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How subtropical marine low cloud cover (LCC) will respond to global warming is a major source of uncertainty in future climate change. Although the estimated inversion strength (EIS) is a good predictive index of LCC, it has a serious limitation when applied to evaluate LCC changes due to warming: The LCC decreases despite increases in EIS in future climate simulations of global climate models (GCMs). In this work, using stat-eof-the-art GCMs, we show that the recently proposed estimated cloud-top entrainment index (ECTEI) decreases consistently with LCC in warmer sea surface temperature (SST) climates. For the patterned SST warming predicted by coupled GCMs, ECTEI can constrain the subtropical marine LCC feedback to −0.41 ± 0.28% K−1 (90% CI), implying virtually certain positive feedback. ECTEI physically explains the heuristic model for LCC changes based on a linear combination of EIS and SST changes in previous studies in terms of cloud-top entrainment processes.

Interannual variations provide insight into the sensitivity of convective processes. Thus, CloudSat and ERA5 are used to explore the relationship among convective cores, outflows and environmental conditions during El Niño‐Southern Oscillation (ENSO) cycles. Results reveal greater upper‐tropospheric stability during El Niño, resulting in a lower level of neutral buoyancy compared to La Niña. However, outflow levels remain relatively consistent across ENSO cycles. This suggests that, despite less favorable conditions for deep convection during El Niño, stronger convective intensity is required to achieve outflow levels comparable to those in La Niña. Indeed, our results suggest that convection observed during El Niño tends to have broader cores and lower entrainment rates, translating to greater intensity compared to La Niña. These findings emphasize the importance of considering both large‐scale and convective‐scale processes, providing an update to the fixed anvil temperature (FAT) and the proportionately higher anvil temperature (PHAT) hypotheses as originally proposed. Plain Language Summary Examining year‐to‐year variations provides unique insights into understanding how storms may change in a warmer climate. We use CloudSat and ERA5 reanalysis to examine variations in convective outflow (i.e., an airflow pushed out of storms), environmental factors, and cloud properties during ENSO cycles. Comparing El Niño to La Niña, we find that the atmosphere higher up in the troposphere tends to be more stable, which usually slows down the development of storms, during El Niño. However, the heights where convective outflow occurs do not change much during El Niño and La Niña events. This happens because during El Niño, the upward movement of air in storms is more powerful. This stronger upward movement offsets the stabilizing effect of the upper troposphere, so the overall outflow from the storms stays about the same. Our study aligns with the main idea of the FAT hypothesis, which postulates that in a warming climate, the temperature of the anvils (i.e., wide, flat clouds crawling out of the storm top) stays relatively constant primarily due to a thermodynamic constraint. However, our results show that convective‐scale processes with dynamic control play a key role as well, providing an update to the FAT as originally proposed. Key Points LNB is lower during El Niño due to a greater UT stability, but convective outflow levels remain consistent across ENSO cycles The intensity of convective cores during El Niño has to be stronger than that during La Niña Our finding necessitates a modification to FAT and the proportionately higher anvil temperature (PHAT)

A Madden-Julian Oscillation (MJO) is a massive weather event consisting of deep convection coupled with atmospheric circulation, moving slowly eastward over the Indian and Pacific Oceans. Despite its enormous influence on many weather and climate systems worldwide, it has proven very difficult to simulate an MJO because of assumptions about cumulus clouds in global meteorological models. Using a model that allows direct coupling of the atmospheric circulation and clouds, we successfully simulated the slow eastward migration of an MJO event. Topography, the zonal sea surface temperature gradient, and interplay between eastward- and westward-propagating signals controlled the timing of the eastward transition of the convective center. Our results demonstrate the potential making of month-long MJO predictions when global cloud-resolving models with realistic initial conditions are used.

This study examines projections of high clouds related to sea surface temperature (SST) change using 14-km simulation output from NICAM, a global cloud system–resolving model. This study focuses on the vertical and horizontal structure of high cloud response to the SST pattern and how these cloud responses are linked to ice hydrometeors, such as cloud ice, snow, and graupel, which are not resolved by conventional general circulation models (GCMs). Under the present climate, the vertical and horizontal structure of the simulated increase in tropical high cloud amount for positive tropical mean HadISST SST anomalies has similar behavior to that of the GCM-Oriented CALIPSO Cloud Product (GOCCP) cloud fraction for HadISST SST. We further show that cloud ice is the main contributor to the simulated high cloud amount. Under a warming climate, the composite vertical and horizontal structure of the tropical high cloud response to the SST shows similar behavior to that under the present climate, but the amplitude of the variation is greater by a factor of 1.5 and the variation is more widespread. This amplification contributes to the high cloud increase under the warming climate, which is directly linked to the wider spatial extent of cloud ice in the eastern Pacific region. This study specifically reveals the similarity of the patterns of the responses of the high cloud fraction and cloud ice to global warming, indicating that an appropriate treatment of the complete spectrum of ice hydrometeors in global climate models is key to simulating high clouds and their response to global warming.

Global cloud/cloud system-resolving models are perceived to perform well in the prediction of the Madden–Julian Oscillation (MJO), a huge eastward -propagating atmospheric pulse that dominates intraseasonal variation of the tropics and affects the entire globe. However, owing to model complexity, detailed analysis is limited by computational power. Here we carry out a simulation series using a recently developed supercomputer, which enables the statistical evaluation of the MJO prediction skill of a costly new-generation model in a manner similar to operational forecast models. We estimate the current MJO predictability of the model as 27 days by conducting simulations including all winter MJO cases identified during 2003–2012. The simulated precipitation patterns associated with different MJO phases compare well with observations. An MJO case captured in a recent intensive observation is also well reproduced. Our results reveal that the global cloud-resolving approach is effective in understanding the MJO and in providing month-long tropical forecasts. Prediction of the Madden–Julian Oscillation using complex cloud-resolving models has been limited by computational power. Here, Miyakawa et al. run a series of simulations using the newly developed 10 peta-flop ‘K computer’ and demonstrate a Madden–Julian Oscillation predictive window of 27 days.

The Nonhydrostatic ICosahedral Atmospheric Model (NICAM), a global model with an icosahedral grid system, has been under development for nearly two decades. This paper describes NICAM16-S, the latest stable version of NICAM (NICAM.16), modified for the Coupled Model Intercomparison Project Phase 6, High Resolution Model Intercomparison Project (HighResMIP). Major updates of NICAM.12, a previous version used for climate simulations, included updates of the cloud microphysics scheme and land surface model, introduction of natural and anthropogenic aerosols and a subgrid-scale orographic gravity wave drag scheme, and improvement of the coupling between the cloud microphysics and the radiation schemes. External forcings were updated to follow the protocol of the HighResMIP. A series of short-term sensitivity experiments were performed to determine and understand the impacts of these various model updates on the simulated mean states. The NICAM16-S simulations demonstrated improvements in the ice water content, high cloud amount, surface air temperature over the Arctic region, location and strength of zonal mean subtropical jet, and shortwave radiation over Africa and South Asia. Some long-standing biases, such as the double intertropical convergence zone and smaller low cloud amount, still exist or are even worse in some cases, suggesting further necessity for understanding their mechanisms, upgrading schemes and parameter settings, and enhancing horizontal and vertical resolutions.

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 runs Key improvements are retuning of cloud microphysics properties, consideration of grid‐scale turbulent mixing, and increased vertical layers Biases in mean rainfall, radiation balance, and circulation as well as weather (monsoon, Madden–Julian oscillation, equatorial wave, tropical cyclone) are reduced

This article reviews the development of a global non-hydrostatic model, focusing on the pioneering research of the Non-hydrostatic Icosahedral Atmospheric Model (NICAM). Very high resolution global atmospheric circulation simulations with horizontal mesh spacing of approximately O (km) were conducted using recently developed supercomputers. These types of simulations were conducted with a specifically designed atmospheric global model based on a quasi-uniform grid mesh structure and a non-hydrostatic equation system. This review describes the development of each dynamical and physical component of NICAM, the assimilation strategy and its related models, and provides a scientific overview of NICAM studies conducted to date.

This study examines the impact of an alteration of a cloud microphysics scheme on the representation of longwave cloud radiative forcing (LWCRF) and its impact on the atmosphere in global cloud-system-resolving simulations. A new double-moment bulk cloud microphysics scheme is used, and the simulated results are compared with those of a previous study. It is demonstrated that improvements within the new cloud microphysics scheme have the potential to substantially improve climate simulations. The new cloud microphysics scheme represents a realistic spatial distribution of the cloud fraction and LWCRF, particularly near the tropopause. The improvement in the cirrus cloud-top height by the new cloud microphysics scheme substantially reduces the warm bias in atmospheric temperature from the previous simulation via LWCRF by the cirrus clouds. The conversion rate of cloud ice to snow and gravitational sedimentation of cloud ice are the most important parameters for determining the strength of the radiative heating near the tropopause and its impact on atmospheric temperature.

Previous projections of the frequency of tropical cyclone genesis due to global warming, even in terms of sign of the change, depends on the chosen model simulation. Here, we systematically examine projected changes in tropical cyclones using six global atmospheric models with medium-to-high horizontal resolutions included in the sixth phase of the Coupled Model Intercomparison Project/High-Resolution Model Intercomparison Project. Changes in the frequency of tropical cyclone genesis could be broken down into the contributions from (i) the tropical cyclone seed, a depression having a closed contour of sea level pressure with a warm core and (ii) the survival rate, the ratio of the frequency of tropical cyclone genesis to that of tropical cyclone seeds. The multi-model ensemble mean indicates that tropical cyclone genesis frequencies are significantly decreased during the period 1990–2049, which is attributable to changes in tropical cyclone seeds. Analysis of the individual models shows that although most models project a more or less decreasing trend in tropical cyclone genesis frequencies and seeds, the survival rate also contributes to the result in some models. The present study indicates the usefulness of decomposition into the frequency of the tropical cyclone seeds and the survival rate to understand the cause of uncertainty in projected frequencies of tropical cyclone genesis.