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The current standard version of the Whole Atmosphere Community Climate Model (WACCM) simulates Southern Hemisphere winter and spring temperatures that are too cold compared with observations. This “cold-pole bias” leads to unrealistically low ozone column amounts in Antarctic spring. Here, the cold-pole problem is addressed by introducing additional mechanical forcing of the circulation via parameterized gravity waves. Insofar as observational guidance is ambiguous regarding the gravity waves that might be important in the Southern Hemisphere stratosphere, the impact of increasing the forcing by orographic gravity waves was investigated. This reduces the strength of the Antarctic polar vortex in WACCM, bringing it into closer agreement with observations, and accelerates the Brewer–Dobson circulation in the polar stratosphere, which warms the polar cap and improves substantially the simulation of Antarctic temperature. These improvements are achieved without degrading the performance of the model in the Northern Hemisphere stratosphere or in the mesosphere and lower thermosphere of either hemisphere. It is shown, finally, that other approaches that enhance gravity wave forcing can also reduce the cold-pole bias such that careful examination of observational evidence and model performance will be required to establish which gravity wave sources are dominant in the real atmosphere. This is especially important because a “downward control” analysis of these results suggests that the improvement of the cold-pole bias itself is not very sensitive to the details of how gravity wave drag is altered.

The primary goal of the Second Wind Forecast Improvement Project (WFIP2) is to advance the state-of-the-art of wind energy forecasting in complex terrain. To achieve this goal, a comprehensive 18-month field measurement campaign was conducted in the region of the Columbia River basin. The observations were used to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. WFIP2 model development has focused on the boundary layer and surface-layer schemes, cloud–radiation interaction, the representation of drag associated with subgrid-scale topography, and the representation of wind farms in the HRRR. Additionally, refinements to numerical methods have helped to improve some of the common forecast error modes, especially the high wind speed biases associated with early erosion of mountain–valley cold pools. This study describes the model development and testing undertaken during WFIP2 and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotorlayer wind speed forecasts could be reduced by 5%–20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements made in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.

The Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) version of the Goddard Earth Observing System-5 (GEOS-5) atmospheric general circulation model (AGCM) is currently in use in the NASA Global Modeling and Assimilation Office (GMAO) at a wide range of resolutions for a variety of applications. Details of the changes in parameterizations subsequent to the version in the original MERRA reanalysis are presented here. Results of a series of atmosphere-only sensitivity studies are shown to demonstrate changes in simulated climate associated with specific changes in physical parameterizations, and the impact of the newly implemented resolution-aware behavior on simulations at different resolutions is demonstrated. The GEOS-5 AGCM presented here is the model used as part of the GMAO MERRA2 reanalysis, global mesoscale simulations at 10 km resolution through 1.5 km resolution, the real-time numerical weather prediction system, and for atmosphere-only, coupled ocean-atmosphere and coupled atmosphere-chemistry simulations. The seasonal mean climate of the MERRA2 version of the GEOS-5 AGCM represents a substantial improvement over the simulated climate of the MERRA version at all resolutions and for all applications. Fundamental improvements in simulated climate are associated with the increased re-evaporation of frozen precipitation and cloud condensate, resulting in a wetter atmosphere. Improvements in simulated climate are also shown to be attributable to changes in the background gravity wave drag, and to upgrades in the relationship between the ocean surface stress and the ocean roughness. The series of resolution-aware parameters related to the moist physics was shown to result in improvements at higher resolutions and result in AGCM simulations that exhibit seamless behavior across different resolutions and applications.

In Part 2 of this two‐part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model. Key Points Part 2 of the AM4.0/LM4.0 paper provides documentation of key changes in individual components from previous GFDL models Some sensitivities to choices of model formulation and parameter values are presented with emphasis on convection and tuning of clouds We describe the extent to which the effect on aerosol forcing and Cess sensitivity has been taken into account during model development

Long transient simulations of the last deglaciation are increasingly being performed to identify the drivers of multiple rapid Earth system changes that occurred in this period. Such simulations frequently prescribe temporal variations in ice sheet properties, which can play an important role in controlling atmospheric and surface climate. To preserve a model’s standard performance in simulating climate, it is common to apply time dependent orographic variations, including parameterised sub-grid scale orographic variances, as anomalies from the pre-industrial state. This study investigates the causes of two abrupt climate change events in the Northern Hemisphere extratropics occurring between 16 and 14 thousand years ago in transient simulations of the last deglaciation from the Hadley Centre coupled general circulation model (HadCM3). One event is characterized by regional Northern Hemisphere changes comprising a centennial scale cooling of ~ 10 °C across Fennoscandia followed by rapid warming in less than 50 years as well as synchronous shifts in the Northern Annular Mode. The second event has comparable but temporally reversed characteristics. Sensitivity experiments reveal the climate anomalies are exclusively caused by artificially large values of orographic gravity wave drag, resulting from the combined use of the orographic anomaly method along with a unique inclusion of transient orography that linearly interpolates between timesteps in the ice sheet reconstruction. Palaeoclimate modelling groups should therefore carefully check the effects of their sub-grid scale orographic terms in transient palaeoclimate simulations with prescribed topographic evolution.

Orographic gravity waves (OGWs) are an important mechanism for coupling of the free atmosphere with the surface, mediating the momentum and energy transport and influencing the dynamics and circulation especially in the middle-atmosphere. Current global climate models are not able to resolve a large part of the OGW spectrum and hence, OGW effects have to be parameterized in the models. Typically, the only parameterized effect is the OGW induced drag. Despite producing the same quantity as an output and relying on similar assumptions (e.g. instantaneous vertical propagation), the individual OGW parameterization schemes differ in many aspects such as handling of the orography, the inclusion of non-linear effects near the surface and the tuning of the emergent free parameters. In this study, we have reviewed 7 different parameterizations, which are used in 9 different CMIP6 models. We report pronounced differences in the vertical distribution and magnitude of the parameterized OGW drag between the models and study to what extent the inter-model differences can be traced back to the difference in the type and tuning of the schemes. Finally, we demonstrate how the OGW drag differences project to the intermodel differences in the stratospheric dynamics. The study can pave the way for a more systematic research of the OGW parameterizations in the future, with an ultimate goal of lowering the amount of uncertainty of the future climate projections connected with the parameterized effects of unresolved orography.

We assess the value of machine learning as an accelerator for the parameterization schemes of operational weather forecasting systems, specifically the parameterization of nonorographic gravity wave drag. Emulators of this scheme can be trained to produce stable and accurate results up to seasonal forecasting timescales. Generally, networks that are more complex produce emulators that are more accurate. By training on an increased complexity version of the existing parameterization scheme, we build emulators that produce more accurate forecasts. For medium range forecasting, we have found evidence that our emulators are more accurate than the version of the parametrization scheme that is used for operational predictions. Using the current operational CPU hardware, our emulators have a similar computational cost to the existing scheme, but are heavily limited by data movement. On GPU hardware, our emulators perform 10 times faster than the existing scheme on a CPU. Plain Language Summary The ability of computers to construct models from data (machine learning) has had significant impacts on many areas of science. Here, we use this ability to construct a model of an element of a numerical weather forecasting system. This element captures one physical process in the model, a part of the model that describes the propagation of large‐scale waves through the atmosphere, but the long‐term aim would be to make many models each capturing a process. The goal is that the computer‐generated model will perform the task more efficiently than the existing model. Testing is then carried out to ensure that our computer model performs as accurately as the existing model. This is a challenging step, as learning is carried out over short time periods (seconds), but forecasts need to be accurate over years. Our computer‐generated models produce accurate forecasts on all tested timescales. On current computers, they are not faster, but will be if weather forecasting centers invest in computers with graphics processing units. Key Points Nonorographic gravity wave drag parametrization can be accurately emulated with a neural network These emulators produce accurate and stable forecasts over long timescales Neural networks can reduce the cost of an increased complexity scheme

Gravity waves play a significant role in driving the semiannual oscillation (SAO) of the zonal wind in the tropics. However, detailed knowledge of this forcing is missing, and direct estimates from global observations of gravity waves are sparse. For the period 2002–2018, we investigate the SAO in four different reanalyses: ERA-Interim, JRA-55, ERA-5, and MERRA-2. Comparison with the SPARC zonal wind climatology and quasi-geostrophic winds derived from Microwave Limb Sounder (MLS) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) satellite observations show that the reanalyses reproduce some basic features of the SAO. However, there are also large differences, depending on the model setup. Particularly, MERRA-2 seems to benefit from dedicated tuning of the gravity wave drag parameterization and assimilation of MLS observations. To study the interaction of gravity waves with the background wind, absolute values of gravity wave momentum fluxes and a proxy for absolute gravity wave drag derived from SABER satellite observations are compared with different wind data sets: the SPARC wind climatology; data sets combining ERA-Interim at low altitudes and MLS or SABER quasi-geostrophic winds at high altitudes; and data sets that combine ERA-Interim, SABER quasi-geostrophic winds, and direct wind observations by the TIMED Doppler Interferometer (TIDI). In the lower and middle mesosphere the SABER absolute gravity wave drag proxy correlates well with positive vertical gradients of the background wind, indicating that gravity waves contribute mainly to the driving of the SAO eastward wind phases and their downward propagation with time. At altitudes 75–85 km, the SABER absolute gravity wave drag proxy correlates better with absolute values of the background wind, suggesting a more direct forcing of the SAO winds by gravity wave amplitude saturation. Above about 80 km SABER gravity wave drag is mainly governed by tides rather than by the SAO. The reanalyses reproduce some basic features of the SAO gravity wave driving: all reanalyses show stronger gravity wave driving of the SAO eastward phase in the stratopause region. For the higher-top models ERA-5 and MERRA-2, this is also the case in the lower mesosphere. However, all reanalyses are limited by model-inherent damping in the upper model levels, leading to unrealistic features near the model top. Our analysis of the SABER and reanalysis gravity wave drag suggests that the magnitude of SAO gravity wave forcing is often too weak in the free-running general circulation models; therefore, a more realistic representation is needed.

The Internal wave Dissipation, Energy and Mixing (IDEMIX) model presents a novel way of parameterizing internal gravity waves in the atmosphere. Using a continuous full wave spectrum in the energy balance equation and integrating over all vertical wavenumbers and frequencies results in prognostic equations for the energy density of gravity waves in multiple azimuthal compartments. It includes their non‐dissipative interaction with the mean flow, allowing for an evolving and local description of momentum flux and gravity wave drag (GWD). A saturation mechanism maintains the wavefield within convective stability limits, and an energetically consistent closure for critical‐layer effects controls how much wave flux propagates from the troposphere into the middle atmosphere. IDEMIX can simulate zonal GWD around the mesopause, similar to a traditional gravity wave parameterization and to a state‐of‐the‐art wave ray tracing model in an atmospheric circulation model. In addition, IDEMIX shows a reversal of the GWD around the mesopause region due to interaction with the mean flow there. When compared to empirical model data, IDEMIX captures well the summer hemisphere flow reversal, the cold summer mesospheric pole and the alternate positive and negative structures in the meridional mean flow. Plain Language Summary IDEMIX is a new gravity wave parameterization for the atmosphere. Compared to current schemes, it depends on time and derives its parameters using a full spectrum of wavelengths and frequencies. The gravity wavefield can gain or lose momentum through its interaction with the background mean flow, through which it accelerates or decelerates the mean flow, and not only when the waves break. A critical layer closure is energetically consistently included. IDEMIX can simulate zonal GWD around the mesopause, similar to a traditional gravity wave parameterization and to a state‐of‐the‐art wave ray tracing model in an atmospheric circulation model. In addition, IDEMIX shows a reversal of the GWD around the mesopause region due to changes in the momentum flux there. When compared to empirical model data, IDEMIX captures well the summer hemisphere flow reversal, the cold summer mesospheric pole and the alternate positive and negative structures in the meridional mean flow. Key Points Maxima of zonal and meridional momentum flux in mesosphere region Zonal gravity wave drag reversal at mesopause due to interaction with the mean flow Layered alternate meridional wind structures in the mesopause region due to meridional fluxes higher in the atmosphere

Nearly all general circulation models significantly fail to reproduce the observed behaviour of the southern wintertime polar vortex. It has been suggested that these biases result from an underestimation of gravity wave drag on the atmosphere at latitudes near 60° S, especially around the \"hot spot\" of intense gravity wave fluxes above the mountainous Southern Andes and Antarctic peninsula. Here, we use Global Positioning System radio occultation (GPS-RO) data from the COSMIC satellite constellation to determine the properties of gravity waves in the hot spot and beyond. We show considerable southward propagation to latitudes near 60° S of waves apparently generated over the southern Andes. We propose that this propagation may account for much of the wave drag missing from the models. Furthermore, there is a long leeward region of increased gravity wave energy that sweeps eastwards from the mountains over the Southern Ocean. Despite its striking nature, the source of this region has historically proved difficult to determine. Our observations suggest that this region includes both waves generated locally and orographic waves advected downwind from the hot spot. We describe and use a new wavelet-based analysis technique for the quantitative identification of individual waves from COSMIC temperature profiles. This analysis reveals different geographical regimes of wave amplitude and short-timescale variability in the wave field over the Southern Ocean. Finally, we use the increased numbers of closely spaced pairs of profiles from the deployment phase of the COSMIC constellation in 2006 to make estimates of gravity wave horizontal wavelengths. We show that, given sufficient observations, GPS-RO can produce physically reasonable estimates of stratospheric gravity wave momentum flux in the hot spot that are consistent with measurements made by other techniques. We discuss our results in the context of previous satellite and modelling studies and explain how they advance our understanding of the nature and origins of waves in the southern stratosphere.