利用热动力模式模拟1979～1998年北极海冰流出量的变化

本文利用一个Hibler海冰热动力模式。在改进了其热力部分和改变模拟范围以及提高分辨率的基础上,以北极国际浮标计划（IABP）提供的1979～1998年逐日变化的日平均海平面气温场、湿度场、长短波辐射场、风场、洋流场、海洋热流量场为强迫场,模拟了20a北极海冰的流出量。流出量有明显的季节及年际变化,冬、秋季流出量比春、夏季多。与卫星资料反演的流出量相比,冬季海冰面积流出量,反演值小于模拟值,全年则是模拟值小于反演值。     

北极多冰年和少冰年的大气环流差异

本文利用一个改进的海冰热力模式,取北极区大气和有关场的气候资料,模拟了1982年10月至1988年9月的北极海冰空间分布和季节变化的循环特征,较好地模拟出多冰年（1983,1987）和少冰年（1984,1986）。模拟结果与部分研究工作以及实况相比较,基本状况趋于一致。并且在此基础上进一步探讨了北极多冰年和少冰年的大气环境差异,可以看到多冰年的北极极涡偏西半球;少冰年的北极极涡基本是围绕极地。从而进一步影响多冰年和少冰年大气环流差异,特别是对亚洲环流的影响较大。     

渤海海冰单点模式的气候模拟

利用PW1979海冰热力模式，考虑渤海的地理特点和气候特征，假设渤海为薄层海洋，引入二分法求解海冰表面温度。用该地区气候平均的云量、湿度、海平面气压和风速以及附近4站的月平均气温资料作为强迫场，模拟了渤海海冰的气候变化。模拟结果与逐年的海冰级数资料具有一致的变率，表明气温对海冰年际变化有重要影响。     

渤海海冰数值模式的研究进展

根据渤海海冰冰情,从热力和动力两个方面综述了渤海海冰数值模式的研究进展。从热力参数方案和气候特点上,展望新一代渤海中小尺度短期海冰热力模式;从海冰动力模式中3种常用数值方法的主要特点和实际应用情况上,论述SPH(Smoothed Particle Hydrodynamics)方法在渤海海冰短期预报的发展前景。在此基础上,结合海洋气象的发展,讨论海冰短期预报的关键技术。将海冰数值预报模式与传统的中长期海冰统计预报有机地结合起来将是渤海海冰模式未来的发展方向。     

适应极地快速变化海冰模式的研发与挑战

极地海冰是地球气候系统的重要组成部分,也是气候环境变化的指示器和放大器。极地海冰复杂的多尺度物理过程和极地观测资料的匮乏,给海冰模式的研发带来了巨大的挑战。在过去的半个多世纪中,大气-海冰-海洋的复杂相互作用和冰内物理过程在海冰模式中的数学描述取得了重大的进展,但海冰模式对一些重要物理过程的描述仍很不完善,尤其是近年来极地海冰的快速变化及其物理特性的变化,极大地增加了海冰模式物理参数化方案和模拟结果的不确定性。因此,迫切需要具备完善物理过程、适应海冰多尺度快速变化的高分辨率海冰模式,并应用于全球气候变化的研究和预测以及极地的开发利用。本文从海冰模式的发展历程和现状、极地海冰快速变化给海冰模式带来的挑战以及适应极地快速变化海冰模式的改进和发展研究方向三个方面进行了阐述和讨论。     

近年来国外海冰模式发展的回顾

海冰是气候系统中的重要成员，而海冰模式是描述海冰物理过程、模拟和预报海冰演变的有力工具。根据国外发表的文献，对海冰模式从动力学、热力学和厚度分布三个方面的研究进行了回顾，对海冰模拟的研究具有一定的借鉴作用。     

海冰模式CICE4.0与LASG/IAP气候系统模式的耦合试验

利用美国Los Alamos国家实验室发展的最新海冰模式(CICE4.0)替代了LASG/IAP气候系统模式(FGOALS_g1.1)中的海冰模式(CSIM4), 形成新的耦合模式。在此基础上, 利用新的耦合模式对20世纪中后期的全球气候进行了模拟, 来检验CICE4.0对耦合模式中海冰和海洋模拟结果的改进。结果表明CICE4.0对于FGOALS_g1.1的极地气候模拟有一定改进作用, 主要表现在:(1) 南北极海冰边缘碎冰区显著减少; (2) 南大洋海表温度和海冰的模拟明显改善, 分布特征与观测非常吻合。但是新耦合模式也存在如下不足: (1) 北大西洋海冰相对偏多, 北大西洋经圈翻转环流大大减弱, 这主要是由于北大西洋海表面温度的冷误差造成的; (2) 南北极大气环流场的模拟无明显改善。此外, 本文还比较了采用不同短波辐射方案对于耦合模拟结果的影响, 结果表明, 相对于CCSM3短波辐射方案, Delta-Eddington方案模拟的海表面温度偏冷, 海冰厚度偏厚, 北大西洋经圈翻转环流略有偏弱。     

BCC_CSM北极海冰模拟性能的改进对东亚冬季气候模拟的影响

国家气候中心气候系统模式(BCC_CSM)将美国Los Alamos国家实验室发展的海冰模式CICE5.0替代原有的海冰模式SIS,形成一个新版本耦合模式,很好地提高了模式对北极海冰和北极气候的模拟能力。在此基础上,本文评估新耦合模式对1985—2014年东亚冬季气候的模拟性能,检验北极海冰模拟性能的改进对东亚冬季气候模拟性能的影响。结果表明,引入CICE5.0后,新耦合模式能较好地模拟出东亚冬季海平面气压、850 hPa风场以及辐射通量,进而改善东亚气温以及降水的气候态空间分布模拟效果。进一步分析发现,与原有耦合模式相比,新耦合模式更好地抓住了东亚冬季海平面气压、总降水量和气温异常对同期巴伦支海-喀拉海海冰密集度异常的响应,进而提高了模式对东亚冬季中高纬度地区气温以及降水变率的模拟能力。     

BCC_CSM对全球海冰面积和厚度模拟及其误差成因分析

本文评估了国家气候中心发展的BCC_CSM模式对全球海冰的模拟能力,结果表明:该气候系统模式能够较好地模拟出全球海冰面积和厚度的时空分布特征,且南半球海冰模拟能力优于北半球。通过对比分析发现:年平均海冰面积模拟误差最大的区域位于鄂霍次克海、白令海和巴伦支海等海区,年平均海冰厚度分布与观测相近,在北半球冬季模拟的厚度偏薄;从海冰季节变化来看,模拟的夏季海冰面积偏低,冬季偏高;从海冰年际变化来看,近60年南北半球海冰面积模拟都比观测偏多,但南半球偏多幅度较小,然而北半球海冰年际变化趋势的模拟却好于南半球。另外,通过对海冰模拟误差成因分析,发现模拟的净辐射能量收入偏低使得海温异常偏冷,是导致北半球冬季海冰模拟偏多的主要原因。     

北极海冰数值预报的初步研究——基于海冰—海洋耦合模式MITgcm的模拟试验

利用最近发展的MITgcm(麻省理工学院通用环流模式)海冰-海洋耦合模式,以NCEP(美国国家环境预测中心)再分析资料为大气强迫场进行了1992年1月至2009年12月北极海冰数值模拟.结果表明,此模式能很好地模拟卫星观测的北极海冰季节和年际变化,具备很好的北极海冰数值模拟能力.以此为基础,对2009年7月和10月北极...     

SIMULATION ON CLIMATIC VARIATION OF ARCTIC SEA ICE THROUGH AN ICE-OCEAN COUPLED MODEL*

An ocean model developed by the Institute of Marine Research and the University of Bergen in Norway (BOM) and a state-of-the-art sea ice model developed by NCAR (CSIM4) are coupled, Considering influences of 9 major rivers,forced by the NCEP reanalysis atmospheric fields and the Levitus surface salinity,the Arctic sea ice climatic variation from January 1949 to December.1999 was simulated through the coupled model.The comparison of simulated results and observations shows that:(1)the long-term ice concentration variation tendencies are in consistent with the observations in the divisional ocean regions;(2)simulated ice thickness horizontal distribution is reasonable.Simulated ice thickness has a decreasing tendency in the central Arctic,which agrees with the submarine observations.Simulated annually maximum ice thickness is highly related to observed fast-ice thickness off the Russian coast;and (3)sea ice area/volume fluxes through the Fram Strait are in accord with the satellite-derived data.Generally,the coupled model successfully simulated the Arctic Ocean sea ice climatic variation.     

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。      

一个海洋-海冰耦合模式的北极气候模拟

This paper evaluates the simulation of Arctic sea ice states using an ocean-ice coupled model that employs LASG/IAP(the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/the Institute of Atmospheric Physics) Climate Ocean Model(LICOM) and the sea-ice model from the Bergen Climate Model(BCM).It is shown that the coupled model can reasonably reproduce the major characteristics of the mean state,annual cycle,and interannual variability of the Arctic sea ice concentration.The coupled model also shows biases that were generally presented in other models,such as the underestimation of summer sea ice concentration and thickness as well as the unsatisfactory sea ice velocity.Sensitivity experiments indicate that the insufficient performance of the ocean model at high latitudes may be the main reason for the biases in the coupled model.The smoother and the fake "island",which had to be used due to the model’s grid in the North Pole region,likely caused the ocean model’s weak performance.Sea ice model thermodynamics are also responsible for the sea ice simulation biases.Therefore,both the thermodynamic module of the sea ice component and the model grid of the ocean component need to be further improved.     

Mean climatic characteristics in high northern latitudes in an ocean-sea ice-atmosphere coupled model

Emphasizing the model‘s ability in mean climate reproduction in high northern latitudes, resultsfrom an ocean-sea ice-atmosphere coupled model are analyzed. It is shown that the coupled model cansimulate the main characteristics of annual mean global sea surface temperature and sea level pressurewell, but the extent of ice coverage produced in the Southern Hemisphere is not large enough. The maindistribution characteristics of simulated sea level pressure and temperature at 850 hPa in high northernlatitudes agree well with their counterparts in the NCEP reanalysis dataset, and the model can reproducethe Arctic Oscillation (AO) mode successfully. The simulated seasonal variation of sea ice in the NorthernHemisphere is rational and its main distribution features in winter agree well with those from observations.But the ice concentration in the sea ice edge area close to the Eurasian continent in the inner Arctic Oceanis much larger than the observation. There are significant interannual variation signals in the simulated seaice concentration in winter in high northern latitudes and the most significant area lies in the GreenlandSea, followed by the Barents Sea. All of these features agree well with the results from observations.     

Evaluation of Arctic Sea Ice Drift and its Relationship with Near-surface Wind and Ocean Current in Nine CMIP6 Models from China

The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project(CMIP6)are examined by comparison with observational and reanalysis datasets.Most of the models reasonably represent the Beaufort Gyre(BG)and Transpolar Drift Stream(TDS)in the spatial patterns of their long-term mean sea ice drift,while the detailed location,extent,and strength of the BG and TDS vary among the models.About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern.About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern.In the observation/reanalysis,however,the sea ice drift pattern does not match well with the surface ocean current pattern.All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic.For the Arctic basin-wide spatial average,five of the nine models overestimate the Arctic long-term(1979-2014)mean sea ice drift speed in all months.Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn.The increases are weaker than those in the observation.This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.