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| BCC_AGCM2.1对中国东部地区云辐射特征模拟的偏差分析 | |
| 引用本文： | 张祎,王在志,宇如聪.BCC_AGCM2.1对中国东部地区云辐射特征模拟的偏差分析[J].气象学报,2012,70(6):1260-1275. |
| 作者姓名： | 张祎 王在志 宇如聪 |
| 作者单位： | 1. 中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室,北京,100029;中国科学院研究生院,北京,100049 2. 中国气象局国家气候中心,北京,100081 3. 中国气象局,北京,100081 |
| 基金项目： | 全球变化研究国家重大科学研究计划项目(2010CB951900)、公益性行业(气象)科研专项经费项目(GYHY201106022)、科技支撑项目(2009BAC51B03) |
| 摘 要： | 通过与观测及再分析资料的对比,评估了中国国家气候中心大气环流模式BCC_AGCM 2.1对中国东部地区云辐射特征的模拟性能,并着重分析了模拟偏差的原因.在云辐射特征的基本气候态模拟方面,模式能大致再现中国东部中纬度层状云大值带,以及层状云冷季多、暖季少的季节特征,模拟的短波云辐射强迫也具有与观测相对应的季节变化特征.在云辐射强迫和地面温度相互影响过程的模拟方面,模式也能模拟出与观测相近的相互作用过程,即地面温度降低伴随着层状云云量增多以及负的净云辐射强迫加强,升温时层状云云量减少和净云辐射强迫减弱.但模式模拟的大陆层状云云量系统性偏少(尤其在冷季),使得模式在该处的短波云辐射强迫明显偏弱.初步分析表明,造成层状云模拟差异的主要原因是在中国西南地区对流层低层模式模拟的偏南气流明显偏弱以及陆-气潜热通量偏小.偏南气流偏弱导致低层散度和垂直运动条件不利于中层云的形成.同时偏南气流偏弱也不利于向西南地区的水汽输送,再加上模式模拟地表向上潜热通量偏小,这二者都使得模式模拟中国西南区域对流层低层的水汽含量严重偏少,相对湿度偏低,同样不利于层状云生成和发展.水汽偏少进一步导致在冷异常情况下青藏高原下游云辐射-地表温度反馈模拟偏弱,即呈现冷异常时,水汽条件偏弱限制了云量增加,弱化了进一步降低温度的反馈过程. |
| 关 键 词： | 模式 中国东部 层状云 云辐射强迫 云-气候反馈 |
| 收稿时间： | 9/6/2011 12:00:00 AM |
| 修稿时间： | 2012/3/30 0:00:00 |
Analysis of the biases in the cloud radiative feature simulations over eastern China as done by the BCC_AGCM2.1 |
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| ZHANG Yi,WANG Zaizhi and YU Rucong.Analysis of the biases in the cloud radiative feature simulations over eastern China as done by the BCC_AGCM2.1[J].Acta Meteorologica Sinica,2012,70(6):1260-1275. | |
| Authors: | ZHANG Yi WANG Zaizhi and YU Rucong |
| Institution: | State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Graduate University of Chinese Academy of Sciences, Beijing 100049, China,National Climate Center, China Meteorological Administration, Beijing 100081, China and China Meteorological Administration, Beijing 100081, China |
| Abstract: | The cloud radiative features over eastern China simulated by the general circulation model (BCC_AGCM2.1), which is developed at National Climate Center, China Meteorological Administration (CMA), are evaluated based on the observational and reanalysis data. The reasons for biases are analyzed in this paper. As for the climatological mean pattern, the results indicate that BCC_AGCM2.1 can basically reproduce the maxima center of stratiform cloud. The features of maximum cloud fractions in winter and minimum cloud fractions in summer are all reasonably reproduced, and the simulated cloud radiative forcing also has the corresponding features. On the other hand, the model can simulate the similar interaction processes between the cloud radiative forcing and the surface temperature to observations, namely the stratiform cloud increasing and negative net cloud forcing strengthening during the cooling period and the opposite evolution during the warming period. However, model systematically underestimates the continental stratiform clouds (especially in cold seasons), weakening the short wave cloud forcing. The reasons causing the stratiform cloud bias lie mainly in the evidently weakening of the southerly flow at the lower troposphere over southwest China and the shortage of land atmosphere latent heat. The weakening of southerly flow drives the low level divergence and vertical motions to go against the formation of mid level cloud. The weakening of the southerly flow is also unfavorable to the water vapor transportation from the ocean to the southwest area. Along with the discrepancy of surface upward latent heat in the model, these two aspects all result in the water vapor shortage and lower relative humidity at the lower troposphere over southwest area, which obstruct the formation and development of stratiform cloud. The shortage of water vapor further leads to the weakening of the cloud radiative forcing surface temperature feedback in the case of cold anomaly downstream of the Tibetan Plateau, namely the lower water vapor content weakening the feedback process at the temperature decreasing period. |
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