The forward simulation of radar reflectivity requires details of clouds and precipitation from general circulation models (GCMs). But such details are represented as sub-grid processes that involve parameterizations and assumptions about the spatial coverage and thus depend on the GCM. In this research, we propose the use of a statistical method to generate sub-grid precipitation for generic use. In addition, the proposed method can be used to provide uncertainty estimates on the signals. The sub-grid variability is obtained from simulation with a global storm-resolving model called NICAM (non-hydrostatic icosahedral atmospheric model). The proposed method first generates precipitation probabilities for the possible scenarios and then sub-grid precipitation rates are generated from the generalized gamma distribution for the given cloud fraction and grid-scale precipitation rates. Compared to the standard method (which neglects the probabilities) that overestimates the precipitation fraction, our method well reproduces the NICAM dataset profiles of both the precipitation fraction and the radar-based cloud fraction. The in-cloud signal frequencies are also reproduced, although less accurately over a tropical region. Inclusion of sub-grid variability in precipitation rates was particularly important for the tropical region to obtain agreement of the precipitation fraction. Application of the two methods to a GCM shows it to have a robust bias for low-level liquid clouds. The proposed method can be used to identify uncertainty in the signals associated with sub-grid variability in the precipitation processes, indicating an effective way to use a global storm-resolving model to evaluate conventional GCMs.

We investigate the dependence of radiative feedback on the pattern of sea-surface temperature (SST) change in fourteen Atmospheric General Circulation Models (AGCMs) forced with observed variations in SST and sea-ice over the historical record from 1871 to near-present. We find that over 1871-1980, the Earth warmed with feedbacks largely consistent and strongly correlated with long-term climate sensitivity feedbacks (diagnosed from corresponding atmosphere-ocean GCM abrupt-4xCO2 simulations). Post 1980 however, the Earth warmed with unusual trends in tropical Pacific SSTs (enhanced warming in the west, cooling in the east) that drove climate feedback to be uncorrelated with – and indicating much lower climate sensitivity than – that expected for long-term CO2 increase. We show that these conclusions are not strongly dependent on the AMIP II SST dataset used to force the AGCMs, though the magnitude of feedback post 1980 is generally smaller in eight AGCMs forced with alternative HadISST1 SST boundary conditions. We quantify a ‘pattern effect’ (defined as the difference between historical and long-term CO2 feedback) equal to 0.44 ± 0.47 [5-95%] W m-2 K-1 for the time-period 1871-2010, which increases by 0.05 ± 0.04 W m-2 K-1 if calculated over 1871-2014. Assessed changes in the Earth’s historical energy budget are in agreement with the AGCM feedback estimates. Furthermore satellite observations of changes in top-of-atmosphere radiative fluxes since 1985 suggest that the pattern effect was particularly strong over recent decades, though this may be waning post 2014 due to a warming of the eastern Pacific.

The observed sea level (SL) around the Japanese coast shows a peculiar multidecadal variation with the peak in the 1950s followed by the gradual fall until the 1970s and the rebound continuing to the present, making the recent SL rise less remarkable in the historical record. An ensemble mean of the historical simulations conducted for the Coupled Model Intercomparison Project phase 6 (CMIP6) using the Meteorological Research Institute Earth System Model version 2.0 (MRI-ESM2.0) reproduces this variability well, implying that this was a forced one. The MRI-ESM2.0 simulations for the Detection and Attribution Model Intercomparison Project suggest that the increase in anthropogenic aerosols caused the SL fall from the 1950s to the 1970s and the increase in greenhouse gases caused the SL rise after that. Additional sensitivity runs indicate that the surface heat loss in the North Pacific due to anthropogenic aerosols plays a dominant role in the SL fall.

The representations of clouds in climate model MRI-ESM2 (Yukimoto et al. 2019, JMSJ) used in CMIP6 simulations are significantly improved from the previous version MRI-CGCM3 used in CMIP5 simulations. The score of the spatial pattern of 2m temperature for MRI-ESM2 is better than any of the 47 CMIP6 models. The score for radiative fluxes at the top of the atmosphere for MRI-ESM2 is ranked in the top seven models among these CMIP6 models. We will introduce comprehensively various modifications related to clouds, which contribute to the dramatically improved cloud representation, and their main impacts (Kawai et al. 2019, GMD). The modifications cover various schemes and processes including the cloud scheme, turbulence scheme, cloud microphysics processes, the interaction between cloud and convection schemes, resolution issues, cloud radiation processes, aerosol properties, and numerics. In addition, we would like to mention what data we used during the model development, how we evaluated our model, how useful the intercomparison studies were, and what data we need for further model development.

The radiation bias over the Southern Ocean was terribly bad in MRI-CGCM3 that was used for CMIP5 simulations. However, the bias is significantly reduced in MRI-ESM2 (Yukimoto et al. 2019) that is used for CMIP6 simulations by various modifications related to clouds (Kawai et al. 2019). On the other hand, the double-ITCZ problem is also alleviated in the MRI-ESM2 (Tian and Dong, 2020). Is the reduction in the Southern Ocean radiation bias the cause of alleviation of the double-ITCZ problem? Each modification that contributed to the reduction of the Southern Ocean radiation bias in the MRI-ESM2 was progressively reverted to the corresponding older treatment in order to examine their individual impacts on the ITCZ problem. Results show the double-ITCZ problem worsens almost monotonically when the excessive shortwave insolation over the Southern Ocean increases (Kawai et al. 2020, 2021).

In this study, the changes in the occurrence of marine fog over the summer North Pacific in warmer sea surface temperature (SST) or increased CO2 climates were investigated based on atmospheric model simulations by using the fifth phase of the Climate Model Intercomparison Project (CMIP5) multimodel data. Initially, the marine fog representation in CMIP5 multimodels was briefly evaluated globally. We found that the simulated marine fog occurrence was represented relatively well in boreal summer but poorly in other seasons. The results indicated that the changes in the North Pacific high‐pressure system accompanied by changes in horizontal wind patterns control the changes in marine fog occurrence in the North Pacific. The magnitude of contrasting pair changes in marine fog occurrence in the western and eastern North Pacific are primarily determined by the magnitude of changes in the North Pacific high‐pressure system. Global‐scale changes in the vertical profiles of the atmosphere (stability changes) can also affect the marine fog changes. These changes in marine fog over the North Pacific were consistent among most CMIP5 models.