Rainfall Frequency Research Articles

A Nonstationary Daily and Hourly Analysis of the Extreme Rainfall Frequency Considering Climate Teleconnection in Coastal Cities of the United States

The nonstationarity of extreme precipitation is now well established in the presence of climate change and low-frequency variability. Consequently, the implications for urban flooding, for which there are not long flooding records, need to be understood better. The vulnerability is especially high in coastal cities, where the flat terrain and impervious cover present an additional challenge. In this paper, we estimate the time-varying probability distributions for hourly and daily extreme precipitation using the Generalized Additive Model for Location Scale and Shape (GAMLSS), employing different climate indices, such as Atlantic Multi-Decadal Oscillation (AMO), the El Niño 3.4 SST Index (ENSO), Pacific Decadal Oscillation (PDO), the Western Hemisphere Warm Pool (WHWP) and other covariates. Applications to selected coastal cities in the USA are considered. Overall, the AMO, PDO and WHWP are the dominant factors influencing the extreme rainfall. The nonstationary model outperforms the stationary model in 92% of cases during the fitting period. However, in terms of its predictive performance over the next 5 years, the ST model achieves a higher log-likelihood in 86% of cases. The implications for the time-varying design rainfall in coastal areas are considered, whether this corresponds to a structural design or the duration of a contract for a financial instrument for risk securitization. The opportunity to use these time-varying probabilistic models for adaptive flood risk management in a coastal city context is discussed.

Assessment of Rainfall Frequencies from Global Precipitation Datasets

Assessment of Rainfall Frequencies from Global Precipitation Datasets

Increasing photosynthetic benefit with decreasing irrigation frequency in an Australian temperate pasture exposed to elevated carbon dioxide.

Elevated atmospheric CO2 (e[CO2]) often enhances plant photosynthesis and improves water status. However, the effects of e[CO2] vary significantly and are believed to be influenced by water availability. With the future warmer climate expected to increase the frequency and severity of extreme rainfall, the response of plants to e[CO2] under changing precipitation patterns remains uncertain. We examined the effects of e[CO2] and different irrigation regimes on perennial ryegrass in a Free-Air CO2 Enrichment (FACE) experiment. Immediately after irrigation, the mean net photosynthetic rate was 21.2% higher under e[CO2] compared to ambient conditions. This benefit increased over time, reaching 31.3% higher as days since watering increased, indicating a substantial increase in photosynthetic benefit with longer intervals between watering. Mean stomatal conductance was 21% lower in ryegrass under e[CO2] immediately after irrigation compared to ambient plots. However, the reduction in stomatal conductance under e[CO2] decreased as the interval between irrigation events increased, showing no difference 7-10 days after an irrigation event. These results imply that plants benefit most from carbon fertilisation, assimilating relatively more carbon and losing less water, during periods with less frequent rainfall. These findings have significant implications for understanding leaf-level responses to climate change.

Numerical Analysis of Levee Failure Characteristics for Flood Hydrograph Patterns

Recent climate change has significantly affected the magnitude and frequency of rainfall, which critically affects the safety of levees and leads to severe flooding damage when levees fail. This study aimed to analyze the impact of the shape of flood hydrographs on levee failure characteristics using numerical analysis. Three types of flood hydrographs derived from lognormal, beta, and Weibull probability density functions (PDFs) were utilized, with each showing differences in the timing and magnitude of the peak flows. Levee overtopping and failure phenomena were simulated using a three-dimensional numerical analysis model, namely, FLOW-3D. The simulation results indicate that the failure patterns of levees vary, depending on the PDF used, with the lognormal PDF showing significant levee failure, owing to relatively high initial flows. These results suggest that a rapid increase in the flow at the onset is a direct factor that causes levee failure. These numerical analysis results highlight the importance of understanding the characteristics of each probability density function to accurately predict and effectively respond to levee failure risk. Future research should focus on a more precise analysis of levee failure mechanisms as well as the propagation and impacts of flood waves resulting from such failures.

IMPROVEMENT OF METHODS AND TECHNICAL MEANS OF WATER EROSION CONTROL DURING CULTIVATING POTATOES ON A PROFILED FIELD SURFACE

BACKGROUND: Potato is a crop that requires the creation of a fine-grained structure of the upper tuber-inhabited soil layer to form tubers of the correct shape, as well as to ensure conditions for good soil separation during harvesting. For this purpose, most technologies for cultivating this crop provide for the formation of a profiled field surface. One of the results of global climate change is an increase in the frequency of heavy rainfall during the growing season. At the same time, the presence of a profiled surface on fields with even a slight slope leads to significant risks of water erosion during heavy rains due to water flowing from the ridge walls into the row spacing. This leads to annual irreparable losses of the fertile soil layer. Therefore, in order to ensure the preservation of the level of natural soil fertility and eliminate the risks of water erosion when using intensive potato production technologies in the context of global climate change, it is necessary to improve the technological methods and technical means used to form a profiled field surface. AIM: The aim of the study is to protect soil from water erosion during potato cultivation on a profiled field surface by improving technological methods and technical means used to form a profiled field surface, as well as substantiating the parameters and modes of their operation. METHODS: The object of the research is a non-powered rotary dyker mounted on a row-crop cultivator-subsoiler. To select rational parameters of the dyker's blades theoretical studies were conducted on the basis of which the rotor diameter of its blades was selected. The following assumptions were adopted as initial data for determining the technological parameters of the dyker: intensity of rainfall; depth of the loosening tines of the row-crop cultivator-subsoiler; the rate of rain absorption by capillaries on medium-loamy soils at a certain degree of field slope. The theoretical calculation of the technological parameters of thedyker was performed on the basis of the constructed trajectories of the rotor center and its blades during the work process. The calculation of the parameters of the dyker was carried out taking into account that the front and rear walls of the mini pit are formed by its blade by pushing loose soil during rolling with a step t relative to a fixed point at a certain depth h, the step of the dyker's blades t is determined by the design parameters of the rotor: diameter D and the number of blades on it. RESULTS: To determine the number of mini pits per linear meter the volume of water that gets between the rows during a downpour was calculated depending on their interrow width. The calculation results showed that with a precipitation intensity of 15 mm/h the number of mini tip per linear meter of the profiled surface of the field varies from 2.4 to 3.1 pcs/m. These data made it possible to determine the rational parameters of the dyker for protection against water erosion of the fields located on slopes when cultivating potatoes on the profiled surface. CONCLUSION: An effective method for preventing water erosion on the profiled surface of a field when cultivating potatoes is deep loosening between rows with simultaneous formation of mini pits at the bottom of the furrow. For this purpose it is proposed to use a non-powered rotary pit cultivator. When using a dyker with a rotor diameter of 600 mm the number of mini pits per linear meter varies from 2.4 pcs/m with a inter row spacing of 70 cm to 3.1 pcs/m with a inter row spacing of 90 cm. For reliable protection of soils from water erosion with a inter row spacing of 70 cm it is enough to install 4 blades on the rotor, with inter row spacing of 75 and 80 cm best result available with 5 blades per rotor and with a width of 90 cm 6 blades per rotor will be required.

On the Quantification of Thermodynamic Phases of Raining Clouds: Insights From Multi‐Year CloudSat and Ground‐Based Radar Observations Over Longmen, Southern China

AbstractThe thermodynamic phase of clouds is fundamental to rain initiation and development. Although it is well established that majority of rainfall from mid‐ to‐high latitudes originates from ice, there is a lack of consensus on the major thermodynamic phase of raining clouds over low latitudes. Previous CloudSat‐based studies have yet reached consistent results on the fraction of ice‐phase raining clouds over Southern China. In this work, we found that CloudSat‐based approaches are subject to metrics used for flagging rainfall events, which may lead to different estimates. Analysis of multi‐year surface radar observations suggests that has diurnal variation and increases with rain rate, while the surface rainfall originating from warm clouds does not exceed 50 . Using disdrometer observations to flag surface rainfall events, we found that about 71 and 95 of surface rainfall events and rainfall accumulation come from cold clouds, respectively. In addition, the observed rainfall accumulations over Longmen are consistent with the fifth generation atmospheric reanalysis (ERA5), whereas the frequency of warm rainfall over Longmen is significantly underestimated in ERA5.

The Impact of Rainfall on Water, Energy, Industry and Economic Growth—Based on Empirical Data from 29 Provinces in China

Sustainable urban development requires good interaction between water, energy, infrastructure and socio-economic areas. In the context of more frequent heavy rainfall and flooding events, managing the subsystems within the city in an integrated manner and realizing sustainable development have become popular research topics. Based on the above analysis, this paper constructs a water, energy, industry and economic growth system. It also introduces rainfall as an exogenous variable into the model in order to simulate the process of interactions between subsystems within a city and achieve sustainable development. By measuring the dynamic changes and spatial distribution characteristics of the efficiency values of the total water–energy–industry and economic growth system and each subsystem in 29 provinces in China, the following conclusions are drawn: (1) Most of the provinces are in the situation of “high-efficiency–negative growth” or “low-efficiency–positive growth”, and the constraints for them to reach the state of “high efficiency–positive growth” are due to the water subsystem. (2) The low-efficiency provinces are mainly concentrated in the central region, and the spillover effect of the low-efficiency provinces on the neighboring regions is more notable than that of the high-efficiency provinces. (3) The addition of rainfall improves the total efficiency in most provinces, with the most obvious improvement in the efficiency of the water subsystem. (4) The efficiency value of the industry and economic growth subsystem is relatively less affected by the amount of rainfall, but excessive rainfall will also have a negative impact. Finally, relevant policy recommendations are made to inform the relevant government departments in formulating policies related to addressing climate change and achieving sustainable urban development.

Farmers’ Perception and Adaptation Strategies on Climate Change and Variability in Rice Production in Sarlahi, Nepal

A study conducted in Sarlahi, Nepal, from February to July 2024 examined farmers' perceptions of climate change and their adaptive strategies to sustain rice yields. Among the 94 surveyed households, 96.8% reported rising temperatures, while 90.4% noted reduced rainfall frequency and intensity. Additionally, most respondents (70.2%) observed decreased flooding intensity, and 90.4% reported lower water availability in tube wells, ponds, and rivers. The study revealed limited climate knowledge among farmers, with only 2.1% being well-informed; personal experience was the primary source of information for 75.5% of respondents. Farmers employed various adaptation techniques, including improved rice varieties (66%), green manuring (34%), and alternate wetting and drying (24.5%), although only a small percentage (8.5%) utilized crop insurance. Key challenges included climate-induced disease outbreaks like blast and bacterial blight, along with pests such as the rice stem borer and leaf roller. The findings indicated that gender and landholding size significantly influenced the adoption of adaptation practices, with larger landholders more likely to adapt than smaller ones. This research contributes valuable insights into the adaptive capacities of farmers facing climate change, underscoring the need for targeted policy interventions to enhance resilience in rice cultivation through comprehensive education and resource support.

Rainfall Erosivity Projection in South‐East Australia Using the Improved Regional Climate Simulations

ABSTRACTRainfall erosivity is one of the most dynamic factors in the soil erosion process. The increase in soil erosion caused by high rainfall erosivity, and the subsequent loss of soil nutrients, can lead to reduced food production and ecosystem services. This research program under the New South Wales (NSW) Climate Change Adaptation Strategy, assesses rainfall pattern change, rainfall erosivity and erosion risk across NSW under future climate conditions. Daily rainfall erosivity and erosion risk were modelled by Revised Soil Loss Universal Equation (RUSLE) approach and compared with that driven by observed rainfall data. Future rainfall erosivity and soil erosion risk change were investigated from daily precipitation projection of the updated NSW and Australian Regional Climate Modelling (NARCliM1.5) for two future scenarios, RCP4.5 and RCP8.5, from the historical (1986–2005) to far future (2060–2079) periods. The annual average rainfall erosivity is projected to increase about 8% under RCP 4.5 and further decrease 5% under RCP 8.5 in NSW due to the predicted temperature rises. More frequent heavy rainfall events are projected to occur during summer (December–January–February), and the rainfall from these extreme rainfall events is expected to account for 51% of the total annual rainfall in the far future. NARCliM‐derived results underestimate annual rainfall erosivity compared with observation‐derived erosivity. There are greater instability (root mean squared error [RMSE]: 803.2) and erosivity uncertainty (Bias: 16%~48%) in high rainfall zones. At a monthly scale, dry months (June–July–August) are becoming drier, while wet months (December–January–February) are becoming wetter and more erosive. 67% of NSW is predicted to experience increased rainfall erosivity under RCP4.5, whereas most of NSW will shift to drought and its consequent effects under the high‐end emission scenario (RCP 8.5). To address the dual challenges of excessive wetness in coastal and north‐east NSW and increasing aridity in Western NSW, it is necessary to develop climate change adaptation management strategies based on high‐risk areas and monthly or seasonal conditions. With the emerging launch of NARCliM2.0, we anticipate further improvements of these predictions will be achieved by more accurate models and data at higher spatial and temporal resolutions.

Large global-scale vegetation sensitivity to daily rainfall variability.

Rainfall events are globally becoming less frequent but more intense under a changing climate, thereby shifting climatic conditions for terrestrial vegetation independent of annual rainfall totals1-3. However, it remains uncertain how changes in daily rainfall variability are affecting global vegetation photosynthesis and growth3-17. Here we use several satellite-based vegetation indices and field observations indicative of photosynthesis and growth, and find that global annual-scale vegetation indices are sensitive to the daily frequency and intensity of rainfall, independent of the total amount of rainfall per year. Specifically, we find that satellite-based vegetation indices are sensitive to daily rainfall variability across 42 per cent of the vegetated land surfaces. On average, the sensitivity of vegetation to daily rainfall variability is almost as large (95 per cent) as the sensitivity of vegetation to annual rainfall totals. Moreover, we find that wet-day frequency and intensity are projected to change with similar magnitudes and spatial extents as annual rainfall changes. Overall, our findings suggest that daily rainfall variability and its trends are affecting global vegetation photosynthesis, with potential implications for the carbon cycle and food security.

Economic impacts of floods in China and adaptation strategies under climate change

Abstract Climate change has intensified the frequency and severity of heavy rainfall and flooding in China, posing serious threats to economic and social stability. Over the past 40 years, the increasing trend of these events has led to significant economic losses, highlighting the urgent need to develop effective adaptation strategies in both research and policy. This study used the Adaptive Regional Input-Output model to comprehensively assess the economic impacts of the July 2021 Henan flood, with a main focus on indirect economic losses that are often underestimated in traditional assessments. The findings revealed that the indirect economic losses were up to $37.9 billion, nearly twice the direct economic losses. Additionally, a sensitivity analysis showed that increasing production capacity and the timing required to achieve it were two key factors to reduce indirect economic losses. Based on these insights, this study proposes an adaptation strategy framework tailored to China’s current development context, where systemic governance, strategic investments, and technological innovation are accounted for. This framework offers practical strategies to reduce the impacts caused by floods, thereby providing valuable guidance for sustainable disaster risk reduction and long-term economic stability in China.

Spatial Assessment of Soil Erosion and Aridity in Somalia Using the CORINE Model

This study analyzed precipitation patterns, drought conditions, erosivity indices, and arid periods in Somalia using the CORINE model. Utilizing rainfall and temperature data from 50 meteorological stations collected between 2011 and 2019, the study calculated key indices: The Fournier Precipitation Index (35.70%), the Bagnouls-Gaussen Drought Index (61.36), and the erosivity index. The results revealed notable spatial variability in erosivity and aridity across Somalia. Northwestern regions, encompassing 204,978.65 km² (32.14% of the total area), exhibit low erosivity due to reduced rainfall intensity, while southern regions, spanning 252,341.11 km² (39.56%), face high erosivity driven by frequent and intense rainfall events. The study also identified significant arid conditions, with 61.36% of Somalia’s land classified as "dry" and 38.64% as "very dry," highlighting widespread water scarcity and vulnerability. These findings underscore Somalia's environmental challenges, including severe soil degradation, reduced agricultural productivity, and the exacerbation of droughts due to climate change. The integration of the Modified Fournier Index and the Bagnouls-Gaussen Index within the CORINE model provides a comprehensive assessment of the country's susceptibility to erosion and aridity. This research offers critical insights for prioritizing areas that require urgent soil conservation and improved land-use management. It also serves as a vital tool for policymakers and international organizations aiming to mitigate the adverse impacts of climate change, enhance agricultural sustainability, and promote ecological resilience in Somalia’s diverse landscapes.

Nature-Based Solutions for Flood Mitigation in Metropolitan Areas

Flooding is a globally common problem in metropolitan areas including Jakarta, Indonesia. The increased intensity and frequency of rainfall caused by climate change and rapid urbanization have raised the risk of flooding in urban areas. One solution is to implement polders to mitigate flooding in coastal metropolitan areas. Regrettably, the current polder system is inadequate for managing flooding due to rapid land-use changes and regional expansion. This study analyzes flood control in the Jakarta region using the East Sunter Polder System, which experienced flooding in both 1990 and 2020 despite the implementation of the polder system. The polder system, consisting of four catchment areas—Petukangan, KBN 1/Sukapura, KBN 2, and Kebantenan—faces drainage challenges exacerbated by rainfall. To mitigate flood risks, Nature-Based Solutions (NBSs) have been implemented, including retention ponds and long storage systems. Hydrological and hydraulic analyses were conducted using HEC-HMS and HEC-RAS, and ArcGIS was employed for floodplain integration. This study underscores the significance of incorporating NBSs in urban flood management, demonstrating how they enhance resilience and mitigate flood risks. By integrating NBSs into the urban planning framework, the findings suggest that flood risk management can be significantly improved, leading to better preparation and long-term sustainability for managing natural hazards.

Diurnal Changes in Cloud Cover in Eastern Gabon and Their Impacts on Energy Balance, Light Availability, and Water Demand: A Case Study of the 2022 Dry Season

Abstract Western central Africa is atypical of the equatorial domain as the main dry season is cloudier than the rainy seasons. To understand this cloud cover’s diurnal evolution, we set up an infrared camera and acquired measurements of the total cloud cover fraction (TCF) and cloud optical depth at Bambidie, Gabon (0°44′30.5″S, 12°58′12.4″E), from May to October 2022. Diurnal variations in TCF can be summarized into four types, mostly discretized through the timing and duration of clouds clearing in the afternoon [early afternoon clearing (EaC), late afternoon clearing (LaC), and clear night (CNi)], while one type [no clearing (NoC)] shows overcast conditions all day long. Meteorological measurements show that NoC days record 50 W m−2 less shortwave incoming surface radiation, resulting in daytime temperatures 1°C lower than the seasonal norm, but 20% more diffuse light and 0.5 mm day−1 less ETo. Conversely, EaC days record 50 W m−2 more shortwave incoming surface radiation, leading to temperatures 1.5°C higher than the seasonal norm, but 40% more direct light. The larger water demand (0.5 mm day−1 more ETo) is partly compensated by more frequent rainfall at nighttime. The satellite estimates of Satellite Application Facilities for supporting Nowcasting and very short-range Forecasting (SAFNWC) capture the TCF variations for most of the four types well. They confirm that TCF is dominated by very low and low clouds whose dissipation in the afternoon and evolution into fractional and cumuliform convective clouds explains the clearings on EaC and LaC days. Satellite estimates also show that the four types of days extracted at Bambidie are representative of a larger-scale cloud cover evolution in western central Africa, with a west–east gradient in the timing of afternoon cloud dissipation.

Normalization of Suak Ujong Kalak estuary as a flood reduction effort for Meulaboh city

Abstract Meulaboh City frequently experiences flooding, with runoff flowing into the Suak Ujong Kalak Estuary, a natural outlet for the city’s drainage system. Currently, the estuary is unable to effectively accommodate the runoff, exacerbating the flood risk. This study aims to evaluate the existing condition of the Suak Ujong Kalak Estuary and propose a normalization plan to improve flood control. The research employs a descriptive-quantitative methodology, involving field surveys, data collection, and hydrological and hydraulic analyses. The hydrological analysis includes rainfall frequency analysis, chi-square testing, and rainfall intensity calculation using the Mononobe method. Flood discharge estimation is based on the Rational method for a 25-year return period. Hydraulic analysis is conducted using HEC-RAS 6.3.1 software. The results show that the estuary receives an inflow of 79.33 m3/second, which exceeds its current capacity. Hydraulic analysis reveals that the estuary cannot accommodate the discharge, causing overflow with an average height of 0.6 meters and a storage capacity of 40,798.43 m3. To address this, the study recommends a normalization effort, involving excavation with an average depth of 1 meter, to improve the estuary’s capacity and reduce flooding in Meulaboh City.

Study on Multi-Scenario Rain-Flood Disturbance Simulation and Resilient Blue-Green Space Optimization in the Pearl River Delta

In the face of global climate change and rapid urbanization, the Pearl River Delta is confronted with frequent river floods and heavy rainfall, which leads to substantial economic losses and casualties. Enhancing the role of blue-green space in rain-flood resilience is crucial for mitigating such damages in this new era. Firstly, based on an analysis of the current status quo of blue-green space in the Pearl River Delta and the identification of potential areas at risk from rain and floods, this paper elucidates that resilient blue-green space in the Pearl River Delta should be guided by a systematic, bottom-line, and forward-looking orientation while considering spatial characteristics such as multi-scale network connectivity, redundancy and diversity/multi-functionality. Secondly, an optimization route is proposed based on steps of analysis of existing blue-green space, identification of inundated areas prone to rain and flood damage and optimization of blue-green spaces. Strategies for optimizing blue-green space are put forth including enhancing water corridor connectivity, optimizing ecological barriers and corridors, as well as constructing water gates to control hydrological flow direction. Simulation results demonstrate that under similar rain-flood disaster conditions, optimized blue-green space exhibits smaller sizes and lower depths of potential inundated areas compared to the original ones.

Temperature Gradient Characteristics of Rubber-Modified Asphalt Pavement Under Dramatic Cooling-Heating Cycles.

The periodic changes in climatic factors cause the pavement temperature field to change significantly, resulting in fatigue damage to the pavement caused by temperature stress, and the influence depth has a critical value. To reveal the influence range and variation pattern of the rubber-modified pavement temperature field under frequent rainfall and high temperatures, based on indoor tests and the finite element model, the evolution law of different influencing factors and pavement temperature fields was determined by a single factor sensitivity analysis method. The degree of influence of each influencing factor on the pavement temperature field was analyzed using the Pearson correlation. The results showed that with different asphalt mixture initial temperatures, the road surface temperature decreased from 20 °C to 40 °C under sudden rainfall. Repeated rainfall following high temperatures induces cyclic temperature changes 30 mm below the road surface. The pavement temperature difference increased linearly with the dramatic temperature difference, and the changes in the pavement temperature field were small when the number of cycles exceeded 30. The number of cycles and cycle temperature difference were the main factors affecting the changes in the pavement temperature field under dramatic cooling-heating cycles.

Precipitation Patterns and Their Role in Modulating Nitrous Oxide Emissions from Arid Desert Soil

Nitrous oxide (N2O) ranks as the third most significant greenhouse gas, capable of depleting the ozone layer and posing threats to terrestrial ecosystems. Climate change alters precipitation variability, notably in terms of frequency and magnitude. However, the implications of precipitation variability on N2O emissions and the underlying mechanisms remain inadequately understood. In this study, employing laboratory incubation methods on three representative sandy soil types (sandy soil, shrub soil, and crust soil), we examined the impacts of diverse precipitation levels (5 mm and 10 mm) and frequencies (7 days and 14 days) on N2O emissions from these soil types. This study aims to clarify the complex connections between soil N2O emission fluxes and soil physicochemical properties in the soil environment. Our findings reveal that the N2O emission flux exhibits heightened responsiveness to 5 mm precipitation events and a 14-day precipitation frequency, and compared to other treatments, the 5 mm precipitation and 14-day precipitation frequency treatment resulted in a 20% increase in cumulative nitrous oxide emissions. Consequently, cumulative N2O emissions were notably elevated under the 5 mm precipitation and 14-day precipitation frequency treatments compared to the other experimental conditions. The N2O emission flux in sandy soil displayed a positive correlation with available phosphorus (AP) and a negative correlation with pH, primarily attributed to the exceedingly low AP content in sandy soil. In shrub soil, the soil N2O emission flux exhibited a significant positive correlation with NH4+-N and a negative correlation with NO3−-N. Conversely, no significant correlations were observed between soil N2O emission flux and soil physicochemical properties in crust soil, underscoring the importance of considering plant–soil microbial interactions. Our findings suggest that soil nitrous oxide emissions in arid and semi-arid regions will be particularly responsive to small and frequent rainfall events as precipitation patterns change in the future, primarily due to their soil physicochemical characteristics.

Uncovering Below Cloud Rain‐Vapor Interactions During Tropical Rain Events Through Simultaneous and Continuous Real‐Time Monitoring of Rain and Vapor Isotopes

AbstractDue to limited water vapor measurements, vapor isotopes have been traditionally estimated under the assumption of isotopic equilibrium between rain and vapor below cloud base. However, recent advancements in analytical instruments allow more vapor isotopic measurements that have challenged this assumption. To enhance our understanding of rain‐vapor interactions below cloud base in tropical regions, we established an automated system to measure rain and vapor isotopes simultaneously and continuously in real time at minute intervals in Singapore. Among 324 rain events monitored from 2016 to 2019, 81% exhibited a substantial departure of rain and vapor isotopes from the expected equilibrium. This departure suggests that raindrop evaporation plays a larger role in determining their isotopes. The conclusion is supported by the generally lower slopes of the local meteoric water line. Seasonal variations in rain event characteristics indicate changing influences of rain‐vapor interactions: during monsoons, more frequent heavy rainfall maintains relatively high humidity below cloud base, favoring rain‐vapor isotopic equilibrium, whereas during inter‐monsoons, more light rain events lead to pronounced rain evaporation and larger isotopic differences. Furthermore, rain‐vapor interactions below cloud base significantly modulated their isotope evolution during individual events. As events progressed, reduced humidity favored evaporation, increasing rain isotope values and decreasing its d‐excess, whereas vapor isotope values decreased and its d‐excess increased. Our study introduces a new approach to capturing real‐time high‐resolution rain and vapor isotopes at minute intervals to understand the dynamics of rain‐vapor interactions below cloud base. Findings underscore the crucial role of these interactions in influencing rain and vapor isotopes during tropical rain events.

Impact of boundary layer parameterizations on simulated seasonal meteorology over North-East India

This study evaluated the accuracy of six planetary boundary layer (PBL) parameterization schemes in simulating two different seasons of pre-monsoon and monsoon in India's North-East region through the Weather Research and Forecasting (WRF) model. Twelve one-month simulations were conducted with the PBL schemes, six each for April (pre-monsoon) and July (monsoon), and the model outputs were compared against observations. Three non-local schemes, Asymmetric Convective Model (ACM2), Yonsei University (YSU), Shin-Hong (HONG), and three local schemes, Quasi Normal Scale Elimination (QNSE), Mellor Yamada Janjic (MYJ) and Mellor Yamada Nakanishi Nino (MYNN3), were tested. The meteorological variables of temperature, relative humidity (RH), wind speed, wind direction, and rainfall were evaluated, and the performance of each scheme for each meteorological variable is reported. The 2 m temperature (T2) variable was well simulated by ACM2, MYJ in April, and YSU in July, while MYNN3 best simulated the 2 m RH (RH2) during both seasons. 10 m wind speed (WS10) and directions (WD10) were better simulated by MYNN3, HONG and YSU. HONG also best-simulated rainfall in April and MYJ in July. April and July being rainfall periods, an analysis of the schemes’ simulated rainfall frequency was also carried out. Moreover, the PBL schemes were also ranked, considering their combined performance with all the above meteorological parameters. While considering both the seasons and all meteorological variables, the scale-aware scheme, HONG, was the best scheme and can be used to simulate both seasons. Additionally, an in-depth analysis of surface and atmospheric parameters was also carried out to reason the simulated meteorology. QNSE expends the highest amount of its surface energy through surface evaporation, leading to the lowest surface skin temperature and T2 predictions. In contrast, MYNN3 produced the lowest mixing, which caused the moistest boundary layer, highest RH, cloud cover, and highly overestimated rainfall. Besides evaluation, which will help to choose a suitable PBL scheme for weather predictions in this region, this study also identifies the characteristics and deficiencies of PBL and surface layer schemes for improvement.