Tropical cyclones are prone to cause fatalities and damages reaching far into billions of US Dollars. There is evidence that these events could intensify under ongoing global warming, and accordingly disaster prevention and adaptation strategies are necessary. We apply Pseudo-Global Warming (PGW) as a computational cost-efficient alternative to conventional long-term modeling, enabling the assessment of historical events under future storylines. Not many studies specifically assess the sensitivity of PGW in the context of short-term extreme events in the United States. In an attempt to close this gap, this study explores the sensitivity of hurricane intensity to different PGW configurations, including a purely thermodynamic, a dynamic, and a more comprehensive modulation of initial and boundary conditions using the Weather and Research and Forecasting Model (WRF). The climate perturbations are calculated using two individual CMIP6 climate models with a relatively low and high temperature change and the CMIP6 ensemble mean, all under SSP5-8.5. WRF was set up in a two-way nesting framework using domains of 25 and 5 km spatial resolution. Results show that high uncertainties exist between the thermodynamic and dynamic approaches, whereas the deviations between the dynamic approach and the comprehensive variable modulation are low. Hurricanes modeled under the thermodynamic approach tend toward higher intensities, whereas the perturbation of wind under the dynamic approach may impose unwanted effects on cyclogenesis, for example due to increased vertical wind shear. The highest sensitivity, however, stems from the selected CMIP6 model. We conclude that PGW studies should thoroughly assess uncertainties imposed by the PGW scheme, similar to those imposed by model parameterizations. All simulation results suggest an increase in maximum wind speeds and precipitation for the high impact model and the ensemble mean. An unfolding of the inspected events in a warmer world could therefore exacerbate the impacts on nature and society.

The Mediterranean Basin is one of the regions most affected by climate change, which poses significant challenges to agricultural efficiency and food security. While rising temperatures and decreasing precipitation levels already impose great risks, the effects of compound extreme events (CEEs) can be significantly more severe and amplify the risk. It is therefore of high importance to assess these risks under climate change on a regional level to implement efficient adaption strategies. This study focuses on false-spring events (FSEs), which impose a high risk of crop losses during the beginning of the vegetation growing period, as well as heat–drought compound events (HDCEs) in summer, for a high-impact future scenario (Representative Concentration Pathway (RCP) 8.5). The results for 2070–2099 are compared to 1970–1999. In addition, deviations of the near-surface atmospheric state under FSEs and HDCEs are investigated to improve the predictability of these events. We apply a multivariate, trend-conserving bias correction method (MBCn) accounting for temporal coherency between the inspected variables derived from the European branch of the Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX). This method proves to be a suitable choice for the assessment of percentile-threshold-based CEEs. The results show a potential increase in frequency of FSEs for large portions of the study domain, especially impacting later stages of the warming period, caused by disproportionate changes in the behavior of warm phases and frost events. Frost events causing FSEs predominantly occur under high-pressure conditions and northerly to easterly wind flow. HDCEs are projected to significantly increase in frequency, intensity, and duration, mostly driven by dry, continental air masses. This intensification is several times higher than that of the univariate components. This study improves our understanding of the unfolding of climate change in the Mediterranean and shows the need for further, locally refined investigations and adaptation strategies.

While many authors have described the adverse health effects of poor air quality and meteorological extremes, there remain inconsistencies on a regional scale as well as uncertainty about the single and joint effects of atmospheric predictors. In this context, we investigated the short-term impacts of weather and air quality on moderate extreme cancer-related mortality events for the urban area of Augsburg, Southern Germany, during the period 2000–2017. First, single effects were uncovered by applying a case-crossover routine. The overall impact was assessed by performing a Mann–Whitney U testing scheme. We then compared the results of this procedure to extreme noncancer-related mortality events. In a second step, we found periods with contemporaneous significant predictors and carried out an in-depth analysis of these joint-effect periods. We were interested in the atmospheric processes leading to the emergence of significant conditions. Hence, we applied the Principal Component Analysis to large-scale synoptic conditions during these periods. The results demonstrate a strong linkage between high-mortality events in cancer patients and significantly above-average levels of nitrogen dioxide (NO₂) and particulate matter (PM_2.5) during the late winter through spring period. These were mainly linked to northerly to easterly weak airflow under stable, high-pressure conditions. Especially in winter and spring, this can result in low temperatures and a ground-level increase and the accumulation of air pollution from heating and traffic as well as eastern lateral advection of polluted air. Additionally, above-average temperatures were shown to occur on the days before mortality events from mid-summer through fall, which was also caused by high-pressure conditions with weak wind flow and intense solar radiation. Our approach can be used to analyse medical data with epidemiological as well as climatological methods while providing a more vivid representation of the underlying atmospheric processes.

The Mediterranean Basin is one of the regions most affected by climate change. It is highly dependent on the impact of climate change on agricultural efficiency and food security. While rising temperatures and decreasing precipitation levels already impose great risks, the effects of compounding extreme events (CEEs) can be significantly more severe and amplify the risk. It is therefore of high importance to assess these risks under climate change on a regional level to implement efficient adaption strategies. This study focuses on False Spring Events (FSEs), which impose a high risk of crop losses during the beginning of the vegetation growing period, as well as Heat and Drought-based CEEs (HDCEs) in summer, for a high-impact future scenario (RCP8.5). The results for 2070–2099 are compared to 1970–1999. In addition, deviations of the near-surface atmospheric state under FSEs and HDCEs are investigated with the aim to improve the predictability of these events. We apply a multivariate, trend-conserving bias correction method (MBCn) accounting for temporal coherency between the inspected variables derived from EUR-CORDEX. This method proves to be a suitable choice for the assessment of percentile threshold-based CEEs. The results show a potential increase in frequency of FSEs for large portions of the study domain, especially impacting later stages of the warming period, caused by disproportionate changes in the behavior of warm phases and frost events. Frost events causing FSEs predominantly occur under high-pressure conditions and northerly to easterly wind flow. HDCEs are projected to significantly increase in frequency, intensity, and duration, mostly driven by dry, continental air masses. This intensification is multiple times higher than that of the univariate components. This study improves the understanding of the unfolding of climate change in the Mediterranean and shows the need for further, locally refined, investigations and adaptation strategies.

During the Pacific typhoon season of 2023, the Pearl River Delta (PRD) was hit by a series of typhoons, causing unprecedented precipitation as well as fatalities and significant damages. There are indications that these events may intensify under climate change. However, the unfolding of similar events in the future is yet to be fully understood. We therefore conducted an investigation of historical typhoon events affecting the PRD using Pseudo-Global Warming. Within this framework, we perturbed the historical initial and boundary conditions obtained from ERA5 reanalysis and handed to the regional model WRF according to the climate change signal projected by the CMIP6 ensemble under SSP5-8.5. We pursued a storyline-based approach, in which each of the 16 selected CMIP6 models acted as the basis for an individual storyline of future typhoon intensity. Additionally, we created two storylines based on thermodynamic drivers to create scenarios with excessively favorable and unfavorable conditions for typhoon intensification, resulting in 18 storylines that were assessed for seven representative typhoons. WRF was set up in a two-way nesting framework using domains of 25 km and 5 km resolution, of which the latter was used for further assessment. For each typhoon, the simulations were initiated at the start of the first intensification phase and statistically assessed until landfall. Minimum sea level pressure, maximum wind speed, mean and maximum 1-hourly precipitation rates as well as the integrated kinetic energy (IKE) as an advanced measure for typhoon damage potential were used to determine typhoon intensity. Results indicate a general increase in typhoon intensity across all metrics for six of the seven inspected typhoons. This increase is notably higher for specific storylines, and the projected increase in the extreme values of the inspected metrics significantly exceed the median change of all storylines. This indicates that the true potential range may lie above what would be expected under a median approach. The results suggest a maximum decrease of up to 15 hPa for minimum central pressure, 11 m s^-1 increase for maximum wind speed, 2.5 mm h^-1 for mean and 50 mm h^-1 for maximum precipitation rates. The two additional storylines revealed an even higher intensity increase in the form of central minimum pressure decreases and wind maxima increases for two typhoons, but mostly resembled the span provided by the 16 GCM-based storylines. These results can support the optimization of the development of protective measures considering the improved range of intensity potential.