Explore the vast range of titles available.

This contribution describes the ocean biogeochemical component of the Geophysical Fluid Dynamics Laboratory's Earth System Model 4.1 (GFDL‐ESM4.1), assesses GFDL‐ESM4.1's capacity to capture observed ocean biogeochemical patterns, and documents its response to increasing atmospheric CO2. Notable differences relative to the previous generation of GFDL ESM's include enhanced resolution of plankton food web dynamics, refined particle remineralization, and a larger number of exchanges of nutrients across Earth system components. During model spin‐up, the carbon drift rapidly fell below the 10 Pg C per century equilibration criterion established by the Coupled Climate‐Carbon Cycle Model Intercomparison Project (C4MIP). Simulations robustly captured large‐scale observed nutrient distributions, plankton dynamics, and characteristics of the biological pump. The model overexpressed phosphate limitation and open ocean hypoxia in some areas but still yielded realistic surface and deep carbon system properties, including cumulative carbon uptake since preindustrial times and over the last decades that is consistent with observation‐based estimates. The model's response to the direct and radiative effects of a 200% atmospheric CO2 increase from preindustrial conditions (i.e., years 101–120 of a 1% CO2 yr−1 simulation) included (a) a weakened, shoaling organic carbon pump leading to a 38% reduction in the sinking flux at 2,000 m; (b) a two‐thirds reduction in the calcium carbonate pump that nonetheless generated only weak calcite compensation on century time‐scales; and, in contrast to previous GFDL ESMs, (c) a moderate reduction in global net primary production that was amplified at higher trophic levels. We conclude with a discussion of model limitations and priority developments. Plain Language Summary This paper describes and evaluates the ocean biogeochemical component of the Geophysical Fluid Dynamics Laboratory's Earth System Model 4.1 (GFDL‐ESM4.1). GFDL‐ESM4.1 was developed to study the past, present, and future evolution of the Earth system under scenarios for natural and anthropogenic drivers of Earth system change, including greenhouse gases and aerosols. The response of the ocean's vast carbon and heat reservoirs to accumulating greenhouse gases greatly reduces their atmospheric and terrestrial impacts, but also puts ocean environments and the marine resources they support at risk. Relative to previous models, GFDL‐ESM4.1 improves the representation of (a) ocean food webs connecting plankton and fish; (b) biological processes influencing the sequestration of carbon in the deep ocean; and (c) land‐atmosphere‐ocean nutrient exchanges. While simulations have biases, they capture many critical aspects of the global ocean carbon cycle and ocean ecosystem, including the observed uptake of anthropogenic carbon over the last ~150 yr. Projections suggest that continued CO2 increases could significantly decrease ocean productivity and the ocean's capacity to sequester atmospheric carbon. Key Points Enhanced plankton food webs, remineralization, and Earth system linkages yield skillful global carbon cycle and ecosystem simulations Ocean productivity estimates improved, but phosphate limitation and hypoxia overestimated in some areas High CO2 and associated warming substantially reduce the biological pump and ocean productivity across trophic levels

We document the configuration and emergent simulation features from the Geophysical Fluid Dynamics Laboratory (GFDL) OM4.0 ocean/sea ice model. OM4 serves as the ocean/sea ice component for the GFDL climate and Earth system models. It is also used for climate science research and is contributing to the Coupled Model Intercomparison Project version 6 Ocean Model Intercomparison Project. The ocean component of OM4 uses version 6 of the Modular Ocean Model and the sea ice component uses version 2 of the Sea Ice Simulator, which have identical horizontal grid layouts (Arakawa C‐grid). We follow the Coordinated Ocean‐sea ice Reference Experiments protocol to assess simulation quality across a broad suite of climate‐relevant features. We present results from two versions differing by horizontal grid spacing and physical parameterizations: OM4p5 has nominal 0.5° spacing and includes mesoscale eddy parameterizations and OM4p25 has nominal 0.25° spacing with no mesoscale eddy parameterization. Modular Ocean Model version 6 makes use of a vertical Lagrangian‐remap algorithm that enables general vertical coordinates. We show that use of a hybrid depth‐isopycnal coordinate reduces the middepth ocean warming drift commonly found in pure z* vertical coordinate ocean models. To test the need for the mesoscale eddy parameterization used in OM4p5, we examine the results from a simulation that removes the eddy parameterization. The water mass structure and model drift are physically degraded relative to OM4p5, thus supporting the key role for a mesoscale closure at this resolution. Key Points Documentation is provided for a new generation of NOAA‐GFDL CMIP6/OMIP ocean ice climate models Dynamical core and physical parameterizations are described and key features of interannual CORE simulations are assessed Using hybrid vertical coordinates reduces spurious ocean heat drift

The authors describe carbon system formulation and simulation characteristics of two new global coupled carbon–climate Earth System Models (ESM), ESM2M and ESM2G. These models demonstrate good climate fidelity as described in part I of this study while incorporating explicit and consistent carbon dynamics. The two models differ almost exclusively in the physical ocean component; ESM2M uses the Modular Ocean Model version 4.1 with vertical pressure layers, whereas ESM2G uses generalized ocean layer dynamics with a bulk mixed layer and interior isopycnal layers. On land, both ESMs include a revised land model to simulate competitive vegetation distributions and functioning, including carbon cycling among vegetation, soil, and atmosphere. In the ocean, both models include new biogeochemical algorithms including phytoplankton functional group dynamics with flexible stoichiometry. Preindustrial simulations are spun up to give stable, realistic carbon cycle means and variability. Significant differences in simulation characteristics of these two models are described. Because of differences in oceanic ventilation rates, ESM2M has a stronger biological carbon pump but weaker northward implied atmospheric CO₂ transport than ESM2G. The major advantages of ESM2G over ESM2M are improved representation of surface chlorophyll in the Atlantic and Indian Oceans and thermocline nutrients and oxygen in the North Pacific. Improved tree mortality parameters in ESM2G produced more realistic carbon accumulation in vegetation pools. The major advantages of ESM2M over ESM2G are reduced nutrient and oxygen biases in the southern and tropical oceans.

The physical climate formulation and simulation characteristics of two new global coupled carbon–climate Earth System Models, ESM2M and ESM2G, are described. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory’s previous Climate Model version 2.1 (CM2.1) while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4p1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in El Niño–Southern Oscillation being overly strong in ESM2M and overly weak in ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to total heat content variability given its lack of long-term drift, gyre circulation, and ventilation in the North Pacific, tropical Atlantic, and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to surface circulation given its superior surface temperature, salinity, and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. The overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon–climate models.

This paper documents time mean simulation characteristics from the ocean and sea ice components in a new coupled climate model developed at the NOAA Geophysical Fluid Dynamics Laboratory (GFDL). The GFDL Climate Model version 3 (CM3) is formulated with effectively the same ocean and sea ice components as the earlier CM2.1 yet with extensive developments made to the atmosphere and land model components. Both CM2.1 and CM3 show stable mean climate indices, such as large-scale circulation and sea surface temperatures (SSTs). There are notable improvements in the CM3 climate simulation relative to CM2.1, including a modified SST bias pattern and reduced biases in the Arctic sea ice cover. The authors anticipate SST differences between CM2.1 and CM3 in lower latitudes through analysis of the atmospheric fluxes at the ocean surface in corresponding Atmospheric Model Intercomparison Project (AMIP) simulations. In contrast, SST changes in the high latitudes are dominated by ocean and sea ice effects absent in AMIP simulations. The ocean interior simulation in CM3 is generally warmer than in CM2.1, which adversely impacts the interior biases.

Chlorophyll underpins ocean productivity yet simulating chlorophyll across biomes, seasons and depths remains challenging for earth system models. Inconsistencies are often attributed to misrepresentation of the myriad nutrient supply, growth and loss processes that govern phytoplankton biomass. They may also arise, however, from unresolved or misspecified photoacclimation or photoadaptation responses. A series of global ocean ecosystem simulations were conducted to assess these latter sensitivities: alternative photoacclimation schemes implicitly modulated investments in light harvesting versus photodamage avoidance and other cellular functions. Photoadaptation experiments probed the impact of adding low‐ and high‐light adapted phytoplankton ecotypes. Results showed that photoacclimation and photoadaptation alternatives generate chlorophyll differences exceeding a factor of 2 in some regions and seasons. In stratified waters, photoadaptation and acclimation to light levels over mixing depths consistent with the timescale of photoadaptation (days) benefitted model performance. In regions and seasons with deep mixed layers, surface‐skewed photoacclimation yielded improved fidelity across satellite chlorophyll products. Large photoacclimation‐driven differences in chlorophyll concentration had small impacts on primary productivity and carbon export, unlike those arising from changes in the nutrient supply. Improved photoacclimation and photoadaption constraints are thus needed to reduce ambiguities in the drivers of chlorophyll change and their biogeochemical implications. Plain Language Summary The light harvesting pigment chlorophyll enables microscopic plants called phytoplankton to provide the energy that supports ocean food webs and fisheries. Chlorophyll is also one of the most widely observed ocean ecosystem properties, with satellite and ship‐based ocean estimates revealing a rich mosaic of spatial and seasonal variability. Earth system models capture some of these patterns but miss others. This tempers confidence in future ocean ecosystem projections under climate change. We asked whether the missed patterns may arise from flawed assumptions about the way phytoplankton acclimate and adapt their chlorophyll investments to changing light and nutrient levels. We found that including a range of light adaptation strategies and assuming that phytoplankton in vigorously mixed parts of the ocean acclimate to conditions near the ocean's surface improved model performance. Our results also emphasized, however, that there are often multiple plausible ways to explain an observed chlorophyll pattern. A reduction in summer chlorophyll, for example, may indicate reduced nutrient supply or chlorophyll reductions to avoid over‐harvest of light energy under the intense summer sun. These alternatives have much different implications for the ecosystem. We thus emphasize the need for improved observations of acclimation and adaptation responses to reduce this ambiguity. Key Points Simulated chlorophyll was highly sensitive to photoacclimation uncertainties but primary production and export were not Model skill was improved with photoadaptation and surface‐skewed photoacclimation in deep mixed layers Improved photoacclimation constraints are needed to determine the drivers of chlorophyll misfits and their biogeochemical implications

We present a variable‐resolution global chemistry‐climate model (AM4VR) developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) for research at the nexus of US climate and air quality extremes. AM4VR has a horizontal resolution of 13 km over the US, allowing it to resolve urban‐to‐rural chemical regimes, mesoscale convective systems, and land‐surface heterogeneity. With the resolution gradually reducing to 100 km over the Indian Ocean, we achieve multi‐decadal simulations driven by observed sea surface temperatures at 50% of the computational cost for a 25‐km uniform‐resolution grid. In contrast with GFDL's AM4.1 contributing to the sixth Coupled Model Intercomparison Project at 100 km resolution, AM4VR features much improved US climate mean patterns and variability. In particular, AM4VR shows improved representation of: precipitation seasonal‐to‐diurnal cycles and extremes, notably reducing the central US dry‐and‐warm bias; western US snowpack and summer drought, with implications for wildfires; and the North American monsoon, affecting dust storms. AM4VR exhibits excellent representation of winter precipitation, summer drought, and air pollution meteorology in California with complex terrain, enabling skillful prediction of both extreme summer ozone pollution and winter haze events in the Central Valley. AM4VR also provides vast improvements in the process‐level representations of biogenic volatile organic compound emissions, interactive dust emissions from land, and removal of air pollutants by terrestrial ecosystems. We highlight the value of increased model resolution in representing climate–air quality interactions through land‐biosphere feedbacks. AM4VR offers a novel opportunity to study global dimensions to US air quality, especially the role of Earth system feedbacks in a changing climate. Plain Language Summary NOAA's Geophysical Fluid Dynamics Laboratory has developed a new variable‐resolution global chemistry‐climate model for research at the nexus of US climate and air quality extremes. In contrast with the global models contributing to the latest Intergovernmental Panel on Climate Change Report, this model features more than 10 times finer spatial resolution over the contiguous US, allowing it to better resolve cities, mountain valleys, thunderstorms, and urban‐to‐rural air quality variations. This model features much improved representation of regional rainfall extremes, drought, and severe air pollution events in diverse US air basins, including California. Notably, this model reduces the central US dry‐and‐warm bias that has persisted in many generations of climate models. As global climate change leads to more hot and dry weather, the resulting droughts are creating dust‐prone bare lands or stressing plants, making them less able to remove ozone pollution from the air. These effects are included in this model, with particular focus on integrating physical, chemical, and biological components at high spatial resolution to understand Earth system feedbacks to US air quality extremes in a changing climate. Key Points A new variable‐resolution global chemistry‐climate model has been developed for research at the nexus of US climate and air quality extremes This model unifies component advances in physics, chemistry and land‐atmosphere interactions within a seamless variable‐resolution framework This model features much improved US regional precipitation, drought, and air quality extremes compared to previous models

A climate model represents a multitude of processes on a variety of timescales and space scales: a canonical example of multi-physics multi-scale modeling. The underlying climate system is physically characterized by sensitive dependence on initial conditions, and natural stochastic variability, so very long integrations are needed to extract signals of climate change. Algorithms generally possess weak scaling and can be I/O and/or memory-bound. Such weak-scaling, I/O, and memory-bound multi-physics codes present particular challenges to computational performance. Traditional metrics of computational efficiency such as performance counters and scaling curves do not tell us enough about real sustained performance from climate models on different machines. They also do not provide a satisfactory basis for comparative information across models. codes present particular challenges to computational performance. We introduce a set of metrics that can be used for the study of computational performance of climate (and Earth system) models. These measures do not require specialized software or specific hardware counters, and should be accessible to anyone. They are independent of platform and underlying parallel programming models. We show how these metrics can be used to measure actually attained performance of Earth system models on different machines, and identify the most fruitful areas of research and development for performance engineering. codes present particular challenges to computational performance. We present results for these measures for a diverse suite of models from several modeling centers, and propose to use these measures as a basis for a CPMIP, a computational performance model intercomparison project (MIP).

We present the GFDL‐CM4X (Geophysical Fluid Dynamics Laboratory Climate Model version 4X) coupled climate model hierarchy. The primary application for CM4X is to investigate ocean and sea ice physics as part of a realistic coupled Earth climate model. CM4X utilizes an updated MOM6 (Modular Ocean Model version 6) ocean physics package relative to CM4.0, and there are two members of the hierarchy: one that uses a horizontal grid spacing of 0.25°$0.25{}^{\\circ}$(referred to as CM4X‐p25) and the other that uses a 0.125°$0.125{}^{\\circ}$grid (CM4X‐p125). CM4X also refines its atmospheric grid from the nominally 100 km (cubed sphere C96) of CM4.0–50 km (C192). Finally, CM4X simplifies the land model to allow for a more focused study of the role of ocean changes to global mean climate. CM4X‐p125 reaches a global ocean area mean heat flux imbalance of −0.02Wm−2${-}0.02\\hspace*{.5em}\\mathrm{W}\\hspace*{.5em}{\\mathrm{m}}^{-2}$within O(150)$\\mathcal{O}(150)$years in a pre‐industrial simulation, and retains that thermally equilibrated state over the subsequent centuries. This 1850 thermal equilibrium is characterized by roughly 400ZJ$400\\hspace*{.5em}\\text{ZJ}$less ocean heat than present‐day, which corresponds to estimates for anthropogenic ocean heat uptake between 1870 and present‐day. CM4X‐p25 approaches its thermal equilibrium only after more than 1000 years, at which time its ocean has roughly 1100ZJ$1100\\hspace*{.5em}\\text{ZJ}$more heat than its early 21st century ocean initial state. Furthermore, the root‐mean‐square sea surface temperature bias for historical simulations is roughly 20% smaller in CM4X‐p125 relative to CM4X‐p25 (and CM4.0). We offer the mesoscale dominance hypothesis for why CM4X‐p125 shows such favorable thermal equilibration properties. Plain Language Summary We detail a new climate model hierarchy, CM4X. CM4X has two model configurations, CM4X‐p25 and CM4X‐p125, that differ only in the ocean/sea ice horizontal grid spacing. CM4X‐p125 outperforms CM4X‐p25 for certain climate processes, while maintaining skill levels seen in previous generations for other results. CM4X‐p125 requires about 10 times less time than CM4X‐p25 to reach pre‐industrial control thermal equilibration. Also, CM4X‐p125 equilibrates to an ocean state with roughly 400 ZJ less heat content than present‐day, consistent with estimates of anthropogenic heat uptake since 1870, whereas CM4X‐p25 equilibrates to a state with roughly 1100 ZJ more heat than present‐day. Consequently, the CM4X‐p125 ocean state has not drifted far from observational estimates. We propose the mesoscale dominance hypothesis to interpret the relatively rapid thermal equilibration of CM4X‐p125 to a cooler and more realistic pre‐industrial state. Such ocean models result from negligible spurious mixing (from numerical truncation errors) along with an active mesoscale transport and realistic parameterization of small scale (diapycnal) mixing. Noting the preliminary nature of our results, and with caveats detailed in this paper, we suggest that the more rapid thermal equilibration possible from mesoscale dominant ocean models greatly reduces the computational energy footprint of models that are not mesoscale dominant. Key Points CM4X‐p25 and CM4X‐p125 are designed to study ocean and sea ice physics, focusing on effects from eddies and boundary currents CM4X‐p125 reaches pre‐industrial thermal equilibrium in 150 years whereas the coarser CM4X‐p25 has yet to equilibrate after 1000 years CM4X‐p125's active eddies and negligible spurious mixing render an equilibrated pre‐industrial ocean with 400ZJ less heat than present day

This paper is Part II of a two‐part paper that documents the Climate Model version 4X (CM4X) hierarchy of coupled climate models developed at the Geophysical Fluid Dynamics Laboratory. Part I of this paper is presented in Griffies et al. (2025a, https://doi.org/10.1029/2024MS004861). Here we present a suite of case studies that examine ocean and sea ice features that are targeted for further research, which include sea level, eastern boundary upwelling, Arctic and Southern Ocean sea ice, Southern Ocean circulation, and North Atlantic circulation. The case studies are based on experiments that follow the protocol of version 6 from the Coupled Model Intercomparison Project. The analysis reveals a systematic improvement in the simulation fidelity of CM4X relative to its CM4.0 predecessor, as well as an improvement when refining the ocean/sea ice horizontal grid spacing from the 0.25°$0.25{}^{\\circ}$of CM4X‐p25 to the 0.125°$0.125{}^{\\circ}$of CM4X‐p125. Even so, there remain many outstanding biases, thus pointing to the need for further grid refinements, enhancements to numerical methods, and/or advances in parameterizations, each of which target long‐standing model biases and limitations. Plain Language Summary We examine simulations from a new climate model hierarchy, referred to as Climate Model version 4X (CM4X). The finer grid component of the hierarchy, CM4X‐p125, out shines its coarser sibling, CM4X‐p25, for certain processes of interest for climate studies, though in others the results are not dramatically distinct. Each case study reveals the advances made by moving from the predecessor CM4.0 climate model to finer grid spacing in either the atmosphere or ocean. Even so, there remain many unresolved problems that help to guide further research and development goals and strategies. Key Points We present case studies of selected features of the Geophysical Fluid Dynamics Laboratory‐Climate Model version 4X from version 6 from the Coupled Model Intercomparison Project piControl, historical, and SSP5‐8.5 simulations Case studies include sea level, eastern boundary upwelling, sea ice, Southern Ocean circulation, and North Atlantic circulation Refining ocean grid spacing from 0.25°$0.25{}^{\\circ}$to 0.125°$0.125{}^{\\circ}$yields systematic improvements across a number of climate relevant features