Wave‐induced Lagrangian fluctuations of temperature and vertical velocity in the lower stratosphere are quantified using measurements from superpressure balloons (SPBs). Observations recorded every ...minute along SPB flights allow the whole gravity wave spectrum to be described and provide unprecedented information on both the intrinsic frequency spectrum and the probability distribution function of wave fluctuations. The data set has been collected during two campaigns coordinated by the French Space Agency in 2010, involving 19 balloons over Antarctica and 3 in the deep tropics. In both regions, the vertical velocity distributions depart significantly from a Gaussian behavior. Knowledge on such wave fluctuations is essential for modeling microphysical processes along Lagrangian trajectories. We propose a new simple parameterization that reproduces both the non‐Gaussian distribution of vertical velocities (or heating/cooling rates) and their observed intrinsic frequency spectrum.
Key Points
Long‐duration balloon observations are used to characterize Lagrangian temperature fluctuations
Intrinsic frequency spectra and PDFs are derived for temperature and cooling rates
A parameterization of gravity wave temperature fluctuations in the lower stratosphere is developed
Spontaneous generation of inertia‐gravity waves from balanced flows is investigated in idealized simulations of dipoles. Long integrations are performed for dipoles with different Rossby numbers (Ro) ...to identify the backreaction of the waves. Emission of waves is detected only for large enough Ro (>0.15), and it then leads to a slow decay of the dipole's kinetic energy. A major finding is that this decay is well captured by the simulations, although positions of the waves appear still sensitive to the resolution, and their maximum vertical velocity increases linearly with resolution. The interpretation is that the emission process is well resolved and fairly insensitive to resolution, while the propagation and dissipation at small scales remains sensitive to resolution. The implication is that the simulations yield an estimate of the leakage of energy from balanced motions to gravity waves, providing a useful estimate of a poorly constrained flux in the ocean's energy budget.
Key Points
Maximum wave vertical velocity is proportional to the resolution
The energy extracted by the waves is weakly sensitive to the resolution
The dipole loses at most 0.2% energy per day to inertia‐gravity waves
The spontaneous generation of inertia-gravity waves in idealized life cycles of baroclinic instability is investigated using the Weather Research and Forecasting Model. Two substantially different ...life cycles of baroclinic instability are obtained by varying the initial zonal jet. The wave generation depends strongly on the details of the baroclinic wave's development. In the life cycle dominated by cyclonic behavior, the most conspicuous gravity waves are excited by the upper-level jet and are broadly consistent with previous simulations of O'Sullivan and Dunkerton. In the life cycle that is dominated by anticyclonic behavior, the most conspicuous gravity waves even in the stratosphere are excited by the surface fronts, although the fronts are no stronger than in the cyclonic life cycle. The anticyclonic life cycle also reveals waves in the lower stratosphere above the upper-level trough of the baroclinic wave; these waves have not been previously identified in idealized simulations. The sensitivities of the different waves to both resolution and dissipation are discussed. PUBLICATION ABSTRACT
Abstract
In a recent study, O’Neill et al. analyzed the divergence of surface winds above the northwest Atlantic. In the time mean, a band of convergence is found, overlying the southern flank of the ...Gulf Stream. To quantify the impact of synoptic storms, the authors proposed to compare the time-mean divergence with the divergence averaged in the absence of rain. In the resulting conditional-average field, divergence was found to be positive nearly everywhere. O'Neill et al. concluded that this absence of convergence precludes the Ekman-balanced mass adjustment to be responsible for the atmospheric response above the Gulf Stream. Using a simplistic toy model as well as a numerical simulation representative of a storm track, we show that the absence of negative divergence values purely results from the correlation between rain and convergence: the conditional average based on the absence of rain necessarily implies a shift toward positive divergence values. In consequence, we argue that conditional statistics (based on the absence of rain or removing extreme values in the divergence field), as produced by O’Neill et al., do not allow conclusions on the mechanisms underlying the atmospheric response to the Gulf Stream. They nevertheless highlight the essential role of synoptic storms in shaping the divergence field in instantaneous fields.
Abstract
In this article, long-duration balloon and spaceborne observations, and mesoscale numerical simulations are used to study the intermittency of gravity waves in the lower stratosphere above ...Antarctica and the Southern Ocean; namely, the characteristics of the gravity wave momentum-flux probability density functions (pdfs) obtained with these three datasets are described. The pdfs consistently exhibit long tails associated with the occurrence of rare and large-amplitude events. The pdf tails are even longer above mountains than above oceanic areas, which is in agreement with previous studies of gravity wave intermittency in this region. It is moreover found that these rare, large-amplitude events represent the main contribution to the total momentum flux during the winter regime of the stratospheric circulation. In contrast, the wave intermittency significantly decreases when stratospheric easterlies develop in late spring and summer. It is also shown that, except above mountainous areas in winter, the momentum-flux pdfs tend to behave like lognormal distributions. Monte Carlo simulations are undertaken to examine the role played by critical levels in influencing the shape of momentum-flux pdfs. In particular, the study finds that the lognormal shape may result from the propagation of a wave spectrum into a varying background wind field that generates the occurrence of frequent critical levels.
For several decades, jets and fronts have been known from observations to be significant sources of internal gravity waves in the atmosphere. Motivations to investigate these waves have included ...their impact on tropospheric convection, their contribution to local mixing and turbulence in the upper troposphere, their vertical propagation into the middle atmosphere, and the forcing of its global circulation. While many different studies have consistently highlighted jet exit regions as a favored locus for intense gravity waves, the mechanisms responsible for their emission had long remained elusive: one reason is the complexity of the environment in which the waves appear; another reason is that the waves constitute small deviations from the balanced dynamics of the flow generating them; i.e., they arise beyond our fundamental understanding of jets and fronts based on approximations that filter out gravity waves. Over the past two decades, the pressing need for improving parameterizations of nonorographic gravity waves in climate models that include a stratosphere has stimulated renewed investigations. The purpose of this review is to present current knowledge and understanding on gravity waves near jets and fronts from observations, theory, and modeling, and to discuss challenges for progress in coming years.
Key Points
Observations show the importance of non-orographic waves at mid-latitudes
Idealized simulations explain some of the observed gravity waves near jets
Remaining challenges include taking moist processes into account
Transmission system operator (TSOs) need to project the system state at the seasonal scale to evaluate the risk of supply-demand imbalance for the season to come. Seasonal planning of the electricity ...system is currently mainly adressed using climatological approach to handle variability of consumption and production. Our study addresses the need for quantitative measures of the risk of supply-demand imbalance, exploring the use of sub-seasonal to seasonal forecasts which have hitherto not been exploited for this purpose. In this study, the risk of supply-demand imbalance is defined using exclusively the wind energy production and the consumption peak at 7 pm. To forecast the risks of supply-demand imbalance at monthly to seasonal time horizons, a statistical model is developed to reconstruct the joint probability of consumption and production. It is based on a the conditional probability of production and consumption with respect to indexes obtained from a linear regression of principal components of large-scale atmospheric predictors. By integrating the joint probability of consumption and production over different areas, we define two kind of risk measures: one quantifies the probablity of deviating from the climatological means, while the other, which is the value at risk at 95% confidence level (VaR95) of the difference between consumption and production, quantifies extreme risks of imbalance. In the first case, the reconstructed risk accurately reproduces the actual risk with over 0.80 correlation in time, and a hit rate around 70–80%. In the second case, we find a mean absolute error (MAE) between the reconstructed and real extreme risk of 2.5 to 2.8 GW, a coefficient of variation of the root mean square error (CV-RMSE) of 3.8% to 4.2% of the mean actual VaR95 and a correlation of 0.69 and 0.66 for winter and fall, respectively. By applying our model to ensemble forecasts performed with a numerical weather prediction model, we show that forecasted risk measures up to 1 month horizon can outperform the climatology often used as the reference forecast (time correlation with actual risk ranging between 0.54 and 0.82). At seasonal time horizon (3 months), our forecasts seem to tend to the climatology.
The relationship between the wind speed derived from the outputs of a numerical-weather-prediction model and from observations is explored using statistical and machine-learning models. Eight years ...of wind-speed measurements at a height of 10 m (from 2010 to 2017) from 171 stations spread over mainland France and Corsica are used for reference. Operational analyses from the European Center for Medium Range Weather Forecasts (ECMWF) provide the model information not only on the surface flow, but on other aspects of the atmospheric state at the location (or above) each station. In a first step, a large number of explanatory variables are used as input to several models (linear regressions,
k
-nearest neighbours, random forests, and gradient boosting). The modelled wind speed in the ECMWF analyses, by itself, has root-mean-square errors over all stations distributed widely around a median of 1.42 m s
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1
. Using statistical post-processing and making use of a historical dataset for training, the median of the root-mean-square errors at all stations can be reduced down to 1.07 m s
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1
when modelled with linear regressions, and down to 0.94 m s
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1
with the machine-learning models (random forests or gradient boosting). Yet more significant decreases are found for coastal stations where the errors are largest. The random-forest models are further explored to reduce the list of explanatory variables: a list of 25 explanatory variables, mainly consisting of flow variables (wind speed, velocity components, horizontal gradients of geopotential on different isobaric surfaces, wind shear between 10 and 100 m) and including marginally some temperature variables, appears as a good compromise between performance and simplicity. Finally, as a preliminary test for further work, the relation thus captured between the model outputs and the observed wind speed at a given time is applied to forecasts of the numerical-weather-prediction model, for lead times up to 24 h. The machine-learning model is found to be essentially as relevant on the forecasts as it was on the analyses, encouraging further use and development of these approaches for local wind-speed forecasts.
Two case studies of nonorographic gravity waves are carried out for wave events that occurred over the Southern Ocean in November 2005. Mesoscale simulations were carried out with the Weather and ...Research Forecast model. The simulated waves were compared to observations from superpressure balloons of the Vorcore campaign and from the High Resolution Dynamic Limb Sounder satellite. Satisfactory agreement is found, giving confidence in the estimations of wave parameters and amplitudes. For the amplitudes, both the model and observations provide a lower bound, for different reasons. Waves are found in the lower stratosphere with horizontal wavelengths of the order of 150–200 km in the horizontal, 5–8 km in the vertical, corresponding to intrinsic frequencies between 5 and 10 f, where f is the Coriolis parameter. Although the tropospheric flow is very different between the two cases, there are features which are common and appear significant for the gravity waves: these include intense localized updrafts associated with convection in the troposphere and a displaced polar vortex inducing strong winds in the stratosphere above the frontal region. Relative to theoretical expectations, the simulations emphasize the role of moisture. Intrinsic frequencies are significantly higher than those expected for waves produced by dry spontaneous generation from jets. To quantify the contribution of moisture, dry simulations were carried out, yielding momentum fluxes over oceanic regions that were 2.5 times weaker. Identification of the generation mechanisms in these complex flows calls for further study, and these should include moisture and a realistic stratospheric jet.
Key Points
Good agreement between simulated and observed nonorographic gravity waves
Intrinsic frequencies of the order of 5–10 times the inertial frequency
Moist convection and strong stratospheric winds contribute to the waves
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