How Can We Improve the Seamless Representation of Climatological Statistics and Weather Toward Reliable Global K‐Scale Climate Simulations?

Toward the achievement of reliable global kilometer‐scale (k‐scale) climate simulations, we improve the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) by focusing on moist physical processes. A goal of the model improvement is to establish a configuration that can simulate realistic fields seamlessly from the daily‐scale variability to the climatological statistics. Referring to the two representative configurations of the present NICAM, each of which has been used for climate‐scale and sub‐seasonal‐scale experiments, we try to find the appropriate partitioning of fast/local and slow/global‐scale circulations. In a series of sensitivity experiments at 14‐km horizontal resolution, we test (a) the tuning of terminal velocities of rain, snow, and cloud ice, (b) the implementation of turbulent diffusion by the Leonard term, and (c) enhanced vertical resolution. These tests yield reasonable convection triggering and convection‐induced tropospheric moistening, and result in better performance than in previous NICAM climate simulations. In the mean state, double Intertropical Convergence Zone bias disappears, and the zonal contrast of equatorial precipitation, top‐of‐atmosphere radiation balance, vertical temperature profile, and position/strength of subtropical jet are reproduced dramatically better. Variability such as equatorial waves and the Madden–Julian oscillation (MJO) is spontaneously realized with appropriate spectral power balance, and the Asian summer monsoon, boreal‐summer MJO, and tropical cyclone (TC) activities are more realistically simulated especially around the western Pacific. Meanwhile, biases still exist in the representation of low‐cloud fraction, TC intensity, and precipitation diurnal cycle, suggesting that both higher spatial resolutions and further model development are warranted. Plain Language Summary: In the near future, increasing computational power will make it possible to perform a global kilometer‐scale "cloud‐resolving" model (GCRM) simulation on the climate time scale, which is expected to reduce the uncertainty of cloud‐related processes in the climate system. In this sense, it is important to make GCRMs more reliable tools in the evaluation and prediction of the variabilities over a wide range of spatio‐temporal scales. With this perspective, we improve a Japanese GCRM, the Nonhydrostatic Atmospheric Icosahedral Model (NICAM), to achieve the realistic representation of both weather phenomena and climatological features in long‐term simulations. We revise the NICAM by the reconsideration of cloud microphysics properties, the implementation of diffusion processes around strong convection cores, and increased vertical layers. These revisions lead to the substantial improvements in the climatological mean precipitation distributions, radiative energy balance at the top of the atmosphere, westerly jets in the mid‐latitude, and temperature fields. We also find that weather phenomena such as the Asian summer monsoon and tropical cyclone (TC) genesis are simulated more realistically. We expect that, in addition to the above model improvements, kilometer‐scale horizontal resolutions can resolve a part of remaining issues of the representation of TC intensity and precipitation diurnal cycle. Key Points: We improve a global nonhydrostatic atmospheric model focusing on resolution‐independent errors that can exist even in k‐scale climate runsKey improvements are retuning of cloud microphysics properties, consideration of grid‐scale turbulent mixing, and increased vertical layersBiases in mean rainfall, radiation balance, and circulation as well as weather (monsoon, Madden–Julian oscillation, equatorial wave, tropical cyclone) are reduced [ABSTRACT FROM AUTHOR]