Shifts in Precipitation Accumulation Extremes During the Warm Season Over the United States

Martinez‐Villalobos, Cristian; Neelin, J. David

doi:10.1029/2018gl078465

Cited by 42 publications

(32 citation statements)

References 74 publications

(104 reference statements)

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“…We use the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to compare the combination of Power‐law and GPD with many classic distributions, including exponential, generalized Pareto distribution, log‐normal and the gamma distribution. Other various combinations of distributions are also compared such as a mixture of two exponential distributions and a power‐law distribution until an exponential cut‐off for large events which have been widely applied to simulate precipitation intensity surrogate time series (Wilks and Wilby, ; Bernardara et al ., ; Paschalis et al ., ; Martinez‐Villalobos and Neelin, ). According to their criteria, we will choose the model that minimizes,

AIC = 2 * k - 2 * \log ((), \overset{false^}{L}) italicor BIC = k * \log ((), n) - 2 * \log ((), \overset{false^}{L}),

where k is the number of parameters in the model, n is the length of the time series and

\overset{L}{true}

is the maximum value of the likelihood function of the model.…”

Section: Methodsmentioning

confidence: 99%

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Power‐law behaviour of hourly precipitation intensity and dry spell duration over the United States

Yang

Franzke

2019

Intl Journal of Climatology

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Precipitation is an important meteorological variable which is critical for weather risk assessment. For instance, intense but short precipitation events can lead to flash floods and landslides. Most statistical modelling studies assume that the occurrence of precipitation events is based on a Poisson process with exponentially distributed waiting times while precipitation intensities are typically described by a gamma distribution or a mixture of two exponential distributions. Here, we show by using hourly precipitation data over the United Sates that the waiting time between precipitation events is non‐exponentially distributed and best described by a fractional Poisson process. A systematic model selection procedure reveals that the hourly precipitation intensities are best represented by a two‐distribution model for about 90% of all stations. The two‐distribution model consists of (a) a generalized Pareto distribution (GPD) model for bulk precipitation event sizes and (b) a power‐law distribution for large and extreme events. Finally, we analyse regional climate model output to evaluate how the climate models represent the high‐frequency temporal structure of U.S. precipitation. Our results reveal that these regional climate models fail to accurately reproduce the power‐law behaviour of intensities and severely underestimate the long durations between events.

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AIC = 2 * k - 2 * \log ((), \overset{false^}{L}) italicor BIC = k * \log ((), n) - 2 * \log ((), \overset{false^}{L}),

where k is the number of parameters in the model, n is the length of the time series and

\overset{L}{true}

is the maximum value of the likelihood function of the model.…”

Section: Methodsmentioning

confidence: 99%

“…Another possible model for the power-law range of precipitation is the idea of self-organized criticality (Bak et al, 1988;Peters et al, 2001). In such a process the event intensity is power-law distributed until it reaches an exponential cut-off for large events (Martinez-Villalobos and Neelin, 2018).…”

Section: Introductionmentioning

confidence: 99%

Power‐law behaviour of hourly precipitation intensity and dry spell duration over the United States

Yang

Franzke

2019

Intl Journal of Climatology

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“…However, not only the winter extreme precipitation has changed over the United States but there is also evidence that similar changes are observed during the summer. Martinez‐Villalobos and Neelin () investigated precipitation accumulations integrated over events in hourly data in the warm season (May–October) over the United States from 1979 to 2013 focusing on characterizing the power law that describes the exponential drop of the accumulation distribution. These coefficients are not universal but depend on local climate.…”

Section: Trends In Precipitationmentioning

confidence: 99%

Assessing precipitation trends in the Americas with historical data: A review

Carvalho

2019

WIREs Climate Change

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North, Central, and South America (collectively referred to as the Americas) extend across two hemispheres, and together cover approximately 28% of Earth's land area and are home to about 13% of the world's population. Unique ecosystems, diversified cultures, and communities that inhabit the region rely on precipitation delivered yearly by multiple systems, including mid-latitudes storms, the North and South American Monsoons, and tropical storms and hurricanes. The rapid warming of the Earth's atmosphere and oceans combined with internal variability of the climate system, have modified precipitation patterns from the tropics to high latitudes.In the Americas, instrumental records have shown evidence of upward trends in extreme precipitation (amount, intensity, and frequency) in many areas. The most consistent evidence of precipitation trends occurs in mid-latitudes of North America and in the subtropics of South America. Recent studies have indicated a poleward shift of heavy precipitation associated with South American Monsoon.Nonetheless, the deficient network of rain gauges in vast areas over tropical Americas limits the assessment of trends in regions with heavy rainfall amounts. Additionally, observed trends in the North America monsoon precipitation are difficult to separate from the contribution of tropical storms and hurricanes. Furthermore, coupled modes such as the El Nino/Southern Oscillation, the Pacific Decadal Oscillation, and the Atlantic Multidecadal Oscillation modulate precipitation in the Americas, from the tropics to the extratropics, and these teleconnections are relevant to assess precipitation trends using historical records. This review evaluates all these complex issues focusing on observations based on instrumental datasets.

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“…Expected intensification of extreme precipitation due to a warming climate is of considerable societal concern, with resultant floods being one of the most common, dangerous, and destructive natural disasters (FitzGerald et al, 2010;Hallegatte et al, 2013;Johnson et al, 2019). Extreme precipitation events have been found to be increasing in both observations (Guerreiro et al, 2018;Martinez-Villalobos & Neelin, 2018;Peleg et al, 2018;Wasko & Nathan, 2019a;Westra et al, 2013) and climate models over the past six decades (Donat et al, 2016;Kendon et al, 2014Kendon et al, , 2017. The primary physical reasoning for the future increase in extreme precipitation events is the increase of atmospheric water vapor as governed by the Clausius-Clapeyron (CC) relation at an approximate rate of 6-7%/°C.…”

Section: Introductionmentioning

confidence: 99%

Resolving Inconsistencies in Extreme Precipitation‐Temperature Sensitivities

Visser

Wasko

Sharma

2020

Geophysical Research Letters

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Extreme precipitation events are intensifying with increasing temperatures. However, observed extreme precipitation-temperature sensitivities have been found to vary significantly across the globe. Here we show that negative sensitivities found in previous studies are the result of limited consideration of within-day temperature variations due to precipitation. We find that short-duration extreme precipitation can be better described by subdaily atmospheric conditions before the start of storm events, resulting in positive sensitivities with increased consistency with the Clausius-Clapeyron relation across a wide range of climatic regions. Contrary to previous studies that advocate that dew point temperature drives precipitation, dry-bulb temperature is found to be a sufficient descriptor of precipitation variability. We argue that analysis methods for estimating extreme precipitation-temperature sensitivities should account for the strong and prolonged cooling effect of intense precipitation, as well as for the intermittent nature of precipitation. Plain Language Summary Increasing global temperatures are likely to result in the intensification of extreme precipitation events with resultant flooding of great societal concern. Understanding the relationship between extreme precipitation and temperature provides valuable information for the design, operation, and risk assessment of high-hazard infrastructure. However, the observed precipitation-temperature relationship has been found to vary significantly across the globe, with negative relationships found in warmer climatic regions. Using station-based subdaily observations, we show that careful sampling of higher temperatures measured before the start of the storm events can result in positive extreme precipitation-temperature relationships across a wide range of climatic regions. Dry-bulb temperature is found to drive short-duration precipitation extremes, contradicting previous studies promoting dew point temperature as the main driver of precipitation variability. Our results indicate the use of coarser daily-scale observations in previous studies contributed to obtaining negative relationships by limiting consideration for within-day temperature variation caused by the rainfall event itself.

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Shifts in Precipitation Accumulation Extremes During the Warm Season Over the United States

Cited by 42 publications

References 74 publications

Power‐law behaviour of hourly precipitation intensity and dry spell duration over the United States

Power‐law behaviour of hourly precipitation intensity and dry spell duration over the United States

Assessing precipitation trends in the Americas with historical data: A review

Resolving Inconsistencies in Extreme Precipitation‐Temperature Sensitivities

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