The improvement of the accuracy of simulated cloud-related variables,such as the cloud fraction,in global climate models(GCMs)is still a challenging problem in climate modeling.In this study,the influence of cloud mic...The improvement of the accuracy of simulated cloud-related variables,such as the cloud fraction,in global climate models(GCMs)is still a challenging problem in climate modeling.In this study,the influence of cloud microphysics schemes(one-moment versus two-moment schemes)and cloud overlap methods(observation-based versus a fixed vertical decorrelation length)on the simulated cloud fraction was assessed in the BCC_AGCM2.0_CUACE/Aero.Compared with the fixed decorrelation length method,the observation-based approach produced a significantly improved cloud fraction both globally and for four representative regions.The utilization of a two-moment cloud microphysics scheme,on the other hand,notably improved the simulated cloud fraction compared with the one-moment scheme;specifically,the relative bias in the global mean total cloud fraction decreased by 42.9%–84.8%.Furthermore,the total cloud fraction bias decreased by 6.6%in the boreal winter(DJF)and 1.64%in the boreal summer(JJA).Cloud radiative forcing globally and in the four regions improved by 0.3%−1.2% and 0.2%−2.0%,respectively.Thus,our results showed that the interaction between clouds and climate through microphysical and radiation processes is a key contributor to simulation uncertainty.展开更多
The decorrelation length(Lcf) has been widely used to describe the behavior of vertical overlap of clouds in general circulation models(GCMs); however, it has been a challenge to associate Lcf with the large-scale...The decorrelation length(Lcf) has been widely used to describe the behavior of vertical overlap of clouds in general circulation models(GCMs); however, it has been a challenge to associate Lcf with the large-scale meteorological conditions during cloud evolution. This study explored the relationship between Lcf and the strength of atmospheric convection in the tropics based on output from a global cloud-resolving model. Lcf tends to increase with vertical velocity in the mid-troposphere(w500) at locations of ascent, but shows little or no dependency on w500 at locations of descent. A representation of Lcf as a function of vertical velocity is obtained, with a linear regression in ascending regions and a constant value in descending regions. This simple and dynamic-related representation of Lcf leads to a significant improvement in simulation of both cloud cover and radiation fields compared with traditional overlap treatments. This work presents a physically justifiable approach to depicting cloud overlap in the tropics in GCMs.展开更多
基金supported by the National Key R&D Program of China(2017YFA0603502)(Key)National Natural Science Foundation of China(91644211)S&T Development Fund of CAMS(2021KJ004).
文摘The improvement of the accuracy of simulated cloud-related variables,such as the cloud fraction,in global climate models(GCMs)is still a challenging problem in climate modeling.In this study,the influence of cloud microphysics schemes(one-moment versus two-moment schemes)and cloud overlap methods(observation-based versus a fixed vertical decorrelation length)on the simulated cloud fraction was assessed in the BCC_AGCM2.0_CUACE/Aero.Compared with the fixed decorrelation length method,the observation-based approach produced a significantly improved cloud fraction both globally and for four representative regions.The utilization of a two-moment cloud microphysics scheme,on the other hand,notably improved the simulated cloud fraction compared with the one-moment scheme;specifically,the relative bias in the global mean total cloud fraction decreased by 42.9%–84.8%.Furthermore,the total cloud fraction bias decreased by 6.6%in the boreal winter(DJF)and 1.64%in the boreal summer(JJA).Cloud radiative forcing globally and in the four regions improved by 0.3%−1.2% and 0.2%−2.0%,respectively.Thus,our results showed that the interaction between clouds and climate through microphysical and radiation processes is a key contributor to simulation uncertainty.
基金Supported by the National Key Research and Development Program of China(2017YFA0603502)(Key)National Natural Science Foundation of China(91644211 and 41375080)China Meteorological Administration Special Public Welfare Research Fund(GYHY201406023)
文摘The decorrelation length(Lcf) has been widely used to describe the behavior of vertical overlap of clouds in general circulation models(GCMs); however, it has been a challenge to associate Lcf with the large-scale meteorological conditions during cloud evolution. This study explored the relationship between Lcf and the strength of atmospheric convection in the tropics based on output from a global cloud-resolving model. Lcf tends to increase with vertical velocity in the mid-troposphere(w500) at locations of ascent, but shows little or no dependency on w500 at locations of descent. A representation of Lcf as a function of vertical velocity is obtained, with a linear regression in ascending regions and a constant value in descending regions. This simple and dynamic-related representation of Lcf leads to a significant improvement in simulation of both cloud cover and radiation fields compared with traditional overlap treatments. This work presents a physically justifiable approach to depicting cloud overlap in the tropics in GCMs.