Complexity in estimating past and future extreme short-duration rainfall
TL;DR: In this article, an analysis suggests that links ofrainfall extremes with daily temperature variations do not provide a reliable basis for projections, and the observed precipitation-temperature scaling relationships have been established almost exclusively by linking precipitation extremes with day-to-day temperature variations.
Abstract: The atmosphere can hold more water in a warming climate, which may lead to more extreme rainfall events. An analysis suggests that links ofrainfall extremes with daily temperature variations do not provide a reliable basis for projections. Warming of the climate is now unequivocal. The water holding capacity of the atmosphere increases by about 7% per °C of warming, which in turn raises the expectation of more intense extreme rainfall events. Meeting the demand for robust projections for extreme short-duration rainfall is challenging, however, because of our poor understanding of its past and future behaviour. The characterization of past changes is severely limited by the availability of observational data. Climate models, including typical regional climate models, do not directly simulate all extreme rainfall producing processes, such as convection. Recently developed convection-permitting models better simulate extreme precipitation, but simulations are not yet widely available due to their computational cost, and they have their own uncertainties. Attention has thus been focused on precipitation–temperature relationships in the hope of obtaining more robust extreme precipitation projections that exploit higher confidence temperature projections. However, the observed precipitation–temperature scaling relationships have been established almost exclusively by linking precipitation extremes with day-to-day temperature variations. These scaling relationships do not appear to provide a reliable basis for projecting future precipitation extremes. Until better methods are available, the relationship of the atmosphere's water holding capacity with temperature provides better guidance for planners in the mid-latitudes, albeit with large uncertainties.
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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
TL;DR: An intensification of extreme precipitation and flood events over all climate regions which increases as water availability increases from wet to dry regions and spatial and seasonal water availability becomes stronger as events become less extreme.
Abstract: The hydrological cycle is expected to intensify with global warming, which likely increases the intensity of extreme precipitation events and the risk of flooding. The changes, however, often differ from the theorized expectation of increases in water-holding capacity of the atmosphere in the warmer conditions, especially when water availability is limited. Here, the relationships of changes in extreme precipitation and flood intensities for the end of the twenty-first century with spatial and seasonal water availability are quantified. Results show an intensification of extreme precipitation and flood events over all climate regions which increases as water availability increases from wet to dry regions. Similarly, there is an increase in the intensification of extreme precipitation and flood with the seasonal cycle of water availability. The connection between extreme precipitation and flood intensity changes and spatial and seasonal water availability becomes stronger as events become less extreme.
400 citations
01 Apr 2015
TL;DR: In this article, the authors employ a convection-resolving model using a horizontal grid spacing of 2.2 km across an extended region covering the Alps and its larger-scale surrounding from northern Italy to northern Germany, and find that both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation.
Abstract: Climate models project that heavy precipitation events intensify with climate change. It is generally accepted that extreme day-long events will increase at a rate of about 6–7% per degree warming, consistent with the Clausius-Clapeyron relation. However, recent studies suggest that subdaily (e.g., hourly) precipitation extremes may increase at about twice this rate. Conventional climate models are not suited to assess such events, due to the limited spatial resolution and the need to parametrize convective precipitation (i.e., thunderstorms and rain showers). Here we employ a convection-resolving model using a horizontal grid spacing of 2.2 km across an extended region covering the Alps and its larger-scale surrounding from northern Italy to northern Germany. Consistent with previous results, projections using a Representative Concentration Pathways version 8.5 greenhouse gas scenario reveal a significant decrease of mean summer precipitation. However, unlike previous studies, we find that both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation. Differences to previous studies might be due to the model or region considered, but we also show that it is inconsistent to extrapolate from present-day precipitation scaling into the future.
241 citations
TL;DR: It is shown that storm runoff extremes increase in most regions at rates higher than suggested by Clausius-Clapeyron scaling, which are systematically close to or exceed those of precipitation extremes over most regions of the globe, accompanied by large spatial and decadal variability.
Abstract: Weather extremes have widespread harmful impacts on ecosystems and human communities with more deaths and economic losses from flash floods than any other severe weather-related hazards. Flash floods attributed to storm runoff extremes are projected to become more frequent and damaging globally due to a warming climate and anthropogenic changes, but previous studies have not examined the response of these storm runoff extremes to naturally and anthropogenically driven changes in surface temperature and atmospheric moisture content. Here we show that storm runoff extremes increase in most regions at rates higher than suggested by Clausius-Clapeyron scaling, which are systematically close to or exceed those of precipitation extremes over most regions of the globe, accompanied by large spatial and decadal variability. These results suggest that current projected response of storm runoff extremes to climate and anthropogenic changes may be underestimated, posing large threats for ecosystem and community resilience under future warming conditions.
237 citations
TL;DR: In this paper, the authors used the gridded observations and simulations from the Coupled model intercomparison project 5 (CMIP5) and Climate of 20th century plus (C20C+) detection and attribution (D&A) project to show that the frequency and intensity of extreme precipitation events have increased in India during the last few decades.
Abstract: India has witnessed some of the most devastating extreme precipitation events, which have affected urban transportation, agriculture, and infrastructure. Despite the profound implications and damage due to extreme precipitation events, the influence of anthropogenic warming on the intensity and frequency of extreme precipitation events over India remains poorly constrained. Here using the gridded observations and simulations from the Coupled model intercomparison project 5 (CMIP5) and Climate of 20th century plus (C20C+) detection and attribution (D&A) project, we show that the frequency and intensity of extreme precipitation events have increased in India during the last few decades. Along with the extreme precipitation, dew point temperature has also increased during 1979–2015. The scaling relationship between extreme precipitation and dew point temperature shows a super (more than 7% increase per unit rise in dew point temperature) Clausius-Clapeyron (C-C) relationship for the majority of south India. Moreover, southern and central India show a higher (10%/°C) scaling relationship than north India (3.5%/°C). Our analysis using the Hist (historic) and HistNat (historic natural) simulations from the CMIP5 and C20C+ projects confirms an increase in the frequency of extreme precipitation events under the anthropogenic warming. Moreover, we show that 1–5 day precipitation maxima at 5–500 year return period increases (10–30%) under the anthropogenic warming. The frequency of precipitation extremes is projected to rise more prominently in southern and central India in the mid and end of the 21st century under the representative concentration pathway (RCP) 8.5. Our results show a significant contribution of anthropogenic warming in the rise of the frequency of extreme precipitation, which has implications for infrastructure, agriculture, and water resources in India.
233 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
01 Jan 2013
TL;DR: In this paper, a summary of issues to assist policymakers, a technical summary, and a list of frequently-asked questions are presented, with an emphasis on physical science issues.
Abstract: Report summarizing climate change issues in 2013, with an emphasis on physical science. It includes a summary of issues to assist policymakers, a technical summary, and a list of frequently-asked questions.
7,858 citations
TL;DR: It will be substantially harder to quantify the range of possible changes in the hydrologic cycle than in global-mean temperature, both because the observations are less complete and because the physical constraints are weaker.
Abstract: What can we say about changes in the hydrologic cycle on 50-year timescales when we cannot predict rainfall next week? Eventually, perhaps, a great deal: the overall climate response to increasing atmospheric concentrations of greenhouse gases may prove much simpler and more predictable than the chaos of short-term weather. Quantifying the diversity of possible responses is essential for any objective, probability-based climate forecast, and this task will require a new generation of climate modelling experiments, systematically exploring the range of model behaviour that is consistent with observations. It will be substantially harder to quantify the range of possible changes in the hydrologic cycle than in global-mean temperature, both because the observations are less complete and because the physical constraints are weaker.
2,267 citations
TL;DR: It is shown that human-induced increases in greenhouse gases have contributed to the observed intensification of heavy precipitation events found over approximately two-thirds of data-covered parts of Northern Hemisphere land areas.
Abstract: A significant effect of anthropogenic activities has already been detected in observed trends in temperature and mean precipitation. But to date, no study has formally identified such a human fingerprint on extreme precipitation — an increase in which is one of the central theoretical expectations for a warming climate. Seung-Ki Min and colleagues compare observations and simulations of rainfall between 1951 and 1999 in North America, Europe and northern Asia. They find a statistically significant effect of increased greenhouse gases on observed increases in extreme precipitation events over much of the Northern Hemisphere land area. A significant effect of anthropogenic activities has already been detected in observed trends in temperature and mean precipitation. But so far, no study has formally identified such a human fingerprint on extreme precipitation — an increase in which is one of the central theoretical expectations for a warming climate. This study compares observations and simulations and detects a statistically significant effect of increased greenhouse gases on observed increases in extreme precipitation events over much of the Northern Hemisphere land area. Extremes of weather and climate can have devastating effects on human society and the environment1,2. Understanding past changes in the characteristics of such events, including recent increases in the intensity of heavy precipitation events over a large part of the Northern Hemisphere land area3,4,5, is critical for reliable projections of future changes. Given that atmospheric water-holding capacity is expected to increase roughly exponentially with temperature—and that atmospheric water content is increasing in accord with this theoretical expectation6,7,8,9,10,11—it has been suggested that human-influenced global warming may be partly responsible for increases in heavy precipitation3,5,7. Because of the limited availability of daily observations, however, most previous studies have examined only the potential detectability of changes in extreme precipitation through model–model comparisons12,13,14,15. Here we show that human-induced increases in greenhouse gases have contributed to the observed intensification of heavy precipitation events found over approximately two-thirds of data-covered parts of Northern Hemisphere land areas. These results are based on a comparison of observed and multi-model simulated changes in extreme precipitation over the latter half of the twentieth century analysed with an optimal fingerprinting technique. Changes in extreme precipitation projected by models, and thus the impacts of future changes in extreme precipitation, may be underestimated because models seem to underestimate the observed increase in heavy precipitation with warming16.
1,773 citations
TL;DR: In this paper, uncertainty arising from internal climate variability is investigated using a new 40-member ensemble conducted with the National Center for Atmospheric Research Community Climate System Model Version 3 (CCSM3) under the SRES A1B greenhouse gas and ozone recovery forcing scenarios during 2000-2060.
Abstract: Uncertainty in future climate change presents a key challenge for adaptation planning. In this study, uncertainty arising from internal climate variability is investigated using a new 40-member ensemble conducted with the National Center for Atmospheric Research Community Climate System Model Version 3 (CCSM3) under the SRES A1B greenhouse gas and ozone recovery forcing scenarios during 2000–2060. The contribution of intrinsic atmospheric variability to the total uncertainty is further examined using a 10,000-year control integration of the atmospheric model component of CCSM3 under fixed boundary conditions. The global climate response is characterized in terms of air temperature, precipitation, and sea level pressure during winter and summer. The dominant source of uncertainty in the simulated climate response at middle and high latitudes is internal atmospheric variability associated with the annular modes of circulation variability. Coupled ocean-atmosphere variability plays a dominant role in the tropics, with attendant effects at higher latitudes via atmospheric teleconnections. Uncertainties in the forced response are generally larger for sea level pressure than precipitation, and smallest for air temperature. Accordingly, forced changes in air temperature can be detected earlier and with fewer ensemble members than those in atmospheric circulation and precipitation. Implications of the results for detection and attribution of observed climate change and for multi-model climate assessments are discussed. Internal variability is estimated to account for at least half of the inter-model spread in projected climate trends during 2005–2060 in the CMIP3 multi-model ensemble.
1,337 citations