bluuebunny/crossref_metadata_2025 huggingface dataset:
Heatwave impacts on urban indoor air temperature assessed through citizen science observations in the Netherlands
Authors: Peerlings Esther , van Esch Marjolein , Poolman Hans Roeland , Steeneveld Gert-Jan
Published: July 2023

Due to climate change and urbanization, the world's population is increasingly exposed to extreme heat, posing a threat to public health. Despite people spending ~90% of their time indoors, heat effects in buildings have been studied far less than outdoor heat island effects. This study aims to observe, understand and model the behaviour of indoor air temperatures (Tin) during summer heat. As a proof of concept, we present and analyse up to 27 years of individual Tin timeseries of seven citizen weather stations (CWS) across the Netherlands. First, we find that typically Tin increases slower, but also cools down slower than Tout with a lag difference of ~130 minutes in the diurnal cycle. We demonstrate that nocturnal indoor human thermal comfort (HTC) can be worse than outdoor HTC even for days after a heatwave.
Second, to model Tin behaviour, we simulate six-hour changes in Tin behaviour with a physics-based statistical model by Vant-Hull et al. (2018) that has an outdoor conduction, indoor conduction and solar transfer component. Preliminary results of this computationally-fast model for each of the seven houses are promising, showing on average a R-squared of 0.74 and a root mean squared error of 0.13 K. Third, we are also interested in how Tin may evolve due to climate change. We study this by converting the Tin measurements to 2050 and 2085 values based on the Royal Netherlands Meteorological Institute 2014 climate scenarios.
Finally, in the next research step, we will scale up our proof-of-concept analyses to 100 indoor CWS placed in Amsterdam. The participating households receive a CWS for three years to measure their indoor climate – temperature, relative humidity, CO2 concentrations – in the bedroom and living room. Based on our insights, we will make recommendations for climate-sensitive urban design to reduce indoor heat stress.
Galapagos Rainfall retrieval using multispectral GOES-16 infrared brightness temperature _ Part 1: Rainfall area delineation
Authors: Turini Nazli , Delgado Maldonado Byron , Bendix Jörg
Published: July 2023

The Galápagos archipelago is renowned for its exceptional and diverse flora and fauna, primarily due to its unique location and climate. However, since the archipelago has limited access to permanent freshwater sources, available freshwater depends on rainfall. Unfortunately, information is scarce regarding the spatial and temporal distribution of rainfall in the Galápagos, making it challenging to fully comprehend short- and long-term rainfall patterns and changes.  This is particularly important considering extreme rainfall events caused by climate change, as highlighted in the IPCC report. IPCC emphasizes that the increased frequency and severity of extreme events caused by climate change impact the destruction and harm to both nature and people. 

For such regions, satellite-based rainfall products potentially represent a source of reliable and area-wide data on rainfall. Therefore, the aim of this project is to develop the Galápagos Rainfall Retrieval (GRR) product;, a new satellite-based algorithm for retrieving rainfall in Galapagos archipelago. The GRR has the potential to provide high spatio-temporal resolution rainfall data (2 km, 10 min) in near real-time for the study region. 

 

The GRR algorithm combines physical methods with machine learning techniques using sequences of Geostationary Earth Orbit infrared (GEO-IR) images to retrieve both cold season Garua drizzle and warm season convective rainfall. The algorithm comprises of two main steps. i) Rain area delineation: a threshold technique and spectral spatial analysis are utilized to identify areas with cloud cover and differentiate between low, middle, and high clouds. Following this, a slope test and machine learning algorithm are used to classify cloud-covered areas and identify low stratus/Garua drizzle and potentially convective core regions. The convective cores are then evaluated to determine whether they are decaying or not, and subsequently labeled as stratiform rain or active convective cores, respectively. ii) Rain rate assignment is carried out by training random forest regression models separately for convective and stratiform cells, based on microwave-only IMERG-V06 rainfall data. To train rainfall rates for Garua detected regions, CloudSat and the newly installed automated weather station (AWS) network from DARWIN project is utilized. 

 

The GRR product is set to be developed between 1/1/2022-1/1/2023 and then applied to the entire available GOES-16 dataset. Independent microwave-only IMERG-V06 rainfall data and AWS network with a high temporal resolution of 10 minutes will be used for validation purposes. The AWS network will cover W-E and luff-lee transects over three islands (Isabela, S. Cruz, S. Cristóbal). 

 The poster will present the overall structure of the GRR algorithm and some first results of the rain area delineation.  
The process of creating the new Climate Atlas of Catalonia (1991-2020)
Authors: Prohom Marc J. , Barnolas Mercè , Martín-Vide Javier
Published: July 2023

Climate normals have two main functions in climate studies: (1) become an implicit predictor of the conditions most likely to be experienced in the near future at any location, and (2) be a stable reference against which to compare long-term changes in climate observations. When normals are expressed as georeferenced climate data in a regular grid, then we talk of digital climate atlases.
Here we describe the steps followed to develop the new Climate Atlas of Catalonia (1991-2020), the reference tool to provide information to the government, regional authorities, businesses and citizens about the characteristics of Catalonia's climate during the last thirty years. First, a description is made of the database used (daily mean, maximum and minimum temperature, and precipitation), which presents a much higher density of climate information than other previous periods, including data from automatic weather stations, and from high mountain and remote areas, about which there was very little knowledge of its climatology. Secondly, the quality control procedure that has been applied is detailed, and the subsequent homogeneity analysis (by means of ACMANTv5), which has made it possible to correct artificial biases in the series. Finally, the interpolation methodologies that have been tested are described, and the one that has finally been chosen for the generation of the digital cartography.
The final product includes high-resolution digital cartography (1 km for precipitation, and 100 m for temperature) at different time scales (monthly, seasonal, and annual) and for the four essential climate variables mentioned above, which will be freely available through the SIG portal of the Government of Catalonia (https://sig.gencat.cat/visors/hipermapa.html). To conclude, the work includes a comparison of the results obtained between the periods 1961-1990 and 1991-2020, making visible the warming experienced in the region and some changes in rainfall patterns.
Coastal wave conditions in the Ionian Sea during the Medicane Ianos (2020).
Authors: Christakos Konstantinos , Varlas George , Björkqvist Jan-Victor
Published: July 2023

An intense Mediterranean tropical-like cyclone (Medicane) known as Ianos developed in the central-eastern Mediterranean Sea in mid-September 2020. The parent cyclone of Ianos initially formed on 14 September and strengthened on 15-16 September. Ianos acquired its tropical characteristics mainly on 17-18 September and it began to gradually lose its energy on 19-20 September while it finally dissipated on 21 September. Although Ianos affected several Mediterranean areas, it significantly influenced Greece with strong winds, high waves, storm surge, coastal inundation, heavy rainfall, flash floods, and landslides, thus having severe socioeconomic implications including four deaths and extensive damages. The impact of Ianos on the sea state was very intense, especially across the coastal areas of the Ionian Sea where the cyclone was characterized by its maximum winds reaching even Category 2 of the Saffir-Simpson scale. Moreover, high waves were observed in the coastal areas of the Ionian Sea during the passage of Ianos. In this framework, this study investigates the coastal wave conditions during Ianos in the Ionian Sea using the open-source tool DNORA (https://github.com/KonstantinChri/dnora) to dynamically downscale the ERA5 reanalysis data applying the spectral wave model SWAN. We use high-resolution bathymetry from the EMODNET database. We analyze the wave conditions using integrated wave parameters such as significant wave height and wave periods as well as wave spectrum. Particular focus is given to the evolution of the 2D wave spectrum during the Medicane Ianos. Preliminary results indicate that such extreme atmospheric events can lead to rapid growth of wind sea conditions with a significant impact on coastal areas.
Physics-informed detection of tropical cyclonesbased on dynamical systems metrics
Authors: Vaittinada Ayar Pradeebane , Faranda Davide , Vrac Mathieu
Published: July 2023

Even though tropical cyclones are well documented from the moment they materialise to the moment they evanesce, many physical processes governing them are not resolved by global circulation models (GCMs). Thus, the simulation and the projection of future changes in tropical cyclones characteristics remain challenging. In particular, due to the low spatial resolution of most GCMs, studying simulated tropical cyclones is difficult because they are hard to detect. Some cyclone detection schemes are now available but their results are subject to the spatial resolution of the simulations and  usually need numerous variables that are not always available in the models. In this study, the ability of dynamical system metrics to detect atmospheric situations related to cyclones in coarse-resolution data-sets, where maximum wind speed and minimum sea-level pressure may not be accurately represented, is explored.
Our analysis is based on 613 cyclones occurring in Tropical Atlantic over the 1980-2021 period and extracted from the IBTrACS database. Three dynamical system metrics, the local dimension d, local persistence θ and the co-recurrence ratio α, are computed from mean sea level pressure and the total column water of the ERA5 reanalysis dataset. They respectively characterise the number of degrees of freedom of the atmospheric flow, its stability and the  coupling between different atmospheric variables. In the preliminary results, atmospheric situations corresponding to cyclones stand out from other situations. This preliminary result shows potential for detection and attribution studies in climate change context.
False spring events in the eastern part of the Baltic Sea region
Authors: Klimavičius Laurynas
Published: July 2023

False spring is one of the preconditioned compound climate events that gained a lot of attention in recent years because of its negative impact on agriculture, fruit trees, damage to native forests, and reduction of carbon uptake. The aim of this research is to identify these events in the eastern part of the Baltic Sea region during the spring months from 1950 to 2022 and to assess their frequency, intensity and potential damage to agriculture. To do that, the date of the last spring frost (LSF) as well as the date of the start of the growing season (SGS) were found for each cell of analysed territory for each year. In this study the SGS for a particular year was defined as the first day in a period of six days when the average daily temperature (Tavg) during all these six days was at least +5.0 °C. Meanwhile, the LSF date was determined when the minimum daily air temperature (Tmin) in April-June dropped below 0°C for the last time during a particular year. Daily Tavg and Tmin data that was needed to determine SGS and LSF dates were obtained from European Centre of Medium-range Weather Forecast ERA-5 reanalysis dataset with a spatial resolution of 0.25° x 0.25°. In this study, a false spring was identified at the corresponding point of the study area if the last spring frost was identified after the start of the growing season. The study showed, that at the end of the analysed period (1950–2022), the growing season started earlier in the entire study area. This change ranged from -0.5 days per decade in the northeastern part of the study area to -2.1 days per decade in the western part of Lithuania. The LSF date during the 73-year study period has also become earlier in almost all study area points. The largest changes (-1.8 days per decade) were observed in the northern and northeastern part of the analysed territory. However, the changes of LSF date were not as rapid as those of the SGS. Therefore, during the study period, the number of false spring cases increased in 73.76% of the study area. The largest growth of such cases was observed in the eastern part of the study area and in coastal regions. There was also an increase in the amount of accumulated heat from the SGS date to the LSF date. Positive changes were found in 82.76% of the study area points, with the largest ones occurring at the border between Lithuania and Kaliningrad and in the eastern part of the study area.
SSEA- Statistical and machine learning based post-processing for high-resolution subseasonal ensemble predictions
Authors: Schicker Irene , Papazek Petrina , Dabernig Markus , Schellander-Gorgas Theresa
Published: July 2023

Subseasonal predictions are gaining more and more attention and importance in many applications, e.g. agriculture or energy&consumption predictions. To bridge the gap between those two temporal horizons and their drivers is, however, a challenge. Several attempts have been made in recent years to improve the numerical weather predictions but they to come at a high computation cost resulting in coarse spatial resolutions.  In the past decade, significant advances were made in improving the S2S and seasonal prediction using mainly numerical weather prediction models (NWP) and in some cases climate models for generating the predictions. Recently, the application of these models in real time forecasting through the S2S Real-Time Pilot Initiative (Robbins et al., 2020) was evaluated and is ongoing. There are, however, drawbacks. Computational costs for performing one forecast cycle are high (RAM, storage, ensemble for uncertainty) and limit the spatial, and to some extent temporal, resolution which are currently roughly 1.5° in spatial and at most 6-hourly in temporal resolution. Both resolutions are not sufficient for small scale renewable production sites. To overcome this, post-processing can be applied using statistical and machine leraning methods.
In this study, statistical (EPISODES, GMOS, SAMOS) and machine learning methods (U-net, random forest) are used to downscale and post-process the coarse subseasonal ensemble predictions for temperature and precipitation. The domain in centred on Austria with a spatial resolution of 1 km  using the INCA analysis as target fields. Evaluation against INCA and point observations show the skills of all methods and highlight the need for additional downscaling.
Rainfall intensities to enhance resilience in support of climate change adaptation in Ireland
Authors: Mateus Carla , Coonan Barry
Published: July 2023

The climate of Ireland is changing. Extreme rainfall events are responsible for major socio-economic impacts and can be hazardous to life. Short-duration and intense localised rainfall events can cause severe flooding. Estimating the return levels of rainfall thresholds for specific return periods has diverse applications, such as informing the design criteria for drainage schemes, sewerage systems, bridges, gutters, and fluvial flood mitigation measures.
The goal of this research was to calculate return values for various return periods from 2 to 120 years and for specific rainfall durations ranging from 15 minutes to 25 days based on the depth-duration-frequency model described by Fitzgerald (2007), but with a denser network of stations with up-to-date data.
Estimates of rainfall intensities were produced for use in building design in support of Action 203 of Ireland’s Climate Action Plan 2021 - Develop specific climate maps and data for use in building design to enhance resilience in support of climate change adaptation and to support the National Adaptation Framework. This project was carried out by Met Éireann under its strategy ‘Making Ireland Weather and Climate Prepared’ and funded by the Department of Housing, Local Government and Heritage.
The outputs of this research will benefit a wide range of stakeholders currently collaborating with Met Éireann, such as the National Standards Authority of Ireland, the Office of Public Works and Transport Infrastructure Ireland, and the Department of Housing, Local Government and Heritage’s building standards team. This report will also inform policy in delivering key national infrastructure such as housing and building renovation. The results will also be of interest to a diversity of sectors, planners and policy makers to make long, lasting and climate sensitive decisions.
 
References
Fitzgerald, D. L. 2007. Estimation of point rainfall frequencies. Technical Note no. 61. Dublin: Met Éireann. http://hdl.handle.net/2262/70546
Mateus, C., and Coonan, B. 2023. Estimation of point rainfall frequencies in Ireland. Technical Note No. 68. Dublin: Met Éireann. http://hdl.handle.net/2262/102417 
The dynamic fingerprint of ENSO on European summer weather regimes
Authors: Pons Flavio , Yiou Pascal
Published: July 2023

The El-Niño Southern Oscillation (ENSO) is the main known predictor of interannual natural climate variability. It presents several known teleconnections to weather in different regions of the world. When it comes to the influence of ENSO on European climate, the existing literature is mainly focused on the variability of precipitation and, more recently, temperature. In most of these studies, the variability modes of the target variables are directly recovered with techniques such as empirical orthogonal functions, and the role of atmospheric dynamics is assessed a posteriori by considering composites of dynamical variables. Here we take on a different approach, and we directly assess the influence of ENSO on atmospheric dynamics over the Europe and North Atlantic (ENA) region. This is particularly relevant when considering summer, given the vulnerability of parts of this region to increasing risk of drought and summer heatwaves. To conduct this assessment, we use Latent Dirichlet Allocation (LDA), a generative statistical topic model traditionally used in natural language processing, which can also be utilized as a weather pattern recognition technique. In particular, we apply LDA to the ERA5 daily 500 hPa geopotential height anomaly field (Z500). As a result, we obtain a prescribed number of positive and negative Z500 anomaly patterns, each associated with a daily weight. The analysis of the weights time series for each LDA pattern shows a significant association between the ENSO phase and the importance of some Z500 patterns during summer over ENA. By clustering the pattern weights after conditioning on the ENSO phase, we show how this identified teleconnection affects precipitation and temperature variability over the ENA region. 
Homogenised input series for generating gridded data, does it matter?
Authors: Tveito Ole Einar
Published: July 2023

When assessing long term climate trends and variability it is important to analyse data that are not disturbed by external factors that might lead to misleading trends. It is also urgent to analyse consistent series that cover the entire time period. Since observation networks are continuously changing not too many complete series are available for a centennial long analysis. 
Gridded climate monitoring data are often based on all available data for each timestep, which might disturb the spatial and temporal consistency. In order to investigate such impacts we have constructed a long term gridded dataset based on homogenised input data.  165 raw temperature series and 323 raw precipitation series fr Norway covering the entire period 1901-2020 were constructed by an extraction from a gridded data set of monthly climate anomalies, which was based on all available observations. The constructed series were homogenised applying the automatic procedure in Climatol. 
New gridded data sets were established applying the homogenised data series as input. These data sets were compared to a similar gridded dataset based on the raw non-homogenized data series. Analysis of the regional time series of the datasets shows similar temporal variability and trends. The gridded data based on the homogenised data shows less local spatial variability than those based on the raw data series. This means that anomalies due to inhomogeneous data are reduced, and that false local trends are removed. The construction and homogenization of climate data series therefore provides more consistent data for gridding, and leads to better and more reliable gridded data sets for assessing spatio-temporal climate trends.
Impact of tropical eastern Pacific warming bias on Caribbean climate.
Authors: Brotons Marta , Haarsma Rein , Bloemendaal Nadia , de Vries Hylke , Allen Teddy
Published: July 2023

During the last decades, CMIP5 models simulate a warming trend in the tropical eastern Pacific that has not been present in observations (Seager et al., 2019). Associated with this, the Walker circulation has experienced a westward migration while CMIP5 models simulate an eastward migration. This mismatch is still present in CMIP6 models and might affect climate projections worldwide through different teleconnections.
In the Caribbean region, CMIP6 models project a strong drying at the end of the 21st century. El Niño-like changes in the Walker circulation are the dominant processes driving the Caribbean drying. The models that project a strong Caribbean drying also simulate generally a strong equatorial eastern Pacific warming trend over the recent decades. Thus, the mismatch between observed and simulated warming trends over the equatorial eastern Pacific questions the reliability of the Caribbean precipitation projections. The warming bias might also have implications for tropical cyclones’ projections in the Atlantic and Pacific through the effect of vertical wind shear, which is related to shifts in the Walker circulation. In addition, the double Intertropical Convergence Zone (ITCZ) bias might be influenced by the mismatching trends. Based on our understanding of the physical processes affecting Caribbean drying, we carry out an emergent constraint analysis to reduce the projected Caribbean precipitation spread. We find that the future drying in the Caribbean might be weaker than the one projected by CMIP6 models.
The strong influence of El Niño-Southern Oscillation (ENSO) dynamics on the world’s climate through different teleconnections demands more in-depth studies addressing the drivers of the Walker circulation and the equatorial Pacific warming bias.
Large-scale changes in the hydroclimate of the Last Millennium from reconstructions and simulations
Authors: Roldán-Gómez Pedro José , González-Rouco Jesús Fidel , Smerdon Jason , García-Pereira Félix
Published: July 2023

The climate of the Last Millennium (LM) was characterised in many regions by long periods of warmer and cooler conditions, like the Medieval Climate Anomaly (MCA; ca. 950-1250 CE) and the Little Ice Age (LIA; ca. 1450-1850 CE). These changes in temperatures can be linked to changes in the Earth’s energy balance, being the solar and volcanic activity the main drivers during the pre-industrial period. Even if the MCA and LIA are typically defined in terms of temperatures, reconstructions of the hydroclimate conditions from regions of North America, Europe, Northern and Central Africa, Northern and Central South America, and Central and Eastern Asia also show relevant changes during these periods, suggesting a large-scale impact on the hydroclimate.
To analyse these large-scale changes in the hydroclimate, and whether similar changes also extend to other periods of the LM outside the MCA and the LIA, an exhaustive compilation of all the available reconstruction-based and model-based sources providing information about the hydroclimate of the LM has been considered, including the Drought Atlases for Europe (OWDA), North America (NADA), Asia (MADA), and Mexico (MXDA), the Paleo Hydrodynamics Data Assimilation product (PHYDA), the Last Millennium Reanalysis (LMR), and model simulations from the Community Earth System Model - Last Millennium Ensemble (CESM-LME) and the Coupled Model Intercomparison Project Phase 5 (CMIP5) and 6 (CMIP6).
This analysis has shown large-scale changes in the hydroclimate of the LM, particularly relevant in tropical areas around the Intertropical Convergence Zone (ITCZ), in the area of influence of the Northern (NAM) and Southern Annular Modes (SAM), and in the Indian Monsoon region, extending from the Middle East to Southeast Asia. The use of several reconstruction-based products allowed the identification with a robustness assessment of those regions more impacted by hydroclimatic changes, while the comparison between reconstruction-based products and model simulations from different ensembles allowed an assessment of the contributions of external forcing and internal variability on the hydroclimate of each region.
Solar irradiance nowcasting based on a network of all-sky imagers: the value of high-resolution data on variability information
Authors: Schmidt Thomas , Stührenberg Jonas , Blum Niklas , Lezaca Jorge , Hammer Annette , von Bremen Lueder , Vogt Thomas
Published: July 2023

The transition to a fossil-free energy system requires the rapid installation of photovoltaic (PV) systems. For Germany, the government is targeting an installed PV capacity of 215 Gigawatts (GW) by 2030 (70 GW today). This target is associated with an increased installation rate of 22 gigawatts PV per year (around three times compared to the 2021 rate). In urban areas, the majority of systems will be installed on rooftops connected to the low-voltage grid. It is therefore likely, that the majority of suitable rooftops will be equipped with PV systems in the next 10 years. In parallel, significant changes in load patterns (e.g. e-mobility, heat pumps) and the integration of battery storages can be expected. 
The efficient integration of the additional PV systems into the electrical grid also requires a detailed understanding of the generation profiles at different levels from the household to the transformer. Therefore, the impact of very short-term solar irradiance variability on ramp rates and balancing effects should be investigated for scenarios with decentralized, but much denser PV generation than today. Since this variability is mainly caused by small scale cloud dynamics, high resolution information on temporal and spatial cloud cover and irradiance distribution is needed.
In northwestern Germany, DLR has installed and is operating Eye2Sky, a dense network of allsky imagers (ASI). At 30 different locations, high-resolution fisheye images of the sky are taken every 30 seconds. At 10 locations, the images are complemented by radiation and meteorological measurements. The Eye2Sky network covers about 100 km x 100 km centered at the city of Oldenburg. It has a low ASI density in rural areas and a high density in city of Oldenburg, thus providing an almost complete coverage of the city. 
Eye2Sky is used to study solar irradiance variability in the city of Oldenburg at a high spatial (50 meters) and temporal (30 seconds) resolution. This enables simulations of single rooftop PV systems. Compared to state-of-the art radiation data sources like satellite images or numerical weather models (NWP), the camera information in Eye2Sky resolves cloud details that cause solar irradiance fluctuations on small scales down to household level.
In this work, we would like to present a solar irradiance nowcasting validation from the ASI network in Oldenburg and its comparison with methods based on satellite (MSG) as well as NWP (ICON-D2) data. Emphasis will be made on the ability of the different methods to reproduce the spatio-temporal variability under different cloud conditions.
The signature of extreme meridional eddy energy transports on modes of circulation, heatwaves and droughts in Northern Hemisphere mid-latitudes
Authors: Lembo Valerio , Fabiano Federico , Galfi Vera Melinda , Graversen Rune Grand , Messori Gabriele
Published: July 2023

Extremes in extratropical meridional energy transports in the atmosphere are associated with the dynamics of the atmosphere at multiple spatial scales, from planetary to synoptic. This is related to the nature of amplifying baroclinic waves, that are fundamentally intermittent and sporadic, significantly affecting the net seasonal transport across latitudes. In this work, we take advantage of a zonal wavenumber decomposition of meridional energy transports throughout the Northern Hemisphere mid-latitudinal channel to investigate how extreme transports affect the main modes of circulation, namely weather regimes identified through k-means clustering of 500 hPa geopotential height and sea-level pressure fields. We find that, in general, planetary-scale waves determine the strength and meridional position of the synoptic-scale baroclinic activity with their phase and amplitude. During winter, largest wavenumbers (k = 2–3) are key drivers of the meridional-energy-transport extremes, and planetary- and synoptic-scale transport extremes virtually never co-occur. During summer, extremes are associated with higher wavenumbers (k = 4–6), identified as synoptic-scale motions. We look further into the implications of such extreme transports by looking at heat waves and cold spells over continents in the Northern Hemisphere, as well as proxies of droughts, investigating the role of moisture transports and the moist component in static energy transport through the signature of changes into evapo-transpiration and related latent heat fluxes at the land surface. Characterizing the clusters of extreme transport events in space and time, the persistence and co-existence of heat/cold waves/spells and drought over specific regions is investigated in light of the dominant modes of atmospheric dynamics evidenced through the wavenumber decomposition.
Evaluation of human thermal stress within urban environments in Athens, Greece
Authors: Nastos Panagiotis T. , Solomos Stavros , Polychroni Iliana D. , Nastou Marina - Panagiota P. , Zerefos Stelios
Published: July 2023

Climate change has led to national, regional and local adaptation measures. However, these measures are not usually implemented in a targeted way, i.e. in urban areas with the most significant problem, or they are not designed in the optimal way to have the maximum efficiency at local scale. Towards this perspective the evaluation of human thermal stress in different urban environments, using appropriate models at very high resolution is considered fully appropriate.
The assessment and quantification of the thermal comfort for selected urban districts within the wider Athens area, are performed by the application of PET (Physiologically Equivalent Temperature) and UTCI (Universal Thermal Climate Index) indexes, which are based on the energy balance of the human body. The above indexes are calculated with the computational fluid dynamics (CFD) model ENVI-met, at city scale (resolution 1 × 1m). Measurements from the nearest meteorological stations as well as sub-scaling of the ERA5 data of the European COPERNICUS service at a local scale of 1 × 1 km with the atmospheric model WRF, are used as input data to the CFD model. The simulations are evaluated using high spatial and temporal resolution measurements obtained by a bicycle equipped with meteorological sensors and by an unmanned aerial vehicle equipped with a thermal camera. Further, the input data for future runs are obtained from downscaling of the emission mitigation scenario (RCP4.5) and the extreme climate scenario (RCP8.5) with the WRF model.
The findings of the analysis will provide comprehensive actions in order to optimize the resilience of the urban environment to various climate change scenarios.
Acknowledgements: This research is co-financed by European Regional Development Fund  and Greek Operational Program “Competitiveness, Entrepreneurship & Innovation (NSRF 2014-2020), entitled “Bioclimatic urban design services for the sustainability and resilience of the urban environment in the context of climate change (BIOASTY)”
Evaluation of the representativity of reference long-term surface flux measurements in an heterogeneous landscape : the Météopole campaign (MOSAI project)
Authors: Jomé Mathilde , Lohou Fabienne , Lothon Marie , Canut Guylaine , Couvreux Fleur , Brut Aurore , Derrien Solène , Maurel William , Etienne Jean-Claude , Vial Antoine , Garrouste Olivier
Published: July 2023

The meterological phenomena draw their energy from the Earth’s surface and dissipate most of their energy close to the surface. The land surface, through its topography, soil moisture, temperature or vegetation activity, impacts the atmosphere from daily to seasonal time scale. The Working Group on Numerical Experimentation survey on systematic errors established that the outstanding errors in the modelling of surface fluxes of momentum and sensible and latent heat is the second most important issue. Therefore to reduce these biases, an accurate assessment of the Land-Atmosphere (L-A) exchanges, and their correct representation, are essential for weather and climate forecasts.
The evaluation of L-A exchanges in numerical weather and climate prediction models in the context of heterogeneous surfaces is the main objective of the Models and Observations for Surface-Atmosphere Interactions (MOSAI) project. The main objective of our study corresponds to the first scientific objective of MOSAI : to investigate and determine the uncertainty and representativeness of L-A exchanges measured over heterogeneous landscapes by reference towers. To achieve these objectives, dedicated field experiments are needed to document the variability of the L-A exchanges within a grid mesh around the ACTRIS sites. A set of a one year-field campaign per site are currently performed at Météopole (Toulouse, 2021), at SIRTA (Palaiseau, 2022) and at P2OA (Lannemezan, 2023).
Two long-term objectives are defined with the aim of completing the measured surface flux at the ACTRIS sites. The first objective concerns the horizontal representativeness of the local measured surface flux in the heterogeneous landscape at the scale of the ESM or NWP grid. The second one is here to quantify the surface flux uncertainties (random and systematic errors) and provide information on the SEB non-closure at each site.
Results concerning the second objective will be presented using the Météopole campaign during which six sites with different surface types were implemented to estimate the Surface Energy Balance (SEB). The arrangements of the different surface patchesis studied to quantify the heterogeneity of our landscape (patches size distribution,...). With that, several indicators that aim to quantify the surface flux heterogeneities are investigated and applied to several domain sizes (from footprint to larger domains). These indicators are cross-analysed with the SEB non-closure to investigate a possible impact of surface heterogeneity and secondary circulations on SEB non-closure.
Trends in intraseasonal temperature variability in Europe: comparison of station data with gridded data and reanalyses
Authors: Krauskopf Tomas , Huth Radan
Published: July 2023

Trends in temperature variability are often referred to have higher effect on temperature extremes than trends in the mean. We investigate trends in three complementary measures of intraseasonal temperature variability: (a) standard deviation of mean daily temperature (SD), (b) mean absolute value of day to day temperature change (DTD) and (c) 1-day lagged temporal autocorrelation of temperature (LAG). It is a well-established fact that different types of data (station, gridded, reanalyses) possess different temperature characteristics and particularly its trends. Moreover, it has been uncovered during our research that trends in measures of variability are more sensitive to data inhomogeneities. Therefore, we use five different datasets, one station based (ECA&D), one gridded (EOBS) and three reanalyses (JRA-55, NCEP/NCAR, 20CR), and compare them. The period from 1961 to 2014 where all datasets overlap is examined and the linear regression method is utilized to calculate trends of investigated measures in summer and winter. Intraseasonal temperature variability tends to decrease in winter, especially in eastern and northern Europe, where trends below -7% per decade are detected for all measures. Decreases in DTD and LAG (increase in persistence) prevail also in summer while summer SD tends to increase. The increase in the width of temperature distribution and the simultaneous increase in persistence indicate a tendency towards the rise in the frequency of extended extreme events in summer. Our results do not imply that reanalyses are the least accurate in determining trends of temperature variability. JRA-55 appears to be the least diverging from other datasets, while the largest discrepancies were detected for DTD at climate stations. Our consequent research expose that the type of calculation of mean daily temperature is crucial to the resulting value of DTD as T(7+14+21+21)/4 shows warm days warmer and cold days colder than T(0-0)/24. This is the possible explanation of discrepancies in DTD trends as many of ECA&D stations (e.g. German stations at 2001) underwent a change in this calculation during the observed period.
Precipitation Intensity & Variability Over UAE – Connection with Indian Ocean SST
Authors: Awadh Saif , Al Hadhrami Sultan
Published: July 2023

 
In this study, we focus on analyzing the variability and intensity of rainfall over the UAE, associated with the SST over the North Indian Ocean during the period from 2001 to 2010. The first part of the study consists of diving the 10 years into two epochs (5 years each) and studying the difference in the climatology of precipitation over UAE and SST variation over the North Indian Ocean. The variability of monthly precipitation climatology is compared with the monthly SST climatology over the Arabian Sea and Bay of Bengal for each epoch to find the correlation. It was observed that the months with positive SST anomaly over the North Indian Ocean had high precipitation values over UAE. The analysis was conducted for individual years from 2001 to 2010, and the months and years which resulted in high precipitation peaks in the two epochs were identified. The surface meteorological parameters like temperature, relative humidity, horizontal winds, and geopotential height were analyzed for the selected years and compared with the precipitation distribution over UAE, for further validation of the results. The results showed that a high-pressure system always resonates over the Arabian Peninsula which can be due to the Indian High extending to the UAE region making the horizontal winds over the Arabian Peninsula to circulate clockwise. This can cause an increase in inflow of air from the northern part of the Arabian Gulf which causes the wind speeds to increase and possibly carry the moisture content over the Arabian Gulf to produce precipitation. For more validation of results, a second part of the study with detailed analysis of SST in an enlarged domain will be conducted.
Climate conditions in SW Greenland in the second half of the 18th century
Authors: Singh Garima , Przybylak Rajmund , Wyszyński Przemysław , Araźny Andrzej , Chmist Konrad
Published: July 2023

To determine the climate conditions of SW Greenland in the second half of the 18th century, two series of meteorological observations have been used. The first series (Neu-Herrnhut, 1st Sep 1767−22nd Jul 1768) is the oldest long-term series of instrumental measurements of air temperature and atmospheric pressure made by Christopher Brasen (1738−1774). The second (Godthab, Sep 1784−Jun 1792) contains the most significant and reliable data for Greenland for the study period. Observations were made by Danish Reverend Andreas Ginges (1754–1812) using methodology and instruments provided by the Meteorological Society of the Palatinate. Sub-daily or daily data exist for the following periods: Sep 1784−Jun 1785, Jan−Jun 1787, Nov−Dec 1788, Jan 1790−Jun 1792 and are available in the manuscript entitled Astronomiske og meteorologisk Iagttagelser, anstillede i Godthaab i Grønland 1782–1792 and in the society’s yearbook Ephemerides Societatis Meteorologicae Palatinae, which contains data for 1787. All available historical data were quality controlled and corrected prior to being used to calculate daily (MDAT), monthly, seasonal and yearly means. Daily means have been used to calculate less typical climate statistics such as day-to-day temperature variability, thermal seasons, growing degree days (GDD), air thawing index (ATI), positive degree-days (PDD) and air freezing index degree-days (AFI).
            Compared to present day (1991–2020), air temperature in Godthab was, on average, warmer in 1767–68 and colder in 1784–92. In 1767–68, the turn of December to January was exceptionally warm, with positive MDAT reaching even 5 °C. So too was summer significantly warmer than today. On the other hand, in 1784–92, autumn and particularly winter were markedly colder than today, while temperatures in the rest of the year were comparable to present day. The GDD and ATI in each month in the expedition year 1767–68 were equal to or higher than the norm observed in 1991–2020. No important changes were observed for PDD, while AFI was usually lower than the present-day norm. The GDD and ATI in the period 1784–92 usually (except 1787) do not exceed the maximum and minimum values from 1991–2020. The PDD during the cold season (from October to April) in the period 1784–92 is close to the average and minimum PDD in 1991–2020, but the AFI values in 1784–92 are between the average and maximum AFI values calculated for 1991–2020.
The work was supported by the National Science Centre, Poland project No. 2020/39/B/ST10/00653.
Bow echo detection and rainfall scenarios : two ways to extract relevant information from convective-scale ensembles
Authors: Mounier Arnaud , Raynaud Laure , Rottner Lucie , Plu Matthieu
Published: July 2023

The use of ensemble prediction systems (EPS) enables the quantification of forecast uncertainty. However, the use of EPS is challenging due to the large amount of information it provides. Forecasts from EPS are typically summarised using statistical measures (such as quantiles maps). Although this mathematical representation is effective in capturing the ensemble distribution, it lacks physical consistency, which raises issues for many applications of EPS in an operational context. We propose two different ways for providing physically consistent synthesis of French convection-permitting AROME-EPS forecasts.
The first way is dedicated to a specific type of Mesoscale Convective System (MCS) with a bow shape, called a bow echo. To summarise the risk of bow echoes in AROME-EPS forecasts, a convolutional neural network has been trained to automatically detect these MCSs in AROME-EPS members. Different synthesis plots are based on these detections. They have been designed in collaboration with forecasters and improved, based on feedback since 2021. A case study will be presented to better understand the usefulness of these synthesis plots.
The second way is a rainfall scenario synthesis. The aim is to automatically generate a few scenarios that are representative of the different possible outcomes. Each scenario is a reduced set of EPS members. To design a scenario synthesis, the procedure can be divided into two parts. The first step aims to extract relevant features from each EPS member to reduce the problem dimensionality. Then, clustering is done based on these features. The originality of our work is to leverage the capabilities of deep learning for feature extraction. For this purpose, we use a convolutional autoencoder (CAE) to learn an optimal low-dimensional representation (also called latent space representation) of the input forecast field. In this work, the algorithm is developed to work on 1-hour accumulated rainfall from AROME-EPS. To visualise these scenario synthesis, an interactive plot has been developed. This interactive plot summarises information concerning scenario size, members included in a scenario or trajectory across lead times for a specific member. This plot will be presented for a case study in this presentation.
The two methods proposed are shown to provide an additional and complementary information, useful for facilitating the human expertise. In addition, their design is generic enough to be applied to other events and variables.
ARSO podcast - a podcast from the Slovenian Environmental Agency
Authors: Klancar Matija
Published: July 2023

The ARSO podcast story began about five years ago. The main idea was how to present interesting weather events at home and around the world in the form of a new format - podcast. The new format began to gain more and more recognition in the media. On-demand broadcasts have become increasingly popular, and with some earlier experience, a pilot episode of the ARSO podcast on tropical cyclones was recorded in the summer of 2018. Before the official start of recording, it was necessary to arrange all the technical preparation. That was necessary for the smooth operation of the last five years. It was decided that we are publishing the ARSO podcast every 14 days, which turned out to be a relatively very common frequency. The first episode of the ARSO podcast was recorded at the beginning of December 2018. It was about global warming projections, a project nearly finished at our Agency. During these five years, a lot of different natural science topics have taken place, ranging from hydrology, geography, computer science, seismology, and, of course, meteorology, which represents most of the podcast's main topics. During this time, the format of the podcast changed slightly and finally settled on the main topic, where it is presented by one or more guests. There is also a weather forecast for the next few days presented by one of the weather forecasters. ARSO podcast is present on most audio platforms, where you can subscribe to it, and all episodes are also available on our website. This year we recorded our 100th regular episode, and we believe there will be quite a few more in the future.