Shingo Watanabe

A one-year hindcast simulation for 2022 was performed using a high-resolution gravity-wave-permitting general circulation model to quantify the seasonal variation and global distributions of momentum fluxes associated with gravity waves (GWs) in the stratosphere and mesosphere. The global-mean absolute momentum flux (GM-AMF) associated with GWs exhibits clear semiannual variations, with maxima in the solstitial seasons and minima in the equinoctial seasons. GM-AMF is larger in June–August than in December–February in the solstitial seasons throughout the stratosphere and mesosphere. Meanwhile, in the equinoctial seasons, it is larger in September–November than in March–May below z = ∼65 km. The larger GW activity in September–November than in March–May in both hemispheres is consistent with the stronger stratospheric residual circulation in September–November as indicated by a previous study. The zonal and meridional momentum fluxes in meridional cross-sections suggest the presence of GW sources in the summer high-latitudes, in addition to the well-known source of subtropical monsoon convection. The characteristics of the meridional momentum fluxes indicate that, in the stratosphere and mesosphere, upward-propagating GWs generally have poleward intrinsic phase velocities, except in the winter hemisphere above z = ∼75 km where GWs with equatorward intrinsic phase velocities are dominant. The analysis of energy and momentum fluxes as functions of ground-based zonal phase velocity and height suggests that the equatorward-propagating GWs are generated in situ near the winter westerly jet core.

Stratospheric aerosol injection (SAI) modeling experiments are often designed to keep global mean surface air temperature (GMSAT) close to a reference target, such as early‐century SSP2‐4.5. However, meeting this target does not necessarily restore regional climates or the seasonal and spatial patterns of key variables. We evaluate multiple SAI strategies (ARISE‐SAI‐1.0/1.5, G6‐1.5K‐SAI, and G6‐1.5K‐HiLLA) across four Earth system models (CESM2‐WACCM6, UKESM1, E3SMv3, and MIROC) using a dimensionless, variability‐scaled distance‐to‐target metric applied to the monthly climatological seasonal cycle. We decompose this distance into mean offset, seasonal‐cycle amplitude, and phase/pattern contributions, and use matched baseline‐against‐baseline null distributions to estimate the finite‐sampling floor. SAI substantially reduces temperature distance‐to‐target relative to late‐century SSP2‐4.5, but the majority of SAI model–scenario cases exceed the 97.5th percentile of their matched finite‐sampling null distributions, indicating that residual temperature departures remain detectable even when large‐scale temperature targets are met. These residuals are more strongly associated with differences in seasonal timing than with mean offsets. In contrast, most precipitation distances do not exceed their matched null thresholds, so some apparent precipitation residuals cannot be distinguished from finite‐sampling variability. This framework enables consistent comparisons across intervention strategies, variables, and models without regridding, and identifies where meeting GMSAT targets does or does not restore regional and seasonal climate.

Because of the large dynamic range of scales between 3D turbulence and global circulation, the effects of small-scale turbulence, and indeed turbulence at many scales, often need to be parameterized in some way for input into large global-scale computer models. Ideally, it would be good to have a computer program large enough and powerful enough to solve all motions at all scales simultaneously, but this objective is still far from being possible. Yet if implemented poorly, parameterization can lead to errors that can propagate through the model. While turbulence is often considered a “wastebasket” for larger-scale motions, here we look in the other direction and examine how these smaller-scale motions work back to affect the larger-scale flows. The nature of background drag and diffusive forces is reviewed in the context of their impact on larger-scale motions, and the ways that these forces are implemented in models are discussed. The lack of use of measured (as distinct from hypothetical) small-scale turbulence data is noted. It is also noted that vertical diffusion is conceptually more important for atmospheric coupling than horizontal diffusion, and so-called two-dimensional (2D) “turbulence,” sometimes discussed in regard to atmospheric mixing, is less capable of vertical mixing because associated organized vertical motions are generally weak. Very strong evidence from the Global Atmospheric Sampling Program (GASP) for a dominant gravity-wave spectral region at horizontal scales of 200–1000 km, as low in altitude as the tropopause, is presented. Errors in the interpretation of earlier well-cited analyses of these data (often incorrectly cited as evidence for 2D turbulence) are presented. These errors have a profound impact on previous beliefs about the relative roles of gravity waves and nominally 2D turbulence. Non-Kolmogorov diffusive processes that contribute to drag, diffusion and mixing but have rarely been practically employed are considered, including the impact of intermittency, wave saturation, “whitecaps” and Stokes diffusion. When these processes are included, typical realistic diffusion coefficients seem to be 2–3 × higher than those predicted by the COSPAR International Reference Atmosphere. Finally, a comparison between diffusivities using the Whole Atmosphere Community Climate Model (WACCM6) at the National Center for Atmospheric Research in the USA and the Japanese Atmospheric GCM for Upper Atmosphere Research (JAGUAR), which use very different strategies, is undertaken.

Because of the large dynamic range of scales between 3-D turbulence and global circulation, the effects of small scale turbulence, and indeed turbulence at many scales, often need to be parameterized in some way for input into large global-scale computer models. Ideally, it would be good to have a computer program large enough, and powerful enough, to solve all motions at all scales simultaneously, but this objective is still far from possible. Yet if implemented poorly, parameterization can lead to errors which can propagate through the model. While turbulence is often considered as a “wastebasket” for larger scale motions, here we look in the other direction, and examine how these smaller scale motions work back to affect the larger-scale flows. The nature of background drag and diffusive forces is reviewed in the context of impact on larger scale motions, and the ways that these forces are implemented in models is discussed. The lack of use of measured (as distinct from hypothetical) small-scale turbulence data is noted. It is also noted that vertical diffusion is conceptually more important for atmospheric coupling than horizontal diffusion, and so-called “two-dimensional (2-D) turbulence”, sometimes discussed in regard to atmospheric mixing, is less capable of vertical mixing because associated organized vertical motions are generally weak. Very strong evidence from the Global Atmospheric Sampling Program (GASP) for a dominant gravity-wave spectral region at horizontal scales of 200-1000 km, as low in altitude as the tropopause, is presented. Errors in interpretation of earlier well-cited analyses of these data (often incorrectly cited as evidence for 2-D turbulence) are presented, which have profound impact on previous beliefs about the relative roles of gravity waves and nominally 2-D turbulence. Non- Kolmogorov diffusive processes which contribute to drag, diffusion and mixing, but that have rarely been practically employed, are considered, including the impact of intermittency, wave saturation, “whitecaps” and Stokes Diffusion. When these processes are included, typical realistic diffusion coefficients seem to be 2-3 × higher than those predicted by the Cospar International Reference Atmosphere. Finally a comparison between diffusivities using the Whole Atmosphere Community Climate Model (WACCM6) at the National Center for Atmospheric Research in the USA, and the Japanese Atmospheric GCM for Upper Atmosphere Research (JAGUAR), using very different strategies, is undertaken.

The springtime variability of the stratospheric polar vortex over Antarctica is an important source of predictability for the Southern Annular Mode (SAM) and associated Southern Hemisphere (SH) regional climate anomalies in austral spring–summer seasons. Variations in the Antarctic spring vortex often result from anomalous meridional shifts of the SH winter stratospheric jet maximum near the stratopause and associated wave–mean flow feedback. In this study, we evaluate 1) the ability of the models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) under historical forcings to simulate the observed dynamical chain of processes linking wintertime upper-stratospheric vortex anomalies to springtime surface climate anomalies; and 2) the influence of this ability on future projections of the SH stratospheric vortex and SAM under the highest greenhouse gas emission scenario [shared socioeconomic pathway (SSP) 5-8.5]. Our results show that many CMIP6 models are deficient in reproducing the observed dynamical evolution of SH vortex anomalies, mainly due to a systematic poleward bias in the mean position of the SH winter stratospheric jet maximum. These biases appear to significantly influence projected changes in the stratospheric zonal circulation and the associated SAM by the end of the twenty-first century. Therefore, model deficiencies in simulating the correct position of the SH winter stratospheric jet near the stratopause and the dynamical evolution of its anomalous meridional shift to a spring polar vortex strength anomaly constitute a key source of uncertainty in projections of the SAM and associated SH climate changes in austral spring. Significance Statement: The Southern Annular Mode (SAM) is the leading mode of extratropical circulation variability in the Southern Hemisphere (SH) and significantly influences SH regional climate, ocean circulations, and Antarctic sea ice variations. Austral spring SAM variability is substantially driven by the SH springtime stratospheric polar vortex variability, which often follows anomalous meridional shifts of the preceding winter stratospheric jet and associated wave–mean flow interactions. We show that many climate models do not accurately simulate these stratospheric processes largely due to a systematic poleward bias in the mean position of the SH winter stratospheric jet maximum. These model deficiencies appear to be a key source of uncertainty in future projections of the SAM and associated SH climate changes in austral spring.

Arctic ozone is projected to recover over the 21st century in compliance with the Montreal Protocol. Chemistry‐climate models show a large spread in recovery rates and future changes in key dynamical features such as the polar vortex and the residual circulation. Here, we quantify the spread in Arctic ozone recovery explained by uncertainties in these dynamical changes, using simulations from the Chemistry‐Climate Model Initiative, phases 1 and 2022. About 60% of the spread in projected ozone recovery is attributed to differences in polar vortex trends and about one‐third to the intermodel spread in residual circulation trends. Ozone‐depleting substances and greenhouse gas‐driven global warming contribute similarly to the spread in ozone recovery, although uncertainties in dynamical trends primarily affect the warming component. While dynamical changes clearly separate the simulated ozone recovery among different models, the large variability in the Arctic stratosphere precludes establishing an observational constraint on future ozone recovery.

The 2022 Hunga volcanic eruption injected a significant amount of water vapor and a moderate amount of sulfur dioxide into the stratosphere, causing observable responses in the climate system. We have developed a model–observation comparison project to investigate the evolution of volcanic water and aerosols and their impacts on atmospheric dynamics, chemistry, and climate, using several state-of-the-art chemistry climate models. The project goals are (1) to evaluate the current chemistry–climate models to quantify their performance in comparison to observations and (2) to understand atmospheric responses in the Earth system after this exceptional event and investigate the potential impacts in the projected future. To achieve these goals, we designed specific experiments for direct comparisons to observations, for example from balloons and the Microwave Limb Sounder satellite instrument. Experiment 1 consists of two sets of free-running ensemble experiments from 2022 to 2031: one with fixed sea-surface temperatures and sea ice and one with coupled ocean. These experiments will help to understand the long-term evolution of water vapor and aerosols; quantify HTHH effects on stratospheric and mesospheric temperatures, dynamics, and transport; understand the impact of dynamic changes on ozone chemistry; quantify the net radiative forcings; and evaluate any surface climate impact. Experiment 2 is a nudged-run experiment from 2022 to 2023 using observed meteorology. To allow participation of more climate models with varying complexities of aerosol simulation, we include two sets of simulations in Experiment 2: Experiment 2a is designed for models with internally generated aerosol, while Experiment 2b is designed for models using prescribed aerosol surface area density. This experiment will help to analyze H₂O and aerosol evolution, quantify the net radiative forcings, understand the impacts on mid-latitude and polar O₃ chemistry, and allow close comparisons with observations.

Interhemispheric coupling (IHC) is the positive correlation between temperatures in the polar winter stratosphere and polar summer upper mesosphere and lower thermosphere. Over the past two decades, several mechanisms have been proposed to explain the IHC. However, a consensus on the mechanism has yet to be fully reached, particularly regarding the role of gravity waves (GWs). We conduct hindcast simulations for seven boreal winters using a GW-permitting general circulation model encompassing the whole neutral atmosphere. The model is initialized through spectral nudging to state-of-the-art reanalysis data of identical vertical coverage. Treating the 7-year averages of the model outputs as a climatology, the IHC is investigated as a sequential evolution of anomalies relative to it. The results showed that consequential interplay of GWs and quasi-two-day waves in the summer mesosphere is the key driver of the IHC, as is consistent with Yasui et al. (2021) except for the final step toward the summer pole facilitated by primary GWs in the Antarctic. These waves are filtered by an anomalously weak westward jet due to a temperature gradient caused by planetary wave forcing, considered to be quasi-two-day waves. The mechanism is mostly applicable to both types of IHC events: those associated with sudden stratospheric warming and those with vortex intensification. Meanwhile, comparisons across the seven boreal winters indicate vulnerabilities in specific processes underlying the mechanism. In the reanalysis, it is suggested that GW parameterizations underestimate the GW forcing anomalies, but analysis increments reduce this discrepancy.

Interhemispheric coupling (IHC) is the positive correlation between temperatures in the polar winter stratosphere and the polar summer upper mesosphere and the lower thermosphere. Over the past two decades, several mechanisms have been proposed to explain the IHC. However, a consensus on the mechanism is yet to be fully reached, particularly regarding the role of gravity waves (GWs). We conduct hindcast simulations for seven boreal winters using a GW‐permitting general circulation model encompassing the whole neutral atmosphere. The model is initialized through spectral nudging to state‐of‐the‐art reanalysis data of identical vertical coverage. Treating the 7‐year averages of the model outputs as a climatology, the IHC is investigated as a sequential evolution of anomalies relative to it. The results showed that consequential interplay of GWs and quasi‐two‐day waves in the summer mesosphere is the key driver of the IHC, as is consistent with Yasui et al. (2021, doi: 10.1175/jas‐d‐21‐0045.1) except for the final step toward the summer pole facilitated by primary GWs in the Antarctic. These waves are filtered by an anomalously weak westward jet due to a temperature gradient caused by planetary wave forcing, considered to be quasi‐two‐day waves. The mechanism is mostly applicable to both types of IHC events: those associated with sudden stratospheric warming and those with vortex intensification. Meanwhile, comparisons across the seven boreal winters indicate vulnerabilities in specific processes underlying the mechanism. In the reanalysis, it is suggested that GW parameterizations underestimate the GW forcing anomalies, but analysis increments reduce this discrepancy.