Evaluation of the Arctic surface radiation budget in CMIP5 models
Evaluation of the Arctic surface radiation budget in CMIP5 models
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DOI：
10.1002/2016jd025099
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发表时间：
2015-12
期刊：
影响因子：
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通讯作者：
R. Boeke;P. Taylor
中科院分区：
文献类型：
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作者：
R. Boeke;P. Taylor
北极地区的变暖速度是全球平均水平的两倍多，所有耦合模式相互比较项目5（CMIP 5）气候模式预测这一趋势将继续下去。尽管存在这种一致性，显着的模式间传播存在于模拟北极气候有关的差异，在北极表面辐射收支。在先前描述和理解气候模式中地表辐射收支偏差的工作的基础上，使用历史强迫情景的17个CMIP 5模式中北极地表辐射收支的年平均和季节周期根据最先进的云和地球辐射能系统地表能量平衡和填充数据进行了评估。CMIP 5多模式集合在有阳光的月份能够很好地模拟长波表面通量（7月的差异约为1 W m−2），但在冬季表现出显著的偏差（高达-19 W m−2）。短波通量在夏季表现出显著的跨模式传播; 7月模式标准差接近20 W m−2。将分解分析应用于云辐射效应（CRE）季节性周期，在模型模拟的云分数，全天空/晴空通量差异和表面反射率的季节性周期之间发现了不切实际的补偿，使模型能够模拟具有不切实际的个人贡献的真实CRE季节性周期。必须限制模型中这种不切实际的行为，以改善北极气候模拟;观测的不确定性足以做到这一点。最后，在冬季，所有和晴空长波下降流通量的偏差与模式的表面温度呈正相关，而在夏季，表面温度与来自表面反射误差的晴空上升流辐射偏差关系最密切。
The Arctic region is warming at a rate more than double the global average, a trend predicted to continue by all Coupled Model Intercomparison Project 5 (CMIP5) climate models. Despite this consistency, significant intermodel spread exists in the simulated Arctic climate related to differences in the Arctic surface radiation budget. Building upon previous work to characterize and understand surface radiation budget biases in climate models, the annual mean and seasonal cycle of the Arctic surface radiation budget in 17 CMIP5 models using the Historical‐forcing scenario is evaluated against state‐of‐the‐art Cloud and Earth's Radiant Energy System Surface Energy Balanced and Filled data. The CMIP5 multimodel ensemble is found to simulate longwave surface fluxes well during the sunlit months (~1 W m−2 differences in July) but exhibits significant wintertime biases (up to −19 W m−2). Shortwave fluxes show substantial across‐model spread during summer; the model standard deviation approaches 20 W m−2 in July. Applying a decomposition analysis to the cloud radiative effect (CRE) seasonal cycles, an unrealistic compensation is uncovered between the model‐simulated seasonal cycles of cloud fraction, all‐sky/clear‐sky flux differences, and surface albedo that enables models to simulate realistic CRE seasonal cycles with unrealistic individual contributions. This unrealistic behavior in models must be constrained to improve Arctic climate simulation; observational uncertainty is sufficient to do so. Lastly, biases in all and clear‐sky longwave downwelling fluxes positively correlate with model surface temperature in winter, while in summer surface temperature is most strongly related to clear‐sky upwelling radiation biases from surface albedo errors.