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1. Introduction In an age of increasing computer power, so too comes the capability of routinely running atmospheric general circulation models (AGCMs) at increasingly high horizontal resolutions (i.e., grid spacing less than 50 km). Moving to such resolutions requires understanding, and likely improving, the performance of many components of these AGCMs, such as parameterizations of subgrid-scale physics and the interaction of physics and dynamics. Of particular interest is the role of
1. Introduction In an age of increasing computer power, so too comes the capability of routinely running atmospheric general circulation models (AGCMs) at increasingly high horizontal resolutions (i.e., grid spacing less than 50 km). Moving to such resolutions requires understanding, and likely improving, the performance of many components of these AGCMs, such as parameterizations of subgrid-scale physics and the interaction of physics and dynamics. Of particular interest is the role of
factor, the model may be run at high spatial resolution. When CSRMs are used in global models, however, they are run at much lower resolution, and model performance at these resolutions is not a foregone conclusion. CSRMs used in global models are also subject to a much wider range of atmospheric conditions than are explored in most case studies, and evaluation of the CSRM should logically follow suit. What observations may be used to evaluate CSRMs over such a wide range of conditions? One
factor, the model may be run at high spatial resolution. When CSRMs are used in global models, however, they are run at much lower resolution, and model performance at these resolutions is not a foregone conclusion. CSRMs used in global models are also subject to a much wider range of atmospheric conditions than are explored in most case studies, and evaluation of the CSRM should logically follow suit. What observations may be used to evaluate CSRMs over such a wide range of conditions? One
paper is to introduce the concept of the PV diagnostic and to demonstrate its performance by applying it to a set of simulated historical midlatitude cyclones in the Northern Hemisphere. In section 2 , we start with the description of the model simulations and one specific cyclone case that is used later to illustrate the use of the PV diagnostic. Subsequently, some limitations of the PV tendency approach are discussed, which lead us to the main assumptions and technical details of the PV
paper is to introduce the concept of the PV diagnostic and to demonstrate its performance by applying it to a set of simulated historical midlatitude cyclones in the Northern Hemisphere. In section 2 , we start with the description of the model simulations and one specific cyclone case that is used later to illustrate the use of the PV diagnostic. Subsequently, some limitations of the PV tendency approach are discussed, which lead us to the main assumptions and technical details of the PV
discussion A double-nested method is used to simulate climate change over the TP at the resolution of 10 km. First, the model performance is validated by comparing simulations with observations. Then, future climate changes over the TP are evaluated under RCP4.5 and RCP8.5 scenarios, respectively. The results show that RegCM4 can capture the spatial distribution and annual cycle of the surface air temperature over the TP. EXP2 reflects more spatial details that are affected by the complex terrain. EXP2
discussion A double-nested method is used to simulate climate change over the TP at the resolution of 10 km. First, the model performance is validated by comparing simulations with observations. Then, future climate changes over the TP are evaluated under RCP4.5 and RCP8.5 scenarios, respectively. The results show that RegCM4 can capture the spatial distribution and annual cycle of the surface air temperature over the TP. EXP2 reflects more spatial details that are affected by the complex terrain. EXP2
added computation is trivial; it requires solving a K -dimensional linear system and computing K inner products. Finally, the SVD signals identified by the technique can be used by modelers to isolate flow-dependent model deficiencies. In ranking these signals by strength, SVD gives modelers the ability to evaluate the relative importance of various model errors. 4. Numerical experiments a. Lorenz ’96 model In this section we demonstrate the empirical correction procedures using a simple
added computation is trivial; it requires solving a K -dimensional linear system and computing K inner products. Finally, the SVD signals identified by the technique can be used by modelers to isolate flow-dependent model deficiencies. In ranking these signals by strength, SVD gives modelers the ability to evaluate the relative importance of various model errors. 4. Numerical experiments a. Lorenz ’96 model In this section we demonstrate the empirical correction procedures using a simple
deposition process and terminal velocity that reflect crystal habit will be described. Section 5 briefly describes the setups of UW-NMS and AMPS to simulate a winter orographic storm during the second Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2) field experiment and also presents the experiment design. Results of the model simulations will be evaluated and compared to observations of IMPROVE-2 in section 6 , and finally, conclusions will be
deposition process and terminal velocity that reflect crystal habit will be described. Section 5 briefly describes the setups of UW-NMS and AMPS to simulate a winter orographic storm during the second Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2) field experiment and also presents the experiment design. Results of the model simulations will be evaluated and compared to observations of IMPROVE-2 in section 6 , and finally, conclusions will be
since there are fewer prognostic variables compared to traditional schemes, reducing the computational cost. In Part I , the overall behavior of the new scheme was illustrated using idealized two-dimensional (2D) squall-line simulations. It is also critical to test the scheme in a less idealized setting. In this paper, the scheme’s practical performance is evaluated by comparing three-dimensional (3D) simulations with observations and results using other microphysics schemes. Using the Weather
since there are fewer prognostic variables compared to traditional schemes, reducing the computational cost. In Part I , the overall behavior of the new scheme was illustrated using idealized two-dimensional (2D) squall-line simulations. It is also critical to test the scheme in a less idealized setting. In this paper, the scheme’s practical performance is evaluated by comparing three-dimensional (3D) simulations with observations and results using other microphysics schemes. Using the Weather
evaluation. In the first one, a single-column version of the Laboratoire de Météorologie Dynamique GCM (LMDZ) is evaluated against large eddy simulations (LES) of a series of cases of dry convection ( Ayotte et al. 1996 ), and of a case of cumulus convection over land, the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) Atmospheric Radiation Measurements (ARM) cumulus case ( Brown et al. 2002 ). An intercomparison of single-column models on that case ( Lenderink et al. 2004
evaluation. In the first one, a single-column version of the Laboratoire de Météorologie Dynamique GCM (LMDZ) is evaluated against large eddy simulations (LES) of a series of cases of dry convection ( Ayotte et al. 1996 ), and of a case of cumulus convection over land, the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) Atmospheric Radiation Measurements (ARM) cumulus case ( Brown et al. 2002 ). An intercomparison of single-column models on that case ( Lenderink et al. 2004
the Russian doll approach, where the entire range of scales is divided into subsets that are tractable by appropriate techniques, which often rely on information from a finer-scale model or parameterization. Within this context, LES is used in the development and evaluation of weather or climate model parameterizations by resolving quantities that are heavily dependent on small-scale statistics, such as entrainment rates (e.g., Tiedtke 1989 ; Neggers et al. 2009 ). In turn, LES relies on
the Russian doll approach, where the entire range of scales is divided into subsets that are tractable by appropriate techniques, which often rely on information from a finer-scale model or parameterization. Within this context, LES is used in the development and evaluation of weather or climate model parameterizations by resolving quantities that are heavily dependent on small-scale statistics, such as entrainment rates (e.g., Tiedtke 1989 ; Neggers et al. 2009 ). In turn, LES relies on
-organized and smaller-scale convection ( Schiro et al. 2018 ; Schiro and Neelin 2019 ). The relationship to convective instability has been examined in a single GCM ( Sahany et al. 2012 , 2014 ; Kuo et al. 2017 ). Here we systematically evaluate the performance of multiple GCMs in simulating key features of tropical precipitation and deep convection with such diagnostics. KSN18 has detailed observational aspects of the convective transition statistics over tropical oceans using satellite retrievals and
-organized and smaller-scale convection ( Schiro et al. 2018 ; Schiro and Neelin 2019 ). The relationship to convective instability has been examined in a single GCM ( Sahany et al. 2012 , 2014 ; Kuo et al. 2017 ). Here we systematically evaluate the performance of multiple GCMs in simulating key features of tropical precipitation and deep convection with such diagnostics. KSN18 has detailed observational aspects of the convective transition statistics over tropical oceans using satellite retrievals and
