Ildikó Pieczka

Adapting to climate change is already essential in the near future, thus necessitating a good understanding of expected changes by relevant sectors. For instance, severe thunderstorms pose significant economic risks and threats to human life as well as to critical infrastructure, but their detailed analysis is still quite challenging. Recent advancements in climate models have improved spatial resolution, enabling explicit descriptions of thunderstorm formation and development. However, the number of such high-resolution simulations remains limited. To overcome the resolution limitations, several convective parameters (e.g. convective available potential energy, convective inhibition, bulk wind shear, lapse rate, precipitable water, thunderstorm intensity parameter) are commonly used in weather forecasts and hazard warnings to characterize hazardous weather conditions, but their application on a climate scale is hindered by substantial storage and computational demands.Within the CORDEX (Coordinated Regional Climate Downscaling Experiment) framework, model simulation results are available for the entire European region at a fine resolution of 10 km. The aim of our research is to create the climatology of convective parameters based on an ensemble of regional climate models (RCMs), which can be used to explore changes in convective hazards due to climate change over the century. The study starts with the ERA5 reanalysis, from which we determine whether any trend can be detected in the different European subregions. Also, the RCMs have to be validated for the past from the convective processes’ point of view. Then, the future changes and trends are calculated for the available scenarios until the end of the 21st century.Acknowledgements. This work has been implemented by the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014) project within the framework of Hungary's National Recovery and Resilience Plan supported by the Recovery and Resilience Facility of the European Union. We acknowledge the Digital Government Development and Project Management Ltd. for awarding us access to the Komondor HPC facility based in Hungary. In addition, this study has been supported by the European Climate Fund (G-2409-68866).

Although anthropogenic global warming is well-known within the scientific community, the public is still not certain or even misled on how to associate specific local climate events to this global issue. Therefore, it is essential to raise public awareness by providing sound, graphical, interesting, and easily understood scientific information. Our attribution project was initiated in September 2021, and aimed at this task for Hungary. For this purpose, seasonally relevant indicators were calculated and published in each season near the time of a corresponding event occurrence, and the dissemination was done via a national platform aiming for climate awareness (www.masfelfok.hu). In addition, the public is also reached through the republishment of various media platforms, and the social media networks are used as well.The following major issues/indicators were evaluated so far: snow frequency, cold winter anomalies, sleet, fog, vegetation start for cold-resistant and warm-demanding plants, late spring frosts and frost around blooming, heatwaves (using different thresholds), late summer-like conditions in autumn, grape stress factors, drought conditions (e.g. Forest Aridity Index, De Martonne Index, Pálfai Aridity Index, consecutive dry days), fire weather index, human comfort index (UTCI), heating and cooling degree days, precipitation extremes, etc.The analyses were performed using several data sources with at least daily temporal resolution: (1) an ensemble of CMIP6 global climate model simulations of both natural-only forcings and historical runs with around 1° resolution, (2) an ensemble of regional climate model simulations from EURO-CORDEX with 0.11° resolution, including the RCP2.6, RCP4.5, and RCP8.5 scenarios, (3) a fine-resolution (0.1°), homogenized observation-based gridded database (i.e. HuClim) for Hungary updated yearly, (4) a fine-resolution (0.1°), but not homogenized observation-based database (i.e. E-OBS) for Europe, (5) ECMWF Reanalysis data (ERA5 with 0.25° or ERA5-Land with 0.1° resolution) for those variables that are not available in the purely measurement-based HuClim.Acknowledgements. This work has been implemented by the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014) project within the framework of Hungary's National Recovery and Resilience Plan supported by the Recovery and Resilience Facility of the European Union. In addition, this activity has been supported by the European Climate Fund (G-2409-68866).

In this paper, we investigated Cold Air Outbreaks (CAOs) in Hungary using temperature data from ten weather stations located near populous Hungarian cities. Our main motivation for performing this research was the fact that in this rapidly changing climate, these events continue to represent a threat to infrastructure and human life, such as the outbreaks experienced in early 2021 (e.g., Texas, USA) and late 2022 (Winter Storm Elliott). In addition, no comprehensive study of CAOs in Hungary has been conducted using station data. The definition of CAO used in this paper is that the daily mean temperature had to be in the lower 10th percentile of the daily climatology for five consecutive days, and we allowed a maximum two-day gap between periods matching the criteria above, after which we merged events together. We found that the number of CAOs in Hungary decreased considerably in recent decades (due to increasing mean temperatures), and the climates of the investigated stations became increasingly homogenous. Developing our understanding of CAOs around the world is important because, due to climate change, their seasonal distribution may change in a way that negatively impacts our life and economy.

While climate models project that Greenland ice sheet (GrIS) melt will continue to accelerate with climate change, models exhibit limitations in capturing observed connections between GrIS melt and changes in high-latitude atmospheric circulation. Here we impose observed Arctic winds in a fully-coupled climate model with fixed anthropogenic forcing to quantify the influence of the rotational component of large-scale atmospheric circulation variability over the Arctic on the temperature field and the surface mass/energy balances through adiabatic processes. We show that recent changes involving mid-to-upper-tropospheric anticyclonic wind anomalies – linked with tropical forcing – explain half of the observed Greenland surface warming and ice loss acceleration since 1990, suggesting a pathway for large-scale winds to potentially enhance sea-level rise by ~0.2 mm/year per decade. We further reveal fingerprints of this observed teleconnection in paleo-reanalyses spanning the past 400 years, which heightens concern about model limitations to capture wind-driven adiabatic processes associated with GrIS melt.

The current study focuses on the RegCM4.5 model and specifically on a comparison of hydrostatic and non‐hydrostatic approaches as well as on different microphysical parameterisations and planetary boundary layer (PBL) schemes. The main goal of the paper is to simulate the historical regional precipitation characteristics of the Carpathian region as reliably as possible. For this purpose, seven different model experiments at a 10 km horizontal resolution were completed for a 10‐year period (1981–1990) using ERA‐Interim reanalysis data (with 0.75° resolution) as initial and boundary conditions. Our simulation matrix consists of hydrostatic and non‐hydrostatic runs together with different treatments of moisture, namely, the SUBEX and the NogTom schemes. In addition, two PBL schemes are tested, the Holtslag and the UW‐PBL scheme. In this detailed validation study, RegCM outputs (e.g., temperature, global radiation, cloud cover, precipitation) are compared to the homogenized, gridded CarpatClim data (available with 0.1° resolution) that are based on measurements at regular meteorological station sites. The validation considers seasonal and monthly means, as well as extreme climatic events. On the basis of the results we can conclude that the role of the non‐hydrostatic core can be clearly recognized for precipitation, particularly over mountains. Moreover, it was also found that the UW‐PBL scheme performs with a negative bias regarding atmospheric boundary layer thickness and temperature and it reduces the wet/dry biases of the Holtslag PBL scheme. Regarding microphysical schemes, the NogTom scheme performs better than the SUBEX scheme, but the modified SUBEX (SUB4.3) can also reduce the precipitation over mountainous areas.

The paper investigates the reference corpus of a climate change contrarian report. We categorized the journal abstracts according to the endorsement positions on anthropogenic climate change. These results were contrasted by an in-text citation analysis. We focused here on the role of the papers included by the report editors concerning the mainstream claims around climate change. Our results showed moderate differences in the endorsement rates as well as in the sources of contrarian arguments considering the contrarian report in general and the presented journals specifically. These outcomes indicate differences among the journals regarding editorial practice, topic-dependency, and the home field advantage of some authors. Beyond the bibliometric data, our additional rhetorical analysis showed that language and wording are at least as important as the references backing the claims. The well-founded atmosphere of doubt in the climate skeptic report relies on two prevalent factors working together: relevant information accumulated on methodological uncertainties and findings that do not support mainstream knowledge claims (1); and solemn rhetoric supplemented with proper re-contextualization and reinterpretation (2).

In order to satisfy the continuous urging demands for updated and relevant information from various impact researchers, end-users, and decision makers, the RegCM4.3 model is used taking into account the new RCP4.5 and RCP8.5 radiative forcing scenarios to provide climate projection for Hungary with 10 km horizontal resolution. Overall, the results suggest significant warming in Hungary. The greatest temperature increase is likely to occur in summer, which is why the projected changes in warm extremes are also analysed in this study.