High Precipitation Amounts Research Articles

A Study on Rainfall Rate, Temperature and Rain Attenuation of Ka-Band Satellite signal

This research paper is studied rainfall, temperature and rain attenuation of Ka-Band satellite signal by using rainfall and temperature data in 2023. Department of Electronics and Telecommunications Engineering, Faculty of Engineering is where the station is housed. Therefore, this paper aims to investigate the relationship between rainfall values, temperature and rain attenuation in Vientiane Capital using advanced technologies to facilitate and monitor the data in real time. A rain gauge Tipping Bucket 0.1mm/Tip is used to detect the amount of rain, and a DHT22 sensor is used to monitor the temperature. The research procedure entails analyzing temperature and rainfall, designing and setting up measurement sites, setting up a central monitoring station and using the Internet of Things to collect temperature and rainfall data. The analysis showed that the high precipitation amount of the actual rainfall and actual daily data contains two maximum values from August 15, 2023 at 85.3mm/hr with 26°C and September 7, 2023 at 110mm/hr with 25.1°C. ITU-R model is used to analyze the rain attenuation by applying the abovementioned rainfall values. As a result, the rain attenuation of Ka-Band Satellite Signal is 85.3mm/hr the rain attenuation is 11.63 dB and 110mm/hr the rain attenuation is 10.58 dB, respectively, which showed the interlinkage between rainfall amount and temperature while it is raining. The temperature change will not affect the rain attenuation as much as the increase of rainfall amount.

Variations of dissolved trace elements in precipitation and stream water in Japanese forest area: additional evidence of changing air pollution in the region

Trace elements released into the atmosphere by human activities, such as fossil fuel combustion, flow into forest ecosystems via wet and dry deposition and can flow out via mountainous stream water. The Kajikawa catchment site in Niigata Prefecture, located on the Sea of Japan side in central Japan, suffers from large amounts of acidic substance deposition due to its geographical conditions and meteorological seasonality and is affected by transboundary air pollution originating from the Asian continent due to northwesterly seasonal winds in winter. This study determined the concentrations of trace elements dissolved in precipitation and stream water to comprehensively evaluate the effects of transboundary air pollution on forest ecosystems. The results showed that the concentrations of trace elements and major inorganic ions in precipitation tended to be high in winter and low in summer. The fluxes of many trace elements also increased in winter, reflecting high precipitation amount. Except for Sr, the enrichment factors of the highly enriched trace elements did not show clear seasonality. Therefore, they were continuously influenced by anthropogenic activities. Furthermore, the stable Pb isotope ratio changed significantly during the observation period; however, this was not explained by seasonal changes. This study revealed that trace elements are transported to the Sea of Japan side in central Japan, especially in winter; however, their quantity and content change in response to changes in local and transboundary air pollution.Graphical

Effect of aging temperatures on the microstructure and mechanical properties of TC21 forgings with basket–weave microstructure

This study aims to explore the influence of various aging temperatures on the microstructure and mechanical properties of TC21 forgings. Basket-weave microstructures were prepared via quasi-β forging followed by annealed at 900 °C for 1.5 h and aged at 530 °C, 560 °C, and 590 °C for 4 h, and then their tensile performance, impact toughness, and fracture toughness were examined. Results indicate that higher aging temperatures not only facilitate the segregation of Al element, resulting in a reduction in the effective size (dαlaths, the width/length ratio) of primary α laths (αlaths) and their amount, but also promote phase transition, inducing an increase in the effective size (dαfine) of secondary fine α (αfine) lamellae. While both dαlaths−1/2 and dαfine−1/2 have a linear relationship with the strength, which was analyzed using the Hall–Petch relationship, the more pronounced interface strengthening effect and hindering crack propagation mainly results from the αlaths. Moreover, the plasticity declines significantly as the proportion of the αlaths phases decreases. Thus, for strength and plasticity, the αlaths are a much more important factor than the αfine lamellae. However, although the synergistic deformation and fracture of both the αlaths and αfine phases can consume a larger impact initiation energy, the enhancement of the impact energy of the alloy is primarily related to a high precipitation amount of the αfine lamellae. Furthermore, the decrease in dαlaths promotes the misorientation and accumulation of dislocations between αlaths interfaces, hindering the enhancement of KIC (fracture toughness) by forming transgranular fractures. Conversely, the increase in KIC attributed to the energy consumed in the plastic deformation region at the crack tip, due to the αfine lamellae compensates for the energy, resulting in a reduction in the crack propagation path. Therefore, the αfine lamellae may play a more crucial role in increasing the toughness of alloys, in particular the impact toughness of the TC21 alloy.

Different Dynamics Drive Indian Ocean Moisture to the Southern Slope of Central Himalayas: An Isotopic Approach

AbstractThis study uses precipitation oxygen isotopes (δ18Op) to examine key dynamics that deliver moisture to the southern slope of central Himalayas over different seasons. Results show that the majority of pre‐monsoon δ18Op values are relatively high and controlled by the westerlies and local moisture. However, some abnormally low δ18Op values coincide with higher precipitation amounts during the pre‐monsoon season due to moisture driven northwards from the Bay of Bengal and Arabian Sea to central Himalayas by anomalous circulations (quasi‐anticyclone, anticyclone, or/and westerlies trough). The size and location of the quasi‐anticyclone also influences the magnitude of the δ18Op decrease. In comparison, the monsoon δ18Op values are lower due to the combined effects of the Indian summer monsoon and convection. Our findings indicate that researchers need to consider the signals of abnormally low δ18Op values during the pre‐monsoon season when attempting to interpret ice core and tree‐ring records from central Himalayas.

Studies on the Effects of Liming Acidic Soil on Improving Soil Physicochemical Properties and Yield of Crops: A Review

Soil acidity is a major constraint to crop production globally by potentially limiting agricultural productivity and causing environmental challenges, especially in temperate and tropical regions of the world where there is high precipitation. The review article summarizes the works of literature and gathers information on the effects of liming on soil's physicochemical properties and the yield of crops. Soil acidity is caused by natural ways, such as the high amount of precipitation that exceeds evapotranspiration that leaches appreciable amounts of exchangeable bases from the soil surface, weathering, and decomposition of organic matter and by human interference (by the use of nitrogen fertilizer mainly ammonia and urea fertilizers). Application of lime improved soil pH and neutralize the effect of toxic elements. Liming directly improves some physicochemical properties of the soil, such as aggregates, density, and porosity as physical properties and reduction of exchangeable acidity, Al saturation, micronutrients (Cu, Fe, Mn, and Zn) in the soil solutions, from exchange complex to the levels required and increasing soil pH, exchangeable cations (Na+, K+, Ca+2, and Mg+2) as chemical properties. Soil aggregation, density, and porosity of soil undergo changes with the application of lime. The long-term lime application resulted in increased soil chemical properties. Lime application contributed to increased crop productivity and crop quality. The effects of liming can be explained by the flocculation and cementing action of Calcium ions in the short term. In the long term, increases in productivity induced by liming, result in increasing soil pH, available phosphorus, cation exchange capacity, basic cations, microbial activity, organic carbon, total nitrogen, and decreasing leaching of nutrients, exchangeable aluminum, and acidity, all favoring the physical and chemical properties of the soil.

ML-based regionalization of climate variables to forecast seasonal precipitation for water resources management

Numerous dams and reservoirs have been constructed in South Korea, considering the distribution of seasonal precipitation which highly deviates from the actual one with high precipitation amount in summer and very low amount in other seasons. These water-related structures should be properly managed in order to meet seasonal demands of water resources wherein the forecasting of seasonal precipitation plays a critical role. However, owing to the impact of diverse complex weather systems, seasonal precipitation forecasting has been a challenging task. The current study proposes a novel procedure for forecasting seasonal precipitation by: (1) regionalizing the influential climate variables to the seasonal precipitation with k-means clustering; (2) extracting the features from the regionalized climate variables with machine learning-based algorithms such as principal component analysis (PCA), independent component analysis (ICA), and Autoencoder; and (3) finally regressing the extracted features with one linear model of generalized linear model (GLM) and another nonlinear model of support vector machine (SVM). Two globally gridded climate variables-mean sea level pressure (MSLP) and sea surface temperature (SST)-were teleconnected with the seasonal precipitation of South Korea, denoted as accumulated seasonal precipitation (ASP). Results indicated that k-means clustering successfully regionalized the highly correlated climate variables with the ASP, and all three extraction algorithms-PCA, ICA, and Autoencoder-combined with the GLM and SVM models presented their superiority in different seasons. In particular, the PCA combined with the linear GLM model performed better, and the Autoencoder combined with the nonlinear SVM model did better. It can be concluded that the proposed forecasting procedure of the seasonal precipitation, combined with several ML-based algorithms, can be a good alternative.

Atmospheric fallout of 7Be in bulk precipitation at the Adriatic coast, Croatia

ABSTRACT Atmospheric fallout of naturally occurring cosmic radionuclide 7Be was monitored in bulk precipitation over a year (July 2018 to June 2019) at a coastal station (Martinska) of the Adriatic Sea, Croatia. The monthly depositional fluxes varied between 25.08 and 78.97 Bq m−2 month−1 (average: 49.18 ± 19.17 Bq m−2 month−1) and showed a significant correlation with precipitation (r = 0.92). The highest seasonal flux observed in winter (172 ± 4.31 Bq m−2 season−1) coincides with the highest amount of precipitation (190 mm), suggesting an important role of precipitation in the scavenging process of 7Be deposition to the surface. The monthly volume-weighted activities of 7Be varied from 0.63 to 5.74 Bq L−1 (average: 1.96 ± 1.7 Bq L−1) with the highest value corresponding to the summer season. The precipitation-normalised enrichment factor (α) indicates a higher depositional flux of 7Be in the summer season than the desired value due to the stratosphere-troposphere exchange and the contribution of dry deposition. The annual bulk depositional flux of 7Be was 590 Bq m−2 y−1, which is comparable with several Mediterranean coastal stations. The annual bulk depositional fluxes of 7Be in the 30°N - 50°N latitude band showed a good correlation with precipitation and established that the atmospheric fallout of this radionuclide is mainly governed by precipitation in that given latitude band.

Validation of precipitation obtained from GPM and H-SAF satellite data with relation to Ukrainian ground weather stations' data

The main objective of this study is to validate H-SAF and GPM satellite precipitation data for the territory of Ukraine. Validation was carried out by comparing satellite data with data from ground weather stations of Ukrainian Hydrometeorological Center and included the following stages: data collection and processing, bringing the data to the same spatial and temporal resolution, calculation of correlation coefficients and construction of confusion matrices. Correlation coefficients were calculated for each of the stations for two studied periods (the first period - April-September 2020, the second period - April-September 2021). In addition, to ensure a more detailed analysis, confusion matrices were constructed based on division of precipitation into classes of different intensity. The comparative analysis showed that a larger number of stations (117) has a correlation coefficient of 0.5 - 0.8 with relation to GPM data, and, as for HSAF precipitation data, a larger number of stations (59) has a low correlation coefficient (0 - 0.3). Confusion matrices were calculated for the following four classes of rainfalls (mm): “0-2”, “2-5”, “5-10”, “>10”. The confusion matrices coefficients showed that low-intensity precipitation or “no precipitation”, as well as high-intensity precipitation, can be determined by a satellite with high accuracy as opposed to the ground-based weather station measurements. Thus, according to the "specificity" indicator, a precipitation class >10 mm has the highest level of correspondence of satellite data (H-SAF, GPM Late, GPM Early) to ground data. The low value of the "specificity" for the range of 0-2 mm is explained by the fact that satellite methods are able to detect very low values of precipitation intensity, while the station shows their absence – 0 mm. Thus, according to the values of the confusion matrices, we see that a large part of the values of ground measurements of precipitation in the range of 0-2 mm are shown by the satellite method as “2-5 mm” class. We can also see that the “2-5 mm” class by satellite has the most confusion with the 0-2 mm class by station (for H-SAF, GPM Late, GPM Early). But based on the high values of the "recall" for the range of 0-2 mm (for H-SAF, GPM Late, GPM Early), we can conclude that when the station does not show this amount of precipitation (0-2 mm), then the satellite also shows another class of values. The values of "precision" coefficient show that the satellite measurements are actually reliable. This means that presence or absence of precipitation may be determined precisely, since the highest value of the "precision" coefficient is typical for low and high amounts of precipitation (on average 0.76 and 0.66, respectively). Detected by satellites, heavy precipitation or no precipitation are also confirmed in most cases by ground stations. Based on the results of the validation, GPM and H-SAF satellite precipitation data products can be used for rainfall monitoring and considered as an additional source of meteorological information.

COMPARATIVE ASSESSMENT OF THE PRODUCTIVITY OF AGROPHYTOCENOSES WITH PEAS DEPENDING ON HYDROTHERMAL RESOURCES

In the soil and climatic conditions of the Right-Bank Forest-Steppe, regardless of the influence of abiotic and biotic factors, high adaptability of annual agrophytocenoses of spring oats and spring triticale with seed peas was established during the growing season. It is important to note the response of oat and pea plants to changes in moisture supply and temperature during the growing season, provided that the biological characteristics of the crop are maintained, to form an average yield of dry matter and digestible protein within 5.81 and 0.619 t/ha over 24 years of observations, respectively. During the long-term research period, the sum of active temperatures was 874 oC, precipitation was 124 and the hydrothermal coefficient was 1.46. Long-term studies have shown that during the formation of vegetative mass by agrophytocenoses (May-June), the distribution of precipitation was uneven against the background of an increase in the average monthly air temperature, which was reflected in the yield of dry matter and its quality. During the 10 years of research, the highest amount of precipitation was observed - 159-204 mm. The most critical period for growth processes and crop formation was 1999, 2003, 2004, when 37-53 mm of precipitation fell with the sum of active temperatures of 762-880 mm and the GTC of 0.46-0.69. Over the past 9 years (2011-2019), the temperature has increased to 1021°C. Comparing the fodder productivity of binary mixtures of annual crops, it can be stated that with early spring sowing, the yield of fodder units and crude protein in fodder oats was higher compared to spring triticale. This is primarily due to the biological characteristics and duration of the vegetation period of the studied crops, which in spring triticale, unlike oats, the earing phase occurs 8-10 days earlier. The research gives grounds to conclude that it is agrobiologically expedient to use binary grass mixtures with different types of cereal crops in the raw material conveyor. The use of cereal crops that mature at different times ensures the production of plant material for harvesting fodder (green mass, silage, hay or haylage from dried grasses) between the first and second mowing of perennial grasses. In particular, it is also important to note that biological groups of plants effectively use agrometeorological resources during the stages of organogenesis, forming a sustainable crop with high quality indicators. Based on the data obtained, it is possible to predict the productivity of annual agrophytocenoses for the following years.

Precipitation reconstructions for Paris based on the observations by Louis Morin, 1665–1713 CE

Abstract. This paper presents a precipitation reconstruction that is based on the continuous observations by Louis Morin in Paris from 1665–1713. Morin usually recorded precipitation intensity and duration three times each day (sometimes up to six times) when it snowed or rained. The continuity of his observations can be calculated considering all measurements and observations (e.g., temperature, cloud cover), where on 98.7 % of all days between February 1665 and July 1713 at least one entry per day is noted. To convert these observations to common units, we calibrated them with a multiplicative interacting model using Philippe and Gabriele-Philippe de la Hire's instrumental measurements from Paris. The two series of measurements by de la Hire (father and son) and observations by Morin overlap from 1688–1713. To test the quality of the reconstruction, we analyzed it with the de la Hire's measurements, proxy data, an internal analysis of Morin's measurements of different climate variables, and modern data. Thus, we assess the reliability of the precipitation reconstructions based on Morin's data as follows. We have moderate confidence regarding the exact quantities of daily, seasonal, and annual precipitation totals. We have low confidence regarding exceptionally high precipitation amounts, but we have high confidence in the indices of an impact analysis (i.e., dry days, wet days, consecutive dry days, consecutive wet days); in monthly frequencies of rainfall; and in interannual, interseasonal, and interdecadal variability. Rainy seasons with precipitation totals greater than 250 mm occurred in MAM 1682, JJA 1682, SON 1687, JJA 1697, and JJA 1703. Furthermore, compared to other DJF seasons, the winter of 1666/1667 slightly stands out with a precipitation total of 214.6 mm. Dry seasons with precipitation totals less than 60 mm occurred in SON 1669, DJF 1671/1672, and DJF 1690/1691. An impact analysis shows no abnormalities regarding consecutive dry days or wet days in MAM. In JJA a longer dry period of 31 days appeared in 1686 and a dry period of 69 d appeared in DJF 1671/1672.

Using Object-Based Verification to Assess Improvements in Forecasts of Convective Storms between Operational HRRR Versions 3 and 4

Abstract The object-based verification procedure described in a recent paper by Duda and Turner was expanded herein to compare forecasts of composite reflectivity and 6-h precipitation objects between the two most recent operational versions of the High-Resolution Rapid Refresh (HRRR) model, versions 3 and 4, over an expanded set of warm season cases in 2019 and 2020. In addition to analyzing all objects, a reduced set of forecast–observation object pairs was constructed by taking the best forecast match to a given observation object for the purposes of bias-reduction and unequivocal object comparison. Despite the apparent signal of improved scalar metrics such as the object-based threat score in HRRRv4 compared to HRRRv3, no statistically significant differences were found between the models. Nonetheless, many object attribute comparisons revealed indications of improved forecast performance in HRRRv4 compared to HRRRv3. For example, HRRRv4 had a reduced overforecasting bias for medium- and large-sized reflectivity objects, and all objects during the afternoon. HRRRv4 also better replicated the distribution of object complexity and aspect ratio. Results for 6-h precipitation also suggested superior performance in HRRRv4 over HRRRv3. However, HRRRv4 was worse with centroid displacement errors and more severely overforecast objects with a high maximum precipitation amount. Overall, this exercise revealed multiple forecast deficiencies in the HRRR, which enables developers to direct development efforts on detailed and specific endeavors to improve model forecasts. Significance Statement This work builds upon the authors’ prior work in assessing model forecast quality using an alternative verification method—object-based verification. In this paper we verified two versions of the same model (one an upgrade from the other) that were making forecasts covering the same time window, using the object-based verification method. We found that the updated model was not statistically significantly better, although there were indications it performed better in certain aspects such as capturing the change in the number of storms during the daytime. We were able to identify specific problem areas in the models, which helps us direct model developers in their efforts to further improve the model.

Influence of heat treatment processes on microstructure evolution, tensile and tribological properties of Ti6Al4V alloy

The influence of heat treatment processes on microstructure, tensile and tribological properties of Ti6Al4V alloy was investigated. The specimens were heated for 30 min at 925 °C and then cooled at various rates by water quenching, air cooling, and furnace cooling. After that, the samples were aged for four hours at 600 °C. Three phases make up the microstructure: primary α-phase (αp), secondary α-phase (αs), and retained β-phase (βr). Cooling in the air and water followed by aging (AC + Aging and WQ + Aging) resulted, αs-phase precipitating inside βr-phase. The highest hardness of 35 HRC was recorded for WQ + Aging specimen due to existence of a high amount of βr-phase and precipitation of αs-phase. On the other hand, the lowest hardness of 26 HRC was obtained for the FC specimen. AC specimen achieved the highest elongation value of 14%. However, WQ + Aging specimen exhibited the highest ultimate tensile strength of 1028 MPa. For WQ + Aging and AC + Aging specimens, the ideal balance of strength and elongation was discovered. The wear resistance of solution-treated specimens was significantly improved by the aging process and 125% improvement could be achieved in WQ compared to WQ + Aging specimens.

Spatio-temporal analysis of the sources and transformations of anthropogenic nitrogen in a highly degraded coastal basin in Southeast China.

Nitrogen transport from terrestrial to aquatic environments could cause water quality deterioration and eutrophication. By sampling in the high- and low-flow periods in a highly disturbed coastal basin of Southeast China, hydrochemical characteristics, nitrate stable isotope composition, estimation of potential nitrogen source input fluxes, and the Bayesian mixing model were combined to determine the sources and transformation of nitrogen. Nitrate was the main form of nitrogen. Nitrification, nitrate assimilation, and NH4+ volatilization were the main nitrogen transformation processes, whereas denitrification was limited due to the high flow rate and unsuitable physicochemical properties. For both sampling periods, non-point source pollution from the upper to the middle reaches was the main source of nitrogen, especially in the high-flow period. In addition to synthetic fertilizer, atmospheric deposition and sewage and manure input were also major nitrate sources in the low-flow period. Hydrological condition was the main factor determining nitrate transformation in this coastal basin, despite the high degree of urbanization and the high volume of sewage discharge in the middle to the lower reaches. The findings of this study highlight that the control of agricultural non-point contamination sources is essential to pollution and eutrophication alleviation, especially for watersheds that receive high amounts of annual precipitation.

The Mount Washington Observatory Regional Mesonet: A Technical Overview of a Mountain-Based Mesonet

Abstract The Mount Washington Observatory Regional Mesonet (MWRM) is a network of 18 remote meteorological monitoring stations (as of 2022), including the Auto Road Vertical Profile (ARVP), located across the White Mountains of northern New Hampshire. Each station measures temperature and relative humidity, with additional variables at many locations. All stations need to withstand the frequent combination of intense cold, high precipitation amounts, icing, and hurricane-force winds in a mountain environment. Due to these challenges, the MWRM employs rugged instrumentation, an innovative radio-communications relay approach, and carefully selected sites that balance ideal measuring environments with station survivability. Data collected from the MWRM are used operationally by forecasters (including Mount Washington Observatory and National Weather Service staff) to validate model guidance, by alpine and climate scientists, by recreationalists accessing conditions in the backcountry, by groups operating on the mountain (Cog Railway, toll Auto Road), and by search and rescue organizations. This paper provides a detailed description of the network, with emphasis on how the challenging climate and terrain of this mountain region impacts sensor selection, site maintenance, and overall operation. Significance Statement The mountain environment is a heterogeneous landscape, and interactions between the atmosphere and terrain can cause a wide variety of conditions across time and space. Our network of remote stations at different elevations across the White Mountains allows data users to understand how the weather varies spatially across the mountain range where conditions on higher peaks can be drastically, and dangerously, different. Sharing information about the MWRM can help other groups establish networks in similar challenging environments, and broaden our understanding of weather and climate in mountainous regions.

The Effect of the Cordillera Mountain Range on Tropical Cyclone Rainfall in the Northern Philippines

In this study, we examined the sensitivity of tropical cyclone (TC) characteristics and precipitation to the Cordillera Mountain Range (CMR) in Luzon, Philippines. Using the Weather Research and Forecasting (WRF) model, we simulated eight TCs with four different CMR orographic elevations: Control, Flat, Reduced, and Enhanced. We found that at significance level α=0.05, TC intensity significantly weakened as early as 21 h prior to landfall in the Enhanced experiment relative to the Control, whereas there was little change in the Flat and Reduced experiments. However, throughout the period when the TC crossed Luzon, we found no significant differences for TC movement speed and position in the different orographic elevations. When a TC made landfall, associated precipitation over the CMR increased as the mountain height increased. We further investigated the underpinning processes relevant to the effect of the CMR on precipitation by examining the effects of mountain slope, incoming perpendicular wind speed, and the moist Froude Number (Fw). Compared with other factors, TC precipitation was most strongly correlated with the strength of approaching winds multiplied by the mountain slope, i.e., stronger winds blowing up steeper mountain slopes caused higher amounts of precipitation. We also found that individually, Fw, mountain height, and upslope wind speeds were poor indicators of orographically induced precipitation. The effects of mountain range on TC rainfall varied with TC cases, highlighting the complexity of the mountain, wind, and rainfall relationship.

Impacts of extreme climate on nitrogen loss in different forms and pollution risk with the copula model

Climate change is a key factor that profoundly affects aquatic environments. Because of climate warming, the increase in the intensity and frequency of extreme climate events has aggravated the uncertainty of nitrogen pollution. However, the risk of nitrogen loss under different climatic conditions has not been well assessed, which is of great significance for controlling diffuse pollution. In this study, we used the upper and middle Wei River Basin (UMWB) as the study area, and selected organic nitrogen (Org-N) and nitrate (NO3-N) as the two forms of nitrogen pollution. Then, we quantified the contributions of 10 climate factors and combined the Soil and Water Assessment Tool (SWAT) and copula to analyze the risk of pollution when extreme weather occurs. Our results showed that during periods of high precipitation and temperature, Org-N loss accounted for 96% and 83% of the total loss, and nitrate loss accounted for 74% and 67%, respectively. Org-N loss responded more strongly to high precipitation than nitrate loss because Org-N was transported with soil particles. The attribution analysis indicated that high precipitation amount (R95P) contributed to the largest Org-N loss. As for the nitrate loss, R95P, normal precipitation amount, and consecutive days with no precipitation were the most important climatic drivers, accounting for 35%, 32%, and 13% of the watershed area, respectively. After selecting critical source areas by identification method, an optimized copula model for nitrogen loss and the main climatic factors was proposed. The risk of nitrogen pollution under the defined climate severity was then quantified. The probabilities of Org-N and nitrate loss exceeding the top 1%–20% were 0.2%–15% and 0.8%–10% when the precipitation exceeded the top 20%. The pollution risk caused by high temperatures is lower than that caused by precipitation. This study emphasized the dominant role of extreme climate in driving nitrogen loss and proposed a method for quantifying the risk of nitrogen pollution under specific climate conditions, which enabled managers to identify high-risk pollution areas and optimize management measures to prevent diffuse nitrogen pollution.

Changes of extreme precipitation in the middle and lower reaches of the Yangtze River and their correlation with atmospheric circulation

Under the backdrop of climate change, the rising frequency and intensity of extreme precipitation events in the middle and lower Yangtze River (MLYR) region are causing serious consequences and economic losses. To assess regional risk and understand the impact of atmospheric circulation on extreme precipitation, it's crucial to analyze the spatial and temporal fluctuations of these events, focusing on the time-frequency phase relationship. Using the observed precipitation data from 1979 to 2015, nine extreme precipitation indices were calculated and a trend analysis and wavelet coherence analysis were performed to evaluate their variation. The results show that: 1) an overall increase in the frequency, intensity, and duration of precipitation in the MLYR, with significant rises in the wet daily precipitation and highest precipitation amount in 1-day period; 2) a higher likelihood of extreme precipitation events in the southeast of the MLYR, and an uneven spatial distribution; 3) the Western Pacific Subtropical High (WPSH), the South China Sea high (SCSH), and the East Asian westerly jet (EAJ) all play a role in precipitation changes in the MLYR, with the WPSH having the most significant impact, followed by the SCSH, and the EAJ being weaker. The results deepen our understanding of the various characteristics and causes of extreme precipitation in the MLYR.

Evaluation of the effect of pre-sowing treatment of grain sorghum seeds with fungicides on the development of blotches in the forest-steppe of the Samara Region

Relevance. It is important to evaluate the effectiveness of modern fungicides and their effect on the development of leaf infections of grain sorghum in order to optimize plant protection against diseases. Methods. The studies were carried out in the fields of the Volga Scientific Research Institute of Selection and Seed-Growing named after P.N. Konstantinov on grain sorghum variety Premiere in 2014–2016. Leaf diseases were estimated by eye in the field during the phases of flowering, milky, waxy, and full grain ripeness. The average lesion of each plant was evaluated, and the prevalence and intensity of disease development was established. Seeds were treated immediately before sowing. Biological effectiveness of the studied fungicides was determined by prevalence and intensity of disease development. Results. Analysis of leaves showed that quite a wide complex of pathogens belonging to the kingdom of fungi caused blotches on sorghum leaves. Mycelium and spores of fungi Alternaria sp., Fusarium sp., Helminthosporium sp. and others were detected on the affected leaves in the stain area. The obtained results allow us to conclude that the development of the fungal leaf blotches in sorghum in the conditions of forest-steppe of the Samara region considerably depends on hydrothermal conditions of the year: the more arid are conditions of May and June, the higher amount of precipitation and thelower temperature is in July, the higher is leaf blotch infestation of sorghum. Seed pretreatment with fungicides suppressed fungal leaf blotch development in the Premiere variety by 13.6–47.0 % in 2014, 6.9–62.2 % – in 2015, and 3.5–53.7 % – in 2016. At the same time, the highest biological efficacy showed treatment of seeds with fungicides of contact-system action “Fundazol” and “Vitaros”; was 25.0–75.0 % in prevalence and 26.2–62.2 % in the intensity of leaf blotch development.

High-Resolution Reanalysis of Daily Precipitation using AROME Model Over France

Among the various meteorological variables, precipitation is one of significant interest, especially for hydrological studies. However, obtaining a reliable precipitation data set is a difficult challenge as precipitation can be very discontinuous in space and time. In this study, a method to obtain a high resolution precipitation reanalysis over France is purposed based on a study from 01/01/2016 to 31/12/2018. The French operational regional model Application de la Recherche à l’Opérationnel à Méso-Echelle (AROME) is combined with precipitation observations, which have been quality controlled, using an optimum interpolation data assimilation algorithm. To use this technique, some hypotheses have to be verified, such as the Gaussian distribution of the innovations. Since the precipitation distribution is highly asymmetric, a Box-Cox transformation is applied to both background and observations to work with variables which behave like Gaussian variables. Then, the background and observation standard deviation errors are determined thanks to the semi-variogram technique, which provides daily values. Results show that the Box-Cox transformation provides better scores for light precipitation and has the same quality as the reference – analysis in the physical space – for high precipitation amounts.

Study of floods on the rivers of the Kaliningrad region at the beginning of 2020 in the absence of snow cover and ice

To develop measures for engineering protection of territories from flooding, it is necessary to identify spatiotemporal patterns in the formation of floods, since they are the cause of devastating floods in recent years. The paper presents the results of an analysis of flood phenomena on the rivers of the Kaliningrad region at the beginning of 2020. An array of observational data on daily water flows in rivers was processed, and the main components of the water balance of river basins were assessed by month (amount of precipitation, evaporation layer, monthly river flow layer, change in basin moisture reserves). It was found that the greatest amount of runoff was in February, while the highest amount of precipitation was in June; the highest runoff coefficient was in March and February (0.41), and in June it was only 0.03. Presumably, the main reasons for such phenomena are the distribution of the evaporation layer within the year and a decrease in the permeability of the upper soil layer for precipitation at low temperatures.