Obtaining the distribution of quiescent periods directly from the power spectral densities of Sea waves

There is a growing practical interest in the ability to increase the sea states at which marine operations can be safely undertaken by exploiting the quiescent periods that are well known to exist under a wide range of sea conditions. While the actual prediction of quiescent periods at sea for the control of operations is a deterministic process, the long term planning of future maritime tasks that rely on these quiescent periods is a statistical process involving the anticipated quiescence properties of the forecasted sea conditions in the geographical region of interest. It is in principle possible to obtain such data in tabular form either large scale simulation or from field data. However, such simulations are computationally intensive and libraries of appropriate field data are not common. Thus, it is clearly attractive to develop techniques that exploit standard wave spectral models for describing the quiescence statistics directly from such spectra. The present study focuses upon such techniques and is a first step towards the production of a computationally low-cost quiescence prediction tool and compares its efficacy against simulations. Two significant properties emerge for a large class of wave spectral models that encompasses the ubiquitous Neumann and Pierson Moskowitz or Bretschneider forms. Firstly, the auto-correlation function of the wave profile that are required to produce the quiescence property can be obtained analytically in terms of standard special functions. This considerably reduces the computational cost making desktop computer-based planning tools a reality. Secondly, for each class of these parametric spectra, the probability of a given number of consecutive wave heights (normalised to the significant wave heights) less than some critical value is in fact independent of absolute wave height. Thus, for a broad class of practically interesting wave spectra all that is required to obtain the statistical distribution of the quiescent periods is simple rescaling.     

气候系统预测:基础创新和集成应用

随着全球变暖,极端天气气候事件增强,天气气候灾害造成的损失也愈发严重。当前气候预测的准确性远远不能满足社会需要,气候系统预测理论和方法面临着众多挑战性问题。为提档气候预测科学水平和准确率,由南京信息工程大学和中山大学承担的“气候系统预测研究中心”获得国家自然科学基金基础科学中心项目支持(2021年1月—2025年12月)。在该项目执行的前三年,项目团队开展了大量深入系统的研究,并取得了若干重要进展:1)揭示了气候系统的若干关键变化、驱动力和机制;2)剖析了海-陆-冰-气相互作用对我国重大极端气候事件的影响;3)在气候系统数值模式研发和预测系统集成方面取得重要进展;4)发展了延伸期-S2S-年代际的气候系统预测理论和方法。本文对这些进展作了扼要介绍,并针对气候与环境变化归因、古今气候环境研究融合、跨时空气候系统变异和极端气候、人工智能与气候科学、年代际预测和风险应对体系等关键科学问题做了展望。     

梅雨降水季节预测的多方法比较

基于1961—2000年逐月降水观测资料和全球大气再分析资料,分析了6—7月长江中下游(108°～123°E,27°～33°N)梅雨的时空分布特征。通过观测诊断和数值试验确定了影响梅雨异常偏多的3个前期因子:4—5月平均的西北太平洋海平面气压正异常;3月至5月北大西洋海平面气压负变压倾向;1月至4月西伯利亚的2 m温度负倾向。利用这3个具有物理意义的影响因子构建了梅雨季节预测模型,该模型在训练期(1961—2000年)和独立预测期(2001—2022年)均具有显著的预测技巧(相关系数分别为0.79和0.77,均方根误差分别为0.59和0.68)。同时,基于相似的潜在预测因子,对比了利用偏最小二乘回归方法和5种机器学习方法(随机森林、轻量级梯度提升机、自适应提升、类别型特征提升、极端梯度提升)建立的预测模型的技巧。虽然训练期(1961—2000年)偏最小二乘回归和机器学习建模拟合效果更高,但在独立预测期(2001—2022年)上述模型的预测技巧显著降低(相关系数均低于0.44,均方根误差均大于0.93),出现了明显的过拟合问题。本研究强调梅雨的短期气候预测应建立在物理机制基础之上,而使用机器学习方法需谨慎。     

基于AR（p）的卡尔曼滤波在GPS变形监测中的应用

由于AR（p）模型结构比较简单且计算比较方便,在变形分析中,目前常采用此模型建立变形模型。然而单纯的AR模型把模型参数作为定值,变形数据拟合误差及变形预测误差可能会比较大。介绍了将卡尔曼滤波引入AR模型,利用观测数据建立AR模型,即建立观测方程;以AR模型的参数为状态向量建立状态方程。从而形成动态系统的卡尔曼滤波函数模型,动态计算出AR模型的参数以便预测。此方法快速、实时,且占有较少内存,充分利用了AR模型和卡尔曼滤波二者的优点。     

Climate change and coral reef bleaching: An ecological assessment of long-term impacts,recovery trends and future outlook

Since the early 1980s, episodes of coral reef bleaching and mortality, due primarily to climate-induced ocean warming, have occurred almost annually in one or more of the world's tropical or subtropical seas. Bleaching is episodic, with the most severe events typically accompanying coupled ocean–atmosphere phenomena, such as the El Niño-Southern Oscillation (ENSO), which result in sustained regional elevations of ocean temperature. Using this extended dataset (25+ years), we review the short- and long-term ecological impacts of coral bleaching on reef ecosystems, and quantitatively synthesize recovery data worldwide. Bleaching episodes have resulted in catastrophic loss of coral cover in some locations, and have changed coral community structure in many others, with a potentially critical influence on the maintenance of biodiversity in the marine tropics. Bleaching has also set the stage for other declines in reef health, such as increases in coral diseases, the breakdown of reef framework by bioeroders, and the loss of critical habitat for associated reef fishes and other biota. Secondary ecological effects, such as the concentration of predators on remnant surviving coral populations, have also accelerated the pace of decline in some areas. Although bleaching severity and recovery have been variable across all spatial scales, some reefs have experienced relatively rapid recovery from severe bleaching impacts. There has been a significant overall recovery of coral cover in the Indian Ocean, where many reefs were devastated by a single large bleaching event in 1998. In contrast, coral cover on western Atlantic reefs has generally continued to decline in response to multiple smaller bleaching events and a diverse set of chronic secondary stressors. No clear trends are apparent in the eastern Pacific, the central-southern-western Pacific or the Arabian Gulf, where some reefs are recovering and others are not. The majority of survivors and new recruits on regenerating and recovering coral reefs have originated from broadcast spawning taxa with a potential for asexual growth, relatively long distance dispersal, successful settlement, rapid growth and a capacity for framework construction. Whether or not affected reefs can continue to function as before will depend on: (1) how much coral cover is lost, and which species are locally extirpated; (2) the ability of remnant and recovering coral communities to adapt or acclimatize to higher temperatures and other climatic factors such as reductions in aragonite saturation state; (3) the changing balance between reef accumulation and bioerosion; and (4) our ability to maintain ecosystem resilience by restoring healthy levels of herbivory, macroalgal cover, and coral recruitment. Bleaching disturbances are likely to become a chronic stress in many reef areas in the coming decades, and coral communities, if they cannot recover quickly enough, are likely to be reduced to their most hardy or adaptable constituents. Some degraded reefs may already be approaching this ecological asymptote, although to date there have not been any global extinctions of individual coral species as a result of bleaching events. Since human populations inhabiting tropical coastal areas derive great value from coral reefs, the degradation of these ecosystems as a result of coral bleaching and its associated impacts is of considerable societal, as well as biological concern. Coral reef conservation strategies now recognize climate change as a principal threat, and are engaged in efforts to allocate conservation activity according to geographic-, taxonomic-, and habitat-specific priorities to maximize coral reef survival. Efforts to forecast and monitor bleaching, involving both remote sensed observations and coupled ocean–atmosphere climate models, are also underway. In addition to these efforts, attempts to minimize and mitigate bleaching impacts on reefs are immediately required. If significant reductions in greenhouse gas emissions can be achieved within the next two to three decades, maximizing coral survivorship during this time may be critical to ensuring healthy reefs can recover in the long term.     

墨西哥湾天然气水合物矿产资源预测模型及其应用

墨西哥湾是世界上研究天然气水合物较深入的海区,调查资料丰富,已在50多处采集到天然气水合物样品,具备建立天然气水合物矿产资源预测模型的条件。选择34处已知天然气水合物矿点和34处已知无矿点作为训练区,建立矿点存在与否的预测模型。模型的相关系数值表明墨西哥湾天然气水合物与盐底辟关系密切。将该模型应用于整个墨西哥湾北部,初步获得了天然气水合物存在可能性概率分布图;概率大于0.7的预测单元包含已知矿点中的30个,利用该阈值圈定了墨西哥湾天然气水合物潜在资源分布区。     

����ARģ�͵��Ϻ������������Ԥ�����

????AR?????????????????????????????????????AIC?????AR????????????????????,AR??4?????????????????????AR(4)???????????δ??10???????????????????     

基于集合预报极端天气预测指数的浙江分类强对流预报模型

利用2016—2021年ECWMF集合预报资料、浙江自动站实况资料等,计算浙江短时强降水、雷暴大风和冰雹等强对流天气相关物理量的极端天气预报指数（EFI：Extreme Forecast Index）,分析EFI分布特征,并构建了分类强对流预报模型。结果表明：强对流天气与物理量的EFI有密切联系,发生短时强降水时,对流有效位能、整层可降水量、850 hPa与500 hPa温差和位温差的EFI较大,而垂直风切变的EFI为负值,因而较小的垂直风切变更有利于出现极端降水;发生雷暴大风和冰雹时,对流有效位能、850 hPa与500 hPa温差和位温差以及850 hPa温度露点差的EFI较大,700 hPa露点温度的EFI为负值,与上层干冷下层暖湿的有利层结条件有关。利用支持向量机多分类方法,将强对流天气相关物理量的EFI作为特征值开展训练,构建的预报模型对于非局地强对流天气有较好的预报效果,其中短时强降水的误判率明显低于雷暴大风。     

广平地震台地磁异常与地震关系的研究

利用加卸载响应比、日变幅逐日比、空间相关分析法,研究分析了广平台1982-2006年地磁垂直分量观测资料与河北省及邻近地区Ms≥5.0地震之间的关系,发现它们之间有较好的对应关系;同时给出了适用于广平地磁台的地震分析预报参数,为今后广平台依磁报震提供了依据.     

Estimation and prediction of plastic waste annual input into the sea from China

Marine plastic debris has been a pervasive issue since the last century, and research on its sources and fates plays a vital role in the establishment of mitigation measures. However, data on the quantity of plastic waste that enters the sea on a certain timescale remain largely unavailable in China. Here, we established a model using material flow analysis method based on life cycle assessment to follow plastic product from primary plastic to plastic waste with statistical data and monitoring data from accurate sources. This model can be used to estimate and forecast the annual input of plastic waste into the sea from China until 2020. In 2011, 0.547 3–0.751 5 million tons of plastic waste entered the seas in China, with a growth rate of 4.55% per year until 2017. And the amount will decrease to0.257 1 to 0.353 1 million tons in 2020 under the influence of governmental management. The amount of plastic waste discharged from coastal areas calculated in this study was much larger than that from river, thus it is suggested to strengthen the governance and control of plastic waste in coastal fishery activities in China in order to reduce the amount of marine plastic waste input.