bluuebunny/crossref_metadata_2025 huggingface dataset:
AOD differences analysis Prede-PFR-Cimel on a 11 years dataset at Meteorological Observatory Lindenberg
Authors: Doppler Lionel , Balenzategui Jose L. , Garcia-Suñer Merixtell , González-Sicilia Pablo , Masoom Akriti , Papadimitiriou Nikolaos , Salgueiro Vanda , Karanikolas Angelos
Published: July 2024

Photometers are the most accurate instruments to retrieve the aerosol optical depth (AOD) for a given spectral channel (e.g. 500 nm). There are three main networks of photometers: GAW-PFR (Global Atmosphere Watch - Precision Filter Radiometer) using the instrument PFR (Precision Spectral radiometer), AERONET (AErosol RObotic NETwork): AOD and aerosol properties measurements network using Cimel CE-318 photometer, and SkyNet (SKY Measurements NETwork), using the instrument Prede POM (Precise design Of Meteorological). These three networks use different instruments, different measurement methods, different calibration methods and different retrieval methods algorithms).The Meteorological observatory Lindenberg (MOL-RAO) from German meteorological service (Deutscher Wetterdienst: DWD) in Lindenberg (Tauche, Germany) is the only site worldwide operating permanently the three instruments of these three networks. There is a dataset of 11 years (since 2013) of colocated and synchronized AOD measurements of GAW-PFR, AERONET, SKYNET photometry networks at this station.In this study, supported by COST action HARMONIA and initiated at the COST HARMONIA training school “Sky over BerLin”, we quantify the differences in the AOD from the products of these three different networks, we investigate the sources of these differences, computing the corrections on the optical depth (rayleigh, ozone, NO2) regarding amount of components consider in inputs of the retrieval algorithm and the equation used by the algorithm to consider these corrections. Analizing the temporal and  air mass dependences o the differences and analyzing which differences are artificial (different way of computing with different inputs or equations during the retrievals) or inherent to the measurement itself (instrumental difference, calibration issues). 
ECMWF lightning forecasts evaluation during fire seasons in Portugal
Authors: Campos Cátia , T. Couto Flavio , L.M. Santos Filippe , Rio João , Ferreira Teresa , Salgado Rui
Published: July 2024

Lightning represents only 5-10% of fire causes in Europe and 1-2% in Portugal and correctly predicting its occurrence can help to mitigate large forest fires. In 2016, the European Centre for Medium-Range Weather Forecasts (ECMWF) introduced a parametrization for lightning forecast. Therefore, aiming to assess the feasibility of using ECMWF forecasts in the context of natural wildfires, this study analyses the ECMWF data for mainland Portugal over 4 fire seasons (2019 - 2022). The dataset used is composed by the total average lightning density in 3 hours from the ECMWF and the observation data from the detection network from IPMA and grouped for the same times. The data was also aggregated into horizontal resolution grids of 1⁰ and 0.5⁰. To carry out the statistical analysis, two contingency tables were constructed, and some statistical indices were calculated (e.g., BIAS, Success rate, False alarm rate, Threat score, Equitable threat score, True skill score). The results reveal a Bias score bigger than 1, indicating that model tends to overestimate the lightning occurrence. Moreover, the success rate was about 57.7% (1⁰) and 49% (0.5⁰). The temporal analysis indicated a time lag between both data, with the model starting and ending the prediction earlier than observed. Furthermore, two meteorological patterns were found producing lightning during the period studied: the development of a thermal low overlapping with an Upper Level Low and the passage of large-scale systems. These results show that the ECMWF lightning forecast can be used as an additional tool to prevent natural fires, with the model being able to indicate the days and locations of lightning occurrence. The research was funded by the European Union through the CILIFO project (0753-CILIFO-5-E) and also by national funds through FCT Foundation for Science and Technology, I.P. under the PyroC.pt project (PCIF/MPG/0175/2019).
Urban modification of the atmospheric boundary layer over Paris – insights from intensive ALC profiling observations along a rural-urban transect
Authors: Looschelders Dana , Morrison William , Carrera Manuel , Christen Andreas , Fenner Daniel , Grimmond Sue , Haeffelin Martial , Hilland Rainer , Kotthaus Simone , Legain Dominique , Masson Valéry , Zeeman Matthias
Published: July 2024

Improving understanding of urban atmospheric boundary layer (ABL) processes and dynamics is central to improving the modelling and forecasting of weather, air quality, and thermal comfort, in particular in densely populated urban areas. The ERC (European Research Council) urbisphere-Paris measurement campaign generated extensive in-situ and remotely sensed observations of the ABL from a network of concurrently operated automated lidars and ceilometers (ALC), doppler wind lidars, radiometers, and automatic weather stations to explore surface-atmosphere feedbacks focusing on ABL dynamics upwind, over, and downwind of a metropolitan area.Paris, one of the densest metropolitan areas in Europe, is located ~130 km from the coast in relatively flat orography, making it well-suited to study urban modifications of atmospheric boundary layer dynamics. urbisphere-Paris aims to gather consistent and coherent datasets on the magnitude and interplay of surface heat fluxes, radiation fluxes, aerosol load, and boundary layer dynamics to evaluate and improve next generation numerical weather and air quality modelling approaches.From March 2023 to March 2024 a transect along the predominant wind direction had seven Vaisala CL61 Ceilometers operating. As the transect extended both upwind and downwind of the city centre by 60 km to include the rural periphery, modifications of the ABL aerosol profile, cloud properties, and mixed layer dynamics could be observed as air moves into, across, and beyond the metropolitan area.The transect provides continuous profiles of attenuated backscatter and linear depolarisation ratio, with very high vertical (4.8 m up to 15.4 km) and temporal (every 5 s) resolution. From this other variables are derived, such as mixed layer height (MLH), cloud cover of boundary layer clouds (CC), and cloud base height (CBH). This contribution will present selected cases of spatiotemporal differences in ABL processes along the urban-rural continuum. Wind direction changes the upwind/ downwind effects such as the urban plume. Differences in temporal evolution of the ABL are also explored, including MLH, CC and CBH. These results will help identify both typical and unusual patterns to explore further with high resolution numerical weather prediction models.
Forecast Clarity: A User-Focused Index Framework 
Authors: Sládek David
Published: July 2024

The expanding user base of meteorological forecasts underscores the growing demand for accurate forecast interpretation, particularly among aviation professional users who rely on various applications and models. Meteorologists often face the questions not only about the reliability of these forecasts but also about the changes users observe during forecast updates. This work proposes a framework of indices aimed at providing users with relevant forecast insights tailored to their specific needs. These indices consider factors such as overall suitability for activities, mission requirements, and the reliability of forecast products. For instance, the Warning Related Source Suitability Index (WSSI) assesses the suitability of TAF forecasts in predicting conditions that meet warning threshold values. Vehicle-related feasibility index (VRFI) presents probability that vehicle with its limits will be able to accomplish the mission. The Source Uncertainty Index (SUI) describes the spread characteristics of the product at a specific time and estimates its ongoing uncertainty when continuously observed by the user. These indexes might be expanded or improved, providing potential for the novel interpretation framework.Our research involved testing various methods for determining probabilities from numerical model archives, professional landing forecasts and TAF forecasts. The results indicate the superiority of machine learning methods, which achieved accuracy rates up to 10% higher than conditional probability (98% vs 88%) for aviation indices. The index framework will help simplify the output of increasingly sophisticated systems and evaluate only relevant information from meteorological big data databases. In the area of decision-making processes, the machine-readable nature of these indices supports integration into automated systems. This enables fast and informed decision making in real time. Overall, this open index system aims to enhance the understanding and trustworthiness of forecast predictions, delivering to both amateur and professional users.
The lower atmospheric response to SST sub-mesoscale variability: low level clouds and surface fluxes
Authors: Borgnino Matteo , Storer Alessandro , Meroni Agostino , Desbiolles Fabien , Pasquero Claudia
Published: July 2024

Many processes happen at the air-sea interface. Ocean-atmosphere exchange energy (heat, moisture and momentum), mass (precipitation, evaporation).Ocean sea surface thermal structures affect the stability of the air-column and its properties through dynamical and thermodynamical processes within the marine atmospheric boundary layer (MABL). Such processes severely impact on sensitivity of surface fluxes, wind and cloud cover to fine scale variations of sea-surface temperature (SST). Moreover, nonlinearities in the fluxes of momentum, heat, freshwater and gases make the small scales important.This study addresses the role of the ocean fine scales in north-west tropical Atlantic Ocean air-sea interactions, with the goal of evaluating the MABL statistical response to SST variability using cloud-resolving regional numerical simulations of the atmosphere and ocean. This is to quantify the physical process that can explain the modulation of low-level clouds and surface fluxes by SST variability.Recent field campaign (EURECA and ATOMIC) have collected a wealth of data to study the link between circulation, clouds and air-sea coupling; deSzoeke et al. (2021) and Acquistapace et al. (2022) show that the increased MABL turbulence over warm SST is linked to enhanced low-level cloudiness because the MABL moisture is exported above the lifting condensation level (LCL). They do so in single case studies from in situ (ship) data.Using numerical simulation of such region, we can extend the analysis of the entire EUREC4A region. We found that SST at the sub-mesoscale affects the air column stability and, therefore, the entrainment of dry and outer-MABL air. The main effects of such entrainment are visible in the dynamics of the mixed layer, both in terms of relative humidity (RH) response and in the vertical exchange of horizontal momentum. Changes in RH are reflected on surface fluxes and low-level clouds.
Assessment of SAR offshore wind fields in the Gulf of Lion 
Authors: Dimitriadou Krystallia , Olsen Bjarke Tobias , Badger Merete , Hasager Charlotte Bay
Published: July 2024

The Mediterranean Sea heavily relies on fossil fuels for its energy supply, but the shift toward green energy is imminent. Offshore wind farms represent a pivotal step in this transition. However, deploying these wind farms effectively requires an accurate assessment of the wind potential in offshore areas.Unlike Northern Europe, research on Mediterranean wind energy is sparse due to its intricate topography and bathymetry. The Mediterranean's coastlines, hemmed in by mountain ranges, create unique wind climates, posing challenges for modeling offshore wind conditions. Additionally, existing in-situ observations are limited to specific points.Sentinel-1 satellite Synthetic Aperture Radar (SAR) wind fields can resolve wind variability at sub-km scales. The strength of satellite wind fields lies in the observation of large spatial domains over broad temporal periods. Therefore, this technology holds promise for uncovering the wind resource potential.This study focuses on the Gulf of Lion, located in the NW Mediterranean Sea and currently the Mediterranean's most promising area for floating wind turbine installation. Here, two dominant local winds—the Mistral and Tramontane—prevail. The Mistral, a northerly wind, forms between the Alps and the Massif Central, while the Tramontane, a northwesterly wind, sweeps through the Aude valley between the Massif Central and the Pyrénées.SAR records images of the radar backscatter from the Earth’s surface, which is commonly known as the Normalized Radar Cross Section (NRCS). NRCS values can be used as inputs in a Geophysical Model Function (GMF), along with other radar parameters, to retrieve the SAR ocean wind fields. For the SAR wind speed retrieval, a necessary input is the wind direction, commonly provided by numerical models. This study utilizes SAR wind speed retrievals driven by three numerical model wind directions—GFS and ERA-5 with 27 km spatial resolution, and New European Wind Atlas - NEWA (WRF) with 3 km spatial resolution—over a year-long period. We first compare the three model wind directions against in situ measurements from two buoys located in the greater area of the Gulf of Lion, which are provided by the Copernicus Marin Service In Situ TAC data platform.Then, we compare the in-situ wind speeds against the three SAR wind speeds and the three model wind speeds. Our objective is to determine which SAR-model data synergy best reflects true wind conditions in the area. This study also aims to highlight the benefits of involving satellite-derived wind fields for wind resource estimations in upcoming wind farm areas characterized by complex wind climates.This work is supported by the ESAWAAI project, funded by the European Space Agency under the grant agreement 4000142170/23/DT.
The compound effect of acute respiratory infections and temperatures on mortality in the Czech Republic, 1982–2019
Authors: Borisova Ekaterina , Urban Aleš , Hanzlíková Hana , Plavcová Eva , Kyselý Jan , Kynčl Jan , Ballester Joan
Published: July 2024

Numerous studies have thoroughly documented the contribution of non-optimal temperatures and acute respiratory infections (ARIs) to increased mortality. However, there is still a gap in understanding how these factors interact together to affect human mortality during the cold season, and how this impacts population susceptibility to heat waves in the summer.In this study we conduct an analysis over a period spanning 38 years (1982–2019), utilizing: a) daily all-cause mortality counts across the Czech Republic, b) daily proxies of acute respiratory infections (ARIs) incidence, interpolated from weekly healthcare surveillance data, and distinguished regarding three dominant influenza viruses (A/H3N2, A/H1N1, and B), and c) a suite of weather variables, sourced from E-OBS gridded data, including daily mean, maximum, and minimum temperatures, daily precipitation, daily mean sea level pressure, daily mean wind speed, daily mean relative humidity, and radiation level.To investigate the complex associations between mortality rates, ARI incidence, and weather variability, we employ a distributed lag non-linear model (DLNM) with multiple cross-bases. This approach facilitates the adjustment for confounding meteorological variables and provides a better understanding of their impact as fluctuating confounders. From these refined models, we derived the fraction of mortality attributable to ARIs and low temperatures, offering a quantification of their impact on excess mortality in the cold season. Additionally, we analyse changes in seasonal patterns of mortality according to the meteorological and epidemiological characteristics and assess temporal associations between air temperature and mortality in summer considering factors like intensity of ARI outbreaks and the mean winter temperature in the previous cold season. Our results contribute to better understanding of the links between temperature variability, respiratory infection dynamics and the seasonal variations in mortality.
An advanced bias correction technique for improved Seasonal Forecasts: a focus on extreme events in Southern Africa
Authors: Trentini Laura , Venturini Marco , Guerrini Federica , Dal Gesso Sara , Calmanti Sandro , Petitta Marcello
Published: July 2024

In the context of climate change adaptation, the use of climate predictions is steadily gaining importance. One critical challenge to consider when dealing with climate simulation outputs is the systematic bias affecting the modelled data. While bias correction methods are commonly employed in impact models to assess the effect of climate events on human activities, their effectiveness is often reduced in the case of extreme events, due to the scarcity of data for these low-probability and high-impact phenomena. This study, conducted as part of the European project FOCUS-Africa, is dedicated to advancing innovative climate services in the southern regions of Africa. Our primary objective is to respond to the needs of risk assessment studies, focusing on the impact of extreme events and their implications for climate change adaptation. To this end, we designed a novel bias correction method to consistently correct extreme events of temperature and precipitation, but is adaptable to other climate variables, such as wind speed. Our approach conceptually extends one of the classic Quantile Mapping (QM) methods by improving the description of the tail ends of the distribution through a generalised extreme value distribution (GEV) fitting. Our methodology also incorporates a downscaling component. QM is indeed frequently both as a bias correction method and for downscaling simulations to finer observed scales. Therefore, our method not only corrects the climate data but also enhances the raw resolution of the model outputs (typically around 100 km) to match the 9 km grid of the observational reference. In this study, we applied our technique to daily mean temperature and total precipitation data from three seasonal forecasting systems: SEAS5, System7, and GCFS2.1, developed respectively by ECMWF, Météo-France, and DWD. The bias correction efficiency was tested over the Southern African Development Community (SADC) region, which includes 15 Southern African countries. The performance was verified by comparing each of the three models with a reference dataset, the ECMWF reanalysis ERA5-Land. The results reveal that this novel technique significantly reduces the systematic biases in the forecasting models, yielding further improvements over the classic QM. For both the mean temperature and total precipitation, the bias correction produces a decrease in the Root Mean Squared Error (RMSE) and in the bias between the simulated and the reference data. After bias correcting the data, the ensemble forecasts members that correctly predict the temperature extreme increases. On the other hand, the number of members identifying precipitation extremes decreases after the bias correction, highlighting the challenge of obtaining robust statistics due to the lack of information about extreme events.
Climate Mitigation Pathways for Cities – enabling a just transition through quantified actions?
Authors: Bügelmayer-Blaschek Marianne , Millonig Alexandra , Zach Martin
Published: July 2024

As Climate Change challenges threaten future quality of life, urgent action to mitigate CO2 emissions as well as to adapt to current and future risks is mandatory. Cities are crucial for both areas: mitigation, because 2/3 of the world wide population live in urban areas and thus cause XX emissions; adaptation: because the settlements structure, mainly sealed areas, enhances the negative effects of climate change. Within the Horizon Europe Research and Innovation Action KNOWING [1] climate mitigation pathways, which represent timelines of specific interventions, are compiled for different regions.Urban areas are a core region type within KNOWING as they are particularly vulnerable towards climate change. Over the past years cities have responded by defining strategies regarding mitigation and adaptation that identify measures for specific sectors. Although there is vast knowledge with respect to future impacts and possible mitigation and adaptation measures within different sectors (e.g. transport, energy, etc.), implementation remains inadequateExisting strategies often tackle the different sectors separately, thus ignoring possible spill-over and rebound effects of one measure taken to other areasKNOWING develops a framework for defining Climate Mitigation Pathways based on understanding and integrated assessment of climate impacts, adaptation strategies and societal transformation. The modelling framework will be used to assess the interrelations between potential risks of climate responses, i.e., public and private adaptation and mitigation strategies. For instance, the installation of air conditioning can improve living conditions inside, but it also has a two-fold negatively impact due to its heat and CO2 emissions.To quantify the interrelations, the chosen comprehensive approach builds upon a system dynamics (SD) model for quantifying cross-sectoral influences of measures taken in different sectors (e.g., energy, mobility, land use, construction, agriculture) affecting the overall emission budget. Therefore, specific so-called domain models for mitigation (e.g. energy demand model MAED-City, energy supply IES-opt) and adaptation (e.g. urban climate PALM4U, flooding model SFINCS, ICM-Infowork) are applied, fed with high resolution (5x5km) WRF input data. Based on this systems perspective, mitigation pathways along optimised combinations of interventions in the different sectors are developed. The framework also includes a coping behaviour model that provides guidance on how measures can be implemented in an equitable way to enable a just and broadly supported transition.
Emission and short range re-deposition of ammonia on grassland determined by an inverse dispersion method
Authors: Ammann Christof , Häni Christoph
Published: July 2024

Methods to measure gaseous emissions from spatially confined sources (e.g. from plots with slurry application or grazing excreta) often rely on atmospheric dispersion models to relate downwind concentration or flux measurements to the respective emission rate. Since ammonia (NH3) is very reactive and water soluble, it adsorbs readily to surfaces leading to a significant loss due to re-deposition, which affects concentration and surface-atmosphere exchange measurements even at short distances from the source.In the present study, a backward Lagrangian stochastic (bLS) model was used, which has been enhanced to incorporate dry re-deposition. Controlled release experiments were carried out at a grassland site with a parallel release of ammonia (NH3) and methane (CH4) at a defined release rate through a source grid with 36 critical orifices at ground level. NH3 and CH4 concentrations and vertical fluxes (by eddy covariance) were measured downwind of the source and the bLS model was used to infer the emission fluxes from the measured quantities, with and without considering dry re-deposition. When disregarding deposition, the median recovery fractions (ratios between the observed emission and the known release rate) were close to 100% for CH4 but considerably lower (between 32% and 72%) for NH3. The difference in the recovered fraction of NH3 compared to CH4 could be attributed to dry deposition loss between the source and the concentration measurements. In a second step,  surface deposition velocities were derived to match recovered fractions of NH3 and CH4. This resulted in median NH3 deposition velocities (related to 2 m height) between 0.6 and 1.7 cm s-1. Compared to literature values this is in the expected range of deposition velocities for grassland sites.
The Meteorological Observations of Jovellanos at Bellver Castle (Mallorca, Spain)
Authors: Vaquero José Manuel
Published: July 2024

The development of meteorology in Spain began in the 18th century, similar to other European countries. Anduaga [1] has shown that three communities fostered the first systematic meteorological observations [2]. Firstly, astronomical observatories in Cádiz and Madrid promoted such observations. Additionally, the medical community made notable efforts in this regard, and lastly, the Economic Societies of Friends of the Country propelled meteorological studies related to agricultural activities.Gaspar Melchor de Jovellanos (5 January 1744 – 27 November 1811) is a major figure of the Age of Enlightenment in Spain. He is well-konw as statesman and author. Until now, no one has highlighted Gaspar Melchor de Jovellanos's interest in atmospheric sciences despite his evident connection with the Economic Societies of Friends of the Country and agronomic sciences. I began reading his correspondence (Complete Works, volumes II-IV [3]) hoping to find numerous references to weather or climate, and the initial results were rather disheartening. However, I continued consulting his diary (Complete Works, volumes VI-VIII) and found an extensive collection of meteorological comments.The surprise was immense when I saw in one of the last notebooks of his diary, the twelfth, a complete set of systematic meteorological observations made during his stay at Bellver Castle in Mallorca for almost a year (which practically coincides with the year 1806). Therefore, the aim of this study is twofold: I will demonstrate Jovellanos's immense interest in meteorology and describe in detail the thermometric and barometric records obtained by Jovellanos at Bellver Castle [4].[1] Anduaga Egaña, A. (2012) Meteorología, ideología y sociedad en la España contemporánea (Madrid: CSIC).[2] Domínguez-Castro, F., Vaquero, J.M., et al. (2014) "Early Spanish meteorological records (1750-1850)". International Journal of Climatology 34, 593-603.[3] Jovellanos, G.M. (1984-2022) Obras completas, 15 volumes (Gijón: KRK Ediciones).[4] Vaquero, J.M. (2023) "Las observaciones meteorológicas de Jovellanos en el castillo de Bellver" Revista Española de Física 37(3), 22-27.
Streamflow changes in the European Alps indicate increasing drought risk from past to future
Authors: Guo Rui , Nguyen Hung , Galelli Stefano , Ceola Serena , Montanari Alberto
Published: July 2024

Relatively short instrumental streamflow records in the European Alps limit our understanding of the long-term variability of streamflow, which could greatly impact freshwater resources management. To improve the accuracy of future scenarios for rare extreme events that recently impacted severely important water resource systems and communities at the global level, a better understanding of past climatological and hydrological information is essential. Tree-ring-based proxy data have proven to be a viable opportunity for reconstructing streamflow in different regions. Here, the station-based streamflow of six rivers originating from the European Alps are reconstructed dating back to the year 1100 by using a climate-informed framework. Additionally, we use paleo simulations and future projections from state-of-the-art CMIP6 and PMIP4 climate models to study past and future streamflow changes, including the characteristics of rare extreme events like multi-year droughts and floods. By integrating proxy-based reconstructions, climate model simulations and projections, and observations, the changes in streamflow and rare extreme events in the European Alps are put into a millennial perspective covering the past nine centuries and one century into the future. Our findings reveal that the observed worst annual streamflow deficit events are among the most severe in the past 900 years. In addition, climate models project a coherent decrease in streamflow for all the basins, which indicates an unprecedented drought condition in the future. Our framework offers a unique opportunity to assess the risk of extreme events for rivers in the European Alps, thus playing a crucial role in developing robust water management strategies for climate change adaptation.
Turbulent boundary layer measurements near the surface below the jet maximum in a katabatic wind along alpine slope.
Authors: Brun Christophe , Bessem Wilfred , Dublanche Ambre , Lagauzère Muriel , Pioz Stéphane
Published: July 2024

Katabatic winds are gravity flows generated at night by radiative cooling at the ground surface. They are mainly observed in winter during anticyclonic weather episodes associated with stratification and temperature inversion in the lower troposphere. Although their intensity is relatively low, they play a major role in areas with complex terrain, as they systematically contribute to the generation of cold air pools in the valley. There are a large number of in situ observations of the katabatic process along gentle slopes such as those reported in valleys or glaciers but far fewer along steep alpine slopes in the mountains. The katabatic wind consists of a turbulent wall jet along the slope coupled to a turbulent thermal boundary layer cooled at the surface, both subject to the effects of gravity. Little is known about the flow region below the maximum jet velocity, very close to the surface. It is aimed here to deepen general knowledge of the turbulent properties of katabatic winds in this region, which is rarely observed in situ for technical reasons. We further propose and validate a set of laws of the wall necessary for the definition of surface boundary conditions for the appropriate use of regional models over complex terrain. A recent campaign of in situ measurements has been carried out on 3-15 February 2023 in the French Alps near Grenoble. A continuous set of measurements is available from the ground up to a height of 1m, i.e. close to the maximum height of the jet, using a multi-hole 3D velocity probe mounted on a high-precision vertical displacement system. Measurements were taken from z=2 mm close to the snow surface (z+ = 20) to z=1 m high (z+ = 10000). In addition, a thermocouple and an infrared radiation probe were used to determine the temperature profile at the same vertical positions. Firstly, direct measurement of the w velocity component normal to the slope shows a significant contribution towards the ground of the order of 10% of the maximum upslope velocity of the katabatic jet. The trend is well described by a simplified analytical model derived from the Navier-Stokes equations. This model reveals the main role of buoyancy close to the surface, quantified by the strong cooling at ground level and the steep slope. Secondly, measured temperature profile deviates from the logarithmic distribution expected on flat ground. This study will be transposed to a more comprehensive planned as part of the European alpine observation campaign TeamX in 2024-2026 in the Austrian Alps near Innsbruck. A pre-installation was carried out this winter 2024 on the slopes overlooking the Inn valley at InnBox station NF27.
Application of Multi-source Observations in a Heavy Rainfall Case Analysis
Authors: Liang Xudong
Published: July 2024

   On 20th July 2021, an extreme rainfall event occurred at Zhengzhou city in China with maximum hourly rainfall of 201.9 mm and 24h accumulated rainfall of 624.1 mm at Zhengzhou weather station. From 8:00 (BJT) 17th to 8:00 (BJT) 23rd, the maximum accumulated rainfall reaches 1122.6 mm at the Hebi Science and Technology Innovation Center Weather Station.In this study, multi-source observations including dense surface observations, Doppler weather radar network, radio sounding, and wind profiler were used to analyze the evolution of the rainfall process. Quality control and data analysis methods were implemented to check and merge the individual observations.The dense observations provide an opportunity to analyze the distributions of the rainfall, the vortex, convergence zone, vertical wind share, and the interaction between the winds and mountains. Surface observations and radar retrieved winds provide a three dimensional wind field with horizontal resolution of a few kilometers and vertical resolution of five hundred meters. More details were shown by the data. For example, the vortex is not obvious in surface observations in 19th and 20th , while radar retrieved winds shown a vortex structure in higher levels. The mountains enhanced the convergence of lower level winds which are important for forming the convective storms. The nudging and the 4Dvar methods were tested to assimilate the dense observations. Based on the experiments, high resolution reanalysis data were produced using the dense observations and WRF model. More details about the heavy rainfall case will be shown in this study based on hourly observations and the reanalysis data.
Fog Detection Based on Microwave Signal Attenuation
Authors: Seo Ziwoo , Kwon Byung Hyuk , Kim Sang Jin , Lee Kyung Hun , Bae Hyeok Jin , Koo Yu Jung , Kim Geun Mu
Published: July 2024

Fog is a meteorological event characterized by visibility reduction to under one kilometer, posing a primary threat to maritime and land vehicle navigation. Visibility and present weather sensors have been introduced to measure fog, however single-point observation cannot determine the horizontal scale of fog. Microwave links have been validated effective in detecting rainfall and estimating rainfall quantitatively by collecting attenuation information from microwaves. Attenuation of microwaves is not limited to precipitation but also occurs in the presence of fog, dust and snow; the higher the frequency, the more pronounced the attenuation effect due to fine particles. This study aims to collect signal data received through a 24 GHz microwave link under various weather conditions and compare those with observed meteorological data to determine the presence or absence of fog and sea fog. This microwave link has a transmitter output of 20 dBm, and the maximum received signal strength appears to be around -100 dBm under clear weather conditions at a distance of 10 km. It was installed over a path length of 11.4 km that crosses the bay between Boseong and Goheung, optimizing it for detecting weather changes. Additionally, A spectrum of the attenuation signal is expected to provide information that can classify clear skies, rain, and fog. This study suggest potential application in monitoring fog with difficult road weather conditions. Furthermore, effective detection with high temporal resolution is expected in observation gap areas, such as urban centers, islands, and mountainous areas. As the UAM (Urban Air Mobility) era arrives, the weather enterprise needs to develop and adapt benchmarks for creating and validating finescale weather guidance for urban aviation. Microwave links would be an answer to this challenge.
Diverging estimates of future global wetland areas under warming scenarios
Authors: Kim Daeha , Kim Eunji
Published: July 2024

Despite its critical importance in the global cycles of energy, water, and carbon, the extent of global wetlands remains highly uncertain. A straightforward approach to estimating global wetland areas is to relate the topographic wetness index (TWI) with groundwater or climate variables. In this study, we examined multiple TWI-based methods for estimating wetland areas across historical and future timeframes. First, we identified inland wetlands using global TWI data combined with soil moisture data from an advanced reanalysis system. For comparison, we also generated three other sets of wetland area estimates using monthly precipitation and potential evaporation (Ep) data from the same system, applying three different Ep formulas to assess the sensitivity of wetland areas to changes in surface resistance. We extended this methodology to multiple Earth system models (ESMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6) to explore the impact of atmospheric CO2 concentrations on wetland dynamics. Our findings indicated that increases in historical atmospheric CO2 had a minimal impact on TWI-based wetland areas. However, their influence is expected to become more significant even under a sustainable emission scenario by the mid-2050s. We also found that CMIP6 ESM soil moisture projections show smaller changes in wetland areas compared to those estimated using a traditional Ep formula. This highlights potential inconsistencies between future wetland projections based on climatic variables and those derived from soil moisture projections.Acknowledgements: This work was supported by Korea Environmental Industry & Technology Institute (KEITI) through Wetland Ecosystem Value Evaluation and Carbon Absorption Value Promotion Technology Development Project (2022003640001), funded by Korea Ministry of Environment (MOE). 
Evaluation of Flood Risk in South Korea Through Time Series Analysis of Precipitation Data
Authors: Choi Seungcheol , Choo Kyungsu , Kim Byungsik
Published: July 2024

The recent increase in extreme and intense rainfall events is a pressing concern, mainly due to the effects of climate change. These heavy downpours contribute significantly to urban damage, triggering floods, landslides and other related disasters. Such natural disasters pose serious risks to human life and infrastructure. Seoul, South Korea, is particularly vulnerable. In 2001, for example, the city recorded a staggering 273 mm of rainfall in a single day. More recently, in 2011 and again in 2022, Seoul suffered extensive urban flooding. These events were largely due to the inability of rivers and stormwater systems to handle the sudden deluge, which exceeded the design frequencies that these infrastructures were originally built to withstand. As climate change accelerates, the frequency of such extreme weather events is expected to increase, requiring advanced research to fully understand their impact on urban infrastructure. This includes vital structures such as dams, embankments and stormwater pipes, all of which require robust designs to cope with such unprecedented environmental stress. This study focuses on collecting and analysing rainfall data from meteorological stations across Korea. By using the Generalised Extreme Value (GEV) distribution along with time series analysis, our research aims to meticulously map flood risk patterns. These statistical methods are crucial for understanding and predicting the behaviour of rare but severe weather phenomena. In addition, our research calculates flood loads based on specific return periods and design frequencies. These calculations are essential for designing infrastructure that can withstand future climatic challenges, thereby ensuring the safety and resilience of urban environments against the increasing threat of flooding. This comprehensive approach not only highlights historically flood-rich or flood-poor periods, but also assists in the strategic planning and upgrading of urban infrastructure to cope with the realities of climate change. AcknowledgementThis research was supported by a (2022-MOIS63-002(RS-2022-ND641012)) of Cooperative Research Method and Safety Management Technology in National Disaster funded by Ministry of Interior and Safety(MOIS, Korea).
An Evaluation of the Likelihood of Rainfall-induced Inundation Using the Impact-Based Forecast Model with Heavy Rainfall Damage Data
Authors: Kim Eun-Jin , Bae Jeong-Ho , Park Byoung-Kwon , Jung Hye-Hoon
Published: July 2024

  In recent years, the intensity and frequency of hazardous weather events, such as heavy rainfall, have been increasing due to the influence of climate change. However, even under similar severe weather conditions, outcomes can vary depending on temporal and topographical features. Therefore, it is important to be aware of the potential impacts when facing the risk of sudden weather disasters and to take proactive measures.  From August 8th to 10th, 2022, South Korea experienced heavy rainfall, with hourly rainfall exceeding 100mm and daily rainfall exceeding 100-300mm. This resulted in widespread flooding of roads, surrounding the residential and commercial areas, leading to over 5,000 evacuees and 14 fatalities over the Metropolitan area. The damages were significant due to the intense rainfall within a short period. The Korea Meteorological Administration (KMA) has constructed a database of damages caused by rainfall, including this heavy rainfall case. Rainfall damages were collected from the National Fire Agency, the National Disaster Management System (NDMS), and newspapers. Following that, meteorological data (wind speed, temperature, and accumulated precipitation) from Automatic Weather Stations (AWS) was incorporated. Based on this database, the damages caused by heavy rainfall were classified and analyzed.  The Impact-Based Forecast model for heavy rainfall has been developed to provide region-specific likelihoods of rainfall-induced inundation. This study examined the predicted results from several numerical weather prediction models for heavy rainfall in this case. It is expected that the results of this study will contribute to the production and provision of preemptive rainfall-induced impact information for disaster preparedness.
Two types of cold surges of Korea and their predictability in Korea Integrated Model (KIM) 
Authors: Yeo Sae-Rim , Seol Kyung-Hee
Published: July 2024

Extreme cold events in East Asia have significant socio-economic impacts, and accurate prediction is crucial for effective risk management. Understanding cold surges requires consideration not only of their intensity but also their duration. Some cold surge events are notable for their prolonged duration. Meanwhile, cold surges accompanied by abrupt temperature fluctuations have become increasingly frequent in recent years. These drastic cold surges pose substantial risks to human lives and energy supply. In this study, cold surge events in Korea are classified into two types based on their temporal characteristics. Prolonged type cold surges last about three weeks, while drastic type cold surges are defined by a difference of 8˚C or more between the lowest and highest temperatures within a three-week span. It is observed that a trough over East Asia stagnates due to a blocking high over the northeastern Pacific under negative Arctic Oscillation conditions, leading to prolonged cold surges. Conversely, drastic cold surges occur in association with the Madden Julian Oscillation (MJO). Specifically, when the MJO phase spans through 8-1-2-3, warm conditions over East Asia are followed by cold surges. The predictability of these features in the Korea Integrated Model (KIM) has been investigated. KIM demonstrates skillful prediction capability by capturing both types of cold surges within a 2-week lead time. However, as the forecast lead time increases, the predictability of drastic type cold surges tends to surpass that of prolonged type. This is attributed to the better predictability of tropical convection compared to blocking over the northeastern Pacific. This study will provide detailed descriptions of the dynamical characteristics of the two types of cold surges and their subseasonal predictability sources.
Estimating en-route turbulence using ADS-B aircraft data
Authors: Leung Christy Yan-yu , Leung Hok To
Published: July 2024

Aviation turbulence is a hazardous weather phenomenon that affects aviation safety and operations. It can be in the form of convective induced turbulence (CIT), clear air turbulence (CAT), mountain waves or in relation to low level jets. Currently, observations of aviation turbulence are based on either reports from pilots or automated observations from the equipment on board of aircraft. Pilot reports were scarce and could be subjective. Besides, due to the wide range of aircrafts deployed by different airlines, not all aircraft were equipped with automatic equipment to measure turbulence. As aviation traffic recovers, the volume of navigation information broadcasted by commercial aircraft has also increased significantly. The Observatory has installed an Automatic Dependent Surveillance - Broadcast (ADS-B) reception system at Tai Mo Shan Weather Radar Station to track ADS-B equipped aircraft within a range of approximately 500 km. This study attempts to identify and estimate turbulence from these ADS-B signals with an aim to expand turbulence observation over the ADS-B coverage. The analysis would be based on the vertical acceleration and attitude information extracted from ADS-B aircraft data. As aircraft maneuvers would induce noise to the turbulence signal, an algorithm was developed to first identify the en-route phase of the aircraft. As an initial step, the study focused on the en-route phase of aircraft only. Several methodologies, including frequency analysis, peaks analysis, etc., were developed to derive turbulence information from ADS-B data. The results were then compared with the observations from flights that encountered turbulence in 2023. The comparison analysis using different methodologies and their limitations would be discussed. Such turbulence detection algorithm has the potential application on the provision of real-time turbulence information within the ADS-B coverage to aviation users.
Power disruption risk analysis in Portugal associated with extratropical cyclones
Authors: Liberato Margarida L. R. , Gonçalves Ana , Loureiro Sílvia , Nieto Raquel , Correia Marques Margarida
Published: July 2024

The growing increase in frequency and intensity of extreme weather events (EWEs) has a wide impact on energy systems and consumers, such as energy transmission infrastructures - namely overhead power lines (OPL). The main objective of this work is to assess recent high-impact storms and to present the methodology of risk analysis of the extreme weather events on power outages in Portugal. The considered events are windstorms, snowstorms and heavy precipitation associated with extratropical cyclones. In this study, a comprehensive assessment of these events, synoptic conditions and large-scale dynamics are investigated using the ERA5 reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF). Furthermore, the level of risk associated with each of the identified events is classified according to the probability of occurrence and consequences, in a risk matrix, and through the cause-and-effect analysis. It is shown that, in Portugal, the extreme wind – corresponding to level 11 of the Beaufort Wind Force Scale, that is, values equal to or higher than 105 km h-1 – is the main factor that provoked the OPL disruption, between 28% and 40% of analyzed events associated with windstorms. Considering the occurrence of compound events - wind and rain - the probability of damage to OPL is between 21% and 30%; for wind and ice, it is 3%–5%. EWEs represent increasing serious risk for electrical systems, and thus this study highlights the need to develop effective solutions to minimize the associated impacts, such as the modification and upgrade of the current design and engineering standards, and electrical network monitoring. References:Gonçalves, Ana, Margarida Correia Marques, Sílvia Loureiro, Raquel Nieto, and Margarida L.R. Liberato (2023) "Disruption Risk Analysis of the Overhead Power Lines in Portugal", Energy, 263, 125583. https://doi.org/10.1016/j.energy.2022.125583Gonçalves, A.C.R., Nieto R., Liberato M.L.R. (2023) "Synoptic and Dynamical Characteristics of High-Impact Storms Affecting the Iberian Peninsula during the 2018–2021 Extended Winters", Atmosphere, 14, 1353. https://doi.org/10.3390/atmos14091353 Acknowledgements:This work is supported by the Portuguese Science and Technology Foundation through the projects WEx-Atlantic (PTDC/CTAMET/29233/2017, LISBOA-01-0145-FEDER-029233, NORTE-01-0145-FEDER-029233) and UID/GEO/50019/2019. FCT is providing for Ana Gonçalves doctoral grant (2021.04927.BD). This work is supported by national funds by FCT - Portuguese Foundation for Science and Technology, under the project UIDB/04033/2020(https://doi.org/10.54499/UIDB/04033/2020). The EPhysLab group is also funded by Xunta de Galicia, Consellería de Cultura, Educación e Universidade, under project ED431C 2021/44 “Programa de Consolidación e Estructuración de Unidades de Investigación Competitivas.