The Quarterly Journal of the Royal Meteorological Society

doi: 10.1002/qj.3566pmid: N/A

Renaud, Antoine; Venaille, Antoine

doi: 10.1002/qj.3821pmid: N/A

The Holton–Lindzen–Plumb (HLP) model describes the spontaneous emergence of mean flow reversals in stratified fluids. It has played a central role in understanding the Quasi‐Biennial Oscillation of equatorial winds in Earth's stratosphere and has arguably become a linchpin of wave–mean flow interaction theory in geophysical and astrophysical fluid dynamics. The derivation of the model's equation from primary equations follows from several assumptions, including quasi‐linear approximations, WKB expansion of the wavefield, simplifications of boundary‐layer terms, among others. Starting from the two‐dimensional, non‐rotating, Boussinesq equations, we present in this paper a self‐consistent derivation of the HLP model and show the existence of a distinguished limit for which all approximations remains valid. We furthermore discuss the important role of boundary conditions, and the relevance of this model to describe secondary bifurcations associated with a quasi‐periodic route to chaos.

Spensberger, C.; Madonna, E.; Boettcher, M.; Grams, C. M.; Papritz, L.; Quinting, J. F.; Röthlisberger, M.; Sprenger, M.; Zschenderlein, P.

doi: 10.1002/qj.3822pmid: N/A

In both 2003 and 2018 a heatwave in Scandinavia in July was followed by a heatwave in Central Europe in August. Whereas the transition occurred abruptly in 2003, it was gradual in 2018 with a 12‐day period of concurrent heatwaves in both regions. This study contrasts these two events in the context of a heatwave climatology to elucidate the dynamics of both concurrent and sequential heatwaves. Central European and, in particular, concurrent heatwaves are climatologically associated with weak pressure gradient (WPG) events over Central Europe, which indicate the absence of synoptic activity over this region. One synoptic pattern associated with such events is Scandinavian blocking. This pattern is at the same time conducive to heatwaves in Scandinavia, thereby providing a mechanism by which Scandinavian and Central European heatwaves can co‐occur. Further, the association of WPG events with Scandinavian blocking constitutes a mechanism that allows heatwaves to grow beyond the perimeter of the synoptic system from which they emanated. A trajectory analysis of the source regions of the low‐level air incorporated in the heatwaves indicates rapidly changing air mass sources throughout the heatwaves in both regions, but no recycling of heat from one heatwave to the other. This finding is line with a composite analysis indicating that transitions between Scandinavian and Central European heatwaves are merely a random coincidence of heatwave onset and decay.

Hamidi, Yamina; Raynaud, Laure; Rottner, Lucie; Arbogast, Philippe

doi: 10.1002/qj.3823pmid: N/A

Object‐based methods are commonly used for verification and postprocessing of high‐resolution precipitation forecasts. They usually detect objects based on intensity criteria only, without considering the spatial organization of rainfall, known as texture. This article evaluates the performance of several machine‐learning methods to detect “continuous” and “intermittent” rainfall patterns in the forecasts of the French convective‐scale Arome model. A sliding‐window segmentation algorithm, which applies a classification model at each grid point, is implemented. Several classifiers and input textural features are compared. Overall, intermittent precipitation is the most difficult to detect. The random forest classifier is shown to provide the best classification results independently of the predictor used, with a surprising ability to extract a relevant signal from a synthetic descriptor such as the rainfall cumulative distribution function, as well as from the large amount of unprocessed information provided by neighbouring grid points. On the other hand, the logistic regression classifier needs a texture‐oriented predictor, such as the statistics derived from the grey‐level co‐occurrence matrix, to perform well. Global insight into model behaviour is then obtained by examining the importance of input features. Finally, we show that random forests trained on Arome deterministic forecasts can be applied successfully to discriminate between precipitation textures in different Arome configuration outputs and gridded observations.

Chen, Yan ; Zhang, Weimin; Wang, Pinqiang

doi: 10.1002/qj.3824pmid: N/A

We presented a new local particle filter named the localized weighted ensemble Kalman filter (LWEnKF), which was tested and verified using a simple high‐dimensional Lorenz 96 model. A revised LWEnKF, the proposal weights calculation of which is modified through localization to prevent filter degeneracy for real geophysical models, is explored further in this article and shows lots of potential in the implementation of real complex models. For geophysical models, the ocean dynamics changes slowly compared with that of the atmosphere. With a relatively low resolution, it is weakly nonlinear in the surface layers of the ocean model used in this article, which fits the linear and Gaussian assumptions of the EnKF but could be a challenge for particle filters in the data assimilation process. With only 50 particles, the LWEnKF assimilates the sea‐surface temperature (SST), sea‐surface height (SSH), temperature, and salinity profiles with affordable computational cost, providing a reasonable forecast. Moreover, the LWEnKF is compared with the ensemble Kalman filter (EnKF) and the local particle filter (PF). For observed variables, the LWEnKF performs comparably to the EnKF, as the observation operator is linear. For unobserved variables, the LWEnKF provides more accurate forecasts than the EnKF, since the latter considers only the correlations, while the former considers higher‐order moments. The local PF ensemble does not converge to the observed solution in an ample amount of time in this study, which needs further investigation.

Alves, José M.R.; Caldeira, Rui M.A.; Miranda, Pedro M.A.

doi: 10.1002/qj.3825pmid: N/A

Madeira island is a well‐known source of atmospheric and oceanic eddy activity, with relevant downstream impact in both media. Previous studies focused on the dynamics of the island wake environment, suggesting the relevance of different atmosphere–ocean interactions in its maintenance. Here, results from one summer (two months) of fully coupled atmosphere–ocean high‐resolution simulations are used to explore such interactions and to further understand the dynamics of Madeira's wake. Those results, validated against available in situ and remote‐sensing data, indicate that the atmospheric and ocean circulations near Madeira are dominated by the variability of two quasi‐permanent features, its tip‐jets, and more so by the variability of its eastern jet. While both jets are of comparable magnitude and present similar intraseasonal variability at the multi‐week time‐scale, they are associated with qualitatively different forcing. The jets dominate the atmosphere forcing over the upper ocean, leading to enhanced mixing and deeper mixed‐layer depth. Oceanic eddies are more frequent in the east jet region, as shedding anticyclones, confirming observational evidence. A comparison with a similar one‐way coupled atmospheric simulation indicates that atmosphere–ocean feedbacks are relevant to the coastal surface temperature.

Boyaj, Alugula; Dasari, Hari P.; Hoteit, Ibrahim; Ashok, Karumuri

doi: 10.1002/qj.3826pmid: N/A

Through an analysis of land use and land cover (LULC) data for the years 2005 and 2017 from the Advanced Wide Field Sensor onboard the Indian Remote Sensing satellite, we find considerable changes in the LULC in three major states of south India, namely, Tamil Nadu, Telangana and Kerala. This change is mainly due to increasing urbanization, in addition to the change of prevalent mixed forest into deciduous needle/leaf forest in Kerala. Motivated by this finding, we study the impact of these LULC changes over a decade on the extremes of twelve heavy rainfall events in these states through several sensitivity experiments with a convection‐permitting Weather Research and Forecasting model, by changing the LULC boundary conditions. We particularly focus on three representative heavy rainfall events, specifically, over (a) Chennai (1 December 2015), (b) Telangana (24 September 2016), and (c) Kerala (15 August 2018). The simulated rainfall patterns of the three heavy rainfall events are found to be relatively better with the use of the 2017 LULC boundary conditions. The improvement is statistically significant in the case of the Chennai and Kerala events. On analysis of these simulations, and output from additional simulations we have conducted for nine other heavy rainfall events, we suggest that the recent LULC changes result in higher surface temperatures and sensible heat fluxes, and a deeper and moist boundary layer. This causes a relatively higher convective available potential energy and, consequently, heavier rainfall. We find the LULC changes in the three states, mainly dominated by the increasing urbanization in Telangana and Tamil Nadu, enhance the rainfall during the heavy rainfall events by 20–25%. This is the first extensive investigation of multiple and multi‐regional cases over the Indian region.

Xu, Xin; Teixeira, Miguel A. C.; Xue, Ming; Lu, Yixiong; Tang, Jianping

doi: 10.1002/qj.3828pmid: N/A

The 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.

Montgomery, Michael T.; Kilroy, Gerard; Smith, Roger K.; Črnivec, Nina

doi: 10.1002/qj.3837pmid: N/A

An idealized, three‐dimensional, 1 km horizontal grid spacing numerical simulation of a rapidly intensifying tropical cyclone is used to extend basic knowledge on the role of mean and eddy momentum transfer on the dynamics of the intensification process. Examination of terms in the tangential and radial velocity tendency equations provides an improved quantitative understanding of the dynamics of the spin‐up process within the inner‐core boundary layer and eyewall regions of the system‐scale vortex. Unbalanced and non‐axisymmetric processes are prominent features of the rapid spin‐up process. In particular, the wind asymmetries, associated in part with the asymmetric deep convection, make a substantive contribution (∼30%) to the maximum wind speed inside the radius of this maximum. The analysis provides a novel explanation for inflow jets sandwiching the upper‐tropospheric outflow layer which are frequently found in numerical model simulations. In addition, it provides an opportunity to assess the applicability of generalized Ekman balance during rapid vortex spin‐up. The maximum tangential wind occurs within and near the top of the frictional inflow layer and as much as 10 km inside the maximum gradient wind. Spin‐up in the friction layer is accompanied by supergradient winds that exceed the gradient wind by up to 20%. Overall, the results affirm prior work pointing to significant limitations of a purely axisymmetric balance description, for example, gradient balance/Ekman balance, when applied to a rapidly intensifying tropical cyclone.

Niwa, Yosuke; Fujii, Yosuke

doi: 10.1002/qj.3838pmid: N/A

One effective data assimilation/inversion method is the four‐dimensional variational method (4D‐Var). However, it is a non‐trivial task for a conventional 4D‐Var to estimate a posterior error covariance matrix. This study proposes a method to estimate a posterior error covariance matrix applied to the linear inverse problem of an atmospheric constituent. The method was constructed within a 4D‐Var framework using a quasi‐Newton method with the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm. The proposed method was constructed such that conjugacy among the set of increment vector pairs was ensured. It is theoretically demonstrated that, when this conjugate property is coupled with preconditioning, an analytical solution of a posterior error covariance matrix could be obtained from the same number of vector pairs as observations. Furthermore, to accelerate the speed of convergence, the method can be coupled with an ensemble approach. By performing a simple advection test, it was confirmed that the proposed method could obtain an analytical matrix of the posterior error covariance within the same number of iterations as the observations. Furthermore, the method was also evaluated using an atmospheric CO2 inverse problem, which demonstrated its practical utility. The evaluation revealed that the proposed method could provide accurate estimates not only of the diagonal but also of the off‐diagonal elements of the posterior error covariance matrix. Although far more expensive than optimal state estimation, the computational efficiency was found to be reasonable for practical use, especially in conjunction with an ensemble approach. The accurate estimation of a posterior error covariance matrix resulting from the proposed method could provide valuable quantitative information regarding the uncertainties of estimated variables as well as the observational impacts, which would be beneficial for designing observation networks. Furthermore, error correlations derived from the estimated off‐diagonal elements could benefit the interpretation of optimised parameter variations.