2013年海洋和大气环流异常及对中国气候的影响     

司东  袁媛  崔童  孙冷  王东阡  柳艳菊  郭艳君  王遵娅 《气象》2014,40(4):494-501

本文对2013年海洋和大气环流异常特征进行分析,讨论这些异常特征对中国气温和降水的主要影响。结果表明：2012/2013年冬季,北极涛动持续维持负位相,500 hPa位势高度场上,欧亚大陆中高纬环流呈“两槽一脊”的环流形势,乌拉尔山的高压脊持续偏强,而东亚槽也异常偏强,导致全国平均气温较常年同期偏低。季内,西伯利亚高压强度变化显著,与之相对应,我国气温季内阶段性变化大,前冬冷、后冬暖。进一步研究表明,前秋北极海冰的大幅偏少是造成东亚冬季风偏强的重要原因。2013年冬季至夏季,赤道中东太平洋海温异常偏低而海洋性大陆至西太平洋海温异常偏高,受此影响,夏季西太平洋副热带高压位置明显偏北,导致我国北方夏季多雨。与此同时,受西太平洋副热带高压下沉气流的控制,我国南方大部高温持续。2013年南海夏季风爆发偏早两候,结束偏晚4候,强度偏弱。  相似文献   

WRF_Lake湖气模式对我国太湖的湖温模拟应用评估   总被引：1，自引：0，他引：1  

古红萍  沈学顺  金继明  赵林  肖薇  王咏薇 《气象》2014,40(2):166-173

文章把一维热扩散湖模式成功地耦合到中尺度天气研究和预报模式WRF3.2中,建立了湖气耦合模式。并用太湖区梅梁湾获得的2010年8月11—28日的观测资料对该耦合模式模拟湖温的能力进行了初步评估。设计了3组方案进行对照试验,分别为:(1)没有加入湖模块的WRF模式试验(WRF);(2)没有对参数进行优化的原始耦合模式试验(WRF_Lake_Old);(3)对3个参数进行优化后的耦合模式试验(WRF_Lake_New)。结果表明耦合了湖泊模块并且参数优化后的湖气耦合模式(WRF_Lake_New)比没有包含湖面方案的WRF模式对太湖水温的模拟能力有了很大的改进。WRF_Lake_New能够合理地模拟出太湖梅梁湾上湖表温度的日变化,模拟的湖表温度误差范围平均在±1℃左右,模拟的空气温度平均误差范围在±0.5℃以内,模拟的感、潜热通量也与观测更为接近。该耦合模式在太湖的初步评估结果表明,该湖气耦合模式为下一步研究湖泊过程和湖气相互作用提供了重要的工具。  相似文献   

基于地基微波辐射计资料对咸宁两次冰雹天气的观测分析   总被引：3，自引：2，他引：1  

黄治勇  徐桂荣  王晓芳  唐永兰 《气象》2014,40(2):216-222

利用地基微波辐射计观测资料,对两次冰雹过程进行观测分析。结果表明:中低层暖湿气流输送、中层干冷空气侵入,在0~10 km形成"上干、下湿"2层垂直分布结构。低层的感热和潜热随上升气流向上输送,2~3 km层明显增温,0、-5和-20℃层略微上升。同时,低层水汽也随上升气流向上输送,降雹前大气液态水总含量(ILW,下同)和大气水汽总含量(IWV,下同)及过冷水含量快速增长。水汽经过冷层后,冰晶增多增大。当冰晶增大落入0℃以上区融化层时,冰晶融化导致液态水增加,一部分形成冰雹或地面降水,导致降雹之后ILW、IWV及0℃以下液态水含量减小。上述结论对冰雹的预警有一定指示意义。  相似文献   

江苏—南黄海地区M≥6强震有序网络结构及其预测研究   总被引：2，自引：1，他引：1  

门可佩 《南京气象学院学报》2014,6(3):268-274

基于TIGGE（THORPEX Interactive Grand Global Ensemble,全球交互式大集合）资料中欧洲中期天气预报中心（European Centre for Medium-Range Weather,ECMWF）、日本气象厅（Japan Meteorological Agency,JMA）、美国国家环境预报中心（National Centers for Environmental Prediction,NCEP）和英国气象局（United Kingdom Met Office,UKMO）4个中心的北半球地面2m气温集合平均预报资料,利用插值技术与回归分析,并引入了消除偏差集合平均（bias-removed ensemble mean,BREM）和多模式超级集合（superensemble,SUP）方法进行统计降尺度预报研究.结果表明,在2007年夏季3个月中,4个单中心的降尺度预报明显地改善了预报效果.引入SUP和BREM两种集成预报方法后,预报误差得到进一步减小.对比综合表现最好的单中心ECMWF的预报,1～7d的降尺度预报误差改进率均达20％以上.研究还发现,引入SUP方法的降尺度预报效果优于引入BREM方法的降尺度预报,利用双线性插值方法在上述两方案中的预报效果优于其他3种插值方法.  相似文献   

2014年7月大气环流和天气分析   总被引：5，自引：2，他引：3  

唐健  代刊 《气象》2014,40(10):1286-1292

提2014年7月环流特征如下：北半球高纬地区为单一极涡,中高纬地区呈5波型分布,巴尔喀什湖附近低槽和东亚大槽强度均较常年偏强;西北太平洋副热带高压带呈东西带状分布,强度与常年同期相当。7月全国平均降水量115．0 mm,较常年同期（120．6 mm）偏少4．6％;全国平均气温为22．3℃,较常年同期（21．9℃）偏高0．4℃。月内共出现8次强降水过程,多站出现极端日降水量。7月共有5个热带气旋（风力8级以上）在西北太平洋和南海活动,生成个数较常年偏多,并有“威马逊”、“麦德姆”2个热带气旋登陆。华南、江南等地出现持续高温天气,全国87个气象观测站发生极端高温事件,74站发生极端日降水量事件。  相似文献   

2013年夏季我国南方区域性高温天气的极端性分析   总被引：16，自引：2，他引：14  

唐恬  金荣花  彭相瑜  牛若芸 《气象》2014,40(10):1207-1215

提利用1960-2013年我国南方10省（市）733个站点的日最高、最低气温和日平均气温资料,对2013年夏季我国南方高温天气的极端性进行了系统的分析。分析结果显示：2013年夏季我国南方高温天气具有显著的群发性特征,覆盖了长江中下游以及重庆等八个省、两个直辖市;也具有以高温天气过程重现构成的持续性特征,主要经历了4次高温天气过程,其中,7月22日至8月21日的第三次高温天气过程,强度最强、范围最广。重点围绕区域性高温在历史上的极端性做进一步分析,结果表明：所研究高温区域的夏季平均气温、平均最高气温、平均最低气温均破历史纪录,为近50年新高;平均高温日数和强度也超过了历年平均高温日数和强度的极值,属历史罕见;高温日数和高温强度的高值区域范围比历年向北扩展,且高值中心值超过历史最高纪录,极端性突出;2013年极端高温事件的发生次数突破了历史纪录,其中8月的极端高温事件十分突出。  相似文献   

气象要素对太阳能电池板温度的影响   总被引：1，自引：1，他引：0       下载免费PDF全文

潘进军  申彦波  边泽强  王香云 《应用气象学报》2014,25(2):150-157

温度升高会引起光伏电池发电效率下降,电池板温度是确定温度折减系数的必要条件,目前我国尚没有充足的外场实测电池板温度数据。该文基于北京南郊太阳能试验站2010年全年逐时电池板温度、气温、地表温度、斜面和水平辐照度实测数据,分析了电池板温度随时间的变化及其与各气象要素的关系。结果表明:电池板温度与气温和斜面辐照度的综合相关或与地表温度的线性相关最好,但实测数据不易获得;电池板温度与气温的线性相关较好,数据较易获得且质量有保证,从现实可行性考虑,是推算电池板温度最实用的相关方程;电池板温度与气温和水平辐照度的综合相关可以作为辅助方程,用于推算气温较高情况下的电池板温度。基于2010年电池板温度实测数据和加权计算的方法,得到北京地区年平均光伏发电温度折减系数约为2%,最高可达到13.3%。  相似文献   

Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.  相似文献   

A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

In recent years, it has been widely agreed that spatial features derived from textural, structural, and object-based methods are important information sources to complement spectral properties for accurate urban classification of high-resolution imagery. However, the spatial features always refer to a series of parameters, such as scales, directions, and statistical measures, leading to high-dimensional feature space. The high-dimensional space is almost impractical to deal with considering the huge storage and computational cost while processing high-resolution images. To this aim, we propose a novel multi-index learning (MIL) method, where a set of low-dimensional information indices is used to represent the complex geospatial scenes in high-resolution images. Specifically, two categories of indices are proposed in the study: (1) Primitive indices (PI): High-resolution urban scenes are represented using a group of primitives (e.g., building/shadow/vegetation) that are calculated automatically and rapidly; (2) Variation indices (VI): A couple of spectral and spatial variation indices are proposed based on the 3D wavelet transformation in order to describe the local variation in the joint spectral-spatial domains. In this way, urban landscapes can be decomposed into a set of low-dimensional and semantic indices replacing the high-dimensional but low-level features (e.g., textures). The information indices are then learned via the multi-kernel support vector machines. The proposed MIL method is evaluated using various high-resolution images including GeoEye-1, QuickBird, WorldView-2, and ZY-3, as well as an elaborate comparison to the state-of-the-art image classification algorithms such as object-based analysis, and spectral-spatial approaches based on textural and morphological features. It is revealed that the MIL method is able to achieve promising results with a low-dimensional feature space, and, provide a practical strategy for processing large-scale high-resolution images.  相似文献   

Spectral monitoring of moorland plant phenology to identify a temporal window for hyperspectral remote sensing of peatland     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

Recognising the importance of the timing of image acquisition on the spectral response in remote sensing of vegetated ecosystems is essential. This study used full wavelength, 350–2500 nm, field spectroscopy to establish a spectral library of phenological change for key moorland species, and to investigate suitable temporal windows for monitoring upland peatland systems. Spectral responses over two consecutive growing seasons were recorded at single species plots for key moorland species and species sown to restore eroding peat. This was related to phenological change using narrowband vegetation indices (Red Edge Position, Photochemical Reflectance Index, Plant Senescence Reflection Index and Cellulose Absorption Index); that capture green-up and senescence related changes in absorption features in the visible to near infrared and the shortwave infrared. The selection of indices was confirmed by identifying the regions of maximum variation in the captured reflectance across the full spectrum. The indices show change in the degree of variation between species occurring from April to September, measured for plant functional types. A discriminant function analysis between indices and plant functional types determines how well each index was able to differentiate between the plant functional groups for each month. It identifies April and July as the two months where the species are most separable. What is presented here is not one single recommendation for the optimal temporal window for operational monitoring, but a fuller understanding of how the spectral response changes with the phenological cycle, including recommendations for what indices are important throughout the year.  相似文献