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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

We present an analysis of extreme precipitation events in convection-resolving climate simulations. The simulations are performed with the COSMO-CLM model at 2.2 km resolution across an extended Alpine region and its larger-scale surrounding. Generalized extreme value theory (GEV) is applied to address projections of 5-day, daily and hourly extreme precipitation events in all seasons. Validation using ERA-Interim driven simulations reveals significant improvements with the 2.2 km resolution. In comparison to its driving 12 km model, high resolution improves the simulation of precipitation on most investigated timescales and seasons. The climate change signal is analyzed in 10-year long control and scenario simulations (1991–2000 and 2081–2090) driven by a CMIP5 coupled climate model (MPI-ESM-LR) under an RCP8.5 greenhouse gas scenario. Analysis shows negligible differences between the two resolutions for winter precipitation on all time scales, while in the other seasons the 2.2 km model shows smaller changes in extreme hourly precipitation, and yields narrower uncertainty estimates. Changes in extreme summer precipitation qualitatively scale with the Clausius–Clapeyron rate, i.e., 6–7% per degree warming, and are consistent with previous percentile based analysis. In winter, changes exceed the Clausius–Clapeyron rate. Some interpretations of this result are provided.

Convection-resolving models (CRMs) can explicitly simulate deep convection and resolve interactions between convective updrafts. They are thus increasingly used in numerous weather and climate applications. However, the truncation of the continuous energy cascade at scales of O(1 km) poses a serious challenge, as in kilometer-scale simulations the size and properties of the simulated convective cells are often determined by the horizontal grid spacing (Δx).In this study, idealized simulations of deep moist convection over land are performed to assess the convergence behavior of a CRM at Δx= 8, 4, 2, 1 km and 500 m. Two types of convergence estimates are investigated: bulk convergence addressing domain-averaged and integrated variables related to the water and energy budgets, and structural convergence addressing the statistics and scales of individual clouds and updrafts. Results show that bulk convergence generally begins at Δx=4 km, while structural convergence is not yet fully achieved at the kilometer scale, despite some evidence that the resolution sensitivity of updraft velocities and convective mass fluxes decreases at finer resolution. In particular, at finer grid spacings the maximum updraft velocity generally increases, and the size of the smallest clouds is mostly determined by Δx. A number of different experiments are conducted, and it is found that the presence of orography and environmental vertical wind shear yields more energetic structures at scales much larger than Δx, sometimes reducing the resolution sensitivity. Overall the results lend support to the use of kilometer-scale resolutions in CRMs, despite the inability of these models to fully resolve the associated cloud field.

The aggregation of tropical convection greatly influences the mean‐state of the atmosphere, altering humidity distributions, total atmospheric radiative cooling, and cloud amounts. Although studies have demonstrated the sensitivity of convective aggregation to horizontal resolution and domain size, few studies have explored the impact of vertical resolution on convective aggregation. Here, we investigate the impact of vertical resolution on simulations of deep convection and convective aggregation using the System for Atmospheric Modeling convection resolving model. We analyze simulations of tropical radiative‐convective equilibrium with varying vertical levels (32, 64, 128, and 256) across small (100 km), medium (700 km) and large (1,500 km) domains. We demonstrate that relative humidity and cloud fraction decrease with increasing vertical resolution as a result of reduced turbulent mixing. Vertical resolution also influences the occurrence of, onset time, and equilibrium intensity of aggregated convection, and also appears to affect the sensitivity of convective aggregation to domain size. Understanding how simulated convection aggregates, as well as its simulated sensitivity to model formulation, is critical for making and interpreting future predictions of global climate change. Plain Language Summary We study the simulation of clouds and storms in simple computer models of the tropical atmosphere. These models calculate air movement on a grid. Large grid boxes result in a very coarse, pixelated representation of the atmosphere, while smaller grid boxes offer a much clearer, high‐resolution video. Ideally, the average air movement, cloud formation, and rainfall simulated by these models shouldn't be affected by the size of the grid boxes, with smaller boxes just providing additional detail. However, here we show that the height of grid boxes influences average properties of the simulations, such as the total cloud amount, the amount of rain that falls, and the relative humidity. Key Points The relative humidity and high cloud fraction both decrease with increasing vertical resolution in System for Atmospheric Modeling Vertical resolution impacts convective aggregation occurrence, onset time, and equilibrium intensity The sensitivity of convective aggregation to domain size may depend on vertical resolution

Over the past few decades the horizontal resolution of regional climate models (RCMs) has steadily increased, leading to a better representation of small-scale topographic features and more details in simulating dynamical aspects, especially in coastal regions and over complex terrain. Due to its complex terrain, the broader Adriatic region represents a major challenge to state-of-the-art RCMs in simulating local wind systems realistically. The objective of this study is to identify the added value in near-surface wind due to the refined grid spacing of RCMs. For this purpose, we use a multi-model ensemble composed of CORDEX regional climate simulations at 0.11° and 0.44° grid spacing, forced by the ERA-Interim reanalysis, a COSMO convection-parameterizing simulation at 0.11° and a COSMO convection-resolving simulation at 0.02° grid spacing. Surface station observations from this region and satellite QuikSCAT data over the Adriatic Sea have been compared against daily output obtained from the available simulations. Both day-to-day wind and its frequency distribution are examined. The results indicate that the 0.44° RCMs rarely outperform ERA-Interim reanalysis, while the performance of the high-resolution simulations surpasses that of ERA-Interim. We also disclose that refining the grid spacing to a few km is needed to properly capture the small-scale wind systems. Finally, we show that the simulations frequently yield the accurate angle of local wind regimes, such as for the Bora flow, but overestimate the associated wind magnitude. Finally, spectral analysis shows good agreement between measurements and simulations, indicating the correct temporal variability of the wind speed.

The fractional entrainment rate in convective clouds is an important parameter in current convective parameterization schemes of climate models. In this paper, it is estimated using a 1-km-resolution cloud-resolving model (CRM) simulation of convective clouds from TWP-ICE (the Tropical Warm Pool-International Cloud Experiment). The clouds are divided into different types, characterized by cloud-top heights. The entrainment rates and moist static energy that is entrained or detrained are determined by analyzing the budget of moist static energy for each cloud type. Results show that the entrained air is a mixture of approximately equal amount of cloud air and environmental air, and the detrained air is a mixture of ~80 % of cloud air and 20 % of the air with saturation moist static energy at the environmental temperature. After taking into account the difference in moist static energy between the entrained air and the mean environment, the estimated fractional entrainment rate is much larger than those used in current convective parameterization schemes. High-resolution (100 m) large-eddy simulation of TWP-ICE convection was also analyzed to support the CRM results. It is shown that the characteristics of entrainment rates estimated using both the high-resolution data and CRM-resolution coarse-grained data are similar. For each cloud category, the entrainment rate is high near cloud base and top, but low in the middle of clouds. The entrainment rates are best fitted to the inverse of in-cloud vertical velocity by a second order polynomial.

The dynamical system behaviour of tropical cyclones and their potential intensity with a view to sea surface temperature, tropospheric temperature stratification and tropospheric moisture content is investigated in the axisymmetric convective model HURMOD. The model results exhibit the existence of a fixed-point attractor associated with a strong tropical cyclone. Moreover, the initial vortex strength forms an amplitude threshold to cyclogenesis. Above this threshold, the size of the tropical cyclone and its intensity are independent of the initial vortex strength and its horizontal extent. Below the amplitude threshold, cyclogenesis does not occur and the system approaches an atmospheric state of rest. In case one allows for a deviation of the tropospheric stratification from moist-neutral conditions, the modelling results reveal the existence of bifurcations with the sea surface temperature representing the bifurcation parameter: As the sea surface temperature decreases and the storm weakens, the fixed-point attractor turns first into a limit cycle indicating a Hopf-bifurcation and then gives way to a steady-state of lower intensity, before the intensity oscillation becomes chaotic, and finally the tropical storm dies. The amplitude threshold and the sea surface temperature range, within which the system exhibits bifurcation points, are sensitive to the reference value of relative humidity and the reference tropospheric temperature stratification. If the reference troposphere is presumed to be moist-neutral, the dynamical behaviour of the modelled tropical cyclone does not change within the range of tropical sea surface temperature, and the tropical cyclone only slightly weakens with decreasing sea surface temperature, without any abrupt changes in intensity. Apart from the existence of Hopf-bifurcations, these findings are qualitatively similar to results gained from a low-order model presented in a precursory study.

Global cloud-resolving models (GCRMs) are a new category of atmospheric global models designed to solve different flavors of the nonhydrostatic equations through the use of kilometer-scale global meshes. GCRMs make it possible to explicitly simulate deep convection, thereby avoiding the need for cumulus parameterization and allowing for clouds to be “resolved” by microphysical models responding to grid-scale forcing. GCRMs require high-resolution discretization over the globe, for which a variety of mesh structures have been proposed and employed. The first GCRM was constructed 15 years ago, and in recent years, other groups have also begun adopting this approach, enabling the first intercomparison studies of such models. Because conventional general circulation models (GCMs) suffer from large biases associated with cumulus parameterization, GCRMs are attractive tools for researchers studying global weather and climate. In this review, GCRMs are described, with some emphasis on their historical development and the associated literature documenting their use. The advantages of GCRMs are presented, and currently existing GCRMs are listed and described. Future prospects for GCRMs are also presented in the final section.

This paper describes the first implementation of the Δx = 3.25 km version of the Energy Exascale Earth System Model (E3SM) global atmosphere model and its behavior in a 40‐day prescribed‐sea‐surface‐temperature simulation (January 20 through February 28, 2020). This simulation was performed as part of the DYnamics of the Atmospheric general circulation Modeled On Non‐hydrostatic Domains (DYAMOND) Phase 2 model intercomparison. Effective resolution is found to be ∼6× the horizontal dynamics grid resolution despite using a coarser grid for physical parameterizations. Despite this new model being in an immature and untuned state, moving to 3.25 km grid spacing solves several long‐standing problems with the E3SM model. In particular, Amazon precipitation is much more realistic, the frequency of light and heavy precipitation is improved, agreement between the simulated and observed diurnal cycle of tropical precipitation is excellent, and the vertical structure of tropical convection and coastal stratocumulus look good. In addition, the new model is able to capture the frequency and structure of important weather events (e.g., tropical cyclones, extratropical cyclones including atmospheric rivers, and cold air outbreaks). Interestingly, this model does not get rid of the erroneous southern branch of the intertropical convergence zone nor the tendency for strongest convection to occur over the Maritime Continent rather than the West Pacific, both of which are classic climate model biases. Several other problems with the simulation are identified, underscoring the fact that this model is a work in progress. Plain Language Summary This paper describes the new global 3.25 km version of the Energy Exascale Earth System Model (E3SM) atmosphere model and its behavior in a 40‐day northern‐hemisphere wintertime simulation. In exchange for huge computational expense, this high‐resolution model avoids many but not all biases common in lower‐resolution models. It also captures several types of extreme weather that would simply not be resolved in lower‐resolution models. Several opportunities for further development are identified. Key Points Describes the Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) SCREAM performs well in a 40‐day boreal winter simulation at 3.25 km Δx Resolving deep convection solves many long‐standing climate model biases

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