A new three-dimensional residual flow theory and its application to Brewer–Dobson circulation in the middle and upper stratosphere

This study formulates three-dimensional (3-D) residual flow, treating both stationary and transient waves. The zonal and meridional momentum equations contain four terms: the geostrophic wind tendency, Coriolis force for the residual horizontal flow, product of the geostrophic wind and potential vorticity other than the constant planetary vorticity, and friction. The thermodynamic equation contains three terms: the potential temperature tendency, advection of the basic potential temperature by the residual vertical flow, and diabatic heating. The zonal mean of the 3-D residual flow equals the time mean of the residual flow of the transformed Eulerian mean equations. The new residual flow is the sum of that derived by Plumb for transient waves and the quadratic terms of the time-mean fields, which correspond approximately to the Stokes correction due to stationary waves. The 3-D residual flow and momentum equations are symmetric in the zonal and meridional directions, in contrast with those formulated by Kinoshita et al., which treat the time-mean zonal-mean zonal wind as the basic wind. The newly derived formulae are applied to the climatology of the 3-D structure of the deep branch of the Brewer–Dobson circulation. In the Northern Hemisphere in December–January–February, the residual flows are directed inward toward the polar vortex strongly over East Siberia, where the downward flow is maximized, and weakly over the Atlantic; meanwhile, they are directed outward from the vortex over North America and Europe. A longitudinal dependence of the poleward flow is also observed in the Southern Hemisphere in June–July–August.

Marine boundary layers above heterogeneous SST: Along-front winds

Turbulent flow in a weakly convective marine atmospheric boundary layer (MABL) driven by geostrophic winds Vg = 10ms−1 and heterogeneous sea surface temperature (SST) is examined using fine mesh large eddy simulation (LES). The imposed SST heterogeneity is a single-sided warm or cold front with jumps Δθ = (2, −1.5)K varying over a horizontal x distance of 1 km characteristic of an upper ocean mesoscale or submesoscale front. The geostrophic winds are oriented parallel to the SST isotherms, i.e., the winds are along-front. Previously, Sullivan et al. (2020) examined a similar flow configuration but with geostrophic winds oriented perpendicular to the imposed SST isotherms, i.e., the winds were across-front. Results with along-front and across-front winds differ in important ways. With along-front winds the ageostrophic surface wind is weak, about 5 times smaller than the geostrophic wind, and horizontal pressure gradients couple the SST front and the atmosphere in the momentum budget. With across-front winds horizontal pressure gradients are weak and mean horizontal advection primarily balances vertical flux divergence. Along-front winds generate persistent secondary circulations (SC) that modify the surface fluxes as well as turbulent fluxes in the MABL interior depending on the sign of Δθ. Warm and cold filaments develop opposing pairs of SC with a central upwelling or downwelling region between the cells. Cold filaments reduce the entrainment near the boundary-layer top which can potentially impact cloud initiation. The surface-wind SST-isotherm orientation is an important component of atmosphere-ocean coupling. The results also show frontogenetic tendencies in the MABL.

Spatial constraints in large-scale expansion of wind power plants

When wind turbines are arranged in clusters, their performance is mutually affected, and their energy generation is reduced relative to what it would be if they were widely separated. Land-area power densities of small wind farms can exceed 10 W/m2, and wakes are several rotor diameters in length. In contrast, large-scale wind farms have an upper-limit power density in the order of 1 W/m2 and wakes that can extend several tens of kilometers. Here, we address two important questions: 1) How large can a wind farm be before its generation reaches energy replenishment limits and 2) How far apart must large wind farms be spaced to avoid inter–wind-farm interference? We characterize controls on these spatial and temporal scales by running a set of idealized atmospheric simulations using the Weather and Research Forecasting model. Power generation and wind speed within and over the wind farm show that a timescale inversely proportional to the Coriolis parameter governs such transition, and the corresponding length scale is obtained by multiplying the timescale by the geostrophic wind speed. A geostrophic wind of 8 m/s and a Coriolis parameter of 1.05 × 10−4 rad/s (latitude of ∼46°) would give a transitional scale of about 30 km. Wind farms smaller than this result in greater power densities and shorter wakes. Larger wind farms result instead in power densities that asymptotically reach their minimum and wakes that reach their maximum extent.

Northeast Atlantic storminess in centennial reanalyses

<p>Global atmospheric reanalyses are commonly applied for the validation of climate models, diagnostic studies, and driving higher resolution numerical models with the emphasis on assessing climate variability and long-term trends. Over recent years, longer reanalyses spanning a period of more than hundred years have become available. In this study, the variability and long-term trends of storm activity is assessed over the northeast Atlantic in modern centennial reanalysis datasets, namely ERA-20cm, ERA-20c, CERA-20c, and the 20CR-reanalysis suite with 20CRv3 being the most recent one. All reanalyses, except from ERA-20cm, assimilate surface pressure observations, whereby ERA-20C and CERA-20c additionally assimilate surface winds. For the assessment, the well-established storm index of higher annual percentiles of geostrophic wind speeds derived from pressure observations at sea level over a relatively densely monitored marine area is used.</p><p>The results indicate that the examined centennial reanalyses are not able to represent long-term trends of storm activity over the northeast Atlantic, particularly in the earlier years of the period examined when compared with the geostrophic wind index based on pressure observations. Moreover, the reanalyses show inconsistent long-term behaviour when compared with each other. Only in the latter half of the 20th century, the variability of reanalysed and observed storminess time series starts to agree with each other. Additionally, 20CRv3, the most recent centennial reanalysis examined, shows markedly improved results with increased uncertainty, albeit multidecadal storminess variability does not match observed values in earlier times before about 1920.</p><p>The behaviour shown by the centennial reanalyses are likely caused by the increasing number of assimilated observations, changes in the observational databases used, and the different underlying numerical model systems. Furthermore, the results derived from the ERA-20cm reanalysis that does not assimilate any pressure or wind observations suggests that the variability and uncertainty of storminess over the northeast Atlantic is high making it difficult to determine storm activity when numerical models are not bound by observations. The results of this study imply and reconfirm previous findings that the assessment of long-term storminess trends and variability in centennial reanalyses remains a rather delicate matter, at least for the northeast Atlantic region.</p>

North Atlantic winter storm activity in modern reanalyses and pressure-based observations

This study analyzes changes in extratropical windstorms over the North Atlantic during the last decades. We assessed and compared North Atlantic winter storm activity in a comprehensive approach from three different data sources: modern reanalysis data sets, a dynamically downscaled high-resolution global atmospheric climate simulation, and observations. The multi-decadal observations comprise both a storm index derived from geostrophic wind speed triangles and an observational record of low pressure systems counted from weather analyses. Both observational data sets have neither been compared to the most recent reanalyses nor to the downscaled global climate simulation with respect to North Atlantic winter storms before.The similarity of the geostrophic wind speed storm index to reanalyzed high wind speed percentiles and storm numbers confirms its suitability to describe storm frequencies and intensities for multi-decadal time scales. The results show that high wind speeds, storm numbers, and spatial storm track distributions are generally alike in high-resolution reanalyses and downscaled data sets and they reveal an increasing similarity to observations over time. Strong decadal and multi-decadal variability emerged in high wind speed percentiles and storm frequency, but no long-term changes for the last decades were detected.

A k–ε Turbulence Model for the Convective Atmosphere

A k–ε turbulence model for the stable atmosphere is extended for the convective atmosphere. The new model represents the buoyancy-induced increase in the kinetic energy and scale of eddies, and is consistent with the Monin–Obukhov similarity theory for convective atmospheric boundary layers (ABLs). After being incorporated into an ABL model with the Coriolis force, the model is tested by comparing the ABL model results with the Businger–Dyer (BD) relationship. ABL model simulations are carried out to reveal the sensitivity of the vertical wind profile to model parameters (e.g., the Obukhov length, friction velocity, and geostrophic wind). When the friction velocity is consistent with geostrophic wind speed (or the turbulence in the inner regime is in equilibrium with that in the outer regime), the modeled wind profile is close to the BD relationship near the ground surface. Otherwise, the modeled wind profile deviates from the BD relationship, resembling the hockey stick transition model.

Composite Vertical-Motion Patterns near North American Polar–Subtropical Jet Superposition Events

A polar–subtropical jet superposition is preceded by the development of a polar cyclonic potential vorticity (PV) anomaly at high latitudes and a tropical anticyclonic PV anomaly at subtropical latitudes. A confluent large-scale flow pattern can lead to the juxtaposition of these respective PV anomalies at middle latitudes, resulting in the addition of the nondivergent circulations induced by each PV anomaly and an increase in upper-tropospheric wind speeds at the location of jet superposition. Once these PV anomalies become juxtaposed, vertical motion within the near-jet environment facilitates the advection and diabatic redistribution of tropopause-level PV, and the subsequent formation of the steep, single-step tropopause structure that characterizes a jet superposition. Given the importance of vertical motion during the formation of jet superpositions, this study adopts a quasigeostrophic (QG) diagnostic approach to quantify the production of vertical motion during three types of jet superposition events: polar dominant, eastern subtropical dominant, and western subtropical dominant. The diagnosis reveals that the geostrophic wind induced by polar cyclonic QGPV anomalies is predominantly responsible for QG vertical motion in the vicinity of jet superpositions. The QG vertical motion diagnosed from the along-isotherm component of the Q vector, which represents the vertical motion associated with synoptic-scale waves, is dominant within the near-jet environment. The QG vertical motion diagnosed from the across-isotherm component of the Q vector, which represents the vertical motion associated with frontal circulations in the vicinity of the jet, is subordinate within the near-jet environment, but is relatively more important during eastern subtropical dominant events compared to polar dominant and western subtropical dominant events.

Stilling and Recovery of the Surface Wind Speed Based on Observation, Reanalysis, and Geostrophic Wind Theory over China from 1960 to 2017

Surface wind speed (SWS) from meteorological observation, global atmospheric reanalysis, and geostrophic wind speed (GWS) calculated from surface pressure were used to study the stilling and recovery of SWS over China from 1960 to 2017. China experienced anemometer changes and automatic observation transitions in approximately 1969 and 2004, resulting in SWS inhomogeneity. Therefore, we divided the entire period into three sections to study the SWS trend, and found a near-zero annual trend in the SWS in China from 1960 to 1969, a significant decrease of −0.24 m s−1 decade−1 from 1970 to 2004, and a weak recovery from 2005 to 2017. By defining the 95th and 5th percentiles of daily mean wind speeds as strong and weak winds, respectively, we found that the SWS decrease was primarily caused by a strong wind decrease of −8% decade−1 from 1960 to 2017, but weak wind showed an insignificant decreasing trend of −2% decade−1. GWS decreased with a significant trend of −3% decade−1 before the 1990s; during the 1990s, GWS increased with a trend of 3% decade−1 whereas SWS continued to decrease with a trend of 10% decade−1. Consistent with SWS, GWS demonstrated a weak increase after the 2000s. After detrending, both SWS and GWS showed synchronous decadal variability, which is related to the intensity of Aleutian low pressure over the North Pacific. However, current reanalyses cannot reproduce the decadal variability and cannot capture the decreasing trend of SWS either.

German Bight Storminess over the Last Century

<p>Assessing past storm activity provides valuable knowledge for economic and ecological sectors, such as the renewable energy sector, insurances, or health and safety. However, long time series of wind speed measurements are often not available as they are usually hampered by inhomogeneities due to changes in the surroundings of a measurement site, station relocations, and changes in the instrumentation. On the contrary, air pressure measurements provide mostly homogeneous time series as the air pressure is usually unaffected by such factors.</p><p>Therefore, we perform statistical analyses on historical pressure data measured at several locations within the German Bight (southeastern North Sea) between 1897 and 2018. We calculate geostrophic wind speeds from triplets of mean sea level pressure observations that form triangles over the German Bight. We then investigate the evolution of German Bight storminess from 1897 to 2018 through analyzing upper quantiles of geostrophic wind speeds, which act as a proxy for past storm activity. The derivation of storm activity is achieved by enhancing the established triangle proxy method via combining and merging storminess time series from numerous partially overlapping triangles in an ensemble-like manner. The utilized approach allows for the construction of robust, long-term and subdaily German Bight storminess time series. Further, the method provides insights into the underlying uncertainty of the time series.</p><p>The results show that storm activity over the German Bight is subject to multidecadal variability. The latest decades are characterized by an increase in activity from the 1960s to the 1990s, followed by a decline lasting into the 2000s and below-average activity up until present. The results are backed through a comparison with reanalysis products from four datasets, which provide high-resolution wind and pressure data starting in 1979 and offshore wind speed measurements taken from the FINO-WIND project. This study also finds that German Bight storminess positively correlates with storminess in the North-East Atlantic in general. In certain years, however, notably different levels of storm activity in the two regions can be found, which likely result from shifted large-scale circulation patterns.</p>