Types Of Precipitation Events Research Articles

Regional characteristics of extreme precipitation events over Aotearoa New Zealand

We document 1394 extreme precipitation events (EPEs) over Aotearoa New Zealand’s (ANZ) Regional Councils between March 1996 and December 2021. The characteristics of EPEs are documented using a novel spatio-temporal framework that diagnoses the peak intensity, duration, and accumulation of the EPE using the ERA-5 and MERRA-2 reanalysis products. Properties of EPEs were evaluated according to region across ANZ, and clear regional differences are highlighted. In particular, it is found that the duration of an EPE has a stronger influence than the peak intensity on the total accumulated precipitation across all regions and precipitation event types (large-scale or convective). Since larger precipitation accumulations have greater potential to cause extensive flooding over larger areas, an important implication is the need for numerical weather prediction in ANZ to forecast the duration of an intense precipitation event adequately in order to improve emergency preparedness.

Synoptic Typing of Multiduration, Heavy Precipitation Records in the Northeastern United States: 1895–2017

Abstract Much of the previous research on total and heavy precipitation trends across the northeastern United States (herein, the Northeast) used daily precipitation totals over relatively short periods of record, which do not capture the full range of climate variability and change. Less well understood are the characteristics of long-term changes and synoptic patterns in longer-duration heavy precipitation events across the Northeast. A multiduration (1, 2, 3, 7, 14, and 30 days), multi-return-interval (2, 5, 10, and 50 years) precipitation dataset was used to diagnose changes in various types of precipitation events across the Northeast from 1895 to 2017. Increasing trends were found in all duration and return-interval event combinations with the rarest, longest duration events increasing at faster rates than more-frequent, shorter-duration ones. Daily 850-hPa geopotential height patterns associated with precipitation events were extracted from rotated principal component analysis and k-means clustering analysis, which allowed for the main synoptic types present as well as their structure and evolution to be analyzed. The daily synoptic patterns thus identified were found to be similar across all durations and return intervals and included coastal low (Northeasters, tropical cyclones, and predecessor rain events), deep trough, East Coast trough, zonal, and high pressure patterns.

Radial Growth Responses of Four Southeastern USA Pine Species to Summertime Precipitation Event Types and Intense Rainfall Events

Previous dendroclimatic studies have examined the relationship between total precipitation amounts and tree radial growth in the southeastern USA, yet recent studies indicate that specific precipitation event types and rainfall intensities influence longleaf pine (Pinus palustris Mill.) radial growth unequally. It remains unknown if other pine species respond similarly regarding specific precipitation types and intensities as most dendroclimatic studies have focused on precipitation amounts on monthly-to-annual scales without examining either the event type or intensity nor focusing on daily data. Here, we examine summertime climate–radial growth relationships in the southeastern USA for four native pine species (longleaf, shortleaf, Virginia, pitch) during 1940–2020. We examine and compare each species’ response to precipitation event types and intense rainfall events (IREs) and address if the temporal sensitivity to these events is species specific. Distinct temporal sensitivities exist among species, and there is a consistent association between convective, stationary front, and quasi-stationary precipitation and radial growth. All species except Virginia pine have significant (p < 0.001) associations between IREs and radial growth, even though IREs account for ~49% of summertime rainfall. These results suggest precipitation-type sensitivity to radial growth may have dendroclimatic implications.

Characteristics Analysis of Precipitation Observations and Climate Change Along the High-speed Railway in Jiangsu

<p>High-speed railway (HSR) is severely affected by precipitation disasters. There are many studies on precipitation and precipitation disasters, most of which are precipitation and analysis of disasters caused by precipitation, and few explain climate changes caused by precipitation. This paper uses surface meteorological observation data within 90 km along the Jiangsu section of the Beijing-Shanghai HSR to study the characteristics of precipitation along the line in 2016 ~ 2018 and the characteristics of climate change before the occurrence of precipitation events. This paper presents that when air pressure along the HSR with a relatively low level and a higher probability of precipitation. The low temperatures in April, June and July are more likely to produce precipitation. Correlations analysis shows that the three types of precipitation events are different. The time scale of the correlation between temperature and pressure changes before the occurrence of mild to moderate precipitation events is farther, and the temperature and short-term pressure changes 6 hours before the occurrence of heavy precipitation events. In contrast, the air pressure and temperature within 2 hours before the occurrence of extreme precipitation change rapidly and have a strong correlation, which indicates the occurrence of extreme events.</p>

Evaluation and Application of Quantitative Precipitation Forecast Products for Mainland China Based on TIGGE Multimodel Data

AbstractWe evaluated 24-h control forecast products from The International Grand Global Ensemble center over the 10 first-class water resource regions of Mainland China in 2013–18 from the perspective of precipitation processes (continuous) and precipitation events (discrete). We evaluated the forecasts from the China Meteorological Administration (CMA), the Centro de Previsão de Tempo e Estudos Climáticos (CPTEC), the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF), the Japan Meteorological Agency (JMA), the Korea Meteorological Administration (KMA), the United Kingdom Met Office (UKMO), and the National Centers for Environmental Prediction (NCEP). We analyzed the differences among the numerical weather prediction (NWP) models in predicting various types of precipitation events and showed the spatial variations in the quantitative precipitation forecast efficiency of the NWP models over Mainland China. Meanwhile, we also combined four hydrological models to conduct meteo-hydrological runoff forecasting in three typical basins and used the Bayesian model averaging (BMA) method to perform the ensemble forecast of different scenarios. Our results showed that the models generally underestimate and overestimate precipitation in northwestern China and southwestern China, respectively. This tendency became increasingly clear as the lead time rose. Each model has a high reliability for the forecast of no-rain and light rain in the next 10 days, whereas the NWP model only has high reliability on the next day for moderate and heavy rain events. In general, each model showed different capabilities of capturing various precipitation events. For example, the CMA and CMC forecasts had a better prediction performance for heavy rain but greater errors for other events. The CPTEC forecast performed well for long lead times for no-rain and light rain but had poor predictability for moderate and heavy rains. The KMA, UKMO, and NCEP forecasts performed better for no-rain and light rain. However, their forecasting ability was average for moderate and heavy rain. Although the JMA model performed better in terms of errors and accuracy, it seriously underestimated heavy rain events. The extreme rainstorm and flood forecast results of the coupled JMA model should be treated with caution. Overall, the ECMWF had the most robust performance. Discrepancies in the forecasting effects of various models on different precipitation events vary with the lead time and region. When coupled with hydrological models, NWP models not only control the accuracy of runoff prediction directly but also increase the difference among the prediction results of different hydrological models with the increase in NWP error significantly. Among all the single models, ECMWF, JMA, and NCEP have better effects than the other models. Moreover, the ensemble forecast based on BMA is more robust than the single model, which can improve the quality of runoff prediction in terms of accuracy and reliability.

Contribution of precipitation events with different consecutive days to rainfall change over Asia during ENSO years

The present study investigates the contributions of four types of precipitation events with different consecutive days (1–3-day, 4–7-day, 8–14-day, and over-14 day) of precipitation to April–October rainfall anomalies over Asia and roles of the three factors (intensity, number, duration) in area-mean rainfall anomalies of four types of precipitation events in El Nino and La Nina years. It is found that precipitation tends to be below normal in the entire tropical and extratropical regions except for northeastern Asia and east and west Indochina Peninsula during El Nino years. During La Nina years, precipitation tends to increase in eastern China, India, the south hills of the Himalayas, west Indochina Peninsula-southwest China, and the Maritime Continent, but decreases in northeast China, east Kazakhstan, Afghanistan, and east Indochina Peninsula. The precipitation change at the low latitudinal regions has a larger contribution from the over-14-day events. The number of events is a main factor in changes of precipitation of primary events during El Nino years. The precipitation changes in El Nino and La Nina years are consistent with changes in the activity of cyclonic wind anomalies corresponding to the precipitation events. The intraseasonal wind anomalies leading to the precipitation events in China are preceded by northwestward move of cyclonic systems from the tropical western North Pacific that promotes the start of precipitation in the concerned regions. The present study points to the impacts of intraseasonal wind systems with various lifespans on precipitation changes over Asia in El Nino and La Nina years.

Effects of warming and rainfall pulses on soil respiration in a biological soil crust-dominated desert ecosystem

Biological soil crusts (BSCs) across desert ecosystems play an important role in modulating terrestrial carbon cycles. Global warming and changes in precipitation patterns are expected to be important triggers for biological activity in BSC-dominated desert ecosystems. Therefore, it is crucial to study the effects of warming and rainfall pulses on soil respiration dynamics at BSC-dominated microsites to predict terrestrial carbon cycling under climate change. In this study, soil respiration rates were monitored continuously during three types of natural precipitation events in lichen-dominated and moss-dominated crusts in both control and warming treatments. Our results revealed that soil respiration was inhibited in BSC-dominated microsites in the warming treatment because of reduced soil water content induced by the warmer conditions, and that the extent of inhibition was lower in the lichen-dominated crusts than in the moss-dominated crusts. During all the precipitation events, soil respiration rates were significantly increased by rainfall pulses and gradually declined thereafter. Over the daily cycle, the clockwise diel hysteresis loop between soil respiration and soil temperature was modified by soil water availability, which was affected by the magnitude of rainfall pulses. Moreover, the effect of photosynthetically active radiation and the mismatch between the depth of carbon dioxide (CO2) production and soil temperature measurement may have contributed to the diel hysteresis pattern. Our results indicated that warming and different types of precipitation events in BSC-dominated desert ecosystems impact soil carbon release through changes in the magnitude of soil respiration.

High-Resolution (2.5 km) Ensemble Precipitation Analysis across Canada

AbstractConsistent and continuous fields provided by precipitation analyses are valuable for hydrometeorological applications and land data assimilation modeling, among others. Providing uncertainty estimates is a logical step in the analysis development, and a consistent approach to reach this objective is the production of an ensemble analysis. In the present study, a 6-h High-Resolution Ensemble Precipitation Analysis (HREPA) was developed for the domain covering Canada and the northern part of the contiguous United States. The data assimilation system is the same as the Canadian Precipitation Analysis (CaPA) and is based on optimal interpolation (OI). Precipitation from the Canadian national 2.5-km atmospheric prediction system constitutes the background field of the analysis, while at-site records and radar quantitative precipitation estimates (QPE) compose the observation datasets. By using stochastic perturbations, multiple observations and background field random realizations were generated to subsequently feed the data assimilation system and provide 24 HREPA members plus one control run. Based on one summer and one winter experiment, HREPA capabilities in terms of bias and skill were verified against at-site observations for different climatic regions. The results indicated HREPA’s reliability and skill for almost all types of precipitation events in winter, and for precipitation of medium intensity in summer. For both seasons, HREPA displayed resolution and sharpness. The overall good performance of HREPA and the lack of ensemble precipitation analysis (PA) at such spatiotemporal resolution in the literature motivate further investigations on transitional seasons and more advanced perturbation approaches.

Contribution of precipitation events with different consecutive days to summer rainfall change over China

The climatological features, regional trends, and interdecadal changes of summer precipitation over China are investigated in this study from the perspective of four types of precipitation events with different consecutive days. The precipitation events are classified based on the consecutive days of precipitation into 1-to-3-, 4-to-7-, 8-to-14-, and over-14-day events. The contribution of 1-to-3-day events to climatological precipitation is larger than the other events over central Asia. Longer duration events contributed more than the shorter duration events to precipitation in tropical regions. The positive precipitation trend in northwestern and southern China is mainly due to 4-to-7-day and 8-to-14-day events, respectively; and the negative precipitation trend in North China is largely related to 4-to-7-day events. In general, the frequency change of precipitation events is a major reason for the precipitation change of these events in the concerned regions. The precipitation decrease in northern China around the mid-1960s is attributed to the reduction in 4-to-7-day events. The precipitation increase in northeastern and central China in the late 1970s is due to a combination of increases in 4-to-7-day and 8-to-14-day events. The precipitation increase in southern China around 1993 is mainly contributed by over-14-day events. The precipitation decrease in the mid-latitude Asia is due to the decrease in 4-to-7-day events. Most of the interdecadal precipitation changes are related to decrease or increase in the activity of anomalous cyclones. Results suggest that the frequency of occurrence of cyclonic perturbations is a major factor for interdecadal changes in summer precipitation over China.

The importance of infrequent, high-intensity rainfall events for longleaf pine (Pinus palustris Mill.) radial growth and implications for dendroclimatic research

Tree-ring based precipitation reconstructions are beneficial in placing interannual variability in an historical context. However, absent specificity on what is being modeled (e.g., event type or rainfall intensity), similar rainfall totals inferred from reconstructions between different years imply similar conditions. Consequently, variability in specific precipitation event types or intensity can affect radial growth widths despite no changes in overall precipitation amount. Here, we use a longleaf pine latewood chronology to demonstrate how infrequent, intense (i.e., > 2.0 SD above mean) rainfall events (IREs), representing ~ 50% of total summer (July–September) precipitation amounts and 14.1% of rainfall events, principally determine interannual variability (R2 = 40.7%) in latewood while total summer rainfall amounts excluding IREs provide minimal explanatory power (R2 = 10.4%). These results suggest that slight decreases in IRE frequency can promote significant reductions in latewood growth indicating strong sensitivity to minor changes in climate.

Learning about the vertical structure of radar reflectivity using hydrometeor classes and neural networks in the Swiss Alps

Abstract. The use of radar for precipitation measurement in mountainous regions is complicated by many factors, especially beam shielding by terrain features, which, for example, reduces the visibility of the shallow precipitation systems during the cold season. When extrapolating the radar measurements aloft for quantitative precipitation estimation (QPE) at the ground, these must be corrected for the vertical change of the radar echo caused by the growth and transformation of precipitation. Building on the availability of polarimetric data and a hydrometeor classification algorithm, this work explores the potential of machine learning methods to study the vertical structure of precipitation in Switzerland and to propose a more localised vertical profile correction. It first establishes the ground work for the use of machine learning methods in this context: from volumetric data of 30 precipitation events, vertical cones with 500 m vertical resolution are extracted. It is shown that these cones can well represent the vertical structure of different types of precipitation events (stratiform, convective, snowfall). The reflectivity data and the hydrometeor proportions from the extracted cones constitute the input for the training of artificial neural networks (ANNs), which are used to predict the vertical change in reflectivity. Lower height levels are gradually removed in order to test the ANN's ability to extrapolate the radar measurements to the ground level. It is found that ANN models using the information on hydrometeor proportions can predict from altitudes between 500 and 1000 m higher than the ANN based on only reflectivity data. In comparison to more traditional vertical profile correction techniques, the ANNs show less prediction errors made from all height levels up to 4000 m a.s.l., above which the ANNs lose predictive skill and the performance levels off to a constant value.

Changes in southeastern USA summer precipitation event types using instrumental (1940–2018) and tree-ring (1790–2018) data

We examined short- and long-term changes in precipitation event types using instrumental (1940–2018) and tree-ring (1790–2018) data from North Carolina, USA. We documented the amount and frequency of summer (July–September) precipitation events using daily weather station data. Stationary front precipitation (SFP) represented 71% of total summer rainfall and SFP and convective uplift combined (i.e., quasi-stationary precipitation, QSP) represented 87%. SFP (r = 0.52, p < 0.01) and QSP (r = 0.61, p < 0.01) precipitation reconstructions from a montane longleaf pine latewood chronology both recorded significant declines during 1940–2018, matching the instrumental record. Conversely, no significant change in either SFP or QSP occured during the full reconstruction indicating the instrumental decline was unmatched throughout 1790–1939. Our method demonstrates that variations in latewood growth can be attributed to specific precipitation event types and that the relative contribution of each event type can be quantified over a multi-century period.

Relevance of the correlation between precipitation and the 0 °C isothermal altitude for extreme flood estimation

Extreme floods are commonly estimated with the help of design storms and hydrological models. In this paper, we propose a new method to take into account the relationship between precipitation intensity (P) and air temperature (T) to account for potential snow accumulation and melt processes during the elaboration of design storms. The proposed method is based on a detailed analysis of this P-T relationship in the Swiss Alps. The region, no upper precipitation intensity limit is detectable for increasing temperature. However, a relationship between the highest measured temperature before a precipitation event and the duration of the subsequent event could be identified. An explanation for this relationship is proposed here based on the temperature gradient measured before the precipitation events. The relevance of these results is discussed for an example of Probable Maximum Precipitation-Probable Maximum Flood (PMP-PMF) estimation for the high mountainous Mattmark dam catchment in the Swiss Alps.The proposed method to associate a critical air temperature to a PMP is easily transposable to similar alpine settings where meteorological soundings as well as ground temperature and precipitation measurements are available. In the future, the analyses presented here might be further refined by distinguishing between precipitation event types (frontal versus orographic).

Mesoscale extreme rainfall events in West Africa: The cases of Niamey (Niger) and the Upper Ouémé Valley (Benin)

Abstract In West Africa, a sharp decrease in rainfall has occurred in conjunction with an increase in flood damage since 1970. The material damage and loss of life resulting from floods highlights the undeniable vulnerability of populations to this threat and illustrates the importance of addressing the evolution of hazardous precipitation caused by intense rainstorms. This work aims to improve our knowledge of the behaviour of extreme rainfall in West Africa by studying the sub-hourly, hourly and daily evolution of the most extreme rainfall events, a topic that is especially important to those interested in studying the links between heavy rainfall and flash flooding or inundation. This study analyses the classes of extreme rainfall events in two distinct climatic areas within West Africa using the meteorological scales relevant to rainfall processes. The study is based on two precipitation datasets recorded by dense networks of rain gauges set up within the meso-sites of Niamey (Niger, Sahelian area) and the Upper Oueme Valley (Northern Benin, Soudanian zone) from 2000 to 2010 and 1998 to 2010, respectively. The Gumbel distribution was used to analyse the frequency of the maximum rainfall series for durations varying from 5 min to 24 h. The reliability of this model was examined, and the Intensity-Density-Frequency (IDF) curves derived from it were used to estimate the critical rainfall intensities at each site. The results returned exceeded frequencies that were useful for the isolation and classification of extreme rainfall cases using temporal characteristics. The climatological results confirm the existence of a latitudinal gradient in the mean annual rainfall and number of extreme events at the mesoscale. The classification methods illustrate clear distinctions between local, meso and synoptic scale events derived from convective systems over the Sahel. In contrast, Soudanian climate conditions lead to a nesting of the phenomena involved in the formation of cloud systems, making it difficult to classify rain events in that area. However, we were able to utilize the duration of rainfall events within this zone to discriminate between types of convective systems that cause extreme rainfall. For both areas, the proportion of precipitation in an extreme event compared to total yearly precipitation served as a suitable additional criterion used to objectively identify extreme precipitation event types.

The operational use and assessment of a layered precipitable water product for weather forecasting

Operational forecasters have a variety of new research products and tools to interrogate precipitation systems for different environments and precipitation regimes. One such product is satellite-derived, columntotal precipitable water retrieved in discrete layers as an experimental product developed by the Cooperative Institute for Research in the Atmosphere (CIRA), and transitioned by the National Aeronautics and Space Administration’s Short-term Prediction, Research, and Transition Center to numerous weather forecast offices (WFOs) to address specific forecast issues. In 2013 the CIRA layered precipitable water (LPW) product was formally assessed by National Weather Service WFOs in Alaska, the West Coast of the United States, and San Juan, Puerto Rico. Forecasters used LPW to address forecast challenges associated with atmospheric rivers, convective storms, and other types of precipitation events across diverse forecasting domains ranging from marine zones to complex topography. This paper describes the use of LPW by operational forecasters at their WFOs and shows the impact LPW had on precipitation forecasting, as determined by assessment results. During 72 formal user feedback submissions and multiple assessment periods, 62.5% of forecasters had high confidence in LPW. Fifty percent stated that LPW had a “large” impact on their decision process, and another 22.2% said LPW had “some” impact. For 76.4% of the events surveyed, forecasters stated that LPW had “large” to “very large” value over traditional total precipitable water products. Individual case examples will provide a context for forecasters’ evaluation of the product in their county warning area.

Spatiotemporal characteristics of precipitation and extreme events on the Loess Plateau of China between 1957 and 2009

Spatiotemporal trends in precipitation may influence vegetation restoration, and extreme precipitation events profoundly affect soil erosion processes on the Loess Plateau. Daily data collected at 89 meteorological stations in the area between 1957 and 2009 were used to analyze the spatiotemporal trends of precipitation on the Loess Plateau and the return periods of different types of precipitation events classified in the study. Nonparametric methods were employed for temporal analysis, and the Kriging interpolation method was employed for spatial analysis. The results indicate a small decrease in precipitation over the Loess Plateau in last 53 years (although a Mann–Kendall test did not show this decrease to be significant), a southward shift in precipitation isohyets, a slightly delayed rainy season, and prolonged return periods, especially for rainstorm and heavy rainstorm events. Regional responses to global climate change have varied greatly. A slightly increasing trend in precipitation in annual and sub-annual series, with no obvious shift of isohyets, and an evident decreasing trend in extreme precipitation events were detected in the northwest. In the southeast, correspondingly, a more seriously decreasing trend occurred, with clear shifts of isohyets and a slightly decreasing trend in extreme precipitation events. The result suggests that a negative trend in annual precipitation may have led to decreased soil erosion but an increase in sediment yield during several extreme events. These changes in the precipitation over the Loess Plateau should be noted, and countermeasures should be taken to reduce their adverse impacts on the sustainable development of the region. Copyright © 2013 John Wiley & Sons, Ltd.

Scaling of raindrop size distributions and classification of radar reflectivity–rain rate relations in intense Mediterranean precipitation

In radar hydrology the relationship between the reflectivity factor (Z) and the rainfall intensity (R) is generally assumed to follow a power law of which the parameters change both in space and time and depend on the drop size distribution (DSD). Based on disdrometer data, this study tries to improve our understanding of the temporal variability of the power-law relationship between Z and R using a scaling-law formalism for the raindrop size distribution proposed in previous contributions. In particular, this study focuses on the inter-event variability of Z–R coefficients and associated DSD-parameters and their relationship to the type of precipitation. This is crucial for developing improved quantitative precipitation estimation algorithms for extreme, flash flood triggering rainfall. Within the DSD scaling-law framework a new normalized parameter estimation method is presented, which calculates significantly faster than the original method and leads to bulk event estimates of the DSD-parameters and associated Z–R coefficients. Based on a 2.5-year disdrometer dataset collected in the Cévennes-Vivarais region in the south of France, comprising a total of 70 events, it is shown that the quality of the resulting Z–R relationships obtained by the new method compares well to two standard least-squares fitting techniques. A major benefit of the new implementation, as compared to such purely statistical methods, is that it also provides information concerning the properties of the DSD. For each of the 70 events this study also estimates the convective activity based on a threshold technique. Results show that convective events generally tend to have smaller Z–R exponents, which is assumed to result from an increased amount of drop interaction. For stratiform events, a much larger range in exponents is obtained, which is thought to depend on differences in meteorological origin (snow vs. ice). For the types of precipitation events observed in the Cévennes region, for a given value of the exponent, the prefactor of the Z–R relation tends to be larger for the more convective type of events. This emphasizes the different meteorological origin of the heavy rainfall observed in the south of France as compared to other regions of the world.

Comparison of Measured and MM5 Modeled Meteorology Data for Simulating Flow in a Mountain Watershed1

Herr, Joel W., Krish Vijayaraghavan, and Eladio Knipping, 2010. Comparison of Measured and MM5 Modeled Meteorology Data for Simulating Flow in a Mountain Watershed. Journal of the American Water Resources Association (JAWRA) 46(6):1255–1263. DOI: 10.1111/j.1752‐1688.2010.00489.xAbstract: Accurate simulation of time‐varying flow in a river system depends on the quality of meteorology inputs. The density of meteorology measurement stations can be insufficient to capture spatial heterogeneity of precipitation, especially in mountainous areas. The Watershed Analysis Risk Management Framework (WARMF) model was applied to the Catawba River watershed of North and South Carolina to simulate flow and water quality in rivers and a series of 11 reservoirs. WARMF was linked with the AMSTERDAM air model to analyze the water quality benefit from reduced atmospheric emissions. The linkage requires accurate simulation of meteorology for all seasons and for all types of precipitation events. WARMF was driven by the mesoscale meteorology model MM5 processed by the Meteorology Chemistry Interface Processor, which provides greater spatial density but less accuracy than meteorology stations. WARMF was also run with measured data from the National Climatic Data Center (NCDC) to compare the performance of the watershed model using measured data vs. modeled meteorology as input. A one year simulation using MM5 modeled meteorology performed better overall than the simulation using NCDC data for the volumetric water balance measure used for calibration, but MM5 represented precipitation from a dissipated hurricane poorly, which propagated into errors of simulated flow.

Differential winter stemflow generation under contrasting storm conditions in a southern New England broad‐leaved deciduous forest

AbstractDespite the importance of stemflow as a hydroecological process, differential winter stemflow generation among and within precipitation types (e.g. snow, rain‐to‐snow) is poorly understood. The purpose of the present study is to understand winter stemflow generation better under contrasting meteorological conditions in a leafless deciduous forest. It is hypothesized that stemflow volume and production, expressed as a funnelling ratio, will differ significantly among and within precipitation event types. Acceptance of this hypothesis would mean that intra‐event meteorological conditions have a significant and discernible effect on stemflow production in deciduous forests, differentially affecting soil moisture, groundwater recharge, soil solution chemistry, and nutrient cycling. Stemflow volumes generated from seven canopy trees were monitored in a leafless deciduous forest of southern New England on a precipitation event basis over two successive winter seasons. Stemflow volume was found to differ significantly among different and same‐type precipitation events. A rain event that occurred on 8 December 1998 and snow‐to‐rain event on 18 January 1999 were of similar duration, magnitude, and intensity, yet produced stemflow volumes that differed by a factor of 4. For two snow‐to‐rain events, stemflow volumes differed by a factor of 11. Stemflow production even varies widely within a discrete precipitation event as a function of meteorological conditions. Significant differential stemflow yield under contrasting storm conditions obviates generalizations concerning stemflow production as a function of precipitation event type and necessitates a deeper, process‐level understanding of winter stemflow generation before modelling exercises are undertaken. Copyright © 2004 John Wiley &amp; Sons, Ltd.

Winter stemflow nutrient inputs into a southern new england broadleaved deciduous forest

Stemflow leaching from the above‐ground vegetative surfaces of broadleaved deciduous canopy trees has been well documented during the growing season. Winter stemflow leaching from the leafless crowns of deciduous trees is less well understood, especially in the context of global climate change. Boreal and northern temperate forests are forecast to have a lower incidence of snow events and an increased frequency of rain and mixed precipitation events. A change in the seasonal precipitation regime may be significant due to linkages among global change, stemflow leaching, and biogeochemical processes. The aim of this paper is to (1) demonstrate the extent of winter stemflow nutrient leaching from deciduous trees; (2) explore how winter stemflow leachate quantity may vary as a function of the type of precipitation event; and (3) quantify the extent to which an increase in the incidence of snow‐to‐rain events would enhance stemflow leaching. Measuring meteorological conditions, stemflow volumes, and stemflow chemistry over two successive winter seasons in New England demonstrated that winter stemflow drainage was significantly enriched compared to the incident bulk precipitation: 162 times greater for K+, 44 times greater for Ca2+, and 29 times greater for Mg2+. Snow‐to‐rain events leached considerably greater quantities of base cations from the deciduous trees than all other types of precipitation events. An increased frequency of snow‐to‐rain events from 13.8% to 25% of winter precipitation events would substantially increase mean stemflow nutrient inputs to the bases of forest trees during winter. Implications for significantly increased winter stemflow leachate inputs, corresponding to an increased incidence of snow‐to‐rain events, include a shift in the biogeographic range of species, delayed leaf emergence, and increased soil respiration.