前期土壤湿度、海表面温度对中国夏季极端气温的预测能力评估

基于中国587站日最高、最低气温观测资料、月平均的ERA_interim土壤湿度（Soil Moisture,SM）再分析资料及扩展重建的海表面温度（Sea Surface Temperature,SST）资料（ERSST）,对极端气温指数进行了定义,利用变形的典型相关分析和集合典型相关分析方法（Ensemble Canonical Correlation,ECC）,分析了1979-2009年我国夏季极端气温与前期（春、前冬）SM、SST间的线性联系,建立了中国夏季极端气温预测模型,并对独立样本检验的效果进行了评估。结果表明：1）与中国夏季极端气温联系密切的前期SST异常的空间分布为类PDO（Pacific Decadal Oscillation）型,前期土壤湿度异常的区域为华南、青藏高原、东北和西北地区。2）交叉检验结果表明基于前冬预测因子的极端气温预测模型技巧高于春季,基于SM的极端气温预测模型技巧高于SST。3）独立样本检验表明基于前期SM、SST的ECC模型对中国东部夏季极端气温有一定的预测能力。因此,可以在夏季极端气温的预测业务中考虑前期SM、SST的影响。     

2022年夏季中国高温干旱气候特征及成因探讨

2022年夏季,中国中东部发生了极端高温干旱气候异常,给经济、农业、人民生活造成了严重影响。本文回顾了此次高温干旱气候异常的时空特征,分析了其主要成因。2022年夏季,中国中东部区域平均的极端高温频次、日最高温度平均值、高温日数等指标均达到了1979年以来的最大值,区域平均降水则达到了1979年以来的最低值。此次气候异常主要是由于夏季中国中东部受强大的高压系统控制,与偏强的西太副高、中纬度的西风带扰动以及热带海温的影响有关。此外,本文探讨了全球增暖趋势对极端高温事件增多的影响,以及未来中国地区高温和干旱事件的可能变化。     

中国大陆密度和地震波速扰动异常的年龄属性研究

大陆动力学研究需要物质随空间和时间的变化的信息.三维密度和地震波速度扰动图像反映岩石圈物质的空间分布,要和大地构造学中的时间尺度信息综合起来,才能恢复动力学作用的过程.本文通过对比不同构造期的构造图和地壳不同深度的地球物理性质图像,研究中国大陆密度以及地震波速度扰动和构造事件的相关度.研究表明,岩石圈地幔的密度和波速扰...     

GPS变形监测动态数据处理中卡尔曼滤波的应用

介绍了卡尔曼滤波的基本原理,针对常规GPS变形监测数据处理中存在着不连续、非实时的缺点,结合卡尔曼滤波的特点,运用三峡实测数据对GPS变形监测动态数据处理中卡尔曼滤波的应用进行研究。并采用各点点位位移速度图对所建立的函数模型进行验证,同时对状态方程的建立及初始值的选取进行分析总结。     

Adjustment time of the first baroclinic Rossby wave in the global oceans

1Introduction Planetary waves involve the main processes bywhich perturbation signal in one part of the ocean istransferred to another part.In the1970s,mostof theprevious theoretical studies focus on the local Ekmanpumping and the nondispersive long baroc…     

马氏珠母贝生长性状的相关分析

对马氏珠母贝(Pinctadamartensi)不同生长时期的壳长、壳高、壳宽和活体质量进行了一年多的跟踪测量。分析表明,在不同生长时期,其4个性状的两两间的相关系数均达到极显著水平(P<0.01),但其相关系数大小排列顺序存在差异,8次测量的平均相关系数大小依次为壳高-壳长>壳宽-体质量>壳高-体质量>壳长-体质量>壳长-壳宽>壳高-壳宽。在不同生长时期,活体质量对壳高、壳宽的偏回归系数均极显著(P<0.01),而对壳长的偏回归系数在第1,3,7,15个月时不显著(P>0.05)。该研究的结果可为珍珠贝的选育种的重要目标性状的确定提供理论指导。     

全球寒武系四统划分框架正式确立

国际地层委员会最近陆续发布了2005和2006年版《国际地层表》(http://www.stratigraphy.org/cheu.pdf),这两张新表较以往各版最为突出的变动是将寒武系分为四个统和十个阶,不再采用国际地学界沿用了近一百七十年的上、中、下3统的传统划分方法。这一改写是全球地层学的重大事件     

Trends in stream and river temperature

Information on past and likely future trends in water temperature from different parts of the world is collated. The potential causes of trends in the thermal regimes of streams and rivers are many, but the existing database of water temperature information is inadequate to provide a global perspective on changes during the recent, let alone the more remote, past. Data from Europe suggest that warming of up to ca. 1°C in mean river temperatures has occurred during the 20th century, but that this trend has not been continuous, is distorted by extreme hydrological events, is not correlated with simple hydrometeorological factors and has been influenced by a variety of human activities. Predictive studies indicate that an accelerated rise in stream and river temperatures will occur during the next century as a consequence of global warming. However, forecasts must be tentative because future climatic conditions are uncertain and interactions between climate, hydrological and vegetation changes are complex.     

拉萨河冬季径流对气候变暖和冻土退化的响应

20世纪90年代以来,拉萨河流域的气温经历了10年升高0.54 ^oC的气候变暖,这期间以秋冬季升温为主。在近40年 (1963~2004年) 气候和28年 (1976~2004年) 月径流数据的基础上,研究了具有多年冻土的高海拔拉萨河流域的冻土和水文响应。结果表明,冬季径流对11~2月气温升高具有显著响应,在12~2月份增加了16%,其中2月份增加22%。水热相关分析表明,10~11月地表温度升高0.8~0.9 ^oC导致冬季河流水量增多,介于0.9~1.5m深度的季节冻土深度和温度变化导致了径流量变化的响应。20世纪90年代的气候变暖使得多年冻土区的季节冻土深度萎缩了大约14cm,冻土区的冬季径流水文响应比气温更快、更显著。但冻土积雪观测的不足使冬季水文变化具有不确定性。     

Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios： A Case Study of Swedish Precipitation

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.