基于大数据分析下的气候模型     

张宸豪  冯曦  冯卫兵  刘涛  丁坤 《海洋科学》2020,44(10):1-11

为研究全球变暖与极寒天气间的关系，对加拿大13个省代表性测站10年的观测数据进行时空变化趋势分析，采用经验正交函数（EOF）寻找海洋表面温度历史数据的变化规律。另外利用BP神经网络建立了年平均温度、日降水量与地球吸热、散热、海表面温度、当地纬度间的关系，预测未来25年气候的变化，并建立了“极寒天气”与气候变化的关系模型。研究表明：高纬度地区温度、降水量普遍较低，同经度地区的温度差异较小且降水量变化不大；加拿大地区温度呈周期性变化，符合北半球的季节变化特征；北大西洋的东部与其他海洋的温度是反相关的，西太平洋南北回归线附近的海洋表面温度升高；“极寒天气”出现频率与气候变化有一定关系，局地极寒现象与全球变暖的大趋势并不矛盾。本研究为人们认识和理解“全球变暖”提供了一个新的思路。  相似文献   

青岛地区海雾分布及大气边界层条件分析     

任兆鹏  李昊倩  鞠霞  王国清 《海洋科学》2020,44(5):96-106

青岛地区海雾多发,观测表明海雾对沿海地区影响范围不尽相同,特别是海雾影响内陆的机理尚缺乏研究。本文利用观测资料及数值模式统计了青岛地区4月-7月海雾分布特征,并对不同影响范围海雾典型个例进行对比分析,结果表明:海雾发生日数自沿海向内陆递减。胶州湾沿岸雾日数比黄海沿岸明显减少,胶州湾东北部的雾日数要少于胶州湾西北部。海雾多发生于高空形势稳定,低层偏南流场的天气条件下。大气边界层内逆温层的的范围大致影响着海雾的分布。只影响沿海的海雾,地面为偏南风,风速在3~8 m/s之间,内陆风力减弱不明显。500 m以下大气边界层内风速切变大。湍流作用使海雾向内陆推进过程中倾斜抬升为低云,地面雾区减弱。能够影响内陆地区的海雾,多出现在地面风力较弱的情况之下,大部分在1~3 m/s之间。500 m以下大气边界层内风速切变小,大气边界层内湍流强度不强,使沿海到内陆的逆温层能够始终维持,沿海海雾在弱南风影响下延伸影响内陆地区。  相似文献   

砾石单元法与SPH耦合模型在数值波浪水槽中的应用研究     

李彦卿  别社安  李大鸣  王鑫 《海洋科学》2020,44(9):100-111

为研究以流体粒子描述波浪运动，以固体单元描述砾石运动的两相介质大变形运动，在港口、海岸工程科学研究中具有重要意义。本文提出砾石单元法（GEM），介绍了光滑粒子动力学方法（SPH）和GEM的基本原理，阐述了GEM与离散单元法（DEM）的异同之处，说明了采用SPH方法与GEM构建波浪砾石耦合运动数学模型的方法和过程。应用SPH方法建立数值波浪水槽，用GEM模拟波浪作用下堆积砾石的滚落、坍塌变形，构建了SPH方法与GEM耦合数学模型。模拟了水槽造波和波浪生成过程和波浪作用下砾石的滚落、坍塌变形，并与物理模型试验成果进行了比较，结果基本吻合。本文提出的GEM法具有模拟单相堆积砾石运动和堆积砾石与流体粒子耦合多相介质运动的功能，是对DEM法的补充和改善。本文提出的堆积力学球概念和拟序排列求解方法是砾石单元法的重要组成部分。  相似文献   

基于机器学习的海洋环境预报订正方法研究     

许立兵  王安喜  汪纯阳  陈悦  陈昱文  周峥  陈幸荣  邢建勇  刘克威  黄小猛 《海洋通报》2020,39(6):695-704

结合中尺度数值模式 WRF 预报数据和 ERA5 再分析资料，利用机器学习方法对 WRF 预报场的风场、温度、气压进行预报订正。采用 ERA5 作为真值，与原始 WRF 预报相比，利用随机森林模型可以将预报结果整体均方根误差降低 44%以 上，利用深度神经网络模型可以将预报结果整体均方根误差降低 34%以上。通过随机森林模型实验得到不同输入特征对预报要素的影响程度，分析了关键的预报订正因子。  相似文献   

碟形越浪式波能发电装置的三维数值模拟     

刘大方  刘臻  张国梁 《海岸工程》2020,39(4):237-245

基于计算流体力学软件的三维数值模拟技术,分析了碟形越浪式波能发电装置的越浪性能,通过构建基于水气两相VOF(Volume of Fluid)模型的三维数值波浪水槽对该装置进行三维数值模拟研究,数值计算结果与物理试验结果相互对比验证较为吻合,验证了所构建的三维数值波浪水槽的可靠性,通过考察装置的坡度、导流叶片个数、干舷高度对越浪性能的影响确定装置的最优结构参数。结果表明,在装置的斜坡面边缘增加回流板可减少波浪的反射,提高装置的越浪性能。在数值模拟中将装置的斜坡面边缘处安装回流板对碟形越浪式波能发电装置参数进行优化,通过分析回流板的长度对装置越浪性能的影响来探索最优回流板长度。  相似文献   

一种利用浮标站资料改进海浪模式有效波高预报的方法     

龚 《海洋预报》2020,37(1):50-54

基于浮标站海浪历史数据,利用回归分析方法建立了海浪数值模式有效波高预报产品的一元二次回归方程订正统计模型。通过2017年7月1日-2018年10月10日期间业务试运行结果发现:订正方程能有效改善有效波高数值预报产品的预报精度,且预报时效越短订正效果越显著。其中,第6~11 h预报时效内的订正前后平均绝对误差值减小0.17~0. 241 m,第6~18 h预报时效内订正前后均方根误差减小幅度为0.103~0. 28 m。这说明应用订正统计模型对海浪模式输出产品进行订正,也是改进海浪模式预报准确率的一种有效途径。  相似文献   

不同天气现象下毕节高温特征及预报回归检验分析          下载免费PDF全文

吴姗  姚浪  刘健平  帅龙  聂祥 《中低纬山地气象》2022,46(1):68-72

利用毕节2010-2019年观测资料,分析不同天气现象下日最高气温特征,建立高温模型,并对近5 a 24 h高温进行检验,得出如下结论:(1)毕节高温日变化在夏季最稳定,春季波动最大。气温日较差晴天最大,阴天最小,多云时略大于阴间多云。(2)毕节8~10成云出现频率高达65.7%,夏季晴天频率波动大,春、夏季多云频率较高,且按天气现象分类统计月平均高温时,其峰值均出现在7月。(3) 24 h高温预报准确率月、季变化特征明显,夏季准确率最高,较最低的冬季高出21.4%,在区别天气现象的情况下,阴雨天时预报准确率最高,多云时最低,其中12月多云时最低为25%。(4)回归模型分析发现不同季节同种天气现象24 h高温预报影响因子权重差异明显,日照时数和平均本站气压对模型影响程度较高。不同季节晴天影响因子差异最大,拟合效果最好时段在夏季,平均估计误差为1.2℃,估计误差最大在冬季,平均估计误差为1.7℃。  相似文献   

Contributions of Fuqing ZHANG to Predictability,Data Assimilation,and Dynamics of High Impact Weather: A Tribute     

Zhiyong MENG  Eugene E.CLOTHIAUX 《大气科学进展》2022,39(5):676-683

This article reviews Fuqing ZHANG’s contributions to mesoscale atmospheric science,from research to mentoring to academic service,over his 20-year career.His fundamental scientific contributions on predictability,data assimilation,and dynamics of high impact weather,especially gravity waves and tropical cyclones,are highlighted.His extremely generous efforts to efficiently transmit to the community new scientific knowledge and ideas through mentoring,interacting,workshop organizing,and reviewing are summarized.Special appreciation is given to his tremendous contributions to the development of mesoscale meteorology in China and the education of Chinese graduate students and young scientists.  相似文献   

Identification of Convective and Stratiform Clouds Based on the Improved DBSCAN Clustering Algorithm     

Yuanyuan ZUO  Zhiqun HU  Shujie YUAN  Jiafeng ZHENG  Xiaoyan YIN  Boyong LI 《大气科学进展》2022,39(12):2203-2212

A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. To identify convective and stratiform clouds in different developmental phases, two-dimensional (2D) and three-dimensional (3D) models are proposed by applying reflectivity factors at 0.5° and at 0.5°, 1.5°, and 2.4° elevation angles, respectively. According to the thresholds of the algorithm, which include echo intensity, the echo top height of 35 dBZ (ET), density threshold, and ε neighborhood, cloud clusters can be marked into four types: deep-convective cloud (DCC), shallow-convective cloud (SCC), hybrid convective-stratiform cloud (HCS), and stratiform cloud (SFC) types. Each cloud cluster type is further identified as a core area and boundary area, which can provide more abundant cloud structure information. The algorithm is verified using the volume scan data observed with new-generation S-band weather radars in Nanjing, Xuzhou, and Qingdao. The results show that cloud clusters can be intuitively identified as core and boundary points, which change in area continuously during the process of convective evolution, by the improved DBSCAN algorithm. Therefore, the occurrence and disappearance of convective weather can be estimated in advance by observing the changes of the classification. Because density thresholds are different and multiple elevations are utilized in the 3D model, the identified echo types and areas are dissimilar between the 2D and 3D models. The 3D model identifies larger convective and stratiform clouds than the 2D model. However, the developing convective clouds of small areas at lower heights cannot be identified with the 3D model because they are covered by thick stratiform clouds. In addition, the 3D model can avoid the influence of the melting layer and better suggest convective clouds in the developmental stage.  相似文献   

Effects of Drag Coefficients on Surface Heat Flux during Typhoon Kalmaegi (2014)     

Lei LIU  Guihua WANG  Ze ZHANG  Huizan WANG 《大气科学进展》2022,39(9):1501-1518

The lack of in situ observations and the uncertainties of the drag coefficient at high wind speeds result in limited understanding of heat flux through the air-sea interface and thus inaccurate estimation of typhoon intensity in numerical models. In this study, buoy observations and numerical simulations from an air-sea coupled model are used to assess the surface heat flux changes and impacts of the drag coefficient parameterization schemes on its simulations during the passage of Typhoon Kalmaegi (2014). Three drag coefficient schemes, which make the drag coefficient increase, level off, and decrease, respectively, are considered. The air-sea coupled model captured both trajectory and intensity changes better than the atmosphere-only model, though with relatively weaker sea surface cooling (SSC) compared to that captured by buoy observations, which led to relatively higher heat flux and thus a stronger typhoon. Different from previous studies, for a moderate typhoon, the coupled simulation with the increasing drag coefficient scheme outputted an intensity most consistent with the observation because of the strongest SSC, reasonable ratio of latent and sensible heat exchange coefficients, and an obvious reduction in the overestimated surface heat flux among all experiments. Results from sensitivity experiments showed that surface heat flux was significantly determined by the drag coefficient-induced SSC rather than the resulting wind speed changes. Only when SSC differs indistinctively (<0.4°C) between the coupled simulations, heat flux showed a weak positive correlation with the drag coefficient-impacted 10-m wind speed. The drag coefficient also played an important role in decreasing heat flux even a long time after the passage of Kalmaegi because of the continuous upwelling from deeper ocean layers driven by the impacted momentum flux through the air-sea interface.  相似文献