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Extreme short-duration rainfall is intensifying with climate warming, and growing evidence suggests that subhourly rainfall extremes are increasing faster than more widely studied durations at hourly and daily timescales. In this case study, we used 55 years (1968–2022) of 5-min precipitation data from Mahantango Creek, a long-term experimental agricultural watershed in east-central Pennsylvania, United States, to examine annual and seasonal changes in subhourly (15-min), hourly, and daily rainfall extremes. Specifically, we evaluated temporal trends in the magnitude and frequency of subhourly, hourly, and daily rainfall extremes. We then estimated apparent scaling rates between rainfall extremes and dew point temperature (Td) and compared these rates to the Clausius-Clapeyron (CC) rate (∼ 7% per °C). We also determined the coincidence of extreme rainfall trends with indicators of atmospheric instability and convective-type precipitation. Overall, we found the most significant changes in rainfall extremes at 15-min durations during the spring, with magnitudes of these subhourly extremes increasing by 0.6 to 0.9% per year, and frequencies rising by 3.4% per year. Apparent scaling rates in the spring showed that 15-min rainfall extremes transitioned from sub-CC scaling to greater than 2CC scaling when Td reached 11° C, implying a possible shift from stratiform rains to more intense convective rains above this Td threshold. Notably, trends in maximum hourly convective available potential energy (CAPE) increased during spring, as did the ratio of 15-min rainfall extremes to their corresponding daily rainfall totals. Findings indicate that convective-type precipitation may be playing an increasing role in the intensification of springtime 15-min rainfall extremes in Mahantango Creek. [ABSTRACT FROM AUTHOR]

Precipitation intensity-duration-frequency (IDF) Model was developed for designated regions in Southern Nigeria. Thirty-two years (1983-2014) daily rainfall data were collected for Lagos, Ibadan, Benin, Calabar, Port Harcourt and Warri from Nigeria Meteorological Agency (NIMET) Oshodi, Lagos State for the study. The procedure of annual maximum series was used to select data sets for precipitation investigation. The advanced storm, a pattern developed by United State Department of Agriculture (USDA) Soil Conservation service was used to in the development of the models, which was used to break down daily rainfall into shorter durations. Gumbel and Log Pearson Type III distributions were used to compute the observed rainfall intensity values at durations of 10, 15, 20, 30, 60, 120, 180, 240, 300, and 360 minutes for return periods of 2, 5, 10, 25, 50, and 100 years. To obtain parameters for the IDF models for each location, the computed rainfall intensities were subjected to non-linear regression analysis using Microsoft Excel Optimization Technique Solver wizard for the respective durations and return periods. The performance of the models were analyzed by determining the chi-square(X² ), coefficient of determination (R²), and root mean square error(RMSE) of the fitted distributions. Coefficient of determination values, R² obtained from the fitted IDF Models adopting Log Pearson Type 111 and Gumbel distributions gave perfect value of 1 for both regions. Gumbel distribution RMSE values ranged from 0.20 -11.73 for Port Harcourt, 0.50 – 10.94, 0.21 – 9.25 for Calabar and Warri, also Benin, Lagos and Ibadan regions has 1.31 – 9.5, 1.28 – 15.92, 0.49 – 13.08 while, Log Pearson Type 111 RMSE values ranges from 0.23 – 9.68 for Port Harcourt, 0.41 – 11.47, 0.01 – 10.23 for Calabar and Warri while Benin, Lagos and Ibadan regions has 0.29 – 10.0, 0.51 – 15.69, 0.79 – 10.37. However, there was no significant difference amongst the predicted intensities of the various IDF models. [ABSTRACT FROM AUTHOR]

Abstract Extreme short-duration rainfall is intensifying with climate warming, and growing evidence suggests that subhourly rainfall extremes are increasing faster than more widely studied durations at hourly and daily timescales. In this case study, we used 55 years (1968–2022) of 5-min precipitation data from Mahantango Creek, a long-term experimental agricultural watershed in east-central Pennsylvania, United States, to examine annual and seasonal changes in subhourly (15-min), hourly, and daily rainfall extremes. Specifically, we evaluated temporal trends in the magnitude and frequency of subhourly, hourly, and daily rainfall extremes. We then estimated apparent scaling rates between rainfall extremes and dew point temperature (Td) and compared these rates to the Clausius-Clapeyron (CC) rate (∼ 7% per °C). We also determined the coincidence of extreme rainfall trends with indicators of atmospheric instability and convective-type precipitation. Overall, we found the most significant changes in rainfall extremes at 15-min durations during the spring, with magnitudes of these subhourly extremes increasing by 0.6 to 0.9% per year, and frequencies rising by 3.4% per year. Apparent scaling rates in the spring showed that 15-min rainfall extremes transitioned from sub-CC scaling to greater than 2CC scaling when Td reached 11° C, implying a possible shift from stratiform rains to more intense convective rains above this Td threshold. Notably, trends in maximum hourly convective available potential energy (CAPE) increased during spring, as did the ratio of 15-min rainfall extremes to their corresponding daily rainfall totals. Findings indicate that convective-type precipitation may be playing an increasing role in the intensification of springtime 15-min rainfall extremes in Mahantango Creek.

The Three River Headwaters （TRH） region， known as the “Water Tower of China”， is a crucial freshwater source and an ecological barrier in China.Changes in precipitation concentration， seasonal precipitation amount， frequency， and intensity is a key process of water cycle in the context of global warming， holding significant implications for vegetation growth and water resource management in the TRH region.In this study， utilizing the CN05.1 daily precipitation gridded dataset from 1961 to 2020 prepared by the China Meteorological Administration， the Precipitation Concentration Index （PCI） were calculated， and the evolving patterns of precipitation concentration and intra-annual distribution in the TRH region were clarified.The climatology， relative interannual variability， long-term trends， and anomalies of annual and seasonal precipitation amount， frequency， and intensity were investigated.The results find that： （1） Precipitation in the TRH region exhibits a certain degree of concentration with PCI of 17.5.PCI increased from southeast to northwest， suggesting an increased precipitation concentration.Over the past 60 years， PCI has declined at a rate of -1.71% per decade， indicating a trend towards more evenly distributed monthly precipitation throughout the year.It’s noteworthy that the reduction in the proportion of precipitation during the growing season may have ramifications for agricultural production and ecosystem maintenance in the TRH region.（2） Over the past six decades， there has been a significant overall increase in precipitation amount and intensity during different seasons.However， precipitation frequency decreased during summer while increasing in other seasons.Enhanced precipitation intensity has predominantly contributed to the rise in precipitation amount during spring， summer， and autumn， while increased precipitation frequency has played a dominant role in elevating precipitation amount during winter.The increase rate in humidity during winter and spring was higher than that during summer and autumn.In spring， precipitation amount and intensity increased by 8.09% and 6.94% per decade respectively， while winter saw snowfall amount and frequency grow by 7.27% and 4.4% per decade.Also noteworthy is the distribution of droughts and floods in parts of the Yangtze River source area tends towards extreme， exacerbating the ecosystem vulnerability.（3） The regional average precipitation amount， frequency， and intensity in the TRH region have shown an increase of 1.36 mm， 0.024%， and 0.0056 mm·d-1 per year over the past 60 years.The cumulative anomalies of precipitation amount， frequency， and intensity in the last 60 years were negative， with abrupt changes occurring in 2003， 1989， and 2003， respectively.There has been a significant decrease in precipitation frequency during the rainy season， coupled with a substantial increase in precipitation intensity.In contrast， both precipitation frequency and intensity during the dry season have experienced significant increases.These changes have been particularly pronounced in the past decade.This study can serve as a valuable reference for research concerning soil erosion， agricultural production， water resource management， and climate change in the TRH region.

Climate models indicate that a warmer environment will increase low‐level moisture, potentially intensify extreme precipitation. However, its impact on different rainfall types remains unclear. Using satellite data, we examined changes in light (0‐95th percentile, ≤5.28 mm hr−1) and heavy (95‐100th percentile, >5.28 mm hr−1) precipitation in the tropics from 1998 to 2019. Our findings show a −9 ± 2% (23 ± 2%) change in heavy (light) rain intensity and a 13 ± 2% (−24 ± 1%) change in heavy (light) rain frequency. These changes link to warmer sea surface temperatures, increased atmospheric stability and water vapor, and weakened upward velocity. These insights shed light on how heavy and light precipitation patterns respond to changing climate, emphasizing the complexities within the hydrological cycle. Plain Language Summary: The hydrologic cycle depends greatly on precipitation. With the expectation of climate warming causing substantial changes to the global water cycle, comprehending these shifts becomes pivotal in foreseeing how climate changes will affect society. Climate models suggest that as temperatures rise, low‐level moisture will increase. However, the specific impacts of this heightened moisture on the intensity and frequency of precipitation events remain uncertain. Analyzing data from the Tropical Rainfall Measuring Mission (1998–2019), we found notable changes: a 23 ± 2% increase in light rain intensity, a −9 ± 2 % decrease in heavy rain intensity, a 13 ± 2 % rise in heavy rain frequency, and a significant −24 ± 1% decrease in light rain frequency. These changes result diverse factors like warming oceans, stabilized atmospheric conditions, increased water vapor, and weakened upward velocity. This underscores the intricate interplay between different rainfall types and how they respond to the evolving climate. Key Points: In the tropics from 1998 to 2019, heavy rain intensity decreased and light rain intensity increasedIn the tropics from 1998 to 2019, heavy rain frequency increased and light rain frequency decreasedRain shifting patterns linked to increased SST, atmospheric stability, and water vapor and decreased upward velocity [ABSTRACT FROM AUTHOR]

In this study, concentrations of three different air pollutants (PM10, SO2, and NO2) were obtained from four air quality monitoring stations (AQMSs) over an 11-year period from 2013 to 2023. Meteorological variables (temperature, dew point temperature, wind speed, sea level pressure, and precipitation) were then obtained from the nearest European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) grid point to each station, and their relationships were analyzed. Homogeneity and normality tests were conducted for air pollutant concentrations and meteorological variables, followed by data preprocessing analyses using non-parametric tests. The ultimate aim of this study is to determine the effects of the presence and intensity of precipitation on pollutant concentrations. Analyses based on four different precipitation intensity categories (light, moderate, heavy, and severe) indicated that increasing precipitation intensity is associated with decreasing pollutant concentrations. Specifically, higher precipitation intensities were associated with a reduction in pollutant levels, with reductions ranging from 15% to 35% compared to dry conditions. This effect was particularly pronounced during the winter season, when PM10 concentrations decreased by up to 45% on wet days compared to dry days. This finding highlighted the importance of not only precipitation intensity but also the type of hydrometeor for air pollution. The significant decrease observed during winter is thought to be due to snowfall, which is believed to have a greater removal effect on air pollution compared to rain. [ABSTRACT FROM AUTHOR]

Extreme precipitation events induced by tropical cyclones have increased frequency and intensity, significantly impacting human socioeconomic activities and ecological environments. This study systematically examines the spatiotemporal characteristics of these events across Hainan Island and their influencing factors using GsMAP satellite precipitation data and tropical cyclone track data. The results indicate that while the frequency of typhoon events in Hainan decreased by 0.3 events decade−1 from 1949 to 2020, extreme precipitation events have increased significantly since 2000, especially in the eastern and central regions. Different typhoon tracks have distinct impacts on the island, with Track 1 (Northeastern track) and Track 2 (Central track) primarily affecting the western and central regions and Track 3 (Southern track) impacting the western region. The impact of typhoon precipitation on extreme events increased over time, being the greatest in the eastern region, followed by the central and western regions. Incorporating typhoon precipitation data shortened the recurrence interval of extreme precipitation in the central and eastern regions. Diurnal peaks occur in the early morning and late evening, primarily affecting coastal areas. Typhoon duration (CC_max = 0.850) and wind speed (CC_max = 0.369) positively correlated with extreme precipitation, while the pressure was negatively correlated. High sea surface temperature areas were closely associated with extreme precipitation events. The atmospheric circulation indices showed a significant negative correlation with extreme precipitation, particularly in the western and central regions. ENSO events, especially sea surface temperature changes in the Niño 1 + 2 region (−0.340 to −0.406), have significantly influenced typhoon precipitation characteristics. These findings can inform region-specific disaster prevention and mitigation strategies for Hainan Island. [ABSTRACT FROM AUTHOR]

Copyright of Plateau Meteorology is the property of Plateau Meteorology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Specific features of nowcasting as a forecast of current weather, its needs for observational data, and main approaches to solving a forecast problem are discussed: from simple extrapolation to hydrodynamic models with assimilation of an extended set of high-resolution observations. Prospects of machine learning applications are assessed. Some peculiarities of the nowcasting of precipitation and wind, which are the parameters of particular interest for most of users, are considered. The methodological complexity of the seamless approach to the nowcasting problems, extremely limited deterministic predictability on convective spatiotemporal scales, and importance of using a probabilistic approach are noted. Some illustrations from the national nowcasting developments are presented. [ABSTRACT FROM AUTHOR]

A unipolar ground-based weather radar is a widely-used instrument for rainfall measurement. These radar measurements, however, need to be calibrated for more accurate rainfall estimation. This article introduces a new calibration approach using time-stepwise processing of reflectivity–rainfall rate () relationship. Based on the previous work utilizing the radar–rainfall relationship, this article hypothesizes that the rainfall measurement from a ground based radar are affected by the distance from radar, altitudes and rainfall time duration. Unipolar ground-based radar data sets for two consecutive years with 77 occurrences of rainfall from 39 stations in calibration window of three hours as well as the corresponding rainfall measured from registered rain gauges were used in this study. The results indicated that it is better to use the radar–rainfall relationship in view of the altitude effect () and empirical coefficient (), such that . The changes in the distance from the radar and duration of precipitation were evidently significant. For radar–rainfall relationship individually, the values of the determination coefficient made up from 0.88 to 0.97, and those for this relationship in view of the altitude effect () were from 0.70 to 0.97. It is therefore concluded that the use of other effective parameters (distance from radar, altitude and rainfall time duration) leads to optimum accuracy of the relationship. [ABSTRACT FROM AUTHOR]

This study aims to reveal the long-term station-based characteristics of precipitation in Istanbul, a mega city located on the continents of Europe and Asia, with complex topography and coastline along the Marmara and Black Seas. Using data from five different stations, three located in the European continent and two in the Asian continent, with measurement periods ranging from 72 to 93 years, wet and dry days have been identified, statistics on precipitation conditions during the warm and cold seasons have been generated, categorization based on precipitation intensities has been performed, and analyses have been conducted using extreme precipitation indices. At stations located in the northern part of the city, higher annual total precipitation has been observed compared to those in the south. A similar situation applies to the number of wet days. While during the cold season, the wet and dry day counts are nearly the same across all stations, this condition exhibits significant differences in favor of dry days during the warm season. Apart from dry conditions, "moderate" precipitation is the most frequently observed type across all stations. However, "extreme" events occur significantly more often (6%) during the warm season compared to the cold season (2%). Long-term anomalies in terms of annual precipitation totals have shown similarity between stations in the north and south, which has also been observed in longitudinally close stations. Despite the longer duration of the cold season and stronger temperature gradients, extreme rainfall events are more frequent during the warm season, primarily due to thunderstorm activity. While trend analyses revealed limited significant trends in precipitation intensity categories and extreme indices, the study highlights the importance of comprehensive examination of extreme rainfall events on both station-based and regional levels, shedding light on potential implications for regional climate change. Lastly, during the cold season, the inter-station correlation in terms of annual total precipitation amounts has been considerably higher compared to the warm season. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the spatial and temporal distribution characteristics and seasonal change patterns of precipitation of various grades across China, enhance the knowledge of the occurrence patterns of different grades of precipitation in China, and then provide scientific and technological support for enhancing the national disaster prevention and mitigation capacity. [Methods] Based on the daily surface precipitation data from 681 meteorological stations in China during 1961—2020, the temporal and spatial distribution characteristics and seasonal variation of the days and intensity of precipitation of different grades (light rain, moderate rain, large rain and heavy rain) across China were analyzes. [Results] (1) From 1961 to 2020, the number of light rain days showed a decreasing trend, while the number of moderate rain, large rain and heavy rain days showed an increasing trend, and no significant changes in the intensity of light, moderate and large rain except for great changes in the intensity of heavy rain were found. The number of light rain days decreased the most in autumn, large and heavy rain days increased the fastest in summer, and the slowest in autumn. The intensity of heavy rain fluctuated greatly in each season. (2) There was some variability in the spatial distribution of different precipitation levels, the high number of light rain days mainly distributed in the southwest river basins, the number of days with moderate rain and above and the intensity of precipitation at each level gradually decreased from southeast to northwest, and the number of days and intensity of precipitation in the Inland River basins were the smallest. (3) Precipitation in spring, autumn and winter mainly concentrated in the southeastern River Basins and the Pearl River Basin, where light rainfall predominated, and in summer precipitation mainly concentrated in the southwestern Rivers Basin, the southeastern Rivers Basin and the Pearl River Basin. The areas with higher intensity of precipitation at all levels in spring were mainly located in the southeastern Rivers Basin, the Yangtze River Basin and the Pearl River Basin, and the areas with higher intensity of precipitation in winter were mainly located in the southeastern Rivers Basin and the Huaihe River Basin. (4) The decrease in the number of light rain days was more obvious in spring and winter, and the southeastern River Basins and the Pearl River Basin contributed greatly to the decrease in the number of light rain days. The number of precipitation days above the moderate rain level was generally on an upward trend in all seasons. The intensity of large rain strengthens in spring and weakened in autumn, and the intensity of heavy rain in all basins was on an increasing trend in spring. [Conclusion] There are obvious differences in the spatial and temporal distribution and seasonal scales of precipitation levels across China, and the contribution of the nine major river basins to the different levels of precipitation across the China varies, so future research on the influence of the major circulation systems and the water cycle in each river basin on the different levels of precipitation should be strengthened. [ABSTRACT FROM AUTHOR]

Global climate change will significantly impact the biodiversity of freshwater ecosystems, both directly and indirectly via the exacerbation of impacts from other stressors. Pesticides form a prime example of chemical stressors that are expected to synergize with climate change. Aquatic exposures to pesticides might change in magnitude due to increased runoff from agricultural fields, and in composition, as application patterns will change due to changes in pest pressures and crop types. Any prospective chemical risk assessment that aims to capture the influence of climate change should properly and comprehensively account for the variabilities and uncertainties that are inherent to projections of future climate. This is only feasible if they probabilistically propagate extensive ensembles of climate model projections. However, current prospective risk assessments typically make use of process‐based models of chemical fate that do not typically allow for such high‐throughput applications. Here, we describe a Bayesian network model that does. It incorporates a two‐step univariate regression model based on a 30‐day antecedent precipitation index, circumventing the need for computationally laborious mechanistic models. We show its feasibility and application potential in a case study with two pesticides in a Norwegian stream: the fungicide trifloxystrobin and herbicide clopyralid. Our analysis showed that variations in pesticide application rates as well as precipitation intensity lead to variations in in‐stream exposures. When relating to aquatic risks, the influence of these processes is reduced and distributions of risk are dominated by effect‐related parameters. Predicted risks for clopyralid were negligible, but the probability of unacceptable future environmental risks due to exposure to trifloxystrobin (i.e., a risk quotient >1) was 8%–12%. This percentage further increased to 30%–35% when a more conservative precautionary factor of 100 instead of 30 was used. Integr Environ Assess Manag 2024;20:384–400. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Key Points: A Bayesian network (BN) model was presented that allows the high‐throughput incorporation of local climate projections into the environmental risk assessment of pesticides in aquatic ecosystems.Predictions for the fungicide trifloxystrobin and the herbicide clopyralid showed that variations in pesticide application rates and precipitation intensity lead to variations in in‐stream exposures.Predicted risks for clopyralid were negligible, but there was an 8%–12% probability of unacceptable future risks due to trifloxystrobin exposure (at a precautionary factor of 30), increasing to 30%–35% when a more precautionary factor of 100 was used.The BN model is set up to facilitate future inclusion of climate‐dependent pesticide applications and large ensembles of local climate projections, downscaled from global climate models. [ABSTRACT FROM AUTHOR]

Abstract Climate models indicate that a warmer environment will increase low‐level moisture, potentially intensify extreme precipitation. However, its impact on different rainfall types remains unclear. Using satellite data, we examined changes in light (0‐95th percentile, ≤5.28 mm hr−1) and heavy (95‐100th percentile, >5.28 mm hr−1) precipitation in the tropics from 1998 to 2019. Our findings show a −9 ± 2% (23 ± 2%) change in heavy (light) rain intensity and a 13 ± 2% (−24 ± 1%) change in heavy (light) rain frequency. These changes link to warmer sea surface temperatures, increased atmospheric stability and water vapor, and weakened upward velocity. These insights shed light on how heavy and light precipitation patterns respond to changing climate, emphasizing the complexities within the hydrological cycle.

Abstract Background Global climate change has resulted in precipitation regimes exhibiting an increasing trend in rainfall intensity but a reduction in its frequency. Nitrogen (N) deposition is a crucial component of the global N cycling. Nematode body size is a trait that responds to climate change and is used as a standard trait-based indicator in soil community analysis. Variations in body size influence metabolic carbon (C). We examined the ways by which body size and metabolic C of nematodes respond to changing precipitation regimes and how N deposition regulates these responses by an 8-year manipulative experiment. Methods Nematode body size was indicated by the community-weighted mean (CWM) mass. We quantified C metabolism components of soil nematodes including production C, respiration C, and corresponding C use efficiency (CUE) under different precipitation intensities and N addition in a semi-arid steppe on the Mongolian Plateau. The Mantel test was used to determine the correlations between CWM, CUE and environmental factors. The partial least squares path modeling (PLS-PM) was conducted to quantify direct or indirect contributions among latent variables. Results We found that heavy precipitation intensity increased the CWM mass of total nematodes and omnivores-predators without N addition. N addition decreased CWM mass of bacterivores across all the precipitation intensity treatments. Stronger precipitation intensities might be favorable for nematode production and respiration C. Variations in the nematode CWM mass drove the CUE to change with N addition. Conclusions Our findings provide new insights into the mechanisms underlying nematode body size and C metabolism, and highlight that explorative studies, such as manipulative experiments, are needed to identify traits underlying size-related effects and to investigate how they affect CUE of nematodes. These efforts may increase our understanding of how changes in precipitation regimes and N deposition may alter soil nematode communities in grassland ecosystems.

Background: Global climate change has resulted in precipitation regimes exhibiting an increasing trend in rainfall intensity but a reduction in its frequency. Nitrogen (N) deposition is a crucial component of the global N cycling. Nematode body size is a trait that responds to climate change and is used as a standard trait-based indicator in soil community analysis. Variations in body size influence metabolic carbon (C). We examined the ways by which body size and metabolic C of nematodes respond to changing precipitation regimes and how N deposition regulates these responses by an 8-year manipulative experiment. Methods: Nematode body size was indicated by the community-weighted mean (CWM) mass. We quantified C metabolism components of soil nematodes including production C, respiration C, and corresponding C use efficiency (CUE) under different precipitation intensities and N addition in a semi-arid steppe on the Mongolian Plateau. The Mantel test was used to determine the correlations between CWM, CUE and environmental factors. The partial least squares path modeling (PLS-PM) was conducted to quantify direct or indirect contributions among latent variables. Results: We found that heavy precipitation intensity increased the CWM mass of total nematodes and omnivores-predators without N addition. N addition decreased CWM mass of bacterivores across all the precipitation intensity treatments. Stronger precipitation intensities might be favorable for nematode production and respiration C. Variations in the nematode CWM mass drove the CUE to change with N addition. Conclusions: Our findings provide new insights into the mechanisms underlying nematode body size and C metabolism, and highlight that explorative studies, such as manipulative experiments, are needed to identify traits underlying size-related effects and to investigate how they affect CUE of nematodes. These efforts may increase our understanding of how changes in precipitation regimes and N deposition may alter soil nematode communities in grassland ecosystems. [ABSTRACT FROM AUTHOR]

The intensity of precipitation, particularly high extreme precipitation (HEP), has always been responsible for numerous natural hazards, such as floods and landslides. Therefore, it is crucial to investigate the behavior change of precipitation intensity as a consequence of climate change. This research aims to investigate precipitation intensity, its decadal changes, and precipitation duration for all types of extreme precipitation in Iran. To this end, gridded data of precipitation from the hydrological year 1971–1972 through 2015–2016 was utilized, and the days of heavy (HP), very heavy (VHP), and extremely heavy (EHP) precipitation were extracted using the 90th, 95th, and 99th percentile thresholds, respectively. The investigation results indicated that the maximum intensity of the extreme precipitation types occurred mostly in the Zagros Mountains, the Iranian Coast of the Caspian Sea (ICCS), and parts of the coasts of the Oman Sea and the Persian Gulf. The correlation coefficient between precipitation intensity and spatial features revealed a strong and inverse relationship between precipitation intensity and geographic coordinates (i.e., longitude and latitude). Our findings revealed that the durations of rainy days for HP, VHP, and EHP were 1–8, 1–7, and 1–4 days, respectively. Furthermore, the most intense precipitation occurred in short-term durations (e.g., 1-day duration). The findings also exposed an increasing trend in precipitation intensity of short-term durations in mountainous regions. Moreover, the intensity of HP and VHP increased, while EHP decreased in large areas of the country. Decadal analysis revealed that the maximum intensity of all types of extreme precipitation occurred mainly in the second and third decades. Additionally, the heaviest precipitation events took place in the second decade, which coincided with the dominance of the positive North Atlantic Oscillation (NAO) phase. [ABSTRACT FROM AUTHOR]

In this paper, an algorithm for restoring the precipitation intensity over the ocean surface according to data from the MTVZA-GYa Russian microwave sounder is presented. The developed algorithm is based on the ALG'85 regression model in which the precipitation intensity is estimated using the scattering index on a high-frequency radiometric channel (~90 GHz). In this work, the scattering index is simulated based on MTVZA-GYa data and compared with GPM IMERG reanalysis data. To restore the precipitation intensity, it is proposed to use a fourth-degree polynomial. The quantitative estimates show that the RMS spread reaches 50%, and the correlation coefficient does not exceed 0.75. The qualitative comparison indicates a significant difference between the restored rain rate and the GPM IMERG data, as well as the presence of a shift of the precipitation area. As a result of the analysis, it is concluded that the incorrect convergence of the beams of the radiation patterns for different frequency channels of the MTVZA-GYa device might be one of the causes. [ABSTRACT FROM AUTHOR]

Rainfall simulators are important pieces of equipment to investigate hydrological processes and soil erosion. Here, we investigated the operational characteristics, the rainfall characteristics, and the soil erosion process under collecting plots and rainfall patterns using the InfiAsper simulator. We evaluated the standard plot of the simulator in a rectangular shape (1.0 × 0.7 m), as well as a circular plot (0.8 m diameter), and four precipitation patterns, characterized as advanced (AV), intermediate (IN), delayed (DL), and constant (CT). In the laboratory, uniformity and water consumption tests were carried out for shutter-disk rotations from 138 to 804 rpm, and in the field, simulated rains were applied on a Dystric Acrisol. Rains with different patterns were simulated and presented a uniformity coefficient above 83% for the circular plot and 78.2% for the rectangular plot. The soil erosion varied as a function of the precipitation patterns and, to a lesser extent, according to the shape of the experimental plot. However, runoff and soil loss in AV were 2.1 and 3.5 times greater when using a circular plot. Concerning IN and DL, the length of the rectangular plot may have influenced the formation of small furrows throughout most of the simulated rainfall event, providing greater runoff (13.1 mm) and soil loss (13.6 g m−2). The results obtained are promising, but plots with different shapes associated with rainfall patterns simulated by InfiAsper must be evaluated in other classes and soil use and cover conditions. [ABSTRACT FROM AUTHOR]

This study explores the relationship between water vapor and rainfall intensities over three tropical lands (Amazon Basin, Sahel, southern South America) and three tropical ocean regions (Atlantic Ocean, Indian Ocean, Niño 4). We utilized daily total column water vapor (TCWV) data from the Atmospheric Infrared Sounder (AIRS) and daily precipitation records from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation. Over tropical land, precipitation shows higher sensitivity to changes in water vapor, with a well-sorted pattern of an increased occurrence of higher daily precipitation as TCWV increases. Precipitation intensity over the Sahel, in particular, is extremely responsive to TCWV change. Over tropical oceans, the precipitation intensity is less sensitive to water vapor, particularly in the Indian Ocean and Niño 4 where precipitation intensities above the 40th percentile are no longer responding to the increasing TCWV. Quantifying water vapor and precipitation intensity aids in forecasting the occurrence of precipitation between tropical land and oceans.

Extreme precipitation events induced by tropical cyclones have increased frequency and intensity, significantly impacting human socioeconomic activities and ecological environments. This study systematically examines the spatiotemporal characteristics of these events across Hainan Island and their influencing factors using GsMAP satellite precipitation data and tropical cyclone track data. The results indicate that while the frequency of typhoon events in Hainan decreased by 0.3 events decade−1 from 1949 to 2020, extreme precipitation events have increased significantly since 2000, especially in the eastern and central regions. Different typhoon tracks have distinct impacts on the island, with Track 1 (Northeastern track) and Track 2 (Central track) primarily affecting the western and central regions and Track 3 (Southern track) impacting the western region. The impact of typhoon precipitation on extreme events increased over time, being the greatest in the eastern region, followed by the central and western regions. Incorporating typhoon precipitation data shortened the recurrence interval of extreme precipitation in the central and eastern regions. Diurnal peaks occur in the early morning and late evening, primarily affecting coastal areas. Typhoon duration (CC_max = 0.850) and wind speed (CC_max = 0.369) positively correlated with extreme precipitation, while the pressure was negatively correlated. High sea surface temperature areas were closely associated with extreme precipitation events. The atmospheric circulation indices showed a significant negative correlation with extreme precipitation, particularly in the western and central regions. ENSO events, especially sea surface temperature changes in the Niño 1 + 2 region (−0.340 to −0.406), have significantly influenced typhoon precipitation characteristics. These findings can inform region-specific disaster prevention and mitigation strategies for Hainan Island.

In this study, concentrations of three different air pollutants (PM10, SO2, and NO2) were obtained from four air quality monitoring stations (AQMSs) over an 11-year period from 2013 to 2023. Meteorological variables (temperature, dew point temperature, wind speed, sea level pressure, and precipitation) were then obtained from the nearest European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) grid point to each station, and their relationships were analyzed. Homogeneity and normality tests were conducted for air pollutant concentrations and meteorological variables, followed by data preprocessing analyses using non-parametric tests. The ultimate aim of this study is to determine the effects of the presence and intensity of precipitation on pollutant concentrations. Analyses based on four different precipitation intensity categories (light, moderate, heavy, and severe) indicated that increasing precipitation intensity is associated with decreasing pollutant concentrations. Specifically, higher precipitation intensities were associated with a reduction in pollutant levels, with reductions ranging from 15% to 35% compared to dry conditions. This effect was particularly pronounced during the winter season, when PM10 concentrations decreased by up to 45% on wet days compared to dry days. This finding highlighted the importance of not only precipitation intensity but also the type of hydrometeor for air pollution. The significant decrease observed during winter is thought to be due to snowfall, which is believed to have a greater removal effect on air pollution compared to rain.

The Three-River Headwaters (TRH) region in the Tibetan Plateau is vulnerable to climate change; changes in summer (June–August) precipitation have a significant impact on water security and sustainability in both local and downstream areas. However, the changes in summer precipitation of different intensities over the TRH region, along with their influencing factors, remain unclear. In this study, we used observational and ERA5 reanalysis data and employed a precipitation categorization and water vapor budget analysis to quantify the categorized precipitation variations and investigate their possible linkages with the water vapor budget. Our results showed an increasing trend in summer precipitation at a rate of 0.9 mm per year (p

Currently, there are many scientific publications concerning changes in climatic conditions of individual regions, countries, continents and the entire earth as a planet. This fact has led us to consider these changes regarding their impact on the development of erosion processes in mountain conditions. The basis was the research presented in S.E Kuchiev’s PhD thesis of 1996-1998, as well as the verification of hypotheses put forward in the research on the development of erosion processes. The above mentioned required the continuation of research in the second period from 2008 to 2013. On average, 605 mm fell during the years of research, 478 mm in the first period 1996-1998, 668 mm in the second 2008-2013, and from 2 to 8 rains with an intensity of more than 20 mm fell in different years.The correlation analysis shows that with the increase in precipitation observed in recent years, there is a correlation with the amount of heavy rainfall. During the period under review, there were 27 to 48 rains with an intensity above 5 mm. In 2009 heavy rainfall was characterized mainly by an intensity of 20 to 40 mm per day, but in August 2009 and 2010, 71 and 73 mm each fell. The peak of heavy rains was noted in 2012, when in June it rained two days in a row with an intensity of 121 and 101 mm.The indicator of surface runoff has significantly increased, both in the control variant (pure steam) and in rotation crops, which can be arranged in ascending order of their erosion resistance: row crops, cereals of the continuous sowing method and perennial grasses. The research was carried out at the mountain long-term station of the SCNII–GPSH – a branch of the VNC RAS in the village of Dargavs.

Abstract Background Global climate change has resulted in precipitation regimes exhibiting an increasing trend in rainfall intensity but a reduction in frequency. In addition, nitrogen (N) deposition occurs simultaneously in arid and semi-arid regions. Microbial biomass, diversity, composition, and species interactions are key determinants of ecological functions. We examined the effects of changes in precipitation intensity and N addition on the soil bacterial and fungal communities in a semi-arid grassland in Inner Mongolia, China. Methods The microbial biomass (bacterial PLFAs and fungal PLFAs) was determined through phospholipid fatty acid (PLFA) analysis, and microbial diversity (Shannon index and evenness index) was determined with high-throughput sequencing (16S and ITS). Species interactions were determined using a molecular ecological network analysis. The relationships between microbial community (bacterial community and fungal community) and environmental variables were examined by Mantel tests. Results We found that N addition decreased fungal PLFA under moderate, high, and extreme precipitation intensity treatments and increased fungal community complexity under the high precipitation intensity treatment. Furthermore, N addition increased bacterial diversity under moderate and high precipitation intensity treatments. N addition caused greater environmental stress to the fungal community, which was dominated by deterministic processes. Conclusions The effects of N deposition on soil bacterial and fungal communities were altered by precipitation intensity. The changes in soil bacterial and fungal communities were different, implying that composition and functional traits adapt differently to projected global changes at a regional scale.

The IMERG V06 hourly rainfall product at daily and hourly scales was evaluated during the warm season (May to September) from 2015 to 2020 using 651 high-quality rain-gauge stations over the Tibetan Plateau (TP). Based on hourly observed rain-gauge precipitation, four categories were classified: light rainfall (0–12 mm·d−1), moderate rainfall (12–20.1 mm·d−1), torrential rainfall (20.1–32.2 mm·d−1), and extreme torrential rainfall (>32.2 mm·d−1). Precipitation frequency and intensity were calculated to further validate the accuracy and suitability of the IMERG estimated-precipitation product. At the daily scale, IMERG underestimated the number of days with less than moderate rainfall, but overestimated the frequency of torrential and extreme torrential rainfall. IMERG estimated the main characteristics of precipitation frequency at different daily precipitation amount levels better than the precipitation intensity, but its best estimate was at the moderate rainfall level, with the highest correlation coefficient (0.69) and the lowest root mean square error (0.17). At the hourly scale, IMERG underestimated the hourly precipitation amount mainly between the early morning and midday (the average deviation was 0.019 mm·h−1) and overestimated it between the afternoon and late night (the average deviation was 0.047 mm·h−1). IMERG overestimated precipitation frequency and underestimated precipitation intensity between the afternoon and the evening, which means that this analysis shows that IMERG estimated more precipitation hours than the observation and underestimated precipitation intensity. These results further our understanding of the suitability of the IMERG precipitation products over the TP and further improve the IMERG retrieval algorithm to better apply the corresponding precipitation product to light and extreme rainfall over regions with complicated topography. [ABSTRACT FROM AUTHOR]

It is widely known that precipitation is a key variable of the hydrological cycle that is strongly affected by recent climate changes. Therefore, there is a growing interest in research activities focused on alteration of rainfall regime, as it conditions the planning of countermeasures against flood and landslide hazards. The available literature about precipitation tendencies over Italian peninsula offers a limited number of studies about recent changes of extreme events and precipitation intensity. This work aims at adding a contribution to fill this research gap, investigating the changes in rainfall regime observed over the 2002–2021 period in the Campania region (southern Italy). To pursue this aim, a dataset including daily precipitation records collected at 107 stations was analysed both through 11 indices developed by the Expert Team on Climate Change Detection and Indices and through the Standardized Precipitation Index in order to detect signals of changes in extreme events and to assess tendencies towards drier or wetter conditions. The Theil‐Sen method and the Mann–Kendall non‐parametric test were employed to evaluate the trends and their statistical significance. The main results emerging from this work are (i) an increasing tendency in precipitation intensity and in the frequency of occurrence of heavy rainfall events in autumn, mainly in the northern part of the region and in the mountainous areas, (ii) an upward trend of the duration of the longest wet spell in the coastal areas and (iii) an increasing trend of dry spells in spring and in summer in the Gulf of Salerno. [ABSTRACT FROM AUTHOR]

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The spatiotemporal characteristics of subdaily extreme precipitation over the Tibetan Plateau (TP) have undergone significant changes due to global warming. In this study, we employed the high‐resolution Weather Research and Forecasting regional climate model to conduct a series of historical and projection simulations under representative concentration pathways (RCPs), especially RCP4.5 and RCP8.5. The aim was to investigate the past and future climatologies and spatiotemporal evolution of subdaily precipitation extremes using newly proposed subdaily extreme precipitation indices (EPIs). The results show that projected changes in precipitation amount, particularly during wet hours, exhibit spatial disparaties. Notably, there are significant decreases along the southern border of the TP and over the western TP, while obvious increases are observed over the inner TP. The southeastern TP, western TP, and southern border of the TP are expected to experience less frequent, shorter duration, and more intense precipitation on an hourly basis. The TP, as a whole, has demonstrated significantly increasing trends in moderate‐to‐heavy precipitation frequencies, along with consistent decreasing trends in precipitation events with short, medium, and long durations. Furthermore, it is predicted that the relationship between extreme precipitation and temperature will deviate from the Clausius‐Clapeyron (C‐C) relationship toward the double C‐C relationship in the far‐future under RCP8.5, particularly over the southeastern TP. Additionally, there are robust correlations between the intensity‐related EPIs and elevation. This indicates that, at the local scale, the complex topography of the region may play a crucial role in shaping the nonuniform distribution of precipitation extremes by modulating associated upward motion. Plain Language Summary: The Tibetan Plateau (TP) has experienced substantial warming during the past decades, at a rate twice that of the global average due to its unique location and elevated terrain. Warming has significantly changed the amount, intensity, frequency, and extremes of precipitation over the TP. The changes in precipitation would influence the stability of the local ecoenvironment and the development of agriculture and industry directly. Previous studies have shown the big picture of daily precipitation extremes in the future, but the characteristics of precipitation extremes at hourly timescale are unclear. This study simulates the changes in subdaily precipitation extremes in the historical (1980–2005) and future (2006–2099) periods under different climate scenarios (RCP4.5 and RCP8.5). Our results show that the spatiotemporal changes and variability over the western TP, the southern border of TP and the southeastern TP are more dramatic than that over the central TP. The southeastern TP shows higher sensitivity and vulnerability to subdaily precipitation extremes and may experience less frequent precipitation lasting for a shorter duration, but with stronger intensity at hourly timescale. The results of this study can guide adaptive measures and be helpful for long‐term water resource management over the TP. Key Points: The simulated hourly precipitation over the Tibetan Plateau (TP) is characterized by heterogeneity and spatially disparate changesLess frequent, shorter duration, and more intense precipitation over the southeastern and the southern border of the TP are projectedThe distributions of the intensity‐related indices exhibit a dependency on elevation [ABSTRACT FROM AUTHOR]

Climate change research has received increasing attention from both researchers and the public, and the analysis of precipitation is one of the most important topics in this field. As a supplement to gauge observations, satellite-derived precipitation data present advantages, as they have high spatiotemporal resolution and good continuity. The Global Precipitation Measurement (GPM) mission is the newest generation of precipitation measurement products designed to conduct quasi-global satellite observations. This study used the latest Integrated Multi-satellitE Retrievals for GPM data collected between 2001 and 2020 to analyze changes in precipitation amount, frequency, and intensity on global land and ocean surfaces. The results showed that precipitation intensity over the ocean was generally higher than on land, and the two were more similar at the hourly scale than at the daily scale, as shown by the JS divergence statistics: 0.0323 and 0.0461, respectively. This may be due to the thermodynamic differences between land and the ocean, which can accumulate over a longer time scale. The average number of annual precipitation hours and days increased by 50 h and 5 days during 2011–2020 compared with the previous decade. The absence of obvious changes in annual precipitation amounts led to a decrease in annual precipitation intensity and the weakening of extreme precipitation on land. The analysis of precipitation regimes in nine mainland regions of the globe showed a significant increasing trend for both hourly and daily precipitation in North Asia, while insignificant changes or even decreasing trends were detected in the other regions. The results of this study elucidated the variations in precipitation between land and ocean areas and can contribute to the understanding of global precipitation. [ABSTRACT FROM AUTHOR]

Abstract The intensity definition and classification of the extratropical cyclone (EC) are still less studied than the tropical cyclone, due to the relatively ambiguous structure and diverse life cycle of ECs. In this study, a two-dimensional objective cyclone identification method based on outermost closed isolines is used to obtain the EC-related datasets, and the summertime ECs in East Asia are classified by the relationship between ECs of different intensities and the corresponding precipitation. The results show that compared with the cyclone mean depth, central wind and other traditional intensity indicators, the cyclone intensity index that is the maximum product of the EC-associated wind speed and specific humidity, has the highest correlation with the EC-associated maximum precipitation (r = 0.74). To simplify the definition of cyclone intensity index, the vq max within the radius of 300 km from the cyclone center is defined as the cyclone intensity. According to the relationship between EC and precipitation intensity and the precipitation grades in China, the ECs in East Asia are classified into four levels. Accordingly, the EC-associated maximum precipitation increases substantially with the raising of cyclone level. In particular, 32.8% of heavy rain events in East Asia in summer are related to ECs of the strongest category. The results will facilitate a better understanding of the relationship between the strongest category EC and local precipitation.

This study aims to reveal the long-term station-based characteristics of precipitation in Istanbul, a mega city located on the continents of Europe and Asia, with complex topography and coastline along the Marmara and Black Seas. Using data from five different stations, three located in the European continent and two in the Asian continent, with measurement periods ranging from 72 to 93 years, wet and dry days have been identified, statistics on precipitation conditions during the warm and cold seasons have been generated, categorization based on precipitation intensities has been performed, and analyses have been conducted using extreme precipitation indices. At stations located in the northern part of the city, higher annual total precipitation has been observed compared to those in the south. A similar situation applies to the number of wet days. While during the cold season, the wet and dry day counts are nearly the same across all stations, this condition exhibits significant differences in favor of dry days during the warm season. Apart from dry conditions, “moderate” precipitation is the most frequently observed type across all stations. However, “extreme” events occur significantly more often (6%) during the warm season compared to the cold season (2%). Long-term anomalies in terms of annual precipitation totals have shown similarity between stations in the north and south, which has also been observed in longitudinally close stations. Despite the longer duration of the cold season and stronger temperature gradients, extreme rainfall events are more frequent during the warm season, primarily due to thunderstorm activity. While trend analyses revealed limited significant trends in precipitation intensity categories and extreme indices, the study highlights the importance of comprehensive examination of extreme rainfall events on both station-based and regional levels, shedding light on potential implications for regional climate change. Lastly, during the cold season, the inter-station correlation in terms of annual total precipitation amounts has been considerably higher compared to the warm season.

Abstract It is widely known that precipitation is a key variable of the hydrological cycle that is strongly affected by recent climate changes. Therefore, there is a growing interest in research activities focused on alteration of rainfall regime, as it conditions the planning of countermeasures against flood and landslide hazards. The available literature about precipitation tendencies over Italian peninsula offers a limited number of studies about recent changes of extreme events and precipitation intensity. This work aims at adding a contribution to fill this research gap, investigating the changes in rainfall regime observed over the 2002–2021 period in the Campania region (southern Italy). To pursue this aim, a dataset including daily precipitation records collected at 107 stations was analysed both through 11 indices developed by the Expert Team on Climate Change Detection and Indices and through the Standardized Precipitation Index in order to detect signals of changes in extreme events and to assess tendencies towards drier or wetter conditions. The Theil‐Sen method and the Mann–Kendall non‐parametric test were employed to evaluate the trends and their statistical significance. The main results emerging from this work are (i) an increasing tendency in precipitation intensity and in the frequency of occurrence of heavy rainfall events in autumn, mainly in the northern part of the region and in the mountainous areas, (ii) an upward trend of the duration of the longest wet spell in the coastal areas and (iii) an increasing trend of dry spells in spring and in summer in the Gulf of Salerno.

Background: Global climate change has resulted in precipitation regimes exhibiting an increasing trend in rainfall intensity but a reduction in frequency. In addition, nitrogen (N) deposition occurs simultaneously in arid and semi-arid regions. Microbial biomass, diversity, composition, and species interactions are key determinants of ecological functions. We examined the effects of changes in precipitation intensity and N addition on the soil bacterial and fungal communities in a semi-arid grassland in Inner Mongolia, China. Methods: The microbial biomass (bacterial PLFAs and fungal PLFAs) was determined through phospholipid fatty acid (PLFA) analysis, and microbial diversity (Shannon index and evenness index) was determined with high-throughput sequencing (16S and ITS). Species interactions were determined using a molecular ecological network analysis. The relationships between microbial community (bacterial community and fungal community) and environmental variables were examined by Mantel tests. Results: We found that N addition decreased fungal PLFA under moderate, high, and extreme precipitation intensity treatments and increased fungal community complexity under the high precipitation intensity treatment. Furthermore, N addition increased bacterial diversity under moderate and high precipitation intensity treatments. N addition caused greater environmental stress to the fungal community, which was dominated by deterministic processes. Conclusions: The effects of N deposition on soil bacterial and fungal communities were altered by precipitation intensity. The changes in soil bacterial and fungal communities were different, implying that composition and functional traits adapt differently to projected global changes at a regional scale. [ABSTRACT FROM AUTHOR]

This study aims to systematically evaluate the accuracy and applicability of GPM satellite precipitation products (IMERG-E, IMERG-L, and IMERG-F) with varying time lags at different spatial and temporal scales over mainland China. We use quantitative statistical indicators, including correlation coefficient (CC), root mean square error (RMSE), mean absolute error (MAE), mean daily precipitation, probability of detection (POD), false alarm rate (FAR), bias, and equitable threat score (ETS), based on observations from 2419 national gauge sites. The results show that GPM satellite precipitation products perform well in eastern and southern humid regions of China, with relatively poorer performance in western and northern regions in terms of spatial distribution. It reflects the sensitivity of GPM precipitation retrieval algorithm to climate and precipitation type, topography, density, and quality of ground observation across different latitudes. Despite the design of GPM for different forms of precipitation, IMERG products perform the best in summer and the worst in winter, indicating that estimating snowfalls via satellite is still challenging. In terms of precipitation intensity, IMERG products significantly improve performance for light and no rain (POD ≥ 0.7), but errors gradually increase for moderate, heavy, and torrential rain, due to the saturation tendency of satellite echoes. Overall, we comprehensively evaluate the IMERG products, revealing the distinct characteristics at various spatial–temporal scales focusing on rainfall accumulations over mainland China. This study provides an important reference for other similar satellite-based precipitation products. It also helps the parameter optimization of hydrological modelling, especially under extreme precipitation conditions, to enhance the accuracy of flood simulation. [ABSTRACT FROM AUTHOR]

Applying constant precipitation intensity, which does not occur in natural events, is one of the main limitations concerning rainfall simulators in soil erosion studies. The present work evaluated the InfiAsper rainfall simulator operating with a new control panel to program rainfalls with different precipitation intensities (PI). Infiltration rates and soil and water losses were evaluated in a Distrophic Acrisol (clay loam texture) with simulated rainfalls of 30 mm and duration of 40 min, considering advanced (AD), intermediate (IN), delayed (DE), and inverted intermediate (II) patterns, all with PI peaks of 110 mm h−1, and a constant (CT) pattern. The experimental design was in randomized blocks with five treatments (rainfall patterns) and experimental units measuring 2.5 × 2.5 m. The simulator worked satisfactorily, applying the rainfall according to the preconfigured programs. The simulated rainfall with the CT and II patterns did not promote runoff nor soil loss. Infiltration and runoff rates varied according to the applied rainfall pattern, reaching 97.8 and 27.3 mm h−1 (AD), 82.1 and 39.5 mm h−1 (IN), and 76.2 and 49.7 mm h−1 (DE), respectively. Soil loss and surface runoff totaled each 4.77 g m−2 and 3.9 mm (AD), 6.70 g m−2 and 6.8 mm (IN), and 6.03 g m−2 and 7.0 mm (DE). The InfiAsper simulator modified enables varying precipitation intensity besides obtaining satisfactory results in the field and information consistent with the expected characteristics of natural rainfall patterns. In the intermediate and delayed rainfall patterns, soil and water losses are higher than in the advanced.

This study evaluates the representativeness of two widely used next-generation global satellite precipitation estimates data for short-term precipitation over China, namely the satellite data from the Climate Prediction Center morphing (CMORPH) and the satellite data from the Global Precipitation Measurement (GPM) mission. These two satellite precipitation data sets were compared with the hourly liquid in-situ precipitation from China national surface stations from 2016 to 2020. The results showed that the GPM precipitation data has better representativeness of surface short-term precipitation than that of the CMORPH data, and these two quantitative precipitation estimate (QPE) data sets underestimated extreme precipitation. Moreover, we analyzed the influence of the error between two QPE data sets and the in-situ precipitation on the classification of short-term precipitation intensity. China uses 8.1–16 mm/h as the definition of heavy precipitation, but the accuracy of the satellite QPE product was different due to the different lowest threshold of heavy rain (more than 8.1 mm/h or more than 16 mm/h). Increasing the threshold value of the QPE data for short-term strong precipitation resulted in lower accuracy for detecting such events, but higher accuracy for detecting moderate intensity rainfall. When studying short-term strong precipitation over China using precipitation grade, selecting an appropriate threshold was important to ensure accurate judgments. Additionally, it is important to account for errors caused by QPE data, which can significantly affect the accuracy of precipitation grading. [ABSTRACT FROM AUTHOR]

The intensity definition and classification of the extratropical cyclone (EC) are still less studied than the tropical cyclone, due to the relatively ambiguous structure and diverse life cycle of ECs. In this study, a two-dimensional objective cyclone identification method based on outermost closed isolines is used to obtain the EC-related datasets, and the summertime ECs in East Asia are classified by the relationship between ECs of different intensities and the corresponding precipitation. The results show that compared with the cyclone mean depth, central wind and other traditional intensity indicators, the cyclone intensity index that is the maximum product of the EC-associated wind speed and specific humidity, has the highest correlation with the EC-associated maximum precipitation (r = 0.74). To simplify the definition of cyclone intensity index, the vqmax within the radius of 300 km from the cyclone center is defined as the cyclone intensity. According to the relationship between EC and precipitation intensity and the precipitation grades in China, the ECs in East Asia are classified into four levels. Accordingly, the EC-associated maximum precipitation increases substantially with the raising of cyclone level. In particular, 32.8% of heavy rain events in East Asia in summer are related to ECs of the strongest category. The results will facilitate a better understanding of the relationship between the strongest category EC and local precipitation. [ABSTRACT FROM AUTHOR]

The effects of precipitation of varying intensity on the operation of a ship's radar are considered. It is shown that during the propagation of the electromagnetic wave emitted by the antenna of a ship's radar, its energy is absorbed by precipitation. To determine the power loss of an electromagnetic wave due to its absorption by particles of precipitation, the effective absorption area, specific absorption coefficient, and specific effective total scattering area are used. The effective areas of absorption and total scattering depend on the shape of the precipitation particles, their size, state of aggregation, and the length of the electromagnetic wave emitted by the antenna of the ship's radar. The dependence of the effective absorption area on the particle size of precipitation is obtained at two wavelengths of 3 cm and 10 cm, on which the ship's radars operate. A decrease in the tracking range of an object tracked by a ship's radar in the case of rain falling is established compared with the tracking range of an object in clear weather. It is shown that a decrease in the tracking range of an object occurs only with moderate, strong, and very heavy rain. The attenuation of electromagnetic energy in rain with an intensity of 12.5 mm/h at a wavelength of 3 cm is obtained by calculation, which amounted to 24 dB with a length of the falling rain zone of 50 km, as well as with rain with an intensity of 100 mm/h with the same length of the precipitation zone. [ABSTRACT FROM AUTHOR]

Precipitation extremes occurring on consecutive days may be of crucial importance for the formation of extensive and long‐lasting flooding. Changes in such consecutive extreme precipitation (CEP) events between different regions (i.e., dry and wet regions) still remain unclear in China, which may result in different impacts on human livelihoods and ecosystems. Here, the changes in CEP frequency between dry and wet regions of China were studied by utilizing an observation‐based gridded precipitation dataset. We further determined the driving factors of the changes in CEP frequency by separating the effects of precipitation intensification and temporal clustering of daily extreme precipitation. Our results showed that the CEP frequency in dry regions increased faster (9.73%·decade−1) compared with wet regions (1.14%·decade−1) during the last ~60 years. The increasing precipitation intensity primarily (over 90%) resulted in the increases of CEP events. However, changes in the temporal clustering of daily extreme precipitation can benefit the effects of the changes in precipitation intensity in dry regions but can reverse these effects in wet regions. In dry regions, the regression relationship of precipitation intensity and temperature (7.38%·°C−1) was stronger than that in wet regions (3.44%·°C−1), suggesting that the same magnitude of warming would cause greater precipitation intensity and consequently cause more frequent CEP events in dry regions. Therefore, as the intensification of precipitation and the increasing temporal clustering of daily extreme precipitation, more CEP events may increase the flooding risk in dry regions over China with a stronger warming signal. [ABSTRACT FROM AUTHOR]

The spatiotemporal dynamic of rainfall erosivity is essential for environmental studies and guidance to control erosion. The purpose of this study is to assess rainfall erosivity (monthly and annual), testing machine learning algorithms aided by a covariate bank for spatial prediction of rainfall erosivity in Southeastern Brazil. The modeling tested Random Forest-RF, Cubist, Support Vector Machine, Earth, and Linear Model, associated with 154 covariates (topographic, climatic, and vegetation data). However, we apply the cut-off correlation function (findcorrelation) and feature selection algorithm (Recursive Feature Elimination—RFE) to select strong covariates. Our results show that the RF algorithm was more efficient in modeling (R² values between 0.29 and 0.82), whit the best metrics in the low rainfall period (winter). The modeling showed fluidity by selecting only 43 significant covariates due to the findcorrelation and RFE functions. The most important and frequent covariates in spatial modeling were coordinates, water deficit, topographical, and climatic data. In general, the spatial results show that the dynamics of rainfall erosivity is strongly affected by factors of air mass circulation, relief, and geographic position. Our approach is promising as it is a method capable of estimating rainfall erosivity in unsampled areas, capturing information from significant spatial covariates. [ABSTRACT FROM AUTHOR]

The IMERG V06 hourly rainfall product at daily and hourly scales was evaluated during the warm season (May to September) from 2015 to 2020 using 651 high-quality rain-gauge stations over the Tibetan Plateau (TP). Based on hourly observed rain-gauge precipitation, four categories were classified: light rainfall (0–12 mm·d−1), moderate rainfall (12–20.1 mm·d−1), torrential rainfall (20.1–32.2 mm·d−1), and extreme torrential rainfall (>32.2 mm·d−1). Precipitation frequency and intensity were calculated to further validate the accuracy and suitability of the IMERG estimated-precipitation product. At the daily scale, IMERG underestimated the number of days with less than moderate rainfall, but overestimated the frequency of torrential and extreme torrential rainfall. IMERG estimated the main characteristics of precipitation frequency at different daily precipitation amount levels better than the precipitation intensity, but its best estimate was at the moderate rainfall level, with the highest correlation coefficient (0.69) and the lowest root mean square error (0.17). At the hourly scale, IMERG underestimated the hourly precipitation amount mainly between the early morning and midday (the average deviation was 0.019 mm·h−1) and overestimated it between the afternoon and late night (the average deviation was 0.047 mm·h−1). IMERG overestimated precipitation frequency and underestimated precipitation intensity between the afternoon and the evening, which means that this analysis shows that IMERG estimated more precipitation hours than the observation and underestimated precipitation intensity. These results further our understanding of the suitability of the IMERG precipitation products over the TP and further improve the IMERG retrieval algorithm to better apply the corresponding precipitation product to light and extreme rainfall over regions with complicated topography.

Rainfall simulators are important pieces of equipment to investigate hydrological processes and soil erosion. Here, we investigated the operational characteristics, the rainfall characteristics, and the soil erosion process under collecting plots and rainfall patterns using the InfiAsper simulator. We evaluated the standard plot of the simulator in a rectangular shape (1.0 × 0.7 m), as well as a circular plot (0.8 m diameter), and four precipitation patterns, characterized as advanced (AV), intermediate (IN), delayed (DL), and constant (CT). In the laboratory, uniformity and water consumption tests were carried out for shutter-disk rotations from 138 to 804 rpm, and in the field, simulated rains were applied on a Dystric Acrisol. Rains with different patterns were simulated and presented a uniformity coefficient above 83% for the circular plot and 78.2% for the rectangular plot. The soil erosion varied as a function of the precipitation patterns and, to a lesser extent, according to the shape of the experimental plot. However, runoff and soil loss in AV were 2.1 and 3.5 times greater when using a circular plot. Concerning IN and DL, the length of the rectangular plot may have influenced the formation of small furrows throughout most of the simulated rainfall event, providing greater runoff (13.1 mm) and soil loss (13.6 g m−2). The results obtained are promising, but plots with different shapes associated with rainfall patterns simulated by InfiAsper must be evaluated in other classes and soil use and cover conditions.

Application potential and development prospect of satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) have promising implications. This study discusses causes of spatiotemporal differences on GPM data through the following steps: Initially, calculate bias between satellite-based data and rain gauge data of Xiangjiang river catchment to assess the accuracy of GPM (06E, 06 L, and 06F) products. Second, total errors of satellite precipitation data are divided into hit bias (HBIAS: precipitation detected by both GPM and rain gauge station), missed precipitation (MBIAS: precipitation detected only by rain gauge station), and false precipitation (FBIAS: precipitation detected only by GPM). Third, evaluate the impact of precipitation intensity and total precipitation on accuracy of GPM data and their influence on three error components. Several conclusions are drawn from the results above. (1) Satellite-based precipitation measurements perform better on a larger temporal-spatial scale. (2) The accuracy of TRMM and GPM data displays significant variances on space and time. Season, precipitation intensity, and total precipitation are main factors influencing the accuracy of TRMM and GPM data. (3) The detection capability of satellite products change with seasonal variation and different precipitation intensity level. HIGHLIGHTS GPM products have wider spatial coverage, higher temporal and spatial resolution than TRMM products.; GPM products are more in line with the data requirements of hydrological simulation and forecast.; Evaluate accuracy of different GPM products in precipitation measuring, including early, late and final products.; Assess the improvement of GPM products comparing with its predecessor, TRMM.;

Climate change research has received increasing attention from both researchers and the public, and the analysis of precipitation is one of the most important topics in this field. As a supplement to gauge observations, satellite-derived precipitation data present advantages, as they have high spatiotemporal resolution and good continuity. The Global Precipitation Measurement (GPM) mission is the newest generation of precipitation measurement products designed to conduct quasi-global satellite observations. This study used the latest Integrated Multi-satellitE Retrievals for GPM data collected between 2001 and 2020 to analyze changes in precipitation amount, frequency, and intensity on global land and ocean surfaces. The results showed that precipitation intensity over the ocean was generally higher than on land, and the two were more similar at the hourly scale than at the daily scale, as shown by the JS divergence statistics: 0.0323 and 0.0461, respectively. This may be due to the thermodynamic differences between land and the ocean, which can accumulate over a longer time scale. The average number of annual precipitation hours and days increased by 50 h and 5 days during 2011–2020 compared with the previous decade. The absence of obvious changes in annual precipitation amounts led to a decrease in annual precipitation intensity and the weakening of extreme precipitation on land. The analysis of precipitation regimes in nine mainland regions of the globe showed a significant increasing trend for both hourly and daily precipitation in North Asia, while insignificant changes or even decreasing trends were detected in the other regions. The results of this study elucidated the variations in precipitation between land and ocean areas and can contribute to the understanding of global precipitation.

Groundwater is increasingly important for satisfying California's growing fresh water demand. Strategies like managed aquifer recharge (MAR) can improve groundwater supplies, mitigating the negative consequences of persistent groundwater overdraft. Distributed stormwater collection (DSC)-MAR projects collect and infiltrate excess hillslope runoff before it reaches a stream, focusing on 40-400 ha drainage areas (100-1000 ac). We present results from six years of DSC-MAR operation-including high resolution analyses of precipitation, runoff generation, infiltration, and sediment transport-and discuss their implications for regional resource management. This project generated significant water supply benefit over six years, including an extended regional drought, collecting and infiltrating 5.3 × 105 m3 (426 ac-ft). Runoff generation was highly sensitive to sub-daily storm frequency, duration, and intensity, and a single intense storm often accounted for a large fraction of annual runoff. Observed infiltration rates varied widely in space and time. The basin-average infiltration rate during storms was 1-3 m/d, with point-specific rates up to 8 m/d. Despite efforts to limit sediment load, 8.2 × 105 kg of fine-grained sediment accumulated in the infiltration basin over three years, likely reducing soil infiltration capacity. Periodic removal of accumulated material, better source control, and/or improved sediment detention could mitigate this effect in the future. Regional soil analyses can maximize DSC-MAR benefits by identifying high-infiltration capacity features and characterizing upland sediment sources. A regional network of DSC-MAR projects could increase groundwater supplies while contributing to improved groundwater quality, flood mitigation, and stakeholder engagement.