Daily Precipitation Totals Research Articles

REGIONÁLNE KLIMATICKÉ SCENÁRE FREKVENCIE VÝSKYTU DNÍ SO ZRÁŽKAMI NA SLOVENSKU

We present scenarios of how frequency of days with precipitation may change over the territory of Slovakia by 2050 and 2080 in the article. Climatic scenarios were created from three regional climate models EURO-CORDEX for the pessimistic emission scenario RCP8.5. We analysed the occurrence of the number of precipitation days for class intervals: 5 – 9.9 mm, 10 – 19.9 mm, 20 – 29.9 mm, 30 – 39.9 mm, as well as for open intervals ≥ 5 mm, ≥ 10 mm, ≥ 20 mm, ≥ 30 mm, and ≥ 40 mm. To correct systematic errors in climate models, we used data (daily precipitation totals) from the national network of rain gauges. The RCM models were corrected in two steps: first in terms of excessive occurrence of so-called “drizzle days”, and then in terms of systematic underestimation of daily sums across the entire distribution function (bias correction). The occurrence of days with daily rainfall exceeding 40 mm for the horizons of 2050 and 2080 is presented in the form of maps. As our analyses revealed, the annual frequency of days with daily rainfall exceeding 40 mm is expected to increase by approximately 20% by the middle of the 21st century and by up to 60% by the end of the century compared to the present. The paper also includes tables with relative changes and absolute frequencies of wet days for 75 selected locations in Slovakia.

Spatiotemporal variability of flash floods and their human impacts in the Czech Republic during the 2001–2023 period

Abstract. Flash floods, characterized by their sudden onset, extreme discharge, short duration, material damage, and human loss, represent a significant natural hazard. Not well covered by standard hydrological observations, flash flood data can primarily be derived from various types of documentary evidence. This evidence served as the main data source for creating a flash flood database for the Czech Republic from 2001 to 2023. This database enabled detailed analysis of different aspects of flash floods. The annual series of 233 flash flood events, 160 flash flood days, and 424 affected municipalities showed significant inter-annual variability but no linear trends. The triggering rainfall that generates flash floods was analyzed with respect to 1–3-hourly and daily precipitation totals and circulation types from the objective classification. While flash floods can occur anywhere, they were more frequently recorded at the foots of mountain slopes, often coinciding with “critical points” where built-up areas meet concentrated surface runoff pathways. The division of material damage caused by flash floods into eight categories indicated that the highest proportion of damage was to streets and communications (24.3 %), to houses (21.7 %), and to their cellars and basements (18.3 %). There were also 36 recorded fatalities. The understanding of flash floods in the Czech Republic aligns generally well with studies of flash floods in other European regions.

Variability of Dry Days and Sequences of Dry Days in the Polish Carpathians in the Period 1986–2020

This study provides a climatological analysis of annual and long-term variability of dry days and sequences of dry days in the Polish Carpathians between 1986 and 2020. The input data for the research was compiled from the daily precipitation totals from 17 meteorological stations and the T. Niedźwiedź catalogue of circulation types over southern Poland. The frequency of sequences of dry days of different duration has been presented. The incidence of long-term periods has been related to the atmospheric circulation. The number of dry days and the averages of both the number and of the duration of sequences of dry days were analysed for the study period. This yielded an average annual number of dry days ranging from 142 to 195 (39–53% of days in a year), depending on the altitude above sea level and longitude. A general pattern emerged in which the number of dry days increased from west to east. At most stations, there were no statistically significant trends with respect to the dry day characteristics analysed. This is an obvious result of high year-to-year variability, which means that only large changes can achieve statistical significance. Dry days have been evidenced to relate to circulation types. The vast majority of dry days are related to anticyclonic systems, particularly the anticyclonic wedge (Ka) and western anticyclonic (Wa) situations. On the other hand, no clear-cut relationship was established between an increase in air temperature and the occurrence of dry days.

Water Budget Input Linked to Atmospheric Rivers in British Columbia's Nechako River Basin

ABSTRACTThis study explores the contribution of atmospheric rivers (ARs) to the water budget input of the Nechako River Basin (NRB) in British Columbia (BC), western Canada. The study quantifies the fraction of precipitation, rainfall, snowfall, and snow water equivalent (SWE) associated with ARs at multiple scales and tests for trends using the Mann–Kendall (MK) test. AR‐related totals for 1950–2021 were created by linking AR events to water budget input variables of the ERA5‐Land reanalysis product on a daily scale. Associations with different phases of the El Niño‐Southern Oscillation (ENSO) climate pattern and AR‐related contributions to the NRB are also investigated. Results indicate an increasing fractional contribution of rain in ARs landfalling in the NRB in the last two decades (2000–2019). Moreover, 21% of the total annual precipitation in the NRB is associated with ARs, with decreasing contributions from west to east. October has higher AR‐related total precipitation than other months, while March, May and June are the least affected. ARs contribute disproportionately more to mid‐ and high‐intensity daily precipitation totals, and provide up to 45% and 24% of the seasonal rainfall and snowfall, respectively. AR‐related SWE is relatively higher in autumn due to the increased frequency and intensity of ARs, resulting in a greater fractional contribution of ARs to the snowpack compared to winter. ARs influence snowpack accumulation during fall (18%) and winter (13%) but also increase the risk of natural hazards. The MK test for AR‐related water budget variables on the annual scale identified no significant trends. However, AR‐related snowfall shows decreasing trends in the NRB, more specifically in the Upper Nechako, Lower Nechako and Stellako sub‐basins during the summer. Over the study period, ARs consistently contribute up to one‐fifth of the annual input to the NRB's water budget. This study provides the first quantitative assessment and trend analyses of AR contributions to the water budget input of a reservoir‐regulated watershed in north‐central BC, yielding valuable information for hydropower production, ecological flows, irrigation, domestic and industrial water use.

Rapid Estimation of Soil Erosion Rate from Exhumed Roots (Xiaolong Mts, China)

Soil erosion is a challenge worldwide, including in China. The dendrogeomorphic method was applied, for the first time, at Xiaolong Mts in Gansu Province to obtain a quantitative estimate of the soil erosion rate. The dataset built in this pilot study allowed the identification of exhumation texture in exposed roots between 1967 and 2002. The calculated mean erosion rate estimates (Era) ranged from 2.6 to 16.5 mm yr−1 and showed an increase with the slope steepness (s). The best fitting linear model (Era = 0.043(±0.017) × s + 3.09(±1.04); R² = 0.20; R²adj = 0.16; F = 6.18; p = 0.02) could be used in future research to determine and to map soil denudation in this part of the Xiaolong Mts. Notable associations were found between erosive rainfalls and root exhumation events. Daily (Rx1day) and 5-day (Rx5day) precipitation totals of 56 and 73 mm, respectively, seem to be critical thresholds which if exceeded will always induce root exhumation in the same year or in the consecutive season in the forest of the Xiaolong Mts in the studied period.

Dry and Wet Spells in Poland in the Period 1966–2023

The aim of this study is to present the spatial and temporal variability of the frequency of dry and wet days and dry and wet spells against the background of changes in precipitation and atmospheric circulation. The study is based on daily precipitation totals from 46 meteorological stations in Poland from 1966 to 2023. Additionally, seven circulation indices were used, namely GBI, NAO, AO, EA, EA/WR, SCAND, and AMO. Dry days are defined as days without precipitation. Wet days are days with at least 1 mm of precipitation. It was shown that dry spells are much more common than wet spells, are longer, and cover larger areas. Long-term changes in the annual characteristics of dry and wet days and spells are not statistically significant. Only the length of the most extended dry spell in the year increases. However, there are significant changes in their annual cycles. Spring is drier; in summer, precipitation decreases in the south and increases in the north; November and December, symbols of gloomy rainy weather, are increasingly drier; and rainy weather has shifted to January and February. The impact of circulation varies according to the season, with the NAO, AO, SCAND, and GBI indices having the greatest influence.

Identification of the key driving factors of flash flood based on different feature selection techniques coupled with random forest method

Study regionThe mountainous area of Guangdong Province, China. Study focusA random forest coupling with feature selection (RF-FS) method framework, containing random forest coupling with shadow variable search, random forest coupling with recursive feature elimination, and random forest coupling with genetic algorithm, is introduced to identify the key driving factors (KDFs) of flash flood that can be used to explain the flash flood process and generate the flash flood risk map efficiently.New hydrological insights for the region: Among the KDFs identified by the RF-FS method framework, meteorological factors (maximum 1-day precipitation, total daily precipitation exceeding 95 % threshold, and maximum 5-day consecutive precipitation) are dominant, followed by hydrological factors (topographic wetness index and stream power index). Flash flood risk modeling was then developed by using the KDFs identified by the random forest coupling with genetic algorithm which is the best in the RF-FS method framework in predicting flash flood risks. Furthermore, the modeling results show that about 45 % of the mountainous areas in Guangdong Province are high flash flood-prone areas (high and extremely high-risk areas), and most of them are located in the central, eastern, and southwestern mountainous areas of Guangdong Province. The areas with flash flood-prone occurrences are generally consistent with the areas with large precipitation, implying that these areas should be prioritized for flash flood prevention and early warnings.

The Variability of Maximum Daily Precipitation and the Underlying Circulation Conditions in Kraków, Southern Poland

This article studies the intra-annual and long-term variability in the maximum daily precipitation totals and their association with atmospheric circulation in Kraków. It investigates daily precipitation maxima by year and by month. The research is based on daily precipitation totals in the years 1863–2021 and draws on the calendar of atmospheric circulation types by Niedźwiedź. It examines the frequency of precipitation maxima in individual months and their variation from one year to another. No statistically significant trend of change in precipitation over the study period has been found. All annual maximum daily precipitation totals in Kraków fall into the category of heavy precipitation (>10 mm), and almost 99% qualify as very heavy (>20 mm). In the summer months, these are about 3–4 times higher than in winter. The share of the daily precipitation maximum in the monthly total exceeds 30% in all months. The maximum daily precipitation occurring on 5 August 2021 was the highest in the period that extends from the start of instrumental measurements. The study period saw 12 cases of maximum precipitation that belong to ‘flood-inducing’ categories (over 70 mm/day). Such cases of the very heaviest precipitation occurred in cyclonic situations: Cc, Bc, Nc, NEc, Ec and SEc. Most spring and summer maxima were seen on days with a cyclonic circulation. The instances of high daily precipitation in the Kraków area led to the flooding of residential and historic buildings, as well as of municipal infrastructure.

Evaluation of IMERG for GPM satellite-based precipitation products for extreme precipitation indices over Turkiye

As hydrological disasters become more common, the need for monitoring extreme precipitation events is growing globally. Remote sensing technologies developed in recent years help to meet this demand with satellite-based precipitation products, particularly for ungauged basins. However, due to limitations and uncertainties, these products must be validated before being used in hydrometeorological/climatological applications. Validation studies also help improve retrieval algorithms by identifying errors and biases in the data that can be corrected or adjusted. One of NASA's Global Precipitation Measurement products, called Integrated Multi-satellitE Retrievals for GPM (IMERG), has been extensively validated for its ability to detect extreme precipitation events in drastically different climate regions across the world. However, such studies remain limited for Turkiye. In this study, we examined the ability of IMERG Early (E), Late (L), and Final (F) products to detect extreme precipitation in Turkiye using rain gauge data over an eleven-year period (2010−2020). We used extreme precipitation indices recommended by the Expert Team on Climate Change Detection Indices (ETCCDI) to evaluate the ability of IMERG products to detect extreme precipitation. For the stations selected across Turkiye, the Pearson correlation coefficients (R) between daily ground-based precipitation measurements and the three IMERG precipitation products (IMERG-E, IMERG-L, and IMERG-F) were found to be 0.54, 0.55, and 0.64, respectively. IMERG products performed better in detecting the precipitation extreme based on the 85% percentile compared to the 95% and 99% percentiles. IMERG underestimates consecutive dry days by about 25% while overestimating consecutive wet days at the same rate. The performance of IMERG Early, Late, and Final products is inversely proportional to the daily precipitation totals. The annual intensity of precipitation outperformed in the Final run compared to other products across the country. Light and moderate rainfall was detected well, while the detection capability of IMERG decreased for heavy and heavy torrential precipitation. Geographically, the Aegean, Mediterranean, and Southeastern Anatolia regions generally performed better, while Eastern Anatolia and interior parts of the Black Sea region exhibited poorer performance. The low performance in Eastern Anatolia may be attributed to the region's mountainous terrain, while the low performance in the Black Sea region may be due to orographic forcing and land-sea interaction. Overall, the findings of this study showed that the detection capability of IMERG products performed better with increasing latency.

Estimation of the Daily Production Levels of a Run-of-River Hydropower Plant Using the Artificial Neural Network

Renewable energy sources, as well as the studies being conducted regarding these energy sources, are becoming increasingly important for our world. In this manuscript, the daily energy production level of a small (15 MW) run-of-river hydropower plant (RRHPP) was estimated using the artificial neural network (ANN) model. In this context, the model utilized both meteorological data and HPP-related data. The input parameters of the artificial neural network included the daily total precipitation, daily mean temperature, daily mean water vapour pressure, daily mean relative humidity, and the daily mean river water elevation at the hydropower plant, while the only output parameter consisted of the total daily energy production. For the ANN, data from the four years between 2017 and 2020 were used for training purposes, while data from the first eight months of 2021 were used for testing purposes. Ten different ANN networks were tested. A comparison of the ANN data with the real data indicated that the model provided satisfying results. The minimum error rate was 0.13%, the maximum error rate was 9.13%, and the mean error rate was 3.13%. Furthermore, six different algorithms were compared with each other. It was observed that the best results were obtained from the Levenberg-Marquardt algorithm.This study demonstrated that the ANN can estimate the daily energy production of a run-of-river HPP with high accuracy and that this model can potentially contribute to studies investigating the potential of renewable energies.

Evaluation of Selected Amateur Rain Gauges with Hellmann Rain Gauge Measurements

The paper compares precipitation measurements from the Stratus manual rain gauge from the CoCoRaHS network and two Davis Vantage Vue and Davis Vantage Pro 2A rain gauges with the Hellmann rain gauge. Comparative measurements were made on a specially prepared experimental plot. The statistical calculations took into account 15 full months in the period from 1 October 2019, to 31 December 2020. In order to estimate the differences in measurements between amateur rain gauges and the Hellmann rain gauge, two statistics were calculated: the mean square error (MSE) and the mean absolute error (MAE). In order to present formal and more detailed differences in measurements between amateur rain gauges and the Hellmann rain gauge, analyses were performed using a linear regression model. The general form of the tested models was presented. The procedure for estimating the parameters of the models and the method of comparing the fit of the models to the data were described, and the rain gauge whose measurements were most closely related to the measurements of the Hellmann rain gauge was indicated. The study showed that the higher price of amateur rain gauges does not mean higher quality. The study showed that the Stratus rain gauge was the best at recording daily precipitation totals. The Davis Vantage Pro 2A rain gauge recorded daily precipitation sums with less accuracy. The Davis Vantage Vue rain gauge, despite being located on the roof, recorded similar rainfall totals as the Hellmann rain gauge. It was found that, despite the different construction and measurement methods, the precipitation measurement data from the Stratus rain gauge and the Davis Vantage Vue rain gauge are suitable both for climate monitoring and for use, after applying quality control, in NMHS networks.

Trees as bioindicators of hillslope degradation by debris flows and dangerous rockfalls along the Lefthand Canyon, Colorado Front Range

AbstractTrees provide important ecosystem services such as hillslope stabilization from landslides and rockfall protection, and may also be useful indicators of likelihood of those events in the future. Anatomical changes of tree wood are caused by various physical and biological phenomena. There are several geomorphic processes that change tree‐ring characteristics, including hillslope movement, and if detectable, these changes may be used as bioindicators of terrain surface stability. This type of proxy data is vital to places that lack systematic monitoring infrastructure. In the present study, we have evaluated the effects of a heavy rainfall that happened on 11–13 September 2013 in the Colorado Front Range (CFR), which triggered more than 1300 debris flows. We intensely studied one large debris flow that was triggered in the region and the surrounding trees. We explored potential tree‐based records of hillslope instability including compression wood and the method of eccentricity index of tree rings prior to the 2013 event. In addition, the response index was correlated with daily precipitation totals of the previous and current year in a moving window mode. We also evaluated rockfall patterns to explore the frequency and spatial distribution of tree‐scar‐based records. Our primarily goal was to test the method in dry climate conditions and to reconstruct possible soil instability episodes and rockfalls that led to hillslope degradation and tree mortality. In this study, we aimed to fill a significant knowledge gap on debris flows and rockfalls frequency in a dry montane forest system. We were able to distinguish 5 years of increased response index (>25% of trees recording slope instability): 1955 (30%), 1982 (27%), 2002 (27%), 2006 (31%), and 2009 (26%). A spring and early summer season daily precipitation totals of the previous year and summertime daily precipitation totals of the current year explained part of the response index variability. Significant correlation coefficients were up to 0.27. Almost 30 historical rockfall events were dated but only one coincided with an earthquake. In total 138 scars visible on growing trees were mapped. Some of them were found even 3.1 m above the ground level. We conclude that trees can be effective bioindicators of hillslope instability related to debris flows and rock falling. However, extreme climate events such as heavy rainfall causing a high number of debris flows can be difficult to predict based on the method adopted in the present study.

Analysis of Climatic Change through Comparing Methods of Statistical Estimation for Two-Parameter Gamma Distribution in Nigeria

In other to improve the ability of decisionmakers to prepare for and deal with the unforeseen circumstances resulting from climate change as consequences of precipitation fluctuations, extreme and torrential rainfall. It is important to provide a more complete understanding of the range and likelihood of rainfall patterns a location could receive using a probabilistic model whose parameters might complement or even replace such common measures as the mean, median, variance, minimum, maximum and quartile values as major descriptors of rainfall at such location. Daily precipitation totals can be approximated by the gamma distribution as it is bounded on the left at zero and positively skewed indicating an extended tail to the right which suit the distribution of daily rainfall and accommodate the lower limit of zero which constrains rainfall values. This paper presents the comparison between Maximum Likelihood Estimation (MLE) of closed & open form solutions and Method of Moment Estimation (MME) of location and scaling parameters of the twoparameter gamma distribution, the parameters were estimated using MME and MLE with their performance adjudged and the result obtained showed that the closedform solution of the MLE outperformed the open form solution and MME by comparing their estimates for the scaling parameter.

Pavement Distress Initiation Prediction by Time-Lag Analysis and Logistic Regression

Pavement condition prediction plays a vital role in pavement maintenance. Many prediction models and analyses have been conducted based on long-term pavement condition data. However, the condition evaluation for road sections can hardly support daily routine maintenance. This paper uses high-frequency pavement distress data to explore the relationship between distress initiation, weather, and geometric factors. Firstly, a framework is designed to extract the initial time of pavement distress. Weather and geometric data are integrated to establish a pavement distress initiation dataset. Then, the time-lag cross-correlation analysis methods were utilized to explore the relationship between distress initiation and environmental factors. In addition, the logistic regression model is used to establish the distress initiation prediction model. Finally, Akaike information criterion (AIC), Bayesian information criterions (BIC), and areas under receiver operating characteristic curves (AUC) of logistic regression models with or without time-lag variables are compared as performance measurements. The results show that pavement distress initiation is susceptible to weather factors and location relationships. Daily total precipitation, minimum temperature, and daily average temperature have a time delay effect on the initiation of the pavement distress. Distress initiation is negatively correlated with the distance from the nearby intersection and positively correlated with adjacent distresses. The weather factors, considering the time-lag effect, can improve the model performance of the distress initiation prediction model and provide support for emergency management after severe weather.

Climate change influence on brook trout populations in the Central Appalachians

AbstractExamining variation in fish populations over time is strengthened when climatic variations are understood and incorporated into analyses. We used a 18‐year brook trout (Salvelinus fontinalis) data set with samples across a ~4800 km2 spatial area in the Central Appalachian Mountains, combined with PRISM climate data at the HUC‐12 subwatershed level to investigate temporal trends of each. We found significant increases in air temperature (p < .01) with no significant trends in precipitation across time, including no trends in changes in variation of temperature and precipitation also. Extreme rainfall events (# of days above 95% percentile for total daily precipitation in a year) and consecutive dry days (cumulative # of consecutive days with <3 mm precipitation in a year) were also examined and produced no significantly changing trends over time. Using random forests, seasonal climate variables identified as changing over time explained 35.1% of the variability in young‐of‐the‐year brook trout abundance over the 18‐year monitoring period. The same procedure explained 25.1% of the variability in juvenile abundance and only 5.1% in adult abundance. Variable selection following random forest generation illustrated significant effects for winter and spring precipitation (both negative on young‐of‐the‐year abundance. Spring degree days and spring precipitation both had significant negative effects on juvenile abundance. Random effects for stream and year explained a maximum of 27.7% and 10.8% of the variation in abundance across all models. A significant, positive interaction between spring degree days and precipitation was also identified, lending support to the important balance between temperature and flow in these systems that is critical to brook trout persistence. This work provides long‐term evidence to help understand the dynamics of these sentinel headwater fish populations as they experience a changing climate.

Comparing Methods of Estimation for Two-Parameter Gamma Distribution Using Rainfall Patterns in Nigeria

In other to improve the ability of decision-makers to prepare for and deal with the unforeseen circumstances resulting from climate change as consequences of precipitation fluctuations, extreme and torrential rainfall. It is important to provide a more complete understanding of the range and likelihood of rainfall patterns a location could receive using a probabilistic model whose parameters might complement or even replace such common measures as the mean, median, variance, minimum, maximum and quartile values as major descriptors of rainfall at such location. Daily precipitation totals can be approximated by the gamma distribution as it is bounded on the left at zero and positively skewed indicating an extended tail to the right which suit the distribution of daily rainfall and accommodate the lower limit of zero which constrains rainfall values. This paper presents the comparison between Maximum Likelihood Estimation (MLE) of closed & open form solutions and Method of Moment Estimation (MME) of location and scaling parameters of the two-parameter gamma distribution, the parameters were estimated using MME and MLE with their performance adjudged and the result obtained showed that the closed-form solution of the MLE outperformed the open form solution and MME by comparing their estimates for the scaling parameter.

Characterizing temporal trends of meteorological extremes in Southern and Central Ontario, Canada

Forecasts of increased frequency of meteorological extremes have received considerable attention due to their potential impact on the integrity of biotic communities, stability of terrestrial and aquatic environments, availability of ecosystem services, and broader societal prosperity. Canada is projected to experience greater warming rates than many other regions of the world and changes in meteorological extremes are predicted to be variable across the country. In this context, our goal is to evaluate the long-term trends of extreme meteorological variables (air and dew point temperature, relative humidity, wind speed, and precipitation) in southern and central Ontario (from 42°N to 50°N), while considering the role dynamics of large-scale atmospheric oscillations (El Niño–Southern Oscillation, North Atlantic Oscillation, Arctic Oscillation, and Pacific Decadal Oscillation). Air temperature minima increased year-round, while temperature maxima mainly increased during the cooler months of the year. Consistent with recent evidence from the literature, our study identified an increase in the amount of atmospheric water since the 1950s, as shown by the rising trends in dew point temperature maxima and minima during winter and mid-summer/early-autumn, respectively. Likewise, we found a weak decline in the relative humidity during the warm season, and a more discernible declining trend during the cooler part of the year, which could be in turn reflective of the moderate change of temperature maxima and rising minima, respectively. Consistent with the broader evidence of a global terrestrial stilling, our analysis showed a declining occurrence of high wind-speed events across the entire study domain, and more frequent slow-wind speeds during both warm and cold periods of the year. Interestingly, a closer examination of temporal trends in calm wind frequency provides evidence of a recent reversal in the latter trend with diminishing prevalence of very calm wind conditions. We generally found a weakly increasing temporal trend with maximum total daily precipitation, but without a coherent spatial pattern within the broader study area. Our analysis showed that large-scale phenomena have a discernible signature mostly on air temperature and humidity variables, but had little impact on low relative humidity, high and low wind-speed, and precipitation variability. Given the modest impact of teleconnections on long-term temporal trends, our study concludes that the meteorological extremes are more directly influenced by regional and local heat and humidity balance processes rather than global-scale atmospheric circulation. The observed trends of air temperature, humidity, and wind speed extremes suggest a profound impact on the phenology of aquatic and terrestrial ecosystems and human experience of weather.

Daily rainfall intensity and temporal trends in eastern Paraná state – Brazil

The present study aims to analyze the intensity of daily extreme rainfall and trends for precipitation in Castro, Curitiba and Paranaguá stations, located in the state of Paraná, Brazil. Historical series of rainfall registered by the Brazilian National Institute of Meteorology were used considering the period from 1976 to 2015. The Mann-Kendall and Pettitt statistical tests were applied to identify trends and ruptures in historical rainfall series. Other indicators of trends in rainfall and temperature were calculated using the RClimDex software, developed by the Canadian Meteorological System. The classification of cumulative daily rainfall in 24 h with the application of the quantile technique was defined as a standard for percentiles. The months of January, February and December presented greater occurrence frequency of rainfall equal to or greater than 95% and 99% of the quantiles for all locations. The comparative analysis showed that Paranaguá station has the largest accumulated values of rainfall in 24 h during the rainiest months, between September and April, while Castro and Curitiba stations recorded the highest daily totals between May and August. Increasing daily precipitation totals were identified in all quantile's classes with statistical significance only in Curitiba and Paranaguá station, which is attributed to greater urban densities and its direct impacts over daily rainfall totals. Significant trends for increased rainfall were observed, especially in Curitiba, a condition that is associated with the expressive and also significant increase in climate indicators of air temperature.

Analysis of anomalies in the control probes of the Rozgrund dam

The subject of the contribution is to clarify the causes of anomalous development of water levels in some observation objects of the Rozgrund dam. To clarify the anomalous development of the water levels, a detailed analysis of the development of water levels in all observation probes built on the dam, the water levels in the reservoir and the daily total precipitation was performed. An important knowledge is the amplitudes of fluctuations in water levels in observation probes and in the water levels in the reservoir. The calculations of correlation coefficient, expressing the relationship between water level in individual boreholes and the water level in the reservoir are another step in assessment of anomalies. Based on the knowledge obtained, it was possible to assess the degree of the influence of the water level in the reservoir on the development of the water level regime in observation objects. At the same time, it was also possible to detect the existence of other effects influenced the water levels in the probes, such as the leakage into their surroundings caused by precipitation or the impact of waters flowing from hillslopes.

Precipitation in the Czech Republic in Light of Subjective and Objective Classifications of Circulation Types

Many studies in Europe have investigated the relationship between climatological variables and circulation patterns expressed by various classifications of circulation types. This study provides new insights based on an analysis of precipitation in the western (Bohemia—BOH) and eastern (Moravia and Silesia—M&S) parts of the Czech Republic with respect to the subjective classification of the Czech Hydrometeorological Institute and objective classification based on the flow strength, flow direction, and vorticity during the 1961–2020 period. Circulation types are investigated in regard to their contributions to the total precipitation, mean daily precipitation totals, and precipitation probability (daily totals ≥ 1.0 mm). Types with a westerly airflow and a trough over Central Europe exhibit the highest proportions in precipitation totals. Types with a cyclone over Central Europe, especially combined with a northwestern (BOH) or northeastern (M&S) airflow, result in the highest daily mean totals and precipitation probability. Types with a southwestern airflow transport more precipitation to BOH, while those with a northeastern airflow transport more precipitation to M&S, with a slight seasonal shift in the gradient axis between winter and summer. Circulation types under both classifications are examined from the perspective of their precipitation representation in BOH and M&S and the differences between these two regions. In addition, the suitability of both classifications for precipitation analysis is investigated.