排序方式： 共有143条查询结果，搜索用时 15 毫秒
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利用兰州大学半干旱气候与环境观测站(SACOL站)2009—2010年的地基微波辐射计亮温资料和榆中站探空资料,建立了应用于地基微波辐射计温度、相对湿度和水汽密度反演的径向基神经网络,并将反演结果与地基微波辐射计自带反演产品进行了对比,探究了径向基神经网络在地基微波辐射计气象要素反演算法本地化的应用效果。结果表明:径向基神经网络反演的温度、相对湿度和水汽密度的均方根误差最大值分别为2.72 K、22.32%和0.73 g·m^-3,在所有高度层上径向基神经网络的反演结果均优于微波辐射计,反演产品对2—10 km、1—7 km、0—3 km的大气温度、相对湿度和水汽密度廓线的反演均有明显改善,径向基神经网络能够应用于地基微波辐射计气象要素的反演算法的本地化。 相似文献
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海洋盐度在水循环、海洋环流、海洋生态系统、全球天气和气候变化等方面起着至关重要的作用。然而, 受观测的限制, 以往对海洋盐度的研究相对匮乏, 对其进行预报的工作更为少见。本文采用线性马尔可夫模型对印度洋海表面盐度(sea surface salinity, SSS)开展初步的预报工作。根据混合层盐度收支方程, 选择海表面高度(sea surface height, SSH)、海表面温度 (sea surface temperature, SST)、SSS等物理量的异常值作为模型的组成部分, 对印度洋SSS开展预报工作。结果表明, 马尔可夫模型可提前9个月对印度洋SSS进行较好的预报。此外, 南太平洋海表面温度异常(sea surface temperature anomaly, SSTA), 海表面高度异常(sea surface height anomaly, SSHA)和印度洋偶极子(Indian Ocean dipole, IOD)系数等遥相关因素的加入可将线性马尔可夫预报对印度洋SSS的预报效果(相关系数)平均提高10%。利用改进的模型对印度洋SSS进行提前1~11个月的“实时”预测, 得出预报的SSS时空变化特征与观测场相吻合。综上所述, 改进的线性马尔可夫模型对印度洋SSS具有一定的预测能力, 未来可进一步完善。 相似文献
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董昌明 LIM KAM SIAN Kenny Thiam Choy 蒋星亮 曹玉晗 嵇宇翔 王森 余洋 陆晓婕 周书逸 韦销蔚 BETHEL Brandon Justin 徐广珺 董济海 孙文金 王海丽 单海霞 王锦 王东霞 滕芳园 曹茜 谢文鸿 游志伟 王子韵 林连杰 《海洋科学进展》2022,40(4):660-683
海洋预报是进行海上活动的安全保障,海洋预报系统技术已经成为现代海洋气象业务的技术支撑。海洋观测、数据同化、数值模拟和高性能计算机等技术的进步极大地推动着海洋业务化预报的发展。采用大气数值模式（WRF）、海洋数值模式（CROCO）和海浪数值模式（SWAN）的多模式高分辨率离线耦合方式,添加南京信息工程大学“海洋数值模拟与观测实验室”团队自主研发的一系列海洋模式参数化方案,包括浪致混合参数化方案、亚中尺度参数化方案、海山诱导混合参数化方案以及涡旋诱导的沿等密度面和跨等密度面混合参数化方案,并通过同化技术和最新的人工智能技术与观测资料相结合,构建一种面向中国边缘海的风浪流多参数耦合预报系统,用于海上风电功率的预报和其他海洋灾害预警。实际观测资料的验证表明,该预报系统能较准确地模拟海上风场、海流、海温、波浪、潮汐等海洋气象要素。同时实现了按需实时可视化全景展示。 相似文献
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Climate change presents a threat to the sustainability of cities and their societies, and must be adequately addressed. Urban environments (cities) are responsible for the creation of a significant amount of greenhouse gas emissions which are the source of climate change. Cities have been increasingly the focus of action to address climate change, yet emissions are not significantly reducing. Additionally, there a lack of integration between adaptation and mitigation. This prevents responses adequate to limit global warming to 1.5OC, and to be well adapted to anticipated changes. This paper critically analyses existing definitions and typologies of climate change actions. A definition of ‘climate change transformation’ is proposed which includes the integration of adaptation and mitigation goals to enable a new regime in which global warming is limited to 1.5OC. A new three-part typology: ‘coping, malaction and transformation,’ is presented for categorising climate change actions by the extent to which they integrate adaptation and mitigation, and define a new regime. The typology is accompanied by illustrations to demonstrate the relationship between adaptation and mitigation. The definition, typology and illustration serve to guide effective climate change decision making, and provides principles to guide application in urban environments. 相似文献
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A dynamical downscaling approach using a regional climate model WRF (Weather Research and Forecasting Model Vision 3.5) driven by a global climate model CCSM4 (The Community Climate System Model Version 4) was adopted, and the downscaling results for the historical period (1982-2005) were evaluated for annual mean precipitation rate and evaporation rate over the Tibetan Plateau (TP). Furthermore, the spatial distribution and seasonal variation characteristics of Precipitation Recycling Ratio (PRR) simulated by CCSM4 and WRF were analyzed with the QIBT (Quasi-isentropic Back-trajectory method). The results show that the historical spatial distributions of annual mean precipitation rate and evaporation rate over the TP were found to better reproduce in the dynamical downscaling modeling compared to its coarse-resolution forcing. The PRR of the TP is 32% simulated by WRF, with a higher PRR in the wet season and a lower PRR in the dry season for the river basins in the northern TP, but the opposite seasonal variation was found for the river basins in the southern TP. In addition, the different land covers over the TP are more precisely represented in the WRF model, the PRR of grassland, shrubland and sparsely vegetation is higher than that of other land cover types. 相似文献
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水华蓝藻的生物学特性及其竞争优势、蓝藻水华的形成与维持机制等科学问题,一直是国内外研究的热点。氮素是诱发蓝藻水华暴发的重要营养盐,蓝藻对氮素的同化与其光合作用密切偶联。然而,水体中氮素存在多种形态,不同形态氮素对蓝藻生长和水华发生的影响具有显著差异。因此,了解蓝藻光合作用特征及其同化不同形态氮素的机制和策略,对深入理解蓝藻水华的发生机理具有重要意义。本文在蓝藻的光能捕获与激发能转移、光合电子传递、碳浓缩机制及CO2同化等光合作用过程及其特征综述的基础上,对蓝藻摄取、同化5种主要氮素形态(NO3-、NO2-、NH4+、尿素和N2)的分子机制及其特征进行了解读,总结了蓝藻细胞光合碳、氮同化的耦合关系及调控机制;并指出了该领域的未来发展方向,以推动该方向的深入研究。 相似文献
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现阶段降水预报主要依靠数值天气预报模式。但受物理参数化、计算资源等因素的影响,基于数值模式的降水预报还存在非常大的不确定性。近年来,深度学习在天气预报领域显示出巨大优势和潜力。本文通过构建神经网络预报美国东北部日降水分布,探讨神经网络模型基于低分辨率气象场(ERA-Interim, 0.7°)预报高分辨率降水(CPC,0.25°)的能力,并比较3种主流网络框架(VGG,ResNet, GoogleNet)在该任务中的表现。结果表明,3种网络框架都对美国东北部日降水分布具有一定的预报能力(VGG框架表现最优),但三者的均方根误差(RMSE)均高于ERA-Interim 24-h(ERA24)的降水预报。3种神经网络的集合预报结果优于ERA24预报,且这三者与ERA24预报结果的集合平均能够显著提高ERA24对不同季节、不同强度降水的预报。 相似文献
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