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Tropical overshooting deep convections (ODCs) play a vital role in vertical transport of boundary layer pollutants, especially short‐lived species, to upper troposphere and lower stratosphere, with important implications for stratospheric ozone and climate. We use simulations from a global cloud‐system resolving model, Nonhydrostatic Icosahedral Atmosphere Model (NICAM), to study ODC changes from historical period to the end of the 21st century. NICAM well reproduces Tropical Rainfall Measuring Mission‐satellite observed ODC spatiotemporal patterns. The future occurrences of ODCs with cloud top height above 15.5, 16.9, and 18.4 km scaled by the global temperature increase will increase by 7%/K, 27%/K, and 90%/K, respectively, over ocean where the atmosphere is becoming warmer and wetter. The corresponding changes are −1%/K, 10%/K, and 37%/K over land where the atmosphere will become hotter but drier. Relative to tropical cold point tropopause height, ODCs will only change by 3%/K, with 6%/K over the ocean but −3%/K on land. Plain Language Summary Tropical overshooting deep convection (ODC) plays an important role in transporting short‐lived chemical species rapidly from troposphere to stratosphere. This study shows that the simulations from a global cloud‐system resolving model, Nonhydrostatic Icosahedral Atmosphere Model (NICAM), can well capture observed spatiotemporal variations of tropical ODCs. The NICAM simulations predict that by the end of the 21st century (2075–2104) versus the historical period (1979–2008) with a global‐mean surface air temperature increase of 2.67 K, ODC occurrences with cloud tops reaching above 15.5, 16.9, and 18.4 km will increase by 14%, 59%, and 189%, respectively. Thus ODCs with higher cloud tops increase by a larger fraction than ODCs with lower cloud tops. The corresponding changes in ODC occurrences over the future warmer (hotter) and wetter (drier) oceanic (terrestrial) environments will be 20% (−2%), 72% (27%), and 240% (98%). Thus ODCs over ocean generally increase at a faster rate than over land. With tropical cold point tropopause height as a reference level, which will increase from 17.2 to 18.1 km, ODCs will increase by only 8% over the tropics, with 15% over ocean but decrease by −8% over land. Key Points The Nonhydrostatic Icosahedral Atmosphere Model well reproduces observed spatiotemporal distributions of tropical overshooting deep convections (ODCs) Tropical ODC increases with global temperature on ocean (land) by 7%/K (−1%/K) for ODCs above 15.5 km, 27%/K (10%/K) above 16.9 km, and 90%/K (37%/K) above 18.4 km Response of tropical ODCs that penetrate the tropical cold point tropopause height to global warming is 3%/K, with 6%/K over the ocean and −3%/K on land

Future changes in tropical cyclone (TC) activity and structure are investigated using the outputs of a 14-km mesh climate simulation. A set of 30-yr simulations was performed under present-day and warmer climate conditions using a nonhydrostatic icosahedral atmospheric model with explicitly calculated convection. The model projected that the global frequency of TCs is reduced by 22.7%, the ratio of intense TCs is increased by 6.6%, and the precipitation rate within 100 km of the TC center increased by 11.8% under warmer climate conditions. These tendencies are consistent with previous studies using a hydrostatic global model with cumulus parameterization. The responses of vertical and horizontal structures to global warming are investigated for TCs with the same intensity categories. For TCs whose minimum sea level pressure (SLP) reaches less than 980 hPa, the model predicted that tangential wind increases in the outside region of the eyewall. Increases in the tangential wind are related to the elevation of the tropopause caused by global warming. The tropopause rise induces an upward extension of the eyewall, resulting in an increase in latent heating in the upper layers of the inclined eyewall. Thus, SLP is reduced underneath the warmed eyewall regions through hydrostatic adjustment. The altered distribution of SLP enhances tangential winds in the outward region of the eyewall cloud. Hence, this study shows that the horizontal scale of TCs defined by a radius of 12 m s−1 surface wind is projected to increase compared with the same intensity categories for SLP less than 980 hPa.

Reducing the computational cost of weather and climate simulations would lower electric energy consumption. From the standpoint of reducing costs, the use of reduced precision arithmetic has become an active area of research. Here the impact of using single-precision arithmetic on simulation accuracy is examined by conducting Jablonowski and Williamson’s baroclinic wave tests using the dynamical core of a global fully compressible nonhydrostatic model. The model employs a finite-volume method discretized on an icosahedral grid system and its mesh size is set to 220, 56, 14, and 3.5 km. When double-precision arithmetic is fully replaced by single-precision arithmetic, a spurious wavenumber-5 structure becomes dominant in both hemispheres, rather than the expected baroclinic wave growth only in the Northern Hemisphere. It was found that this spurious wave growth comes from errors in the calculation of gridcell geometrics. Therefore, an additional simulation was conducted using double precision for calculations that only need to be performed for model setup, including calculation of gridcell geometrics, and single precision everywhere else, meaning that all calculations performed each time step used single precision. In this case, the model successfully simulated the growth of the baroclinic wave with only small errors and a 46% reduction in runtime. These results suggest that the use of single-precision arithmetic will allow significant reduction of computational costs in next-generation weather and climate simulations using a fully compressible nonhydrostatic global model with the finite-volume method.

This study examined the responses of Asian monsoon precipitation to global warming on the regional scale, focusing on monsoon westerlies and monsoon trough. This is because the Asian monsoon precipitation is closely associated with tropical disturbances. To reproduce convective precipitation and tropical disturbances, this study used outputs of a high-resolution climate simulation. Two sets of approximately 30-yr simulations under present-day (control) and warmer climate conditions (global warming) were conducted by the 14-km Nonhydrostatic Icosahedral Atmospheric Model (NICAM) with explicitly calculated convection. For understanding the spatial pattern of future precipitation changes, a further set of a 5-yr simulation [sea surface temperature (SST) + 4 K] was also conducted. Overall, the Asian summer monsoon was well simulated by the model. Precipitation increased as a result of global warming along the monsoon trough, which was zonally elongated across northern India, the Indochina Peninsula, and the western North Pacific Ocean. This increased precipitation was likely due to an increase in precipitable water. The spatial pattern of the increased precipitation was associated with enhanced cyclonic circulations over a large area along the monsoon trough, although it was difficult to determine whether the large-scale monsoon westerly was enhanced. This enhancement can be explained by future changes in tropical disturbance activity, including weak tropical cyclones. However, over part of South Asia, circulation changes may not contribute to the increased precipitation, suggesting regional characteristics. The regional increase in precipitation along the monsoon trough was mostly explained by the uniform increase in SST, whereas SST spatial patterns are important over some regions.

A review of the experimental protocol and motivation for DYAMOND, the first intercomparison project of global storm-resolving models, is presented. Nine models submitted simulation output for a 40-day (1 August–10 September 2016) intercomparison period. Eight of these employed a tiling of the sphere that was uniformly less than 5 km. By resolving the transient dynamics of convective storms in the tropics, global storm-resolving models remove the need to parameterize tropical deep convection, providing a fundamentally more sound representation of the climate system and a more natural link to commensurately high-resolution data from satellite-borne sensors. The models and some basic characteristics of their output are described in more detail, as is the availability and planned use of this output for future scientific study. Tropically and zonally averaged energy budgets, precipitable water distributions, and precipitation from the model ensemble are evaluated, as is their representation of tropical cyclones and the predictability of column water vapor, the latter being important for tropical weather.

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.

The Deep Numerical Analysis for Climate (DNA-Climate) is a pilot project to develop an Earth system model on a kilometer-scale horizontal mesh. The acronym “DNA” is based on the analogies between the hierarchical structures of atmospheric phenomena and living organisms. The multiscale structure of clouds and circulations may be analogous to the multiscale structure of cells and organs organized according to the blueprint, deoxyribonucleic acid (DNA). Whereas global cloud-resolving models (CRMs) can produce better solutions on shorter time scales that are decisively governed by the initial conditions, global climate models (GCMs) may generate reliable solutions on longer time scales that are largely determined to balance energy inputs and outputs. Our challenge is to build a physically valid model that consistently bridges the shorter- and longer-time-scale solutions in the intermediate time scales. Research topics of DNA-Climate are configured in consideration of the structural similarity between the climate modeling and the technique of matched asymptotic expansions in mathematics. The central question is whether a single modeling framework using only either global CRM or GCM will work adequately at all time scales of climate, or whether a multiscale modeling framework combining several models, of which each is only valid for limited time scales, will be needed. A multiscale modeling is an attractive framework for advancing climate modeling and would be an intriguing topic to be studied in parallel with global CRMs and GCMs.

Typhoon Faxai hit Japan in 2019 and severely damaged the Tokyo metropolitan area. To mitigate such damages, a good track forecast is necessary even before the typhoon formation. To investigate the predictability of the genesis and movement of a precursor vortex and its relationship with the synoptic‐scale flow, 100‐member ensemble simulations of Typhoon Faxai were performed using a 14‐km mesh global nonhydrostatic atmospheric model, which started from 16 different initial days (i.e., 1,600 members in total). The results show that the model could predict an enhanced risk of a Faxai‐like vortex heading toward Japan 2 weeks before landfall, which was up to 70%. The reason for the enhancement was a rapid increase in the members reproducing a precursor vortex from 15 to 12 days before landfall in Japan. In addition, the upper‐tropospheric vortex played an essential role in the track simulation of Faxai. Plain Language Summary Tropical cyclones severely damage coastal regions yearly. Typhoon Faxai hit Japan in 2019 and severely damaged buildings, power grids, and cell phone networks in the Tokyo metropolitan area. To mitigate such damages, better track forecast is necessary even from the timing before typhoon formation. A large ensemble member (1,600‐member in total) and high‐resolution (14‐km) simulation was performed to investigate the genesis and movement of the precursor vortex of Faxai in 2019 and its relationship with the synoptic‐scale environmental flow using a global nonhydrostatic atmospheric model on the Supercomputer Fugaku. The results show the model could predict an enhanced risk of a Faxai‐like vortex heading toward Japan 2 weeks before landfall. A reason for the enhancement was a rapid increase in the members reproducing a precursor vortex from 15 to 12 days before landfall in Japan. In addition, the upper‐tropospheric vortex played an essential role in the movement of the Faxai‐like vortex. Key Points A 1,600‐member ensemble simulation in total for Typhoon Faxai (2019) was performed using a 14‐km mesh nonhydrostatic atmospheric model The model successfully predicts the risk of Faxai's landfall in Japan 2 weeks in advance Reproducibilities of the precursor vortex and upper‐tropospheric vortex yield good prediction of the formation and track of Faxai

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.