浙江省沿海海面日极大风预报

利用浙江海岛站1天4次的平均风速作为人工神经网络的输入层,相对应的日极大风为输出层,建立日极大风速人工神经网络预报模型,试报表明夏季大风天气系统和秋冬季大风天气系统的预报拟合率为89%~90%,春季大风天气系统的预报拟合率为87%~88%,夏季大风天气系统和秋冬季系统6~9级极大风预报准确率较高,基本在70%左右,对预报员有较好的参考价值。与以前大风预报方法相比,它具有简单、有效的优点,可以不受地域限制在各地推广使用。     

灾害性天气个例库智能分析系统的设计与实现

灾害性天气个例库智能分析系统是由基础数据支持子系统(数据层)、气象数据应用中间件子系统(服务层)和个例库综合分析业务子系统(应用层)3部分组成,综合运用HTML5 Canvas技术、数据库技术、GIS技术、高效可视化渲染技术等实现了气象灾害性天气个例的交互式录入、关键词查询与检索以及相关气象资料智能再分析等功能。文章针对系统的组成架构、个例库设计、功能特点等关键技术进行了重点探讨,并详细介绍个例库录入与查询、WebGIS组件、可视化渲染以及气象资料再分析等功能的设计和实现。系统投入业务运行结果表明,页面响应速度快、兼容浏览器性能佳、人机交互体验好,能够满足高效、智能、灵活的业务需求,在为预报员建立正确的预报思路、提升天气过程分析能力等方面发挥了重要作用。     

A NOVEL CLASSIFICATION METHOD FOR TROPICAL CYCLONE INTENSITY CHANGE ANALYSIS BASED ON HIERARCHICAL PARTICLE SWARM OPTIMIZATION ALGORITHM

Based on the tropical cyclone (TC) observations in the western North Pacific from 2000 to 2008, this paper adopts the particle swarm optimization (PSO) algorithm of evolutionary computation to optimize one comprehensive classification rule, and apply the optimized classification rule to the forecasting of TC intensity change. In the process of the optimization, the strategy of hierarchical pruning has been adopted in the PSO algorithm to narrow the search area, and thus to enhance the local search ability, i.e. hierarchical PSO algorithm. The TC intensity classification rule involves core attributes including 12-HMWS, MPI, and Rainrate which play vital roles in TC intensity change. The testing accuracy using the new mined rule by hierarchical PSO algorithm reaches 89.6%. The current study shows that the novel classification method for TC intensity change analysis based on hierarchic PSO algorithm is not only easy to explain the source of rule core attributes, but also has great potential to improve the forecasting of TC intensity change.     

海底沉积物声速经验方程的分析和研究

比较国内外主要研究者提出的海底沉积物声速单参数、双参数和多参数预报经验方程的物理意义和适用性,提出了孔隙度-含水量预报海底沉积物声速新的双参数公式,该式避免了单一参数预报声速经验方程和某些双参数公式中物理意义不明确以及多参数方程复杂性及对提高预报计算能力效果不显著之处.基于理论分析,改进孔隙度-含水量双参数计算公式得到的通用模型具有明确的物理意义,可以通过修改参数适用于不同海域的声速预报,提高了泛化能力,扩大了适用范围.通过对孔隙度、含水量等物理参数的权值分析研究,更加明确了孔隙度是影响海底沉积物声速大小的最关键参数.用台湾海峡北部、南海海域、珠江口大陆架三处的海域沉积物测量数据比较了不同模型,验证了本模型的优越性.     

Forecast Performance of the Pre-operational CMA-TRAMS (EPS) in South China During April - September 2020

The mesoscale ensemble prediction system based on the Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS (EPS)) has been pre-operational since April 2020 at South China Regional Meteorological Center (SCRMC), which was developed by the Guangzhou Institute of Tropical and Marine Meteorology (GITMM). To better understand the performance of the CMA-TRAMS (EPS) and provide guidance to forecasters, we assess the performance of this system on both deterministic and probabilistic forecasts from April to September 2020 in this study through objective verification. Compared with the control (deterministic) forecasts, the ensemble mean of the CMATRAMS (EPS) shows advantages in most non-precipitation variables. In addition, the threat score indicates that the CMA-TRAMS (EPS) obviously improves light and heavy rainfall forecasts in terms of the probability-matched mean. Compared with the European Center for Medium-range Weather Forecasts operational ensemble prediction system (ECMWF-EPS), the CMA-TRAMS (EPS) improves the probabilistic forecasts of light rainfall in terms of accuracy, reliability and discrimination, and this system also improves the heavy rainfall forecasts in terms of discrimination. Moreover, two typical heavy rainfall cases in south China during the pre-summer rainy season are investigated to visually demonstrate the deterministic and probabilistic forecasts, and the results of these two cases indicate the differences and advantages (deficiencies) of the two ensemble systems.     

Strategy Analysis of the Marine Science Projects of National Science Foundation of the United States

The National Science Foundation (NSF) is an international research funding institution with significant influence. As one of the main bodies of marine science research grant, NSF plays nonsubstitutable role in the development of marine science, the establishment of international research programs and projects, and the construction of infrastructures in the marine field. By mainly analyzing the area focus of NSF support, grant distribution and change trend, project application and acceptance rate in recent years, we summarized its funding characteristics and trends in marine science, and finally put forward four suggestions for reference to the efficient management of China's funding institutions.     

超短期风速预报方法研究进展

综合分析国内外风速预报相关文献,从物理方法、统计与机器学习方法、组合方法3个方面对超短期风速预报方法的研究现状进行归纳总结,对比了主要预报方法的优缺点,给出了不确定分析和误差评价指标,探讨了在超短期风速预报研究中应重点解决的问题和发展方向。     

沙澧河流域致洪预警系统设计与应用

沙澧河流域致洪预警系统基于中小河流致洪预警气象服务需求,以气象与水文相结合,应用地理信息(GIS)先进技术,利用气象常规数据、地面自动雨量站资料、数值模式、卫星雷达资料及水文雨量、水位数据等资料,运用动力学诊断和统计分析、多元线性回归方法、模式输出法、相似预报等方法,输出暴雨和水位增量预报模型。该系统通过C/C++语言编程,集气象水文信息显示分析、数据库、预报模型和用户界面于一体,建立了涵盖流域暴雨预报、水位增量监测预测、洪涝灾害预警服务等多功能的可视化业务技术平台。在本地基层台站首次将气象和水文两个学科结合,建立降水、水文和洪涝数据库;首次对沙澧河流域进行暴雨形势分型,并建立流域暴雨预报模型;首次建立沙澧河流域五大水库水位增量预报模型。自系统运行以来,成功对沙澧河流域出现的几次致洪暴雨进行了预警,服务效果明显。     

Seasonal Forecasts of the Summer 2016 Yangtze River Basin Rainfall

The Yangtze River has been subject to heavy flooding throughout history,and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods.Dams along the river help to manage flood waters,and are important sources of electricity for the region.Being able to forecast high-impact events at long lead times therefore has enormous potential benefit.Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services.The teleconnection from El Ni ?no to Yangtze River basin rainfall meant that the strong El Ni ?no in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system.This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin,building on previous work demonstrating the retrospective skill of such a forecast.A simple forecasting methodology is presented,in which the forecast probabilities are derived from the historical relationship between hindcast and observations.Its performance for2016 is discussed.The heavy rainfall in the May–June–July period was correctly forecast well in advance.August saw anomalously low rainfall,and the forecasts for the June–July–August period correctly showed closer to average levels.The forecasts contributed to the confidence of decision-makers across the Yangtze River basin.Trials of climate services such as this help to promote appropriate use of seasonal forecasts,and highlight areas for future improvements.     

Air transportation in China: Temporal and spatial evolution and development forecasts

This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic development of every province throughout the country in the years 2006 and 2015, and employs airport passenger and cargo throughput per capita and per unit of GDP as measures of regional air transportation utilization, which is significant for refining indicators of regional air transportation scale and comparing against them. It also analyzes the spatial differences of coupling between the regional air transportation utilization indicators and the key influencing factors on regional air transportation demand and utilization, which include per capita GDP, urbanization rate, and population density. Based on these key influencing factors, it establishes a multiple linear regression model to conduct forecasting of each province’s future airport passenger and cargo throughput as well as throughput growth rates. The findings of the study are as follows: (1) Between 2006 and 2015, every province throughout the country showed a trend of year on year growth in their airport passenger and cargo throughput per capita. Throughput per capita grew fastest in Hebei, with a rise of 780%, and slowest in Beijing, with a rise of 38%. Throughput per capita was relatively high in western and southeastern coastal regions, and relatively low in northern and central regions. Airport passenger and cargo throughput per unit of GDP showed growth in provinces with relatively slow economic development, and showed negative growth in provinces with relatively rapid economic development. Throughput per unit of GDP grew fastest in Hebei, rising 265% between 2006 and 2015, and Hunan had the fastest negative growth, with a fall of 44% in the same period. Southwestern regions had relatively high throughput per unit of GDP, while in central, northern, and northeastern regions it was relatively low. (2) Strong correlation exists between airport passenger and cargo throughput per capita and per capita GDP, urbanization rate, and population density. Throughput per capita has positive correlation with per capita GDP and urbanization rate in all regions, and positive correlation with population density in most regions. Meanwhile, there is weak correlation between airport passenger and cargo throughput per unit of GDP and per capita GDP, urbanization rate, and population density, with positive correlation in some regions and negative correlation in others. (3) Between 2015 and 2025, it is estimated that all provinces experience a trend of rapid growth in their airport passenger and cargo throughput. Inner Mongolia and Hebei will see the fastest growth, rising 221% and 155%, respectively, while Yunnan, Sichuan, and Hubei will see the slowest growth, with increases of 62%, 63%, and 65%, respectively.