Total Amount Of Precipitation Research Articles

Analyzing the Spatiotemporal Changes in Climatic Extremes in Cold and Mountainous Environment: Insights from the Himalayan Mountains of Pakistan

This study assessed the past changes in extreme precipitation and temperature events across the Himalayan Mountains of Pakistan. This cold and mountainous environmental region has witnessed a significant increase in climate-related disasters over the past few decades. Spatiotemporal changes in extreme temperature and precipitation events were analyzed using 24 indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this study, in situ data of 16 national meteorological stations were obtained from the Pakistan Meteorological Department (PMD) for the past three decades (1991–2020). The significance of the trends was assessed using the modified Mann–Kendall (MMK) test, and the Theil–Sen (TS) slope estimator was used to estimate the slope of the trend. The results showed that there has been a consistent decline in the total precipitation amount across the Himalayan Mountains of Pakistan. The trend exhibited a decrease in the annual average precipitation at a rate of −6.56 mm/year. Simultaneously, there was an increasing trend in the annual average minimum and maximum temperatures at rates of 0.02 °C/year and 0.07 °C/year, respectively. The frequencies of consecutive wet days (CWDs) and maximum 5-day precipitation (RX5day) have decreased significantly, with decreasing rates of −0.40 days/year and −1.18 mm/year, respectively. The amount of precipitation during very wet days (R95p) and extremely wet days was decreased by −19.20 and −13.60 mm/decade, respectively. The warm spell duration (WSDI) and the frequency of warm days (TX90p) across the Himalayan Range both increased by 1.5 and 1.4 days/decade. The number of cold days (TX10p) and cold nights (TN10p) decreased by 2.9 and 3.4 days/decade. The average temperature of the hottest nights (TXn) and the diurnal temperature range (DTR) were increased by 0.10 and 0.30 °C/decade. The results indicated an increasing tendency of dry and warm weather in the Himalayan region of Pakistan, which could have adverse consequences for water resources, agriculture, and disaster management in the country. Therefore, it is essential to prioritize the implementation of localized adaptation techniques in order to enhance sustainable climate resilience and effectively address the emerging climate challenges faced by these mountainous regions.

Breaking Rossby waves drive extreme precipitation in the world’s arid regions

More than a third of the world’s population lives in drylands and is disproportionately at risk from hydrometeorological hazards such as drought and flooding. While weather systems governing precipitation formation in humid regions have been widely explored, our understanding of the atmospheric processes generating precipitation in arid regions remains fragmented at best. Here we show, using a variety of precipitation datasets, that Rossby wave breaking is a key atmospheric driver of precipitation in arid regions worldwide. Rossby wave breaking contributes up to 90% of daily precipitation extremes and up to 80% of total precipitation amounts in arid regions equatorward and downstream of the midlatitude storm tracks. The relevance of Rossby wave breaking for precipitation increases with increasing land aridity. Contributions of wave breaking to precipitation dominate in the poleward and westward portions of arid subtropical regions during the cool season. Our findings imply that Rossby wave breaking plays a crucial role in projections and uncertainties of future precipitation changes in societally vulnerable regions that are exposed to both freshwater shortages and flood hazards.

Projected near-future changes in precipitation extremes over Anambra-Imo River Basin inferred from CMIP6 HighResMIP

The southeastern region of Nigeria is susceptible to flood disasters primarily triggered by extreme precipitation with localized impacts. This study uses the output of High-Resolution Model Intercomparison Project (HighResMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to investigate seasonal dependent changes in precipitation extremes in the near future (2031–2050) in the Anambra-Imo River Basin, in the southeastern region of Nigeria. Evaluating the models against observation for the 1995–2014 period, it is found that models reproduced the spatial pattern of the observed annual precipitation extremes over the river basin. Results show that in the near future, annual precipitation extremes will be characterized by a robust increase in annual total precipitation amount (PRCPTOT), maximum 5-day precipitation (RX5day), and heavy precipitation (R10mm). The models project a significant increase in PRCPTOT, RX5day, R10mm, and wet-day intensity (SDII) for the June–July–August (JJA) and September–October–November (SON) seasons. The results demonstrate a robust and higher magnitude increase in precipitation extremes during the SON season. Specifically, PRCPTOT, RX5day, R10mm and SDII are projected to increase by up to 46 mm, 24 mm, 1.2 days and 2.4 mm/day, respectively. Whereas during the March–April-May (MAM) season, the HighResMIP suggests that PRCPTOT, R10mm, and SDII will marginally increase over the eastern part of the Anambra-Imo River Basin. Besides, the December–January–February (DJF) season will be characterized by a marginal increase in the precipitation extremes, especially over the southern fringes of the river basin. We note that in the near future, precipitation extremes in the river basin will be characterized by more intense and less frequent precipitation extremes during the JJA and SON, potentially exacerbating flash flooding in the river basin. Hence, the results of this study may be vital for near-term socio-economic planning and policy decisions that will minimize the impact of flood disasters in the Anambra-Imo River Basin.

A Quality Control System for Historical In Situ Precipitation Data

ABSTRACT In this study, a comprehensive quality control (QC) system for in-situ precipitation data records was developed and applied to Canadian in situ precipitation datasets. The system includes a pair of screening procedures to screen for two types of random errors: one procedure is applied to the untransformed monthly total precipitation data series, which is good at finding erroneous data of unusually large values; another is applied to the log-transformed monthly precipitation data (in mm) series, log(P + 0.1), which is good at identifying erroneous zero or near-zero monthly total precipitation amounts. The system then applies three QC (threshold, kriging, and temporal) tests and a decision-making process to confirm whether the screened suspects are erroneous. There is generally good agreement between all the QC tests, while the decision-making process yields the most accurate results when compared to the manually reviewed results. The QC work on Canadian precipitation data sets revealed that it is necessary to apply a pair of screening procedures to identify both types of random errors. All the monthly values identified to be erroneous are set to missing, and so are the corresponding daily values, while keeping records of the original data.

Changes in precipitation phases based on the multi-discrimination method in the Tibetan Plateau

Global warming is rapidly changing the precipitation structure, and the shift in precipitation phases is even more pronounced in the Tibetan Plateau (TP), a region sensitive to global climate change. The accuracy of precipitation phase discrimination is essential for studying precipitation variability. Based on the observed data from 112 meteorological stations in the study area obtained from the China Meteorological Administration (CMA) and the National Climatic Data Center (NCDC) before 1980, we compared and assessed six methods for distinguishing precipitation phases and the optimal method was determined to complete the precipitation phase data after 1980 in the study area. Subsequently, the changes in precipitation amount, intensity, and frequency were analyzed by classifying them into light, moderate, heavy, and extreme precipitation using the percentile threshold discrimination method. It found that the dynamic threshold temperature method (presented by Ding et al., 2014) was the most effective to distinguish precipitation phases in the TP, and its performance was further improved from 80.9% to 86.1% after using frequency intersection and probability guarantee methods. Precipitation was mainly concentrated in July. Meanwhile, the proportion of snowfall to total precipitation (S/P) was approximately 9%. From 1961 to 2020, the amount of total precipitation, rainfall and snowfall in the TP exhibited increasing trends, while the sleet demonstrated a persistent decline. Spatial and temporal heterogeneity existed in the changes of precipitation of different phases. The average single precipitation amount increased. Moreover, the changes in the amount and frequency of extreme precipitation were more pronounced. Increased frequency and amount of both rainfall and snowfall were distributed in the central and eastern parts of the study area with a more significant proportion. In contrast, the peripheral areas witnessed a decrease. The spatial distribution of frequency and amount of different precipitation intensities was comparable to that of the total precipitation. This study offers novel procedure into changes of precipitation phases at high altitudes, which will inform future research on climate change and water resource management.

Projecting Climate Change Impact on Precipitation Patterns during Different Growth Stages of Rainfed Wheat Crop in the Pothwar Plateau, Pakistan

In rainfed areas, precipitation variations directly impact wheat growth stages such as emergence, tillering, jointing and booting, and maturity. Evaluating the impact of climate change on precipitation patterns during these critical growth stages is crucial for adapting climate change and ensuring global food security. In this study, projections of five General Circulation models (GCMs) under two shared socioeconomic pathways (SSPs) were used to predict the changing characteristics of precipitation during four main growth stages of wheat in the rainfed region of the Pothwar Plateau, Pakistan. Historical datasets of daily precipitation at six weather stations were analyzed to check the past changes in the precipitation patterns. During the baseline period (1985–2014), the annual average precipitation decreased at a rate of −9.75 mm/decade, while the amount of precipitation during the rabi season (wheat-growing season) decreased at a rate of −20.47 mm/decade. An increase in the precipitation was found during the fourth (flowering) stage of crop growth, while the first three stages experienced a decrease in the precipitation amount. The multimodal ensembled data, under the SSP2-4.5 scenario, revealed a significant decline (at the rate of −16.63 mm/decade) in the future annual precipitation. However, it is projected that, under SSP2-4.5, there may be a slight increase (4.03 mm/decade) in the total precipitation amount during the future rabi season. Under the SSP5-8.5 scenario, average annual precipitation exhibited a slightly increasing trend, increasing by 1.0 mm/decade. However, during the rabi season, there was a possibility of a decrease in precipitation amount, with a rate of 11.64 mm/decade. It is also expected that the precipitation amount may vary significantly during the crown root initiation, jointing and booting, and flowering stages in the near future. These results provide a framework for the planning of wheat production in the Pothwar region of Pakistan, taking into account the potential impact of shifting weather patterns, particularly in terms of uneven precipitation.

Projection of Changes in Rainfall and Drought Based on CMIP6 Scenarios on the Ca River Basin, Vietnam

In this study, future precipitation and drought in the Ca river basin, Vietnam, were projected based on an ensemble of 27 CMIP6 models for four climate change scenarios. The impact of climate change on precipitation and drought was investigated. Monthly precipitation observation data were adjusted using the bias correction method. To detect drought events, the Standard Precipitation Index (SPI) was employed. Changes in drought were assessed using SPI3, SPI6, and SPI12. Although the amount of annual total precipitation slightly increased, the drought events may become more severe. There is a high likelihood of increased drought intensity and severity in Vietnam due to climate change. The frequency of droughts is likely to change depending on the location and climate change scenario. We found that the frequency and severity of droughts may be altered depending on the window size of SPI. The short-term drought events will be more frequent and severe, and long-term drought events will become more severe in the Ca river basin.

Assessment of two approaches for very short range precipitation prediction for a convection-dominant period at different scales

Extreme precipitation plays a crucial role in managing weather-related risks, particularly flooding, and has a significant impact on various sectors such as hydrology, agriculture, and economy. It is important to evaluate precipitation forecast outputs to help refining prediction models, especially for heavy events. This study examines the performance of two weather models, both designed to provide frequently updated forecasts for a short time range, but using different approaches: extrapolation-based and fully dynamical 3D numerical weather prediction (NWP) models. These models are assessed over a two-month period with several heavy thunderstorms, using data from Austria and a smaller catchment in southeast Austria. We addressed the errors and uncertainties in these models using different verification metrics and two different observational datasets. In general, both models performed well in the first hour of the forecast at both large and small scales. However, performance decreased with lead time after the first hour, with a faster decline in the extrapolation-based model. The performance of the models changed when considering different precipitation thresholds. For higher thresholds (heavier precipitation), the NWP model performed better than the extrapolation-based model, whereas it performed worse for lower thresholds. When using the object-oriented Structure Amplitude Location (SAL) metric, the dynamical NWP model performed better regarding the structure of precipitation, while the extrapolated-based model had a better performance when considering the amplitude parameter, i.e., the total amount of precipitation. With a lower error in the first hours of each run, the dynamical NWP model showed that an hourly update cycle helps to reduce the forecast errors noticeably. The results highlight the need of considering forecast model performance at different intensity thresholds and spatial scales.

Intra‐annual radial growth of Quercus acutissma and its response to hydrometeorological factors in the Nandadish experimental catchment, eastern China

AbstractInvestigating the relationship between tree growth within a year and environmental factors is crucial for understanding how climate change affects seasonal tree growth patterns. In this study, high‐resolution point dendrometers were used to monitor the stem radial changes of Oak trees (Quercus acutissma) over two years (2020 and 2021) in the eastern subtropical monsoon region of China. We find that the main growth period of Oak trees spans from March to September, and air temperature significantly affects the growth onset of Oak trees but with no clear impact on their growth cessation. The observations show that precipitation substantially affects daily stem radial increment (SRI), but the frequency of precipitation days plays a more crucial role in enhancing seasonal growth than the total precipitation amount. In the growing season, the stem radius of the Oak trees shows obvious diurnal cycles with shrinkage during the day and expansion at night, reflecting a delicate balance between canopy water loss and soil water absorption. The diurnal variations of the stem radius during the cold period (January and December) show an opposite pattern to that of the growing season, due to the sap's freezing under the condition of low air temperature at night as well as no or weak transpiration in the daytime. Because the temporal dynamics and intensity of tree activities significantly affect the timing and mechanisms of carbon assimilation in terrestrial ecosystems, our results are helpful to evaluate the carbon sequestration capacity of subtropical forests under the global climate change.

Generating synthetic rainfall fields by R‐vine copulas applied to seamless probabilistic predictions

AbstractMany post‐processing methods improve forecasts at individual locations but remove their correlation structure. However, this information is essential for forecasting larger‐scale events, such as the total precipitation amount over areas like river catchments, which are relevant for weather warnings and flood predictions. We propose a method to reintroduce spatial correlation into a post‐processed forecast using an R‐vine copula fitted to historical observations. The method rearranges predictions at individual locations and ensures that they still exhibit the post‐processed marginal distributions. It works similarly to well‐known approaches, like the “Schaake shuffle” and “ensemble copula coupling.” However, compared to these methods, which rely on a ranking with no ties at each considered location in their source for spatial correlation, the copula serves as a measure of how well a given arrangement compares with the observed historical distribution. Therefore, no close relationship is required between the post‐processed marginal distributions and the spatial correlation source. This is advantageous for post‐processed seamless forecasts in two ways. First, meteorological parameters such as the precipitation amount, whose distribution has an atom at zero, have rankings with ties. Second, seamless forecasts represent an optimal combination of their input forecasts and may spatially shifted from them at scales larger than the areas considered herein, leading to non‐reasonable spatial correlation sources for the well‐known methods. Our results indicate that the calibration of the combination model carries over to the output of the proposed model, that is, the evaluation of area predictions shows a similar improvement in forecast quality as the predictions for individual locations. Additionally, the spatial correlation of the forecast is evaluated with the help of object‐based metrics, for which the proposed model also shows an improvement compared to both input forecasts.

The impact of aerosols as ice nucleating particle on microphysics and electrification in the cumulus model

Here, a heterogeneous ice nucleation parameterization associated with aerosol acting as ice nucleating particle (INP) was implanted into a two-dimensional numerical cumulus model. To explore the impact of INP on microphysical and electrical processes, a comparison was conducted with the original approach, which employs an empirical formula. Simulation results indicate that INP greatly impacted microphysical evolution in the heterogeneous ice nucleation process, reducing total liquid precipitation amounts and causing a slight precipitation delay, as well as increasing the diameter and mixing ratio of ice crystals and the expansion of the vertical distribution of ice crystals. This led to a notable change in electrification in thunderstorms. The increase of ice crystal diameter was the dominant contributor to the enhancement of electrification using the new parameterization. Additionally, unlike the structure of thunderclouds in a mature stage, which always retains a normal dipole structure adopting the empirical formula, a tripole structure developed a lower positive charge, and the polarity inversion with upper negative and lower positive charges occurred when the new parameterization was adopted. This predominately was the result of abundant ice crystals present below the reversal temperature. The electrification characteristics of thunderstorms may have a close connection with lightning activity. It has been found that charge structure changed significantly in the two cases, with the tripolar charge structure facilitating the production of inverted intra-cloud (IC) flashes and negative Cloud-to-ground (CG) flashes simulated by the new parameterization; additionally, clouds simulated using the empirical formula may be able to develop normal IC lightning and positive CG flashes. Therefore, it will be very meaningful to obtain greater insight into the characteristics of thunderstorms electrification in cumulus model with aerosols.

Exploring Spatio-Temporal Precipitation Variations in Istanbul: Trends and Patterns from Five Stations across Two Continents

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.

Climate change impacts on precipitation and water resources in Northwestern China

A statistical analysis is conducted on the hourly precipitation at 105 national meteorological stations in the Xinjiang region of China from 2011 to 2020. The purpose of this analysis is to determine the total quantity of precipitation during the warm and cold seasons, as well as the precipitation frequency at each station. The results of the analysis indicate that there is a more pronounced inter-annual variation in precipitation during the warm and cold seasons in Xinjiang, where the total amount of precipitation during the warm season is significantly higher than that during the cold season, with the warm season experiencing at least twice as much precipitation. In terms of the inter-annual incremental amount of precipitation, both the warm and cold seasons exhibit a trend of increasing and then decreasing over the years. However, the curvature change is more prominent in the cold season compared to the warm season, suggesting that the inter-annual variation in precipitation during the warm season remains relatively stable. The spatial distribution characteristics of the total precipitation in Xinjiang indicate that warm-season precipitation is more scattered, while cold-season precipitation is mainly concentrated in the northern region of the territory. This pattern holds true at low, medium, medium–high, and high altitudes. The cumulative precipitation during the warm season is always higher than that in the cold season, and this difference becomes more prominent with increasing altitude. This indicates that warm-season precipitation in Xinjiang is closely related to its complex topographic structure, particularly the convective weather generated by topographic clouds. On the other hand, precipitation in the cold season is mainly concentrated in the low- and medium-altitude stations, and there is not much correlation between precipitation and altitude. Precipitation is mainly affected by the mesoscale and the direct influence of large-scale weather systems. Analysis of precipitation in extreme moments reveals that during the warm season, extreme precipitation events occur mainly from the evening to early morning (19:00–03:00 the next day), accounting for 75.24% of the 105 stations. In contrast, during the cold season, extreme precipitation events occur between 03:00 and 18:00, corresponding to 74.29% of the stations. The relationship between precipitation and altitude differs in the warm and cold seasons. In the warm season, there is a linear relationship between precipitation and altitude, with a slope of 0.72 and a correlation coefficient of 0.52, indicating that precipitation increases with increasing altitude. However, in the cold season, the linear relationship between precipitation and altitude is very inconspicuous, with a slope of −0.05 and a correlation coefficient of −0.05, suggesting that there is no significant relationship between precipitation and altitude during this season. These findings provide valuable insights into the changing patterns of precipitation gradients at different altitudes and seasons in Xinjiang. This information can be used for the site selection of smokestack operations in high-altitude areas and for ground and air weather modification operations in low-altitude areas. Additionally, these data contribute to the understanding of precipitation patterns in Xinjiang, further improving the effectiveness of weather modification efforts and increasing the utilization of airborne water resources.

Impact of Rainfall on the Detection Performance of Non-Contact Safety Sensors for UAVs/UGVs.

This study comprehensively investigates how rain and drizzle affect the object-detection performance of non-contact safety sensors, which are essential for the operation of unmanned aerial vehicles and ground vehicles in adverse weather conditions. In contrast to conventional sensor-performance evaluation based on the amount of precipitation, this paper proposes spatial transmittance and particle density as more appropriate metrics for rain environments. Through detailed experiments conducted under a variety of precipitation conditions, it is shown that sensor performance is significantly affected by the density of small raindrops rather than the total amount of precipitation. This finding challenges traditional sensor-evaluation metrics in rainfall environments and suggests a paradigm shift toward the use of spatial transmittance as a universal metric for evaluating sensor performance in rain, drizzle, and potentially other adverse weather scenarios.

Rice mutants, selected under severe drought stress, show reduced stomatal density and improved water use efficiency under restricted water conditions.

Rice is among the least water-use-efficient crops, and rice plants utilise most of their water uptake for transpirational cooling via stomata. To improve water-use efficiency (WUE) in rice, reducing stomatal density and size could help optimise transpiration and photosynthesis. In this study, we compared two series of purple rice stomata mutants: the Stomatal Model Mutant (SMM) identified by microscopic observation of flag-leaf stomata, and the Drought-selected Model Mutant (DMM) generated through screening under severe water stress. After undergoing two rounds of severe water stress between -60 to -80 Ym, right before the R1-2 reproductive stage, three DMMs were selected based on their rapid recovery rate and % filled-grain percentage. The three DMMs displayed 618-697 stomatal units per mm2, similar to the SMMs low-density stomata mutant (JHN 8756 (LD)). Furthermore, the four SMMs, three DMMs and the Jao Hom Nin wild type (JHN WT) were treated with two restricted water condition schemes from seedlings to harvest. The total amount of irrigation and precipitation during the experiment was 78.1 L/plant (69.1 mm/plant) for the less restricted water condition (LR) and 47.5 L/plant (42 mm/plant) for the more restricted water condition (MR). Water condition treatments had no effects on stomatal density and stomatal index. In contrast, genotypes and restricted water condition schemes affected plant height, tillers/plant, % filled grains and shoot dry weight (SDW). The three DMMs and the JHN 8756 (LD), the SMM's low-density stomata mutant, displayed greater resilience towards more restricted water conditions than the SMMs and the JHN wild type. Particularly, DMMs were tolerant to more restricted water condition treatments, showing no SDW penalties. Together, the DMMs and the JHN 8756 (LD) displayed higher WUE under these conditions of more restricted water conditions. A rigorous screening process to distinguish tolerant mutants with a rapid drought recovery rate from severe water stress could pave the way to isolate more mutants with better stomatal functionality and resilience in preparation for imminent climate changes.

The Effect of Convective/Advective Precipitation Partitions on the Precipitation Isotopes in the Monsoon Regions of China: A Case Study of Changsha

Abstract Convective/advective precipitation partitions refer to the divisions of precipitation that are either convective or advective in nature, relative to the total precipitation amount. These distinct partitions can have a significant influence on the stable isotope composition of precipitation. This study analyzed and compared the effect of precipitation partitions on δ18O in precipitation (δ18Op) by using daily precipitation stable isotope data from Changsha station and monthly precipitation stable isotope data from the Global Network of Isotopes in Precipitation (GNIP), under different time scales, time intervals (i.e., annual, warm season, and cold season), and precipitation intensities. The results showed that the correlation between the convective precipitation fraction (CPF) and total precipitation amount was influenced by the intensity of convection in different time intervals. On both the daily and monthly scales, the CPF decreased as the precipitation amount increased in the warm season, while it increased with increasing precipitation amount in the cold season. Regardless of the season, daily δ18Op at Changsha station consistently increased with an increase in daily CPF. On a daily scale, the effect of convective activity on δ18Op was stronger than that of the “precipitation amount effect” in the cold season, as compared to the situation in the warm season. As a result, the regression line slope between δ18Op and CPF increased with increasing precipitation intensity in the warm season, meaning that as the CPF increased, the δ18Op increased at a faster rate under higher precipitation intensity. Similarly, the slope increased with increasing precipitation intensity in the cold season. This suggests that precipitation intensity and convection intensity can affect the relationship between δ18Op and CPF. Our findings shed light on how different precipitation partitions affect stable isotope composition of precipitation, thus enhancing our understanding of the variability of precipitation stable isotopes in the monsoon regions of China. Significance Statement This study aims to better elucidate the influence of different precipitation partitions on precipitation stable isotopes. In the eastern monsoon region of China, stable isotopes in precipitation showed a robust positive relationship with convective precipitation faction. On a daily scale, the convective activity enhanced the influences of the “precipitation amount effect” on precipitation stable isotopes in the warm season and reduced such influences in the cold season. These results improve our understanding of stable isotopic variability of precipitation in the eastern monsoon region, China.

Bрожайність ранньостиглих сортів картоплі за впливу природно-кліматичних умов західного лісостепу

Agriculture remains a key branch of the economy, ensuring food security and the production of important types of raw materials, but due to the fact that predictive assessments demonstrate the negative impact of climate change on the yield of agricultural crops, there is a need to modernize existing models of agricultural production and improve methods of managing agricultural systems with taking into account climate change. The issues of optimization of obtaining high productivity of potatoes, in certain regions, should first of all be aimed at the rational use of natural and climatic conditions of the year, with the aim of timely revision of the cultivation technology, which would correspond to the most complete realization of the agro-climatic potential of the research area, namely the Western Forest-Steppe. Solving this task depends on the degree of study of the interaction and interdependence of the influence of natural and climatic conditions on the processes of formation of yield and quality of potatoes. The results of the analysis of weather and climate conditions in the Western Forest-Steppe during 2010-2023 and their impact on the yield of early-ripening potato varieties are presented. It was investigated that the meteorological conditions in some years fluctuated sharply in comparison both to previous years and to the average long-term data. This is especially true about the total amount of precipitation and its distribution during the potato growing season, because with regard to the dynamics of the temperature regime, as already noted, a significant increase has been observed. Despite this during the potato growing season the temperature and water conditions provided favorable conditions for obtaining a high yield of early-ripening potato varieties. The presented results of the analysis of weather and climate conditions in the Western Forest-Steppe during 2010-2023 indicate a positive effect on the yield of potato varieties of the early-ripening group. It was established that the weather and climatic conditions of the research area favor the cultivation of potato varieties of the early-ripening group, and the yield compared to the standard variety increased by 0.9-5.2 t/ha. The conducted analysis makes it possible to select the most productive potato varieties of the early-ripening group, which are the most optimal for cultivation in the conditions of the Western Forest-Steppe of Ukraine as well as further study and improvement regarding the formation of their productivity

A 131-year evidence of more extreme and higher total amount of hourly precipitation in Hong Kong

Based on the observations of hourly precipitation for 131 years from Hong Kong Observatory Headquarters, this study examined the long-term changes in the characteristics of hourly precipitation extremes in terms of intensity, total precipitation amount, duration, and frequency. Results show that the hourly precipitation extremes have significantly intensified by 29%–38% from 1885 to 2022. The 131-year observations evidence that the more extreme the hourly precipitation is (i.e. higher percentiles), the faster the increasing rate it has. Specifically, the magnitudes of hourly precipitation with the 95th, 97.5th, 99th, and 99.9th percentiles increased by rates of 0.03 mm, 0.05 mm, 0.07 mm, and 0.12 mm per year, respectively. Through the secular trend analysis, we found that only the maximum intensity of extreme precipitation events (i.e. events with maximum intensity exceeding the 95th percentiles) shows a significant increasing trend during 1885–2022, while the trends in the total precipitation amount, duration, and mean intensity are not significant. However, by comparing the percentile bin values between three sub-periods of the 131-year record, we found a significant rise over time in the total precipitation amount, mean intensity, and maximum intensity of extreme precipitation events with different intensities (i.e. 95th, 96th, 97th, 98th, and 99th percentiles), while the change in the duration is not significant. The analysis of the frequency of precipitation events shows significant increases in the proportion of extreme precipitation events during 1885–2022. The observations of 53 stations across Hong Kong from 1986 to 2022 show significant intensification and increasing frequency in the hourly precipitation extremes in most areas of Hong Kong. Meanwhile, the precipitation duration shows a decreasing tendency, which may explain the insignificant changes in the total precipitation amount. These findings provide important insights into the longer-term variations in the characteristics of hourly precipitation extremes.

Reconstructing Historical Intense and Total Summer Rainfall in Central North Carolina Using Tree-Ring Data (1770–2020)

Contextualizing historic hydroclimate variability in the southeastern USA has relied significantly on proxy indicators such as tree-ring data, and while previous studies have reconstructed total precipitation, less is known about the historic variability of intense rainfall events, which are climatologically and ecologically important and distinct from non-intense rainfall events. Here, a combined longleaf pine and shortleaf pine adjusted latewood chronology spanning 1770–2020 was used to reconstruct July–September total precipitation and intense rainfall event precipitation in central North Carolina, USA. The adjusted latewood chronology explains 46% of the variance in July–September total precipitation and 37% of the variance in July–September intense rainfall event precipitation during the 1940–2020 instrumental period with intense rainfall event precipitation amounts comprising 52% of total precipitation amounts. The models provide context about historic hydroclimate variability at this location and suggest overall stability in both total and intense rainfall event precipitation amounts during the instrumental and reconstruction periods with three identical significant regime shifts during 1770–2020: 1770–1935, 1936–1959 (above-average moisture), 1960–2020 (below-average moisture). To compare model strength, the models were split into early (1940–1980) and late (1981–2020) analysis periods with the intense rainfall event precipitation model exhibiting greater skill during the early analysis period. The early analysis period has a greater frequency and magnitude of intense rainfall events, and these results suggest the influence of intense rainfall event precipitation on latewood growth and the potential susceptibility of reconstruction models to decreased skill and/or error with differing frequencies of extreme events, a finding of particular importance to future dendroclimatic research.

Vertical structure of tropical cyclone precipitation over the North Indian Ocean: a spaceborne precipitation radar perspective

ABSTRACT Spaceborne precipitation radars provide an unprecedented opportunity to study three-dimensional structure of precipitation, particularly over the open ocean where in-situ observations are rather meagre. In this study, instantaneous surface precipitation characteristics and their vertical structures during the tropical cyclones (TCs) over the North Indian Ocean (NIO) between 2014 and 2022 have been analysed using the dual-frequency precipitation radar onboard the Global Precipitation Measurement Core Observatory. Although stratiform precipitation accounts for more than 70% of total TC surface precipitation area, convective precipitation contributes about half of the total TC surface precipitation amount over the NIO. About 90% of stratiform TC precipitation area yields surface precipitation of less than 10 mm/hour. The vertical structures of stratiform and convective TC precipitation vary with surface precipitation intensity and have nearly similar characteristics over both basins of the NIO. This preliminary quantitative TC precipitation analysis would be useful for better understanding of precipitation processes during TCs over the NIO, and for further advancement in numerical models through improved parameterization schemes for TC precipitation forecasting.