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198 6- 1 987年中国第三次南极考察中 ,对南极长城站空气、陆上和海滨的微生物作了考察。长城站野外空气中的微生物含量较低 ,海洋性微生物为 1 4 8.7CFU/ m3 ,陆源性微生物为 1 7.9CFU/ m3 ,表明野外空气相当洁净。室内空气微生物数比室外及野外均高得多 ,霉菌的检出率和含量都不高。微生物因人群活动和环境的不同而异。陆上的微生物含量次序是 :冰雪 <湖水 <原土等。海滨的微生物含量相当多 ,>1 0 3 CFU/ cm3 (或 g)。长城站的微生物组成有 1 1属以上 ,包括偶见的芽孢杆菌。温度试验结果表明 ,野外的大部分菌株适于低温生活。没有发现能在≥2 5℃的温度中存活者。低温是控制长城站微生物生态的一个重要因子。在长城站这类环境中 ,低温微生物对物质转化和循环发挥着持久的重要作用 相似文献
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利用南极长城站和中山站的降水、风、湿度、气压和云量等高质量的地面气象观测资料,对两站基本气候特征和变化趋势进行了分析。结果显示,长城站年降水量为503mm,年际变化呈减少趋势,变化速率为-27mm/10a。长城站和中山站年降水日数均呈下降趋势,变化速率分别为-2.9d/10a和-12.1d/10a。长城站和中山站年平均相对湿度分别为88%和58%。长城站年平均湿度总体上呈不明显下降趋势,中山站没有趋势。长城站盛行风向为西北风,中山站为偏东风,年平均风速分别为7.3m/s和7.1m/s。两站年平均风速呈减小趋势,变化速率分别为-0.09m/s/10a和-0.23m/s/10a。长城站平均大风日数为137d,记录的极大风速为37.2m/s。中山站平均大风日159d,记录的极大风速为50.3m/s。长城站和中山站年平均气压分别为990hPa和985hPa,变化速率分别为0.65hPa/10a和-0.80hPa/10a。其变化趋势相反,并与两站风速和大风日数及降水日数的变化倾向基本相同。长城站和中山站月平均云量分别为8.8和6.2,其差异显示了两站所处气候带的特点,即长城站地区全年阴天多、云量大,中山站则与此相反。 相似文献
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继在南极中山站建成我国南极首个永久性验潮站后,2012年1月在南极长城站又建成了我国南极第二个永久性验潮站。通过对长城站验潮站相关数据进行分析处理,得到了验潮基准系统的水准网平差结果和验潮仪零点标定结果,以及长城站附近海域海洋潮汐170个分潮的调和常数,并据此进行了潮汐预报,同时分析了长城站潮汐余水位的变化特征,探讨了利用附近的Antarctic Base Prat验潮站的余水位改正长城站潮汐预报的可行性,结果表明使用Antarctic Base Prat验潮站余水位改正长城站潮汐预报,可以显著提高长城站验潮站潮汐预报的精度,余水位改正后2014时段的潮汐预报中误差为±3.42 cm,明显好于改正前的预报中误差±10.43 cm。 相似文献
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198 9年 2月 1— 1 0日 ,对南极乔治王岛菲尔德斯半岛长城站附近的苔藓小气候进行了初步考察、观测和分析 ,并与长城站相应时间的常规记录进行了比较 ,初步揭示了南极地区苔藓小气候方面值得引起注意的某些特征。 相似文献
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中国西北地区季节性积雪的性质与结构 总被引：17，自引：2，他引：17
中国内陆地区积雪分布十分广泛。根据西北地区大陆性气候条件下形成的“干寒型”积雪的特征 ,对中国天山和阿尔泰山山区的季节性积雪进行了观测与分析。结果表明 ,该区最大积雪深度达 15 2cm(1997) ,积雪层一般由新雪 (或表层凝结霜 )、细粒雪、中粒雪、粗粒雪、松散深霜、聚合深霜层和薄融冻冰层组成。与“湿暖型”积雪相比 ,“干寒型”积雪的性质具有密度小 (新雪的最小密度为 0 .0 4 g/cm3 )、含水率少 (隆冬期 <1% )、温度梯度大(最大可达 - 0 .5 2℃ /cm)、深霜发育层厚等特点 ,并且变质作用以热量交换和雪层压力变质作用为主。据中国科学院天山积雪与雪崩研究站 (43°2 0N ,84°2 9E ,海拔 1776m)的观测资料 ,中国内陆干旱区冬季积雪期雪面太阳辐射通量以负平衡为主 ,新雪雪面反射率达 96 % ,短波辐射在干寒型积雪中的穿透厚度达 2 8cm。春季积雪消融期 ,深霜层厚度可占整个积雪层厚度的 80 %。随着气温的升高 ,雪粒间的键链首先融化 ,使积雪变得松散 ,内聚力、抗压、抗拉和抗剪强度降低 ,积雪含水率也随之增大 ,整个积雪层趋于接近 0℃的等温现象 ,因此 ,春季天山、阿尔泰山等山地全层性湿雪崩频繁发生 相似文献
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In order to analyze the differences between the two snow cover data, the snow cover data of 884 meteorological stations in China from 1951 to 2005 are counted. The data include days of visual snow observation, snow depth, and snow cover durations, which vary according to different definitions of snow cover days. Two series of data, as defined by "snow depth" and by "weather observation," are investigated here. Our results show that there is no apparent difference between them in east China and the Xinjiang region, but in northeast China and the Tibetan Plateau the "weather observation" data vary by more than 10 days and the "snow depth" data vary by 0.4 cm. Especially in the Tibetan Plateau, there are at least 15 more days of "weather observation" snow in most areas (sometimes more than 30 days). There is an obvious difference in the snow cover data due to bimodal snowfall data in the Tibetan Plateau, which has peak snowfalls from September to October and from April to May. At those times the temperature is too high for snow cover formation and only a few days have trace snow cover. Also, the characteristics and changing trends of snow cover are analyzed here based on the snow cover data of nine weather stations in the northeast region of the Tibetan Plateau, by the Mann-Kendall test. The results show significantly fewer days of snow cover and shorter snow durations as defined by "snow depth" compared to that as defined by "weather observation." Mann-Kendall tests of both series of snow cover durations show an abrupt change in 1987. 相似文献
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论述了长江之源各拉丹冬峰东坡的尕日曲流域冈加曲巴冰川和水晶矿冰川冰、雪、水样品中的ｐＨ值、总碱度、总硬度、矿化度，以及Ｋ＋，Ｎａ＋，Ｃａ（２＋），Ｍｇ（２＋）和Ｃｌ－，ＳｉＯ２等可溶性离子的含量，同时讨论了其水化学组成类型． 相似文献
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In this paper, a variation series of snow cover and seasonal freeze-thaw layer from 1965 to 2004 on the Tibetan Plateau has been established by using the observation data from meteorological stations. The sliding T-test, M-K test and B-G algorithm are used to verify abrupt changes of snow cover and seasonal freeze-thaw layer in the Tibetan plateau. The results show that the snow cover has not undergone an abrupt change, but the seasonal freeze-thaw layer obviously witnessed a rapid degradation in 1987, with the frozen soil depth being reduced by about 15 cm. It is also found that when there is less snow in the plateau region, precipitation in South China and Southwest China increases. But when the frozen soil is deep, precipitation in most of China apparently decreases. Both snow cover and seasonal freeze-thaw layer on the plateau can be used to predict the summer precipitation in China. However, if the impacts of snow cover and seasonal freeze-thaw layer are used at the same time, the predictability of summer precipitation can be significantly improved. The significant correlation zone of snow is located in middle reaches of the Yangtze River covering the Hexi Corridor and northeastern Inner Mongolia, and the seasonal freeze-thaw layer exists in Mt. Nanling, northern Shannxi and northwestern part of North China. The significant correlation zone of simultaneous impacts of snow cover and seasonal freeze-thaw layer is larger than that of either snow cover or seasonal freeze-thaw layer. There are three significant correlation zones extending from north to south: the north zone spreads from Mt. Daxinganling to the Hexi Corridor, crossing northern Mt. Taihang and northern Shannxi; the central zone covers middle and lower reaches of the Yangtze River; and the south zone extends from Mt. Wuyi to Yunnan and Guizhou Plateau through Mt. Nanling. 相似文献
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中国降雪气候学特征 总被引：18，自引：1，他引：17
利用逐日地面降雪观测资料,分析中国25oN以北范围内降雪量、降雪日数、雪带分布和各强度降雪的气候学特征,得到以下结论:①雪季长度与年降雪日数在东部呈纬向分布,大兴安岭北部最长(>210 d),长江以南最短(常年无雪或偶尔降雪);在西部青海省南部和西藏自治区北部最长(>300 d),滇、川、藏交界处及新疆自治区北部较长,南疆较短(<60 d)。年降雪量东南部最少,东北和西北北部较多(>30 mm),青海和西藏降雪量最多(>60 mm)。平均降雪强度江淮一带最大。②根据雪季降雪频次划分中国的雪带,东北大部、内蒙自治区东部、新疆北部、青藏高原大部、秦岭等地区为常年多雪带;长江以南的滇南、四川盆地、江浙沿海等地区为永久无雪带;其余地区为常年降雪带和偶尔降雪带。③不同区域各级降雪日数占总降雪日数的比例都是暴雪日数最少,大雪日数其次,小雪日数最多;但中雪降雪量占总降雪量的比例在东北北部、华北、西北、新疆、东南、青藏高原东部等区域仅高于小雪降雪量,而在黄-淮地区仅次于暴雪降雪量。④降雪年内分配在东北北部、西北、新疆、青藏高原东部等地区都呈双峰型,最多雪时节在早冬和晚冬、早春,隆冬时节并不是降雪最多时间,黄-淮和东南地区呈单峰型,东南地区峰值更陡。⑤总降雪日数和除暴雪外的各等级降雪日数与地理位置关系较明显,在中国东部主要随着纬度升高增加,在中国西部随海拔高度增加而增加;随着纬度升高,东部和西部的总降雪强度都减小,西部的小雪强度也减小。 相似文献
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Ground snow observation data from 1999 to 2008 were used to analyze the temporal and spatial distribution of snow density in
China. The monthly maximum density shifted from north to south during the period from October to the following January, and
then moved back from south to north during the period from January to April. The maximum snow density occurred at the border
between Hunan and Jiangxi provinces in January, where snow cover duration was short and varied remarkably. Snow density in
Northeast China and the Xinjiang Uygur Autonomous Region were also high and showed less variation when the snow cover duration
was long. Ground observation data from nine weather stations were selected to study changes of snow density in Northeast
and Northwest China. A phase of stable snow density occurred from the middle ten days of November to the following February;
non-stationary density phases were observed from October to the first ten days of November and from March to April. To further
investigate the effects of climatic factors on snow density, correlations between snow density and precipitation, air temperature,
snow depth and wind velocity for Northeast and Northwest China were analyzed. Correlation analysis showed that snow depth was
the primary influence on snow density. 相似文献
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Nelson冰帽位于南极洲边缘地区,周围海洋环绕。雪层剖面受融水干扰,但综合分析后仍能观察到季节变化的轮廓。结合雪层剖面和杂质成分及浓度分析,推知这里以局地海洋气团降水为主,冬季降水中杂质含量高于夏季,平均杂质含量远远高于内陆,人类活动等对环境的影响已在雪层中留下痕迹。但NO_3~-的沉积速率在整个西南极洲相差不显著,大气圈作用是控制NO_3~-沉积的主要因素。 相似文献
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The successful bid for the Beijing Winter Olympics has brought historic opportunities for the development of ice and snow tourism in China. An index system for the evaluation of tourist satisfaction in ice and snow tourism destinations was constructed from the target layer-factor layer-index layer approach in this paper. Taking tourists with ice and snow tourism experience as the research object, and integrating a questionnaire survey and the Importance-Performance Analysis (IPA) method, a total of 840 valid questionnaires were collected to assess the satisfaction of tourists in snow and ice tourism destinations, and the promotion model of tourist satisfaction in ice and snow tourism destinations was put forward. This process led to three main results. (1) Ice and snow tourists in China are characterized as young and better-educated, with college students aged 19 to 25 as the main consumer group. More than 70% of ice and snow tourists are pretty satisfied with the current development of ice and snow destinations in China, and are willing to participate again. (2) Other than “ice and snow souvenirs”, tourists’ perceptions of importance are all higher than the level of perceived satisfaction, and the importance values of the 13 indicators including “Scenic spot security” and “Diversity of ice and snow entertainment and sports” are especially high, showing that tourists have high expectations and demands of the destinations. However, the perceived satisfaction level of tourists for all indexes is generally low, mostly at the general satisfaction level, indicating that ice and snow tourism destinations have only partially met the demands of ice and snow tourists, and there is still much room for improvement. (3) After IPA analysis, five suggestions for improving the satisfaction of tourists in ice and snow tourism destinations were put forward, including diversification of the tourism business model, construction of tourism facilities, a market diversified cultivation model, a humanized mode of tourism service and a refined management model. The results of this study will help to enrich the theory of ice and snow tourist satisfaction and promote the high-quality development of China's ice and snow tourism in the post-Winter Olympics era. 相似文献
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积雪资源深刻影响着滑雪旅游的发展与布局,刻画中国积雪资源时空特征,识别旅游开发关键区,对中国冰雪旅游高质量发展具有重要意义。本文通过Mann-Kendall突变检验、热点分析、重要-感知实绩分析（IPA）等方法刻画中国1979—2020年积雪资源时空演变特征,构建资源稳定性-旅游开发适宜性指标体系,识别中国滑雪旅游开发关键区。结果表明：(1)中国积雪资源过去40年变化可划为3个阶段,1980—1995年（Ⅰ）积雪资源下降,1995—2010年（Ⅱ）增加,2010—2020年（Ⅲ）下降。在空间上,变化面积呈现Ⅰ-Ⅱ（33.2%）>Ⅱ-Ⅲ（31.1%）>Ⅰ-Ⅲ（29.3%）的特征;(2)中国积雪资源在月尺度上,1—3月（Ⅰ）积雪资源基本维持稳定,3—10月（Ⅱ）显著下降,10—12月（Ⅲ）恢复。在空间上,变化面积呈Ⅰ-Ⅲ（30.3%）>Ⅱ-Ⅲ（28.3%）>Ⅰ-Ⅱ（26.8%）的变化规律;(3)中国境内滑雪旅游开发极关键区面积占比为4.90%、关键区为11.69%、一般区为31.57%、不关键区为25.73%、极不关键区为26.11%,总体来看中国境内85%的区域不... 相似文献