bluuebunny/crossref_metadata_2025 huggingface dataset:
Using opportunistic sensors in a new hydro-meteorological precipitation and flood forecasting system for small catchments
Authors: Winterrath Tanja , Wenzel Malte , Chwala Christian , Graf Maximilian , Grundmann Jens , Wagner Michael , Elghorab Mohamed , Philipp Andy , Sallwey Jana , Stefanova Anastassi , Müller Matthias
Published: July 2024

Small, fast responding catchments are prone to flooding induced by local convective precipitation events. In such cases, the availability of high-quality information as basis for target-oriented warnings and effective protective measures in potentially affected regions is essential. More precisely, they rely on high-quality precipitation data, reliable weather and flood forecasting and last but not least information and education of persons in charge for prevention of hazards.Within the project HoWa-PRO funded by the German Federal Ministry of Education and Research (BMBF) a new hydro-meteorological processing chain has been established to improve flood forecasting and warnings for small catchments. The system has been automated and a routine mode consisting of three main parts has been established:To produce high-quality Quantitative Precipitation Estimates (QPE) the Deutscher Wetterdienst (DWD) performs an operational gauge-adjustment of radar-based precipitation estimates. Within HoWa-PRO, the additional merging of precipitation data derived from numerous Commercial Microwave Links (CML) with high temporal resolution and low latency promises an improvement of capturing local extreme precipitation events leading to a multi-sensor QPE product optimized for convective weather.
The QPE products together with forecasts from DWD’s seamless prediction system SINFONY-INTENSE – a combination of nowcasting and numerical weather prediction run in a Rapid Update Cycle (RUC) – serve as input for a hydrologic ensemble prediction system designed for small catchments resulting in discharge time series including uncertainty information.
To meet the requirements of communicating the uncertainty information of the ensemble forecasts to key clients in disaster and risk management, an information platform (howapro.de) with tailored visual information on flood early warnings for small catchments constitute the last part of the processing chain. In addition, a serious game has been designed for educational purposes.
This contribution gives an overview of the whole processing chain and presents case studies and first verification results.
Integrating and validating crowdsourced data for improved weather predictions in MET Nordic
Authors: Neuville Amélie , Nipen Thomas N. , Seierstad Ivar  A. , Båserud Line , Lussana Cristian
Published: July 2024

The MET Nordic dataset, developed by the Norwegian Meteorological Institute (MET Norway), offers high-resolution (1 km) near-surface meteorological variables for Scandinavia, Finland, and the Baltic countries. Derived through statistical post-processing of numerical model outputs, MET Nordic serves two main purposes: historical weather reconstruction and real-time weather monitoring with short-term forecasts. This presentation focuses on the real-time stream (MET Nordic RT), which updates hourly with a 20-minute latency and maintains an operational archive dating back to 2012.The near-surface variables included in MET Nordic RT are: two-metre temperature, precipitation, air pressure at sea level, relative humidity, wind speed and direction, solar global radiation, long-wave downwelling radiation, cloud area fraction. The dataset combines data from the MetCoOp Ensemble Prediction System (MEPS) and diverse observational inputs, including -for temperature and precipitation- crowdsourced data from consumer-grade weather stations managed by citizens. The integration of such opportunistic data sources has enhanced the precision of reconstruction analysis and short-term forecasts, particularly temperature predictions in regions with sparse professional meteorological stations.This study describes the automatic quality control system employed to vet incoming data, ensuring reliability in statistical processing. The system uses a range of validation techniques—ranging from basic range checks to sophisticated spatial consistency tests via Bayesian inference—to mitigate the risks posed by the inherently variable quality of crowdsourced data. Our findings underscore the importance of treating such data as a network to capitalize on its dense, high-resolution coverage. The quality control software, Titanlib, is important to this process and it is freely available for use at https://github.com/metno/titanlib.The integration of data from Netatmo’s crowdsourced network into MET Nordic can be regarded as a success story. This now heavily influences MET Norway's work on upgrading our main quality control system through the internal project CONFIDENT.
Wave breaking events and their Link to Rossby wave packets and atmospheric blockings during Southern Hemisphere Summer
Authors: Perez Iago , Barreiro Marcelo , Ehstand Noémie , Hernández‐García2 Emilio , Lopez Cristobal
Published: July 2024

Rossby Wave Packets (RWPs) are atmospheric perturbations located at the upper levels in mid‐latitudes which, under certain circumstances, terminate in Rossby Wave Breaking (RWB) events. When RWB events are sufficiently persistent and spatially extended, they are synoptically identical to atmospheric blockings, which are linked to heatwaves and droughts. Therefore, studying RWB events that occur after RWPs propagation and their link with blocking is key to enhance extreme weather events detection between 10–30 days in advance. In this study we assessed the occurrence of RWB events after the propagation of transient RWPs, whether long‐lived RWPs (RWPs with a lifespan > 8 days, or LLRWPs) are linked to large‐scale RWB events that could form a blocking event, and the proportion of blocking situations that occur near large-scale RWB events. To do so, we applied a tracking algorithm to detect and follow transient RWPs in the southern hemisphere during summertime between 1979-2021, developed a wave breaking algorithm to identify RWB events, and searched for blocking events with different intensities. Results show that LLRWPs and the other RWPs displayed large‐scale RWB events around 40% of the time, and most of the RWB events in both distributions last around 1–2 days, which is not long enough to identify them as blocking situations. Nearly 17% of blockings showed a RWB event nearby, but barely 5% of these blockings were linked to RWPs, thus suggesting that transient RWPs are not strongly linked to blocking development. Lastly, large‐scale RWB events associated with RWPs that lasted less than 8 days are influenced by El Niño‐Southern Oscillation
Luxury effect and Urban Heat Island: a reassessment in Madrid.
Authors: Toribio-Pérez Miguel , Conde-Oria Francisco , Rasilla Domingo F.
Published: July 2024

“Greenness is often associated with more attractive, healthful, and wealthy urban areas since vegetation increases the urban biodiversity and reduces summer temperatures. Some analyses have pointed out a relationship between neighborhood demographics and urban vegetation that has been referred to as “luxury effect” (Leong, Dunn, and Trautwein 2018) or tree gap (Visram 2021), from which wealthy residential areas benefit from greater vegetation cover and a lower intensity of the urban heat island effect. So, this contribution relates some of the urban features, derived from remote sensing, with the dynamic of the urban heat island of Madrid, and some socio-demographic parameters at census tract level, for the summers of the 2008-2017 period.The remote sensing indices were calculated from Landsat 5 and Landsat 8 platforms (https://earthexplorer.usgs.gov/). The urban heat island of Madrid was studied using the “Climate variables for cities in Europe from 2008 to 2017” dataset, obtained from Copernicus (https://cds.climate.copernicus.eu/cdsapp#!/software/app-health-urban-heat-islands-current-climate?tab=app), combined with observed temperature data from the Spanish Meteorological Agency (AeMet) and the Regional and Local authorities (Ayuntamiento and Gobierno Regional de Madrid). Demographic data were retrieved from the Atlas de distribución de renta de los hogares (https://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736177088&menu=ultiDatos&idp=1254735976608) and the Municipality of Madrid (https://www.madrid.es/portales/munimadrid/es/Inicio/El-Ayuntamiento/Estadistica?vgnextchannel=8156e39873674210VgnVCM1000000b205a0aRCRD).Analyses show that Madrid's UHI is particularly intense at night, while during daytime is much weaker. This can be explained by the thermal behavior of its urban periphery, which is mainly made up of agricultural areas with rainfed crops, suffering an intense daytime heating. It is also observed that the relationship between remote sensing indices and the urban temperatures varies depending on the information provided by the indices (vegetation, built-up or aquatic surfaces density) and the time of day. The "luxury effect" is not evident, as the relationship between vegetation, heat island and various sociodemographic indicators is statistically weak. As an urban space which has evolved from many decades, Madrid offers a remarkable spatial diversity in terms of income levels or demographic composition, although some risk neighborhoods can be delimited because of the coincidence of a high amount of vulnerable population (low income, senior population, migrants) and an intense urban heat island.”
Thunder probability nowcast
Authors: Korpinen Anniina , Hieta Leila , Partio Mikko
Published: July 2024

 

The Finnish Meteorological Institute (FMI) has developed the Smartmet Nowcast (SNWC) system to provide accurate and timely nowcast information to end-users in the Scandinavian forecast domain. SNWC combines observation-based data with the NWP nowcast model and integrates it with the 10-day forecast, ensuring rapid and automated weather forecast production. 

SNWC was integrated into FMI's operational forecast production pipeline in 2021, initially focusing on key parameters like temperature, humidity, wind speed, precipitation, and total cloud cover. Different methodologies were used to handle the diverse characteristics of these parameters. Over time, the system has evolved to include machine learning techniques, incorporating new parameters like thunder probability and wind gusts into the production process since autumn 2023. 

The thunder probability nowcast follows a methodology similar to pySTEPS commonly used for radar-based nowcasts. This involves generating a present state based on observed lightning and creating a nowcast based on motion vector fields. Before blending the thunder nowcast with the operative forecast, a four-hour nowcast with 15-minute timesteps is created, part of the high-resolution nowcast family (HRNWC) alongside total cloud cover and precipitation accumulation. This thunder probability nowcast information is then integrated temporally with NWP data to account for dynamic evolution. 

Even though the thunder probability nowcast is created with quite simple methods, it has improved accuracy and quality of thunder nowcast greatly. This is mainly due to the systems ability to incorporate the observed lighting information with NWP forecast in high updating frequency of 15 minutes. The high time frequency is some way covering a lack of convection, but generating convection producing system might evolve thunder probability nowcast even further. 
Reanalysis of Giant Hail Event in Catalonia (NE of the Iberian Peninsula)
Authors: soler Temprano Xavier , Rigo Ribas Tomeu , Farnell Barqué Carme , Batalla Esther , Pineda Rüegg Nicolau , Mercader Jordi , Martín Vide Javier
Published: July 2024

On the afternoon of 30th August 2022, a powerful supercell thunderstorm in northeastern Catalonia, Spain, produced a giant hail episode. This rare event resulted in one fatality, over 70 injuries and substantial property damage. According to the records of the severe weather of the Meteorological Service of Catalonia (SMC), this is the largest hailstone ever recorded by Meteorological Network Spotted (XOM).  The focus of the study is to understand why hailstones of exceptional size, reaching 10 cm in diameter, were produced by this storm. For this purpose, firstly we consulted the observations recorded by the local people to identify the path of the hailstorm and the different affectations along the way. Next, we combined the remote sensing data to reveal the severe weather signatures. The radar fields revealed large reflectivity strong vertical development, and very large forward anvil, which measured over 40 km in length. Complementary to this, the total lightning flash rate steeply increased at the same time as an intensification of severe weather radar signatures (tilting, three-body scatter spike, BWER-Bounded weak echo region). The satellite imagery allowed the cold ring pattern detection and extreme cold overshooting top-down to -64 ºC.  On the other hand, the synoptic, mesoscale, radiosonde, and cross-sections run by WRF 3 km and 1.5 km were evaluated to characterize the thermodynamic and environmental conditions favourable for the growth of a supercell with large-hail potential. The values of CAPE in the coastal line were > 2.500 J/kg, the Total Precipitable Water was > 4 cm, and the hodograph signature revealed a strong low-level inflow and strong upper outflow. 
Sensitivity of deep convective cloud climatology to inconsistency of spectral response functions among various generations of satellite sensors
Authors: Wojciechowska Izabela , Kotarba Andrzej
Published: July 2024

Building a homogenous and reliable cloud climatology requires merging observations collected over decades with generations of satellites. Each generation introduces improved instrumentation, causing heterogeneity in terms of spatial, radiometric, and/or spectral resolution. Even if a specific spectral channel is preserved on different satellites (heritage bands), detailed characteristic of a channel may still be different among individual devices. Specifically, each sensor will reveal a different sensitivity to radiation of given vale length, a feature quantitatively defined by the sensor’s Spectral Response Function (SRF).In this study we evaluate how the differences in SRFs impact the homogeneity of global cloud climatology. We focus on specific type of clouds (deep convective clouds, DCCs), and consider all generations of the Meteosat satellites that have been in service since 1977. Over that time Meteosats featured the three following imagers: MVIRI (Meteosat Visible Infra-Red Imager; first generation of Meteosat), SEVIRI (Spinning Enhanced Visible Infra-Red Imager; second generation), and FCI (Flexible Combined Imager; third generation).In order to meet the study goal we simulate radiances for MVIRI, SEVIRI and FCI by convolving sensors’ SRF with a high-spectral-resolution data collected globally with the Infrared Atmospheric Sounding Interferometer (IASI) onboard MetOp satellite. Two infrared heritage channels of Meteosat are examined: the infrared window channel (IR, ~11 mm) and the water vapor absorption channel (WV, ~6.5 mm). Both are essential for DCC detection.Based on simulated radiances we detect deep convective clouds examining brightness temperature difference between WV and IR channels. Whenever the difference is greater than 0K, an IASI pixel is flagged ‘DCC’. Then a DCC frequency is computed globally, and individually for MVIRI, SEVIRI and FCI. Statistics is developed for three summer months of 2013 (June-August).The results demonstrate how much of a difference in DCC cloud amount between MVIRI, SEVIRI, and FCI may be attributed to a different spectral sensitivity in IR/WV for that sensors. More generally, we address the question how sensitive is a (DCC) cloud climatology to spectral evolution of clouds observing instrumentation.This research was funded by the National Science Centre of Poland. Grant no. UMO-2020/39/B/ST10/00850.
Urban Wind Corridor Identification and Verification of Thermal Comfort Enhancement in Urban Area
Authors: Lin Tzu-Ping , Chen Yi-Ling , Liu-Chen Wang
Published: July 2024

In the context of climate change and extreme weather, urban heat island (UHI) phenomenon is exacerbated, affecting people's quality of life and environmental comfort. In the hot and humid climate of Asia, urban ventilation and heat dissipation play a crucial role in improving the thermal environment and reducing heat-related risks. Previous studies have mostly focused on urban wind corridor planning, lacking sufficient evidence of the ventilation benefits of such corridors. This study aims to fill this gap by using Tainan City as a case study to demonstrate the ventilation benefits of urban wind corridors through corridor identification and long-term measurements.Utilizing the 2-kilometer resolution historical climate reconstruction grid data (TReAD) built by the Taiwan Climate Change Projection and Information Platform (TCCIP) of the National Science and Technology Center for Disaster Reduction (NCDR), the heat island phenomenon in Tainan City is examined, and prevailing wind directions are summarized. Geographic information software is employed to calculate the roughness length and formulate urban wind corridors. Mobile observations are conducted to select and evaluate measurement points for assessing the ventilation efficiency of the corridors, followed by long-term observations to obtain high-density data and confirm the ventilation benefits of urban wind corridors.The analysis of corridor formulation and observation yields the following research findings (1) Large open spaces in urban areas significantly increase wind speeds. For instance, at the elementary school near Tainan Park, the hourly average wind speed reaches 1.8 m/s compared to a decrease of 0.9 m/s at points without nearby open spaces, such as roads with a width of 23 meters on both sides. (2) The alignment of road traffic direction with wind direction is the primary factor affecting ventilation efficiency, followed by road width. For example, on Road A with a width of 3 meters and aligned with the wind direction, the hourly average wind speed is 0.7 m/s, compared to an increase of 0.4 m/s at Road B with a width of 21 meters but misaligned with the wind direction. (3) Wind speeds are more stable in crossroad areas. For instance, at the intersection of two road, where dual-directional ventilation occurs, the hourly average wind speed is 0.9 m/s, falling between the efficiency levels of a second-level corridor (1.2 m/s) and a third-level corridor (0.8 m/s).The results of this study can serve as a basis for future urban wind corridor planning, effectively guiding the implementation of strategies to cool urban areas and mitigate the urban heat island effect.
Lightning-Ignited Wildfires On A Global Scale: Prediction and Climate Change Projections based on Explainable Machine Learning Models
Authors: Shmuel Assaf , Glickman Oren , Lazebnik Teddy , Heifetz Eyal , Price Colin
Published: July 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.
An event-based analysis of weather-related fire brigade operations
Authors: Becker Nico , Göber Martin , Ulbrich Uwe , Rust Henning
Published: July 2024

Extreme weather conditions like wind gusts and heavy precipitation frequently lead to impacts like treefall or flooded roads. This in turn leads to a large number of emergency calls to fire brigades, which they have to deal with in addition to their routine operations. If suitable warning information about approaching hazardous weather is available in time, there is potential for preparatory actions like calling in additional staff or preparing equipment and vehicles. However, in order to properly prepare for an event, it is important to understand how a particular fire department is affected by different types of weather conditions.Therefore, an event detection algorithm is applied to operation data provided by different fire brigades in Southern Germany. The algorithm is applied to time series of hourly numbers of weather-related emergency calls to detect time periods with high numbers of operations. Each of the identified time periods, which we refer to as events, is characterized by different parameters, like total number of operations, maximum hourly number of operations, duration and affected area. Furthermore, the meteorological conditions during the event are characterized using convective cell tracks, tracks of large-scale windstorms, radar-based precipitation amounts and wind gusts from reanalysis data. The 100 events with the highest number of operations are selected and their characteristics are compiled into an event catalog. To facilitate the analysis of the event catalog, an interactive dashboard is developed to visualize the mutual interactions between the different event characteristics.It is shown that thunderstorms are responsible for most of the events, followed by windstorms and continuous rainfall. In general, events related to thunderstorms are short and intense and cover a smaller area, whereas events related to windstorms generally affect a larger area. Events related to continuous rainfall are shown to have the longest durations, leading to fire brigade operations for time periods of up to several days.The event catalog is helpful to analyze past events, but can also be useful in the context of impact forecasting. In case of an approaching meteorological hazard, it allows to visualize the potential impacts on fire departments referring to previous events and their characteristics. Furthermore, the event catalog builds the foundation to the development models for the prediction of weather-related fire brigade operations in future work.
Studies of Convection-Permitting Ensemble Forecasting for ICON-D2 with a 1km Nest over the Alps
Authors: Parsakhoo Zahra , Marsigli Chiara , Gebhardt Christoph , Seifert Axel , Steinert Thorsten , Keller Jan
Published: July 2024

Within the context of the “Global-to-Regional ICON digital twin” (GLORI) project, a convection-permitting ensemble forecasting is established in order to study the predictability of high-impact weather events with high-resolution modeling (up to 500 m) and the influence of the land-surface—atmosphere coupling mechanisms.At the DWD, ICON-D2-EPS is the limited-area high-resolution component of the ICON modeling system, running as an ensemble of 20 members at 2 km horizontal resolution over Germany and surrounding areas. The perturbed initial conditions are provided by the km-scale ensemble data assimilation system KENDA, run at the same resolution, assimilating a wide range of observations, including radar-derived radar volumes. Boundary conditions are provided by ICON-EPS, the global ensemble with a refinement at 13 km over Europe and is refreshed every 3 hours.In this work, we employ a nested domain with horizontal resolution of 1-km in the southern region of the ICON-D2, encompassing the Alps mountains. We run a 24-hour forecast simulation starting at 00UTC on the 21st of June 2022, with 20 ensemble members. The choice of the date is crucial as it corresponds to a day when the DWD recorded instances of heavy rain and hail in southern Germany.In our study, we perform all experiments using a two-moment microphysics scheme. Additionally, we incorporate the standard operational model perturbations and subsequently analyze the influence of various convection schemes on the predictability of processes that lead to convection development. Specifically, we examine the behavior of the convection scheme in two configurations: shallow convection only and deep convection parameterization in the so-called gray-zone-tuning version. By selectively enabling and disabling these schemes, our goal is to evaluate their individual contributions to predictability.Following this, we implement a tailored variant of the stochastically perturbed parameterization scheme (SPP) in ICON in order to delve into the influence of some uncertain parameters within either microphysics or turbulent parameterization, further advancing our understanding of its effects on the model performance.
Assessing irradiance forecasts value for an hybrid PV/fuel industrial site 
Authors: Carriere Thomas , Yezeguelian Loïc , De Gabaï Daniel , Rodriguez Benjamin , Pitaval Sébastien , Blanc Philippe
Published: July 2024

With the worldwide increase of photovoltaic (PV) resources in the recent years, PV power forecasting becomes widely used by system operators in many contexts e.g. energy trading, smart grids, island grid operations or industrial off-grid power systems.Forecasts providers generally have a good understanding of how to evaluate forecast accuracy, but low understanding of how the forecasts are used and generate value. It is the opposite for the forecasts user, which results in difficulties for the provider to generate high-value forecasts, and for the user to use them effectively.Estimating the added-value of forecasts is thus a difficult task. Attempts have been made for market-related use-cases [1], [2]. However it is difficult to extend this work to power systems operation, since they have much more physical constraints and no quantitative price signal. In this work, we present a forecasting framework for operators of an hybrid PV/fuel off-grid industrial site, combined with a simulator that estimates the overall economical added-value of the system.Based on discussions with the forecast users and understanding of their decision-making process, the framework is based on three elements. The first is a standard day-ahead forecast algorithm based on weather forecast. The second is a hour-ahead forecast that corrects the first based on measurements and satellite observations, which also takes into account live operational conditions of the PV plant : trackers malfunction, inverters faults, or curtailment. Finally, a state-of-the-art algorithm based on sky imagers that identifies incoming clouds in the next 30 minutes and the expected PV production drop.The simulator takes the outputs of this framework and all measurements from the PV plant and simulates the system operation. Infering the added value of the system is helpful for all parties :The forecast supplier can promote his solution in a quantitative way to other potential customers,
The forecast user can estimate the financial gain that came from using forecasts,
The community can benefit from a reference point on how much value can be expected from forecasts in this use case, and progress towards increasing this value.
[1] David, M., Boland, J., Cirocco, L., Lauret, P., & Voyant, C. (2021). Value of deterministic day-ahead forecasts of PV generation in PV+ Storage operation for the Australian electricity market. Solar Energy, 224, 672-684.[2] Alvarenga, R., Herbaux, H., & Linguet, L. (2023). On the Added Value of State-of-the-Art Probabilistic Forecasting Methods Applied to the Optimal Scheduling of a PV Power Plant with Batteries. Energies, 16(18), 6543.
Projected climate change impacts on water availability and hydrological droughts in Japan
Authors: Ohba Masamichi , Arai Ryosuke , Sato Takahiro , Imamura Masahiro , Toyoda Yasushi
Published: July 2024

The global community is increasingly alarmed by the impact of climate change, particularly in relation to the increased occurrence of droughts and the subsequent depletion of water resources in coming years. However, specific future projections using high-resolution climate simulations that focus on the  water resources and frequency and intensity of hydrological droughts in Japan is currently lacking. This study investigated the impact of climate change on water availability and dry spells in Japan using large ensemble regional climate projections derived from the database for Policy Decision making for Future climate change (d4PDF). Self-organizing maps were applied to atmospheric circulation fields to study the linkages between water availability and weather patterns (WPs) during summer in the present and future climate simulations. The climate projections exhibited a reduced water availability defined by precipitation and evapotranspiration in the majority of Japan, consistent with increases in both frequency and duration of dry spells. The impacts of climate change on water availability vary by WP, with a significant increase in dry conditions under WPs with intensified climatological Pacific high over eastern Japan. Our results suggest that future changes in water availability can be attributed to changes in WP-related precipitation/evapotranspiration under warming conditions and in WP frequency in relation to the Pacific high, recognized as thermodynamic and dynamic effects of climate change, respectively. The decompositions of climate change impacts by WP analogs revealed that thermodynamic and dynamic effects account for approximately 80 and 20% of water availability changes, respectively. In addition, the effects of climate change on hydrological drought in central Japan were examined using hydrological model simulations that were based on climate projections derived from an ensemble of high-resolution downscaling at a 5-km scale. The results indicated a decrease in the streamflow during summer as the climate change progressed, corresponding to an increase in drought years. In addition, the 1%ile values of streamflow decreased by 40 (15) % in the +4-K (+2-K) warming climate simulations. Moreover, there was a considerable increase in the number of consecutive hydrological drought days, reaching an unprecedented level. The yielded results are useful in the consideration of adaptive solutions that will ensure the sustainable use of water resources that balances economic and environmental demands.
Communicating Climate Change Adaptation to Color-Blind Audience: Are We Paying Attention?
Authors: Milošević Dragan , Orero Pilar
Published: July 2024

Thousands of research articles on climate change adaptation are published each year. Most of them contain figures and images that share scientific findings with interested audiences. These findings are important information for human adaptation to climate change and no one should be left behind. However, how many of these studies are paying attention to the color-blind audiences (about 300 million people worldwide) when designing and sharing scientific information through figures and images?In order to answer this important question, we performed an analysis of highly cited studies from the Web of Science database on the topic of climate change adaptation in the last 30 years. Screening of papers was done by two independent reviewers and special focus was placed on the types of figures and images included in the studies and their representation elements such as color palettes and color contrast. The findings from this research can be useful for better communicating climate change adaptation to color-blind audiences as this is an important issue to address in order to ensure accessibility, avoid misinterpretation, enhance engagement, and fulfill our ethical responsibility to inclusivity in addressing climate change. Finally, we hope that this type of research will raise awareness among researchers and motivate them to pay attention when communicating climate change adaptation strategies and solutions to color-blind audience worldwide. Acknowledgement: This research is supported by the project ClearClimate - “Engaging approaches and services for meaningful climate actions”. This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101131220.
Validation of GPM DPR rainfall and Drop Size Distribution through disdrometers in the Northeastern Iberian Peninsula
Authors: Peinó Eric , Bech Joan , Polls Francesc , Udina Mireia , Petracca Marco , Adirosi Elisa , Gonzalez Sergi , Boudevillain Brice
Published: July 2024

Assessing global precipitation trends with some degree of certainty under climate change is a challenge for the scientific community. Therefore, accurate and reliable observations of this variable are required on a global scale that extend to climatological time scales. For this purpose, the Dual-frequency Precipitation Radar (DPR) aboard the Core Satellite of the Global Precipitation Measurement (GPM) mission is currently the only active sensor able to provide, at global scale, three-dimensional measurements of the structure and characteristics of precipitation. In this study, the performance of the variable's precipitation intensity, radar reflectivity factor (ZKu and ZKa) and Drop Size Distribution (DSD) parameters (weighted mean diameter, Dm; intercept parameter, Nw) of the GPM DPR are evaluated. For this purpose, information from seven disdrometers (OTT Parsivels1, 2) located in different topographic areas of the northeast of the Iberian Peninsula is used as reference. Comparison of the DSD parameters show an overestimation of Dm approximately 0.1 mm at low and moderate precipitation rates (0.1-4 mm/h) and of 0.4 mm at precipitation rates higher than 4 mm/h by the dual-frequency DPR algorithm regarding the disdrometer. In contrast, the performance of Nw is underestimated by the DPR, with a maximum value close to 6 dB at moderate precipitation rates (4-8 mm/h). The lowest errors were observed regarding radar reflectivity factor and Dm, while the agreement was poorer considering the Nw and rainfall index.  This lack of accuracy of the GPM DPR rainfall index measurement in Catalonia could be due to the use of predefined constants in the relationships between the rainfall rate and the Dm on which its algorithm is based. This suggests an in-depth investigation of the retrieval algorithms adopted to improve their performance, which requires more disdrometer data to increase precipitation sampling opportunities.
Climate scenarios for Switzerland: How to provide seamless information by bridging models and observations?
Authors: Mülchi Regula , Anet Julien , Stefanie Boersig , Laura Booth , Mischa Croci-Maspoli , Erich M. Fischer , Lilja Jonsdottir , Reto Knutti , Sven Kotlarski , Mark Liniger , Ruth Lorenz , Anna Merrifield , Jan Rajczak , Christoph Schär , Simon C. Scherrer , Christina Schnadt Poberaj , Dominik Schumacher , Cornelia Schwierz , Sonia I. Seneviratne
Published: July 2024

National climate scenarios reflecting the current scientific state of knowledge are an indispensable basis for public and private sectors to plan and design adaptation and mitigation measures. Regional or even local assessments of future climate change are therefore an important climate service. The next generation of climate scenarios for Switzerland is currently under development in the project Klima CH2025. Similar to previous climate scenario generations, the new project is a joint effort involving the Federal Office of Meteorology and Climatology MeteoSwiss, ETH Zurich, C2SM and further partners from academia and administration. The main goal of Klima CH2025 is to develop, update and provide the physical basis of climate change in Switzerland and related products. Two main scientific questions will be addressed: 1) How can we better merge observations and model-based climate scenarios in order to provide consistent and temporally seamless information to best serve user needs?; 2) What is the projected evolution of impact-relevant climate extremes in Switzerland and what are their underlying processes? Guided by these two questions, we will develop a range of new products, engage with stakeholders, and plan active communication and dissemination.We build our scenarios upon the existing CMIP5-based EURO-CORDEX simulations but combine them with CMIP6 GCM information using a variant of a pattern scaling approach. Our approach bridges the gap between different CMIP and CORDEX generations and at the same time merges models and observations to provide consistent information on climate change for the past, the present and the future. In this presentation, the general approach of the Klima CH2025 framework will be presented together with the method applied to bridge models and observations and to integrate CMIP6 evidence into CMIP5-based EURO-CORDEX simulations. In addition, first results of the project and planned products will be presented. 
Opportunities and challenges of impact-based forecasts for hail damage in Switzerland
Authors: Schmid Timo , Villiger Leonie , Raphael Portmann , Bresch David N.
Published: July 2024

Hail is a severe meteorological hazard causing extensive damage to agriculture, buildings, and cars. Within the scClim hail research project, we prototype an application of the open-source risk assessment platform CLIMADA to quantify hail risk. This allows for the provision of impact-based forecasts in Switzerland based on operational radar data, crowdsourced hail reports, and ensemble weather forecasts with the HAILCAST diagnostic built into the operational COSMO model. Combining this with exposure and vulnerability information, we provide hail impact estimates for buildings and different crops in Switzerland. The platform is co-designed with relevant stakeholders from public and private institutions and is running in a pre-operational fashion during the 4-year research project. In addition to forecast products, the platform provides post-event assessments of hail impacts based on radar data and exposure information, which is being used by, e.g., building insurances to have an immediate first estimate for the extent of damages. However, radar-based damage estimates entail considerable uncertainties, which may be constrained locally by using crowdsourced hail reports.Exchanges with stakeholders show that for bespoke preventive actions, such as sheltering cars and animals, or rolling up blinds to avoid hail damage, nowcasting information on expected hazard intensities is often sufficient. Nevertheless, for larger-scale actions such as a preterm crop harvest, preparation of temporary roof covers, or communication to the public, impact forecasts based on ensemble weather prediction may prove highly beneficial, depending on the forecast’s accuracy.As a possible expansion, probabilistic hazard event sets were generated using kilometer-scale regional climate model simulations for Europe covering the present-day period from 2011 to 2021 and projecting a future climate using the pseudo global warming approach for a 3 K global warming level. The feasibility and utility of such an expansion are currently being evaluated, not least to assign return periods to predicted hail events.
Parameter estimation for boundary-layer turbulence parameterizations over heterogeneous terrain
Authors: Fritz Magdalena , Serafin Stefano , Weissmann Martin
Published: July 2024

Accurate representation of turbulent exchange in the mountain boundary layer is particularly challenging for numerical weather prediction models. The use of common planetary boundary layer schemes, which invariably assume flat and homogeneous terrain, results in significant model errors and can even decrease the forecast skill over hills and mountains.We seek to improve the accuracy of planetary boundary layer parameterization schemes over heterogeneous terrain using ensemble-based parameter estimation. Parameter estimation within a data assimilation framework offers a way to reduce model errors by constraining model parameters with atmospheric observations. We consider an idealized modelling environment structured as Observing System Simulation Experiments, consisting of a large-eddy simulation, providing a simulated truth, and a single column model ensemble, where the only model error source is the planetary boundary layer parameterization. This way, we eliminate additional error sources, such as initial-condition error, which could have a detrimental impact on parameter estimation. We attempt to estimate parameters in planetary boundary layer schemes affecting vertical turbulent mixing by assimilating appropriate synthetic surface observations and vertical profiles from the large-eddy simulation run. We demonstrate that, by appropriately configuring the data assimilation system, parameter estimation drives the estimated parameters to converge toward optimal values, and at the same time reduces systematic errors in atmospheric state simulations. This approach holds promise for improving the accuracy of numerical weather prediction models, especially over heterogeneous terrain. It will also make it possible to assimilate many meteorological observations made over mountains, which are often rejected by operational assimilation systems due to large discrepancies of the observed and modelled climatology.
Driving Change: User Engagement and Governance in Climate Adaptation for Coastal Destinations
Authors: Boqué-Ciurana Anna , Saladié Òscar , Garcia-Lozano Carla , Borràs Gabriel , Martí Carolina , Rovira Soto Maria Trinitat , Aguilar Enric , Plana Puig Queralt , Cester Ivan
Published: July 2024

This study investigates climate challenges at national level focusing mainly in two prominent coastal destinations, Costa Daurada and Terres de l'Ebre, situated in Catalonia (northeastern Spain), within the southeastern Mediterranean region. With the urgency to bolster societal resilience to climate hazards and manage risks in these Mediterranean locales, adapting tourist destinations to climate change and mitigating associated risks demand a comprehensive understanding of behavioral change factors affecting businesses, citizens, tourists, and administration.Central to the climate adaptation strategy for the tourism sector is access to high-quality Climate Services tailored to end-users' needs. These services function as decision-making tools, offer incentives for social benefits, and communicate effectively, as highlighted by Scott et al. (2011). The Horizon2020 Impetus project, commenced in October 2021, aligns with the EU's 2050 climate goals, translating commitments into actionable steps for community and planetary protection.Focusing on achieving climate-resilient tourism and implementing the Catalan Climate Change Adaptation Strategy (ESCACC30) in the tourism sector, the project seeks a fundamental behavioral shift. Recognizing the pivotal role of Behavioral Change, the strategy adopts a problem-solving approach based on Michie et al.'s (2013) taxonomy, meticulously examining factors impacting behavioral change, devising strategies to overcome challenges, and enhancing change facilitators, while also incorporating measures to prevent setbacks and address climate change consequences.Inspired by Font et al.'s (2021) methodology, the co-creation process involved public and private stakeholders from Costa Daurada and Terres de l'Ebre actively participating in workshops. These workshops focused on themes such as weather, climate change, tourism, energy, water, and the perception of the beach-dune system. Through this collaborative effort, stakeholders developed indicators shedding light on the climatic potential for various tourism modalities, identifying physical impacts of climate change affecting the attractiveness and vulnerability of the tourist destinations.Proposed measures related to water and energy were classified based on priority and vulnerability. Additionally, the repeat photography method was employed to gather data on citizens' awareness of temporal changes in the beach-dune system within the study area. This approach also provided insights into their perceptions regarding the roles and landscape of the beaches and dunes, ultimately contributing to the development of climate co-created indicators essential for effective climate adaptation in these Mediterranean coastal destinations.
Decadal predictions outperform projections in forecasting winter precipitation over the Mediterranean region
Authors: Nicolì Dario , Gualdi Silvio , Athanasiadis Panos
Published: July 2024

The Mediterranean region is highly sensitive to climate change, having experienced an intense warming and drying trend in recent decades. In the context of decision-making processes, there is a growing interest in understanding the near-term climate evolution of this region. Climate change projections consistently indicate that southern Europe and the Mediterranean region will undergo significantly drier conditions in the latter half of the 21st century. However, if our focus shifts to the next decade or so, as is the case for many stakeholders and decision-makers, do climate change projections remain the best tool for understanding climate evolution during this timeframe? In this study, using retrospective forecasts from eight decadal prediction systems contributing to the CMIP6 Decadal Climate Prediction Project (CMIP6 DCPP) and the corresponding ensemble of non-initialized simulations (historical and projections), we compare the capabilities of the state-of-the-art climate models in predicting the near-term climate anomalies of the wintertime Mediterranean region for some key quantities so as to assess the added value of initialization. Our findings indicate that decadal predictions exhibit higher reliability than projections, particularly over the subpolar gyre for surface temperature and over southern Europe for precipitation. Therefore, their use should be preferred over projections for a decadal time horizon.We also inspect the role of the North Atlantic Oscillation (NAO) index and subpolar sea surface temperature (SP-SST) in influencing the predictability of the Mediterranean climate. Therefore, we develop a statistical model to explore the potential impact of the NAO and SP-SST indices on Mediterranean precipitation predictability. The hybrid approach offers higher predictive skill, suggesting that both oceanic and atmospheric factors contribute to the increased skill in predicting European rainfall and can be potential predictors of Euro-Mediterranean rainfall variability on decadal timescale.