Ming Zhao

We implemented in GFDL's global atmospheric model a parameterization for convective gravity waves, which explicitly describes the wave source based on the latent heating rates from the parameterized deep convection. The characteristics of the simulated Quasi‐Biennial Oscillation (QBO) in the equatorial stratosphere depend on the tunable parameters in the convective gravity wave scheme. In particular, a larger efficiency factor or a smaller convective area leads to a shorter QBO period. A less‐than‐one scaling factor for the convective heating depth, though unphysical, is necessary for the model to simulate a realistic QBO over the lower stratosphere. Furthermore, we relax the assumption of constant convective area and replace it with the prognostic convective area diagnosed from the convection scheme. While the model with a constant convective area simulates a similar QBO to that with variable convective area at the present‐day condition, it simulates a stronger reduction of the QBO period and the QBO amplitude in response to surface warming. Our results highlight the sensitivity of the simulated QBO in general circulation models to details of the parameterization for convective gravity waves.

In this study, we extend the Cloud Layers Unified by Binormals (CLUBB) turbulence scheme within the GFDL atmospheric model (AM4) by implementing direct momentum‐flux prognosis and a multiscale turbulent lengthscale, to improve the simulation of nocturnal precipitation and associated Low‐Level Jets (LLJs) over the Great Plains (GP). Toward this aim, we set up four AM4‐CLUBB configurations: diagnosed momentum flux, prognosed momentum flux, diagnosed momentum flux with a multiscale turbulent lengthscale, and prognosed momentum flux with a multiscale turbulent lengthscale. Simulations are evaluated against the AM4 control, the Integrated Multi‐satellitE Retrievals for GPM (IMERG), and the Doppler wind radar profiles from the Atmospheric Radiation Measurement program. Results show that all AM4‐CLUBB configurations improve the precipitation timing from the unrealistic midday peak seen in the AM4 control simulation toward the satellite‐observed nocturnal maximum. The configuration that prognoses momentum flux and uses a multi‐scale turbulent lengthscale, best matches the timing and intensity of GP precipitation rate. This configuration is also that which more accurately simulates the ARM‐observed nocturnal LLJ wind profiles, while increasing the frequency of counter‐gradient momentum fluxes near the LLJ core compared to prognosing momentum fluxes with the original AM4‐CLUBB turbulent lengthscale. Momentum budget analysis attributes this increase to a nearly fivefold enhancement in the buoyancy production term when using the multiscale formulation, and leads to stronger nocturnal convective activity, as diagnosed from the greater vertical velocity skewness and plume asymmetry.

Future precipitation projections rely heavily on climate models, underscoring the need to evaluate their ability to simulate historical precipitation changes. Using multiple atmospheric models and ensemble simulations, we estimate the forced signals driven by sea surface warming and the direct effects of greenhouse gases and aerosols, as well as the atmospheric internal variability in precipitation trends since 1980. We find that forced precipitation trends are generally consistent across models, while atmospheric internal variability significantly influences regional patterns. Additionally, a few model members can reasonably well reproduce the observed pattern of precipitation trends. We highlight some regional wetting and drying are likely driven by forcings rather than the atmospheric internal variability. Zonal‐mean trends over land reveal a “wet gets wetter, dry gets drier” paradigm in the Northern Hemisphere, while the Southern Hemisphere shows drying near 45°S associated with jet stream shifts. These results help improve our understanding of historical precipitation changes.

National Centers for Environmental Prediction turbulent kinetic energy (TKE)‐based eddy‐diffusivity mass‐flux (EDMF) scheme is implemented in Geophysical Fluid Dynamics Laboratory atmospheric model (AM4.0) for improving the physical consistency of subgrid‐scale planetary boundary layer (PBL) turbulence parameterization. The mass flux (MF) component represents vertically coherent convective structures responsible for countergradient transport in the upper PBL, which the original AM4.0's ED‐only scheme cannot represent. Consequently, AM4.0 with EDMF produces a deeper and more well‐mixed PBL, leading to better zonal‐mean vertical temperature and humidity profiles and reduced near‐surface wet bias over subtropical and midlatitude oceans. Other model performance changes are generally minor, such as similar biases in global top of atmosphere (TOA) net radiation and shortwave cloud radiative effects, small and compensating changes in low cloud amount and cloud liquid water path, improved low‐level equatorial easterlies but deteriorated extratropical westerlies, slightly increased global‐mean precipitation, and weaker TOA radiative response to uniform sea surface warming. Three adaptations of EDMF are important for its performance at AM4.0's relatively coarse vertical resolution: limiting the overshoot of MF updraft above PBL‐top, reducing the ED‐induced mixing across PBL‐top, and disabling the MF transport of TKE. Low clouds and their radiative effects are also sensitive to four EDMF parameters that control the ED in the lower and upper PBL respectively, the TKE dissipation rate, and the lateral entrainment of MF updraft and downdraft. An automatic linear tuning of these parameters slightly improves the radiative bias, especially for the coastal stratocumulus. More substantial improvements likely require formulation updates of the EDMF scheme and its coupling with other AM4.0 model components.

The “warming hole” over the United States refers to a long‐term summer cooling anomaly in near‐surface temperatures across the central and northern U.S. since the midtwentieth century. It is most pronounced in maximum temperature ( T _max ), contrasting with widespread warming elsewhere. Using the European Centre for Medium‐Range Weather Forecasts ERA5 reanalysis and a 30‐member large ensemble of the Seamless System for Prediction and Earth System Research (SPEAR) model, we show that the warming hole has shrunk and weakened in recent decades, with contraction accelerating during 2021–2024. The changes are seasonally asymmetric: June exhibits the strongest weakening, whereas May retains negative anomalies. Composite analyses confirm a well‐known mechanism in which a strengthened southerly low‐level jet enhances precipitation and suppresses T _max . We also identify an additional process: enhanced northerly winds from Canada that advect cooler air and increase convergence and rainfall, reinforcing the cooling. In many years, opposite circulation and precipitation anomalies reduced these cooling effects; recently, such anomalies have strengthened in step with the warming trend, contributing to rapid shrinkage. SPEAR reasonably captures the detrended variability and spatial pattern of anomalies but overestimates the warming trend relative to ERA5. Combining SPEAR's detrended variability with the ERA5 trend, we project that the warming hole would vanish around 2050 under a strong external forcing. This result contrasts with recent studies emphasizing seasonal persistence and southerly winds alone, underscoring the importance of both externally forced and internal variability associated with hydrologic cycle changes in shaping the future trajectory of the U.S. warming hole.

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 of CM4X‐p25 to the 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.

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 (referred to as CM4X‐p25) and the other that uses a 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 within years in a pre‐industrial simulation, and retains that thermally equilibrated state over the subsequent centuries. This 1850 thermal equilibrium is characterized by roughly 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 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.

Future precipitation projections rely heavily on climate models, underscoring the need to evaluate their ability to simulate historical precipitation changes. Using multiple atmospheric models and ensemble simulations, we estimate the forced signals driven by sea surface warming and the direct effects of greenhouse gases and aerosols, as well as the atmospheric internal variability in precipitation trends since 1980. We find that forced precipitation trends are generally consistent across models, while atmospheric internal variability significantly influences regional patterns. Additionally, some model members can reasonably well reproduce the observed pattern of precipitation trends. Our findings highlight some regional wetting and drying are likely driven by forcings rather than the atmospheric internal variability. Zonal-mean trends over land reveal a ”wet gets wetter, dry gets drier” paradigm in Northern Hemisphere, while Southern Hemisphere shows drying near 45°S associated with jet stream shifts. These results help improve our understanding of historical precipitation changes.

Changes in cloud scattering properties and emissivity that arise from atmospheric warming cause substantial radiative feedbacks in model projections of anthropogenic climate change, and the relative importance of the underlying mechanisms is poorly understood. One leading hypothesis is that ice-to-liquid conversions cause clouds to optically thicken, producing a major negative feedback. We test this hypothesis by developing a method to decompose cloud radiative feedbacks by cloud-top phase. The method is applied to an ensemble of six state-of-the-art global climate models run with prescribed sea surface temperature. In these simulations, the global mean of the net cloud scattering and emissivity feedback from cloud-phase conversions ranges from −0.17 to −0.01 W m⁻² K⁻¹, while the overall net cloud feedback ranges from 0.02 to 0.91 W m⁻² K⁻¹. The multimodel mean of the cloud scattering and emissivity feedback from cloud-phase conversions is approximately 19% of the magnitude of the multimodel mean of the overall cloud feedback (−0.10 vs 0.52 W m⁻² K⁻¹). These results indicate that cloud-phase conversions cause a robust negative feedback by changing cloud scattering and emissivity, but this mechanism makes a modest contribution to the overall cloud feedback at the global scale. Significance Statement: Climate warming changes Earth’s cloud properties, which then change the temperature further. One cloud-climate feedback mechanism involves the conversion of cloud ice particles to liquid droplets with warming. This makes clouds more opaque, causing them to reflect more solar radiation back to space. It is widely accepted that this mechanism dampens climate warming, but its importance relative to other feedback mechanisms has been unclear. This study develops a method to estimate the cloud opacity feedback from ice-to-liquid conversions in climate-model simulations. On average, cloud-opacity changes from phase conversions explain approximately 19% of the overall cloud–climate feedback in an ensemble of six climate models. This finding clarifies the importance of cloud-phase conversions in projections of anthropogenic climate change.