then extracted by vertical scanning of the belts.Relationships between the altitudinal belts based on the montane natural zones concerning vegetation types and the geomorphological altitudinal belts were also discussed.As a tentative method,the digital extraction method presented here is effective at digitally identifying altitudinal belts,and could be helpful in rapid information extraction over large-scale areas. | XIAO Fei LING Feng DU Yun XUE Huaiping WU Shengjun | 2010 | Journal of Mountain Science2010，7，2： | 8 |
| 2 | The Tibetan Plateau Surface–Atmosphere Coupling System and Its Weather and Climate Effects: The Third Tibetan Plateau Atmospheric Science Experiment显示文摘The Tibetan Plateau(TP) is a key area affecting forecasts of weather and climate in China and occurrences of extreme weather and climate events over the world. The China Meteorological Administration, the National Natural Science Foundation of China, and the Chinese Academy of Sciences jointly initiated the Third Tibetan Plateau Atmospheric Science Experiment(TIPEX-Ⅲ) in 2013, with an 8–10-yr implementation plan. Since its preliminary field measurements conducted in 2013, routine automatic sounding systems have been deployed at Shiquanhe, Gaize, and Shenzha stations in western TP, where no routine sounding observations were available previously. The observational networks for soil temperature and soil moisture in the central and western TP have also been established. Meanwhile, the plateau-scale and regional-scale boundary layer observations, cloud–precipitation microphysical observations with multiple radars and aircraft campaigns, and tropospheric–stratospheric air composition observations at multiple sites, were performed. The results so far show that the turbulent heat exchange coefficient and sensible heat flux are remarkably lower than the earlier estimations at grassland, meadow, and bare soil surfaces of the central and western TP. Climatologically, cumulus clouds over the main body of the TP might develop locally instead of originating from the cumulus clouds that propagate northward from South Asia. The TIPEX-Ⅲ observations up to now also reveal diurnal variations, macro-and microphysical characteristics, and water-phase transition mechanisms, of cumulus clouds at Naqu station. Moreover, TIPEX-Ⅲ related studies have proposed a maintenance mechanism responsible for the Asian 'atmospheric water tower' and demonstrated the effects of the TP heating anomalies on African, Asian, and North American climates. Additionally, numerical modeling studies show that the Γ distribution of raindrop size is more suitable for depicting the TP raindrop characteristics compared to the M–P distribution, the overestimation of sensible heat flux can be reduced via modifying the heat transfer parameterization over the TP, and considering climatic signals in some key areas of the TP can improve the skill for rainfall forecast in the central and eastern parts of China. Furthermore, the TIPEX-Ⅲ has been promoting the technology in processing surface observations, soundings, and radar observations, improving the quality of satellite retrieved soil moisture and atmospheric water vapor content products as well as high-resolution gauge–radar–satellite merged rainfall products, and facilitating the meteorological monitoring, forecasting, and data sharing operations. | Ping ZHAO Yueqing LI Xueliang GUO Xiangde XU Yimin LIU Shihao TANG Wenming XIAO Chunxiang SHI Yaoming MA Xing YU Huizhi LIU La JIA Yun CHEN Yanju LIU Jian LI Dabiao LUO Yunchang CAO Xiangdong ZHENG Junming CHEN An XIAO Fang YUAN Donghui CHEN Yang PANG Zhiqun HU Shengjun ZHANG Lixin DONG Juyang HU Shuai HAN Xiuji ZHOU | 2019 | Journal of Meteorological Research2019，33，3： | 4 |
| 3 | Mechanism of sea ice formation based on comprehensive observation data in Liaodong Bay, China显示文摘Sea ice disaster is one of the principal natural hazards that affect some coastal areas of China,and the formation of ice cover in a wave field has important characteristics.However,analysis of the mechanism in which waves affect the thermodynamic process of sea ice is lacking,and the influence of waves is not taken into consideration in numerical models of sea ice,largely because of a lack of simultaneous observations of waves and sea ice.Using observational data of the sea ice cycle in the coastal waters of Liaodong Bay(China),we analyzed the characteristics of hydrology,meteorology,and sea ice thickness during the formation of sea ice,and explored the changes in the interrelationships among heat fluxes,waves,and sea ice under actual sea conditions.The results could provide a decision-making support as a reference to the establishment and improvement of China's early waming system to sea ice disasters,and the protection of ice drilling operations and production platform safety. | SHI Yongfang YANG Yongzeng TENG Yong SUN Meng YUN Shengjun | 2019 | Journal of Oceanology and Limnology2019，37，6： | 1 |
| 4 | Initial 24-h perfusion index of ICU admission is associated with acutekidney injury in perioperative critically ill patients: A retrospective cohortanalysis显示文摘Background:The relationship between perfusion index(PI)and organ dysfunction in patients in the intensivecare unit(ICU)is not clear.This study aimed to explore the relationship between PI and renal function in theperioperative critical care setting and evaluate the predictive efficiency of PI on patients with acute kidney injury(AKI)in the ICU.Methods:This retrospective analysis involved 12,979 patients who had undergone an operation and were admitted to the ICU in Peking Union Medical College Hospital from January 2014 to December 2019.The distributionof average PI in the first 24 h after ICU admission and its correlation with AKI was calculated by Cox regression.Receiver operating characteristic(ROC)curves were generated to compare the ability of PI,mean arterial pressure(MAP),creatinine,blood urea nitrogen(BUN),and central venous pressure(CVP)to discriminate AKI in thefirst 48 h in all perioperative critically ill patients.Results:Average PI in the first 24 h served as an independent protective factor of AKI(Odds ratio[OR]=0.786,95%confidence interval[CI]:0.704–0.873,P<0.0001).With a decrease in PI by one unit,the incidence of AKIincreased 1.74 times.Among the variables explored for the prediction of AKI(PI,MAP,creatine,BUN,and CVP),PI yielded the highest area under the ROC curve,with a sensitivity of 64.34%and specificity of 70.14%.A cut-offvalue of PI≤2.12 could be used to predict AKI according to the Youden index.Moreover,patients in the low PIgroup(PI≤2.12)exhibited a marked creatine elevation at 24–48 h with a slower decrease compared with thosein the high PI group(PI>2.12).Conclusions:As a local blood flow indicator,the initial 24-h average PI for perioperative critically ill patients canpredict AKI during their first 120 h in the ICU. | Shengjun Liu Longxiang Su Changjing Zhuge Huaiwu He Yun Long | 2023 | Journal of Intensive Medicine2023，3，3： | 0 |
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