Johannes Lutzmann

Due to their strong temperature gradients, fronts are a focal point of intense precipitation and gustiness related to extratropical cyclones. In addition, sustained condensational heating along trailing cold fronts has been shown to raise background baroclinicity, which can trigger secondary cyclogenesis and, consequentially, cyclone clustering.To study the driving mechanism, synoptic-scale characteristics, and impacts of fronts throughout their lifecycles, we have developed a front tracking algorithm. A frontal lifecycle is therein defined as a 4-dimensional space-time volume of strong gradients in equivalent potential temperature that is coherent in both time and space.Based on the climatology of frontal lifecycles, we identify distinct frontogenesis regions in the mid-latitudes. Frontogenesis typically occurs in the lee of meridionally oriented mountain ranges, such as the Rocky Mountains or the Andes, or along western boundary currents, such as the Gulf Stream or the Kuroshio. Fronts forming in these regions travel eastward along the storm tracks over a lifetime of one to two weeks. Such lifecycle characteristics distinguish mid-latitude fronts from stationary or short-lived airmass boundaries in lower latitudes, which are typically classified as fronts by conventional algorithms.We furthermore associate characteristic dynamic drivers of frontogenesis in the identified frontogenesis regions to lifecycle properties such as duration, strength, and the occurrence of one or multiple secondary cyclogenesis. Thus, investigating how fronts link large-scale atmospheric conditions with downstream storm activity in the Storm Track regions.

Many of the most societally impactful weather events in Europe occur on short timescales and there is a growing demand for improved projections of how such extremes will change in the future. That is, how will global climate change over decades impact extreme weather over days? The multiscale nature of this question challenges the capabilities of current earth system models, and this is especially the case for hydrometeorological extremes. Accurately simulating the hazards posed by extreme precipitation requires faithfully resolving interactions between the large-scale circulation, synoptic dynamics, the local boundary-layer, and hydrological and land surface conditions. This is not only a quantitative modelling challenge, but a challenge of interpretation and narrative: the dynamics of extreme precipitation are diverse across space and time, and the statistics of the highest impact events are necessarily poorly constrained. These challenges are complicated further by the evergrowing size and hetereogeneity of multi-model datasets How can we explain model biases and trends in extreme precipitation? When models project similar changes in hydrometeorological risk do they do so for the same reasons? What implications do these factors have for regional downscaling and impact modelling? Can we relate future extremes quantitatively and robustly to historical high-impact events, as often requested by societal stakeholders? We tackle these questions through a novel flow-precursor framework, applied to observational data, large ensemble climate simulations and subseasonal weather forecasts. We decompose extreme event risk into contributions from different scales and flow conditions, using regionally specific synoptic flow precursors which are directly associated with individual high-impact extremes or classes of extreme. These precursors are algorithmically identified and can be easily computed in large datasets, allowing us to obtain a physical interpretation of changing extreme risk across Europe without obscuring regional or seasonal diversity in precipitation dynamics. We show how climate model biases and forced changes in extreme precipitation can be explained, categorised, and visualised in a succinct way that highlights important differences in their suitability for use in downscaling, impact modelling and storyline development. We demonstrate how dynamical decomposition can extract usable climate information even from heavily biased models, and how insights from models at different scales–such as from large climate ensembles and high-resolution weather forecasts–can be quantitatively synthesised to provide new insights on future hazards and plausible worst-case scenarios. Finally, we show how the method can be used to reframe complex, probabilistic climate projections and weather forecasts in terms of individual high impact historical events, aiding scenario visualisation, and allowing stakeholders to leverage their experience and domain knowledge when preparing for future high-impact extremes.

The release of latent heat on the warm side of trailing cold fronts can leave elevated levels of baroclinicity. This can lead to one or multiple secondary cyclones forming in the wake of the parent cyclone, intensifying moisture advection and latent heating. Although this mechanism has been demonstrated in case studies, we still lack a consistent global mapping of the evolution of fronts and associated diabatic processes. We develop a novel algorithm to both detect fronts in global weather and climate datasets and track them in time. We utilise a watershed algorithm to identify individual fronts as volumes in the four-dimensional domain of space and time. We apply this algorithm to equivalent potential-temperature fields from the ERA5 reanalysis on three pressure levels in the lower to middle troposphere to compile a global climatology of frontal lifecycles. We then categorise these lifecycles with respect to their characteristics as well as dynamic and thermodynamic properties. Furthermore, the intensification mechanisms are explored, in particular with respect to latent heating.

Precipitation has increased globally in the mean during the past century and is expected to continue to increase with rising temperatures. In the mid- to high latitudes, extratropical cyclones, fronts, atmospheric rivers, and cold air outbreaks are associated with a substantial fraction of the total precipitation. As these weather features might respond differently to a changing climate, investigating precipitation changes in the context of weather systems provides further insight into the observed changes in precipitation. Therefore, we introduce a new method for attributing precipitation to weather features. The method allows us to decompose total precipitation into the respective contributions by extratropical cyclones, fronts, atmospheric rivers, cold air outbreaks, and their combinations.We have classified precipitation between 1930-2010 in the ECMWF’s twentieth century reanalyses project, ERA-20C. Our method assigns 70% of the total precipitation poleward of 30° to the aforementioned categories, allowing us to assess the relative importance of these weather features for total precipitation and for precipitation extremes. We find that the combination of extratropical cyclones, fronts, and atmospheric rivers accounts for more than 50% of the total precipitation and for 90% of the extreme events in the northern hemisphere storm-track regions, despite these precipitation events occurring less than 20% of the time.