ALBERT

Description: 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.

Description: Safety compliance issues for operational studies of the atmosphere with balloons require quantifying risks associated with descent and developing strategies to reduce the uncertainties at the location of the touchdown point. Trajectory forecasts are typically computed from weather forecasts produced by an operational center, for example, the European Centre for Medium-Range Weather Forecasts. This study uses past experiments to investigate strategies for improving these forecasts. Trajectories for open stratospheric balloon (OSB) short-term flights are computed using mesoscale simulations with the Weather and Research Forecasting (WRF) Model initialized with ECMWF operational forecasts and are assimilated with radio soundings using the Data Assimilation Research Testbed (DART) ensemble Kalman filter, for three case studies during the Strapolété 2009 campaign in Sweden. The results are very variable: in one case, the error in the final simulated position is reduced by 90% relative to the forecast using the ECMWF winds, while in another case the forecast is hardly improved. Nonetheless, they reveal the main source of forecasting error: during the ceiling phase, errors due to unresolved inertia–gravity waves accumulate as the balloon continuously experiences one phase of a wave for a few hours, whereas they essentially average out during the ascent and descent phases, when the balloon rapidly samples through whole wave packets. This sensitivity to wind during the ceiling phase raises issues regarding the feasibility of such forecasts and the observations that would be needed. The ensemble spread is also analyzed, and it is noted that the initial ensemble perturbations should probably be improved in the future for better forecasts.

Description: The austral stratospheric final warming date is often predicted with substantial delay in several climate models. This systematic error is generally attributed to insufficient parameterized gravity wave (GW) drag in the stratosphere around 60°S. A simulation with a general circulation model [Laboratoire de Météorologie Dynamique zoom model (LMDZ)] with a much less pronounced bias is used to analyze the contribution of the different types of waves to the dynamics of the final warming. For this purpose, the resolved and unresolved wave forcing of the middle atmosphere during the austral spring are examined in LMDZ and reanalysis data, and a good agreement is found between the two datasets. The role of parameterized orographic and nonorographic GWs in LMDZ is further examined, and it is found that orographic and nonorographic GWs contribute evenly to the GW forcing in the stratosphere, unlike in other climate models, where orographic GWs are the main contributor. This result is shown to be in good agreement with GW-resolving operational analysis products. It is demonstrated that the significant contribution of the nonorographic GWs is due to highly intermittent momentum fluxes produced by the source-related parameterizations used in LMDZ, in qualitative agreement with recent observations. This yields sporadic high-amplitude GWs that break in the stratosphere and force the circulation at lower altitudes than more homogeneously distributed nonorographic GW parameterizations do.

Description: Quantification of inertia–gravity waves (IGWs) generated by upper-level jet–surface front systems and their parameterization in global models of the atmosphere relies on suitable methods to estimate the strength of IGWs. A harmonic divergence analysis (HDA) that has been previously employed for quantification of IGWs combines wave properties from linear dynamics with a sophisticated statistical analysis to provide such estimates. A question of fundamental importance that arises is how the measures of IGW activity provided by the HDA are related to the measures coming from the wave–vortex decomposition (WVD) methods. The question is addressed by employing the nonlinear balance relations of the first-order δ–γ, the Bolin–Charney, and the first- to third-order Rossby number expansion to carry out WVD. The global kinetic energy of IGWs given by the HDA and WVD are compared in numerical simulations of moist baroclinic waves by the Weather Research and Forecasting (WRF) Model in a channel on the f plane. The estimates of the HDA are found to be 2–3 times smaller than those of the optimal WVD. This is in part due to the absence of a well-defined scale separation between the waves and vortical flows, the IGW estimates by the HDA capturing only the dominant wave packets and with limited scales. It is also shown that the difference between the HDA and WVD estimates is related to the width of the IGW spectrum.

Description: The contribution of turbulent mixing to heat and tracer transport in the tropical tropopause layer (TTL) is poorly constrained, partly owing to a lack of direct observations. Here, the authors use high-resolution (20 Hz) airborne measurements to study the occurrence and properties of small-scale (

Description: The relationship between gravity wave momentum fluxes and local wind speed is investigated for oceanic regions at high southern latitudes during austral spring. The motivation is to better describe the gravity wave field by identifying a simple relationship between gravity waves and the large-scale flow. The tools used to describe the gravity waves are probability density functions of the gravity wave momentum fluxes. Three independent datasets covering high latitudes in the Southern Hemisphere springtime are analyzed: simulations with a mesoscale model, analyses from the European Centre for Medium-Range Weather Forecasts, and observations from superpressure balloons of the Concordiasi campaign in 2010. A remarkably robust relation is found, with stronger momentum fluxes much more likely in regions of strong winds. The tails of the probability density functions are well described as lognormal. The median momentum flux increases linearly with background wind speed: for winds stronger than 50 m s−1, the median gravity wave momentum fluxes are about 4 times larger than for winds weaker than 10 m s−1. From model output, this relation is found to be relevant from the tropopause to the midstratosphere at least. The flux dependence on wind speed shows a somewhat steeper slope at higher altitude. Several different processes contribute to this relation, involving both the distribution of sources and the effects of propagation and filtering. It is argued that the location of tropospheric sources is the main contributor in the upper troposphere and lowermost stratosphere and that lateral propagation into regions of strong winds becomes increasingly important above.

Description: Due to their increasing spatial resolution, numerical weather prediction (NWP) models and the associated analyses resolve a growing fraction of the gravity wave (GW) spectrum. However, it is unclear how well this “resolved” part of the spectrum truly compares to the actual atmospheric variability. In particular, the Lagrangian variability, relevant, for example, to atmospheric dispersion and to microphysical modeling in the upper troposphere–lower stratosphere (UTLS), has not yet been documented in recent products. To address this shortcoming, this paper presents an assessment of the GW spectrum as a function of the intrinsic (air parcel following) frequency in recent (re)analyses (ERA-Interim, ERA5, the ECMWF operational analysis and MERRA-2). Long-duration, quasi-Lagrangian balloon observations in the equatorial and Antarctic lower stratosphere are used as a reference for the atmospheric spectrum and are compared to synthetic balloon observations along trajectories calculated using the wind and temperature fields of the reanalyses. Overall, the reanalyses represent realistic features of the spectrum, notably the spectral gap between planetary and gravity waves and a peak in horizontal kinetic energy associated with inertial waves near the Coriolis frequency f in the polar region. In the tropics, they represent the slope of the spectrum at low frequency. However, the variability is generally underestimated even in the low-frequency portion of the spectrum. In particular, the near-inertial peak, although present in the reanalyses, has a reduced magnitude compared to balloon observations. We compare the observed and modeled variabilities of temperature, zonal momentum flux and vertical wind speed, which are related to low-, mid- and high-frequency waves, respectively. The probability density function (PDF) distributions have similar shapes but show increasing disagreement with increasing intrinsic frequency. Since at those altitudes they are mainly caused by gravity waves, we also compare the geographic distribution of vertical wind fluctuations in the different products, which emphasizes the increase of both GW variance and intermittency with horizontal resolution. Finally, we quantify the fraction of resolved variability and its dependency on model resolution for the different variables. In all (re)analysis products, a significant part of the variability is still missing, especially at high frequencies, and should hence be parameterized. Among the two polar balloon datasets used, one was broadcast on the Global Telecommunication System for assimilation in NWP models, while the other consists of independent observations (unassimilated in the reanalyses). Comparing the Lagrangian spectra between the two campaigns shows that the (re)analyses are largely influenced by balloon data assimilation, which especially enhances the variance at low GW frequency.

Description: 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.