Evaluating cloud tuning in a climate model with satellite observations
Evaluating cloud tuning in a climate model with satellite observations
复制标题
通过卫星观测评估气候模型中的云调整
DOI：
10.1002/grl.50874
复制
发表时间：
2013
影响因子：
5.2
通讯作者：
G. Stephens
中科院分区：
文献类型：
--
作者：
Kentaroh Suzuki;J. Golaz;G. Stephens
这项研究检验了气候模型中可调云参数（触发暖雨形成的阈值粒子半径）的有效性。由于气溶胶间接强迫的大小不同，模型特定参数在不确定性范围内的替代值已被证明会产生截然不同的历史温度趋势。根据描述暖雨形成的微物理过程特征的统计数据，根据卫星观测评估了三个不同的阈值半径。结果表明，当模型采用最差地再现卫星观测的微物理统计数据的阈值半径时，模拟的温度趋势与观测的趋势最匹配，反之亦然。 “自下而上”的基于过程的约束与“自上而下”的温度趋势约束之间的不一致意味着模型中存在补偿误差。
This study examines the validity of a tunable cloud parameter, the threshold particle radius triggering the warm rain formation, in a climate model. Alternate values of the model's particular parameter within uncertainty have been shown to produce severely different historical temperature trends due to differing magnitude of aerosol indirect forcing. Three different threshold radii are evaluated against satellite observations in terms of the statistics depicting microphysical process signatures of the warm rain formation. The results show that the simulated temperature trend best matches to observed trend when the model adopts the threshold radius that worst reproduces satellite‒observed microphysical statistics and vice versa. This inconsistency between the “bottom‒up” process‒based constraint and the “top‒down” temperature trend constraint implies the presence of compensating errors in the model.