The achievement, published in the journal Geophysical Research Letters by project researcher Shuhei Matsugishi and colleagues Masaki Satoh and Tomoki Ohno of the Atmosphere and Ocean Research Institute, is being described as the world’s first demonstration of a global large-eddy simulation, or GLES. Large-eddy simulation is a technique long used in small-scale fluid dynamics studies to resolve the largest turbulent eddies explicitly rather than modeling them statistically. Applying it to the whole planet means that the fine internal anatomy of deep convective clouds, including the storm-bringing cumulonimbus systems that deliver much of the world’s heaviest rainfall, can be represented directly. Individual updrafts and downdrafts, the vertical conveyor belts of rising and sinking air that drive a storm’s growth, become visible features of the simulation rather than assumed quantities.

To appreciate why this matters, it helps to understand the hierarchy of global models. Conventional global climate models, or GCMs, typically operate with grid cells spanning tens to hundreds of kilometers. At those scales, an entire thunderstorm fits comfortably inside a single cell, so the model must guess at its behavior using relationships derived from observations and theory. More recent global storm-resolving models, or GSRMs, narrow the spacing to between one and ten kilometers, which allows them to resolve the largest storm systems explicitly and to capture how those systems interact with larger-scale atmospheric and energy flows. Even at kilometer resolution, however, the fine-grained turbulence inside a convective cloud remains below the resolvable limit, and parameterization schemes still shape the model’s behavior in ways that can distort rainfall patterns.

Popcornlike rain is one of the clearest symptoms of that distortion. In current GSRMs, precipitation tends to appear as scattered, unrealistically intense, highly localized bursts, resembling kernels of popcorn popping across the map. These phantom downpours arise because the parameterization schemes that trigger convection at sub-kilometer scales do not communicate properly with their neighbors, so rain forms in isolated cells rather than in the broader, more organized structures seen in nature. Because the bias is systematic rather than random, it can skew a model’s estimates of where and how heavily rain falls, which in turn affects projections of flooding risk, water resources, and the atmospheric energy budget. In the Tokyo team’s 220-meter simulation, precipitation emerged in a far more realistic pattern, without those spurious localized bursts, because convection no longer needed to be parameterized at all.

The finer resolution also changes what scientists can study. As Matsugishi explained, representing the internal structure of convective clouds explicitly opens the possibility of investigating not only individual clouds but also how they interact with one another and with the larger-scale atmospheric circulation. Convection is not a purely local phenomenon: clusters of thunderstorms organize into larger systems, those systems influence the circulation around them, and the circulation in turn determines where new storms form. A global simulation that resolves each link in that chain provides a virtual laboratory in which these feedbacks can be observed directly, something that has previously been possible only in limited regional domains or in heavily simplified idealized setups.

The demonstration came at a staggering computational price. The simulation contained nearly one trillion three-dimensional grid points, each representing a data location across the globe and through the depth of the atmosphere. To simulate a single eight-hour period, specifically August 5, 2016, the team had to occupy more than half of the supercomputer Fugaku simultaneously, one of the most powerful machines in the world. The energy consumed was equivalent to roughly forty years of electricity use by an average Japanese household. The chosen date was not arbitrary: it allowed the researchers to validate their simulation against a real tropical weather system, Typhoon Omais, and to compare how the storm’s precipitation rate and location appeared at kilometer-scale versus 200-meter grid spacing, with the finer version showing markedly more realistic structure.

Despite the success, the researchers are careful about what the result does and does not imply for forecasting. At present, a global simulation at 220-meter resolution is far too computationally expensive to replace operational weather prediction systems, which must deliver forecasts within hours on fixed computing budgets. For now, Matsugishi noted, these simulations are better suited to research experiments. One promising application is the detailed study of tropical convection and heavy rainfall, processes that remain among the largest sources of uncertainty in climate science. Another is the use of the high-resolution output as a reference benchmark: because the GLES resolves processes that coarser models must parameterize, its results can serve as ground truth against which the parameterization schemes in kilometer-scale and hundred-kilometer-scale models can be evaluated and improved.

Indeed, the new model is not bias-free. While the higher resolution eliminated the popcornlike rain artifact, other biases related to the distribution of cloud cover persisted, a reminder that resolving more of the atmosphere does not automatically resolve every problem. Cloud microphysics, the microscopic processes by which water vapor condenses into droplets and ice crystals, still must be represented through simplified schemes even in a large-eddy simulation, and turbulence near the smallest scales remains only partially resolved. The team intends to use the model to investigate the characteristics and properties of convective clouds in much greater detail, with the goal of understanding how turbulence, cloud microphysics, and other unresolved processes should be represented as global models march from kilometer scale to several-hundred-meter and eventually tens-of-meters resolution.

The timing of the work is significant. This year has brought record-breaking weather across multiple continents, with intense storms battering Europe, exceptional August heat, and devastating flooding in parts of Asia and Africa. Climate change is expected to make strong and unpredictable storms more common, raising the stakes for precise climate modeling, weather forecasting, and early warning systems. Better representation of convection is central to that effort, because convective storms deliver extreme rainfall and are poorly captured by coarse models. Ultimately, the researchers argue, the kind of explicit simulation demonstrated here could better represent extreme weather and reduce uncertainties in future weather and climate predictions, turning what is today a research experiment running on one of the world’s largest supercomputers into the foundation of tomorrow’s forecasting systems.

The study, titled Resolution Dependence in a Global Atmospheric Simulation from km to 220 m Grid Spacing, was supported by JSPS KAKENHI grants and by the Core-to-Core Program, with simulations performed on the Fugaku supercomputer under a series of project proposals. It stands as a proof of concept for a new tier in the hierarchy of atmospheric models, one in which the planet’s storms are no longer approximated but resolved, and in which the errors born of approximation, like the phantom popcorn rain that has plagued global simulations for years, can finally be left behind.

Subject of Research: A 220-meter-resolution global large-eddy atmospheric simulation that eliminates the popcornlike rain bias in global storm-resolving models

Article Title: New 220-meter global atmospheric model erases “popcornlike” rain

Article References: New 220-meter global atmospheric model erases “popcornlike” rain. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: global large-eddy simulation, atmospheric modeling, convection, cumulonimbus clouds, popcornlike rain bias, grid resolution, supercomputer Fugaku, Typhoon Omais, climate prediction, weather forecasting, cloud microphysics, Geophysical Research Letters