首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到17条相似文献,搜索用时 234 毫秒
1.
地球系统模式FIO-ESM对北极海冰的模拟和预估   总被引:5,自引:3,他引:2  
评估了地球系统模式FIO-ESM(First Institute of Oceanography-Earth System Model)基于CMIP5(Coupled Model Intercomparison Project Phase 5)的历史实验对北极海冰的模拟能力,分析了该模式基于CMIP5未来情景实验在不同典型浓度路径(RCPs,Representative Concentration Pathways)下对北极海冰的预估情况。通过与卫星观测的海冰覆盖范围资料相比,该模式能够很好地模拟出多年平均海冰覆盖范围的季节变化特征,模拟的气候态月平均海冰覆盖范围均在卫星观测值±15%范围以内。FIO-ESM能够较好地模拟1979-2005年期间北极海冰的衰减趋势,模拟衰减速度为每年减少2.24×104 km2,但仍小于观测衰减速度(每年减少4.72×104 km2)。特别值得注意的是:不同于其他模式所预估的海冰一直衰减,FIO-ESM对21世纪北极海冰预估在不同情景下呈现不同的变化趋势,在RCP2.6和RCP4.5情景下,北极海冰总体呈增加趋势,在RCP6情景下,北极海冰基本维持不变,而在RCP8.5情景下,北极海冰呈现继续衰减趋势。  相似文献   

2.
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   

3.
近40年北极海冰范围变化特征分析   总被引:1,自引:0,他引:1  
随着全球变暖,北极海冰正在发生快速变化。文中使用北极地区1972年1月—2012年12月海冰密集度卫星遥感资料,计算了北极海冰范围,讨论了北极海冰范围的各月年变化趋势,并分析了北极海冰范围与北半球温度异常、大气中CO2浓度的关系。分析结果表明:近40年北极海冰呈显著减少趋势,9月份减少最快;北极海冰的减少滞后于北半球2—4月的异常高温;北极年海冰范围与大气中CO2浓度为负相关,相关系数r为-0.94,说明大气中CO2浓度的增长影响了包括气温在内的气候变化要素,而导致北极海冰消退。  相似文献   

4.
2013年北极最小海冰范围比2012年增加的原因分析   总被引:4,自引:4,他引:0  
崔红艳  乔方利  舒启 《海洋学报》2015,37(11):23-32
北极海冰范围从1979年有卫星观测资料以来呈现明显下降趋势,尤其是9月份。2012年9月北极海冰范围达到有观测记录以来的最小值,而2013年9月比2012年同期增加了60%。增加的区域主要在东西伯利亚海区、楚科奇海和波弗特海区。本文应用距平和经验模态分解方法,分析了美国国家冰雪数据中心的北极海冰卫星数据、欧洲预报中心的夏季底层大气环流数据和上层海洋的温度,指出2013年北极最小海冰范围比2012年在北冰洋太平洋扇区增加的原因,是由于表面气温(SAT)降低、海平面气压(SLP)升高、气旋式风场异常、表面空气中水汽含量(SH)降低以及海表面温度(SST)降低5个条件形成的冰-SAT、冰-SST和冰-汽(SH)3个正反馈机制共同作用造成的。  相似文献   

5.
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   

6.
北极海冰正处于快速减退时期,北极海冰体积变化是全球气候变化的重要指示因子。本文利用两种卫星高度计数据(ICESat和CryoSat-2)反演得到的海冰厚度数据,结合星载辐射计提取的海冰密集度数据以及海冰年龄数据,估算了近期的北极海冰体积以及一年冰和多年冰体积变化。CryoSat-2观测时段(2011-2013年)与ICESat观测时段(2003-2008年)相比,北极海冰体积在秋季(10-11月)和冬季(2-3月)分别减少了1 426 km3和412 km3。其中,秋季和冬季的一年冰的体积增加了702 km3和2 975 km3。相反,多年冰分别减少了2 108 km3和3 206 km3。多年冰的大量流失是造成北极海冰净储量下降的主要原因。  相似文献   

7.
国际气候研究计划(WCRP)最近计划在南极和北极地区组织实施国际冰厚监测项目,该项目由世界气象组织(WMO)和国际科联(ICSU)组织实施。 海冰在气候变化中对控制高纬度地区大气和海洋中的热交换,驱动海洋中的温盐环流起着重要作用。海冰作为巨大的冷源对全球气候变化的影响已引起全球海洋学界和气候学界的极大关注。对海冰范围,密集度和厚度的长期观测是发展和试验全球大气-海洋-海冰耦合模式的重要基础。 海冰范围和密集度的观测,自1972年美国NOAA系列卫星和Nimbus系列卫星装载了甚高分辨率辐射仪(AVHRR)和微波辐射仪以来,比较成功地解决了海冰密集度和海冰外缘线的监测问题。但冰厚观测必须现场进行。冰厚也是确定热量收支和流变学重要的参数。所以是当今关于研究海冰自身变化及全球气候变化中的重要难题之一。目前仅有一些分散的零星海冰厚度观测资料,不能满足在全球冰-气-海耦合模式中的所需要求。  相似文献   

8.
在全球变暖背景下,北极海冰覆盖面积持续减少,对全球的温盐环流、海洋生物化学过程和气候变化产生了深远的影响,研究北极古海冰的变化可以使我们对北极环境有全面的认识,更准确地预测其未来的变化规律。近十年来,一种新发展的海冰生物标志物IP_(25)(Ice Proxy with 25 carbon atoms)被广泛用于北极及亚北极的海冰重建。IP_(25)是北极冰藻产生的一种高度分化的单不饱和类异戊二烯(HBIs),能够稳定地保存在海洋沉积物中。自从IP_(25)被发现以来,越来越多的研究者对其指示海冰变化的应用进行了深入的研究。本文首先总结了重建古海冰的传统指标和限制性并介绍了IP_(25)指示海冰的原理、由定性到定量的发展以及存在的局限性。然后归纳了利用IP_(25)重建北极地区海冰分布和变化的实例研究,涵盖了北冰洋中心、陆架边缘海、河口以及亚北极地区不同空间海域,跨越了近现代、全新世、第四纪以及中新世不同时间尺度。其中,近现代的海冰重建结果与海冰的卫星观测数据取得了很好的相关性,为古海冰的重建提供了基础;古海冰的重建为数值模拟古气候以及预测未来海冰变化趋势提供了重要依据。  相似文献   

9.
北极海冰变化影响着全球物质平衡、能量交换和气候变化。本文基于CryoSat-2测高数据和OSI SAF海冰密集度及海冰类型产品,分析了2010-2017年北极海冰面积、厚度和体积的季节和年际变化特征,结合NCEP再分析资料探讨了融冰期北极气温异常和夏季风异常对海冰变化的影响。结果表明,结冰期海冰面积的增加量波动较大,海冰厚度的增加量呈明显下降趋势。融冰期海冰厚度的减小量波动较大,2013年以后融冰期海冰面积的减小量逐年增加。海冰体积的变化趋势和面积变化更相似,融冰期的减小速率大于结冰期的增加速率。融冰期北极海表面大气温度异常与海冰融化量正相关。夏季风影响海冰的辐合和辐散,在弗拉姆海峡海冰的输运过程中起关键作用,促进了北冰洋表层水向大洋深层的传输。  相似文献   

10.
本文主要根据1953~1977年资料,从观测分析和数值试验两方面研究了北极海冰覆盖面积异常对全球的大气环流和气候、特别是对中国气候的影响,发现北极海冰的影响可与中东赤道太平洋海温异常的影响相比拟,甚或可以超过,指出在气候和长期天气预报研究工作中,极冰变异及其影响需要很好重视。  相似文献   

11.
To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model (FIO-ESM) climate forecast system, satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) are assimilated into this system, using the method of localized error subspace transform ensemble Kalman ?lter (LESTKF). Five-year (2014–2018) Arctic sea ice assimilation experiments and a 2-month near-real-time forecast in August 2018 were conducted to study the roles of ice data assimilation. Assimilation experiment results show that ice concentration assimilation can help to get better modeled ice concentration and ice extent. All the biases of ice concentration, ice cover, ice volume, and ice thickness can be reduced dramatically through ice concentration and thickness assimilation. The near-real-time forecast results indicate that ice data assimilation can improve the forecast skill significantly in the FIO-ESM climate forecast system. The forecasted Arctic integrated ice edge error is reduced by around 1/3 by sea ice data assimilation. Compared with the six near-real-time Arctic sea ice forecast results from the subseasonal-to-seasonal (S2S) Prediction Project, FIO-ESM climate forecast system with LESTKF ice data assimilation has relatively high Arctic sea ice forecast skill in 2018 summer sea ice forecast. Since sea ice thickness in the PIOMAS is updated in time, it is a good choice for data assimilation to improve sea ice prediction skills in the near-real-time Arctic sea ice seasonal prediction.  相似文献   

12.
We introduced the Coupled Model Intercomparison Project Phase 6 (CMIP6) Ocean Model Intercomparison Project CORE2-forced (OMIP-1) experiment by using the First Institute of Oceanography Earth System Model version 2.0 (FIO-ESM v2.0), and comprehensively evaluated the simulation results. Unlike other OMIP models, FIO-ESM v2.0 includes a coupled ocean surface wave component model that takes into account non-breaking surface wave-induced vertical mixing in the ocean and effect of surface wave Stokes drift on air-sea momentum and heat fluxes in the climate system. A sub-layer sea surface temperature (SST) diurnal cycle parameterization was also employed to take into account effect of SST diurnal cycle on air-sea heat ?uxes to improve simulations of air-sea interactions. Evaluations show that mean values and long-term trends of significant wave height were adequately reproduced in the FIO-ESM v2.0 OMIP-1 simulations, and there is a reasonable fit between the SST diurnal cycle obtained from in situ observations and that parameterized by FIO-ESM v2.0. Evaluations of model drift, temperature, salinity, mixed layer depth, and the Atlantic Meridional Overturning Circulation show that the model performs well in the FIO-ESM v2.0 OMIP-1 simulation. However, the summer sea ice extent of the Arctic and Antarctic is underestimated.  相似文献   

13.
王坤  毕海波  黄珏 《海洋科学》2022,46(4):44-54
北极海冰作为一个巨大的淡水资源库, 每年向全球输送大量淡水资源, 从北极输出的海冰在向南输送的过程中融化, 对海洋水循环与水环境产生影响, 进而影响全球气候变化, 弗雷姆海峡作为北极海冰输出的主要通道, 对其研究显得尤为重要。为了解弗雷姆海峡海冰长期输出量, 利用美国冰雪数据中心(NSIDC)发布的海冰密集度、海冰厚度与海冰漂移速度数据, 计算得到 1979 年至 2019 年弗雷姆海峡海冰输出面积通量与 2010 至 2019 年弗雷姆海峡海冰输出体积通量, 并在此基础上分析弗雷姆海峡近 40 a 海冰输出量的变化状况以及弗雷姆海峡海冰输出的年际变化、季节变化, 并分析了影响弗雷姆海峡海冰输出量的可能原因。结果表明: 近 40 a 弗雷姆海峡年均海冰输出面积通量为 7.83×105 km2,近 10 a 弗雷姆海峡海冰年均输出体积通量为 1.34×106 km3, 从长期来看, 弗雷姆海峡海冰输出面积通量呈略微增加趋势, 弗雷姆海峡海冰输出体积通量在 2010—20...  相似文献   

14.
李淑瑶  崔红艳 《海岸工程》2022,41(2):162-172
基于北极海冰密集度、海冰范围、大气环流和海温数据,研究了1982—2001年与2002—2021年两阶段各20 a间北极秋季海冰的时空变化特征及其原因。结果表明,近20 a(2002—2021年)北极海冰密集度的下降中心由过去(1982—2001年)的楚科奇海及白令海峡一带,转移至亚欧大陆海岸的巴伦支海附近,且海冰范围每10 a减少量由0.44×106 km2增长至0.72×106 km2,减少速度加快约64%。秋季北极海冰范围与海水表面温度(Sea Surface Temperature,SST)、表面气温(Surface Air Temperature,SAT)及比湿(Specific Humidity)均呈显著负相关。2002—2021年的相关系数较1982—2001年有所提高,且与温度相关系数最高的月份提前了一个月。通过对海水表面温度、表面气温、比湿、气压场和风场的经验正交分解(Empirical Orthogonal Function,EOF)可知,1982—2001年间,北极地区的温度及比湿的上升中心集中在楚科奇海及白令海峡一带;2002—2021年间,上升中心则转移至巴伦支海一带。气压场和风场在前后两阶段也出现了中心转移的分布变化。北极地区大气与海洋环流各因素的协同变化影响着北极海冰的消融。  相似文献   

15.
基于AMSR-E数据的多年冰密集度反演算法研究   总被引:2,自引:1,他引:1  
In recent years, the rapid decline of Arctic sea ice area(SIA) and sea ice extent(SIE), especially for the multiyear(MY) ice, has led to significant effect on climate change. The accurate retrieval of MY ice concentration retrieval is very important and challenging to understand the ongoing changes. Three MY ice concentration retrieval algorithms were systematically evaluated. A similar total ice concentration was yielded by these algorithms, while the retrieved MY sea ice concentrations differs from each other. The MY SIA derived from NASA TEAM algorithm is relatively stable. Other two algorithms created seasonal fluctuations of MY SIA, particularly in autumn and winter. In this paper, we proposed an ice concentration retrieval algorithm, which developed the NASA TEAM algorithm by adding to use AMSR-E 6.9 GHz brightness temperature data and sea ice concentration using 89.0GHz data. Comparison with the reference MY SIA from reference MY ice, indicates that the mean difference and root mean square(rms) difference of MY SIA derived from the algorithm of this study are 0.65×106 km2 and0.69×106 km2 during January to March, –0.06×106 km2 and 0.14×106 km2 during September to December respectively. Comparison with MY SIE obtained from weekly ice age data provided by University of Colorado show that, the mean difference and rms difference are 0.69×106 km2 and 0.84×106 km2, respectively. The developed algorithm proposed in this study has smaller difference compared with the reference MY ice and MY SIE from ice age data than the Wang's, Lomax' and NASA TEAM algorithms.  相似文献   

16.
Though narrow straits may have a strong influence on the large-scale sea ice mass balance, they are often crudely represented in coarse resolution sea ice models. Unstructured meshes, with their natural ability to fit boundaries and locally increase the mesh resolution, propose an alternative framework to capture the complex oceanic areas formed by coasts and islands. In this paper, we develop a finite element sea ice model to investigate the sensitivity of the Arctic sea ice cover features to the resolution of the narrow straits constituting the Canadian Arctic Archipelago. The model is a two-level dynamic-thermodynamic sea ice model, including a viscous-plastic rheology. It is run over 1979–2005, forced by daily NCEP/NCAR reanalysis data. Confronting qualitatively numerical experiments with observations shows a good agreement with satellite and buoys measurements. Due to its simple representation of the oceanic interactions, the model overestimates the sea ice extent during winter in the southernmost parts of the Arctic, while the Baffin Bay and Kara Sea remain ice-covered during summer. In order to isolate the benefits from resolving the Canadian Arctic Archipelago, a numerical experiment is performed where we artificially close the archipelago. Focusing on the large-scale sea ice thickness pattern, no significant change is found in our model, except in the close surroundings of the archipelago. However, the local and short-term influences of the ice exchanges are nonnegligible. In particular, we show that the ice volume associated to the Canadian Arctic Archipelago represents 10% of the Northern Hemisphere sea ice volume and that the annual mean ice export towards Baffin Bay amounts to 125 km3 yr−1, which may play an important role on the convective overturning in the Labrador Sea.  相似文献   

17.
Arctic sea ice extent has been declining in recent decades. There is ongoing debate on the contribution of natural internal variability to recent and future Arctic sea ice changes. In this study, we contrast the trends in the forced and unforced simulations of carefully selected global climate models with the extended observed Arctic sea ice records. The results suggest that the natural variability explains no more than 42.3% of the observed September sea ice extent trend during 35 a(1979–2013) satellite observations, which is comparable to the results of the observed sea ice record extended back to 1953(61 a, less than 48.5% natural variability). This reinforces the evidence that anthropogenic forcing plays a substantial role in the observed decline of September Arctic sea ice in recent decades. The magnitude of both positive and negative trends induced by the natural variability in the unforced simulations is slightly enlarged in the context of increasing greenhouse gases in the 21st century.However, the ratio between the realizations of positive and negative trends change has remained steady, which enforces the standpoint that external forcing will remain the principal determiner of the decreasing Arctic sea ice extent trend in the future.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号