The aim of this session will be studies that bridge the spatial scales and reach the timescales of extreme events that impact all our lives. Papers are solicited on advancing the understanding of causes of observed changes in mean climate, in its variability and in the frequency and intensity of extreme events. In particular, papers are invited on trends in the regional climate of Europe, not just the mean, but variability and extremes, often for the latter measured through well-chosen indices.
Climate change is a global challenge with manifold and widespread consequences, including the intensification and increased frequency of numerous extreme weather phenomena. In response to this pressing issue, we introduce ClimaMeter, a platform designed to assess and contextualize extreme weather phenomena in relation to climate change. The platform provides near-real-time information on the dynamics of extreme events, serving as a resource for researchers, policymakers, and acting as a scientific outreach tool for the general public. ClimaMeter currently analyzes heatwaves, cold spells, heavy precipitation, and windstorms.Our methodology is based on looking for weather conditions similar to those that caused the extreme event of interest with physics-informed machine-learning methodologies. We focus on the satellite era, namely the period since 1979, when widespread observations of climate variables from satellites have become available. The object studied (i.e. "the event") is asurface-pressure pattern over a certain region and averaged over a certain number of days, that has lead to a extreme weather conditions. We split the dataset 1979-Present in two parts of equal length and consider the first half of the satellite era as "past" and the second part as "present" separately. We use data from MSWX. We then compare how the selected weather conditions have changed between the two periods, and whether such changes are likely due to natural climate variability or anthropogenic climate change.
This presentation sheds light on the methodology, data sources, and analytical techniques that ClimaMeter relies on, offering a comprehensive overview of its scientific foundations. To illustrate ClimaMeter, we present some examples of recent extreme weather events. Additionally, we highlight the role of ClimaMeter in promoting a profound understanding of the complex interactions between climate change and extreme weather phenomena, with the hope of ultimately contributing to informed decision-making and climate resilience. Follow us on X @ClimaMeter and visit www.climameter.org.
How to cite: Faranda, D. and the The ClimaMeter team: ClimateMeter: Putting Extreme Weather Phenomena in Climate Perspective , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-126, https://doi.org/10.5194/ems2024-126, 2024.
We create Intensity-Duration-Frequency (IDF) curves which describe the major statistical characteristics of extreme precipitation events (return level, return period, time scale) and are capable of considering large-scale influences. They provide information on the probability of exceedance of certain precipitation intensities for a range of durations from minutes to days and can help to visualize either how extreme (in terms of probability/frequency/return period) a specific event is or which intensity is expected for a given probability. We modeled the underlying distribution of block maxima with the Generalized Extreme Value (GEV) distribution. Maxima from different durations are used and enable a model that can evaluate different time scales. All durations are modeled in one single model in order to prevent quantile-crossing and to assure that estimated quantiles are consistent.
The influence of climate change is included by letting the GEV parameters (covariates) depend on the variables NAO, temperature, humidity, blocking and year (as a proxy for climate change). We found an increase in probability of extreme precipitation with year and temperature, while the effect of the other variables depends on the season. This corresponds to the aim of the session UP3.1, to answer whether there have been significant changes in frequency or amplitude of extreme events. Since it is easier to project average values than to project extremes, we use the modeled relations between average large-scale covariates and extreme precipitation to create future IDF-relations based on climate projections and the projected average large-scale values. This poses some challenges because the polynomial dependencies of the past might not hold for an extrapolation into the future. Furthermore, we plan to add a spatial component to the model that enables the usage of data from several neighboring stations in one model and interpolate to ungauged sites. This will be the basis for investigating how gridded data sets can be used to complement the station-based approach. One focus will lie on the dependence between neighboring grid points.
How to cite: Fauer, F. S. and Rust, H. W.: Extreme precipitation in the past and future, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-87, https://doi.org/10.5194/ems2024-87, 2024.
According to climate and socioeconomic projections, a global development based on high-emission scenarios is likely to see a progressive increase in magnitude of climate extremes, resulting in large impacts who can lead to devastating impacts and hinder the stability of ecosystems. To minimize the risk of such events, the Paris Agreement recommended pursuing the strongest efforts to keep the global temperature increase – compared to pre-industrial level – to 1.5°C or, at least, well below 2°C. Considering the global temperature tendency of the last decades, it is likely that the World would exceed the 1.5°C threshold, and so the efforts to limit the temperature increase, and possibly revert it, fit into the 1.5°C (or 2°C) overshoot pathways. However, if the World will follow low-emission scenarios, will such overshoot trajectory prevent us from unprecedented climate extremes or are we unavoidably bound to experience new record-breaking events? To answer this question, we used the bias-adjusted multi-model ISIMIP3b data, we constructed a dataset of 12 hazards (including heat and cold waves, droughts, precipitation extremes, fire danger, snowfall, and compound events), and we evaluated – for each hazard – whether, where, and when the most severe event recorded in the past is likely to be exceeded in the future. The results are presented at grid point scale (0.5°) and separately for the SSP1-1.9 and SSP1-2.6 scenarios. To expand the analyses, we coupled the integrated assessment model WITCH with a climate emulator to create multiple overshoot curves (still at 1.5°C, but with different timing and duration), and we again estimated the possible occurrence of such unprecedented events. In this presentation, we also discussed the population and land-use shares exposed to such events, depending on the scenario and the shape of the temperature overshoot.
How to cite: Spinoni, J., Chiani, L., Dosio, A., Ghirri, J., Mastropietro, M., Rodriguez-Pardo, C., and Tavoni, M.: Are unprecedented climate extremes unavoidable with temperature overshoot pathways?, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-546, https://doi.org/10.5194/ems2024-546, 2024.
Both extremely low and high temperatures can be relevant for the operation of nuclear power plants (NPPs). For example, temperatures higher than 40 °C might endanger safe shutdown of an NPP (STUK, 2011). The MAWECLI project aims to provide reliable estimates about the likelihood of extreme events affecting NPPs in the changing climate of Finland.
In this study, we evaluate the annual probabilities of low and high temperature extremes in the past and future climate of Finland. To produce estimates for events with low annual probabilities (2%, 1%, 0.2%, and 0.1%), we utilise statistical extreme value analysis, employing both the generalized extreme value distribution with block maxima approach and the generalized Pareto distribution with peak-over-threshold approach. Furthermore, any potential non-stationarity in the time series is addressed by utilising distribution parameter covariates based on linear trends identified from the time series.
For the past, the extreme value analysis is performed for 35 weather stations across Finland. The analysis is based on a 60-year period of observations (1963-2022), which is common for all stations, as well as longer station-specific historic records, starting from 1844 for the longest operational weather station. In addition to instantaneous extreme temperatures, estimates are also calculated for high (or low) temperatures that have prevailed for time periods of six and 24 hours.
For the future projections, bias-corrected daily mean temperature data from 25 CMIP6 global climate models (GCM) is utilised (Ruosteenoja and Jylhä, 2023). To produce extensive data sets for 20-year periods representing current (1999-2018) and mid-century (2041-2060) climatic conditions, 20-year time series of each climate model were combined to create a 500-year ensemble depicting the climatic conditions of each period. The use of this 500-year ensemble enables more robust estimates in comparison to extreme value analysis relying on only 20-year data periods for each individual GCM. Our results show higher warming for extremes compared to changes in mean temperatures, the difference increasing towards smaller annual probabilities, i.e., more rare events.
References:
Ruosteenoja, K., Jylhä, K. Average and extreme heatwaves in Europe at 0.5–2.0 °C global warming levels in CMIP6 model simulations. Clim Dyn 61, 4259–4281 (2023). https://doi.org/10.1007/s00382-023-06798-4
STUK, 2011. European Stress Tests for Nuclear Power Plants. National Report. Finland 3/0600/2011 2011 Tomi Routamo (ed.) Radiation and Nuclear Safety Authority 2011. Available at: https://www.ensreg.eu/sites/default/files/EU_Stress_Tests_-_National_Report_-_Finland.pdf
How to cite: Laapas, M., Jylhä, K., and Ruosteenoja, K.: Annual probabilities of extreme air temperatures in the past and future climate of Finland, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-706, https://doi.org/10.5194/ems2024-706, 2024.
This paper aims to evaluate the precipitation extremes over Northwest of Iran based on 5th generation reanalysis precipitation data (ERA5) for long-term historical period from 1941 to 2020. The trend of 10 selected extremes precipitation indices (EPI) were evaluated in monthly, seasonal, annual and decadal time scales. The nonparametric Mann–Kendall test were applied to 960 grid (600,000 km2) with a high spatial resolution of 0.25° × 0.25° to detect the possible temporal trends in all EPI on the significance levels of 1% and 5%, include frequency and intensity indices. Notably, anomalies in precipitation for the recent reference period (1991-2020) compared to a different subperiods (e.g. 1961-1990 and 1941-2020) seeking to distinguish shifts in precipitation patterns.
Our findings have uncovered a significant increase in the frequency of daily heavy precipitation events over the studied period, particularly in the latter decades. Trends showing mostly positive patterns, many of which are statistically significant. Moreover, in some areas over the past 30 years, the total rainfall has increased by approximately 25%. Although most events occur during the winter (DJF) and spring (MAM) seasons, the highest number of events belongs to March. The largest positive trend in terms of intensity and frequency is associated with the fall season (SON) and the month of October and November in this region. Also the highest number of grid points with significant positive trends is related to fall in seasonal timescale and November in monthly timescale. Although the results of the annual study indicate that 56.5% of the respected territory have a positive trend which statistically significant in at least one of the indices, this percentage increases to 80.3% on a seasonal scale for (SON). In some cases, negative trends were observed for few number of grids, none of which were statistically significant in annual scale. Also, periodic behavior observed, characterized by oscillations spanning on interdecadal scales.
Overall, the combination of the results of the EPI trends, illustrate a considerable changes towards more intense and more frequent precipitation on interannual scales. Consequently, this region can be considered as a high risk area in terms of extreme events and flash floods.
How to cite: Fakour, P. and Ustrnul, Z.: Long-Term Trends in Extreme Precipitation Events in Northwest Iran: A Comprehensive Analysis Using ERA5 Reanalysis Data , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-479, https://doi.org/10.5194/ems2024-479, 2024.
The recent increase in extreme and intense rainfall events is a pressing concern, mainly due to the effects of climate change. These heavy downpours contribute significantly to urban damage, triggering floods, landslides and other related disasters. Such natural disasters pose serious risks to human life and infrastructure. Seoul, South Korea, is particularly vulnerable. In 2001, for example, the city recorded a staggering 273 mm of rainfall in a single day. More recently, in 2011 and again in 2022, Seoul suffered extensive urban flooding. These events were largely due to the inability of rivers and stormwater systems to handle the sudden deluge, which exceeded the design frequencies that these infrastructures were originally built to withstand. As climate change accelerates, the frequency of such extreme weather events is expected to increase, requiring advanced research to fully understand their impact on urban infrastructure. This includes vital structures such as dams, embankments and stormwater pipes, all of which require robust designs to cope with such unprecedented environmental stress. This study focuses on collecting and analysing rainfall data from meteorological stations across Korea. By using the Generalised Extreme Value (GEV) distribution along with time series analysis, our research aims to meticulously map flood risk patterns. These statistical methods are crucial for understanding and predicting the behaviour of rare but severe weather phenomena. In addition, our research calculates flood loads based on specific return periods and design frequencies. These calculations are essential for designing infrastructure that can withstand future climatic challenges, thereby ensuring the safety and resilience of urban environments against the increasing threat of flooding. This comprehensive approach not only highlights historically flood-rich or flood-poor periods, but also assists in the strategic planning and upgrading of urban infrastructure to cope with the realities of climate change.
Acknowledgement
This research was supported by a (2022-MOIS63-002(RS-2022-ND641012)) of Cooperative Research Method and Safety Management Technology in National Disaster funded by Ministry of Interior and Safety(MOIS, Korea).
How to cite: Choi, S., Choo, K., and Kim, B.: Evaluation of Flood Risk in South Korea Through Time Series Analysis of Precipitation Data, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-628, https://doi.org/10.5194/ems2024-628, 2024.
The Alpine area is one of the most vulnerable and sensitive regions to the continuous warming of climate and it is considered an important hotspot of climate change. In particular, climate change is expected to exert a strong influence on all components of the hydrological cycle, including river regimes, with consequent effects on the services offered by the freshwater ecosystem, as well as on water availability for users, thus affecting several socio-economic sectors. Climate change assessment in the Alpine region relies on direct application of climate observations and, thus, their quality may strongly impact climate and hydrological studies results and predictions in terms of reliability, accuracy and precision. Here, we present an extended climatological-trend analysis focused on the Alpine region over the 1961-2020 period. The potential of a recently developed and unprecedented observational dataset, addressing the key issues in terms of spatial density, data quality, time resolution and completeness, was exploited. About 300 time series of air temperature and 1000 of precipitation, covering homogeneously the extent and the elevation gradient of this area, were selected depending on World Meteorological Organization (WMO) requirements. Climatological and trend analysis was carried out on different time scales considering both mean values and a selection of ETCCDI indices. The phenomena of elevation-dependent warming (EDW) and precipitation change (EDPC) were also assessed. A pca-based clustering approach was applied to identify climatic regions and evaluate the spatial-dependency of trends. A further analysis concerned the relationship between detrended time series and the main teleconnection patterns. The present study aims to provide a reliable analysis of the evolution of key climate variables in the Alpine region. Being a study based on the most comprehensive spatial coverage in this area to date, the related results significantly increase the amount of information available to involved stakeholders to prevent and quickly plan for disaster management, risk mitigation and formulating proper locally relevant adaptation strategies.
How to cite: Bongiovanni, G., Matiu, M., Crespi, A., Napoli, A., Majone, B., and Zardi, D.: Climate-trend analysis of air temperature and precipitation in the Extended Alpine Region (1961-2020), EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-385, https://doi.org/10.5194/ems2024-385, 2024.
Mountainous regions present a distinct vulnerability to climate change, serving as valuable barometers for tracking these shifts. Studies conducted across various global locales reveal a recent uptick in temperatures within mountainous terrains, notably evident since the 1980s, with variations in intensity across specific altitude bands. While temperature rises are not consistently accompanied by notable trends in annual precipitation totals, they do prompt alterations in the annual precipitation patterns and types, thereby impacting the frequency and duration of snow cover.
Since snow cover plays a pivotal role in the Earth's systems, influencing hydrology, climate, and ecological environments, any alterations in snowpack patterns will yield multifaceted effects. This study aims to investigate the variability of snow cover metrics, including snow depth, duration, persistence, and extent.
The study focused on mountainous regions in Central Europe, defined as areas with elevations exceeding 500 meters above sea level within the domain of 10°E - 25°E longitude and 47°N - 55°N latitude. Data analysis spanned from 1961 to 2023 and drew upon various meteorological sources, including on-site snow depth measurements and regional ERA5-Land reanalysis. To better capture the details of complex terrain, a new gridded dataset was generated by integrating measurements with reanalysis data at a spatial resolution of 0.5 kilometers.
The primary findings underscore the significant influence of ongoing climate change on snow cover characteristics, with the intensity of this impact varying based on geographical and terrain factors such as altitude, landform, slope, and aspect. However, a consistent multiannual decrease in snowpack persistence was observed across the entire research area.
A comprehensive understanding of the timing of snow accumulation and ablation is essential, as it governs springtime mountain runoff rates, water infiltration, groundwater storage, and transpiration rates—all critical components of the hydrological cycle.
How to cite: Wypych, A., Ustrnul, Z., and Sałaja, J.: Variability and changes of snow cover in Central European mountains , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-929, https://doi.org/10.5194/ems2024-929, 2024.
Six gridded datasets of mean, minimum and maximum temperatures and one dataset of 22 individual sites distributed over mainland Spain and the Balearic Islands are compared. The gridded datasets vary in spatial resolution, temporal coverage and interpolation procedures as well as in the number of individual predictor sites used to create them. The six gridded datasets start in 1901 (1951) in the longest (shortest) case and extend until present or some date within the last decade. The spatial resolution ranges from 0.11◦ to 1 km. The site-resolved dataset includes the 22 longest data records over Spain, reaching back until the mid-19th century and thus complementing the temporal analysis of this study. The availability of datasets with different levels of predictor data, methodologies and final characteristics allows for an assessment of the observational uncertainties in temperature climatologies and trends at the local/regional scales.
The structure of the spatial patterns for the climatologies of the mean, minimum and maximum temperatures is quite consistent across datasets, with the coldest temperatures over areas of the Pyrenees and mountain ranges in winter and the hottest ones over the Guadalquivir Valley in summer. However, notable differences are observed at a regional scale, particularly over the highest elevation regions where average discrepancies greater than 3 ◦C are found. Mean temperatures increase since 1970s between 1-2 ◦C, and uncertainties range from 0.2 to 0.5 ◦C across datasets. The spatial distribution of trends shows that warming is widespread but there are notable differences in magnitude, spatial distribution and even sign of the trends depending on the database considered. The relevant variability estimated among datasets leads to a low confidence on where the warming peaks annually and seasonally. A Principal Component Analysis is used to filter out signals that account for low amounts of regional variance and focus on those responsible for the long term responses. The first principal component reproduces the trends in each dataset and season, and is consistent with the forced response to external forcing found at global and hemispherical scales. This PC accounts for a large percentage of variance in each dataset and season. The corresponding spatial patter has uniform sign and its regional variability varies considerably across datasets with differences being larger in scale than the resolution of the datasets. The results can be relevant for model evaluation and detection and attribution studies over this region.
How to cite: Garrido, J. L., González-Rouco, J. F., Brunet, M., Sigró, J., Herrera, S., Chazarra-Bernabé, A., Serrano-Notivoli, R., Beguería, S., González-Hidalgo, J. C., Peña-Angulo, D., Rodríguez-Camino, E., Rodríguez-Guisado, E., Peral, C., García, M., and García-Bustamante, E.: Temperature trends and uncertainties over peninsular Spain and the Balearic Islands, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-996, https://doi.org/10.5194/ems2024-996, 2024.
Pan-European summer drought of 2022 affected different sectors as agriculture, energy, ecosystems, and population health, with both large-scale and local remarkable impacts. In the last decades, similar extreme droughts hit Europe, to the point that in some areas as the Mediterranean Region such events are becoming the new normal. This study moves from two questions: can we find comparable events as we move back in time? Has Europe ever experienced a period with more frequent and/or severe droughts? To provide the answers, we constructed a new database of meteorological drought events from 1921 to 2014. As input, we used the E-OBS gridded daily precipitation and temperature data, we computed the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) at multiple accumulation scales, and we set a multi-parameter system (including duration, severity, intensity, extent, and peak) to assign a 0-100 score to droughts at country scale. The single events are therefore classified into five big categories to provide decadal statistics and investigate the trends of mega-droughts over the last one hundred years. For the events occurred after 1950, we also estimated population and land-use exposure. According to our analyses, no other summer drought in 1921-2023 exceeded that of 2022, confirming its exceptional features, in particular regarding intensity and extent. Our findings show that - in the last two decades - the meteorological drought severity actually increased through most of Europe, if compared with the second half of the 20th century. However, they also show that Europe already experienced a period of comparable drought hazard from the late 1930s to the late 1940s, including long multi-country droughts never recorded again. Being aware that high-quality climatic data are sparser as we go backwards in time, the results presented here suggest that recent extreme droughts might not be record-breaking – in particular regarding duration - if we extend the analyses to a hundred years ago.
How to cite: Spinoni, J., Cammalleri, C., Chiani, L., Dosio, A., Ghirri, J., Mastropietro, M., Toreti, A., and Tavoni, M.: Record-breaking European meteorological droughts in 1921-2024, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-537, https://doi.org/10.5194/ems2024-537, 2024.
Drought is a defining feature of the Mediterranean climate, characterized by frequent periods of precipitation significantly below average. However, the ongoing drought episode affecting Catalonia shows a severity never recorded in the instrumental period 1915-2023. In the case of the city of Barcelona, where precipitation data stretches back to 1786, one must go back to the early 19th century to find a similar 3-year drought period.
Observing the trend of drought episodes over last few decades, the current drought is the latest in a series of episodes of shorter duration and intensity, but which can be also locally classified as exceptional at the time of their occurrence. Consequently, some areas of North-eastern Catalonia have endured conditions similar to semi-permanent drought over the past decade, or even beyond.
The current drought in Catalonia is not an isolated event but part of a broader regional pattern. In general, the entire South-western Europe and Northern Africa have been under drought conditions to a greater or lesser extent in recent years (Faranda et al, 2023). Moreover, other Mediterranean climate regions across the globe, such as Central Chile and California, have lately witnessed record-breaking droughts during the instrumental period, some being classified as Megadroughts (Garreaud et al., 2020; Williams et al., 2022).
More recently, some authors (Cook et al, 2022) have further explored the concept of Megadrought. These episodes have common characteristics beyond their impacts that justify this qualification, including remarkable temporal persistence, unprecedented nature compared with previous events, links with external climatic forcings, or their connection with SST anomalies.
Currently, the global climate system is strongly forced by the increase in CO2 concentrations in the atmosphere. Climate projections point to a reduction in precipitation for the Mediterranean climate area, which, combined with the increase in temperature values, will lead to greater aridity and the occurrence of droughts with a magnitude never recorded before. In light of these projections and the characteristics exhibited by the current Catalan drought, the question arises: Is Catalonia facing a Megadrought episode?
REFERENCES
Cook, B.I., Smerdon, J.E., Cook, E.R. et al. Megadroughts in the Common Era and the Anthropocene. Nat Rev Earth Environ 3, 741–757 (2022).
Faranda D., Pascale S., Bulut B. Persistent anticyclonic conditions and climate change exacerbated the exceptional 2022 European-Mediterranean drought. Environ. Res. Lett. 18, 034030 (2023)
Garreaud RD, Boisier JP, Rondanelli R, Montecinos A, Sepúlveda HH, Veloso-Aguila D. The Central Chile Mega Drought (2010–2018): A climate dynamics perspective. Int J Climatol. 2020; 40: 421–439.
Williams, A.P., Cook, B.I. & Smerdon, J.E. Rapid intensification of the emerging southwestern North American megadrought in 2020–2021. Nat. Clim. Chang. 12, 232–234 (2022).
How to cite: Altava-Ortiz, V., Barnolas, M., Barrera-Escoda, A., Assimenidis, S., Cortès, M., Prohom, M. J., Moré, J., and Martín-Vide, J.: Is Catalonia facing a Megadrought episode?, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-783, https://doi.org/10.5194/ems2024-783, 2024.
Droughts at the global scale can be described by many variables, expressing their extent, duration, dynamics and severity. To identify common features in global land drought events (GLDEs) based on soil moisture, we present a robust method for their identification and classification (cataloging). Gridded estimates of root-zone soil moisture from the SoilClim model and the mesoscale Hydrologic Model (mHM) were calculated over global land from 1980–2023. Using the 10th and 20th percentile thresholds of soil moisture anomalies, outputs of the two models were merged into a united dataset of drought affected areas in a 10-day step. OPTICS clustering of the gridded data was then used to identify a total of 736 GLDEs. By utilizing four spatiotemporal and three motion-related characteristics for each GLDE, we established threshold percentiles based on their distributions. This information enabled us to categorize droughts into seven severity categories (ranging from extremely weak to extremely severe) and seven dynamic categories (ranging from extremely static to extremely dynamic). The severity and dynamic categories overlapped substantially for extremely severe and extremely dynamic droughts but very little for less severe/dynamic categories, despite some very small droughts that have occasionally been very dynamic. The frequency of GLDEs has generally increased in recent decades across different drought categories but is statistically significant only in some cases. Overall, the cataloging of GLDEs presents a unique opportunity to analyze the evolving features of spatiotemporally connected drought events in recent decades and provides a basis for future investigations of the drivers and impacts of dynamically evolving drought events.
How to cite: Řehoř, J., Brázdil, R., Rakovec, O., Hanel, M., Fischer, M., Kumar, R., Balek, J., and Trnka, M.: Cataloguing global soil moisture droughts since 1980, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-437, https://doi.org/10.5194/ems2024-437, 2024.
The study of the precipitation regime aims to verify the hypothesis about the decrease of rainfall in Spain. Is the climate of peninsular Spain and the Balearic Islands moving towards a drier and drier climate?
In principle, global warming (GW), at the planetary level, represents an increase in precipitation. The progressive increase in temperature causes greater evaporation, and therefore greater humidity in the atmosphere, which should produce increasing precipitation. However, this trend is not occurring homogeneously. The various scenarios developed by the IPCC suggest that in Mediterranean latitudes the GW generates a tendency towards greater drought.
One of the objectives of this work is to analyze whether, in Spain, there is a temporal evolution of the precipitation regime towards less precipitation, as well as to study the relationship between annual precipitation and the trend towards progressive warming. Specifically, to verify the hypothesis that the increase in temperature resulting from the GW process implies a trend towards progressive drought.
Two different databases are used in this work: on the one hand, the information provided by AEMET from a selection of meteorological stations throughout Spain, with the daily series of precipitation (rr) and maximum (tx) and minimum (tn) temperatures, from January 1, 1971 to December 31, 2023; on the other hand, information from the Copernicus climate service. Specifically, the one resulting from E-OBS, from January 1, 1950 to December 31, 2022 with a resolution of 0.25 degrees.
In addition to multiple regression, the techniques used are the Mann-Kendall test and the Kendall-Theil-Sen regression.
The Mann-Kendall test confirms the statistical significance of the relationship between rr and tx, with a statistical reliability close to 99.9%. The KTS regression predicts a reduction of 38.49 mm for each 1°C increase.
If the warming trend experienced in recent years (1973-2022) continues, it is foreseeable that by 2050 there will be a reduction in precipitation in Spain of between 14% and 20% with respect to current precipitation (understood as the average between 2000 and 2022). Spain's climate is likely to vary from a Mediterranean climate to a warm steppe climate in the Köppen classification system.
How to cite: Roca, J., Arellano, B., and Zheng, Q.: Spain: towards a drier and warmer climate?, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-932, https://doi.org/10.5194/ems2024-932, 2024.
The aim of this study is to present the spatial and temporal variability of the frequency of dry and wet days and dry and wet spells against the background of changes in precipitation and atmospheric circulation. The study is based on daily precipitation totals from 46 meteorological stations in Poland for the years 1966-2023. Additionally seven circulation indices were used: GBI, NAO, AO, EA, EA/WR. SCAND ana AMO. Dry days are defined as days without precipitation. Wet days are days with at least 1 mm of precipitation. It was shown that dry spells are much more common that wet spells, are longer and cover larger areas. Long term changes in annual characteristics of dry and wet days and spells are statistically insignificant. Only the length of the longest dry spell in the year increases. However, there are significant changes in their annual cycles. Spring is drier, especially April in summer months, precipitation decreases in the south and increases in the north, the same concerns dry day frequencies, November and December, symbols of gloomy rainy weather, are increasingly drier, rainy weather moved to January and February. Preliminary analysis of the impact of atmospheric circulation on the occurrence of dry and wet spells indicates high seasonal variability. In cold season, the Scandinavian type has the greatest influence, the presence of high pressure system over Scandinavia favors dry weather. In summer, precipitation and dry and wet spell occurrence are influenced by the NAO, AO, type EA and presence of high pressure system over Greenland. In spring and autumn, EA/WR type influences can be noticed.
This research was funded by National Science Center (NCN), grant number 2019/33/B/ST10/01136
How to cite: Wibig, J.: Dry and wet spells variability in Poland in the period 1966-2023, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-552, https://doi.org/10.5194/ems2024-552, 2024.
The Amazon rainforest is one of the most ecologically diverse and important ecosystems on Earth and plays a fundamental role in regulating the global climate. Extreme weather events, such as droughts, heatwaves, and floods, can lead to various consequences such as increased soil erosion, altered water availability, and changes in vegetation dynamics, which can affect the Amazon forest's carbon balance, biodiversity, and overall ecosystem functioning. Moreover, global-scale studies employing Coupled Model Intercomparison Project Phase 6 (CMIP6) future climate scenarios project an increase in extreme events over South America, further emphasizing the vulnerability of the Amazon forest ecosystem.
Previous studies have examined heatwaves, droughts, and extreme precipitation events within the Amazon forest as singular extreme events. However, few studies have considered these weather extremes simultaneously as compound or concurrent extreme events. These compound events can have a more significant impact than individual extreme events alone; recent research has shown that the occurrence of combined drought and heatwave can increase the probability of vegetation decline compared to the individual effects of these events. Furthermore, existing research has primarily focused on hot-dry compound events, leaving a knowledge gap regarding the occurrence of combined hot and wet extremes.
In this context, the main research question addressed in this study is: What is the climatology of compound hot-dry and hot-wet extreme events in the Amazon region? To answer this question, our analysis involves identifying compound events of heatwaves and dry spells (hot-dry) and heatwaves and extreme precipitation (hot-wet) events that have occurred in the Amazon region over the last few decades. For this, we utilize data on maximum temperature and precipitation from rain gauges and weather stations, as well as from gridded datasets. The intensity and frequency of the compound events will be discussed, as well as the main atmospheric drivers.
How to cite: Ferreira, V. and Ramming, A.: Identifying compound extremes in the Amazon rainforest: dry-hot and dry-wet events, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-786, https://doi.org/10.5194/ems2024-786, 2024.
Drought is one of the extreme events that will be increasingly present in the context of climate change. As revealed in recent studies, meteorological droughts will become the principal factor modulating compound hot-dry events and analysis; thereof is therefore fundamental with regard to understanding future climate patterns. The average citizen knows little of geometry, but it plays an essential role in the characteristics of the droughts, by means of "fractional lengths". We analysed the fractality of the meteorological droughts under the most recent climate change scenarios. In addition, a new criterion for defining the beginning and end of meteorological droughts is established, which allows the analysis of seasonal variability. A temporal fractality measure based upon the Cantor set reveals consensual changes in the behavior of droughts worldwide. Most regions will undergo a slight increase in fractality (up to +10% on average), particularly associated with an acceleration of the hydrological cycle and the Hadley cell expansion, with a shift towards the higher latitudes of the tropical edge in both hemispheres. Geometrical measures were applied to the dry spells (<1mm) simulated by Earth System Models of the CMIP6, showing more concentrated or unequal distribution of droughts in mid latitudes. Simultaneously, the polar regions might benefit from more regular precipitation patterns. Other inequality measures, such as the indices of Gini and Monjo, showed similar results. In general terms, the earth’s climate will be more fractal in the rainfall-related patterns, which likely means that the consequences will be more catastrophic for the human population.
How to cite: Galiano, L., Monjo, R., Royé, D., and Martin-Vide, J.: Future changes in global drought fractality, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-794, https://doi.org/10.5194/ems2024-794, 2024.
Recently, changes in the intensity and frequency of tropical cyclones related to Warming Climate have been observed, although uncertainties persist regarding this matter. Tropical cyclones, which are among the most dangerous weather phenomena, can arise from different conditions. However, those affecting Western Europe predominantly originate from a tropical transition and occur during the Autumn season. Consequently, this study aims to examine differences in the climatology of the variables related to tropical cyclogenesis during different periods from 1980 to 2100 in the North Atlantic basin under the influence of Warming Climate. The periods considered are: historical (1981 - 2010), near future (2021 – 2050) and far future (2071 – 2100), since periods with a statistically significant length, which represent the historical climate and two future climates spaced in time are needed. For this purpose, the SSP5-8.5 scenario from the EC-Earth3 climate model is used.
The results indicate significant rises in Sea Surface Temperature, Total Column Water and Geopotential Height at 300 hPa, alongside significant anomalies in the tropospheric Averaged Potential Vorticity, especially for the last part of the XX1 century. These changes lead to a percentile Vertical Wind Shear and air column stability reduction in almost the whole domain for the last part of the current century. Overall, these outcomes suggest an increased susceptibility to tropical cyclones formation in the North Atlantic basin due to Warming Climate, raising concerns about the potential for significant material damage and loss of human life caused by these systems. This study is a first approximation on how these high-impact severe weather events can evolve in the future, allowing for a better understanding of how tropical cyclogenesis could change with global warming.
How to cite: Montoro-Mendoza, A., Calvo-Sancho, C., González-Alemán, J. J., Díaz-Fernández, J., Bolgiani, P., Sastre, M., Moreno Chamarro, E., and Martín, M. L.: Warming Climate effect on favorable environments for tropical cyclogenesis in the North Atlantic basin, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-732, https://doi.org/10.5194/ems2024-732, 2024.
We investigate the Oceanic Niño Index (ONI), for simplicity called in this paper an El Nino Southern Oscillation (ENSO) index in 1950-2023 by applying the wavelet spectral transform and the IBM SPSS correlations analysis. ONI follows the three months current measurements of an average temperature of the sea surface in the East-Central tropical part of the Pacific ocean nearby the international line of the date change over the average sea surface temperature over the past 30 years. The ENSO index is found to have a strong ($>$0.87) correlation with the Global Land-Ocean Temperature (GLOT). The scatter plots of the ENSO-GLOT correlation with the linear and cubic fits have shown that the ENSO index is better fit by the cubic polynomial increasing proportionally to a cubic power of the GLOT variations. The wavelet analysis allowed us to detect the two key periods in the ENSO (ONI) index: 4-5 year and 12 years. The smaller period of 4.5 years can be linked to the motion of tectonic plates while the larger period of 12 years is shown to have a noticeable correlation of 0.25 with frequencies of the under-water (submarine) volcanic eruptions in the areas with ENSO occurrences. Not withstanding any local terrestrial factors considered to contribute to the ENSO occurrences, we investigated the possibility of these volcanic eruptions to be also induced by tidal forces of the Jupiter and Sun showing the correlation of the under-water volcanic eruption frequency to be 0.12 with the Jupiter-Earth distances and 0.15 with the Sun-Earth distances in January, induced by the solar inertial motion, when the Earth is turned to the Sun with the southern hemisphere where the ENSO occurs. Hence, the underwater volcanic eruptions induced by tidal forces of Jupiter and Sun can be the essential additional factors imposing this 12 year period of the ENSO (ONI) index variations.
How to cite: Zharkova, V. and Vasilieva, I.: The ENSO variations and their link with solar and volcanic activity , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-23, https://doi.org/10.5194/ems2024-23, 2024.
The Arctic ozone layer is characterised by high interannual variability, especially in the springtime period, which depends on stratospheric circulation and polar vortex forcing. Since the 1990s, there has been a gradual ozone recovery in the Arctic polar stratosphere. However, the increasing ozone trend may be different in unlike pressure levels of the stratosphere in connection with the ongoing climate change, which is related to the strengthening of the Brewer-Dobson circulation. This strengthening is related to changes in vertical distribution of ozone concentrations in different levels of the stratosphere. The aim of this study is a spatiotemporal analysis of the stratospheric ozone trend at different pressure levels between 10–100 hPa in the spring periods 1980–2023. In the following section, trends of geopotential height, temperature or potential vorticity at pressure levels between 10–100 hPa are analysed in particular. The monthly means of ERA-5 reanalysis layers were utilized. The trend was assessed using linear regression, and its statistical significance was determined using the non-parametric Mann-Kendall test. In March, the statistically significant decreasing trend (p=0.05) of the ozone mass mixing ratio was detected over Siberia at 10 hPa, while at 100 hPa, the statistically significant decreasing trend was registered over eastern Siberia and Greenland. In April, there was a statistically significant increasing trend at 10 hPa over eastern Siberia, and at 100 hPa, the trend over uniform parts of the central Arctic is spatially heterogeneous. In May, a statistically insignificant increasing trend occurred over the Arctic Ocean at 10 hPa, while at 100 hPa statistically significant decreasing trend was registered in the peripheral parts of the Arctic between 60–70°N.
How to cite: Tichopad, D. and Láska, K.: Springtime stratospheric ozone trends in the Arctic since 1980, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-682, https://doi.org/10.5194/ems2024-682, 2024.
The research focuses on evaluating of changes in fire risk in the vicinity of reservoirs Švihov and Vír in the Czech Republic in the context of rapidly advancing climate change and recent bark beetle calamities. The global interest in fire risk research and management emphasizes its significance in various ecosystems and sensitive locations. Studied areas are suitable for evaluation of potential fire occurrences around the dams, which have far-reaching consequences besides overall ecosystem degradation, pollution, and drinking water shortage, as both reservoirs supply drinking water to 2 million inhabitants, including the capital city.
The methodology for predicting fire risk is based on the analysis of historical and current data, modeling, and simulation of fire behavior using modern technologies. Data evaluation identifies changes in vegetation characteristics and fire behavior due to climate change. Fire behavior simulation is currently the most effective scientific research approach for assessing the impact of fire weather on the landscape. The main tool for its identification is the widely used American program FlamMap, which takes into account topography, fuel types, wind speed, and fuel moisture.
Climate change alters the composition of forests and agroecosystems, resulting in an increased fire risk in many cases. Higher temperatures and lower humidity increase vegetation flammability, while forest disturbances (such as drought, pests) bring dry fuel and reduce tree resistance to fire. The aim of this study is to assess the change in fire risk due to climate change and bark beetle calamity, which affected the areas of interest in the years 2018–2022. The application of the FlamMap program will provide characteristics of fire behavior and also predict fire risk in the future. This analysis will contribute to the design of prevention strategies and fire protection in water management protected areas, among other things.
How to cite: Kudláčková, L., Poděbradská, M., Cienciala, E., Mašková, R., Beranová, J., Novotný, J., Pikl, M., Bláhová, M., Zahradníček, P., Štěpánek, P., Žalud, Z., and Trnka, M.: Assessment of wildfire risk due to climate change in the vicinity of the Švihov and Vír water reservoirs in the Czech republic, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-48, https://doi.org/10.5194/ems2024-48, 2024.
Climate change is one of the major challenges that humanity faces today. The latest IPCC report highlights that an increase in the frequency and intensity of extreme weather and climate events are likely to occur in the future. Global and regional climate models (GCMs and RCMs, respectively) are key tools for climate research which provide valuable information about future climate change. However, model simulations are subjects to uncertainties of various origins. In order to quantify and reduce these uncertainties it is recommended to evaluate several RCM simulations together, as members of an ensemble, and/or apply a bias-correction method. The implementation of a bias-correction procedure has become a standard step in the process of using climate model outputs, since unbiased data are required for impact studies. During this procedure, the raw simulated meteorological variables are adjusted to measurements, so the use of a high-quality, observation-based dataset as a reference is a crucial point for all bias-correction methods, in addition, the choice of the calibration period is also an important factor.
In our research an ensemble of 5 RCMs (CCLM, HIRHAM, RACMO, RCA, REMO) driven by 4 different GCMs are investigated from the framework of EURO-CORDEX with the finer (0.11°) horizontal resolution for the historical (1976–2005) and the scenario (2006–2099) time periods under two radiative forcing scenarios (RCP4.5 and RCP8.5). Our aim is to investigate how the choice of the reference dataset and different calibration periods affects the results of the expected changes based on the different bias-corrected datasets, focusing on Hungary. For this purpose, a bias-adjustment was carried out by applying the internationally widely used percentile-based quantile mapping method on a monthly level for 4 variables: daily minimum- and maximum temperature, mean temperature and precipitation. The most accurate, measurement-based and quality controlled HuClim dataset was used as a reference. Two calibration periods were chosen from HuClim for the bias-correction: an earlier (1976–2005) and a more recent (1993–2022) one, thus creating two, different bias-corrected databases. Beside them, a third bias-corrected database was also analyzed, namely, the same RCMs provided by the EURO-CORDEX community and adjusted using the MESAN reanalysis data based on the 1989–2010 calibration period. In the present study, we analyze and show the results of the different bias-adjusted RCM simulations for two future periods (2021–2050; 2070–2099) focusing on the detected change of climate indices.
How to cite: Simon, C., Torma, C. Z., and Kis, A.: Climate change signals based on different bias-corrected EURO-CORDEX simulations over Hungary, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-160, https://doi.org/10.5194/ems2024-160, 2024.
Climate describes how the atmosphere behaves over a long period of time informing us on the “average of weather”, as well as the description of other aspects of weather patterns and meteorological parameters’ distribution, including anomalous, rare and extreme events. Some examples of extreme weather or climate events include heat waves, cold waves, floods, extreme precipitation, drought, tornadoes and tropical cyclones (WMO-CCL, 2018).
Drought is a natural weather phenomenon that occurs in all climates and can differ greatly from other extreme events. Unlike other extreme events, such as floods, which are weather events that are immediately detectable, droughts develop slowly, making it difficult to determine the onset and end.
Portugal is a country with recurrent phenomena’s of drought, which creates the strong need for impact reduction strategies as an integral part of drought preparedness plans.
To better understand the risk of droughts in mainland Portugal, was used indices that rely on precipitation deficits and allows us to characterize and monitor drought in Portugal, determining drought onset, duration and intensity. In this study was used the PDSI (palmer Drought Severity Index), SPI (Standardized Precipitation Index), SMI (Soil Moisture Index).
These indices were computed using daily and monthly data and based on the recommendations of CCL task team on the definition of extreme weather and climate events: Threshold (is determined based on historical values of the index); Temporal (Station-level information on starting date, ending date, and duration of the event); Spatial (calculates the area affected, by providing the distribution of stations where the threshold was surpassed and uses a geographical information system (GIS) to determine the area affected by the event, the magnitude, and severity).
In order to characterize the drought events was used the following properties:
- Magnitude: measures the departure from the threshold and reflects unusualness or extremity of the event.
- Duration: defined by the time at which the event begin and end.
- Extent: defined as the geographical area affected by the extreme event.
- Severity: severity should indicate the potential damages and impacts that can be associated to the event. It is a combination of magnitude and persistence of a drought.
It is also aimed the framing of this extreme event with climate changes based on trend analyses and simulation of scenarios with variables such as precipitation, temperature and evapotranspiration.
How to cite: Pires, V. and Cota, T.: Drought Monitoring and Analysis in Mainland Portugal , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-312, https://doi.org/10.5194/ems2024-312, 2024.
Climate change affects ecosystems and biodiversity, and the phenological development of plants has been changing. In this paper, we focused on the beginning of the flowering of the lime tree (Tilia cordata) in urban and rural settings. The long-term series were evaluated from phenological and meteorological stations of the Czech Hydrometeorological Institute (period 1923–2023). The trends (using the Mann-Kendall test) and Pearson’s correlation coefficients between the beginning of flowering and meteorological variables were calculated. Climate scenarios SPP2 4.5 and SPP5 8.5 (ALADIN-CLIMATE/CZ) were used to predict future climate conditions for lime tree phenological development. The main finding of this research is that the beginning of flowering of the lime tree during the period 1923–2023 is negative, and it varies in urban and rural environments. The results express the most significant acceleration of the beginning of flowering of T. cordata by -0.227 day per year in urban area and by -0.119 day per year in rural area. Moreover, the study proved that the beginning of flowering of T. cordata closely correlated with temperature (the Pearson’s correlation coefficient is in the range from -0.498 to -0.508.), and the correlation with precipitation is significantly weaker in both environments. The increase in air temperature in June and July will be significant in the period 2081–2100 (by 1.5 °C). Based on these findings, we expect a further shift in the beginning of T. cordata flowering to earlier dates. A change in the beginning of lime tree flowering will also affect the course of the pollen season.
How to cite: Hájková, L., Možný, M., Vlach, V., and Musilová, A.: Changes in the phenological development of lime tree under future climate conditions, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-328, https://doi.org/10.5194/ems2024-328, 2024.
Seasonal snowpack plays a significant role in the climate system. Its characteristics are monitored as climate change indicators considering the snow importance from ecological, hydrological, and economic perspectives. Observation data provides evidence of declining depth, spatial extent and duration of the snow cover, in connection to changes in seasonal air temperature and precipitation, especially in the lowlands and mid-elevation mountain areas. However, these changes underpin the occurrence of compound hazards resulting from the joint actions of rain and snow (rain-on-snow events - ROS). Such hazards entail a wide range of physical and socioeconomic impacts related to the complex processes occurring on and within the snowpack, which influence the occurrence of floods, landslides and snow avalanches. In this context, this study aims to provide a baseline understanding of ROS climatology and how it changes in the present climate conditions. Our work investigates the spatial and temporal changes in the rain-on-snow (ROS) events over the 1961-2021 period, based on 114 weather stations in Romania. This snow hazard is considered in the analysis as it is responsible for important socioeconomic impacts in different sectors (e.g., tourism, forestry, transport). The ROS event detection and trend analysis were conducted at annual and seasonal scales.
The results indicate that ROS events occur mainly in winter months in the lowlands (below 1,000 m) and in late fall, winter and spring in the mountains (above 1,000 m). Overall, in the Romanian Carpathians, the highest ROS frequency is in the December-April interval, but at the highest elevation, such events occur throughout the entire year. The years of maximum ROS frequency ( >60/year) were 1962, 1966, 1981, and 2021 and were recorded in the mountain areas. Observation data indicate a decreasing frequency of ROS events, especially in the lowlands, due to the significant changes in the solid/liquid precipitation ratio (more frequent liquid precipitation than solid) and the decline in snow cover duration in response to seasonal warming. In the mountains, the observed change signal in ROS frequency is mixed, showing both decreases and increases. The high elevation areas (above 1,800-2,000 m) register the highest number of ROS events yearly (over 35-40), where the snow avalanche release areas are mostly located.
Acknowledgements
This research received funds from the project “Cross-sectoral framework for socio-economic resilience to climate change and extreme events in Europe (CROSSEU)” funded by the European Union Horizon Europe programme, under Grant agreement n°101081377.
How to cite: Micu, D., Dumitrescu, A., Amihaesei, V.-A., Cheval, S., and Milian, N.: Rain-on-snow events in Romania: climatology and trend analysis using observation data (1961-2021), EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-407, https://doi.org/10.5194/ems2024-407, 2024.
Impact of climate-related events and their associated risks are important not only for policy makers, they have become a relevant part of important economic analyses.
This topic has been addressed by the project “Prediction, Evaluation and Research for Understanding National sensitivity and impacts of drought and climate change for Czechia“ where we estimated risks of hydrometeorological phenomena and their expected changes during the 21st century.
According to the results of our study, the main risks for the Czech Republic are related to the following phenomena: heat wave, cold wave, extreme wind, extreme precipitation (torrential and permanent), drought and the subsequent risks e.g. firerisk, severe thunderstorm.
To quantify changes in occurrence of heat waves from 1961 till 2020 and their future projection, a set of characteristics has been used: The number of days with maximum temperature above 34 °C, the number of days with minimum temperature above 20 °C and for the heat waves (heat wave defined as a period of at least three consecutive days with maximum daily temperature at least 30 °C) their frequency, duration and intensity .
Whilst statistically significant linear trend for number of days with extreme high temperature has been observed in the period 1961–2020 and the same time the heat waves frequency as well as duration prolonged, the results for occurrence of extreme precipitation and extreme wind were not conclusive.
In our analyses of the future development of the phenomena of our interest we used the data of regional climate model ALADIN-Climate CZ. The results based on ALADIN-Climate CZ data were compared to the results of the selected Euro-Cordex models.
How to cite: Valeriánová, A.: Projection of selected climate-related risks in the Czech Republic, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-757, https://doi.org/10.5194/ems2024-757, 2024.
Earth’s surface radiation and heat balance (or simply called as surface energy budget) is one of the key factors affecting the climate on the local scale. The size, magnitude and temporal variability of its individual components have a direct impact on the surface temperature and hence also 2-meter air temperature. In addition, the surface energy budget is closely related to evapotranspiration and the ratio between both turbulent heat fluxes (latent and sensible heat flux) may help to identify drought conditions. The aim of this work is to analyze the spatial and temporal changes of individual components of the surface energy budget in Europe from 1950 till 2100 using the large ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models (GCMs). The ensemble consists of 17 GCMs in nominal horizontal resolution of 50 or 100 km. For validation purposes in the period 1950–2014 GCMs are compared to the ECMWF ERA5 reanalysis. The climate change signal in 21st century (2015 and onwards) is investigated under the intermediate greenhouse gases emissions of SSP2-4.5 scenario with a special emphasis on the summer half of the year (April – September) that roughly corresponds to the growing season in Europe. Projected changes of the surface energy budget are put into context of the expected changes of 2 m air temperature and precipitation. There is an increase in global irradiance in Europe that leads to higher net radiation and stronger role of sensible heat flux in the second half of growing season indicating a higher risk of soil drought.
How to cite: Skalak, P., Fischer, M., and Trnka, M.: Surface energy budget changes in Europe under the intermediate greenhouse gas emissions, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-860, https://doi.org/10.5194/ems2024-860, 2024.
Climate change in mountain areas is faster than in other parts of the world. In addition, the rate of temperature increase in the context of climate change can be altered by changes in the environment, including the cryosphere. So, the loss snow cover and a dry floor can increase the temperature additionally.
Temperature increase study shows how in recent decades the rise in temperature is accelerating. If we focus on the extremes, in some of climatic indices such as maximum and minimum temperature records, we see that in Andorra maximum temperature records continue to occur while minimum temperature records stopped occurring in the 1980s. The analysis is made with 90-year-old stations in order to have an initial 20 years for comparison and from this period we add registered values up to the present day. Before this analysis, the climate series have undergone a process of quality control and homogenisation.
In this poster we will quantify the speed increase in temperatures rise in two historical weather stations from Andorra over the last decades and we will see how the frequency and intensity of extremes study demonstrates an alteration of the climate beyond a simple statistical distribution.
In terms of precipitation, changes are also observed in the behaviour and distribution of extreme precipitation and drought periods.
Through the SPI drought index we can see how it is becoming easier and easier for it to oscillate in short periods around 0 or negative values, while if we study the SPEI, which takes into account temperature, i.e. evapotranspiration, we will see how this index is increasingly capable of reaching negative extreme values.
capable of reaching negative extreme values.
How to cite: Martín, G., Rivero, L., Albalat, A., Sinfreu, G., and Molné, T.: Climate extreme values in Andorra, evolution in terms of frequency and intensity, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-920, https://doi.org/10.5194/ems2024-920, 2024.
Convective and stratiform precipitation differ not only in their origin, but also in their characteristics. Different risks arise from them, and they also exhibit distinct trends under climate change. Convective precipitation is associated with intense storms and tends to develop rapidly and locally, whereas stratiform precipitation is linked with longer lasting and less intense rainfall events. Their distinct characteristics have varied impacts on ecosystems, agriculture, infrastructure, and human lives.
In this study, we focus on analyzing the current characteristics of convective and stratiform precipitation and assess their future changes using ALADIN-CLIMATE/CZ model. Due to uncertain future concentration of greenhouse gases in the atmosphere, two CMIP6 scenarios are analyzed: SSP5-8.5 and SSP2-4.5. The ALADIN-CLIMATE/CZ model is based on the ALARO canonical model configuration of the ALADIN System. The model domain covers Central Europe, with a horizontal grid size of 2.3 km and it belongs to the so-called convection permitting models. We utilize data from 19 stations in the network of the Czech Hydrometeorological Institute to validate the model. The historical validation period spans from 1990 to 2014. Employing an algorithm that uses information from the SYNOP report, we separate precipitation into convective and stratiform. We have found that the ALADIN-CLIMATE/CZ model overestimates both stratiform and convective precipitation in all months. Convective precipitation is better captured by the model in summer than stratiform precipitation. We examine precipitation characteristics across 25 winter and summer seasons for both the near future (2050-2074) and for the end of the 21st century (2074-2099). In future climate assessments, we focus on extreme events in addition to total seasonal precipitation.
How to cite: Beranova, R. and Rulfova, Z.: Convective and stratiform precipitation under future climate, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-120, https://doi.org/10.5194/ems2024-120, 2024.
This study analyses the characteristics of compound dry and hot (DH) extreme events in Croatia. As in many parts of the world, such events have become more frequent in Croatia in recent decades. In this work, measured data collected at local meteorological stations were used. The analysis covers the period from 1963 to 2021. Croatia’s geographical location includes parts of the Pannonian Basin, the mountainous regions of the Dinarides and the coastal parts of the eastern Adriatic. Therefore, both continental and coastal stations are included in the analysis.
In this study, the temporal and spatial characteristics of DH events are analysed. Precipitation and daily maximum temperature data were used to define DH extremes. The frequency and intensity of DH events in different time periods were analysed. As an additional measure of the dryness of atmospheric conditions, the characteristics of the water vapour pressure deficit during DH events were analysed. The results show an increase in DH events at all stations considered, with the increase being somewhat more pronounced at the continental stations. In addition, an assessment of the compound effect of drought and high temperatures was calculated using cumulative heat. This measure also shows that the characteristics of compound DH events are changing and becoming more intense.
The impacts of compound extremes can have more severe consequences for humans and the environment than the occurrence of individual extremes alone. The change in the characteristics of extremes in terms of their intensification and increasing frequency can cause significant damage to agriculture, the energy sector, etc. Therefore, it is necessary to continue research on DH events to better understand the mechanisms of their occurrence and the atmospheric conditions that support them. With better preparation and adaptation, it may therefore be possible to improve the risk assessment of extreme events and reduce their harmful consequences.
How to cite: Boras, M. and Herceg Bulić, I.: Characteristics of dry and hot extreme events in Croatia, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-150, https://doi.org/10.5194/ems2024-150, 2024.
Wildfires pose a significant natural disaster risk to populations and contribute to accelerated climate change. As wildfires are also affected by climate change, extreme wildfires are becoming increasingly frequent. Although they occur less frequently globally than those sparked by human activities, lightning-ignited wildfires play a substantial role in carbon emissions andaccount for the majority of burned areas in certain regions. While existing computational models, especially those based on machine learning, aim to predict lightning-ignited wildfires, they are typically tailored to specific regions with unique characteristics, limiting their global applicability. In this study, we present machine learning models designed to characterize and predict lightning-ignited wildfires on a global scale. Our approach involves classifying lightning-ignited versus anthropogenic wildfires globally over a long timespan, and estimating with high accuracy of over 91% the probability of lightning to ignite a fire based on a wide spectrum of factors such as meteorological conditions and vegetation. Utilizing these models, we analyze seasonal and spatial trends in lightning-ignited wildfires shedding light on the impact of climate change on this phenomenon. Our findings highlight significant global differences between anthropogenic and lightning-ignited wildfires. Moreover, we demonstrate that, even over a short time span of less than a decade, climate changes have steadily increased the global risk of lightning-ignited wildfires. We also find that models trained to predict lightning-ignited wildfires and models trained to predict anthropogenic wildfires are very different. This dramatically reduces the predictive performance of models trained on anthropogenic wildfires when applied to lightning-ignited ignitions, and vice versa. This distinction underscores the imperative need for dedicated predictive models and fire weather indices tailored specifically to each type of wildfire.
How to cite: Shmuel, A., Glickman, O., Lazebnik, T., Heifetz, E., and Price, C.: Lightning-Ignited Wildfires On A Global Scale: Prediction and Climate Change Projections based on Explainable Machine Learning Models, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-480, https://doi.org/10.5194/ems2024-480, 2024.
Over the past couple of decades, thanks to the sustained development of Global Climate Models (GCMs) combined with dedicated downscaling strategies such as regional climate modelling or statistical downscaling, climate projections and associated services are now increasingly available across many regions of Europe including France. However, whereas this holds for continental France, the national territory includes numerous overseas territories, some of them also EU outermost regions, where this information is still only partially available, if at all.
Here we present the results of statistical downscaling of Coupled Model Intercomparison Project phase 6 (CMIP6) GCMs for the small territory of French Guiana in equatorial South America. Compared with island territories, the larger size of French Guiana makes the direct use of GCMs possible, although statistical downscaling with long daily surface observations of temperature, humidity, precipitation and surface wind remains relevant for bias correction, mapping (the territory is covered by few grid points), and computing tailored climate indices for the agriculture, water resource, energy, or public health sectors.
Obvious advantages are cost-effectiveness and the processing of GCM ensembles that provide more reliable uncertainty estimates made difficult with the more expensive dynamical methods. However, systematic GCM biases such as a displaced Intertropical Convergence Zone may challenge model uncertainty assessment and rather call for a storyline approach supported by selected, skilled GCMs, which all project warming and drying trends over French Guiana. Among the various expected societal impacts, heat stress resulting from the combined humid climate and widespread warming strongly increases the risk of hyperthermia, and the energy demand for air conditioning as a likely local adaptation strategy.
How to cite: Belmadani, A., Gentric, A., Dutrieux, P.-C., Suez-Panama-Bouton, B., Bald, L., Qasmi, S., Longueville, F., and Palany, P.: Downscaling climate change over French Guiana: from CMIP6 projections to sector-based indices, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1029, https://doi.org/10.5194/ems2024-1029, 2024.
