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The Non-hydrostatic ICosahedral Atmospheric Model (NICAM), a global model with an icosahedral grid system, has been under development for nearly two decades. Here, we present its recent updates for the Coupled Model Intercomparison Project Phase 6, High Resolution Model Intercomparison Project (HighResMIP) and their impact on the simulated mean states using 56-14km mesh model. Major updates include 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. A short-term sensitivity experiments demonstrate 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. The decadal climate simulations further reveal an improvement in the genesis and structure of the tropical cyclones compared with those with the previous model. Finally, we will address outlook toward the cloud-resolving climate simulation based on a fresh benchmark result on supercomputer Fugaku, a flagship supercomputer in Japan.

The stable water isotopes (SWIs) (δ18O and δD) are used as an indicator of the intensity of the atmospheric hydrological cycle due to their large variability in time and space. Although data about vapor isotope ratio with high frequency and high resolution are now available by satellite observations and spectroscopic analyses, there is some room for discussion on the variability of isotope ratios in vapor and precipitation related to cloud microphysical processes.Here, we incorporated SWI tracer into the latest version of a global cloud system resolving model (the Nonhydrostatic Icosahedral Atmospheric Model (NICAM)), iso-NICAM, and investigated the contribution of cloud microphysical processes to the variability of isotope ratios in precipitation and vapor. One of the merits used NICAM is that its physical process can cover from low spatial resolution to high spatial resolution. We conducted two mode simulations (GCM and CRM). The GCM mode simulation is based on the Arakawa-Schubert scheme as convective parameterization and a large-scale condensation scheme as the cloud physical process. In contrast, the CRM mode simulation is based on the a single-moment bulk cloud microphysics scheme with 6 water categories as cloud microphysical scheme, convective parameterization scheme was not used. These simulations are set to about 223 km of horizontal mesh resolution and 78 vertical layers. We conducted an AMIP-type climate experiment for one year from 1979.The simulated precipitation δ18O showed the latitude effect pattern (high δ18O in low latitude region, low δ18O in high latitude region), but those values in the CRM mode was slightly lower than that in the GCM mode . The simulated precipitation δ18O in the CRM mode was lower in high altitude or inland regions compared with those in the GCM mode . Besides, the precipitation d-excess in the CRM mode shows large spatial variability compared with the GCM mode. Although the low spatial resolution was set in this study, these simulations indicated cloud microphysical processes are important for understanding the variability of isotope physics. We will conduct these simulations with finer spatial resolution and a more extended simulation period.

In parallel with the new Japanese flagship supercomputer, Fugaku, we have continued improving a nonhydrostatic icosahedral atmospheric model (NICAM). Here, we introduce the results of our system-application co-design since 2014. Fugaku's CPU (A64FX) is based on the Arm instruction-set architecture. This 48-core many-core CPU is equipped with 32GB of HBM2 memory, showing data transfer performance comparable to GPUs. We have implemented kernel-level optimizations to take advantage of Fugaku's high memory performance. Among them, we recognized trade-offs related to ensuring memory locality and parallelism, and register allocation. We improved the application's average arithmetic intensity through detailed loop-by-loop performance measurements and reduced memory pressure by actively using single-precision operations. We also redesigned the data layout and the file I/O component of the ensemble data assimilation (DA) system and achieved good scalability in the atmospheric simulation and DA. We performed a global 3.5km mesh, 1024-member ensemble simulation, and DA using 82% of the Fugaku system (131,072 nodes, 6,291,456 cores). In this world's most massive ensemble DA benchmark experiment, the simulation and the DA achieved 29 PFLOPS and 79 PFLOPS of effective performance.

NICAM, a nonhydrostatic global atmospheric model with an icosahedral grid system, has been developed for nearly two decades. This paper describes NICAM16-S, the latest stable version of NICAM (NICAM.16) modified for Coupled Model Intercomparison Project Phase 6 (CMIP6). Major updates from NICAM.12, a previous version used for climate simulations, include updates of a cloud microphysics scheme and a land model, an introduction of natural and anthropogenic aerosols and a subgrid-scale orographic gravity wave drag, and improvement of coupling between cloud microphysics and radiation schemes. External forcings were updated to follow a protocol of CMIP6 High Resolution Model Intercomparison Project (HighResMIP). A series of short-term sensitivity experiments were performed to check and understand impacts of the model updates on the simulated mean states. Improvements in the ice water content, the high cloud amounts, the surface air temperature over the Arctic region, the location and the strength of zonal mean subtropical jet, and shortwave radiation over the Africa and the South Asia were found in the NICAM16-S simulations. Some long-standing biases such as the double intertropical convergence zone and smaller low cloud amounts still exist or even worsen in some cases, suggesting further necessity for understanding their mechanisms and upgrading schemes and/or their parameter settings as well as for enhancing horizontal and vertical resolutions.

A four-dimensional variational method (4D-Var) is a popular technique for source/sink inversions of atmospheric constituents, but it is not without problems. Using an icosahedral grid transport model and the 4D-Var method, a new atmospheric greenhouse gas (GHG) inversion system has been developed. The system combines offline forward and adjoint models with a quasi-Newton optimization scheme. The new approach is then used to conduct identical twin experiments to investigate optimal system settings for an atmospheric CO2 inversion problem, and to demonstrate the validity of the new inversion system. In this paper, the inversion problem is simplified by assuming the prior flux errors to be reasonably well known and by designing the prior error correlations with a simple function as a first step. It is found that a system of forward and adjoint models with smaller model errors but with nonlinearity has comparable optimization performance to that of another system that conserves linearity with an exact adjoint relationship. Furthermore, the effectiveness of the prior error correlations is demonstrated, as the global error is reduced by about 15 % by adding prior error correlations that are simply designed when 65 weekly flask sampling observations at ground-based stations are used. With the optimal setting, the new inversion system successfully reproduces the spatiotemporal variations of the surface fluxes, from regional (such as biomass burning) to global scales. The optimization algorithm introduced in the new system does not require decomposition of a matrix that establishes the correlation among the prior flux errors. This enables us to design the prior error covariance matrix more freely.

An aerosol-coupled global nonhydrostatic model with a stretched-grid system has been developed. Circulations over the global and target domains are simulated with a single model, which includes fine meshes covering the target region to calculate meso-scale circulations. The stretched global model involves lower computational costs to simulate atmospheric aerosols with fine horizontal resolutions compared with a global uniform nonhydrostatic model, whereas it may require higher computational costs compared with the general regional models, because the stretched-grid system calculates inside and outside the target domain. As opposed to general regional models, the stretched-grid system requires neither a nesting technique nor lateral boundary conditions. In this study, we developed a new-type regional model for the simulation of aerosols over Japan, especially in the Kanto areas surrounding Tokyo, with a maximum horizontal resolution of approximately 10 km. This model usually reproduces temporal variations and their averages of the observed weather around Japan. This model generally reproduces monthly mean distributions of the observed sulfate and SO2 over East Asia, with high correlations (R > 0.6), but the underestimation of the simulated concentrations by 40% (sulfate) and 50% (SO2). Their underestimation of the simulated sulfate and SO2 concentrations over East Asia are strongly affected by their underestimation in China and possibly by the uncertainty of the simulated precipitation around Japan. In the Kanto area, this model succeeds in simulating the wind patterns and the diurnal transitions around the center of the Kanto area, although it is inadequate to simulate the wind patterns and the diurnal transitions at some sites located at the edge of the Kanto area and surrounded on three sides by mountains, e.g., Maebashi, mainly due to the insufficient horizontal resolution. This model also generally reproduces both diurnal and synoptic variations of the observed and/or a regional aerosol-transport model, WRF-CMAQ, simulated EC, sulfate, and SO2 concentrations in the Kanto area, especially with their high correlation (R > 0.5) at Komae/Tokyo. Although the aerosol module used in this study is relatively simplified compared to the general regional aerosol models, this study reveals that our proposed model with the stretched-grid system can be applicable for the regional aerosol simulation.

The dynamical coupling process between the stratosphere and troposphere in the tropical tropopause layer (TTL) during a~stratospheric sudden warming (SSW) in boreal winter was investigated using simulation data from a global non-hydrostatic model (NICAM) that does not use cumulus parameterization. The model reproduced well the observed tropical tropospheric changes during the SSW, including the enhancement of convective activity following the amplification of planetary waves. Deep convective activity was enhanced in the latitude zone 20–10° S, in particular over the southwest Pacific and southwest Indian Ocean. Although the upwelling in the TTL was correlated with that in the stratosphere, the temperature tendency in the TTL changed little due to a compensation by diabatic heating originating from cloud formation. This result suggests that the stratospheric meridional circulation affects cloud formation in the TTL.

Recent advances in high-performance computers facilitate operational numerical weather prediction by global hydrostatic atmospheric models with horizontal resolutions of ∼ 10 km. Given further advances in such computers and the fact that the hydrostatic balance approximation becomes invalid for spatial scales

Using one month of the cloud-resolving Nonhydrostatic Icosahedral Atmospheric Model (NICAM) simulations, we examined the impact of different definitions of clear-sky flux on the determination of longwave cloud radiative forcing (CRF). Because the satellite-like cloud-free composite preferentially samples drier conditions relative to the all-sky mean state, the conventional clear-sky flux calculation using the all-sky mean state in the model may represent a more humid atmospheric state in comparison to the cloud-free state. The drier bias is evident for the cloud-free composite in the NICAM simulations, causing an overestimation of the longwave CRF by about 10% compared to the NICAM simulated longwave CRF. Overall, water vapor contributions of up to 10% of the total longwave CRF should be taken account for making model-generated cloud forcing comparable to the satellite measurements.