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Journal ArticleDOI

Does higher surface temperature intensify extreme precipitation

01 Aug 2011-Geophysical Research Letters (John Wiley & Sons, Ltd)-Vol. 38, Iss: 16
TL;DR: In this paper, the authors assessed the global relationship between extreme daily precipitation intensity and the daily surface air temperature using in-situ data, and showed that the potential applicability of the Clausius-Clapeyron scaling on sub-hourly timescale was observed.
Abstract: [1] Recently, against the backdrop of current climate, several regional studies have investigated the applicability of the Clausius–Clapeyron relation to the scaling relationship between extreme precipitation intensity and surface air temperature. Nevertheless, the temperature relationship of the extreme precipitation intensity on a global scale is still unclear. We assess, for the first time, the global relationship between the extreme daily precipitation intensity and the daily surface air temperature using in-situ data. The extreme daily precipitation intensity increased monotonically with the daily surface air temperature at high latitudes and decreased monotonically in the tropics. Similarly, the extreme daily precipitation intensity at middle latitudes increased at low temperatures and decreased at high temperatures; this decrease could be largely attributed to the decrease in the wet-event duration. The Clausius–Clapeyron scaling is applicable to the increase in the extreme daily precipitation intensity in a limited number of regions. However, the potential applicability of the Clausius–Clapeyron scaling on sub-hourly timescale was observed, even in regions where the Clausius–Clapeyron scaling on daily timescale was not applicable. This implies the potential of warming to intensify extreme precipitation on sub-hourly timescales.

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Citations
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Book Chapter
01 Jan 2013
TL;DR: The authors assesses long-term projections of climate change for the end of the 21st century and beyond, where the forced signal depends on the scenario and is typically larger than the internal variability of the climate system.
Abstract: This chapter assesses long-term projections of climate change for the end of the 21st century and beyond, where the forced signal depends on the scenario and is typically larger than the internal variability of the climate system. Changes are expressed with respect to a baseline period of 1986-2005, unless otherwise stated.

2,253 citations

Journal ArticleDOI
TL;DR: In this paper, a review examines the evidence for sub-daily extreme rainfall intensification due to anthropogenic climate change and describes the current physical understanding of the association between sub-day extreme rainfall intensity and atmospheric temperature.
Abstract: Evidence that extreme rainfall intensity is increasing at the global scale has strengthened considerably in recent years Research now indicates that the greatest increases are likely to occur in short-duration storms lasting less than a day, potentially leading to an increase in the magnitude and frequency of flash floods This review examines the evidence for subdaily extreme rainfall intensification due to anthropogenic climate change and describes our current physical understanding of the association between subdaily extreme rainfall intensity and atmospheric temperature We also examine the nature, quality, and quantity of information needed to allow society to adapt successfully to predicted future changes, and discuss the roles of observational and modeling studies in helping us to better understand the physical processes that can influence subdaily extreme rainfall characteristics We conclude by describing the types of research required to produce a more thorough understanding of the relationships between local-scale thermodynamic effects, large-scale atmospheric circulation, and subdaily extreme rainfall intensity

862 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009.
Abstract: This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann‐Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature,withthemedianintensityofextremeprecipitationchanginginproportionwithchangesinglobal mean temperature at a rate of between 5.9% and 7.7%K 21 , depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 138S and 118N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.

825 citations

01 Jan 2013
TL;DR: In this article, the causes of observed changes assessed in Chapters 2 to 5 and uses understanding of physical processes, climate models and statistical approaches are used to assess the extent to which atmospheric and oceanic changes influence ecosystems, infrastructure, human health and activities in economic sectors.
Abstract: This chapter assesses the causes of observed changes assessed in Chapters 2 to 5 and uses understanding of physical processes, climate models and statistical approaches. The chapter adopts the terminology for detection and attribution proposed by the IPCC good practice guidance paper on detection and attribution (Hegerl et al., 2010) and for uncertainty Mastrandrea et al. (2011). Detection and attribution of impacts of climate changes are assessed by Working Group II, where Chapter 18 assesses the extent to which atmospheric and oceanic changes influence ecosystems, infrastructure, human health and activities in economic sectors.

720 citations

01 Apr 2013
TL;DR: In this paper, the authors investigated the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009.
Abstract: This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann‐Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature,withthemedianintensityofextremeprecipitationchanginginproportionwithchangesinglobal mean temperature at a rate of between 5.9% and 7.7%K 21 , depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 138S and 118N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.

615 citations

References
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01 Jan 2007
TL;DR: The first volume of the IPCC's Fourth Assessment Report as mentioned in this paper was published in 2007 and covers several topics including the extensive range of observations now available for the atmosphere and surface, changes in sea level, assesses the paleoclimatic perspective, climate change causes both natural and anthropogenic, and climate models for projections of global climate.
Abstract: This report is the first volume of the IPCC's Fourth Assessment Report. It covers several topics including the extensive range of observations now available for the atmosphere and surface, changes in sea level, assesses the paleoclimatic perspective, climate change causes both natural and anthropogenic, and climate models for projections of global climate.

32,826 citations

Journal ArticleDOI
William S. Cleveland1
TL;DR: Robust locally weighted regression as discussed by the authors is a method for smoothing a scatterplot, in which the fitted value at z k is the value of a polynomial fit to the data using weighted least squares, where the weight for (x i, y i ) is large if x i is close to x k and small if it is not.
Abstract: The visual information on a scatterplot can be greatly enhanced, with little additional cost, by computing and plotting smoothed points. Robust locally weighted regression is a method for smoothing a scatterplot, (x i , y i ), i = 1, …, n, in which the fitted value at z k is the value of a polynomial fit to the data using weighted least squares, where the weight for (x i , y i ) is large if x i is close to x k and small if it is not. A robust fitting procedure is used that guards against deviant points distorting the smoothed points. Visual, computational, and statistical issues of robust locally weighted regression are discussed. Several examples, including data on lead intoxication, are used to illustrate the methodology.

10,225 citations

Journal ArticleDOI
25 Aug 2006-Science
TL;DR: In this paper, the authors focus on the flow of water in natural and artificial reservoirs and reduce the vulnerability of people living under water stress to seasonal patterns and increasing probability of extreme events.
Abstract: Water is a naturally circulating resource that is constantly recharged. Therefore, even though the stocks of water in natural and artificial reservoirs are helpful to increase the available water resources for human society, the flow of water should be the main focus in water resources assessments. The climate system puts an upper limit on the circulation rate of available renewable freshwater resources (RFWR). Although current global withdrawals are well below the upper limit, more than two billion people live in highly water-stressed areas because of the uneven distribution of RFWR in time and space. Climate change is expected to accelerate water cycles and thereby increase the available RFWR. This would slow down the increase of people living under water stress; however, changes in seasonal patterns and increasing probability of extreme events may offset this effect. Reducing current vulnerability will be the first step to prepare for such anticipated changes.

2,814 citations

Journal ArticleDOI
TL;DR: In this article, precipitation intensity, duration, frequency, and phase are as much of concern as total amounts, as these factors determine the disposition of precipitation once it hits the ground and how much runs off.
Abstract: From a societal, weather, and climate perspective, precipitation intensity, duration, frequency, and phase are as much of concern as total amounts, as these factors determine the disposition of precipitation once it hits the ground and how much runs off. At the extremes of precipitation incidence are the events that give rise to floods and droughts, whose changes in occurrence and severity have an enormous impact on the environment and society. Hence, advancing understanding and the ability to model and predict the character of precipitation is vital but requires new approaches to examining data and models. Various mechanisms, storms and so forth, exist to bring about precipitation. Because the rate of precipitation, conditional on when it falls, greatly exceeds the rate of replenishment of moisture by surface evaporation, most precipitation comes from moisture already in the atmosphere at the time the storm begins, and transport of moisture by the storm-scale circulation into the storm is vital....

2,526 citations

Trending Questions (1)
Does higher surface temperature intensify extreme precipitation?

The paper states that the extreme daily precipitation intensity increases with higher surface air temperature at high latitudes, but decreases in the tropics. The Clausius-Clapeyron scaling is applicable in some regions, but further studies are needed for sub-hourly timescales.