Atmospheric Drivers Associated with Extreme Snow Ablation and Discharge Events in the Susquehanna River Basin: A Climatology

IF 2.6 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Zachary J. Suriano, Gina R. Henderson, Julia Arthur, Kricket Harper, Daniel J. Leathers
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引用次数: 0

Abstract

Abstract Extreme snow ablation can greatly impact regional hydrology, affecting streamflow, soil moisture, and groundwater supplies. Relatively little is known about the climatology of extreme ablation events in the eastern United States, and the causal atmospheric forcing mechanisms behind such events. Studying the Susquehanna River basin over a 50-yr period, here we evaluate the variability of extreme ablation and river discharge events in conjunction with a synoptic classification and global-scale teleconnection pattern analysis. Results indicate that an average of 4.2 extreme ablation events occurred within the basin per year, where some 88% of those events resulted in an increase in river discharge when evaluated at a 3-day lag. Both extreme ablation and extreme discharge events occurred most frequently during instances of southerly synoptic-scale flow, accounting for 35.7% and 35.8% of events, respectively. However, extreme ablation was also regularly observed during high pressure overhead and rain-on-snow synoptic weather types. The largest magnitude of snow ablation per extreme event occurred during occasions of rain-on-snow, where a basinwide, areal-weighted 5.7 cm of snow depth was lost, approximately 23% larger than the average extreme event. Interannually, southerly flow synoptic weather types were more frequent during winter seasons when the Arctic and North Atlantic Oscillations were positively phased. Approximately 30% of the variance in rain-on-snow weather type frequency was explained by the Pacific–North American pattern. Evaluating the pathway of physical forcing mechanisms from regional events up through global patterns allows for improved understanding of the processes resulting in extreme ablation and discharge across the Susquehanna basin. Significance Statement The purpose of this study is to better understand how certain weather patterns are related to extreme snowmelt and streamflow events and what causes those weather patterns to vary with time. This is valuable information for informing hazard preparation and resource management within the basin. We found that weather patterns with southerly winds were the most frequent patterns responsible for extreme melt and streamflow, and those patterns occurred more often when the Arctic and North Atlantic Oscillations were in their “positive” configuration. Future work should consider the potential for these patterns, and related impacts, to change over time.
与萨斯奎哈纳河流域极端积雪消融和排放事件相关的大气驱动因素:气候学
摘要极端积雪消融对区域水文产生巨大影响,影响河流流量、土壤湿度和地下水供应。相对而言,人们对美国东部极端消融事件的气候学以及这些事件背后的大气强迫机制知之甚少。本文以萨斯克汉纳河流域为研究对象,结合天气分类和全球尺度遥相关模式分析,评估了极端消融和河流流量事件的变率。结果表明,流域内每年平均发生4.2次极端消融事件,其中约88%的极端消融事件导致河流流量增加。极端消融和极端放电事件在偏南天气尺度流中发生的频率最高,分别占事件总数的35.7%和35.8%。然而,在高空高压和雨雪天气类型中也经常观察到极端消融。每个极端事件的最大程度的积雪消融发生在雨雪天气,在整个流域,面积加权积雪深度损失为5.7 cm,比平均极端事件大约23%。年际间,在冬季,当北极和北大西洋涛动正相位时,偏南气流天气天气类型更为频繁。大约30%的雨雪天气类型频率变化可以用太平洋-北美模式来解释。评估从区域事件到全球模式的物理强迫机制的路径,可以更好地理解导致萨斯奎哈纳盆地极端消融和排放的过程。本研究的目的是更好地了解某些天气模式与极端融雪和河流事件的关系,以及导致这些天气模式随时间变化的原因。这是为盆地内的灾害准备和资源管理提供有价值的信息。我们发现,偏南风的天气模式是导致极端融化和水流的最常见模式,而这些模式在北极和北大西洋涛动处于“正”状态时发生得更频繁。未来的工作应考虑这些模式及其相关影响随时间变化的可能性。
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来源期刊
Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology 地学-气象与大气科学
CiteScore
5.10
自引率
6.70%
发文量
97
审稿时长
3 months
期刊介绍: The Journal of Applied Meteorology and Climatology (JAMC) (ISSN: 1558-8424; eISSN: 1558-8432) publishes applied research on meteorology and climatology. Examples of meteorological research include topics such as weather modification, satellite meteorology, radar meteorology, boundary layer processes, physical meteorology, air pollution meteorology (including dispersion and chemical processes), agricultural and forest meteorology, mountain meteorology, and applied meteorological numerical models. Examples of climatological research include the use of climate information in impact assessments, dynamical and statistical downscaling, seasonal climate forecast applications and verification, climate risk and vulnerability, development of climate monitoring tools, and urban and local climates.
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