bluuebunny/crossref_metadata_2025 huggingface dataset:
Calibration of Mobile Micrometeorological Measurements in a tropical urban park: Analysis of SMaRTy data on Urban Warming 
Authors: Mandelmilch Moshe Eliezer , Yik Sin Kang , Crank Peter , Chow Winston
Published: July 2024

Anthropogenic activities and land cover changes within cities can result in unique climate conditions in settlements. One of the major phenomena of the city’s climate is the “Urban Heat Island” (UHI), defined as an amplification of temperatures inside cities compared to its rural surroundings arising from the inadvertent development of cities and associated human activity. Apart from remote sensed platforms, the UHI can be measured via two different approaches; fixed meteorological stations and mobile climate measurements. Usually, fixed meteorological stations measure climate information continuously 24 hours a day. However, they are limited in number and cover relatively a small area close to them for their instrumental source area. On the other hand, mobile climate measurements are flexible in terms of instrumental source area, their quantity is greater compared to stationary stations and therefore they can cover larger areas in shorter time intervals, which makes them relevant for biometeorological research.Recently, the development of mobile micrometeorological cars such as MaRTy (Middel et al. 2019) enables measurement of key microclimate parameters (e.g., air temperature (TA), relative humidity (RH), Wind Direction (WD), shortwave and longwave radiation across three dimensions, and wind speed (WS). That can be subsequently used to estimate outdoor thermal comfort (OTC). MaRTy is named after the key climate variable it calculates: Mean radiant temperature (MRT). Since 2019, MaRTy carts have been used in several cities worldwide mainly to assess OTC conditions, as well as to evaluate microclimate models e.g. ENVI-Met. This study examined, for the first time, data from the SMaRTy platform (The Singaporean version of MaRTy) to conduct mobile climate measurements along a designated route in an urban park in Singapore during different monsoon seasons. The study's aims were: (1) To test the influence of the walking speed of the SMaRTy cart on the measured climate variables e.g., TA, RH, and WS. (2) To calibrate the mobile climate measurements of the SMaRTy cart along a designated route in an urban park in Singapore based on data from fixed meteorological stations.  (3) To apply the calibration equations on SMaRTy cart data, and to create a spatial model of the climate variables in the urban park. Initial results suggest that mobile microclimate measurements via the SMaRTy platform along a designated route yield useful data that can be applied towards OTC analysis, but seasonal variations in model calibration occur across temporal measurements from SMaRTy.
New sensor platform for expansion of in-situ measurements for meteorological and climate change measurements
Authors: Johnson Dave , Burba George , Fratini Gerardo , Griessbaum Frank , McCoy Johnathan , Walbridge Ryan , Frodyma Alex , Fuhrman Isaac , Parr Andrew , Trutna Derek , Thomas Taylor , Ivans Sasha , Xu Liukang
Published: July 2024

As water is known to be a critical resource for hydrology and water management, with an estimated 2 billion people already affected by water scarcity and a projected 3 billion facing shortages by 2050, it was realized that this was an opportunity for designing and developing a new solution.Evapotranspiration (ET) plays a vital role in the global water cycle, moving a staggering 500,000 km3 of water annually, with 70,000 km3 occurring over land. However, conventional methods for quantifying ET – such as potential, reference, max, equilibrium, and pan – do not achieve the necessary level of accuracy.To address these challenges, a new cost-effective solution for direct, automated, and real-time ET measurements has been developed. The LI-710 sensor is a user-friendly device that measures ET, sensible heat, temperature, humidity, and air pressure every 30 minutes. It is significantly more affordable than typical eddy covariance flux stations, costing 5-10 times less, and it consumes 3-15 times less power. Moreover, it can be easily installed and utilized by individuals with limited experience in the field.Years of field testing alongside traditional research-grade eddy covariance systems have provided excellent results.Benefits from this innovative sensor have allowed for comprehensive global deployment in locations where infrastructure, funding, and local experience have made it difficult. Applications are extensive across agricultural fields, forests, wetlands, grasslands, water bodies, and many more. Every 30-minutes, fully processed ET values are provided in real-time, including quality flags, to reduce ‘data latency’ for immediate and effective actions.Within the last year, multiple research agencies have been developing ET networks spanning states, countries, and continents, which this new LI-710 sensor makes possible.Further innovations include the establishment of a new Internet of the Environment (IoE) platform. The new IoE system connects the Water Node with the Cloud platform. The Water Node includes all hardware necessary for direct, real-time measurement, data collection, and transmission to the Cloud.  The Cloud platform with remote access allows for data storage, analysis, and sharing.This innovative LI-710 sensor fills needs for both meteorologists and climate change researchers as these two groups work together on new discoveries, interdependencies, and feedback loops. Governments around the world are focusing and funding hydrological-cycle research, and these sensors provide measurements where there were previously gaps in remote field locations. The information from these measurements will help with predicting future weather and climate patterns and with developing solutions for hydrology and water management challenges.
Thermal inversion analysis in the Andorra Central Valley and its relationship with pollutants and meteorological variables
Authors: Trapero Laura , Crespillo Alex , Udina Mireia
Published: July 2024

The behaviour of pollutants in urbanized mountainous areas is complex due to the interactions between the atmosphere and the orography, particularly noticeable in winter due to frequent thermal inversions inside the valleys. This stable Mountain Boundary Layer, present during anticyclonic situations, can lead to critical air pollution episodes that are detrimental to human health and the environment. Another growing concern is the impact of climatic extremes such as increased heat waves and their impact on air quality. This study aims to characterize the thermal inversion episodes in a complex orography area like the Central Valley of Andorra (ACV), answering questions like: (i) Which are the frequency and duration of winter inversion episodes in the central Valley of Andorra? (ii) How these characteristics correlate with pollutant concentrations and meteorological variables? Complementary, we explore the limitations of the current observation strategy for monitoring thermal inversions in the valley using low-cost sensors of temperature: (iii) Could the use of a larger number of stations on the slopes (pseudo-profile) overcome these limitations?Findings indicate an increasing frequency and duration of thermal inversion episodes over the last decades, as well as the heatwaves on mountain areas, predominantly influenced by synoptic high-pressure conditions as daily synoptic classification centred on the Pyrenees has shown. These episodes significantly impact NO2 concentrations, nearly doubling their average levels, while PM10 and O3 did not show a direct correlation. In contrast, during the warm months, exceedances of critical O3 thresholds have been increased in last decades. Furthermore, results show that the effectiveness of low-cost sensors is notably dependent on their placement, particularly in terms of altitude and orientation relative to solar radiation. 
Atmospheric Diabatic Heating Mechanism on the Development of Zonal Shear Line Over the Tibetan Plateau in Boreal Summer
Authors: Yao Xiuping
Published: July 2024

The zonal shear line (ZSL) over the Tibetan Plateau (TP) is one of the most crucial synoptic systems inducing precipitation over the TP in boreal summer. However, few studies have comprehensively explored the thermal mechanism of the intensity evolution of the ZSL. In this study, the mechanism of the atmospheric diabatic heating (hereafter referred to as diabatic heating) effect on the intensity of the ZSL was explored by the methods of composite and diagnostic analysis.
Based on the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate hourly data sets from June to August during 1980–2019, 11 cases of heavy-precipitation-inducing ZSL with life cycles more than 60 hours in the high-frequency region (32–35°N) of the ZSL were selected by using the objective identification method.
Results suggest that the intensity of the ZSL features a significant diurnal variation, with its peak at around 23 LST  (Local Solar Time) and its valley at around 15 LST within a day. There exists a close relationship exists between the ZSL’s intensity and the 10-h-earlier vertically integrated diabatic heating , with a high correlation coefficient of 0.81. The intensity of peaks at around 13 LSTwithin a day. The diabatic heating rate Q reaches the maximum values at 350 hPa. The vertical transport of temperature is the main contributor to the intensity of Q during the intensity evolution of the ZSL. The vertically non-uniform diabatic heating effect is the primary mechanism for the intensity evolution of the ZSL. When the vertically non-uniformdiabatic heating near the ZSL enhances (weakens), it will be favorable (unfavorable) to enhance the ZSL’s intensity.
Using the DWD warning portal prototype to configure own individualized warnings and reports
Authors: Niebuhr Heiko , Riedl Kira , Vogel Christian , Reetz Björn , Schaab Reik , Noël Linda , Feige Kathrin
Published: July 2024

To meet the individual needs requested by many expert users of warning products issued by the German Meteorological Service (Deutscher Wetterdienst / DWD), the idea of a new customizable branch for our future warning system (program RainBoW: "Risk-based, Application-oriented and INdividualizaBle delivery of Optimized Weather warnings”) was born. Based on the prospects of a fully automatic warning system, the possibility of individual warning information can be realized by giving users the option to configure their own parameters and settings for warnings and reports.Based on results of a pilot project named "Kassandra", which marked the first attempt to conceptualize individual warnings at DWD and to determine the meteorological and technical requirements and challenges, a light-weight prototype of the warning portal was released at the end of 2022. The release was made available to a small amount of test users from different application areas to collect feedback and further requirements. Since then, a gradually increasing number of test users continues to evaluate further releases.The light-weight prototype of the warning portal does not yet provide full individualization capabilities for warnings and reports. However, we are planning to implement persistent warning profiles in one of the future releases, in which users will be able to configure warning location (position or geometries), period, warning element and criteria and also probabilistic or time-based thresholds. Using the wide range of available EPS models and other ensemble data sets at DWD, the user configurations will be analyzed periodically. Warnings or reports will be generated and sent to the users by mail or messenger (PUSH) in case of transgression. The system will also give users the possibility for PULL requests at any time by using the DWD warning portal or web API. Especially the web API will enable users to include individual warning information into their own automated processes by directly analyzing individual requests and returning the results as JSON.The poster presents concepts, components and configuration elements for the future provision of individualized warnings via the DWD warning portal.
Role of sea surface temperature and sea-ice changes in high-latitude climate change: a multi-model experiment within the CRiceS H2020 project.
Authors: Naakka Tuomas , Köhler Daniel , Nordling Kalle , Räisänen Petri , Tronstad Lund Marianne , Makkonen Risto , Merikanto Joonas , Samset Bjorn , Sinclair Victoria , Thomas Jennie , Ekman Annica
Published: July 2024

Dramatic sea ice loss has recently occurred at both poles. Multiple studies have suggested that changes to sea ice can impact weather in both the polar regions and mid-latitudes. However, the current generation of climate models disagrees on the rate and location of sea ice loss, and on the rate of warming in the polar regions.Thus, the atmospheric response to sea ice loss within and outside the polar regions remains highly uncertain. To reduce this uncertainty, we have performed a set of coordinated simulations with four different atmospheric general circulation models (AGCMs) within the project “Climate Relevant interactions and feedbacks: the key role of sea ice and Snow in the polar and global climate system” (CRiceS). A baseline simulation and six perturbation simulations were performed, all of which were 40-years long and had prescribed  sea surface temperatures (SSTs) and sea ice concentration. In the perturbation simulations, the SSTs and sea ice concentration were changed independently, and then both were changed together. The SST and sea ice concentrations were obtained from CMIP6 simulations with the Australian Earth system model ACCESS-ESM1.5. Monthly-mean SST and sea-ice area averaged over 20 years of simulation were taken from 1) the historical simulation (years 1950-1970, Baseline simulation), 2) the scenario SSP1-2.6 simulation (years 2080-2100), and 3) the scenario SSP5-8.5 simulation (years 2080-2100) and were then used as perpetual monthly average values of SSTs and sea ice fraction in our model simulations, thus eliminating inter-annual variability in SSTs and sea ice. This array of perturbation experiments, performed with four AGCMs, allows us to isolate atmospheric responses in polar regions and mid-latitudes that are due to SST or sea ice changes, examine the linearity of these feedbacks, and investigate the robustness of the atmospheric responses. The results of this coordinated modelling experiment show that the models agree well on the magnitude and spatial distribution of the 2-m temperature and precipitation response. Increasing SSTs has a larger and more spatially extensive impact on the overall response than decreases in sea ice,  which primarily only cause a localised response in regions where sea ice disappears (most notably, a strong warming over the Arctic ocean in winter). The models agree less well on the magnitude and spatial distribution of the mean sea level pressure response, in particular over northern Europe and Antarctica, suggesting that modelled uncertainties associated with atmospheric circulation are larger than uncertainties associated with thermodynamics. These results and others, along with information about the openly available dataset, will be presented.  
Investigating the medium-range predictability of European heatwave onsets in relation to weather regimes using ensemble reforecasts
Authors: Lemburg Alexander , Fink Andreas H.
Published: July 2024

Over the past years, Europe was stricken by unprecedented heat and drought extremes. Heatwaves (HWs) pose an increasingly major threat to society, which requires to further our understanding of their predictability some days or weeks ahead. In the present study, we focus on medium-range lead times of 5-12 days, for which the successful prediction of HW onsets is strongly dependent on the adequate prediction of large-scale Rossby wave patterns and their dynamics.Using ECMWF and GEFSv12 ensemble reforecasts, we statistically assess the medium-range predictability of HW onsets over multiple European regions for the period 2001-2018. Heatwaves are objectively diagnosed as time periods where the 90th percentile in 2m maximum temperatures is exceeded both grid point-wise and integrated over the region for at least 3 days, giving about 50 HWs for each region. Predictive skill is evaluated mainly for large-scale flow features but also in terms of the ensemble’s capability to predict the extremeness of near-surface temperatures. By adopting the concept of Euro-Atlantic weather regimes, we are further able to stratify HW onsets and their predictability by the concurrent large-scale atmospheric flow pattern.For both the British and Central European region, we find that the medium-range predictive skill is significantly better for HW onsets associated with either Scandinavian or European blocking compared to cases with no pronounced regime. This skill advantage mostly concerns the large-scale flow (500hPa geopotential patterns) and to some extent 850hPa temperatures, particularly in times of a Scandinavian blocking. In contrast, near-surface maximum temperature forecasts do not exhibit increased skill for regimes associated with above-average large-scale predictability, which may point to the inherent difficulty of predicting smaller scales and boundary layer processes.Finally it is explored how exceptionally good or poor forecasts at 10 days lead time are related to the atmospheric state during or shortly after forecast initialisation. For Central European HW onsets, poor large-scale flow predictive skill is associated with significantly increased baroclinicity further upstream and a more intense North Atlantic jet stream whereas particularly good forecasts are on average characterized by an initial atmospheric state close to climatology. Forecast skill for near-surface temperatures is not affected by such dynamical precursors, but rather by pre-existing soil moisture anomalies, with drier than normal soils being linked to better predictions and vice versa. For the British region, exceptionally good forecasts of both large-scale flow and near-surface temperatures are associated with an already established blocking over the continent. In comparison to Central Europe, antecedent soil moisture anomalies do have a same-sign, but less prominent effect on near-surface temperature forecasts.
One step closer to the RainBoW: First results from the development of a new weather warning system at the German Meteorological Service
Authors: Feige Kathrin , Altnau Sebastian , Anger Falk , Baumgartner Manuel , Erhardt Bodo , Felsberg Anne , Hoff Michael , Klink Martin , Kratzsch Thomas , Lambert Andreas , Leschzyk Dinah Kristin , März Benedikt , Niebuhr Heiko , Noël Linda , Riedl Kira , Sauter Christoph , Schaab Reik , Vogel Christian , Wapler Kathrin , Hagedorn Renate
Published: July 2024

With RainBoW ("Risk-based, Application-oriented and INdividualizaBle delivery of Optimized Weather warnings”), the German Meteorological Service (Deutscher Wetterdienst/DWD) launched a program to renew its weather warning system. The overarching goal of the program is to tailor weather warnings more strongly towards the needs of end users, thus enabling the recipients to make informed decisions using the information provided. Specifically, we are working on three fields of action to achieve this. First, we want to increase the forecasting horizon of weather warnings to inform users early on. For this, we are implementing a probabilistic warning trend covering up to seven days and showing the likelihood of a specific warning to occur. It should transition as seamlessly as possible into an actively distributed warning. Second, we want to improve the comprehensibility of our weather warnings. This includes strengthening the consistency of warning criteria across all warning elements. Beyond this, we intend to improve the perception by shifting the communication focus away from the meteorological description of an event towards the associated weather impacts. For the latter, besides restructuring the warning text towards a more prominent placement of recommendations for action, we also plan to establish a data-driven approach resulting in illustrative impact description to add to that text. Third, we want to individualize our weather warnings, since the warning criteria for the general public do not neccesarily meet the needs of specialized user groups (e.g. professional users). For specific weather-dependent use cases, hazard-inducing thresholds can be individual for the application at hand. To cover for this, we are developing a warning portal serving as a warning toolbox for end users, with the possibility to configure, receive and visualize warnings as needed. This contribution will give an overview over the goals of the RainBoW program at DWD, including specific updates on current developments in all three fields of action.
Climate Atlas of extremes in Catalonia (1991-2020) 
Authors: Barnolas Mercè , Barrera-Escoda Antoni , Prohom Marc J. , Serra Aleix
Published: July 2024

As we acknowledge the increasing frequency, broader distribution, and heightened intensity of extreme weather events due to climate change, it becomes crucial to gain a deeper understanding of their behaviour. These extreme events have significant societal impacts, requiring better knowledge and tools for assessment.The Climate Atlas of Extremes in Catalonia, covering the period from 1991 to 2020, serves as a vital reference tool. It provides valuable information to government bodies, regional authorities, businesses, and citizens about the specific characteristics of climate extremes in Catalonia over the past three decades.In this study, we present the methodology behind the creation of the Catalonia Climate Extremes Atlas. Our goal is to provide a comprehensive analysis of extreme climate events in the Catalonia territory. We will present the key steps involved in this process.Data Preparation: we collect and preprocess daily climate data, including mean, maximum, and minimum temperatures, as well as precipitation records. Rigorous quality control procedures are applied to ensure data accuracy. Homogeneity analysis: artificial biases in the data series are addressed using the ACMANTv5 method. This step ensures that the dataset accurately represents the true climate conditions. To obtain descriptive indices to evaluate extreme events, we utilize the CLIMPACT tool (https://climpact-sci.org/indices/). These indices were defined by the joint CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI) and provide valuable insights into extreme weather phenomena.
Digital cartography: we interpolate extreme normals to create georeferenced climate data on a regular grid. The resulting high-resolution digital cartography includes precipitation indices mapped at a 1-kilometer resolution, and temperature indices mapped at a 100-meter resolution. Different time scales (monthly, seasonal, and annual) are considered based on relevance. The extreme normals will be freely accessible through the SIG portal of the Government of Catalonia (https://sig.gencat.cat/visors/hipermapa.html).
Ongoing research involves trend calculations and statistical approaches. We will compare different periods of extremes and assess changes. Additionally, we plan to compare our findings with model-projected changes in the same extremes.
Changing landscape of regional extreme weather events by intersecting large-scale weather types and local-scale potential impacts for the Alpine region
Authors: Lehner Sebastian , Enigl Katharina , Crespi Alice , Pittore Massimiliano , Haslinger Klaus
Published: July 2024

Extreme weather events and their resulting impacts threaten all levels of society. Climate change can amplify the frequency and intensity of associated hazards. One of the key-challenges for decision-makers in civil protection is adapting to the changing landscape of weather-induced impacts driven by climate change. It is therefore essential to assess and estimate the changing conditions for extreme weather events under climate change.This study investigates the changing landscape of regional extreme weather events in the Alpine region by utilizing weather circulation type classification through its relationship with weather-induced potential extreme events. Therein, large-scale weather types take the role of relevant precursors for regional extreme events. The local-scale potential impact events that are associated with prevailing weather types are derived by using percentile-based methods on high-resolution, gridded precipitation data. ERA5 mean sea level pressure and the classification scheme GWT ('Gross-Wetter-Typen') are used to derive 18 classes of cyclonic and anti-cyclonic weather types, representing a prevailing circulation on a daily basis for the whole Alpine region. Subsequently, unsupervised hierarchical clustering (Agglomerative clustering) is used to evaluate overlaps between cluster families in order to derive a subset of 'high-impact' weather types. The relationship between those weather types and local-scale extreme events is further characterized by analyzing percentile-based indicators from station data and high-resolution observational data. Finally, we extend our analysis by applying found relationships to state-of-the-art climate models from the Coupled Model Intercomparison Project 6 (CMIP6) to investigate the changing landscape for extreme weather events under different climate change scenarios.Our findings indicate that a subset of weather types, related to specific cyclonic circulation patterns, is mostly responsible as precursor for extreme precipitation events. Those patterns furthermore show increases in frequency under the scenario SSP3-7.0, that are consistent across the climate model ensemble. Associated changes of precipitation totals suggest increases in intensity, however these intensity changes are not as conclusive due to large inter-model spread.
Validation of Aerosol Optical Depth and Ångström Exponent retrieved by solar and lunar photometry techniques in Burjassot (Valencia)
Authors: Garcia-Suñer Meritxell , Matos Violeta , Kumar Gaurav , Estellés Víctor , Utrillas María Pilar
Published: July 2024

Among the many existing aerosol detection techniques, lunar photometry is particularly appealing, since its combination with sun-photometer retrievals could allow a quasi-continuous monitoring of aerosol properties. Great efforts have therefore been devoted to improve the instrumentation and especially the calibration methods, so as to sort out the inherent difficulties in the computation of the -not constant- extraterrestrial lunar irradiance. Thus, assessing the coherence between solar and lunar retrievals is of utmost importance. In this work, the agreement between Level 1.5 solar and lunar retrievals of Aerosol Optical Depth (AOD) and the Ångström Exponent (α) in AERONET’s Burjassot (Valencia) site from July 2015 to January 2024 are evaluated. Then, inter- and intra-annual monthly means are compared and validated through a correlation study. In agreement with previous analyses of solar measurements over this region, higher values of AOD are observed in summer months in comparison with the rest of the year. This could be related to factors such as particle stagnation, hygroscopic processes, secondary aerosol formation (favoured by higher irradiation levels), or dust outbreaks, which are more frequent at this time of the year. Indeed, the latter could be responsible for a secondary AOD maximum found in April. On the other hand, hourly means from both data sets will be also jointly analyzed in order to study the consistency of retrievals in the transition from day to night and vice versa. In these cases, factors such as the influence of the Moon phase and the interval of time between the last and first Sun and Moon measurements, respectively, will be taken into account. Finally, after checking the agreement between solar and lunar data, hence justifying their joint use, AOD temporal evolution from solar and lunar data are examined, concluding that AOD tends to decrease along the years. This result is not unexpected, taking into account the decreasing AOD trends over Europe and North America that have been reported by several authors.
Projection of selected climate-related risks in the Czech Republic
Authors: Valeriánová Anna
Published: July 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.
Climate risks in cities – how flooding and heat prevention can be tackled holistically. 
Authors: Soler Jesús , Martinez Montserrat , Goler Robert , Bügelmayer-Blaschek Marianne , Schneider Martin , Hochebner Andrea
Published: July 2024

Human-made climate change is increasingly impacting our living conditions, destroying infrastructure and threatening lives. The recent years and months have led to unprecedented events and record-breaking temperatures, with March being the tenth month in a row being the hottest so far (Copernicus).  

Not only rising temperatures but also altered precipitation patterns pose a challenge to the existing urban environments and thus to 2/3 of the human population (REF). Cities are especially affected since they consist of mainly sealed surfaces, which enhance climate change impacts such as increased heat or intensified precipitation events due to their different characteristics as natural areas (e.g. albedo, heat capacity, infiltration). 

Within KNOWING two climate impacts are investigated comprehensively – flooding (fluvial, pluvial) and its impact on infrastructure as well as heat and its impact on health. Therefore, two urban areas (Granollers, Spain and Tallinn, Estonia) are considered. To quantify possible interventions to adapt to current and future climate change impacts, two different models are applied: PALM-4U [1] and ICM-Infoworks. PALM-4U is an urban climate model used for quantifying the impact of greening on urban heat load. ICM-infoworks is used for assessing adaptation measures to lessen pluvial flooding. As both models rely on land use, the changes planned to adapt to heat (e.g. greening and unsealing) and those for reducing flooding (retention areas, unsealing) coincide.  

Within PALM-4U interventions such as increased tree cover, implementation of recreational parks, renaturalization of rivers and building-related measures (e.g. green roofs, retrofitting) are considered. All interventions leading to increased unsealing of areas and thus infiltration, also lessen the risk of flooding and can thus be implemented within ICM-Infoworks, quantifying the impact of the same interventions on flood risk. By assessing the impact of the same interventions within two models and concerning two different climate risks (heat and flooding) the double effectiveness is accounted for, thus allowing the holistic approach of adaptation to climate change. 
Adapting to Change: Social Media Dynamics and Meteorological Communication Practices
Authors: Špoler Čanić Kornelija
Published: July 2024

In the dynamic field of meteorological communication, the use of social media platforms has become an integral part. This work examines the Croatian Meteorological and Hydrological Service's five-year journey with Twitter/X, YouTube, and Flickr, elucidating the rationale behind our platform selection and exploring the efficacy of our communication strategies. Our journey commenced with the utilization of Twitter as a real-time dissemination tool. The decision to embrace YouTube and Flickr raised from our commitment to diversifying content delivery and enhancing user engagement. Each platform offers unique advantages, from Twitter's/X’s immediacy to YouTube's visual storytelling capabilities, shaping our multifaceted approach to meteorological communication. Our methodology encompasses a range of tools tailored to the unique characteristics of each medium. From the integration of visuals to crafting concise messages, we leverage a diverse array of resources to effectively engage our audience.Furthermore, our research extends to understanding the evolving dynamics of social media, particularly in the wake of Twitter's transformation into X. This shift prompted us to reassess our strategies and adapt to the changing ecosystem. We are actively considering the possibility of expanding our presence to other social networks, mindful of the need for platform suitability, resource availability, and alignment with our communication objectives. Additionally, we recognize the evolving preferences of younger audiences, who seek information in different ways, and are exploring tailored approaches to engage them effectively. We remain proactive in our approach, driven by a commitment to innovation and responsiveness to the evolving field of meteorological communication.This work not only summarizes our successes but also the invaluable lessons learned from our experiences. By reflecting on our journey, we interpret the important role of social media in modern meteorological communication and offer insights into our best practices for engaging with media and other audiences.
How has the recent decline in Antarctic sea ice contributed to the strengthening of the cooling trend near the Ross Sea gyre?
Authors: Kim Taekyun , Jo Seonghyun , Moon Jae-Hong , Jin Emilia Kyung
Published: July 2024

Despite the overwhelming warming over most oceans under global warming, cooling in the surface of the Southern Ocean between Australia and South America has been previously reported. The surface cooling is due to wind-driven sea-ice transport and its subsequent melting. However, Antarctic sea ice which has a steady increasing trend during several decades, experienced an abrupt decline to a record low in the mid-2010s. Since then, the interannual variability of Antarctic sea ice has been further intensified, showed another record low in 2022 and 2023 consecutively. Accordingly, the Pacific sector of the Southern Ocean has experienced warming during the period of rapid sea ice decline.Nevertheless, we find that a coherent cooling pattern is observed in a very specific area, near the Ross Sea gyre. Here, to investigate the mechanisms associated with the cooling pattern, we examined how the rapid decline in Antarctic sea ice in recent years has contributed to the strengthening of the cooling trend near the Ross Sea gyre, using satellite observations of sea ice, as well as oceanic and atmospheric reanalysis data. Our result shows that the cooling trend has strengthened despite the rapid decrease in Antarctic sea ice in recent years. The significant cooling trend has been attributed to record atmospheric low pressure systems over the Pacific sector of the Southern Ocean. We demonstrate that the cooling near the Ross Sea gyre is likely influenced by the local and remote large-scale atmospheric variabilities that lead to substantial sea ice anomalies. Since the mid-2010s, local anomalous winds and surface heat flux associated with strong events of natural climate oscillations like the Zonal Wavenumber 3, El Niño–Southern Oscillation, and Southern Annular Mode in the Southern Hemisphere that drive the recent change in Antarctic sea ice, induce strong meridional flows led to enhanced sea ice drifts and melting, and consequently to the strong cooling trend.
 

 
Advances in understanding extreme meteorological events: a review of the UNSEEN methodology and its applications
Authors: Mele Lorenzo , Ruggieri Paolo
Published: July 2024

Extreme meteorological events represent a serious threat to society, due to their strong impacts on mortality and economic losses. However, a deep comprehension of the features of such events is often limited by the scarce availability of reliable observations from the past. The UNSEEN (UNprecedented Simulated Extremes using ENsembles) method relies on the use of large ensemble simulations to investigate both the statistical and the dynamical features of events more severe than those seen in the historical record (Kelder et al. 2022). The study presents a literature review of the UNSEEN method, with particular attention to implications for downstream applications and conclusions reached on model realism. It is shown that the majority of studies addresses rainfall-related extremes with seasonal reforecasts, but the method is used for multiple hazards and with simulations ranging from medium-range weather predictions up to decadal and multi-decadal simulations. We emphasize that UNSEEN studies can rely on an unprecedented of high-resolution models and large ensembles. One of the main advantages emerged from the use of the UNSEEN method involves the possibility to reduce the uncertainty associated to the estimate of the statistics of extreme events, with respect to the only use of observations. Moreover, if the simulated events are considered physically consistent, this approach enables to better comprehend the dynamics of the processes that lead to the occurrence of extremes, including the possible role of remote teleconnection patterns. We discuss potential applications of the UNSEEN method that are currently underrepresented in the scientific literature and the opportunity to apply the UNSEEN method with a hierarchy of climate models to better understand the role of climate teleconnections in driving the emergence of the extreme event. An example application toward this goal has been conducted through the use of a coupled general circulation model of intermediate complexity (SPEEDY-NEMO) for the study of heat extremes in a region in Europe. Finally, we propose a workflow to generate a low-dimension catalogue of simulated plausible events that can be relevant to support adaptation studies and downscaling exercises. 
Exploring Euro-Atlantic Winter Seasonal Predictability: A Comparative Analysis of Deep Learning and Maximum Covariance Analysis
Authors: Galván Fraile Víctor , Martín del Rey Marta , Polo Sánchez Irene , Rodríguez de Fonseca María Belén , Balmaseda Alonso Magdalena
Published: July 2024

The seasonal predictability of wintertime atmospheric patterns is determined, to a large extent, by the anomalous ocean surface thermal conditions. Specifically, the sea surface temperatures (SST) appears as a significant contributor to the predictability of wintertime atmospheric patterns in the Euro-Atlantic region (EAR). Current seasonal prediction systems rely significantly on the interannual phenomenon known as the El Niño-Southern Oscillation (ENSO).On the one hand, current seasonal prediction systems predominantly rely on dynamical models, which propagate the signals associated to these forcings to both local and remote areas. However, the complexity of atmospheric processes, the important biases in reproducing SST in the extratropics and the interaction of signals make this propagation much more challenging. On the other hand, traditional statistical techniques (i.e. Maximum Covariance Analysis (MCA)), allows the possibility of making seasonal predictions with less bias, by focusing on the relationship between the predictor and the predictand. Nevertheless, there is a growing interest in exploring non-linear relationships between seasonal anomalies of various physical variables. Deep learning approaches offer promising avenues for modeling such complex relationships. Therefore, this study aims to assess the predictive capability of autumntime (September-October) SST anomalies in forecasting wintertime (November-December and January-February) sea level pressure (SLP) anomalies across the EAR by using two different statistical prediction techniques.Specifically, the MCA will be used to identify and analyse the dominant patterns of co-variability between SST anomalies in different ocean basins and EAR atmospheric conditions. Additionally, several deep neural network models are developed to capture the complex non-linear atmospheric teleconnections associated with SST anomalies, and their predictive performance is rigorously evaluated over the EAR region. The assessment highlights regions with higher prediction accuracy for the different methods and identifies key sources of skill, particularly over the Pacific basin. Concretely, certain regions show higher skill in the EAR than the one from the ECMWF seasonal forecasting model (SEAS5).By comparing deep learning methodologies with traditional statistical techniques such as MCA, this study provides a comprehensive analysis of wintertime atmospheric predictability over the EAR. The findings contribute to advancing our understanding of oceanic forced atmospheric teleconnections, not only by establishing windows of opportunity for seasonal forecasts but also by means of analysing possible drivers of these teleconnections. All of these aid in the development of more accurate and reliable prediction models for managing climatological risks in the Euro-Atlantic region.
Assessing uncertainties of evaporation over glacial lakes in Antarctica
Authors: Shevnina Elena , Potes Miguel , Vihma Timo , Naakka Tuomas
Published: July 2024

Lakes play a significant role in the global water cycle and influence regional and local weather patterns. They influence local moisture fluxes by providing a constant moisture source to the atmosphere through evaporation, which is difficult to measure. Therefore, indirect methods needing only a few meteorological and hydrological observations are applied in evaluation of evaporation over lakes. In Antarctica, many well known indirect methods tend to underestimate the summertime evaporation over the lakes. This study quantified the uncertainties of the bulk-transfer equations applying to estimate the summertime evaporation over glacial lakes in Antarctica. We used the eddy-covariance (EC) method to provide a reference while evaluating the uncertainties in the bulk-transfer methods applied to estimate daily evaporation over two glacial lakes. The micrometeorological observations of near surface air temperature, wind speed, wind direction, atmospheric pressure, water vapor concentration were collected in the Schirmacher oasis (Dronning Maud Land, East Antarctica) during two austral summers (DJF) 2017-2018 and 2019-2020. Our results show that the summertime evaporation over the glacial lakes 3.0 mm per day on average during the ice-free period, and it is 1.6 mm per day over the ice break-up period. The best indirect method was the bulk-aerodynamic method which underestimated the evaporation over the lakes by 32 %. Changes in evaporation over the lakes was associated with changes in wind speed rather than changes in near surface air temperature, and the changes in wind speed were driven by variations in synoptic scale flow patterns, which the largest changes in daily evaporation.
Identifying compound extremes in the Amazon rainforest: dry-hot and dry-wet events
Authors: Ferreira Vanessa , Ramming Anja
Published: July 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.