Gravity Wave Drag Parameterization Research Articles

A Parameterization Scheme Accounting for Nonhydrostatic Effects on the Momentum Flux of Vertically Propagating Orographic Gravity Waves: Formulas and Preliminary Tests in the Model for Prediction Across Scales (MPAS)

Abstract The momentum transport by orographic gravity waves (OGWs) plays an important role in driving the large-scale circulation throughout the atmosphere and is subject to parameterization in numerical models. Current parameterization schemes, which were originally developed for coarse-resolution models, commonly assume that unresolved OGWs are hydrostatic. With the increase in the horizontal resolution of state-of-the-art numerical models, unresolved OGWs are of smaller horizontal scale and more influenced by nonhydrostatic effects (NHE), thus challenging use of the hydrostatic assumption. Based on the analytical formulas for nonhydrostatic OGWs derived in our recent study, the orographic gravity wave drag (OGWD) parameterization scheme in the Model for Prediction Across Scales is revised by accounting for NHE. Global simulations with 30-km horizontal resolution are conducted to investigate NHE on the momentum transport of OGWs and their impacts on the large-scale circulation in boreal winter. NHE are evident in regions of complex terrain such as the Tibetan Plateau, Rocky Mountains, southern Andes, and eastern Antarctica. The parameterized surface wave momentum flux can be either reduced or enhanced depending on the relative importance of NHE and model physics–dynamics interactions. The NHE corrections to the OGWD scheme significantly reduce the easterly biases in the polar stratosphere of the Northern Hemisphere, due to both weakened OGWD in the upper troposphere and lower stratosphere and suppressed upward propagation of resolved waves into the stratosphere. However, the revised OGWD scheme only has a weak influence on the large-scale circulation in the Southern Hemisphere during boreal winter.

A Novel Gravity Wave Transport Parametrization for Global Chemistry Climate Models: Description and Validation

AbstractThe gravity wave drag parametrization of the Whole Atmosphere Community Climate Model (WACCM) has been modified to include the wave‐driven atmospheric vertical mixing caused by propagating, non‐breaking, gravity waves. The strength of this atmospheric mixing is represented in the model via the “effective wave diffusivity” coefficient (Kwave). Using Kwave, a new total dynamical diffusivity (KDyn) is defined. KDyn represents the vertical mixing of the atmosphere by both breaking (dissipating) and vertically propagating (non‐dissipating) gravity waves. Here we show that, when the new diffusivity is used, the downward fluxes of Fe and Na between 80 and 100 km largely increase. Larger meteoric ablation injection rates of these metals (within a factor 2 of measurements) can now be used in WACCM, which produce Na and Fe layers in good agreement with lidar observations. Mesospheric CO2 is also significantly impacted, with the largest CO2 concentration increase occurring between 80 and 90 km, where model‐observations agreement improves. However, in regions where the model overestimates CO2 concentration, the new parametrization exacerbates the model bias. The mesospheric cooling simulated by the new parametrization, while needed, is currently too strong almost everywhere. The summer mesopause in both hemispheres becomes too cold by about 30 K compared to observations, but it shifts upward, partially correcting the WACCM low summer mesopause. Our results highlight the far‐reaching implications and the necessity of representing vertically propagating non‐breaking gravity waves in climate models. This novel method of modeling gravity waves contributes to growing evidence that it is time to move away from dissipative‐only gravity wave parametrizations.

Contributions of Parameterized Gravity Waves and Resolved Equatorial Waves to the QBO Period in a Future Climate of CESM2

AbstractContributions of the resolved waves and parameterized gravity waves to changes in the quasi‐biennial oscillation (QBO) in a future simulation (2015–2100) under the SSP370 scenario are investigated using the Community Earth System Model 2 (CESM2) with enhanced vertical resolution and are compared with those from four CESM2 historical simulations (1979–2014). The maximum QBO amplitude of the future simulation is 26.0 m s−1, which is slightly less than that of the historical simulations (27.4–29.3 m s−1). However, the QBO period in the future simulation is much shorter: 21.6 months in the early‐future (2015–2050) and 12 months in the late‐future (2065–2100) period, than in the historical simulations (23.5–30.9 months). The shortened QBO period in the future is primarily due to increases in both resolved wave forcing and parameterized gravity wave drag (GWD) in the stratosphere, with a more significant contribution by the GWD. As convective activity becomes stronger in the future simulation, the momentum flux of parameterized convective gravity waves at the cloud top increases, resulting in stronger GWD in the stratosphere. The increases in the magnitude of westward GWD dominate those of eastward GWD in the stratosphere. This is due to a significant increase in westward momentum flux in the troposphere, especially during the descending easterly QBO, and enhanced westerlies in the lowermost stratosphere, which introduces a westward anomaly. For the resolved waves, Kelvin wave forcing is a key contributor to increased eastward forcing in the future simulation, with relatively minor contributions by other equatorial planetary waves.

Recreating Observed Convection‐Generated Gravity Waves From Weather Radar Observations via a Neural Network and a Dynamical Atmospheric Model

AbstractConvection‐generated gravity waves (CGWs) transport momentum and energy, and this momentum is a dominant driver of global features of Earth's atmosphere's general circulation (e.g., the quasi‐biennial oscillation, the pole‐to‐pole mesospheric circulation). As CGWs are not generally resolved by global weather and climate models, their effects on the circulation need to be parameterized. However, quality observations of GWs are spatiotemporally sparse, limiting understanding and preventing constraints on parameterizations. Convection‐permitting or ‐resolving simulations do generate CGWs, but validation is not possible as these simulations cannot reproduce the CGW‐forcing convection at correct times, locations, and intensities. Here, realistic convective diabatic heating, learned from full‐physics convection‐permitting Weather Research and Forecasting simulations, is predicted from weather radar observations using neural networks and a previously developed look‐up table. These heating rates are then used to force an idealized GW‐resolving dynamical model. Simulated CGWs forced in this way closely resembled those observed by the Atmospheric InfraRed Sounder in the upper stratosphere. CGW drag in these validated simulations extends 100s of kilometers away from the convective sources, highlighting errors in current gravity wave drag parameterizations due to the use of the ubiquitous single‐column approximation. Such validatable simulations have significant potential to be used to further basic understanding of CGWs, improve their parameterizations physically, and provide more restrictive constraints on tuning with confidence.

Machine Learning Emulation of Subgrid‐Scale Orographic Gravity Wave Drag in a General Circulation Model With Middle Atmosphere Extension

AbstractGravity wave parameterizations contribute to uncertainties in middle atmosphere modeling. To investigate the potential for using machine learning to represent atmospheric gravity waves and the impact of implementing such schemes in a general circulation model (GCM), we train a random forest (RF) emulator on outputs from an existing complex parameterization scheme for orographic gravity wave drag (GWD). The performance of the RF emulator is then evaluated with a focus on stratospheric climatology and variability in climate simulations from the middle atmosphere resolving Beijing Climate Center Atmospheric Circulation Model. In offline tests, the predicted orographic GWD by the RF agrees remarkably well with the target GWD throughout the troposphere and the middle atmosphere. The RF emulator can reproduce the observed climatology of zonal‐mean wind and air temperature in the GCM simulation, as well as its target scheme. Compared to the target orographic GWD parameterization scheme, the RF emulator can reproduce the breakdown of the polar vortex in the Southern Hemisphere stratosphere. This study demonstrates the feasibility of using machine learning to emulate parameterized orographic GWD for modeling the stratosphere with a GCM.

Improving the Near-Surface Wind and Turbulence at the Edge of the Orographic Drag Gray Zone by Tuning the Roughness Length

Abstract In this paper, we present the implementation and evaluate the impact of the new roughness length configuration in the ALARO canonical model configuration of the ALADIN system at the edge of the orographic gravity wave drag gray zone. As an essential input for turbulence parameterization, the roughness length affects the near-surface turbulent fluxes and the screen-level interpolation of meteorological parameters. We utilize GMTED2010 and ECOCLIMAP-II databases to derive orographic and vegetation components of the effective roughness length and introduce tuning parameters enabling us to optimize predicted near-surface turbulent momentum fluxes and 10-m wind speed. Based on sensitivity tests, we (i) prove the necessity of tuning the roughness length fields, (ii) considerably reduce the RMSE of near-surface turbulent momentum fluxes (6%–7%) and 10-m wind speed for different groups of stations (3%–10%), and (iii) identify the tree height as the most influential input parameter in our computational domain. The RMSE decomposition indicates that the improvement of 10-m wind speed mostly comes from a decrease in the random error and bias of the mean. The variability is slightly underestimated, thus reducing the model accuracy for wind speeds above the 95th percentile but at an acceptable level. We explain that roughness length tuning also compensates for the missing roughness sublayer correction in our system. Finally, we show that, although the impact of the orographic gravity wave drag scheme at a horizontal mesh size of 1.8 km is generally small, it is still beneficial for capturing some finer features observed in atmospheric soundings. Significance Statement Aiming to improve the 10-m wind speed forecast without sacrificing the accuracy of turbulent momentum fluxes in the kilometric resolution numerical weather prediction model, we derived new roughness length fields from high-resolution physiography databases. Therein, we proved the importance of tuning the input orography and vegetation fields and, depending on the time of day and year, reduced the root-mean-square error of 10-m wind speed by 3%–10%. Further, we demonstrated that orographic gravity wave drag parameterization is still needed to predict finer details seen in wind profiles from atmospheric soundings. Finally, we discussed the related simplifications in our model and their implications and proposed steps toward a more consistent and complete treatment of the near-surface turbulence.

Improved Gravity Wave Drag to Enhance Precipitation Simulation: A Case Study of Typhoon In-Fa

Traditional gravity wave drag parameterizations produce wind stresses that are insensitive to changing horizontal resolution in numerical weather prediction (NWP), partly due to the idealized elliptical assumption. This study employs the modified subgrid-scale orography scheme based on the Fourier transform into gravity wave drag scheme of the China Meteorological Administration Global Forecast System (CMA-GFS) to assess its impacts on simulating precipitation during the slow-moving period of Typhoon In-Fa after its landfall in Zhejiang Province, China. The simulation with the updated scheme can effectively reduce the accumulated precipitation bias of the control one and improve the simulation of precipitation distribution and intensity, especially in the hourly precipitation simulation. The improved scheme primarily influences the wind field of the low-level troposphere and also changes the convergence of the integrated water vapor transport and ascending motions related to the reduced precipitation biases. The modified scheme enhances the tendencies of the horizontal winds caused by the varying horizontal resolutions in the model, strengthening the sensitivity of the gravity wave drag across the horizontal scales. Results from medium-range forecasts indicate the modified scheme benefits the statistics scores of precipitation over China and also reduces root-mean-square errors of 2 m temperature and 10 m winds.

Reducing Winter Precipitation Biases Over the Western Tibetan Plateau in the Model for Prediction Across Scales (MPAS) With a Revised Parameterization of Orographic Gravity Wave Drag

AbstractClimate models often overestimate the precipitation in western Tibetan Plateau (TP) during winter, due to their poor ability in representing the orographic drag of unresolved complex terrain. In this study, the parameterization scheme of orographic gravity wave drag (OGWD) in the Model for Prediction Across Scales (MPAS) is revised to account for the nonhydrostatic effects (NHE) on the surface momentum flux of vertically‐propagating orographic gravity waves (OGWs). The effect of revised OGWD scheme on the simulation of winter precipitation over the TP is examined using parallel numerical experiments with the original and revised schemes, respectively. The results show that the revised scheme can effectively alleviate the precipitation biases in western TP by improving the atmospheric circulation and water vapor transport (WVT). The NHE reduces the surface wave momentum flux of OGWs which results in weaker zonal OGWD in the mid‐low troposphere and thus stronger westerlies over the TP, reducing the easterly biases in the experiment with the original OGWD scheme. The weakened zonal OGWD promotes a plateau‐scale cyclonic circulation to the north of the TP, which suppresses the northern branch of the bifurcated westerlies detouring the TP. According to quantitative analysis, the WVT into the western TP and surrounding areas by upstream westerlies is notably reduced by the northeasterlies of the cyclonic circulation, which eventually leads to the decrease of precipitation in this region.

Response of the resolved planetary wave activity and amplitude to turned off gravity waves in the UA-ICON general circulation model

The interaction between the resolved waves and parameterized gravity wave (GW) drag in the upper atmosphere extension of the ICON model (UA-ICON) are investigated. To this end, we performed a set of 30-year long time slice UA-ICON runs with two sensitivity simulations where either the subgrid-scale orographic (SSO) or non-orographic GW drag parameterizations are switched off (noSSO and noGWD, respectively), and compare them against a control (CTL) simulation where both GWs parameterizations are active. The stratospheric polar vortex accelerates, cools and shifts poleward in both sensitivity runs. The frequency of sudden stratospheric warmings in the CTL simulation is 5.7 events per decade and drops to 1.7 and 4 events per decade in the noSSO and noGWD, respectively. In both sensitivity runs (particularly in noGWD), an enhancement in the resolved wave amplitude is found in the high latitude stratosphere and in the mesosphere and lower thermosphere (MLT) region in all latitudes. The magnitudes of the resolved waves responses are generally larger for noGWD than noSSO. Our results confirm the compensation mechanism in the UA-ICON model, whereby the perturbed forcings in the GW parameterization drag are often canceled or partly compensated by a resolved large-scale wave driving of opposite sign. In addition, evidence is presented that the compensation mechanism is not always operative everywhere. For example, we found a suppression of the upward propagation of the resolved waves in the cold seasons in the noSSO experiment, which is likely linked to a significant reduction of the favorable propagation conditions in the upper stratosphere.

Improving Numerical Weather Prediction–Based Near-Cloud Aviation Turbulence Forecasts by Diagnosing Convective Gravity Wave Breaking

AbstractBased on a convective gravity wave drag parameterization scheme in a numerical weather prediction (NWP) model, previously proposed near-cloud turbulence (NCT) diagnostics for better detecting turbulence near convection are tested and evaluated by using global in situ flight data and outputs from the operational global NWP model of the Korea Meteorological Administration for one year (from December 2016 to November 2017). For comparison, 11 widely used clear air turbulence (CAT) diagnostics currently used in operational NWP-based aviation turbulence forecasting systems are separately computed. For selected cases, NCT diagnostics predict more accurately localized turbulence events over convective regions with better intensity, which is clearly distinguished from the turbulence areas diagnosed by conventional CAT diagnostics that they mostly failed to forecast with broad areas and low magnitudes. Although overall performance of NCT diagnostics for one whole year is lower than conventional CAT diagnostics due to the fact that NCT diagnostics exclusively focus on the isolated NCT events, adding the NCT diagnostics to CAT diagnostics improves the performance of aviation turbulence forecasting. Especially in the summertime, performance in terms of an area under the curve (AUC) based on probability of detection statistics is the best (AUC = 0.837 with a 4% increase, compared to conventional CAT forecasts) when the mean of all CAT and NCT diagnostics is used, while performance in terms of root-mean-square error is the best when the maximum among combined CAT and single NCT diagnostic is used. This implies that including NCT diagnostics to currently used NWP-based aviation turbulence forecasting systems should be beneficial for safety of air travel.

The semiannual oscillation (SAO) in the tropical middle atmosphere and its gravity wave driving in reanalyses and satellite observations

Abstract. 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.

Building Tangent‐Linear and Adjoint Models for Data Assimilation With Neural Networks

AbstractWe assess the ability of neural network emulators of physical parametrization schemes in numerical weather prediction models to aid in the construction of linearized models required by four‐dimensional variational (4D‐Var) data assimilation. Neural networks can be differentiated trivially, and so if a physical parametrization scheme can be accurately emulated by a neural network then its tangent‐linear and adjoint versions can be obtained with minimal effort, compared with the standard paradigms of manual or automatic differentiation of the model code. Here we apply this idea by emulating the non‐orographic gravity wave drag parametrization scheme in an atmospheric model with a neural network, and deriving its tangent‐linear and adjoint models. We demonstrate that these neural network‐derived tangent‐linear and adjoint models not only pass the standard consistency tests but also can be used successfully to do 4D‐Var data assimilation. This technique holds the promise of significantly easing maintenance of tangent‐linear and adjoint codes in weather forecasting centers, if accurate neural network emulators can be constructed.

Machine Learning Emulation of Gravity Wave Drag in Numerical Weather Forecasting.

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.

Towards a more “scale‐aware” orographic gravity wave drag parametrization: Description and initial testing

AbstractMany current orographic gravity wave drag parametrizations employed in numerical weather prediction and climate models assume idealised elliptical subgrid orography. As a result, they do not fully capture the spectrum of subgrid orographic scales and do not exhibit the desired behaviour when the model grid length is varied. This article describes the motivation, formulation, and testing of a new orographic gravity wave drag parametrization in the Met Office Unified Model that is more “scale‐aware”. The scheme circumvents the need to make assumptions about the shape and distribution of the subgrid orography, moving away from elliptical mountains, through the use of Fourier transforms. The reduction in gravity wave surface stress when orographic flow blocking is present is also accounted for. The result is a new scheme that represents subgrid mountain scales more faithfully and consistently, rather than assuming a single mountain scale for each grid box. Tests using both regional and global simulations, ranging in grid spacing from 2–130 km, demonstrate that the scale‐aware scheme provides a more constant total, resolved plus parametrized, orographic gravity wave momentum flux, when the grid length is varied over most regions of the globe. Global five‐day forecasts also show a significant reduction in the too‐strong zonal wind bias within the Northern and Southern Hemisphere upper troposphere to lower stratosphere at grid spacings of 130 and 40 km when the scale‐aware scheme is employed. Some discussion on future developments for the scheme is also presented, noting that improvements to the orographic flow‐blocking drag component are required before the scheme can be implemented operationally.

Observational Validation of Parameterized Gravity Waves From Tropical Convection in the Whole Atmosphere Community Climate Model

AbstractTropical gravity waves that are generated by convection are generally too small in scale and too high in frequency to be resolved in global climate models, yet their drag forces drive the important global‐scale quasi‐biennial oscillation (QBO) in the lower stratosphere, and models rely on parameterizations of gravity wave drag to simulate the QBO. We compare detailed properties of tropical parameterized gravity waves in the Whole Atmosphere Community Climate Model version 6 (WACCM6) with gravity waves observed by long‐duration superpressure balloons and also compare properties of parameterized convective latent heating with satellite data. Similarities and differences suggest that the WACCM6 parameterizations are excellent tools for representing tropical gravity waves, but the results also suggest detailed changes to the gravity wave parameterization tuning parameter assumptions that would bring the parameterized waves into much better agreement with observations. While WACCM6 currently includes only nonstationary gravity waves from convection, adding gravity waves generated by the steady component of the heating that are stationary relative to moving convective rain cells is likely to improve the simulation of the QBO in the model. The suggested changes have the potential to alleviate common biases in simulated QBO circulations in models.

Improved Circulation in the Northern Hemisphere by Adjusting Gravity Wave Drag Parameterizations in Seasonal Experiments With ICON‐NWP

AbstractThe stratosphere is one of the main potential sources for subseasonal to seasonal predictability in midlatitudes in winter. The ability of an atmospheric model to realistically simulate the stratospheric dynamics is essential in order to move forward in the field of seasonal predictions in midlatitudes. Earlier studies with the ICOsahedral Nonhydrostatic atmospheric model (ICON) point out that stratospheric westerlies in ICON are underestimated. This is the first extensive study on the evaluation of Northern Hemisphere stratospheric winter circulation with ICON in numerical weather prediction (NWP) mode. Seasonal experiments with the default setup are able to reproduce the basic climatology of the stratospheric polar vortex. However, westerlies are too weak and major stratospheric warmings too frequent in ICON. Both a reduction of the nonorographic, and a reduction of the orographic gravity wave and wake drag lead to a strengthening of the stratospheric vortex and a bias reduction, in particular in January. However, the effect of the nonorographic gravity wave drag scheme on the stratosphere is stronger. Stratosphere‐troposphere coupling is intensified and more realistic due to a reduced gravity wave drag. Furthermore, an adjustment of the subgrid‐scale orographic drag parameterization leads to a significant error reduction in the mean sea level pressure. As a result of these findings, we present our current suggested improved setup for seasonal experiments with ICON‐NWP.

Impacts of wind profile shear and curvature on the parameterized orographic gravity wave stress in the Weather Research and Forecasting model

AbstractThe parameterization of orographic gravity wave drag (OGWD) in the Weather Research and Forecasting model is extended by including the second‐order Wentzel–Kramers–Brillouin (WKB) corrections to the surface wave momentum flux (SWMF) caused by wind profile shear (WSHR) and curvature (WCUR) effects. Simulations of the atmospheric circulation are performed to study the behaviour and impact of the WKB corrections. In January, the SWMF is weakened in the Northern Hemisphere (NH) midlatitudes by the WSHR term, while the WCUR acts to enhance the SWMF over Antarctica. In July, the WSHR corrections are similar to those in January, whereas the WCUR term produces corrections of opposite sign in the high latitudes of each hemisphere. The latter is attributed to the increase of near‐surface winds in the cold season which reverses the low‐level wind profile curvature. The seasonal reversal of the WCUR term contradicts previous findings obtained from offline evaluation using reanalysis datasets. This may be due to the different OGWD parameterization schemes used, or it may suggest a sensitivity to the height at which the wind profile effects are evaluated. Changes in the SWMF can affect the vertical distribution of parameterized OGWD. In January, the OGWD in the NH midlatitudes is decreased in the lower troposphere but increased in the upper troposphere. This is because a reduced SWMF inhibits wave breaking in the lower troposphere. Therefore, more wave momentum flux (WMF) is transported to the upper troposphere which enhances wave breaking there. The increased upper‐tropospheric wave breaking in turn decreases the WMF propagating into the stratosphere where the OGWD is reduced. In July, the reduction of SWMF over Antarctica is more notable than in the NH midlatitudes in January. Consequently, the OGWD is weakened in the upper troposphere over Antarctica.

Improved Simulation of the Antarctic Stratospheric Final Warming by Modifying the Orographic Gravity Wave Parameterization in the Beijing Climate Center Atmospheric General Circulation Model

The Antarctic stratospheric final warming (SFW) is usually simulated with a substantial delay in climate models, and the corresponding temperatures in austral spring are lower than observations, implying insufficient stratospheric wave drag. To investigate the role of orographic gravity wave drag (GWD) in modeling the Antarctic SFW, in this study the orographic GWD parameterization scheme is modified in the middle-atmosphere version of the Beijing Climate Center Atmospheric General Circulation Model. A pair of simulations are conducted to compare two orographic GWD schemes in simulating the breakdown of the stratospheric polar vortex over Antarctica. The control simulation with the default orographic GWD scheme exhibits delayed vortex breakdown and the cold-pole bias seen in most climate models. In the simulation with modified orographic GWD scheme, the simulated vortex breaks down earlier by 8 days, and the associated cold-pole bias is reduced by more than 2 K. The modified scheme provides stronger orographic GWD in the lower stratosphere, which drives an accelerated polar downwelling branch of the Brewer–Dobson circulation and, in turn, produces adiabatic warming. Our study suggests that modifying orographic GWD parameterizations in climate models would be a valid way of improving the SFW simulation over Antarctica.

Reflection of nonlinear mountain waves by critical levels: behaviour of the reflection coefficient

AbstractCritical levels, where the wind vanishes in the atmosphere, are of key importance for gravity wave drag parametrization. The reflectivity of these levels to mountain waves is investigated here using a combination of high‐resolution numerical simulations and insights from linear theory. A methodology is developed for relating the reflection coefficient of 2D hydrostatic orographic gravity waves to the extrema of the associated drag as a function of an independent flow parameter. This method is then used to infer the variation of the reflection coefficient with flow nonlinearity. To isolate the effect of critical levels, a wind profile with negative shear is adopted, which is characterized by its Richardson number and the dimensionless mountain height , based on the mountain height , Brunt‐Väisälä frequency and surface incoming wind speed . Subject to the assumptions of linear theory, the drag is shown to be modified by wave refraction and reflection. The modulation of the drag by wave reflection is used to derive the reflection coefficient from the drag diagnosed from the numerical simulations. Despite considerable uncertainty, the critical level is found to have an that first increases with for low values of this parameter, and for stronger nonlinearity saturates to a value of about 0.6. The flow configuration in this saturated regime is characterized in the case of high‐drag states by constructive wave interference, resembling downslope windstorms. Wave reflection by critical levels enhances the flow nonlinearity and the associated drag amplification, more than doubling it for values of as low as 0.12. These results emphasize the need to represent this process in orographic gravity wave drag parametrizations, and suggest a possible way of doing it using a prescribed critical level reflection coefficient, derived using the present methodology.

Optimization of Gravity Wave Source Parameters for Improved Seasonal Prediction of the Quasi-Biennial Oscillation

AbstractA methodology is presented for objectively optimizing nonorographic gravity wave source parameters to minimize forecast error for target regions and forecast lead times. In this study, we employ a high-altitude version of the Navy Global Environmental Model (NAVGEM-HA) to ascertain the forcing needed to minimize hindcast errors in the equatorial lower stratospheric zonal-mean zonal winds in order to improve forecasts of the quasi-biennial oscillation (QBO) over seasonal time scales. Because subgrid-scale wave effects play a large role in driving the QBO, this method leverages the nonorographic gravity wave drag (GWD) parameterization scheme to provide the necessary forcing. To better constrain the GWD source parameters, we utilize ensembles of NAVGEM-HA hindcasts over the 2014–16 period with perturbed source parameters and develop a cost function to minimize errors in the equatorial lower stratosphere compared to analysis. Thus, we may determine the set of GWD source parameters that yields a forecast state that most closely agrees with observed QBO winds over each optimization time interval. Results show that the source momentum flux and phase speed spectrum width are the most important parameters. The seasonal evolution of optimal parameter value, specifically a robust semiannual periodicity in the source strength, is also revealed. Changes in optimal source parameters with increasing forecast lead time are seen, as the GWD parameterization takes on a more active role as QBO driver at longer forecast lengths. Implementation of a semiannually varying source function at the equator provides RMS error improvement in QBO winds over the default constant value.