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Atmospheric predictability from subseasonal to seasonal time scales and climate variability are both influenced critically by gravity waves (GW). The quality of regional and global numerical models relies on thorough understanding of GW dynamics and its interplay with chemistry, precipitation, clouds, and climate across many scales. For the foreseeable future, GWs and many other relevant processes will remain partly unresolved, and models will continue to rely on parameterizations. Recent model intercomparisons and studies show that present-day GW parameterizations do not accurately represent GW processes. These shortcomings introduce uncertainties, among others, in predicting the effects of climate change on important modes of variability. However, the last decade has produced new data and advances in theoretical and numerical developments that promise to improve the situation. This review gives a survey of these developments, discusses the present status of GW parameterizations, and formulates recommendations on how to proceed from there.

 

The climate model hierarchy encompasses models of varying complexity along different axes, ranging from idealized models that elegantly describe isolated mechanisms to fully coupled Earth system models that aspire to provide useable climate projections. Based on the second Model Hierarchies Workshop, which took place in 2022, we present perspectives on how this field has evolved since the first Model Hierarchies Workshop in 2016. In this period, we have witnessed a dramatic increase in the use of (a) machine learning in climate modeling and (b) climate models to estimate risks and influence decision making under climate change. Here, we discuss the implications of these growing areas of research and how we expect them to become integrated into the model hierarchies framework.

 

Abstract. The effects of wave–wave interactions on sudden stratospheric warming formation are investigated using an idealized atmospheric general circulation model, in which tropospheric heating perturbations of zonal wave numbers 1 and 2 are used to produce planetary-scale wave activity. Zonal wave–wave interactions are removed at different vertical extents of the atmosphere in order to examine the sensitivity of stratospheric circulation to local changes in wave–wave interactions. We show that the effects of wave–wave interactions on sudden warming formation, including sudden warming frequencies, are strongly dependent on the wave number of the tropospheric forcing and the vertical levels where wave–wave interactions are removed. Significant changes in sudden warming frequencies are evident when wave–wave interactions are removed even when the lower-stratospheric wave forcing does not change, highlighting the fact that the upper stratosphere is not a passive recipient of wave forcing from below. We find that while wave–wave interactions are required in the troposphere and lower stratosphere to produce displacements when wave number 2 heating is used, both splits and displacements can be produced without wave–wave interactions in the troposphere and lower stratosphere when the model is forced by wave number 1 heating. We suggest that the relative strengths of wave number 1 and 2 vertical wave flux entering the stratosphere largely determine the split and displacement ratios when wave number 2 forcing is used but not wave number 1. 

We present single‐column gravity wave parameterizations (GWPs) that use machine learning to emulate non‐orographic gravity wave (GW) drag and demonstrate their ability to generalize out‐of‐sample. A set of artificial neural networks (ANNs) are trained to emulate the momentum forcing from a conventional GWP in an idealized climate model, given only one view of the annual cycle and one phase of the Quasi‐Biennial Oscillation (QBO). We investigate the sensitivity of offline and online performance to the choice of input variables and complexity of the ANN. When coupled with the model, moderately complex ANNs accurately generate full cycles of the QBO. When the model is forced with enhanced CO₂, its climate response with the ANN matches that generated with the physics‐based GWP. That ANNs can accurately emulate an existing scheme and generalize to new regimes given limited data suggests the potential for developing GWPs from observational estimates of GW momentum transport.

 

The tropospheric response to Sudden Stratospheric Warmings (SSWs) is associated with an equatorward shift in the midlatitude jet and associated storm tracks, while Strong Polar Vortex (SPV) events elicit a contrasting response. Recent analyses of the North Atlantic jet using probability density functions of a jet latitude index have identified three preferred jet latitudes, raising the question of whether the tropospheric response to SSWs and SPVs results from a change in relative frequencies of these preferred jet regimes rather than a systematic jet shift. We explore this question using atmospheric reanalysis data from 1979 to 2018 (26 SSWs and 33 SPVs), and a 202‐years integration of the Whole Atmosphere Community Climate Model (92 SSWs and 68 SPVs). Following SSWs, the northern jet regime becomes less common and the central and southern regimes become more common. These changes occur almost immediately following “split” vortex events, but are more delayed following “displacement” events. In contrast, the northern regime becomes more frequent and the southern regime less frequent following SPV events. Following SSWs, composites of 500‐hPa geopotential heights, surface air temperatures, and precipitation most closely resemble composites of the southern jet regime, and are generally opposite in sign to the composites of the northern jet regime. These comparisons are reversed following SPVs. Thus, one possible interpretation is that the two southernmost regimes appear to be favored following SSWs, while the southernmost regime becomes less common following SPVs.

 

Superpressure balloon data of unprecedented coverage from Loon LLC is used to investigate the seasonal and latitudinal variability of lower stratospheric gravity waves over the entire intrinsic frequency spectrum. We show that seasonal variability in both gravity wave amplitudes and spectral slopes exist for a wide range of intrinsic frequencies and provide estimates of spectral slopes in five latitudinal regions for all four seasons, in five different frequency windows. The spectral slopes can be used to infer gravity wave amplitudes of intrinsic frequencies as high as 70 cycles/day from gravity waves resolved in model and reanalysis data. We also show that a robust relationship between the phase of the quasi‐biennial oscillation and gravity wave amplitudes exists for intrinsic frequencies as high as the buoyancy frequency. These are the first estimates of seasonal and latitudinal variability of gravity wave spectral slopes and high‐frequency amplitudes and constitute a significant step toward obtaining observationally constrained gravity wave parameterizations in climate models.

 

Recent work suggests that storm track diagnostics such as eddy heat fluxes and eddy kinetic energies have very small signatures in the first annular mode of zonal mean zonal wind, suggesting a lack of co‐variability between the locations of the extratropical jet and storm tracks. The frequency‐dependence of this apparent decoupling is explored in ERA‐Interim reanalysis data. The annular modes show similar spatial characteristics in the different frequency ranges considered. Cancellation between the signatures of storm track diagnostics in the leading low‐pass and high‐pass filtered annular modes is evident, partly explaining their small signature in the total. It is shown that at timescales greater than 30 days, the first zonal wind mode describes latitudinal shifts of both the midlatitude jet and its associated storm tracks, and it appears that the persistence of zonal wind anomalies is sustained primarily by a baroclinic feedback.

 

The North Atlantic atmospheric eddy‐driven jet exhibits three “preferred positions,” latitudes where the maximum jet speed occurs more frequently than others. Using an atmospheric general circulation model, Whole Atmospheric Community Climate Model, we explore the extent to which different mountain ranges affect the northern preferred position. The latitude of this preferred position changes only when the latitude of Greenland is changed, and the preferred position disappears when Greenland orography is flattened. We propose that “Greenland tip jet events” create the appearance of a northern “preferred position” in the eddy‐driven jet; tip jets are localized zonal jets east of the southern tip of Greenland, created by flow interacting with Greenland orography. In reanalysis data the northern preferred position is strongly associated with tip jet days. A case study with the CAM4 model suggests that biases in the northern preferred position may stem from biases in the position or strength of the climatological eddy‐driven jet.

 

Global tropical cyclone (TC) frequency is investigated in a 50‐km‐resolution aquaplanet model forced by zonally symmetric sea surface temperature (SST). TC frequency per unit area is found to be proportional to the Coriolis parameter at the intertropical convergence zone (ITCZ), as defined by the latitude of maximum precipitation. As the latitude of maximum SST is shifted northward from the equator, the precipitation maximum moves northward and TC frequency increases. When the SST maximum is shifted northward past 25°N, the precipitation maximum remains between 15°N and 20°N, and TC frequency per unit area is approximately constant. When applied to observed precipitation and SST data, the same scaling captures a substantial fraction of observed TCs. Results suggest that future changes in TC activity will be modulated by changes in the large‐scale circulation, and in particular that the ITCZ location is an important determinant of the number of TCs.