Standard Meteorological Data Research Articles

Investigating the efficacy of a fast urban climate model for spatial planning of green and blue spaces for heat mitigation

Problems caused by urban heat have prompted the exploration of urban greenery and blue spaces for heat mitigation. Various numerical models can simulate heat-related processes, but their use as support-tools to urban planners remains underexplored, particularly at the city-scale, due to high computational demand and complexity of such models. This study investigates the spatial relationships between urban heat, urban form and urban green and blue spaces with the fast climate model TARGET (The Air-temperature Response to Green/blue-infrastructure Evaluation Tool), which only requires minimal inputs of standard meteorological data, land cover and building geometry data. Using the City of Zurich as our case study, we: (i) validated the TARGET model against air temperature measurements from private sensor networks, (ii) performed a sensitivity analysis to identify key variables affecting urban heat, and (iii) investigated urban heat relationships with blue-green cover at locations frequented by pedestrians. Presence of urban green and blue spaces across the region shows potential for reducing local air temperatures by up to 5.2 °C (with urban forest). Investigating this relationship at different locations in the city revealed key districts that should potentially be targeted for reduction of pedestrian heat-impacts, due to their high pedestrian traffic, fewer green and blue spaces and high daytime air temperatures. Our results not only provide insights into the cooling effect of different amounts of green and blue features in the urban environment, but also demonstrates the application and integration potential of simplified models like TARGET to support the planning of more liveable future cities.

Constructing a Database of Reference Hydrothermal Sources for a Zero-Energy Building Certification Rating in South Korea and Analyzing the Renewable Energy Self-Sufficiency Rate Achieved by Water-Source Heat Pumps

This study aims to institutionalize an evaluation methodology to assess water-source heat pumps (WSHPs) when designing a zero-energy building. Thus, regions where zero-energy buildings were designed were subdivided into 66 sub-regions, thereby standardizing the temperatures on the source side of WSHPs using river water and pipeline water. Based on these data, ground-source and water-source heat pump system-based simulation (new and renewable energy self-sufficiency rate compared to building energy consumption) values were derived for cases whose condition (region or heat source) was different among the buildings certified as zero-energy buildings. The application of the standard meteorological data and reference hydrothermal data to the ECO2 program and outcome evaluation led to the following findings: in all cases (reference: Seoul), ground-source heat pumps (GSHPs) showed a higher self-sufficiency rate than WSHPs (ground source > pipeline water > river water). The self-sufficiency rate of GSHPs was 11–33% higher than that of WSHPs. In a regional comparison among the cold (Jeongseon), central (Seoul), and southern (Jeju Island) regions, WSHPs exhibited higher energy self-sufficiency rates than GSHPs under the conditions of higher water temperatures in winter and lower water temperatures in summer, as in the southern region.

A phenology-driven fire danger index for northern grasslands

Background Directly after snowmelt, northern grasslands typically have highly flammable fuel-beds consisting of 100% grass litter. With green-up, the addition of high-moisture foliage leads to progressively decreasing fire hazard. Aims Our aim was to create a fire-danger index for northern grasslands that incorporated grass phenology. Methods We made use of 25 years of Swedish wildfire data and 56 experimental fires conducted during one full fire-season, merged with established models for moisture content and flame spread rates. Refined data on equilibrium moisture content of grass litter were obtained through laboratory tests. Key results The RING (Rate of spread In Northern Grasslands) model uses cumulative air temperature as a proxy for growing season progression. Three independent functions account for impact of wind, moisture content and the damping effect of live grass, respectively. The latter results in exponentially decaying rate of spread (ROS) with the progressing season. Following the field experiments, green grass proportion as low as 10–20% (live/dead dry-mass) resulted in model-ROS so reduced that the grassland fire season could effectively be considered over. Conclusions The model, calculated from standard meteorological data only, matches the experimental results and separately performed validation tests, as well as wildfire dispatch data. Implications RING has been used in Sweden since 2021 and is likely applicable to other northern regions as well.

СОВРЕМЕННОЕ СОСТОЯНИЕ РЕСУРСОВ ВЛАГИ НА ФОНЕ КЛИМАТИЧЕСКИХ ИЗМЕНЕНИЙ НА СЕВЕРО-ВОСТОЧНОМ СКЛОНЕ БОЛЬШОГО КАВКАЗА (В ПРЕДЕЛАХ АЗЕРБАЙДЖАНСКОЙ РЕСПУБЛИКИ)

The paper presents the results of our investigation of the moisture resources on the northeastern slope of the Greater Caucasus. For this purpose, standard meteorological data archives of the Siyazan, Khachmaz, Guba, Khaltan and Gyryz meteorological stations located at different heights of this slope were used for the period of 1966-2005. Regional climate changes were assessed by comparing the average monthly air temperature and the amount of precipitation using the diff method for 1961-1990 and 1991-2005. Long-term trends in the change in the total amount of atmospheric precipitation, the Selyaninov HTC andD.I. Shashko’s moisture index for the warm period of the year and the ratio of the precipitation amount for the warm period to the annual precipitation amount were evaluated. It was found out that the multi-year tendency of the precipitation amounts during the warm period has not actually changed.

Energetics of Paper Wasps (Polistes sp.) from Differing Climates during the Breeding Season.

Simple SummaryPaper wasps are widely distributed in nearly all regions of Europe. They are found in the warm Mediterranean, and in the harsh Alpine climate. Some species are very careful in the choice of nesting sites to ensure a proper development of the brood. We investigated microclimate conditions at the nests of three species (P. dominula, P. gallicus, P. biglumis) from differing climates, in order to characterize fine-scale environment conditions and conduct energetic calculations for an entire breeding season. The microclimate conditions (temperature) at the nests differed significantly in the Mediterranean, temperate, and Alpine habitats, but in all habitats the mean ambient nest temperatures were about 2 to 3 °C above the standard meteorological climate data. The wasps’ energetic expenditure depended strongly on temperature. P. gallicus from the warm Mediterranean climate exhibited the highest energetic costs, whereas P. biglumis from the harsh Alpine climate had the lowest costs during a breeding season. The energetic expenditure of P. dominula from the temperate climate was somewhat lower than in the Mediterranean species, but clearly higher than in the Alpine species. Temperature increase due to climate change may have a severe impact on the wasps’ survival as energetic costs increase.Paper wasps are widely distributed in Europe. They live in the warm Mediterranean, and in the harsh Alpine climate. Some species are very careful in their choice of nesting sites to ensure a proper development of the brood. We investigated microclimate conditions at the nests of three species (P. dominula, P. gallicus, P. biglumis) from differing climates, in order to characterize environmental conditions and conduct energetic calculations for an entire breeding season. The mean ambient nest temperature differed significantly in the Mediterranean, temperate, and Alpine habitats, but in all habitats it was about 2 to 3 °C above the standard meteorological data. The energetic calculations of adult wasps’ standard and active metabolic rate, based on respiratory measurements, differed significantly, depending on the measured ambient temperatures or the wasps’ body temperatures. P. gallicus from the warm Mediterranean climate exhibited the highest energetic costs, whereas P. biglumis from the harsh Alpine climate had the lowest costs. Energetic costs of P. dominula from the temperate climate were somewhat lower than those in the Mediterranean species, but clearly higher than those in the Alpine species. Temperature increase due to climate change may have a severe impact on the wasps’ survival as energetic costs increase.

Hydrological Forecasting under Climate Variability Using Modeling and Earth Observations in the Naryn River Basin, Kyrgyzstan

The availability of water resources in Central Asia depends greatly on snow accumulation in the mountains of Tien-Shan and Pamir. It is important to precisely forecast water availability as it is shared by several countries and has a transboundary context. The impact of climate change in this region requires improving the quality of hydrological forecasts in the Naryn river basin. This is especially true for the growing season due to the unpredictable climate behavior. A real-time monitoring and forecasting system based on hydrological watershed models is widely used for forecast monitoring. The study’s main objective is to simulate hydrological forecasts for three different hydrological stations (Uch-Terek, Naryn, and Big-Naryn) located in the Naryn river basin, the main water formation area of the Syrdarya River. We used the MODSNOW model to generate statistical forecast models. The model simulates the hydrological cycle using standard meteorological data, discharge data, and remote sensing data based on the MODIS snow cover area. As for the forecast at the monthly scale, the model considers the snow cover conditions at separate elevation zones. The operation of a watershed model includes the effects of climate change on river dynamics, especially snowfall and its melting processes in different altitude zones of the Naryn river basin. The linear regression models were produced for monthly and yearly hydrological forecasts. The linear regression shows R2 values of 0.81, 0.75, and 0.77 (Uch-Terek, Naryn, and Big-Naryn, respectively). The correlation between discharge and snow cover at various elevation zones was used to examine the relationship between snow cover and the elevation of the study. The best correlation was in May, June, and July for the elevation ranging from 1000–1500 m in station Uch-Terek, and 1500–3500 m in stations Naryn and Big-Naryn. The best correlation was in June: 0.87; 0.76; 0.84, and May for the elevation ranging from 1000–3500 m in station Uch-Terek, and 2000–3000 m in stations Naryn and Big-Naryn. Hydrological forecast modeling in this study aims to provide helpful information to improve our under-standing that the snow cover is the central aspect of water accumulation.

Feasibility of Obtaining Surface Layer Moisture Flux Using an IR Thermometer

This paper evaluates the feasibility of a method using a single hand-held infrared (IR) thermometer and a mini tower of wet and dry paper towels to psychometrically obtain surface layer temperature and moisture gradients and fluxes. Sling Psychrometers have long been standard measuring devices for quantifying the thermodynamics of near-surface atmospheric gas–vapor mixtures, specifically moisture parameters. However, these devices are generally only used to measure temperature and humidity at one near-surface level. Multiple self-aspirating psychrometers can be used in a vertical configuration to measure temperature and moisture gradients and fluxes in the first 1–2 m of the surface layer. This study explores a way to make multiple vertical psychrometric measurements with a single non-contact IR temperature sensor rather than using two in situ thermometers at each level. The surface layer dry- and wet-bulb temperatures obtained using an IR Thermometer are compared to Kestrel 4000 Weather Meter and Bacharach Sling Psychrometer measurements under various atmospheric conditions and surface types to test the viability of the method. To evaluate the results obtained using this new approach, standard meteorological surface data are collected during each experiment, and moisture parameters are derived via psychrometric equations. The results indicate that, not only is the method possible and practical, but they suggest that the IR Thermometer method may provide more surface layer temperature and moisture gradient and flux sensitivity than other single instrument methods.

The decline of Svalbard land-fast sea ice extent as a result of climate change

The Svalbard Archipelago has experienced some of the most severe temperature increases in the Arctic in the last three decades. This temperature rise has accelerated sea-ice melting along the coast of the archipelago, thus bringing changes to the local environment. In view of the importance of the near-future distribution of land-fast sea ice along the Svalbard coast, the available observation data on the ice extent between 1973 and 2018 are used herein to create a random forest (RF) model for predicting the daily ice extent and its spatial distribution according to the cumulative number of freezing and thawing degree days and the duration of the ice season. Two RF models are constructed by using either regression or classification algorithms. The regression model makes it possible to estimate the extent of land-fast ice with a root mean square error (RMSE) of 800 km2, while the classification model creates a cluster of submodels in order to forecast the spatial distribution of land-fast ice with less than 10% error. The models also enable the reconstruction of the past ice extent, and the prediction of the near-future extent, from standard meteorological data, and can even analyze the real-time spatial variability of land-fast ice. On average, the minimum two-monthly extent of land-fast sea ice along the Svalbard coast was about 12,000 km2 between 1973 and 2000. In 2005–2019, however, the ice extent declined to about 6,000 km2. A further increase in mean winter air temperatures by two degrees, which is forecast in 10 to 20 years, will result in a minimum two-monthly land-fast ice extent of about 1,500 km2, thus indicating a trend of declining land-fast ice extent in this area.

Spatial analysis of outdoor wet bulb globe temperature under RCP4.5 and RCP8.5 scenarios for 2041–2080 across a range of temperate to hot climates

Wet bulb globe temperature (WBGT) is commonly used to assess human physical activity limits and risk exposure to heat-related injury. Using Australia as a case study location, rates of change in WBGT across a range of temperate to hot and dry to humid climates in response to selected projected climate scenarios were investigated. An established physics-based method for estimating WBGT using standard meteorological data was incorporated into a spatial modelling framework to map WBGT for a baseline period (1986–2005) for mid-summer daytime, mid-summer early morning and mid-winter daytime scenarios, under clear sky conditions and both light (0.5 ms−1) and moderate (3.0 ms−1) wind speeds at a nominal resolution of 0.05 decimal degrees. The resulting maps of WBGT revealed significant spatial variability in the range and pattern of increased WBGT across the three baseline scenarios in response to projected change under RCP4.5 and RCP8.5 for 2041–2060 and 2061–2080 generated by the ACCESS1.0 climate model. Moderate wind speed scenarios produced significantly cooler WBGTs than the equivalent low wind speed scenarios, reducing mean modelled summer daytime WBGT by 3.2 °C, summer morning WBGT by 0.8 °C, and winter daytime WBGT by 3.0 °C. Projected future summer daytime WBGT under unshaded clear atmospheric conditions with light wind speeds can be expected to exceed the range of the commonly used heat categorisation system used to inform recommended restrictions on physical activity and regularly exceed 35 °C in northern Australia's equatorial and tropical climates by mid-century under RCP4.5 and RCP8.5. Summer early morning WBGT and winter daytime WBGT were projected to reach heat categories that would result in recommended restrictions in physical activity continuously (across consecutive 24-h periods) in summer and intermittently (for at least part of the day) year-round by 2050 with more severe conditions by 2070 and/or under RCP8.5 scenarios. Investigations into physical activity limits beyond the current highest heat category and the efficacy of the employed methodology to estimate WBGT above 35 °C using standard meteorological data are required to prepare for the projected warmer climate.

The efficiency of thermosyphon solar water heating system and traditional solar water heating system

Loop thermosyphon (LT) is typically used for solar water heaters (SHW) to solve the freezing and corrosion issues. The LT – SWH system has a less night time heat loss compared to conventional SWH due to its thermal diode property but a greater heat loss due to the secondary heat exchange. However, the above interactions have rarely had an effect on system performance based on long-term operation [6]. In this paper, the annual results of above two processes, including productive supply day numbers and efficient heat gains and night power losses, was evaluated in this analysis in two separate operating modes on the basis of standard meteorological year data from the City of Fuzhou. Variations of the above variables are addressed with the change in the stated temperature. The results show that the effective delivery days of the LT – SWH system are 139 and 153, respectively, in irregular heating method. The number of days is 168 to 173 in ongoing heating method. The SWH system is predictable to have a higher ratio at nighttime with an annual average of 15.07%, which equates to 6.15% for the LT – SWH system. In fact the LT – SWH method results in a lesser decrease in temperature at night and therefore a smaller raise in the temperature on the following day because of multiple relative heat loss factors running at various hours. The results produced are unpredictable, and lead to an approximately successful heat gain for the same month between November and April. The fixed temperature influences substantially the relative quantities of effective annual supply days and effective annual heat gain, slowly reducing the overall dominance of the LT – SWH method and even changing it as the set temperature increases [12]. This shift is triggered by the biggest daily heat loss leading the domination. In combination with a long static reimbursement time, a conventional SWH system must be substituted by an LT - SWHsystem, particularly when water temperatures are high on demand.

Use of Sentinel-2 MSI data to monitor crop irrigation in Mediterranean areas

The availability of accurate information on the water consumed for crop irrigation is of vital importance to support compatible and sustainable environmental policies in arid and semi-arid regions. This has promoted several studies about the use of remote sensing data to monitor irrigated croplands, which are mostly based on statistical classification and/or regression techniques. The current paper proposes a new semi-empirical approach that relies on a water balance logic and does not require local tuning. The method stems from recent investigations which demonstrated the possibility of combining standard meteorological data and Sentinel-2 (S-2) Multi Spectral Instrument (MSI) NDVI images to estimate the actual evapotranspiration (ETa) of irrigated Mediterranean croplands. This ETa estimation method is adapted to drive a simplified site water balance which, for each 10-m S-2 MSI pixel, predicts the irrigation water (IW), i.e. the water which is consumed in addition to that naturally supplied by rainfall. The new method, fed with ground and satellite data from two years (2018–2019), is tested in a Mediterranean area around the town of Grosseto (Central Italy), that is covered by a particularly complex mosaic of rainfed and irrigated crops. The results obtained are first assessed qualitatively for some fields grown with known winter, spring and summer crops. Next, the IW estimates are evaluated quantitatively versus ground measurements taken over two irrigated fields, the first grown with processing tomato in 2018 and the second with early corn in 2019. Finally, the IW estimates are statistically analyzed against various datasets informative on local agricultural practices in the two years. All these analyses indicate that the proposed method is capable of predicting both the intensity and timing of the IW supply in the study area. The method, in fact, correctly identifies rainfed and irrigated crops and, in the latter case, accurately predicts the IW actually supplied. The results of the quantitative tests performed on tomato and corn show that over 50 % and 70 % of the measured IW variance is explained on daily and weekly bases, respectively, with corresponding mean bias errors below 0.3 mm/day and 2.0 mm/week. Similar indications are produced by the qualitative tests; reasonable IW estimates are obtained for all winter, springs and summer crops grown in the study area during 2018 and 2019.

Present climate development in Southern Siberia: a 55-year weather observations record

Siberia is a key region for study of the climate development in north-central Eurasia in terms of global climatic change. The relief creates a major orographic barrier for atmospheric streams influencing the regional altitudinal weather zonality. Systematic 55-year (1963-2017) weather observations along the 700 km N-S latitudinal transect across the southern Siberian plains and the adjoining ranges of the Altai-Sayan Mountains document progressing seasonal temperature and humidity shifts. Standard meteorological data from twenty meteorological stations in different topographical and natural settings with specific weather conditions document a rise of a regional atmospheric humidity balance reflected by the increased bulk annual precipitation rates in the mountain areas accompanied by pronounced seasonal air-temperature fluctuations. This regionally trend provides evidence speaking in favor of the strengthening climate continentality over Siberia, which is also manifested by the pronounced seasonal temperature regime with increased thermally positive and negative air temperature anomalies. A landscape response to a climate warming is particularly evident in the high mountain zone. The present thermal conditions with raised MAT contribute to the progressing melting of mountain glaciers and degradation of permafrost in the alpine zone, as well as aridization of the parkland-steppe areas that are being partly transformed into continental semi-arid to deserted steppes. The associated environmental transformations trigger shifts in the local biotopes and ecosystems, with an altitudinal expansion of taiga-forest into the alpine tundra belt and xerothermic grassland invasions in the foothills. The modern climate changes have a major bearing to the Altai-Sayans socio-economic development.

Urban climate scenario data for European cities

Climate change and the urban heat effect are expected to have a large influence on the energy consumption and thermal comfort of buildings. However, using meteorological data which incorporates effects of climate change and characteristics of cities is not currently a standard practice in building simulation. By default, data of nearby meteorological stations often outside cities are used. This may lead to important discrepancies between simulation results and actual energy consumption and/or indoor climate data for buildings in urban areas. These effects are analysed within building energy part of H2020 climate-fit.city project. First, adapted urban and future meteorological data modelled using the UrbClim model and standard meteorological data were compared. Second, these data were included within the Meteonorm software (version 7.3.2). This was carried out for current climates as well as for future scenarios (RCP 4.5 and 8.5, 2050) for the cities of Barcelona, Bern, Berlin, Bremen, Prague, Rome and Vienna. Like this Meteonorm includes a combination of urban and future climates accessible in a user friendly tool.In a third step the urbanized TMY data sets generated by Meteonorm were used to simulate energy consumption, peak loads and indoor climate conditions with models of several typical buildings. In this comparison we show a simulation for a multi-family house for current and future climates. The whole-year simulation runs were compared to the reference scenario – the standard TMY (available in Bern and Vienna).For current climates heating energy consumption is 10-25% lower within cities and cooling energy up to 60% higher (Barcelona). Even bigger changes are seen for future climates: Heating loads drop by up to 30% and cooling loads rise more than 100% (they are 2-3 times higher than heating loads in Barcelona by 2050).

Data assimilation impact of in situ and remote sensing meteorological observations on wind power forecasts during the first Wind Forecast Improvement Project (WFIP)

AbstractDuring the first Wind Forecast Improvement Project (WFIP), new meteorological observations were collected from a large suite of instruments, including wind velocities measured on networks of tall towers provided by wind industry partners, wind speeds measured by cup anemometers mounted on the nacelles of wind turbines, and wind profiles by networks of Doppler sodars and radar wind profilers. Previous data denial studies found a significant improvement of up to 6% root mean squared error (RMSE) reduction for short‐term wind power forecasts due to the assimilation of all of these observations into the National Oceanic and Atmospheric Administration (NOAA) Rapid Refresh (RAP) forecast model using a 3D variational data assimilation scheme. As a follow‐on study, we now investigate the impacts of assimilating into the RAP model either the additional remote sensing observations (sodars and radar wind profilers) alone or assimilating the industry‐provided in situ observations (tall towers and nacelle anemometers) alone, in addition to routinely available standard meteorological data sets. The more numerous tall tower/nacelle observations provide a relatively large improvement through the first 3 to 4 hours of the forecasts, which diminishes to a negligible impact by forecast hour 6. In comparison, the sparser vertical profiling sodars/radars provide an initially smaller impact that decays at a much slower rate, with a positive impact present through the first 12 hours of the forecast. Large positive assimilation impacts for both sets of instruments are found during daytime hours, while small or even negative impacts are found during nighttime hours.

Long-wave radiation balances of the south-west Poland

The paper goal is to show trends of seasonal and year to year variability of long-wave radiation balances of the active surface in SW Poland, taking into account the standard meteorological data from 1971–2000 for Jelenia Góra, Kłodzko, Legnica, Leszno, Opole, Wrocław and Mt. Śnieżka. The average monthly values of these balances were calculated using the selected two variants of the Brunt’s formula (standard and modified by Michałowska-Smak). In the researched 30-year courses prevail positive trends but with different statistical significance. The analysed trends of the average annual values have been compared with appropriate trends of air temperature, sunshine duration and cloudiness to understand the regional relations of the long-wave radiation balance to these parameters of the climatic variability. These analyses are essential part of wider research fields on long-term variability and trends of net radiation fluxes and their components on different active surfaces in Lower Silesia.

Swimming Pool Evaporative Water Loss and Water Use in the Balearic Islands (Spain)

The Balearic Islands are a major Mediterranean tourist destination that features one of the greatest swimming pool densities within Europe. In this paper, standard meteorological data were combined with a diachronic swimming pool inventory to estimate water evaporation from swimming pools over the Balearic archipelago. Evaporation was estimated using an empirical equation designed for open-water surfaces. Results revealed a 32% increase in swimming pools’ water use by 2015. Evaporation from swimming pools added 9.6 L of water to touristic consumption per guest night and person, and represented 4.9% of the total urban water consumption. In 2015, almost 5 hm3 (5 billion L) were lost from pools across the Balearic Islands. In several densely urbanized areas, evaporative water loss from pools exceeded four million litres per square kilometre and year. The water needed to refill the total of 62,599 swimming pools and to counteract evaporative water loss is equivalent to 1.2 pools per year. Swimming pools have rapidly proliferated across the islands. We have expounded on this development in view of much-needed responsible water management across the islands.

Evaluation of Microclimatic Detection by a Wireless Sensor Network in Forest Ecosystems

Timely and accurate detection of microclimates is extremely valuable for monitoring and stimulating exchanges of mass and energy in forest ecosystems under climate change. Recently, the rapid growth of wireless sensor networks (WSNs) has provided a new approach for detecting microclimates in a complex environment at multiple temporal and spatial scales. However, applications of wireless sensors in forest microclimate monitoring have rarely been studied, and the corresponding observation accuracy, error sources and correction methods are not well understood. In this study, through field experiments in two typical subtropical forest ecosystems in Zhejiang Province, China, the accuracy of the temperature and humidity observed by the wireless sensors was evaluated against standard meteorological data. Furthermore, the observation error sources were analyzed and corresponding correction models were established. The results showed that the wireless sensor-based temperature and humidity values performed well within the total observation accuracy. However, the observation errors varied with season, daily periodicity and weather conditions. For temperature, the wireless sensor observations were overestimated during the daytime while they were underestimated during the nighttime. For humidity, the data observed by the wireless sensors generally appeared as overestimates. Adopting humidity as the corrected factor, correction models were established and effectively improved the accuracy of the microclimatic data observed by the wireless sensors. Notably, our error analysis demonstrated that the observation errors may be associated with the shell material of the wireless sensor, suggesting that shading measures for the wireless sensors should be considered for outdoor work.

MATHEMATICAL SIMULATION FOR IMPROVEMENT OF RELIABILITY OF EVALUATION OF THE FIELD AGRONOMIC EXPERIMENT RESULTS

The programming (simulation) of yield in the area of “risky farming” that Belarus belongs to according to data from a single-factor experiment considering only the food mode, can lead to unacceptably large errors in the calculations. These errors can easily be avoided by increasing the factorality of agronomic experiment by using standard meteorological data processed using mathematical model of crop yields. A mathematical model of environmental factors effect on crop yields is proposed and tested. It is shown that the accuracy of yield simulation (calculation) increases with the growing number of crop-forming factors taken into account. The possibilities of mathematical simulation allowing to switch from one-factor to multifactorial agronomic research are demonstrated, involving meteorological data characterizing the moisture and heat availability of the vegetation period when analyzing the results of the experiment as additional information. The moisture supply conditions can be characterized quite accurately by atmospheric precipitation during the vegetation period, and the heat supply – by the maximum daily air temperatures in the same period. Inclusion in analysis of additional water and heat factors of yield makes it possible not only to increase the factorality of field experiment, but also to substantially increase the conclusions validity according to the results based on the proposed mathematical model.

Ice loads on overhead lines due to freezing radiation fog events in plains

The paper discusses specific ice accretion events that may occur in plains, i.e. freezing radiation fog events, whose worst cases can damage transmission overhead lines. A simple model is proposed able to estimate ice loads due to such events, based on standard meteorological observational data. The simple model has been validated by comparing ice loads estimated by the model with historical input data and ice loads estimated based on historical damages to overhead lines. It has been shown that its most promising application can be obtained by replacing the observed meteorological input data with similar parameters from an operational numerical weather prediction model. Such icing forecasts can be used to generate alarms to anticipate potential damage to overhead lines. This application was successfully tested on a significant freezing radiation fog event that took place in the northern half of France in the very beginning of 2017, using data issued from the French convective-scale numerical weather prediction model AROME (Application of Research to Operations at MEsoscale).

Estimation of diurnal total radiation based on meteorological variables in the period of plant vegetation in Poland

The paper presents selected models for the estimation of diurnal total radiation on the basis of other meteorological variables (using simple data as temperature and rainfall) in the vegetation months in the territory of Poland. For that purpose 6 meteorological stations were selected, having standard meteorological data as well as total radiation data for the period of 2001 – 2010. The stations were chosen so that two of them were situated on the coast, two in the lowland part of the country, and two in the mountains. The models were evaluated with the use of the coefficient of determination R² and the relative error of estimation RMSE with division into 6 months and 6 meteorological stations. In each of the regions the best results were obtained for models 6 and 7 which are combinations of the remaining models and additionally the constructed variable ΔT, used in other non-linear models analysed in the other studies. The best fit for those models was obtained for the mountain stations (R² from 0.67 to 0.75, RMSE from 2.7 to 4.4). The poorest estimation was obtained for the coastal stations (R² from 0.41 to 0.67, RMSE from 2.6 to 5.1). The paper does not indicate the best month in terms of the fitting, due to the high variation of results for the stations and the models.