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1.
The Coupling of three model components, WRF/PCE (polar climate extension version of weather research and forecasting model (WRF)), ROMS (regional ocean modeling system), and CICE (community ice code), has been implemented, and the regional atmosphere-ocean-sea ice coupled model named WRF/PCE- ROMS-CICE has been validated against ERA-interim reanalysis data sets for 1989. To better understand the reasons that generate model biases, the WRF/PCE-ROMS-CICE results were compared with those of its components, the WRF/PCE and the ROMS-CICE. There are cold biases in surface air temperature (SAT) over the Arctic Ocean, which contribute to the sea ice concentration (SIC) and sea surface temperature (SST) biases in the results of the WRF/PCE-ROMS-CICE. The cold SAT biases also appear in results of the atmo- spheric component with a mild temperature in winter and similar temperature in summer. Compared to results from the WRF/PCE, due to influences of different distributions of the SIC and the SST and inclusion of interactions of air-sea-sea ice in the WRF/PCE-ROMS-CICE, the simulated SAT has new features. These influences also lead to apparent differences at higher levels of the atmosphere, which can be thought as responses to biases in the SST and sea ice extent. There are similar atmospheric responses in feature of distribution to sea ice biases at 700 and 500 hPa, and the strength of responses weakens when the pressure decreases in January. The atmospheric responses in July reach up to 200 hPa. There are surplus sea ice ex- tents in the Greenland Sea, the Barents Sea, the Davis Strait and the Chukchi Sea in winter and in the Beau- fort Sea, the Chukchi Sea, the East Siberian Sea and the Laptev Sea in summer in the ROMS-CICE. These differences in the SIC distribution can all be explained by those in the SST distributions. These features in the simulated SST and SIC from ROMS-CICE also appear in the WRF/PCE-ROMS-CICE. It is shown that the performance of the WRF/PCE-ROMS-CICE is determined to a l  相似文献   

2.
A series of numerical experiments have been conducted with a perpetual July, nine-level general circulation spectral model to determine the effect of variation of the Arctic sea ice cover extent and the joint effect of anomalies of both the Arctic sea ice cover and the Central-eastern Equatorial Pacific sea surface temperature on the summer general circulation. Results show that the two factors,anomalously large extent of the Arctic sea ice cover and anomalously warm sea surface temperature over the Central-eastern Equatorial Pacific Ocean, play substantially the equal role in the effect on the summer general circulation, and either of them can notably induce the atmospheric anomalies. The main dynamical processes determining the effect of the Arctic sea ice and the equatorial SST anomalies are associated with two leading teleconnection patterns, i. e. the Asia North/American and Eurasian patterns observed in atmosphere. The results presented in this paper again prove that the general circulation is fun  相似文献   

3.
正In recent decades, Arctic climate is warming at a rate of almost twice the global average(Osborne et al., 2018). The surface atmosphere and oceanic temperatures over Arctic Ocean increase leads to the rapid retreat of sea ice. The extension and thickness of sea ice in the Arctic, as well as the multi-year ice coverage, have decreased significantly. For example, the September sea ice extent in the Arctic, which is the end of the summer melt season, decreases at a rate of larger than 11% per decade(Polyakov et al., 2012).  相似文献   

4.
Application of the HY-1 satellite to sea ice monitoring and forecasting   总被引:2,自引:2,他引:2  
The HY-1A satellite is the first oceanic satellite of China. During the winter of 2002-2003, the data of the HY-1A were applied to the sea ice monitoring and forecasting for the Bohai Sea of China for the fhst time. The sea ice retrieval system of the HY-1A has been constructed. It receives 1B data from the satellite, outputs sea ice images and provides digital products of ice concentration, ice thickness and ice edge, which can be used as important information for sea ice monitoring and the initial fields of the numeric sea ice forecast and as one of the reference data for the sea ice forecasting verification. The sea ice retrieval system of the satellite is described, including its processes, methods and parameters. The retrieving results and their application to the sea ice monitoring and forecasting for the Bohai Sea are also discussed.  相似文献   

5.
The diffuse attenuation coefficient(Kd) for downwelling irradiance is calculated from solar irradiance data measured in the Arctic Ocean during 3rd and 4th Chinese National Arctic Research Expedition(CHINARE), including 18 stations and nine stations selected for irradiance profiles in sea water respectively. In this study, the variation of attenuation coefficient in the Arctic Ocean was studied, and the following results were obtained. First, the relationship between attenuation coefficient and chlorophyll concentration in the Arctic Ocean has the form of a power function. The best fit is at 443 nm, and its determination coefficient is more than 0.7. With increasing wavelength, the determination coefficient decreases abruptly. At 550 nm, it even reaches a value lower than 0.2. However, the exponent fitted is only half of that adapted in low-latitude ocean because of the lower chlorophyll-specific absorption in the Arctic Ocean. The upshot was that, in the case of the same chlorophyll concentration, the attenuation caused by phytoplankton chlorophyll in the Arctic Ocean is lower than in low-latitude ocean. Second, the spectral model, which exhibits the relationship of attenuation coefficients between 490 nm and other wavelength, was built and provided a new method to estimate the attenuation coefficient at other wavelength, if the attenuation coefficient at 490 nm was known. Third, the impact factors on attenuation coefficient, including sea ice and sea water mass, were discussed. The influence of sea ice on attenuation coefficient is indirect and is determined through the control of entering solar radiation. The linear relationship between averaging sea ice concentration(ASIC, from 158 Julian day to observation day) and the depth of maximum chlorophyll is fitted by a simple linear equation. In addition, the sea water mass, such as the ACW(Alaskan Coastal Water), directly affects the amount of chlorophyll through taking more nutrient, and results in the higher attenuation coefficient in the layer of 30–60 m. Consequently, the spectral model of diffuse attenuation coefficient, the relationship between attenuation coefficient and chlorophyll and the linear relationship between the ASIC and the depth of maximum chlorophyll, together provide probability for simulating the process of diffuse attenuation coefficient during summer in the Arctic Ocean.  相似文献   

6.
引入拖曳系数参数化的海冰自由漂流模拟研究   总被引:2,自引:0,他引:2  
Many interesting characteristics of sea ice drift depend on the atmospheric drag coefficient(C_a) and oceanic drag coefficient(C_w).Parameterizations of drag coefficients rather than constant values provide us a way to look insight into the dependence of these characteristics on sea ice conditions.In the present study,the parameterized ice drag coefficients are included into a free-drift sea ice dynamic model,and the wind factor α and the deflection angle θ between sea ice drift and wind velocity as well as the ratio of C_a to C_w are studied to investigate their dependence on the impact factors such as local drag coefficients,floe and ridge geometry.The results reveal that in an idealized steady ocean,C_a/C_w increases obviously with the increasing ice concentration for small ice floes in the marginal ice zone,while it remains at a steady level(0.2-0.25) for large floes in the central ice zone.The wind factor α increases rapidly at first and approaches a steady level of 0.018 when A is greater than 20%.And the deflection angle θ drops rapidly from an initial value of approximate 80° and decreases slowly as A is greater than20%without a steady level like α.The values of these parameters agree well with the previously reported observations in Arctic.The ridging intensity is an important parameter to determine the dominant contribution of the ratio of skin friction drag coefficient(C_s' /C_s) and the ratio of ridge form drag coefficient(C_r'/C_r) to the value of C_a/C_w,α,and θ,because of the dominance of ridge form drag for large ridging intensity and skin friction for small ridging intensity among the total drag forces.Parameterization of sea ice drag coefficients has the potential to be embedded into ice dynamic models to better account for the variability of sea ice in the transient Arctic Ocean.  相似文献   

7.
Possible impact of reduced Arctic sea-ice on winter severe weather in China is investigated regarding the snowstorm over southern China in January 2008. The sea-ice conditions in the summer (July-September) and fall (September-November) of 2007 show that the sea-ice is the lowest that year. During the summer and fall of 2007, sea ice displayed a significant decrease in the East Siberian, the northern Chukchi Sea, the western Beaufort Sea, the Barents Sea, and the Kara Sea. A ECHAM5.4 atmospheric general circula- tion model is forced with realistic sea-ice conditions and strong thermal responses with warmer surface air temperature and higher-than-normal heat flux associated with the sea-ice anomalies are found. The model shows remote atmospheric responses over East Asia in January 2008, which result in severe snowstorm over southern China. Strong water-vapor transported from the Bay of Bengal and from the Pacific Ocean related to Arctic sea-ice anomalies in the fall (instead of summer) of 2007 is considered as one of the main causes of the snowstorm formation.  相似文献   

8.
The seasonal and inter-annual variations of Arctic cyclone are investigated. An automatic cyclone tracking algorithm developed by University of Reading was applied on the basis of European Center for Medium-range Weather Forecasts(ECMWF) ERA-interim mean sea level pressure field with 6 h interval for 34 a period. The maximum number of the Arctic cyclones is counted in winter, and the minimum is in spring not in summer.About 50% of Arctic cyclones in summer generated from south of 70°N, moving into the Arctic. The number of Arctic cyclones has large inter-annual and seasonal variabilities, but no significant linear trend is detected for the period 1979–2012. The spatial distribution and linear trends of the Arctic cyclones track density show that the cyclone activity extent is the widest in summer with significant increasing trend in CRU(central Russia)subregion, and the largest track density is in winter with decreasing trend in the same subregion. The linear regressions between the cyclone track density and large-scale indices for the same period and pre-period sea ice area indices show that Arctic cyclone activities are closely linked to large-scale atmospheric circulations, such as Arctic Oscillation(AO), North Atlantic Oscillation(NAO) and Pacific-North American Pattern(PNA). Moreover,the pre-period sea ice area is significantly associated with the cyclone activities in some regions.  相似文献   

9.
The dramatic decline of summer sea ice extent and thickness has been witnessed in the western Arctic Ocean in recent decades, which hasmotivated scientists to search for possible factors driving the sea ice variability. An eddy-resolving, ice-ocean coupled model covering the entire Arctic Ocean is implemented, with focus on the western Arctic Ocean. Special attention is paid to the summer Alaskan coastal current (ACC), which has a high temperature (up to 5℃ ormore) in the upper layer due to the solar radiation over the open water at the lower latitude. Downstream of the ACC after Barrow Point, a surface-intensified anticyclonic eddy is frequently generated and propagate towards the Canada Basin during the summer season when sea ice has retreated away from the coast. Such an eddy has a warm core, and its source is high-temperature ACC water. A typical warm-core eddy is traced. It is trapped just below summer sea ice melt water and has a thickness about 60 m. Temperature in the eddy core reaches 2-3℃, and most water inside the eddy has a temperature over 1℃. With a definition of the eddy boundary, an eddy heat is calculated, which can melt 1 600 km2 of 1mthick sea ice under extreme conditions.  相似文献   

10.
北极各海域海冰覆盖范围的变化特征   总被引:2,自引:1,他引:1  
Sea ice in the Arctic has been reducing rapidly in the past half century due to global warming.This study analyzes the variations of sea ice extent in the entire Arctic Ocean and its sub regions.The results indicate that sea ice extent reduction during 1979–2013 is most significant in summer,following by that in autumn,winter and spring.In years with rich sea ice,sea ice extent anomaly with seasonal cycle removed changes with a period of 4–6 years.The year of 2003–2006 is the ice-rich period with diverse regional difference in this century.In years with poor sea ice,sea ice margin retreats further north in the Arctic.Sea ice in the Fram Strait changes in an opposite way to that in the entire Arctic.Sea ice coverage index in melting-freezing period is an critical indicator for sea ice changes,which shows an coincident change in the Arctic and sub regions.Since 2002,Region C2 in north of the Pacific sector contributes most to sea ice changes in the central Aarctic,followed by C1 and C3.Sea ice changes in different regions show three relationships.The correlation coefficient between sea ice coverage index of the Chukchi Sea and that of the East Siberian Sea is high,suggesting good consistency of ice variation.In the Atlantic sector,sea ice changes are coincided with each other between the Kara Sea and the Barents Sea as a result of warm inflow into the Kara Sea from the Barents Sea.Sea ice changes in the central Arctic are affected by surrounding seas.  相似文献   

11.
本文系统地评估了国家海洋环境预报中心于我国第七次北极科学考察期间开展的北极海冰密集度数值预报结果。该预报系统基于麻省理工大学通用环流模式,并采用牛顿松弛逼近(Nudging)资料同化方法,计算输出未来1~5 d的北极海冰密集度预报产品。本文将数值预报结果同卫星观测的海冰密集度、再分析资料和"雪龙"号第七次北极考察期间观测的海冰密集度数据进行了对比分析。结果表明,预报的北极海冰密集度小于卫星观测值,24 h、72 h和120 h预报结果的偏差分别为-2.7%、-3.1%和-3.2%;数值产品的预报技巧好于气候态结果和惯性预报,但是在海冰出现快速融化或冻结时,基于Nudging同化的数值预报技巧仍有不足。另外,相比船测数据,数值预报结果在海冰边缘区的偏差相对较大,24 h、72 h和120 h预报结果的偏差分别为8.8%、12.0%和14.5%。  相似文献   

12.
Numerical sea ice prediction in China   总被引:5,自引:2,他引:3  
NumericalseaicepredictioninChinaWuHuiding,BaiShan,ZhangZhanhai1(ReceivedSeptember12,1996;acceptedJune5,1997)Abstract──Adynami...  相似文献   

13.
Nudging资料同化对北极海冰密集度预报的改进   总被引:2,自引:2,他引:0       下载免费PDF全文
北极夏季海冰的快速减少使得北极航道提前开通成为可能。为了给北极冰区船运活动提供及时可靠有效的海冰预报保障,急需提高海冰预报水平。本文基于麻省理工大学通用环流模式(MITgcm),使用牛顿松弛逼近(Nudging)资料同化方法将德国不莱梅大学的第二代先进微波辐射成像仪(AMSR2)海冰密集度资料同化到模式中,建立了北极海冰数值预报系统。设计试验对比3种不同Nudging系数计算方案的改进效果,结果表明选择合适参数后,不同方案均能显著改进海冰密集度初始场。通过设计有无Nudging同化的两组预报试验,结合卫星遥感海冰密集度及中国第五次北极科学考察期间"雪龙"船的走航海冰密集度观测数据,定量分析了Nudging同化方案对北极海冰密集度的24~120 h预报结果的改进效果。结果表明,Nudging同化对120 h内全北极海冰密集度的空间分布和移动单点目标的海冰密集度预报结果均有显著改善;但在海冰变化很小的情况下,Nudging同化试验的24~120 h预报结果均劣于惯性预报结果,说明基于Nudging同化的数值预报系统还需进一步提高预报技巧。  相似文献   

14.
陈迪  孙启振 《海洋学报》2022,44(12):42-54
本文利用1951?2021年哈德莱中心提供的海冰和海温最新资料以及美国国家海洋和大气管理局气候预报中心提供的NCEP/NCAR再分析资料,分析探讨了北极海冰70余年的长期变化特征,进而研究了其快速减少与热带海温场异常变化之间的联系,揭示了在全球热带海洋海温场变化与北极海冰之间存在密切联系的事实。结果表明,北极海冰异常变化最显著区域出现在格陵兰海、卡拉海和巴伦支海。热带不同海区对北极海冰的影响存在明显时滞时间和强度差异,热带大西洋的影响相比偏早,印度洋次之,太平洋偏晚。热带大西洋、印度洋和中东太平洋海温异常影响北极海冰的最佳时间分别是后者滞后26个月、30个月和34个月,全球热带海洋影响北极海冰的时滞时间为33个月。印度洋SST对北极海冰的影响程度最强,其次是太平洋,最弱是大西洋。全球热带海洋对北极海冰的影响过程中,热带东太平洋和印度洋起主导作用。当全球热带海洋SST出现正(负)距平时,北极海冰会出现偏少(多)的趋势,而AO、PNA、NAO对北极海冰变化起重要作用,是热带海洋与北极海冰相系数的重要“纽带”。而AO、PNA和NAO不仅受热带海洋SST的影响,同时也受太平洋年代际振荡PDO和大西洋多年代际AMO的影响,这一研究为未来北极海冰快速减少和全球气候变暖机理的深入研究提供理论支撑。  相似文献   

15.
基于美国国家冰雪数据中心 (NSIDC) 海冰资料、美国国家环境预报中心 (NCEP) 再分析格点数据和黄渤海近岸13个气象站点逐日气温数据,通过相关分析和合成分析,研究了 2007-2018 年黄渤海海冰范围的变化特征,探讨了近 12 年黄渤海海冰范围对近岸陆地气温、大气环流和局地天气过程的响应。结果表明: (1) 黄渤海海冰范围年际振荡明显,近 12 年呈现先增加后减小的趋势,与同期黄渤海近岸气温呈显著负相关关系;每年 1 月下旬至 2 月下旬是一年中海冰范围最大的时期。(2) 海冰范围偏大与偏小年份东亚地区 500 hPa 大气环流形势呈现出近乎相反的分布。 (3) 东亚阻塞形势的建立是黄渤海海冰范围爆发性增大的一个前兆信号,它带来的大风降温天气是造成黄渤海海冰范围爆发性增大的重要原因.  相似文献   

16.
误差订正对2018年夏季次季节尺度海冰预测的作用   总被引:1,自引:1,他引:0  
北极海冰次季节尺度预测在针对破冰船和商船的实际服务中十分重要,但常常受制于气候模拟的模拟能力。本研究提出了一种误差订正方法并分别应用到两个气候模式:海洋一所地球系统模式(FIOESM)和美国国家环境预报中心(NCEP)的气候预报系统(CFS),来改善北极海冰60天尺度的预测。本研究的预测工作是中国第9次北极科学考察和2018年夏季中远集团北极商业航行的业务化海冰服务保障的重要部分。模式起报时间分别是2018年7月1日、8月1日和9月1日,预报时效均是60天。结果显示,FIOESM整体上低估了海冰密集度的数值,平均偏差可达30%。误差订正对海冰密集度(SIC)的均方根偏差(RMSE)的改进比例可达27%,对海冰外缘线(SIE)的整体偏差(IIEE)的改进比例为10%。而对于CFS,SIE在边缘区域的过高估计是其主要特点。误差订正导致了SIC的RMSE改进了7%,而对SIE的IIEE改进了17%。在海冰范围预测方面,FIOESM预测的最小范围数值和时间点都和观测接近,而CFS的预测结果偏差较大。另外和其他S2S模式的结果比较发现,本研究提出的误差订正方法对存在较大偏差的预测结果改进更为有效。  相似文献   

17.
2011-2014年中国北极物理海洋学的研究进展   总被引:2,自引:1,他引:1  
曹勇  赵进平 《海洋学报》2015,37(11):1-10
过去十几年北极的快速变化以海冰变化为主要特征。然而,在冰-海-气变化系统中海洋起着关键性的作用。海洋是北极变化的关键因素,不仅影响着海冰的融化与冻结等过程,而且是大气变化的主要能量来源。在北极海冰快速变化的背景下,北冰洋的海洋特征也发生了一系列的变化。第四次国际极地年之后我国在北极科学研究中取得了一系列的进展,本文从北冰洋水团、锋面、海流等主要水文现象,以及上层海洋结构等方面,总结了2011-2014年我国在北极物理海洋学方面取得的一系列成果。  相似文献   

18.
2011年6月-8月渤海湾溢油事故长期后报数值模拟   总被引:1,自引:1,他引:0  
三维业务化溢油应急预报系统不仅能提供逐时的海洋环境信息预报和溢油漂移扩散,还能对溢油事件进行后报数值模拟。2011年6月4日在渤海湾蓬莱19-3B采油平台发生溢油事件,同月17日19-3C平台也发生溢油事件。此次溢油事故造成了数千平方公里海水受污染。本文采用国家海洋环境预报中心自主研发的溢油模型对蓬莱19-3溢油事件进行长期后报数值模拟,在风流海洋环境场的驱动下,模拟了2016年6月到2016年8月,两个平台溢油的漂移扩散情况、影响范围,靠岸时间和影响岸段等。风场采用基于WRF模型模拟得到的再分析风场,并用实测风对再分析风场进行订正,流场采用基于POM模式在再分析风场驱动下得到的海流。后报结果显示,溢油主要向西北方向漂移,并最终靠岸,其扫过的海域也主要在平台的西北方向,这与观测结果一致,验证了后报的可靠性。  相似文献   

19.
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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