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To provide quantitative elements to the expected rate of change of flood quantiles in Alpine basins due to global warming, a systematical assessment of a river network is undertaken in this paper through the implementation of a geomorphoclimatic approach. The model, called "FloodAlp" produces the flood frequency curve of mountainous catchments based on the stochastic interaction of precipitation and temperature. In view of a widespread application, FloodAlp was revamped here and applied to all the sections of the river network of the Chisone basin (Northwest Italy) identified through a 50 m resolution digital elevation model (DEM). We show that, based on the decrease in snow-affected contributing areas, flood frequency can increase up to 8 times compared to the current frequency, with amplifications depending on the local elevation characteristics of sub-basins. [ABSTRACT FROM AUTHOR]

The Pedersen process is an alumina production process, which combines pyrometallurgical and hydrometallurgical methods. In the pyrometallurgical stage, limestone is calcined and CO2 is generated. This off-gas can be captured with a high CO2 concentration. At the end of the hydrometallurgical process, aluminum hydroxides, like bayerite, are precipitated using CO2. In this paper, experimental work on precipitation of aluminum hydroxides through the addition of a mixture of CO2, O2 and N2 is presented. The parameters varied, as were the percentages of each gas and the temperature. The indicators measured were the time until the beginning of precipitation and the time that the precipitation lasts. These tests simulate the use of a smelter furnace off-gas in the precipitation stage of the Pedersen process and have shown promising results. [ABSTRACT FROM AUTHOR]

According to the recent IPCC report, the Mediterranean, and consequently the region of Sitia, is one of the European "climate hotspots". Its complex geomorphology and multiple locations with very distinct microclimate characteristics make high-resolution climate projections critical for the appropriate determination of effective local adaptation policies. The paper demonstrates the significance of the dynamical downscaling of climate information from 20 km x 20 km to a 5 km x 5 km scale of temperature, precipitation, drought, and fire risk for the region of Sitia and present, near-, and far-future climate projections using RCP4.5 and RCP8.5 scenarios. [ABSTRACT FROM AUTHOR]

One of the impacts of climate change is an increase in the frequency and intensity of extreme rainfall events. This has very significant social and economic consequences for the affected areas (flooding, loss of life, destruction of infrastructure, etc.). Future trends indicate a further increase in extreme rainfall in the second half of the century, making the need for the timely and accurate forecasting of these phenomena more urgent than ever. However, despite the technological development of weather and climate models in recent years, there are still limitations in detecting the extremes, especially regarding the precipitation parameter. Extreme precipitation events show a link with temperature. The Clausius-Clapeyron (CC) equation, which relates temperature to saturation vapor pressure (es), is used to study the sensitivity of precipitation to temperature increase because it can estimate the increase in the available atmospheric water vapor with respect to temperature. Focusing on the Thessaloniki region in Greece, the aim of this paper is to investigate the applicability of the Clausius-Clapeyron relation to the scaling relationship between extreme precipitation intensity and surface air temperature. An additional attempt is also made to test the possibility of improving the underestimation that the reanalysis models exhibit in recording the extremes and in particular the ERA5 Land dataset. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are increasingly being used in meteorology research due to their ability to overcome challenges such as difficult access to hazardous locations and the need for high-resolution and real-time data. UAVs provide accurate and precise high-resolution data that allows scientists to study small-scale weather phenomena in unprecedented detail. This survey highlights the different types of UAVs used in meteorology, including fixed-wing, rotary-wing, and hybrid UAVs, as well as the various payload options available, such as sensors for temperature, humidity, pressure, wind, and precipitation. Overall choosing the appropriate UAV for meteorological applications relies on meeting specific mission requirements, including various factors. [ABSTRACT FROM AUTHOR]

Design and management of combined sewer overflows (CSOs) have been, so far, mainly based only on complying a fixed dilution rate of wastewater in stormwater during rain events. This poses serious environmental issues, since the definition of the acceptable dilution does not consider the characteristics of the upstream urban catchment, nor the climatic features, nor those of the receiving water body. Overflows are usually designed for activation when the mixed discharge reaches about five-times the mean wastewater discharge (though it may vary, depending on country regulations), the latter being the mean dry weather wastewater discharge. Accordingly, recent regulations started enforcing limits also on the frequency of overflows. Overflow activation frequency and discharged volumes of pollutants may depend on the upstream catchment features as well as on the precipitation regime. The great variability in these factors could make the impact on the receiving water body of similarly designed overflows quite different. In this study, the behavior of a CSO placed at the outlet of urban catchments with the same size but different characteristics was simulated with SWMM. The considered hydrological parameters were catchment imperviousness, width and slope, Manning coefficient and depression storage. Served population characteristics affecting the combined sewer hydraulic regime were studied by changing the population density and the mean wastewater discharge per capita. After defining realistic ranges for each parameter, the time series of discharged overflows were calculated for all the combinations of the variable catchment parameters, corresponding to 20-year-long precipitation series from a single rain gauge. The obtained results, although preliminary, indicate that CSOs' impact on the receiving water body strongly depends on the characteristics of the upstream urban catchment. Therefore, such characteristics should be considered in CSO design and management. [ABSTRACT FROM AUTHOR]

In the present study, the introduction of the Innovative Polygon Trend Analysis (IPTA), a non-parametric trend analysis methodology, is proposed as an alternative to the classical trend analysis methodology, according to which processes (normality, independence, and pre-whitening) are not necessary. Monthly precipitation measurements from Thessaloniki are analysed for the period 1971-2020, subdivided into two consecutive equal periods, to identify inherent trends among months and seasons, respectively. A finer interpretation of trends, with physical and numerical explanations and inferences, leads to the obtained results; the total monthly and seasonal precipitation values, their associated standard deviations, as well as trend slopes and trend lengths, are depicted. Increasing trends between the two sub-periods are identified for most months: winter and autumn. [ABSTRACT FROM AUTHOR]

The Atlantic Meridional Overturning Circulation (AMOC) is a major oceanic circulation system in the Atlantic Ocean, which transports heat to the poles and cold saline waters to the tropics. The AMOC mechanism is responsible for many climate and weather systems; however, it is naturally unstable, and it changes in time depending on sea-ice melt, wind patterns, solar radiation variations, etc. At the same time, there are recent indications that the AMOC is in a weaker state than previously thought with impacts more severe than expected. Knowing that the AMOC can impact remote systems, and given the risk the Mediterranean faces with climate change progressing, we focus on the relationship between the AMOC and the Mediterranean climate, based on AMOC indicators and monthly ERA5 fields (sea surface temperature, air temperature and total precipitation) from 1959 to 2021. We find that the two systems exhibit a relationship although it is not homogenous. More specifically, the AMOC is highly correlated with sea and air temperatures of the central and eastern Mediterranean with a time lag of up to 2 years, while strong links are found with the entire Mediterranean's annual total precipitation up to 3 years ahead. The results suggest the possibility of predicting the occurrence of significantly extreme periods in the Mediterranean several months in advance. [ABSTRACT FROM AUTHOR]

Climate change (CC) has altered the hydrological cycle, mainly due to changes in temperature and precipitation, leading indirectly to regional water shortage issues, especially in the Mediterranean areas. The objective of this work was the investigation of the CC impact on water resources. Hydrological simulations under several CC scenarios were performed for the Vivari subbasin, located in the Eurotas river basin, Peloponnese, Greece. The analysis was carried out by applying the Thomas ABCD water balance model on a monthly basis, initially for the period between 2005 and 2009, to calibrate the model using available runoff measurements. Then, CC scenarios were incorporated into the model and the results are presented indicatively for three periods: a historic period (1970-2000), which was used as the reference period for comparisons; and two future periods: 2031-2060 and 2061-2090. Simulations for the three periods were based on freely available monthly precipitation and temperature timeseries, which were provided by the Data Extraction Application for Regional Climate (DEAR-Clima) web application tool. Results regarding average values, trends, and other statistics for monthly runoff are provided for the three periods and for several scenarios. [ABSTRACT FROM AUTHOR]

This study aims to provide insight regarding the future evolution of a series of important agroclimatic indicators for a specific farming area of viticulture in Stimagka, Greece. The calculated indicators cover various aspects of the climate and its impact on agriculture and can be categorized into four broad categories: temperature-, precipitation-, drought-, and animal comfort-related indicators. An ensemble of state-of-the-art regional climate model simulations with a spatial resolution of 12 km are used to calculate the indicators for the period 1986-2055. For the period 2006-2055, two scenarios of possible future evolution of anthropogenic greenhouse gases are used: rcp4.5 and rcp8.5. Results indicate a clear future increase in temperature-related indicators in the region and also more persistent drought conditions. [ABSTRACT FROM AUTHOR]

Aridity monitoring is critical in forestry as it may affect forest growth, species diversity, and treeline shift. A widely used approach to assess the status of and changes in aridity is the aridity index (AI), defined as the ratio of precipitation (P) to potential evapotranspiration (PET). This study investigates the temporal change in the aridity index (AI) at a fir forest site between two distinct climatic periods: 1961-1990 and 1991-2020. To that end, long-term time series of mean monthly air temperature and total monthly precipitation from a forest meteorological station (1180 m a.s.l.) were collected and processed. Furthermore, the PET was estimated using a parsimonious parametric model based on a simplification of the Penman-Monteith formula. The results indicated that AI values slightly changed between the two considered climatic periods, while the climate was classified as humid and remained unchanged. [ABSTRACT FROM AUTHOR]

A forward advection scheme is incorporated in an advanced data assimilation model to provide very short-term predictions. The Local Analysis and Prediction System (LAPS) is implemented in the nowcasting mode in a case study of extreme precipitation event over Attica, Greece. The LAPS assimilated remote sensing data from satellite retrievals and XPOL radar precipitation measurements to produce objective analyses alongside their nowcasts in a forecast window up to 3 h. The results indicate that the assimilation of remote sensing data can increase the short-term precipitation predictability, with varying performance depending on the type and the combination of the assimilated remote sensing data. [ABSTRACT FROM AUTHOR]

Precipitation is a key component of the hydrological cycle and directly affects water availability and hydrometeorological hazards. The objective of this study is to evaluate the performance of two reanalysis precipitation datasets, ERA5 and ERA5-land, in reproducing precipitation accumulations over Greece. These data are compared against rainfall measurements provided by the dense network of surface-automated weather stations operated by the National Observatory of Athens. The comparisons are performed over a 10-year period (January 2010 to December 2020) at multiple temporal and spatial scales. Several statistical metrics are used to assess the performance of the reanalysis precipitation against rain gauge observations. The suitability of gridded products is tested by capturing the temporal and spatial variability in precipitation using accuracy metrics. [ABSTRACT FROM AUTHOR]

Remote sensing of snowfall has been proved to be a great challenge since the start of the satellite era. Several techniques have been applied to satellite data to estimate the fraction of frozen precipitation that reaches the surface. This study aims at investigating the efficacy of machine learning (ML), and especially deep learning (DL), in estimating the precipitation phase of the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM-IMERG). To achieve this, a training phase with hourly high-resolution numerical model outputs and in situ data was chosen for the period of late-2020 and 2021. Preliminary results show that ML models can estimate the precipitation phase with relatively high accuracy based on several case studies. The findings suggest that ML models offer a promising approach for advancing the nowcasting of snowfall and building a long-term archive dataset of IMERG-based snowfall using conventional real-time data. [ABSTRACT FROM AUTHOR]

The Agroray project was aimed at the development of a high-resolution numerical weather prediction system that will allow farmers to optimize their activities and protect their products from adverse weather events. The system is based on the Weather Research and Forecasting model and focuses on Central Macedonia with a horizontal grid spacing of 1 km. The aim of this article is to describe the model configuration and validate its performance during selected frost and intense precipitation events. The evaluation against station measurements and radar precipitation showed that the optimum model setup includes Corine land use and enhanced vertical resolution near the surface. [ABSTRACT FROM AUTHOR]

In this study, we present the preliminary results of our effort to construct a new high spatial resolution precipitation database (1 km x 1 km) over Greece, on an annual and monthly basis. A variety of spatial parameters (i.e., latitude, longitude, altitude, aspect, distance from water bodies, among others) and ERA5 reanalysis data were used as independent variables in an algorithm combined with the Regression Kriging with a Histogram-Based Gradient-Boosting Regression Tree. The dependent variable in the algorithm was the gauge data covering most of the area studied. Maps were constructed for the ERA5 reanalysis and the modelled mean precipitation totals on an annual and monthly basis for the 1980-2010 study period. The findings of the analysis show that the applied methodology improves the spatial resolution and distribution of the ERA5 reanalysis precipitation totals over Greece. Furthermore, when comparing the modelled high spatial resolution datasets against ERA5 datasets over the gauge precipitation totals, the model achieved an average R² improvement of 31.7%, with the largest improvement recorded on an annual basis, while the RMSE decreased by 16.6% on average and more than 40% on an annual basis. [ABSTRACT FROM AUTHOR]

One of the main crops cultivated in Greece is the olive tree. In recent years, olives around the Mediterranean Basin and especially in Greece have been facing increasingly high temperatures and are more often exposed to water deficits, inducing severe abiotic stress, thus affecting plant physiology and productivity. Future projections point to a general increase in temperature of up to 2 °C. Precipitation is projected to decrease in northwestern Halkidiki, leading to enhanced water needs and resulting in a possible decrease in yield. The increase in temperature, especially in the winter season, seems to impact flowering buds. The small number of days with low temperatures resulting in reduced flowering during spring will decrease the quantity and quality of olives and oil. [ABSTRACT FROM AUTHOR]

The synoptic and dynamic characteristics of three extreme precipitation events over the area of Pieria are analyzed. The objective of this study is to identify similarities in structure, intensity and behavior of the synoptic patterns that were responsible for the extreme precipitation over the examined area. Precipitation-derived data from weather radar images were also used to identify the intensity and extent of the events. The high-resolution non-hydrostatic WRF-ARW numerical weather prediction model was also used to simulate these intense precipitation events. Results indicated analogous synoptic conditions in all three cases suggesting the strong synoptic forcing of the events in extreme precipitation over the area. The model was able to capture these events adequately, even though discrepancies occurred regarding the intensity and the location of the precipitation maxima. [ABSTRACT FROM AUTHOR]

Intense cyclones with tropical-like characteristics (also known as "medicanes") occasionally develop in the Mediterranean. They can cause extreme weather phenomena with catastrophic potential due to excessive precipitation, windstorms, and coastal flooding. In this work, the impact of air-sea interactions on the track and intensity of a Mediterranean cyclone is evaluated using an atmosphere-only configuration (WRF) and a two-way coupled ocean-atmosphere configuration (NEMO-WRF). As a case study, we focus on a medicane that evolved over the central Mediterranean basin during 15-20 September 2020 (named "Ianos"), causing severe damage to western Greece. The atmosphere-only simulations were carried out using constant initial SST throughout the model integration, while in the coupling setup, the SST was consistent with the air-sea fluxes and updated every 6 min by the ocean model. The results from the two modeling approaches highlight the importance of air-sea feedbacks for predicting Mediterranean cyclone intensity, along with the forecast initialization time. [ABSTRACT FROM AUTHOR]

The limited availability of wind profile measurements has hindered atmospheric models and climate systems' understanding. The European Space Agency's Aeolus mission's space-based Doppler wind lidar technology could solve this issue by measuring wind profiles in Near-Real-Time, providing valuable data for Numerical Weather Prediction (NWP) models. A case study using the COSMO NWP model demonstrates the potential of Aeolus data in improving NWP models by examining the impact of Medicane IANOS in September 2020 over the Thessaly plain. The study aims to improve our ability to predict severe weather events and advance our understanding of Earth's atmosphere. [ABSTRACT FROM AUTHOR]

This study examined the association between precipitation indices and atmospheric processes in Southeast Europe using ERA5 land data from 1961 to 2020. The Rx1day intensity index showed predominantly positive trends in heavy precipitation events, resulting in more intense precipitation over fewer days in various parts of Southeast Europe, particularly during autumn. These findings highlight the potential increase in extreme precipitation frequency and intensity due to ongoing climate change, leading to an elevated risk of flood events. Such insights provide valuable information for policymakers and stakeholders to adapt to the impacts of extreme precipitation events. [ABSTRACT FROM AUTHOR]

This study examines extreme precipitation seasonality in the Mediterranean for the future period 2081-2100, based on the climate scenario SSP5-8.5. Using data from the CNRM-CM6-1-HR, the study determines the dates of extreme precipitation events using the circular statistics method. The results indicate that almost 50% of grid points experienced the first extreme event of the year between January and February during the reference period. In the future period, there will be an increase in the percentage of grid points experiencing events during the cold period, meaning that there will be a seasonal shift of extreme events to colder months mainly affecting the west and east Mediterranean. [ABSTRACT FROM AUTHOR]

Climate models are fundamental tools for assessing historical climate conditions and projecting future ones. However, the results often differ systematically from observational data. The minimization of these differences is known as bias correction. The present study aims to correct the biases between observed daily precipitation values and the respective simulated ones from a EURO-CORDEX climate model. For this purpose, powerful statistical tools--generalized additive models (GAMs)--are used. GAMs are modified to adjust the simulated rainfall with the highest accuracy, and subsequently, they are evaluated by comparison with observational data. The method was applied to two eastern Mediterranean stations (Larissa in Greece and Larnaca in Cyprus) for the period 1981 to 2005. The results from both stations reveal that GAMs offer a valuable and accurate technique for the bias adjustment of daily precipitation. [ABSTRACT FROM AUTHOR]