Cold wintertime air masses over Europe: where do they come from and how do they form?

Despite the general warming trend, wintertime cold-air outbreaks in Europe have remained nearly as extreme and as common as decades ago. In this study, we identify six principal 850 hPa cold anomaly types over Europe in 1979–2020 using self-organizing maps (SOMs). Based on extensive analysis of atmospheric large-scale circulation patterns combined with nearly 2 million kinematic backward trajectories, we show the origins and contributions of various physical processes to the formation of cold wintertime 850 hPa air masses. The location of the cold anomaly region is closely tied to the location of blocking; if the block is located farther to the east, the cold anomaly is also displaced eastwards. Considering air mass evolution along the trajectories, the air parcels are typically initially (5–10 d before) colder than at their arrival in Europe, but initially warmer air parcels also sometimes lead to cold anomalies over Europe. Most commonly the effect of adiabatic warming on the temperature anomalies is overcompensated for by advection from regions that are climatologically colder than the target region, supported by diabatic cooling along the pathway. However, there are regional differences: cold anomalies over western Europe and southeastern Europe are dominantly caused by advection and over eastern Europe by both advective and diabatic processes. The decadal-scale warming in the site of air mass origin has been partly compensated for by enhanced diabatic (radiative) cooling along the pathway to Europe. There have also been decadal changes in large-scale circulation patterns and air mass origin. Our results suggest that understanding future changes in cold extremes will require in-depth analyses of both large-scale circulation and the physical (adiabatic and diabatic) processes.</p

Dynamics of concurrent and sequential Central European and Scandinavian heatwaves

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

The roles of static stability and tropical – extratropical interactions in the summer interannual variability of the North Atlantic sector

Summer seasonal forecast skill in the North Atlantic sector is lower than winter skill. To identify potential controls on predictability, the sensitivity of North Atlantic baroclinicity to atmospheric drivers is quantified. Using ERA-INTERIM reanalysis data, North Atlantic storm-track baroclinicity is shown to be less sensitive to meridional temperature-gradient variability in summer. Static stability shapes the sector’s interannual variability by modulating the sensitivity of baroclinicity to variations in meridional temperature gradients and tropopause height and by modifying the baroclinicity itself. High static stability anomalies at upper levels result in more zonal extratropical cyclone tracks and higher eddy kinetic energy over the British Isles in the summertime. These static stability anomalies are not strongly related to the summer NAO; but they are correlated with the suppression of convection over the tropical Atlantic and with a poleward-shifted subtropical jet. These results suggest a non-local driver of North Atlantic variability. Furthermore, they imply that improved representations of convection over the south-eastern part of North America and the tropical Atlantic might improve summer seasonal forecast skill

Analytical in vitro approach for studying cyto- and genotoxic effects of particulate airborne material

In the field of inhalation toxicology, progress in the development of in vitro methods and efficient exposure strategies now offers the implementation of cellular-based systems. These can be used to analyze the hazardous potency of airborne substances like gases, particles, and complex mixtures (combustion products). In addition, the regulatory authorities require the integration of such approaches to reduce or replace animal experiments. Although the animal experiment currently still has to provide the last proof of the toxicological potency and classification of a certain compound, in vitro testing is gaining more and more importance in toxicological considerations. This paper gives a brief characterization of the CULTEX® Radial Flow System exposure device, which allows the exposure of cultivated cells as well as bacteria under reproducible and stable conditions for studying cellular and genotoxic effects after the exposure at the air–liquid or air–agar interface, respectively. A commercial bronchial epithelial cell line (16HBE14o-) as well as Salmonella typhimurium tester strains were exposed to smoke of different research and commercial available cigarettes. A dose-dependent reduction of cell viability was found in the case of 16HBE14o- cells; S. typhimurium responded with a dose-dependent induction of revertants. The promising results recommend the integration of cellular studies in the field of inhalation toxicology and their regulatory acceptance by advancing appropriate validation studies

The Iceland Greenland Seas Project

A coordinated atmosphere-ocean research project, centered on a rare wintertime field campaign to the Iceland and Greenland Seas, seeks to determine the location and causes of dense water formation by cold-air outbreaks. The Iceland Greenland Seas Project (IGP) is a coordinated atmosphere-ocean research program investigating climate processes in the source region of the densest waters of the Atlantic Meridional Overturning Circulation. During February and March 2018, a field campaign was executed over the Iceland and southern Greenland Seas that utilized a range of observing platforms to investigate critical processes in the region – including a research vessel, a research aircraft, moorings, sea gliders, floats and a meteorological buoy. A remarkable feature of the field campaign was the highly-coordinated deployment of the observing platforms, whereby the research vessel and aircraft tracks were planned in concert to allow simultaneous sampling of the atmosphere, the ocean and their interactions. This joint planning was supported by tailor-made convection-permitting weather forecasts and novel diagnostics from an ensemble prediction system. The scientific aims of the IGP are to characterize the atmospheric forcing and the ocean response of coupled processes; in particular, cold-air outbreaks in the vicinity of the marginal-ice zone and their triggering of oceanic heat loss, and the role of freshwater in the generation of dense water masses. The campaign observed the lifecycle of a long-lasting cold-air outbreak over the Iceland Sea and the development of a cold-air outbreak over the Greenland Sea. Repeated profiling revealed the immediate impact on the ocean, while a comprehensive hydrographic survey provided a rare picture of these subpolar seas in winter. A joint atmosphere-ocean approach is also being used in the analysis phase, with coupled observational analysis and coordinated numerical modelling activities underway

Simulating the midlatitude atmospheric circulation: what might we gain from high-resolution modeling of air-sea interactions?

Purpose of Review. To provide a snapshot of the current research on the oceanic forcing of the atmospheric circulation in midlatitudes and a concise update on previous review papers. Recent findings. Atmospheric models used for seasonal and longer timescales predictions are starting to resolve motions so far only studied in conjunction with weather forecasts. These phenomena have horizontal scales of ~ 10–100 km which coincide with energetic scales in the ocean circulation. Evidence has been presented that, as a result of this matching of scale, oceanic forcing of the atmosphere was enhanced in models with 10–100 km grid size, especially at upper tropospheric levels. The robustness of these results and their underlying mechanisms are however unclear. Summary. Despite indications that higher resolution atmospheric models respond more strongly to sea surface temperature anomalies, their responses are still generally weaker than those estimated empirically from observations. Coarse atmospheric models (grid size greater than 100 km) will miss important signals arising from future changes in ocean circulation unless new parameterizations are developed

A Lagrangian analysis of the dynamical and thermodynamic drivers of large-scale Greenland melt events during 1979–2017

In this study, we systematically investigate the dynamical and thermodynamic processes that lead to 77 large-scale melt events affecting high-elevation regions of the Greenland Ice Sheet (GrIS) in June–August (JJA) 1979–2017. For that purpose, we compute 8&thinsp;d kinematic backward trajectories from the lowermost ∼500&thinsp;m above the GrIS during these events. The key synoptic feature accompanying the melt events is an upper-tropospheric ridge southeast of the GrIS associated with a surface high-pressure system. This circulation pattern is favorable to induce rapid poleward transport (up to 40∘ latitude) of warm (∼15&thinsp;K warmer than climatological air masses arriving on the GrIS) and moist air masses from the lower troposphere to the western GrIS and subsequently to distribute them in the anticyclonic flow over north and east Greenland. During transport to the GrIS, the melt event air masses cool by ∼15&thinsp;K due to ascent and radiation, which keeps them just above the critical threshold to induce melting. The thermodynamic analyses reveal that the final warm anomaly of the air masses is primarily owed to anomalous horizontal transport from a climatologically warm region of origin. However, before being transported to the GrIS, i.e., in their region of origin, these air masses were not anomalously warm. Latent heating from condensation of water vapor, occurring as the airstreams are forced to ascend orographically or dynamically, is of secondary importance. These characteristics were particularly pronounced during the most extensive melt event in early July 2012, where, importantly, the warm anomaly was not preserved from anomalously warm source regions such as North America experiencing a record heat wave. The mechanisms identified here are in contrast to melt events in the low-elevation high Arctic and to midlatitude heat waves, where adiabatic warming by large-scale subsidence is essential. Considering the impact of moisture on the surface energy balance, we find that radiative effects are closely linked to the air mass trajectories and enhance melt over the entire GrIS accumulation zone due to (i) enhanced downward longwave radiation related to poleward moisture transport and a shift in the cloud phase from ice to liquid primarily west of the ice divide and (ii) increased shortwave radiation in clear-sky regions east of the ice divide. Given the ongoing increase in the frequency and the melt extent of large-scale melt events, the understanding of upper-tropospheric ridges over the North Atlantic, i.e., also Greenland blocking, and its representation in climate models is crucial in determining future GrIS accumulation zone melt and thus global sea level rise.</p

Diabatic heating and jet stream shifts: A case study of the 2010 negative NAO winter

The role of extratropical diabatic heating in the variability of storm tracks and jet streams remains an important open question. This paper analyses the role of diabatic heating in observationally constrained analysis data for the 2010 winter, which was notable for an extreme southward shift of the North Atlantic eddy-driven jet. An isentropic slope framework is employed by which the contribution of diabatic terms to the maintenance of seasonal mean baroclinicity can be quantified. This reveals a striking contrast between the eastern North Atlantic, where the latent heating shifted south along with the storm track in 2010, and the western North Atlantic, where the latent heating remained fixed over the Gulf Stream. This motivates the hypothesis that the latent heating may contribute to the anchoring of the storm track entrance over the Gulf Stream but provide a very different feedback on the jet variability downstream

Mapping of soil properties at high resolution in Switzerland using boosted geoadditive models

High-resolution maps of soil properties are a prerequisite for assessing soil threats and soil functions and for fostering the sustainable use of soil resources. For many regions in the world, accurate maps of soil properties are missing, but often sparsely sampled (legacy) soil data are available. Soil property data (response) can then be related by digital soil mapping (DSM) to spatially exhaustive environmental data that describe soil-forming factors (covariates) to create spatially continuous maps. With airborne and space-borne remote sensing and multi-scale terrain analysis, large sets of covariates have become common. Building parsimonious models amenable to pedological interpretation is then a challenging task. We propose a new boosted geoadditive modelling framework (geoGAM) for DSM. The geoGAM models smooth non-linear relations between responses and single covariates and combines these model terms additively. Residual spatial autocorrelation is captured by a smooth function of spatial coordinates, and non-stationary effects are included through interactions between covariates and smooth spatial functions. The core of fully automated model building for geoGAM is component-wise gradient boosting. We illustrate the application of the geoGAM framework by using soil data from the Canton of Zurich, Switzerland. We modelled effective cation exchange capacity (ECEC) in forest topsoils as a continuous response. For agricultural land we predicted the presence of waterlogged horizons in given soil depths as binary and drainage classes as ordinal responses. For the latter we used proportional odds geoGAM, taking the ordering of the response properly into account. Fitted geoGAM contained only a few covariates (7 to 17) selected from large sets (333 covariates for forests, 498 for agricultural land). Model sparsity allowed for covariate interpretation through partial effects plots. Prediction intervals were computed by model-based bootstrapping for ECEC. The predictive performance of the fitted geoGAM, tested with independent validation data and specific skill scores for continuous, binary and ordinal responses, compared well with other studies that modelled similar soil properties. Skill score (SS) values of 0.23 to 0.53 (with SS = 1 for perfect predictions and SS = 0 for zero explained variance) were achieved depending on the response and type of score. GeoGAM combines efficient model building from large sets of covariates with effects that are easy to interpret and therefore likely raises the acceptance of DSM products by end-users

Evaluation of digital soil mapping approaches with large sets of environmental covariates

The spatial assessment of soil functions requires maps of basic soil properties. Unfortunately, these are either missing for many regions or are not available at the desired spatial resolution or down to the required soil depth. The field-based generation of large soil datasets and conventional soil maps remains costly. Meanwhile, legacy soil data and comprehensive sets of spatial environmental data are available for many regions. Digital soil mapping (DSM) approaches relating soil data (responses) to environmental data (covariates) face the challenge of building statistical models from large sets of covariates originating, for example, from airborne imaging spectroscopy or multi-scale terrain analysis. We evaluated six approaches for DSM in three study regions in Switzerland (Berne, Greifensee, ZH forest) by mapping the effective soil depth available to plants (SD), pH, soil organic matter (SOM), effective cation exchange capacity (ECEC), clay, silt, gravel content and fine fraction bulk density for four soil depths (totalling 48 responses). Models were built from 300–500 environmental covariates by selecting linear models through (1) grouped lasso and (2) an ad hoc stepwise procedure for robust external-drift kriging (georob). For (3) geoadditive models we selected penalized smoothing spline terms by component-wise gradient boosting (geoGAM). We further used two tree-based methods: (4) boosted regression trees (BRTs) and (5) random forest (RF). Lastly, we computed (6) weighted model averages (MAs) from the predictions obtained from methods 1–5. Lasso, georob and geoGAM successfully selected strongly reduced sets of covariates (subsets of 3–6 % of all covariates). Differences in predictive performance, tested on independent validation data, were mostly small and did not reveal a single best method for 48 responses. Nevertheless, RF was often the best among methods 1–5 (28 of 48 responses), but was outcompeted by MA for 14 of these 28 responses. RF tended to over-fit the data. The performance of BRT was slightly worse than RF. GeoGAM performed poorly on some responses and was the best only for 7 of 48 responses. The prediction accuracy of lasso was intermediate. All models generally had small bias. Only the computationally very efficient lasso had slightly larger bias because it tended to under-fit the data. Summarizing, although differences were small, the frequencies of the best and worst performance clearly favoured RF if a single method is applied and MA if multiple prediction models can be developed