Monitoring regional sea ice of the Bohai Sea by SSM/I scattering index

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MOS-1/1b MESSR Observations of the Antarctic Sea Ice: Ice Bands and Ice Streamers

Meso- or submeso-scale features of the Antarctic sea ice are investigated using the MOS-1/1b MESSR Images (spatial resolution of approximately 50 m) received at Syowa Station. Particular attention is paid to the ice bands and ice streamers in coastal polynyas. In the Antarctic Ocean, ice bands can be often seen not only at the ice edge but also in the ice interior zone throughout the year and they extend for hundreds of kilometers in the latitudinal direction. It is found that the width and spacing of ice bands tend to decrease from winter to summer. The width of ice band is about 2–6 km in August and September, and 0.1–0.7 km in December. The spacing of ice bands is about 3–10 km in August and September, and 0.1–2 km in December. In coastal polynyas, ice streamers, which are composed of new ice, are sometimes observed. In general, the row of the streamers is spaced at 0.5–2 km with a width of 0.1–1.0 km.     

1997／98年冬季渤海和黄海北部冰情特征分析

海冰预报是渤、黄海重要的海洋灾害性预报项目之一。本文对１９９７～９８年冬季渤海及黄海北部的冰情概况进行了总结,并分析了渤海流冰范围在短时间内的迅速增长与天气、海洋等因子的相关关系。     

渤海、北黄海海冰与气候变化的关系

渤海和北黄海的冰情随着历年冬季气候差异而不同.暖冬海冰覆盖范围不足海域的15%,而寒冬可覆盖海域80%以上.概述了海冰监测及资料来源.冰覆盖面积、外缘线位置和冰况等级等被作为反映结冰海域冰情的指标.用大连和营口站的气温表示渤海、北黄海海域的局地气候.用1952～2000年大连的月平均气温描述冰情的变化.给出冰情指数由1952/1953年到1999/2000年随大连站月平均气温变化.影响渤海和北黄海冰情和气候的因子很多,诸如大气环流的演变和太阳活动等.分析了多种因子与冰情的滞后相关,指出20世纪90年代渤海冰情持续偏轻与全球气候变暖趋势相当一致;渤海和北黄海冰情的年际变化与El-Nino现象以及太阳活动周期有关;讨论了海冰季节演变的特征     

北极海冰的年代际转型与中国冻雨年代际变化的关系

基于1961-2013年HadISST海冰密集度资料,定义了北极海冰的季节性融冰指数,结果显示近几十年来北极季节性融冰范围呈显著的上升趋势,并分别在20世纪70年代末和90年代中期存在显著的年代际转型,相应地,中国冻雨发生频数总体上呈现出显著的减少趋势,但也存在显著的年代际转型。在20世纪70年代末之前,北极季节性融冰范围较小但显著增长,中国冻雨频数年际变化振幅较大,且主要受巴伦支海、喀拉海海冰的影响;20世纪70年代末至90年代中期北极季节性融冰范围维持振荡特征,没有显著的线性趋势,中国冻雨频数变化振幅减小,与北极海冰相关较弱,主要相关因子为北大西洋及北太平洋海表温度变化;而90年代中期以后,北极海冰融化加快,特别是2007年以后,季节性融冰范围大大增加,而中国冻雨频数处于低发时段,其变化与太平洋扇区海冰及堪察加半岛附近海温呈显著负相关,季节性融冰的显著区域也从东西伯利亚海逆时针旋转向波弗特海-加拿大群岛北部扩张,同时向北极中央区扩张。不同年代影响冻雨的海温或海冰关键海区不同,产生特定的大气环流异常响应,进而影响到我国冻雨。     

渤海冰-海洋耦合模式Ⅰ.模式和参数研究

在国内外冰-海洋耦合模式研究基础上,根据渤海水文、气象和冰情特点,以国家海洋环境预报中心的渤海海冰预报模式和POM海洋模式为基础,开发了一个冰-海洋耦合模式.在该耦合模式中,冰和海洋之间的动量和热量交换是双向的,冰厚和冰密集度的变化不仅由冰表面和冰底的热收支决定,还由开阔水的表面热收支决定.侧重阐述了耦合模式的动力和热力学过程的耦合,并对模式中一些热力参数进行了讨论.     

质点-网格海冰模式在渤海的数值预报试验

在海冰动力学和热力学的研究基础上,开发应用于渤海的质点-网格海冰模式.该模式采用质点-网格法,有效地避免了传统海冰模式的数值扩散问题.该模式采用冰厚分布函数取代传统渤海业务海冰预报模式中平整冰、堆积冰和开阔水的三类海冰分型.应用质点-网格海冰模式对2003年～2004年冬季渤海冰情进行了业务化逐日数值预报试验,并对预报结果进行统计检验和分析比较.     

Ice-Induced Fatigue Analysis by Spectral Approach for Offshore Jacket Platforms with Ice-Breaking Cones

The spectral methods and ice-induced fatigue analysis are discussed based on Miner's linear cumulative fatigue hypothesis and S-N curve data.According to the long-term data of full-scale tests on the platforms in the Bohai Sea,the ice force spectrum of conical structures and the fatigue environmental model are established.Moreover,the finite element model of JZ20-2MSW platform,an example of ice-induced fatigue analysis,is built with ANSYS software.The mode analysis and dynamic analysis in frequency domain under all kinds of ice fatigue work conditions are carried on,and the fatigue life of the structure is estimated in detail.The methods in this paper can be helpful in ice-induced fatigue analysis of ice-resistant platforms.     

秋季巴伦支海海温异常对冬季我国渤海冰情的可能影响

本文利用美国NCEP/NCAR逐月的再分析资料、HadISST海温、中国160台站气温和反映渤海冰情轻重的渤海冰情等级资料,研究了前秋巴伦支海海温异常对后期渤海冰情和东亚冬季风的影响,并对相关的物理过程进行分析。结果表明,前秋巴伦支海关键区海温与该区域海冰密集度呈显著的负相关,且具有较好的持续性,通过调节随后冬季向大气释放的热通量,引起后期环流变化。偏高(偏低)年冬季亚洲纬向环流偏弱(偏强),东亚大槽加深(减弱),东亚冬季风加强(减弱),我国东北、华北及西北地区地区显著偏冷(偏暖),这与冬季渤海海冰异常的强度和范围都偏大(小)及与之相联系的环流异常相一致。进一步的分析揭示了联系上游关键区海温变化与后期东亚地区气候异常的重要途径,前秋巴伦支海海温偏高会导致200 hPa高度场形成一个自西向东的波列形式,在东亚局地Hadley环流异常的作用下,加强了我国北方地区地表的北风异常。因此,前秋巴伦支海海温异常可以作为冬季渤海冰情的预报因子。     

海洋二号微波散射计极地海冰识别算法研究

An Antarctic sea ice identification algorithm on the HY-2A scatterometer(HSCAT) employs backscattering coefficient(σ0) and active polarization ratio(APR) for a preliminary sea ice identification.Then standard deviation(STD) filtering and space filtering are carried out.Finally,it is used to identify sea ice.A process uses a σ0,STD threshold and an APR as sea ice indicators.The sea ice identification results are verified using the sea ice distribution data of the ASMR2 released by the National Snow and Ice Data Center as a reference.The results show very good consistence of sea ice development trends,seasonal changes,area distribution,and sea ice edge distribution of the sea ice identification results obtained by this algorithm relative to the ASMR2 sea ice results.The accuracy of a sea ice coverage is 90.8% versus the ASMR2 sea ice results.This indicates that this algorithm is reliable.