bluuebunny/crossref_metadata_2025 huggingface dataset:
Ability and Sensitivity of WRF configurations in climate mode to represent urban heat waves' characteristics observed over Paris area during summers 2022 and 2023
Authors: Bastin Sophie , Kotthaus Simone , Fita Lluis , Lalonde Morgane , Haeffelin Martial
Published: July 2024

The summer of 2022 has experienced several heat waves that were observed over Paris area by a unique network of instruments set up as part of several measurement campaigns gathered under the PANAME 2022 label. In particular, Advanced remote sensing instruments were deployed in a network of unprecedented detail to gather novel profile observations of temperature, wind and aerosol, allowing to characterize the vertical, spatial and temporal variabilities of the atmospheric boundary layer.The first analyses of these observations were able to highlight the complexity of the processes involved to explain the spatial and temporal variability of temperatures measured during the heat waves of June and July. In particular, marked differences between urban and rural areas are noted, and a high variability in boundary layer heights exists over the period. Wind Doppler lidar and microwave radiometers show the establishment of nocturnal low level jets on some nights and the entrainment of warm tropospheric air in the boundary layer at the end of the period in July when the warmest temperatures were measured. The summer 2022 campaign has also been complemented by a summer 2023's one. The aim of this study is to take advantages of this observational network to better assess the ability of the WRF model torepresentthespatialandtemporalvariabilitiesof urban heatwavesattheresolution of 3km, which is the horizontal resolution used to perform convective-permitting climate simulations. An assessment of the capability of these simulations to study the interactions between climate and urban areas is needed to ensure that vulnerability of cities to climate change and the implementation of specific adaptation policies to make cities more resilient to extreme events can be evaluated with this tool. A set of simulations(3km) was carried out with different configurations and physical parameterizations to test the sensitivity of the WRF model. In particular the role of a better description of cities using WUDAPT dataset and the activation or not of an urban scheme - which makes it possible to better take into account the urban effects related to the density of buildings, their heat capacity, their roughness etc...- will be analyzed.
Reassessing Ireland’s maximum air temperature record value and the monthly maximum air temperature records for June, July and August
Authors: O'Sullivan John , Curley Mary , Kelly Ciarán , McGovern Jonathan
Published: July 2024

It is essential to have validated and trusted records of past climate extremes.These records are used by planners and policymakers to help them make informed decisions regarding many different sectors - from construction projects to health budgets, from environmental legislation to infrastructure planning, for example.They are also used to tune and improve climate models, leading to more reliable future projections in a changing climate. Assessing and improving on the abilities of climate models to reproduce these (by definition) rare events, provides a stronger basis from which better informed mitigation and adaptation measures against such potential future climate extremes can be taken.In this research, we present the comprehensive re-evaluation process of the Irish national maximum air temperature and the records for the months of June, July and August.For records prior to 1961, we use newly digitised historical climate data from the Met Éireann archives and integrate advanced 20CRv3 sparse-input reanalysis data, station metadata, historical newspaper articles, and contemporaneous references from the examined timeframes. For more recent records, we use climate data from the Met Éireann database and integrate the most recent ECMWF reanalyses products, along with all relevant metadata for our analysis. We also employ time series methods and extreme value theory to help us assess the veracity of the records.The result of this study will be a list of validated maximum air temperature summer monthly records for Ireland. This process will then be applied to other months and other climate variables in future work.This research underscores the significance of data rescue efforts in advancing our understanding of past climate extremes, and advocates for continued digitisation and analysis of historical climate data and metadata. By refining national air temperature records through the integration of historical data and advanced reanalysis techniques, the research contributes to a more comprehensive understanding of climate dynamics.
Comprehensive Application Analysis of Multi-source Data in A Supercell  Process in Beijing
Authors: He Na , Zhou Xuan , Tian Ye , Chen Mingxuan , Lei Lei , Liu Ke
Published: July 2024

In this paper, conventional observation data, Fengyun-4 satellite, wind profile radar, S-band dual-polarization Doppler radar, lightning positioning system data, automatic weather stations combined with radar four-dimensional variational assimilation system are used to comprehensively analyze a supercell storm in Beijing on June 4, 2022. The results show that this supercell is triggered by a cold front. Based on the fact that the observation data has the forecasting potential for the occurrence of severe convective weather, the triggering mechanism and development process of supercell is analyzed by using multi-source data. Vertical wind shear and the change of warm and cold advection in vertical direction based on wind profile radar can help forecasters understand the change characteristics of mesoscale environment before the occurrence of strong convection.S-band dual polarization radar can effectively identify the types and characteristics of severe convection. The simulation of different stages of the occurrence and development of supercell by Variational Doppler Radar Analysis System (VDRAS for short)  shows that the collision between thunderstorm outflow and ambient warm and humid air leads to the rapid development of supercell and the right shift feature.The analysis of vdras data can effectively judge the characteristics of thunderstorm structure and development stage, which provides an important reference for the future occurrence and development trend of thunderstorm. The increase time of lightning frequency detected by lightning positioning system is advanced to the occurrence time of severe convective weather, with the advance is 7 min to 58min. The joint application of the above multi-source data has a good guiding significance for the nowcasting and early warning of sudden severe convective weather.
Exploring the probability of occurrence of the present-climate deadliest heatwaves in Spain in the mid- and end-century
Authors: Salvador Coral , Fernández-Alvarez José C. , Gimeno-Sotelo Luis , Alvarez-Socorro Gleisis , Gimeno Luis , Nieto Raquel
Published: July 2024

Spain is a country located in Southwestern Europe highly vulnerable to different extreme weather-related events such as heatwaves, droughts, and wildfires, causing detrimental effects on the environment, economy, and society. Under projected scenarios, the assessment of the exposure and vulnerability to these phenomena, and particularly to the most impactful events, is a priority to improve management and adaptation measures. Following the framework of the European project titled “Extreme meteorological and hydrological risk in Spain: impact assessment, future scenarios and tools to improve resilience and adaptation to climate change (EXMERISK)”, we aimed to conduct a high-resolution analysis identifying specific types of heatwaves linked to a higher number of deaths in Spain and estimating their probability of occurrence in future periods simulated under the SSP585 scenario (2036-2065, mid-century, and 2071-2100, end-century). Daily non-external, circulatory, and respiratory mortality for all population in Spain and separated by sex groups were provided by the Spanish National Institute, between 1985 to 2014. We used Weather Research and Forecasting (WRF) forced with ERA5 reanalysis and the outputs of the Community Earth System Model V2 (CESM2) to obtain dynamic simulations of climatic variables. Heatwaves were defined following the Spanish Meteorological Agency criteria (AEMET), in which for at least three consecutive days daily maximum temperature exceeded the 95th percentile between July-August and affecting at least 10% of the area under study. We determined specific characteristics of heatwaves linked to a higher number of deaths in Spain and estimated the probability of occurrence of future heatwaves of durations and magnitudes equal or higher than those associated with them. This study has relevant implications in the public health field, to better understand the expected occurrence of heatwaves which may be more impactful in terms of death and develop further measures to reduce the health burden and vulnerability associated with climate change.
Stratocumulus variability in global storm-resolving models
Authors: D'Amato Dragaud Ian , Nowak Jakub , Dziekan Piotr , Lee Junhong , Mellado Juan Pedro , Stevens Bjorn
Published: July 2024

Stratocumulus clouds are important for the Earth's planetary albedo and play a central role in determining Earth's sensitivity to forcing. Recent global-coupled simulations at kilometer-scale resolution in the atmosphere and the ocean, conducted in the framework of the H2020 nextGEMS project, offer opportunities to study cloud processes, their environmental factors, and the possibility of using observations to verify them. We investigate the representation of stratocumulus clouds by the ICON and IFS models and it allows us to compare both model strategies. The former uses less parameterizations to better understand process interactions and the latter considers shallow and deep convection schemes and more sophisticated parameterizations, which allows for better tuning. The results of this study show the value of both. The four-year simulations were assessed in terms of the top-of-atmosphere (TOA) albedo and the vertical structure of the atmospheric boundary layer in the coastal and offshore regions of Namibia, Peru and California. We used satellite data from the CERES-EBAF TOA dataset as an observational reference for the albedo. Both simulations reproduced the mean horizontal distribution and seasonal cycle of TOA albedo and the typical vertical structure of the low atmosphere. However, we found some discrepancies. IFS represented the stratocumulus regions slightly displaced towards the southwest, and lower albedo over the coastal regions in comparison with CERES. ICON represented too much cloud liquid water and uses a cloud inhomogeneity factor to reduce the albedo. Analysing the modeled cloud variability in space and time we found that ICON correctly reproduced the observed diurnal variation and the decrease in cloud depth towards the coast. However, the model simulated a more cellular than stratiform character of the cloud field, compared with satellite images.
Meteorological zones delimitation in Andorra through glacial orography
Authors: Martín Guillem , Sinfreu Gemma , Molne Toni , Rivero Lucia
Published: July 2024

The Principality of Andorra (468 km2), in the Pyrenees chain, has an orographic complex terrain with the lowest point at 843 m and the highest point at 2.943 m. In a straight line, there is a distance of 17,5 Km between these two points. Hydrologically, the country of the Pyrenees has the headwater of 5 rivers basins (Arieja, Valira d’Orient, la Llosa, Valira del Nord and Riu d’Os). Glacial modelling produced by the last ice age (20.000 years ago) determine the atmospheric communication between different headwaters and valleys.  The influence of glacial modelling in atmospheric communication is also present between the headwaters valleys that are in the French or Spanish borders.The meddling of the Arieja and Soulcem valleys in southern points than the average line of mountain chain border between Mediterranean and Atlantic, gives some Atlantic climate characteristics in the north zone of the country in terms of precipitation. The most frequents patterns that cause the most important differences on weather type and precipitation accumulation are these that have Atlantic or northern latitude origins. But we also have other patterns with typical weather types or precipitation accumulation in other river basins when the atmospheric instability comes from others orientations (west, south-west, south, south-east or east). The north-east atmospheric flux is the only one which causes dry effects in Andorra due to the continental configuration.The form and the orientation of the glacial valleys determines the meteorological phenomena extension. Therefore, we can define 3 meteorological zones according to the total precipitation accumulation, the valleys orientations and the altitude. These zones are: north, centre and south. The amount of precipitations and altitudinal temperature variations determines the limit of these zones, always in the borders of secondary river basins.Forecasting weather conditions in a small country is an amazing job that demands a great knowledge of the geography and the finest atmospheric models. Vertical profiles and water saturation column become essential tools.
The Effect of Outdoor Thermal Conditions on Daily and Seasonally Pedestrian Behavior in Various Streets of Mediterranean City
Authors: Potchter Oded , Cohen Pninit , Ferenez Michal , Mandelmilch Moshe , Omer Itzhak
Published: July 2024

In recent years, the concept of urban ‘walkability’ has become common in multiple fields connected to urban geography, urban planning, and has both social and environmental benefits. In the last decade urban climatology research has paid more attention to the effect of urban outdoor thermal conditions on walkability. Walkability can be defined as the extent to which the built environment enables, supports and encourages walking, by providing pedestrians on the move friendly and safety environment, visual interest in street network’ and thermal comfort This study examined the relations between outdoor thermal conditions and walkability in the Mediterranean City of Tel Aviv, aiming to: (1) assess the relationship between urban morphology at street level on the objective and subjective thermal comfort of pedestrians on the move, (2) quantify the influence of land use and centrality of streets on pedestrians' thermal perception, and (3) evaluate the seasonal and hourly effect of thermal comfort on pedestrian volume.Field campaigns were conducted in summer and winter, in six different types of streets including micro-climatic measurements, pedestrian observation and counting, and a bio-meteorology questionnaire survey.The results showed that the effect of thermal comfort is more pronounced in summer than winter thus during summer less pedestrian volume was observed during the hottest hours of the day. The pedestrian volume in winter is much higher than in summer. In commercial streets, the relation between thermal perception and pedestrian volume is weak, compared to noncommercial streets. During the summer the pedestrian volume in boulevards and shaded streets is higher compared to exposed streets.The findings indicate that thermal conditions affect pedestrian volume, but this is dependent upon the street network structure and type of land use. 
A machine learning algorithm for converting land surface temperature to air temperature and testing in the determination of the urban heat island effect over the city of Rome
Authors: Cecilia Andrea , Casasanta Giampietro , Petenko Igor , Conidi Alessandro , Argentini Stefania
Published: July 2024

Air temperature (Ta) plays a crucial role in numerous applications, including studies on physical stress conditions and understanding phenomena such as urban heat island (UHI). Ta measurements, acquired from in situ sensors often distributed unevenly, are limited in describing the spatial temperature field pattern. On the other hand, land surface temperature measurements (LST) obtained from geostationary satellites provide a more detailed spatial overview, but represent a different variable. In this work, a method based on machine learning algorithms is presented for converting LST detected from geostationary satellites MSG, into air temperature. To perform the conversion, a gradient boosting algorithm, which is part of the tree-structured family of machine learning algorithms, was implemented. The method is applied to LST and Ta data available for the city of Rome (Italy) during the summers of 2019 and 2020. The Ta data are sourced from 17 weather stations, predominantly consisting of amateur stations whose quality has been verified. Using predictive variables such as instantaneous LST and with delays ranging from 1 to 4 hours, along with other parameters like altitude, imperviousness, land cover, tree cover, grassland, NDVI, and temporal parameters such as time of day, Ta was estimated, designated as the target variable, at points where no in situ measurement sensors are available. The Ta predicted by the model exhibits an average error of 1.2°C during the daytime and 0.8°C at night. This model output has improved the accuracy and spatial resolution of temperature pattern analysis across the city of Rome, compared to analyses based solely on in situ measurements. Furthermore, the spatiotemporal pattern of the UHI, which can now be measured at high resolution, aligns well with the expected pattern.
OVOCs source analysis based on an improved source apportionment model and its influencing factors: A case study of a dense urban agglomeration in the winter
Authors: Zou Yu , Guan Xianghong , Flores Rosa , Yan Xiaolu , Fan Liya , Deng Tao , Deng Xuejiao , Ye Daiqi
Published: July 2024

Oxygenated volatile organic compounds (OVOCs) affect the formation of atmospheric ozone (O3), secondary organic aerosol (SOA), and free radicals, and have complex sources such as anthropogenic and biogenic direct emissions and through series of secondary oxidation reactions of nonmethane hydrocarbons (NMHCs). However, understanding sources of OVOCs in the atmosphere still has large uncertainties. In this study, an improved OVOC source apportionment model was developed by principal component analysis (PCA) and multiple linear regression (MLR) based on the online monitoring of NMHCs and OVOCs in a dense urban agglomeration in the winter. The modelled concentrations were in good agreement with the measured concentrations (R2=0.56-0.97). The concentrations of major OVOCs, except for 2-methylacrolein, were greatly affected by anthropogenic sources (15.8-76.8%) and secondary generation (0.0-51.7%), while transport and natural sources contributed to 0.0-26.8% and 0.0-32.0%, respectively. The selection of isoprene as the natural tracer led to an underestimation of the OVOC species from primary emission and an overestimation from natural sources. In addition, photochemical reactions significantly reduced the simulation accuracy of the model for NMHCs in the afternoon, with the R2 of 0.60 ± 0.23, which was lower than the overall value of 0.82 ± 0.11. However, the R2 for OVOCs (0.83±0.14) did not decrease significantly in the afternoon due to the compensation of secondary oxidation. Furthermore, the concentration gradient distribution of the species gradually changes from a normal distribution to an exponential normal distribution with a decrease in concentration, the accuracy of the model was influenced by the degree of matching between tracer and species concentration gradient as species concentration change. Developing models with additional tracers at different concentration levels may enhance the robustness of the OVOC source apportionment model without increasing its complexity.
Spain: towards a drier and warmer climate?
Authors: Roca Josep , Arellano Blanca , Zheng Qianhui
Published: July 2024

The study of the precipitation regime aims to verify the hypothesis about the decrease of rainfall in Spain. Is the climate of peninsular Spain and the Balearic Islands moving towards a drier and drier climate?In principle, global warming (GW), at the planetary level, represents an increase in precipitation. The progressive increase in temperature causes greater evaporation, and therefore greater humidity in the atmosphere, which should produce increasing precipitation. However, this trend is not occurring homogeneously. The various scenarios developed by the IPCC suggest that in Mediterranean latitudes the GW generates a tendency towards greater drought.One of the objectives of this work is to analyze whether, in Spain, there is a temporal evolution of the precipitation regime towards less precipitation, as well as to study the relationship between annual precipitation and the trend towards progressive warming. Specifically, to verify the hypothesis that the increase in temperature resulting from the GW process implies a trend towards progressive drought.Two different databases are used in this work: on the one hand, the information provided by AEMET from a selection of meteorological stations throughout Spain, with the daily series of precipitation (rr) and maximum (tx) and minimum (tn) temperatures, from January 1, 1971 to December 31, 2023; on the other hand, information from the Copernicus climate service. Specifically, the one resulting from E-OBS, from January 1, 1950 to December 31, 2022 with a resolution of 0.25 degrees.In addition to multiple regression, the techniques used are the Mann-Kendall test and the Kendall-Theil-Sen regression.The Mann-Kendall test confirms the statistical significance of the relationship between rr and tx, with a statistical reliability close to 99.9%. The KTS regression predicts a reduction of 38.49 mm for each 1°C increase.If the warming trend experienced in recent years (1973-2022) continues, it is foreseeable that by 2050 there will be a reduction in precipitation in Spain of between 14% and 20% with respect to current precipitation (understood as the average between 2000 and 2022). Spain's climate is likely to vary from a Mediterranean climate to a warm steppe climate in the Köppen classification system.
The impact of atmospheric new particle formation on air quality
Authors: Kulmala Markku ,   Working group
Published: July 2024

Large fractions of atmospheric aerosols, both locally and globally, relevant to air quality and climate are produced via new particle formation (NPF; Kerminen et al., 2018; Chu et al., 2019; Kulmala et al., 2021). Kulmala et al. (2021) showed that NPF and secondary aerosol formation contribute to over 2/3 of the haze particle number and over 80% of the corresponding mass in Beijing.We combine the following tools to find out physical and chemical mechanisms of atmospheric NPF: i) targeted laboratory experiments, ii) comprehensive in situ observations, iii) comprehensive vertical observations, iv) satellite remote sensing and v) multi-scale modelling.We investigated a closure on sub-6 nm atmospheric aerosol particles and clusters showing that present observations can detect a major fraction of existing atmospheric clusters (Kulmala et al. 2022a). Our second finding, based on long-term measurements in four very different environments, was that even on days traditionally considered as non-event days (no observed NPF), “quiet NPF” occurs with formation rates between 2–20% of traditional NPF event days (Kulmala et al. 2022b). Thirdly, we investigated the growth of newly-formed particles into sizes relevant to climate and air quality using simulations in two different environments: 1) Beijing, a megacity in China, and 2) SMEAR II station, a boreal forest in Finland. Our simulations for Beijing showed that NPF is capable of giving large contributions of haze particle mass and number concentrations (Kulmala et al. 2022c). The results indicate that reducing primary particle emissions may not decrease PM pollution effectively in heavily polluted environments without simultaneous reductions for precursor gases responsible for NPF and subsequent particle growth. At SMEAR II, we simulated the role of NPF in the Continental Biosphere-Atmosphere-Cloud-Climate (COBACC) feedback mechanism (Kulmala et al. 2023). We found that outside the periods when NPF events tend to be rare at SMEAR II, NPF gives a dominant contribution to both condensation sink and cloud condensation nuclei concentration – the two most relevant quantities in the COBACC feedback mechanism. As a side product of our observations, we found surprisingly low variability in growth rates of newly formed particles in both Beijing and SMEAR II. This points toward a potentially important role of multiphase reactions causing the bulk growth of newly formed atmospheric particles – a phenomenon that needs to be investigated in more detail in the future.Chu, B. et al., Atmos. Chem. Phys., 19, 115–138, 2019.Kerminen et al., Environ. Res. Lett., 13, 103003, 2018.Kulmala et al., Faraday Discuss., 226, 334–347, 2021.Kulmala et al., J. Aerosol Sci., 159, 105878, 2022a.Kulmala et al., Front. Environ. Sci., 10, 912385, 2022b.Kulmala et al., Environ. Sci.: Atmos., 2, 352-361, 2022c.Kulmala et al., Boreal. Env. Res., 28, 1-13, 2023.
Exploring vulnerability patterns in heat-related preterm birth: a multi-country multi-city analysis
Authors: Salvador Coral , Iñiguez Carmen , Kim Yoonhee , Lavigne Eric , Orru Hans , Ragettli Martina S. , Royé Dominic , de’Donato Francesca , Leon Guo Yue-Liang , Chang Howard , Astrom Christofer , Konishi Shoko , Tobías Aurelio , Agay-Shay Keren , Scovronick Noa , Singh Tanya , Valdes Ortega Nicolas , Vicedo-Cabrera Ana Maria ,   Multi-Country Multi-City Collaborative Research Network
Published: July 2024

Evidence suggests that high temperatures may trigger preterm birth (PTB), which is associated with a higher risk of infant mortality and morbidity during childhood and adult life. However, there is limited evidence on the role of sociodemographic factors on the vulnerability of pregnant women. In a multi-location setting, we aimed to assess 1) the effect of heat on PTB of different gestational ages (extreme, very, late, standard preterm births) and at-term births and 2) how mother and child characteristics (sex, ethnicity, parity, age, education, marital status, socioeconomic class) influence the association between heat and PTB.The analysis included all singleton births born in the warm season (5 warmer months) in 243 cities in 13 countries between 1979-2019. A two-stage design was applied with conditional quasi-Poisson regression with distributed lag nonlinear models to estimate the association between daily mean temperature and PTB or at-term birth (lags 0-4 days) in each location and for each category of characteristic of the mother and child. Then, a random-effects multilevel metaanalytical model was applied to report overall effects and by country level. Extreme heat effects were measured as the percentage change (ch%, 95%CI) in the outcome when the mean temperature increased from 1% to the 95% percentile.Heat was positively associated with all endpoints, except for extreme or very PTB whose risks were very imprecise, with larger risks for late-PTB (5%, 0.8-9.3) and smaller in at term births (2%, 1-3.1). Younger, Caucasian mothers and those with low socioeconomic class seemed to be more vulnerable to heat. Female fetal gender was associated with higher risk than males.This is the largest multi-location study assessing vulnerability patterns of heat-related PTB. It emphasises the need to integrate evidence from vulnerability assessments in designing public health interventions to face climate change effects.
Influence of Asian Mountains on Arctic Pressure System and the Stratospheric Ozone
Authors: Pan Zhulei , Duan Anmin , Wang Qilu
Published: July 2024

The majority of Asian mountain region is made up of the Tibetan Plateau (TP), often referred to as the “Third Pole”. The TP, characterized by its high elevation, is a critical and sensitive region for climate change, experiencing a warming trend at a rate twice that of the global average. Its significance extends beyond local climate impacts, exerting a profound influence in shaping global climate dynamics. While its influence on the Asian is well-documented, its impact on the remote Arctic region has remained unclear. By conducting orographically sensitive experiments using the Whole Atmosphere Community Climate Model Version 6, we shed light on the intricate relationship between the TP and Arctic climate variability. The results reveal that the Asian topography significantly influences Arctic pressure anomalies by modulating the Aleutian Low–Icelandic Low seesaw teleconnection. Furthermore, the topography facilitates the stratosphere-troposphere coupling, leading to the change of the stratospheric polar vortex in its strength and position. In addition to the impact on atmospheric circulation, the response of the Arctic ozone levels to the removal of the Asian mountain is also investigated. It is demonstrated that the topography significantly enhances the Arctic stratospheric ozone during winter, with a notable increase of 15% in the lower Arctic stratosphere. This increase is attributed to the intensified residual mean circulation transport, which is primarily influenced by the robust strengthening of planetary waves induced by Asian topography. The enhancement of planetary waves results in a weakened polar vortex, further promoting ozone accumulation in the Arctic region, ultimately influencing the dynamics and chemistry of the Arctic stratosphere. Overall, this research underlines the significant role of the Asian topography in driving Arctic climate variability and stratospheric ozone dynamics, providing valuable insights into the mechanisms underlying paleoclimatic evolution and atmospheric circulation.
Meteorological drivers of a winter shamal dust storm over the Middle East
Authors: Karbasi Samira , Chham Essaid , G. Orza Jose A.
Published: July 2024

Severe dust storms are frequent throughout the year in the Middle East. While dust events are more active during winter and spring in the north, their maximum activity with the greater intensity occurs in the summer in the southwest of the region. The Middle East is affected by frontal dust storms mainly in winter and “Shamal” dust storms mostly in summer.Surface and satellite observations as well as ERA5 reanalysis data were used to describe the formation and evolution of a winter shamal dust storm that occurred in February 2017. It initiated in central western Iraq and dust was transported southeastward towards the Persian Gulf, impacting all the countries in the region up to the Oman Sea.The SEVIRI Dust RGB product shows dust mobilization at 07 UTC (10 LT) in several point areas west of the Euphrates River and over Mesopotamia, in Iraq. A dense dust plume is then advected between the Zagros Mountains, to the North and East, and the high plains of Saudi Arabia, to the South and West, reaching the Persian Gulf in the first hours of February 18. The next day, dust spreads throughout the Persian Gulf and surrounding countries. It resulted in the widespread reduction of horizontal visibility and impaired air quality, as reported by the region's Synop/METAR surface observations and air quality stations.The large-scale upper-level processes leading to this event started days before with a strong amplification of an anticyclonic Rossby wave break in the Polar Jet over the North East Atlantic, with large penetration poleward of subtropical air up to Scandinavia and cold air advection equatorward over Iberia on February 11. At a late dissipative stage and downstream displacement, the RWB resulted in a closed ridge over southeastern Europe and Turkey and a trough downstream over the study area. A strong pressure gradient was established at low levels between high pressures centered over southeastern Europe and the Black Sea and low pressures over the Persian Gulf with minima over the Arabian Peninsula and over Iran to the north of the Zagros Mountains. Strong northerly winds, imposed by the pressure gradient, accelerated downslope in the lee of the mountains in southern Turkey. The analysis suggests the formation of a low-level jet to the south of the mountains. During the morning hours of February 17 it mixed with the air over the surface, transferring momentum and initiating dust deflation in source areas of northern Iraq and Syria. Dust plumes were transported southeastward at heights below 2 km, as shown by CALIPSO profiles in the first half of February 18, within the PBL. On February 19, the dust plume was mixed all over the Persian Gulf basin.
Indoor and outdoor air quality relationships modelling
Authors: Kosmopoulos Georgios , Logothetis Stavros-Andreas , Kazantzidis Andreas
Published: July 2024

Particulate matter (PM) related ambient pollution has emerged as one of the most significant environmental and human health issues during the last decades. Thus, ambient PM concentration levels have been widely investigated through several studies. On the contrary, investigation of indoor microenvironments, where people spend most of their time, air quality conditions is rather limited.In this study, indoor and outdoor air quality conditions were analyzed across different areas with distinct characteristics towards a better understanding of the complex relationships between indoor and outdoor air quality levels and the mechanisms governing infiltration factors. Simultaneous PM2.5 concentration measurements were conducted, using particle sensors, providing useful information for the identification of Indoor Air Quality (IAQ) variation due to sharp changes in outdoor conditions.The dynamics of PM infiltration factor, the fraction of ambient particles that infiltrate indoors either by mechanical or natural ventilation, that provoked degraded indoor air quality conditions, have also been evaluated. Moreover, an algorithm is developed, based on regression models, to estimate the infiltration factor, through IO (indoor/outdoor) ratios. The estimated infiltration factor would facilitate the quantification of the fraction of the indoor generated particles to the total indoor concentrations.The integration of several parameters such us as building characteristics, ventilation systems, air exchange rates, indoor activities and meteorological conditions will elucidate the mechanisms that affect relationship between outdoor and indoor measurements. These findings could provide substantial knowledge to the relationship between infiltration factor and IAQ that is crucial for promoting healthier indoor environments. The study mainly focuses on time periods where outdoor PM2.5 concentrations are dominant, to model more accurately the infiltration factor and the corresponding IAQ at each measurement site. Overall, the synergy of in situ, outdoor and indoor air quality, measurements and  physical modelling will enhance the knowledge on IAQ and could engage the adoption of better IAQ systems and practices.
A deep learning approach for PM2.5 exceedances forecasting in an urban area
Authors: Logothetis Stavros-Andreas , Kosmopoulos Georgios , Panagopoulos Orestis , Salamalikis Vasileios , Kazantzidis Andreas
Published: July 2024

Fine airborne particles with aerodynamic diameter lower than 2.5 μm (PM2.5) pose a pivotal atmospheric threat. High PM2.5 values are highly associated with numerous adverse health effects affecting the respiratory and cardiovascular systems. Apart from densely populated urban environments, where anthropogenic emissions are more intense and population density is constantly increasing, suburban and rural are also prone to experience severe PM2.5 related pollution events. Eventually, PM2.5 levels across many environments may report elevated concentrations that may lead to exceedances of the Word Health Organization (WHO) regulated thresholds severely affecting humans’ life, well-being, and ecosystems. A precise forecasting technique of the PM2.5 concentrations could be essential to tackle air pollution control and warn vulnerable citizens.In this study, a novel deep learning approach (long short-term memory, LSTM) was developed, to forecast the intraday air pollution exceedances across urban and suburban environments in northern Greece (Municipality of Thermi). A three-year dataset was used for the training (two years, 2021-2022) and testing (one year, 2023) of the proposed LSTM model. PM2.5 measurements were provided by a dense low-cost PM monitoring network with approximately 28 sensors deployed across the greater measuring area.  In the scope of this study ground based PM2.5 observations from 3 regions, that share a rather similar meteorological profile, the corresponding meteorological variables, acquired from the Copernicus Atmosphere Monitoring Service (CAMS) and operated by ECMWF, and time variables related to local emissions were utilized. These data were integrated into the LSTM-based methodology, to enhance the hourly intraday PM2.5 concentrations forecasting capabilities. Additionally, the applicability of PM2.5 forecast concentrations to capture the daily exceedances of air pollution was also assessed.The proposed model's forecasting accuracy yielded promising outcomes, revealing correlation coefficients ranging between 0.68 and 0.93 among the observed PM2.5 concentrations and LSTM forecasted data for various time horizons. Longer forecasting intervals though reported lower correlation coefficients values. Finally, regarding PM2.5 threshold exceedances, the LSTM forecasting system correctly identified over 73% of such events in the examined area. These findings underline the model's capabilities in detecting potential breaches of WHO guideline limits and provide crucial local air quality management insights.
Evaluation of climate change impacts for tourism in Hungary based on tourism climate metrics
Authors: Kovács Attila
Published: July 2024

Weather and climate constitute vital resources exploited by the tourism sector. Climate influences the behaviour of tourists through their motivation to travel and destination selection. Climate change is a major challenge for tourism, significantly affecting tourism supply and demand. Thus, the recognition of the observed and expected future climate suitability for a given region or destination is of outstanding importance. In the research, I evaluate the impacts of climate change for the area of Hungary based on two tourism climate metrics: a modified form of the Tourism Climate Index (mTCI, Kovács et al. 2016) and the urban Holiday Climate Index (HCI:Urban, Scott et al. 2016). The observed tourism climate conditions are quantified for the period 1971–2000 using the grid point based observational database CarpatClim-HU at 10 km horizontal resolution. Future conditions are described for the periods 2041–2070 and 2071–2100 based on two regional climate models (ALADIN and REMO) driven by different global climate models. Two emission scenarios (RCP4.5 and RCP8.5) are used to describe the future anthropogenic activity in the models. This multi-model and multi-scenario ensemble method allows taking into consideration the uncertainties in climate model predictions. The spatial distribution of indices are displayed on maps on a Hungarian district scale as well as on a monthly basis. In the present period, based on both indices, the shoulder months (April, May, September and October) are characterised with the most favourable conditions, while there is a slight deterioration in climate suitability in summer. According to future tendencies, both metrics indicate that less favourable conditions are expected in the summer months in large parts of the country. Certain scenarios also show a slight drop in May and September. However, most shoulder months (March, April, October and November) seem to bring more pleasant circumstances for tourism. The winter period is likely to be characterised with the same or slightly better conditions in the future. The results demonstrate that climate change will have an apparent impact on tourism in Hungary.Project no. 142335 has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the PD_22 funding scheme.
Overview of the gridded daily and monthly precipitation data sets provided by the Global Precipitation Climatology Centre (GPCC)
Authors: Rustemeier Elke , Ziese Markus , Schirmeister Zora , Finger Peter , Heller Astrid , Schulze Raphaele , Zepperitz Magdalena , Fränkling Siegfried , Breidenbach Jan Nicolas
Published: July 2024

Since its founding in 1989, the Global Precipitation Climatology Centre (GPCC) has been producing global precipitation analyses based on land surface in-situ measurements. This year the GPCC marks its 35th anniversary. During these years the precipitation database has been continuously expanded and includes a high station density and large temporal coverage. Due to the semi-automatic quality control routinely performed on the incoming station data, the GPCC database has a very high quality. Today, the GPCC holds data from more than 126,000 stations, about three quarters of them having long time series.The core of the analyses is formed by data from the global meteorological and hydrological services, which provided their records to the GPCC, as well as national meteorological and hydrological services from all over the world.  In addition, the GPCC receives SYNOP and CLIMAT reports via the WMO-GTS. These form a supplement for the high quality precipitation analyses and the basis for the near real-time evaluations.Quality control activities include cross-referencing stations from different sources, flagging of data errors, and correcting temporally or spatially offset data. This data then forms the basis for the following interpolation and product generation.In near real time, the 'First Guess Monthly', 'First Guess Daily', 'Monitoring Product', ‘Provisional Daily Precipitation Analysis’ and the 'GPCC Drought Index' are generated. These are based on WMO-GTS data and monthly data generated by the CPC (NOAA).With a 2-3 year update cycle, the high quality data products are generated with intensive quality control and built on the entire GPCC data base. These non-real time products consist of the 'Full Data Monthly', 'Full Data Daily', 'Climatology', and 'HOMPRA-Europe' and are now available in the 2022 version.All gridded datasets presented in this paper are freely available in netcdf format on the GPCC website https://gpcc.dwd.de and referenced by a digital object identifier (DOI). The site also provides an overview of all datasets, as well as a detailed description and further references for each dataset.
HOMPRA Europe 2 – An update of a gridded precipitation data set from European homogenized time series
Authors: Rustemeier Elke , Finger Peter , Ziese Markus , Schirmeister Zora
Published: July 2024

Reliable observational data are essential for robust climate analyses, especially long-term trends.HOMPRA Europe 2 (HOMogenized PRecipitation Analysis of European in-situ data) is a gridded monthly precipitation dataset based on homogenized time-series. The carefully selected database of more than 5500 stations is a subset of the time series collected by the Global Precipitation Climatology Centre (GPCC). The subset is characterized by few missing values < 20% and intensive quality control.Compared to its predecessor, the new HOMPRA Europe 2 product covers a longer period from 1951-2015 and is syncronized with the more recent data of the GPCC Full Data Monthly product, so that the data can be extended to the present without a break, although a homogeneous time series cannot be guaranteed for these more recent data.The actual homogenization process consists of multiple steps: In the first step, for each station, comparable time series are selected. The decision is based on the correlation and Ward's method of minimum variance performed on the deterministic first derivative. For the artificial breakpoint detection, natural variability and natural trends are temporarily removed using the previously selected neighboring time series. This ensures that only artificial changes can be detected. The actual detection applied to annual values is based on the segmentation algorithm of Caussinus and Mestre (2004). In the final step, the breaks detected in the monthly data are corrected using multiple linear regression (Mestre, 2003).An additional random variation of the neighboring stations shows the robustness of the correction of the individual time series.Finally, the actual HOMPRA Europe 2 product is created by interpolating the homogenized series onto a 1° grid using the modified spheremap interpolation schemes in operation at the GPCC (Becker et al., 2013 and Schamm et al., 2014). 
An evaluation and comparison of wind speeds from different reanalysis models in the context of wind energy – the influence of topography
Authors: Pauscher Lukas , Geiger David , Yuan Dehong , Bär Franziska , Good Garrett , Spangehl Thomas , Kaspar Frank , Weber Helga , Callies Doron
Published: July 2024

Wind speed data from reanalysis models is used for a wide range of industrial and research applications in the wind energy sector. These range from resource estimation in the development phase to planning of the future (wind) energy system and the integration of wind energy into electrical grids. Validation of reanalysis models for offshore conditions far away from the coast is relatively straightforward, for which very good agreement between reanalysis models and wind speed measurements has been demonstrated. In contrast, validation in heterogeneous and complex terrain is much more difficult.This study uses an extensive measurement dataset with high-quality wind speed measurements at heights relevant for modern wind energy applications (100 – 200 m) to evaluate and compare a set of reanalysis models, i.e. ERA5, COSMO-REA6, CERRA, and NEWA. The evaluation dataset in this study comprises approximately 100 lidar and mast measurements, mainly carried out for wind park developments, distributed over Germany and covering a wide range of topographic conditions.The analysis focuses on identifying local topographic effects and indicators that influence the quality of the agreement between the reanalysis models and the measurements (i.e. correlation) as well as systematic deviations (biases). The investigated topographic effects include orographic exposure, land /forest cover, and sub-grid scale orography. In a preliminary analysis based on 44 measurement stations, a clear correlation between the bias in the reanalysis models (compared to the measurements) and the orographic exposure of the measurement location could be demonstrated. At measurement locations with ground heights exceeding the height of the grid cell of the reanalysis model, the model data underestimated the observed wind speeds. The opposite could be observed at measurement location below grid height.These findings are especially important for wind energy applications, as wind farm developments tend to concentrate on areas with high exposure and specific land use types. Moreover, the observed relationships with local geography potentially provide the possibility to empirically correct and downscale wind speeds from reanalysis models. This allows to better represent the wind resource available for wind parks and to estimate the uncertainties based on local geographical conditions.