Meteorological Situations Research Articles

Required sampling density of ground-based soil moisture and brightness temperature observations for calibration and validation of L-band satellite observations based on a virtual reality

Abstract. Microwave remote sensing is the most promising tool for monitoring near-surface soil moisture distributions globally. With the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions in orbit, considerable efforts are being made to evaluate derived soil moisture products via ground observations, microwave transfer simulation, and independent remote sensing retrievals. Due to the large footprint of the satellite radiometers of about 40 km in diameter and the spatial heterogeneity of soil moisture, minimum sampling densities for soil moisture are required to challenge the targeted precision. Here we use 400 m resolution simulations with the regional Terrestrial System Modeling Platform (TerrSysMP) and its coupling with the Community Microwave Emission Modelling platform (CMEM) to quantify the maximum sampling distance allowed for soil moisture and brightness temperature validation. Our analysis suggests that an overall sampling distance of finer than 6 km is required to validate the targeted accuracy of 0.04 cm3 cm−3 with a 70 % confidence level in SMOS and SMAP estimates over typical mid-latitude European regions. The maximum allowed sampling distance depends on the land-surface heterogeneity and the meteorological situation, which influences the soil moisture patterns, and ranges from about 6 to 17 km for a 70 % confidence level for a typical year. At the maximum allowed sampling distance on a 70 % confidence level, the accuracy of footprint-averaged soil moisture is equal to or better than brightness temperature estimates over the same area. Estimates strongly deteriorate with larger sampling distances. For the evaluation of the smaller footprints of the active and active–passive products of SMAP the required sampling densities increase; e.g., when a grid resolution of 3 km diameter is sampled by three sites of footprints of 9 km sampled by five sites required, only 50 %–60 % of the pixels have a sampling error below the nominal values. The required minimum sampling densities for ground-based radiometer networks to estimate footprint-averaged brightness temperature are higher than for soil moisture due to the non-linearities of radiative transfer, and only weakly correlated in space and time. This study provides a basis for a better understanding of the sometimes strong mismatches between derived satellite soil moisture products and ground-based measurements.

Changing nature of Saharan dust deposition in the Carpathian Basin (Central Europe): 40 years of identified North African dust events (1979–2018)

Several billion tonnes of mineral dust is emitted, and transported through winds every year from arid-semiarid areas. North African dust hot spots located in the Sahara are responsible for 50–70% of the global mineral dust budget. Dust-loaded air-masses originated from these sources can be transported over long distances and can also affect remote areas, such as North and South Americas, Europe, and the Middle East.In this study, we analysed 218 identified Saharan dust events (SDEs) in the Carpathian Basin (Central Europe) during 1979 to 2018. Systematic identification of SDEs and analyses of dust emission, dust source area activity, dust transporting wind systems, and transport routes revealed that different synoptic meteorological patterns are responsible for SDEs, and these are occurring mostly in spring and summer. The characteristic synoptic meteorological background of episodes was also identified, and three major types of atmospheric pressure-system patterns were distinguished.In recent years, several intense wintertime dust deposition events have been recorded in Central Europe. All of the identified unusual episodes were characterised by severe washout of mineral dust material and were related to very similar synoptic meteorological situations. Enhanced southward propagation of a high-latitude upper-level atmospheric trough to north-western Africa and orographic blocking of Atlas Mountains played an essential role in the formation of severe dust storms, whereas the long-range transport was associated with the northward branch of the meandering jet. The occurrence and southerly penetration of high-latitude upper-level atmospheric trough to low-latitudes and the increased meridionality of the dominant flow patterns may be associated with enhanced warming of the Arctic, leading to more meandering jet streams.Particles size of sampled dust material of some intense deposition episodes were very coarse with a considerable volumetric proportion of > 20 µm particles.

The Avalanche of Les Fonts d’Arinsal (Andorra): An Example of a Pure Powder, Dry Snow Avalanche

On 8th February 1996, in the north-western part of Andorra in the Pyrenees, the Les Fonts d’Arinsal (LFd’A) pure powder avalanche was triggered, descending some 1200 m to the bottom of the Arinsal valley and continuing up the opposite slope for about 200 m. This size 4–5 avalanche reached velocities of up to 80 ms−1, devastated 18 ha of forest, involved a minimum volume of up to 1.8 × 106 m−3 and caused major damage to eight buildings. Fortunately, no one was injured thanks to an evacuation, but 322 people lost their properties. This study describes the physical characteristics of the LFd’A avalanche path and provides data on earlier avalanches, the meteorological synoptic situation and snowpack conditions that generated the avalanche episode, the warning and preventive actions carried out, the effects and evidence of the large avalanche, and the defence system implemented afterwards. A discussion of the avalanche dynamics based on observations and damage, including the role of snow entrainment, the total lack of characteristic dense flow deposits, as well as the evidence of a two-phase flow (fluidisation and suspension), is presented. This case study is an example of a paradigmatic large, pure powder, dry-snow avalanche, which will be useful for model calibration.

Analysis of total signal decay and capacity of information data in wireless atmospheric communication links. Part 2

Introduction: Analysis of total signal decay is based on prognosis of the total path loss occurring in the atmospheric communication links, accounting for effects of gaseous structures attenuation and scattering, hydrometeors (rain, snow and clouds) absorption and attenuation, and turbulent structures fast fading on radio and optical signals passing atmospheric channels with fading. Purpose: To perform a novel methodology of definition and estimation of effects of decay, absorption, scattering, and fading of radio and optical signals propagating in atmospheric channels in various meteorological conditions. Results: Wasanalyzed the impact of gaseous structures, hydrometeors and turbulent structures in total path loss for link budget design and in degradation of data stream parameters, such as capacity, spectral efficiency and bit-error-rate, which lead in loss of information data signals passing such kinds of channels with fast fading and decrease of quality of service. An optimal algorithm was found of the total path loss prediction for various meteorological situations occurring in the real atmosphere at different heights and for various frequencies of radiated signals. A method was proposed of how to evaluate the data stream parameters, capacity, spectralefficiency and bit-error-rate, accounting for the effects of atmospheric turbulence impact on fast fading, which corrupts information passing such kinds of channels. All practical tests were illustrated by the use of the MATLAB utility. A new methodology was proposed on how to evaluate and estimate the capacity, the spectral efficiency, and the loss in energy and in the information data stream for different scenarios of radio and optical signals propagation via atmospheric channels with fading caused by different meteorological conditions. Practical relevance: The results obtained allow to achieve better accuracy of prognosis and increase quality of service in atmospheric communication channels.

Modeling the forecasted power of a photovoltaic generator using numerical weather prediction and radiative transfer models coupled with a behavioral electrical model

The intermittency of the solar radiation is the big challenger for the management of electrical SMART GRID network. So the forecasting of the solar radiation remains the crucial objective to anticipate the injection of the electrical power produced by a photovoltaic generator. In this study, we use the Numerical Weather Prediction model WRF coupled to a radiative transfer model libRadtran to forecast the global, direct and diffuse solar radiations. The NMM core of WRF model was used to predict the vertical profiles of the atmospheric meteorological parameters such as liquid and ice water concentration, cloud cover, relative humidity, temperature, etc. These data are used as input in libRadtran to calculate the hourly solar radiations components (Direct, Diffuse and Global) in real meteorological situations. The radiation values are obtained on regular geographical grid points. A behavioral electrical power model is used to compute the electrical power produced by a photovoltaic generator located at the Center of Development of Renewable Energy in the city of Algiers in Algeria. The comparative study shows well that the results are very encouraging.

Effectiveness of an air quality intervention: an accountability study in a highly polluted industrial town

Public interventions to reduce industrial emissions and improve air quality are particularly necessary in areas that suffer an environmental and health emergency. Taranto (Apulia region, Southern Italy) is one of the most industrialized cities in Southern Italy due to the massive presence of industrial sites, including a huge steel plant. The latter hosts a large open-air mineral deposit, whose dust strongly impacts the Tamburi neighborhood, downwind of the plant when the wind blows north-wester. In order to reduce the PM10 (particulate matter) and B(a)P (Benzo(a)pirene) concentrations in this neighborhood, the Apulia Region enacted a law restricting some industrial activities during certain meteorological situations, called wind days, characterized by strong north-westerly winds. Connected to the regional law, there was a Local Health Unit warning to the Tamburi population to ventilate indoor environments during the central hours of the day. The aim of this work is to assess the effectiveness and the appropriateness of the intervention implemented and to evaluate whether it effectively improved the air quality in the neighborhood close to the mineral deposit. Time-space statistical analysis of PM data measured by the fixed monitoring network before and after the intervention period was carried out. The analysis was performed for different meteorological conditions, different wind days characteristics (long/short), time periods, and other pollutants such as PAH (polycyclic aromatic hydrocarbon), which includes B(a)P for which measurements were not available. In the area closest to the industrial area, there was a reduction in the difference between the concentration of PM10 on wind days and those in other weather conditions. The reduction was more consistent on long, persistent wind days, when the difference in concentrations reduced from 13.3 to 3.9 μg/m3. However, the uncertainties regarding the wind days predictions suggest that the PM reduction may only partially be attributed to the regional law. Furthermore, the analysis of the PAH showed that there are weather conditions other than wind days that lead to a deterioration in the air quality in the neighborhood. Regarding the warning given by local health authorities to protect the population from dust injuries, the wind days daily PM10 profiles do not evidence a sharp reduction during the selected time slot, while other industrial pollutants clearly increase in the same time slot. Overall, results evidence the partiality of the intervention and call for a more comprehensive emissions plan to reduce their impact on air quality. In general, the study shows the need to periodically evaluate the effectiveness of any intervention and to take the consequent decisions to adapt them.

Assessment of the dust pollution level in the workspaces by the methods of mathematical modeling

Coal dust leakage from coal stacks leads to intensive contamination of the working areas. Therefore, determining level of air pollution near the coal piles for various meteorological situations, when new coal piles are arranged, is an important applied problem. For practice, it is necessary to have quick-calculating mathematical models whiсh take into account the most significant physical processes impacting on formation of contamination zones near the coal piles. Today, to predict the level of air pollution at dust leaking from the coal stacks, the normative technique OND-86 or the Gauss model is used. These forecasting methods make it possible to quickly calculate the contamination zones, but they do not take into account geometric shape of the coal stack and unevenness of the velocity field near it. The subject of this research was creation of a mathematical model for predicting the level of air pollution near coal piles with taking into account the aerodynamics of air flows around them. The purpose of the work was to develop a set of numerical models for quick calculation of the level of air pollution at coal dust leaking from the coal piles with taking into account the uneven emission of dust from different areas of the stack surface. The modelling equations are the three-dimensional mass transfer equation (Marchuk's model) and the three-dimensional equation for the velocity potential. The Marchuk's model allows taking into account rate of the coal dust particles settling, parameters of turbulent diffusion and uneven air flow rate near the coal pile. The Dirac delta function is used for modelling coal dust leaking from various sections of the coal pile. For the numerical solution of the mass transfer equation, a difference splitting scheme is used. On the basis of the three-dimensional equation for the velocity potential, an uneven velocity field near the coal pile is determined. The Richardson method is used for numerical solution of the three-dimensional equation for the velocity potential. An algorithm for solving the problem of calculating a level of contamination of working areas near a coal pile is considered. The description of the structure of the created complex of computer programs is given.

Real-time NWP simulations over north-Africa and Morocco using the Unified Environmental Modeling System (UEMS)

Weather forecasting is a very challenging task due to dynamical and nonlinear structures associated to the atmosphere. In fact, the atmosphere is described as a chaotic system; this means that small changes at a point in time can lead to large changes later in the forecast period. Despite its complexity, numerical weather prediction models (NWP) are good tools that allow us to make a big step forward in weather forecasting because of the huge increases in computing power and better physical modelling schemes available today. In this work we summarize the achieved tasks of the implementation of a real-time NWP simulation using the Unified Environmental Modeling System (UEMS) over north-Africa and Morocco. Technical and operational characteristics of our real-time weather forecast system will be described, and a case study will be illustrated on a real meteorological situation. The validation of our model is performed based on comparisons against surface and upper air observations, using the verification package of the Model Evaluation Tools (MET).

Analysis of the meteorological situation during period of forest fires and smoke-blanketing monitoring in Siberia in 2019

Analysis of the meteorological situation during period of forest fires and smoke-blanketing monitoring in Siberia in 2019

Climate factors and incidence of Middle East respiratory syndrome coronavirus

BackgroundOur understanding of climate factors and their links to the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) outbreaks is incomplete. This study aimed to estimate the monthly incidence of MERS-CoV cases and to investigate their correlation to climate factors. MethodsThe study used aggregated monthly MERS-CoV cases that reported to the Saudi Center for Disease Prevention and Control from the Riyadh Region between November 1, 2012 and December 31, 2018. Data on the meteorological situation throughout the study period was calculated based on Google reports on the Riyadh Region (24.7136°N, 46.6753°E). The Poisson regression was used to estimate the incidence rate ratio (IRR) and its 95% confidence intervals (CI) for each climate factor. ResultsA total of 712 MERS-CoV cases were included in the analysis (mean age 54.2±9.9 years), and more than half (404) (56.1%) MERS-CoV cases were diagnosed during a five-month period from April to August. The highest peak timing positioned in August 2015, followed by April 2014, June 2017, March 2015, and June 2016. High temperatures (IRR=1.054, 95% CI: 1.043–1.065) and a high ultraviolet index (IRR=1.401, 95% CI: 1.331–1.475) were correlated with a higher incidence of MERS-CoV cases. However, low relative humidity (IRR=0.956, 95% CI: 0.948–0.964) and low wind speed (IRR=0.945, 95% CI: 0.912–0.979) were correlated with a lower incidence of MERS-CoV cases. ConclusionThe novel coronavirus, MERS-CoV, is influenced by climate conditions with increasing incidence between April and August. High temperature, high ultraviolet index, low wind speed, and low relative humidity are contributors to increased MERS-CoV cases. The climate factors must be evaluated in hospitals and community settings and integrated into guidelines to serve as source of control measures to prevent and eliminate the risk of infection.

Exploring the regional pollution characteristics and meteorological formation mechanism of PM2.5 in North China during 2013–2017

In the last decade, North China (NC) has been one of the most populated and polluted regions in the world. The regional air pollution has had a serious impact on people’s health; thus, all levels of government have implemented various pollution prevention measures since 2013. Based on multi-city in situ environmental and meteorological data, as well as the meteorological reanalysis dataset from 2013 to 2017, regional pollution characteristics and meteorological formation mechanisms were analyzed to provide a more comprehensive understanding of the evolution of PM2.5 in NC. The domain-averaged PM2.5 was 79 ± 17 µg m−3 from 2013 to 2017, with a decreasing rate of 10 μg m−3 yr−1. Two automatic computer algorithms were established to identify 6 daily regional pollution types (DRPTs) and 48 persistent regional pollution events (PRPEs) over NC during 2014–2017. The average PM2.5 concentration for the Large-Region-Pollution type (including the Large-Moderate-Region-Pollution and Large-Severe-Region-Pollution types) was 113 ± 40 µg m−3, and more than half of Large-Region-Pollution days and PRPEs occurred in winter. The PRPEs in NC mainly developed from the area south of Hebei. The number of Large-Region-Pollution days decreased notably from 2014 to 2017, the annual number of days varying between 194 and 97 days, whereas a slight decline was observed in winter. In addition, the averaged PM2.5 concentrations and the numbers and durations of the PRPEs decreased. Lamb-Jenkinson weather typing was used to reveal the impact of synoptic circulations on PM2.5 across NC. Generally, the contributions of the variations in circulation to the reduction in PM2.5 levels over NC between 2013 and 2017 were 64% and 45% in summer and winter, respectively. The three most highly polluted weather types were types C, S and E, with an average PM2.5 concentration of 137 ± 40 µg m−3 in winter. Furthermore, three typical circulation dynamics were categorized in the peak stage of the PRPEs, namely, the southerly airflow pattern, the northerly airflow pattern and anticyclone pattern; the averaged relative humidity, recirculation index, wind speed and boundary layer height were 63%, 0.33, 2.0 m s−1 and 493 m, respectively. Our results imply that additional emission reduction measures should be implemented under unfavorable meteorological situations to attain ambient air quality standards in the future.

Assessment of the Effects of Wastewater Treatment Plant Modernization by Means of the Field Olfactometry Method

Methodological aspects of odor studies in ex-post analyses for Polish wastewater management facilities were analyzed based on the example of a modernized and enlarged wastewater treatment plant (WWTP) in Mazovia, in the vicinity of the Warsaw agglomeration. It is a mechanical–biological treatment plant with increased efficiency of biogen removal, using activated sludge in the treatment process, with a maximum hydraulic capacity of 60,000 m3/day. Olfactometric research was carried out by means of a method based on identification and characterization of the odor plume emitted from the examined source. This paper presents the results of odor intensity assessment (in sensory examinations according to a 6-stage scale) and odor concentration measurement (using portable field olfactometers) after the completion of the project, and compares them with similar studies conducted before the commencement of the investment. A total of 10 measurement series were carried out before modernization, and 12 after modernization of the WWTP. Odor concentration and intensity were determined, and the current meteorological situation was assessed at the measurement and observation points (receptors) located within the premises (in total 462 points) and around the WWTP (342 points). In each series of measurements on the windward side of the treatment plant, the background of air pollution with odorous substances was marked. The research showed that air flowing into the area of the sewage treatment plant is clean in terms of odor. During the research, basic sources of odor nuisance were identified, and their impact before and after modernization was characterized. The results presented in radar diagrams show changes in the percentage distribution of frequency of occurrence of individual intensity values at receptor points within and outside the area of the treatment plant. After modernization, a significant decrease in the concentration of odor emitted from the sludge dewatering building and sludge containers was determined. The air-tightness of the sewage channel (covered with concrete slabs and sealed) resulted in a significant decrease in the concentration of odor emitted from this source. Waste (in particular, sewage sludge) collected in the emergency waste storage yard was identified as the main source of odor nuisance. The waste, even after modernization, was an emitter of odorous compounds spreading outside the area of the WWTP. Nevertheless, as a result of the investment, the desired effect of reduction of the degree of odor nuisance was achieved.

Can Data Assimilation of Surface PM2.5 and Satellite AOD Improve WRF-Chem Forecasting? A Case Study for Two Scenarios of Particulate Air Pollution Episodes in Poland

Based on the Weather Research and Forecasting model with Chemistry (WRF-Chem) model and Gridpoint Statistical Interpolation (GSI) assimilation tool, a forecasting system was used for two selected episodes (winter and summer) over Eastern Europe. During the winter episode, very high particular matter (PM2.5, diameter less than 2.5 µm) concentrations, related to low air temperatures and increased emission from residential heating, were measured at many stations in Poland. During the summer episode, elevated aerosol optical depth (AOD), likely related to the transport of pollution from biomass fires, was observed in Southern Poland. Our aim is to verify if there is a relevant positive impact of surface and satellite data assimilation (DA) on modeled PM2.5 concentrations, and to assess whether there are significant differences in the DA’s impact on concentrations between the two seasons. The results show a significant difference in the impact of surface and satellite DA on the model results between the summer and winter episode, which to a large degree is related to the availability of the satellite data. For example, the application of satellite DA raises the factor of two statistic from 0.18 to 0.78 for the summer episode, whereas this statistic remains unchanged (0.71) for the winter. The study suggests that severe winter air pollution episodes in Poland and Eastern Europe in general, often related to the dense cover of low clouds, will benefit from the assimilation of surface observations rather than satellite data, which can be very sparse in such meteorological situations. In contrast, the assimilation of satellite data can have a greater positive impact on the model results during summer than the assimilation of surface data for the same period.

The correction of TEOM $${\hbox {PM}}_{10}$$ measurements at different monitoring sites and climates

The reference method for $${\hbox {PM}}_{{10}}$$ and $${\hbox {PM}}_{2.5}$$ measurement in Europe is active sampling with subsequent gravimetric analysis. Also tapered element oscillating microbalance (TEOM) monitors are widely used across Europe for the assessment of particulate matter (PM), even though they are known to be biased due to the loss of semi-volatile materials attributed to sample heating. In our work we correct TEOM $${\hbox {PM}}_{{10}}$$ measurements at eight different monitoring sites located in different surroundings and different climates across Slovenia to replicate reference measurements. We use simultaneous reference and TEOM measurements from a period of seven years (2011–2017) and assess the advantage of custom defined correction factors (with linear and orthogonal regression) compared to default correction factors. We further try to improve the corrections by adding meteorological parameters as inputs and training a linear model (lasso) and nonlinear model (random forest). Random forest and lasso models also enable us to evaluate the impact of different meteorological parameters or chemical compounds on TEOM measurements. Our results show that TEOM measurements can be efficiently corrected using correction factors defined with two linear regressions (for summer and winter) at most locations across continental Slovenia. Koper, which lies at the sea side, was the most problematic measurement site. There the measurements were the most affected by the meteorological situation, and they could not be successfully corrected. When examining the effect of the chemical composition at two different locations, levels of $${\hbox {NH}}_4^+$$ , $${\hbox {NO}}_3^{-}$$ , and organic carbon exhibited major impact on the discrepancies between reference and TEOM measurements.

COMPUTER MODELING OF AIR POLLUTION IN CASE OF DUST CLOUD MOVEMENT IN OPEN PIT MINE

Purpose. Explosions in open pits lead to the formation of dust clouds. These clouds lead to intense air pollution. An important task is the development of methods for predicting the dynamics of atmospheric air pollution during explosions in open pits. The purpose of this work is development of a numerical model to predict atmosphere pollution after explosion in open mine pit. The task is to develop a numerical model that would allow for the calculation to take into account the geometrical shape of the open pit mine, the parameters of the meteorological situation (wind speed, atmosphere), the shape of the dust cloud that is formed in the open pit mine at the site of the explosion. Methodology. Mathematical modeling of dust cloud dispersion during an explosion in an open pit mine is based on the use of fundamental equations of aerodynamics and mass transfer. The airflow velocity field in the open pit mine is modeled using the Laplace equation for the velocity potential. The formation of the concentration field of dust is modeled on the basis of the equation of convective-diffusion dispersion of an impurity. For numerical integration of modeling equations, difference schemes are used. The Laplace equation for the velocity potential is numerically integrated using the Richardson method. For the numerical integration of the convective-diffusion dispersion equation for an impurity, an implicit difference splitting scheme is used. Findings. A CFD model has been developed that allows you to calculate the formation of pollution zones during the movement of a dust cloud in the open pit mine. A feature of the developed model is the speed of calculation. For practical use of the developed model, standard input information is required. Originality. In contrast to the existing models in Ukraine, the developed numerical model allows taking into account the geometrical shape of the open pit mine and the geometrical shape of the dust cloud when making predictive calculations to assess the level of air pollution caused by explosions in open pits. Practical value. The developed numerical model can be implemented on computers of low and medium power. For practical use of the numerical model, standard information on meteorological conditions in open pit mine is required. The numerical model can be used for environmental assessment of the effect of explosions in open pit mine on environmental pollution and work areas.

Influence of the origin of the air mass on the background levels of atmospheric particulate matter and secondary inorganic compounds in the Madrid air basin.

This study has assessed the influence of the origin of air mass on levels of particulate matter (PM10) and chemical composition (SO42- and NO3-) in the air basin of Madrid. A data set of back-trajectories of air mass arriving to this area of study from 15 June 15 2009 to 8 July 2011 has been analyzed. Firstly, the cluster analysis statistical method has been used to group the back-trajectories into 5 sets according to the angle, direction, and speed of the air mass. Afterwards, the synoptic meteorological scenarios associated with each cluster were obtained and interpreted. Subsequently, an analysis was made on the influence of these clusters on the surface levels of particulate pollutants recorded in a regional background station ("El Atazar"), as well as in two urban background stations ("Casa de Campo" and "CIEMAT"). Finally, potential source areas of PM10, SO42-, and NO3- that contributed to the increase in their background levels in the Madrid air basin were detected by analyzing residence times of trajectories. Transport of mineral desert dust is probably the main cause of the increase of regional and urban background levels of PM10 in the Madrid air basin. In the case of SO42-, relatively high levels were registered, associated with air mass coming from Southern Europe and the Mediterranean Sea. In these regions, strong emissions of SO42- are produced due to industrial combustion and maritime traffic. Otherwise, relatively high levels of NO3- were registered during meteorological situations defined by a low baric gradient in the Iberian Peninsula. This meteorological pattern favors the accumulation of emissions from local and regional sources. Besides, the main urban centers of northeastern Europe and industrial areas located in the north African coast were also identified as potential source areas of NO3-. The statistical analysis of the back-trajectories by different methods and the comparison of the results obtained with observational data confirmed that numerous industrial areas in Europe and North Africa, as well as natural ones, such as deserts, had an influence on the regional and urban background levels of mass and chemical composition of particulate matter in the Madrid air basin, under the development of specific synoptic meteorological situations. Graphical abstract.

Atmospheric circulation amplifies shift of winter streamflow in southern Ontario

Flooding is a major concern for Canadian society as it is the costliest natural disaster type in Canada. Southern Ontario, which houses one-third of the Canadian population, is located in an area of high vulnerability for floods. The most significant floods in the region have historically occurred during the months of March and April due to snowmelt coupled with extreme rain events. However, during the last three decades, there has been a shift of flooding events to earlier months. The aim of this study was to understand the impacts of atmospheric circulation on the temporal shift of streamflow and high flow events observed in southern Ontario over 1957–2013 period. Predominant weather regimes over North America, corresponding to recurrent meteorological situations, were identified using a discretization of daily geopotential height at 500HpA level (Z500). A regime-normalized hypothetical temperature and precipitation dataset was constructed to quantify the contribution of atmospheric circulation on streamflow response. The hypothetical dataset was used as input in the Precipitation Runoff Modeling System (PRMS), a rainfall-runoff semi-distributed hydrological model, and applied to four watersheds in southern Ontario. The results showed an increase in the temporal frequency of the regime identified here as High Pressure (HP) close to eight occurrences per decade. Regime HP, characterized by a northern position of the polar vortex, is correlated with a positive phase of the NAO and is associated with warm and wet conditions over southern Ontario during winter. The temporal increase in HP contributed more than 40% of the increase in streamflow in winter and 30–45% decrease in streamflow in April. This atmospheric situation also contributed to increase the number of high flows by 25–50% in January. These results are important to improve the seasonal forecasting of high flows and to assess the uncertainty in the temporal evolution of streamflow in the Great Lakes region.

Statistical modelling of spatial patterns of the urban heat island intensity in the urban environment of Augsburg, Germany

Spatial and temporal variability of meteorological variables across urban areas due to differences in land surface characteristics is a common phenomenon. Most pronounced is the effect of land cover on air temperature. In this study, parametric and non-parametric statistical approaches (stepwise multiple linear regression, random forests) were applied in order to model sub-daily and daily spatial patterns of the urban heat island intensity in the major city of Augsburg, Southern Germany, and its rural surroundings. A large number of model setups utilizing variables from different land surface data sets as predictors and taking into account different seasonal, daily and meteorological situations was examined. The results were compared concerning different measures of model performance (mean squared skill score, mean squared error, explained variance). For individual setups and situations considerable skill with a mean squared skill score of up to 0.85 was reached. The best performing models were obtained from multiple linear regression for situations with low wind speeds and cloud cover in the morning and evening. Selected models were utilized to derive continuous spatial distributions of the air temperature deviations from a rural reference station. The resulting maps can be useful for various applications, e.g. in the context of urban planning.

THE ROLE OF MOSQUITOES IN THE OCCURRENCE OF ANTHROPOZOONOSIS

Climate change leads to a change in the distribution of insects, including blood-sucking. Mosquitoes are vectors for the transmission of dangerous anthropozoonotic diseases. Every year in the Kirov region up to 1100 diseases of natural focal infec-tions are registered. The temperate continental climate, abundant rainfall (500-680 mm per year) with a predominance of up to 70% in warm weather, the presence of forests and water bodies, swamped territory (40%) are favorable factors for the de-velopment of mosquitoes. On the territory of the region 25 species of mosquitoes of 5 genus are registered. The information on the fauna of mosquitoes on the territory of the Kirov region, the meteorological situation, and the epizoological situation on anthropozoonotic diseases, including dirofilariasis, were analyzed. Since 1942, the region has been unfavorable for tularemia with the last outbreak in 2012 near the floodplain of the Vyatka River. Since 2008, cases of human dirofilariasis with local-ization of the pathogen in the organs of vision have been recorded annually in the Kirov region. May – September is the most favorable for human infection, subject to the presence of a sick animal and a significant number of blood-sucking insects. Since 2013, cases of dirofilariasis of domestic and working dogs have been reported in the Kirov region, which indicates the presence of a local focus of dirofilariasis, in which mosquitoes are carriers of human and dog diseases. In dogs, the subcutane-ous (pathogen Dirofilaria repens) or cardiac (pathogen Dirofilaria immitis) forms of anthropozoonosis are recorded. The cardiac form of the disease is the most atypical. The diagnosis of dirofilariasis is made on the basis of anamnesis, clinical picture, laboratory tests for the detection of microfilariae in the blood.

Object‐based verification metrics applied to the evaluation and weighting of convective‐scale precipitation forecasts

Traditional pointwise verification scores are not always appropriate for the evaluation of high‐resolution precipitation forecasts because of double‐penalty problems. An alternative approach, based on the identification of homogeneous rainfall areas called “precipitating objects”, allows forecast evaluation at a larger and thus more predictable scale, and specific information about the nature of errors (e.g. location, size, intensity) can be obtained. A novel object detection method is first introduced and the object‐based verification of precipitation forecasts from the convective‐scale deterministic and ensemble models Arome and Arome‐EPS is then discussed, using several scores and diagnostics. Three types of precipitating objects characterizing total, moderate and heavy rainfall are considered. In the second part, object‐based metrics are used to compute objective weights for time‐lagged ensemble forecasts, based on their performance at early forecast ranges. The weights obtained clearly depend on the meteorological situation and on the precipitation type, reflecting for instance the lower predictability of moderate precipitation compared to total precipitation. There is also a dependence on the production time with, on average, slightly larger and more homogeneous weights associated with the most recent run. However, in some situations of moderate and heavy rainfall, a relevant signal can be extracted from older runs. It is finally shown that object‐based weights are better suited than classical quadratic weights to improve nowcasting performance.