DOI: 10.1175/JCLI-D-17-0362.1
Scopus记录号: 2-s2.0-85047090405
论文题名: Using the Atmospheric Radiation Measurement (ARM) datasets to evaluate climate models in simulating diurnal and seasonal variations of tropical clouds
作者: Wang H. ; Burleyson C.D. ; Ma P.-L. ; Fast J.D. ; Rasch P.J.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2018
卷: 31, 期: 8 起始页码: 3301
结束页码: 3325
语种: 英语
英文关键词: Climate models
; Cloud retrieval
; Clouds
; Model evaluation/performance
; Radiosonde observations
; Surface observations
Scopus关键词: ARM processors
; Atmospheric radiation
; Clouds
; Ice
; Radiosondes
; Atmospheric radiation measurements
; Cloud retrieval
; Community atmosphere model
; Model evaluation/performance
; Radiosonde observations
; Seasonal and diurnal variations
; Surface observation
; Tropical Western Pacific
; Climate models
; atmospheric modeling
; climate modeling
; cloud
; computer simulation
; data set
; diurnal variation
; observational method
; parameterization
; radiosonde
; seasonal variation
; shortwave radiation
; stratiform cloud
; thermodynamic property
; Pacific Ocean
; Pacific Ocean (West)
英文摘要: Long-term Atmospheric Radiation Measurement (ARM) datasets collected at the three tropical western Pacific (TWP) sites are used to evaluate the ability of the Community Atmosphere Model (CAM5) to simulate the various types of clouds, their seasonal and diurnal variations, and their impact on surface radiation. A number of CAM5 simulations are conducted at various horizontal grid spacing (around 2°, 1°, 0.5°, and 0.25°) with meteorological constraints from analysis or reanalysis. Model biases in the seasonal cycle of cloudiness are found to be weakly dependent on model resolution. Positive biases (up to 20%) in the annual mean total cloud fraction appear mostly in stratiform ice clouds. Higher-resolution simulations do reduce the positive bias in ice clouds, but they inadvertently increase the negative biases in convective clouds and low-level liquid clouds, leading to a positive bias in annual mean shortwave fluxes at the sites, as high as 65 W m-2 in the 0.25° simulation. Such resolution-dependent biases in clouds can adversely lead to biases in ambient thermodynamic properties and, in turn, produce feedback onto clouds. Both the model and observations show distinct diurnal cycles in total, stratiform, and convective cloud fractions; however, they are out of phase by 12 h and the biases vary by site. The results suggest that biases in deep convection affect the vertical distribution and diurnal cycle of stratiform clouds through the transport of vapor and/or the detrainment of liquid and ice. The approach used here can be easily adapted for the evaluation of new parameterizations being developed for CAM5 or other global or regional models. © 2018 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/111572
Appears in Collections: 气候减缓与适应
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作者单位: Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, United States
Recommended Citation:
Wang H.,Burleyson C.D.,Ma P.-L.,et al. Using the Atmospheric Radiation Measurement (ARM) datasets to evaluate climate models in simulating diurnal and seasonal variations of tropical clouds[J]. Journal of Climate,2018-01-01,31(8)