Modeling of Arctic Sea Ice Variability During 1948–2009: Validation of Two Versions of the Los Alamos Sea Ice Model(CICE)

The Los Alamos sea ice model(CICE) is used to simulate the Arctic sea ice variability from 1948 to 2009. Two versions of CICE are validated through comparison with Hadley Centre Global Sea Ice and Sea Surface Temperature(Had ISST) observations. Version 5.0 of CICE with elastic-viscous-plastic(EVP) dynamics simulates a September Arctic sea ice concentration(SASIC) trend of –0.619 × 1012 m2 per decade from 1969 to 2009, which is very close to the observed trend(-0.585 × 1012 m2 per decade). Version 4.0 of CICE with EVP dynamics underestimates the SASIC trend(-0.470 × 1012 m2 per decade). Version 5.0 has a higher correlation(0.742) with observation than version 4.0(0.653). Both versions of CICE simulate the seasonal cycle of the Arctic sea ice, but version 5.0 outperforms version 4.0 in both phase and amplitude. The timing of the minimum and maximum sea ice coverage occurs a little earlier(phase advancing) in both versions. Simulations also show that the September Arctic sea ice volume(SASIV) has a faster decreasing trend than SASIC.

Advantages of the latest Los Alamos Sea-Ice Model(CICE):evaluation of the simulated spatiotemporal variation of Arctic sea ice

The Los Alamos Sea-Ice Model(CICE)is one of the most popular sea-ice models.All versions of it have been the main sea-ice module coupled to climate system models.Therefore,evaluating their simulation capability is an important step in developing climate system models.Compared with observations and previous versions(CICE4.0 and CICE5.0),the advantages of CICE6.0(the latest version)are analyzed in this paper.It is found that CICE6.0 has the minimum interannual errors,and the seasonal cycle it simulates is the most consistent with observations.CICE4.0 overestimates winter sea-ice and underestimates summer sea-ice severely.Meanwhile,the errors of CICE5.0 in winter are larger than for the other versions.The main attention is paid to the perennial ice and the seasonal ice.The spatial distribution of root-mean-square errors indicates that the simulated errors are distributed in the Atlantic sector and the outer Arctic.Both CICE4.0 and CICE5.0 underestimate the concentration of the perennial ice and overestimate that of the seasonal ice in these areas.Meanwhile,CICE6.0 solves this problem commendably.Moreover,the decadal trends it simulates are comparatively the best,especially in the central Arctic sea.The other versions underestimate the decadal trend of the perennial ice and overestimate that of the seasonal ice.In addition,an index used to objectively describe the difference in the spatial distribution between the simulation and observation shows that CICE6.0 produces the best simulated spatial distribution.

黑碳对北冰洋积雪和海冰影响的模拟研究

当黑碳沉降到冰雪表面时,可使冰雪表面反照率降低,对短波辐射的吸收增加,黑碳的变化对海冰融化过程的影响值得研究。本文利用CICE海冰模式进行数值模拟,并定量分析北冰洋冰雪中黑碳造成的影响。研究表明,在不同黑碳数据源的强迫下,1980-2014年间,模拟结果给出的夏季北冰洋反照率平均下降为0.82%~1.71%,最终造成海冰面积下降了0.97%~1.93%,而在巴伦支海、喀拉海以及拉普捷夫海,夏季黑碳造成的海冰面积下降约为北冰洋整体的2-3倍。不同黑碳沉降强迫下的模拟结果均显示,1980-1995年,北冰洋区域黑碳对反照率的影响呈现减小趋势,但在1996-2014年,黑碳影响转为增加趋势。在低纬度海区,由于海冰的消退,黑碳的辐射效应呈现减小趋势,而在高纬度海区,由于多年冰内黑碳的累积效应,黑碳的辐射影响呈现增强效应。

CICE海冰模式中反照率相关参数对北极海冰模拟的影响

国家气候中心气候系统模式BCC_CSM2.0最新耦合了美国Los Alamos国家实验室发展的海冰模式CICE5.0,为试验模式中与反照率相关参数的敏感性及其对模拟结果的影响,提高模式对北极海冰的模拟能力,选取海冰模式中3个主要参数进行了敏感性试验。利用以BCC_CSM2.0耦合框架为基础建立的海冰-海洋耦合模式,选取CORE资料为大气强迫场开展试验,试验的3个参数分别为冰/雪表面反射率、雪粒半径和雪粒半径参考温度。结果表明,参数取值的不同对北极海冰的模拟有显著的影响,优化后的取值组合极大提高了模式的模拟能力,主要表现在:(1)改善了对北极冬季海冰厚度的模拟,海冰厚度增大,与观测资料更为吻合;(2)显著提高了对北极夏季海冰密集度的模拟能力,从而模拟的北极海冰范围年际循环与观测更为一致。参数取值的优化改进了模式对海冰反照率的模拟,进而影响了冰面短波辐射的吸收和海冰表层的融化,最终提高了模式对海冰密集度和厚度的模拟效果。

CICE海冰模式中融池参数化方案的比较研究

冰面融池的反照率介于海水和海冰之间,获得较准确的融池覆盖率对认识极区气冰海耦合系统的热量收支有重要意义。在数值模式中,融池覆盖率的模拟结果直接影响到冰面反照率计算的准确性,本文对CICE5.0中的3种融池参数化方案进行了较系统的比较分析,结果显示3种方案各有优缺点,模拟结果都存在一些问题。cesm方案中判断融池冻结的条件更为合理。比较而言,融池冻结条件更改后的topo方案模拟的北冰洋区域平均融池覆盖率的年际变化幅度、融池覆盖范围、融池发展盛期持续时间与MODIS数据最接近。通过修改CICE5.0中的代码漏洞,研究了融池水的垂向渗透效应,这一效应会带来一些负面影响,如lvl方案中多年冰上几乎没有融池,说明目前的CICE模式中对于海冰渗透性演化或其他物理机制的处理仍有待改进。最后,着重讨论了topo方案的改进思路。

白令海冰间湖的数值模拟及影响模拟准确度的关键因素

冬季在北白令海陆架区域频繁地出现潜热冰间湖,对当地的生态系统和北极盐跃层贡献很大。将CICE海冰模式应用到该区域,采用高分辨率(6.37 km)网格,模拟2002年11月至2003年4月的海冰变化过程,模拟的海冰总面积和海冰密集度与AMSR-E/Aqua卫星遥感结果吻合很好,其中两者日平均海冰总面积在模拟期间的相关系数达到0.97。模拟结果表明,东北风将海冰向南输运在东西走向的海岸南部形成冰间湖,反映了潜热冰间湖形成和演化的动力过程。对卫星观测数据,将海冰密集度<75%作为冰间湖的判据;而对数值模拟结果,确定海冰密集度<70%为冰间湖的判据。据此讨论白令海4个区域的冰间湖形成过程,与卫星数据进行比较,大部分冰间湖得到很好的模拟。深入讨论了影响冰间湖模拟准确度的主要因素,认为选用恰当的阈值、提高气象强迫场的空间和时间分辨率有助于提高模拟效果。对部分海域的冰间湖模拟效果不佳,需要发展冰海耦合模式才能最终解决。