基于CryoSat-2卫星测高数据的北极海冰体积估算方法

近30年来,北极海冰正发生着剧烈的变化。海冰体积是量化海冰变化的重要指标之一。本文以2015年CryoSat-2卫星测高数据和OSI SAF海冰类型产品为基础。提取了浮冰出水高度、积雪深度、海冰密集度、海冰类型等属性信息,通过数据内插、投影变换、栅格转换、空间重采样等工作将海冰属性信息统一为25 km×25 km分辨率的栅格数据集。根据流体静力学平衡原理,逐个估算栅格像元对应的海冰厚度值,将其与对应的海冰面积相乘,估算了北极海冰密集度大于75%海域的海冰体积,并分析了海冰厚度和体积的月变化和季节变化特征。用NASA IceBridge海冰厚度产品对反演的海冰厚度进行验证。结果表明二者相关系数为0.72,有较高的一致性。北极海冰平均厚度春季最大,夏季最小,分别约为2.99 m和1.77 m,最厚的海冰集中在格陵兰沿岸北部和埃尔斯米尔半岛以北海域。多年冰平均厚度大于一年冰。冬季海冰体积最大,约为23.30×103 km3,经过夏季的融化,减少了近70%。一年冰体积季节波动较大,而多年冰体积相对稳定,季节变化不明显。     

海水物质平衡浮标对北冰洋中心区海冰温度与物质平衡的观测

利用中国第3次北极科学考察所布放海冰物质平衡浮标(Ice Mass-Balance buoy,IMB)的观测数据,分析了北冰洋中心区多年冰2008年8月-2009年7月温度与物质平衡的变化特征.结果表明,冰温廓线呈现明显的季节变化,秋季降温过程从海冰表面开始向冰体内部传播.海冰底部的生长/消融率受海水温度控制,随水温的...     

长序列北极海冰覆盖数据集对比分析

国家卫星气象中心使用2011年至今的风云三号卫星数据开发了一套基于Nasa Team2（NT2）算法的北极海冰密集度数据集，并可实时业务更新。将该数据集与其他国家不同机构业务运行并实时更新多种同类型数据集进行横向对比分析，其中包括:（1）美国冰雪中心基于Nasa Team（NT）算法以及SSM/I、SSMIS数据制作的1978年至今25 km分辨率全球极区海冰覆盖数据集；（2）美国冰雪中心基于Boot Strap（BS）算法以及SSM/I、SSMIS数据制作的1978年至今25 km分辨率全球极区海冰覆盖数据集；（3）美国NOAA基于多种卫星资料、地面观测数据以及海冰模型制作的2004年至今4 km分辨率北半球海冰覆盖数据集（IMS）。对比表明，上述数据集在北极地区不同的时空范围内存在一定的偏差。以分辨率较高的IMS数据集为基准，对其他3种长序列数据集进行初步评价，总体最大偏差超过100×104 km2，其中，NT2数据集过估较明显。经过与IMS数据集多年各月监测最大值的对比订正，NT2数据集过估情况得到改善。在此基础上的分析结果表明，NT、BS、NT2等3种数据集与IMS数据集相比，过估区域主要分布在海岸线附近，夏季过估比冬季更加明显，少估区域与算法、月份相关性明显，夏季少估面积也较冬季更大。NT、BS、NT2等3种数据集之中，NT2数据集与IMS数据集偏差最小，NT数据集次之，BS数据集与IMS数据集偏差最大。结果表明使用风云三号卫星数据的北极海冰覆盖数据集精度与国外3种同类型数据集相当。     

北极冬季季节性海冰双模态特征分析

近年来北极海冰快速变化,北极中央区边缘正由以多年冰为主转为季节性海冰为主。通过对北极冬季季节性海冰的EOF分解发现,2002-2012年期间北极季节性海冰变化的前两模态主要体现为2005年和2007年的季节性海冰距平。其中第二模态主要体现了北极海冰在2005年的一种极端变化,而第一模态不仅体现了北极海冰在2007年的变化,还体现了北极季节性海冰的从负位相到正位相的转变。通过比较发现,在研究时段北极季节性海冰最主要的变化发生在北极太平洋扇区,在2007年,冬季季节性海冰距平发生位相转变,2007-2010年一直维持正位相,北极太平洋扇区冬季季节性海冰保持显著正距平。太平洋扇区表面温度最大异常也发生在2007年,从大气环流来看,2007年之后波弗特海区异常高压有利于夏季太平洋扇区海冰的减少,而西风急流的减弱有利于夏季波弗特海区异常高压的维持,结合夏季海冰速度,顺时针的冰速分布有利于海冰离开太平洋扇区,因而会导致冬季太平洋扇区季节性海冰转为正距平并且从2007年一直维持到2010年。     

利用卫星遥感和再分析数据刻画2017-2018年格陵兰北部罕见冰间湖事件

以90%海冰密集度为阈值，基于卫星遥感数据，2017-2018年冰季在格陵兰北部识别了两次冰间湖事件，分别出现在冬季和夏季。冬季的冰间湖事件从2018年2月20日持续至3月3日，夏季的事件从8月2日持续到9月5日。AMSR2被动微波的海冰密集度产品表明，冬季和夏季冰间湖事件对应的最低海冰密集度分别为72%和65%。两次冰间湖事件都与格陵兰北部东西气压梯度异常引起的南风加强有关，而气压梯度的异常则与对流层中部极涡的扰动有关。冬季冰间湖事件期间，相对暖和的气温和频繁出现的冰间湖，导致冬季海冰生长不持续，海冰热力增厚较小，这为夏季海冰发生破碎并形成冰间湖创造了条件。南风减弱和新冰生成是冬季冰间湖消失的主要原因。对于夏季的冰间湖，导致其消失的主要原因则是从北部输入的浮冰增加。Sentinel-1 合成孔径雷达产品相对AMSR2被动微波观测产品更加适合于应用到冰间湖事件伴随的新冰生长，这与前者具有更高的空间分辨率有关。格陵兰北部是北冰洋多年冰的聚集地，该区域被认为是北冰洋海冰的“避难所”。因此区域在2017-2018年出现罕见的冰间湖事件，对于整个北冰洋海冰的快速减少具有重要意义，也助于北冰洋海冰，尤其是多年冰的消退。     

基于CryoSat-2数据的2010-2017年北极海冰厚度和体积的季节与年际变化特征

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。     

北极海冰漂移对多年冰分布的影响研究

本文基于美国冰雪数据中心(NSIDC)提供的海冰漂移和冰龄数据,分析了1985-2014年北极海冰漂移场的主要模态和多年冰的分布特征,初步评估了海冰漂移对多年冰分布的影响。多年冰面积序列的小波变换结果显示多年冰面积的显著周期为1年和5年,其中5年周期在2007年之后变得显著。海冰漂移速度的经验正交分解的冬季第一模态向穿极流模态的转化,穿极流模态在30年间方差贡献率的逐步上升,穿极流态流轴位置的偏移与多年冰的分布在三个年代相吻合,揭示了二者的密切关系。波弗特海域在三个10年间速度趋势的上升,对于多年冰的输运起到了重要的作用。从三个时间段冬夏两季速度的变化来看,冬季是海冰漂移速度增加的主要时期,与该海域内多年冰面积的下降形成了正反馈关系。     

北极海冰输出区域海冰运动变化特征及其与北极航道适航性的关系

随着北极地区气候变暖的加剧，北极海冰正在急剧消融，海冰的减少增加了北极地区航道的适航性。本文利用遥感数据反演得到的海冰运动产品对北极海冰输出区域以及东北航道以北区域的海冰运动特征进行了量化。结果显示，从北极中央海域向弗拉姆海峡以及格陵兰海流出海冰的南向位移量呈现出显著增长趋势，海冰的平均南向位移量在2007-2014年间达到1511 km，是2007年之前（617 km）的两倍以上，反映了北极穿极流（TDS）强度在不断增强。通过长时间序列分析发现，春季东北航道以北区域的海冰北向漂移速度在喀拉海呈现+0.04 厘米/秒/年的显著增长趋势（P<0.05）。海冰北向漂移对于东北航道的开通具有显著的影响，在拉普捷夫海与喀拉海，海冰北向运动速度与航道适航期的决定系数分别达到0.33（P<0.001）和0.15（P<0.05）。东西伯利亚海、拉普捷夫海以及喀拉海存在冰间湖区域的春季海冰面积变化与航道的适航期密切相关，海冰的北向漂移对拉普捷夫海和喀拉海的海冰面积减少也有显著影响，这说明北向漂移促进了海冰的离岸输送，造成海冰面积减少的同时形成冰间水道或冰间湖促使航道开通。为探究大气环流指数对海冰运动以及东北航道适航期的影响，本文利用大气再分析数据计算了中央北极指数（CAI）和北极大气偶极子异常（DA）指数。相关性分析表明，CAI比DA更能解释东北航道的适航期，而且CAI能够解释北极海冰输出区域海冰南向位移量变化的45%。最近10年，夏季正相位的CAI进一步加强，通过加强海冰离岸输运和冰间湖活动加剧了东北航道区域海冰变薄及其强度变弱，从而促进了东北航道的开通。     

变暖背景下北极海冰减少在冬季北半球高纬大陆降雪增加中的作用

过去的几个冬季中,北美、欧洲、西伯利亚和东亚大部分地区经历了冷冬和强降雪,而这与北极海冰的快速减少有关。尽管北极海冰减少在冷冬和强降雪中的作用仍存在争议,但这种新兴的气候反馈在未来变暖背景下是否会持续仍值得关注。中等排放情境下的气候模式模拟结果揭示,欧洲东北部、亚洲中部北部、北美北部的冬季降雪增加会成为贯穿21世纪的一个稳健的特征。21世纪这些区域冬季降雪增加的主要原因是北极秋季海冰的减少（很大的外部强迫）,而冬季北极涛动的变化（北半球主要的自然变化形态）对降雪增加的作用很小。这一结果不仅体现在多模式平均上,而且每个单独模式的结果依然如此。我们认为海冰-降雪之间的强反馈作用可能已经出现,并且在接下来的几十年中这种强反馈作用可能会增强,北半球高纬地区的强降雪事件也会增加。     

地球系统模式FIO-ESM对北极海冰的模拟和预估

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。     

Recent satellite-derived sea ice volume flux through the Fram Strait: 2011–2015

The Fram Strait(FS) is the primary region of sea ice export from the Arctic Ocean and thus plays an important role in regulating the amount of sea ice and fresh water entering the North Atlantic seas. A 5 a(2011–2015) sea ice thickness record retrieved from Cryo Sat-2 observations is used to derive a sea ice volume flux via the FS. Over this period, a mean winter accumulative volume flux(WAVF) based on sea ice drift data derived from passivemicrowave measurements, which are provided by the National Snow and Ice Data Center(NSIDC) and the Institut Francais de Recherche pour d'Exploitation de la Mer(IFREMER), amounts to 1 029 km~3(NSIDC) and1 463 km~3(IFREMER), respectively. For this period, a mean monthly volume flux(area flux) difference between the estimates derived from the NSIDC and IFREMER drift data is –62 km~3 per month(–18×10~6 km~2 per month).Analysis reveals that this negative bias is mainly attributable to faster IFREMER drift speeds in comparison with slower NSIDC drift data. NSIDC-based sea ice volume flux estimates are compared with the results from the University of Bremen(UB), and the two products agree relatively well with a mean monthly bias of(5.7±45.9) km~3 per month for the period from January 2011 to August 2013. IFREMER-based volume flux is also in good agreement with previous results of the 1990 s. Compared with P1(1990/1991–1993/1994) and P2(2003/2004–2007/2008), the WAVF estimates indicate a decline of more than 600 km~3 in P3(2011/2012–2014/2015). Over the three periods, the variability and the decline in the sea ice volume flux are mainly attributable to sea ice motion changes, and second to sea ice thickness changes, and the least to sea ice concentration variations.     

1982—2001年与2002—2021年北极秋季海冰的时空变化及原因

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。     

A Coupled Ice-Ocean Model in the Pan-Arctic and North Atlantic Ocean: Simulation of Seasonal Cycles

A coupled ice-ocean model is configured for the pan-Arctic and northern North Atlantic Ocean with a 27.5 km resolution. The model is driven by the daily atmospheric climatology averaged from the 40-year NCEP reanalysis (1958–1997). The ocean model is the Princeton Ocean Model (POM), while the sea ice model is based on a full thermodynamical and dynamical model with plastic-viscous rheology. A sea ice model with multiple categories of thickness is utilized. A systematic model-data comparison was conducted. This model reasonably reproduces seasonal cycles of both the sea ice and the ocean. Climatological sea ice areas derived from historical data are used to validate the ice model performance. The simulated sea ice cover reaches a maximum of 14 × 10⁶ km² in winter and a minimum of 6.7 × 10⁶ km² in summer. This is close to the 95-year climatology with a maximum of 13.3 × 10⁶ km² in winter and a minimum of 7 × 10⁶ km² in summer. The simulated general circulation in the Arctic Ocean, the GIN (Greenland, Iceland, and Norwegian) seas, and northern North Atlantic Ocean are qualitatively consistent with historical mapping. It is found that the low winter salinity or freshwater in the Canada Basin tends to converge due to the strong anticyclonic atmospheric circulation that drives the anticyclonic ocean surface current, while low summer salinity or freshwater tends to spread inside the Arctic and exports out of the Arctic due to the relaxing wind field. It is also found that the warm, saline Atlantic Water has little seasonal variation, based on both simulation and observations. Seasonal cycles of temperature and salinity at several representative locations reveals regional features that characterize different water mass properties.     

对地球系统模式FIO-ESM同化实验中北极海冰模拟的评估

本文评估了地球系统模式FIO-ESM(First Institute of Oceanography-Earth System Model)基于集合调整Kalman滤波同化实验对1992-2013年北极海冰的模拟能力。结果显示:尽管同化资料只包括了全球海表温度和全球海面高度异常两类数据,而并没有对海冰进行同化,但实验结果能很好地模拟出与观测相符的北极海冰基本态和长期变化趋势,卫星观测和FIO-ESM同化实验所得的北极海冰覆盖范围在1992-2013年间的线性变化趋势分别为-7.06×105和-6.44×105 km2/(10a),同化所得的逐月海冰覆盖范围异常和卫星观测之间的相关系数为0.78。与FIO-ESM参加CMIP5(Coupled Model Intercomparison Project Phase 5)实验结果相比,该同化结果所模拟的北极海冰覆盖范围的长期变化趋势和海冰密集度的空间变化趋势均与卫星观测更加吻合,这说明该同化可为利用FIO-ESM开展北极短期气候预测提供较好的预测初始场。     

基于遥感数据的近40 a弗雷姆海峡海冰输出研究

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...     

The effects of resolving the Canadian Arctic Archipelago in a finite element sea ice model

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.     

基于AMSR-E数据的多年冰密集度反演算法研究

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.     

Arctic sea ice volume export through the Fram Strait from combined satellite and model data: 1979–2012

By combing satellite-derived ice motion and concentration with ice thickness fields from a popular model PIOMAS we obtain the estimates of ice volume flux passing the Fram Strait over the 1979–2012 period. Since current satellite and field observations for sea ice thickness are limited in time and space, the use of PIOMAS is expected to fill the gap by providing temporally continued ice thickness fields. Calculated monthly volume flux exhibits a prominent annual cycle with the peak record in March(roughly 145 km3/month) and the trough in August(10 km~3/month). Annual ice volume flux(1 132 km~3) is primarily attributable to winter(October through May) outflow(approximately 92%). Uncertainty in annual ice volume export is estimated to be 55 km~3(or 5.7%). Our results also verified the extremely large volume flux appearing between late 1980 s and mid-1990 s. Nevertheless, no clear trend was found in our volume flux results. Ice motion is the primary factor in the determination of behavior of volume flux. Ice thickness presented a general decline trend may partly enhance or weaken the volume flux trend. Ice concentration exerted the least influences on modulating trends and variability in volume flux. Moreover, the linkage between winter ice volume flux and three established Arctic atmospheric schemes were examined. Compared to NAO, the DA and EOF3 mechanism explains a larger part of variations of ice volume flux across the strait.