A Multiregion Assessment of Observed Changes in the Areal Extent of Temperature and Precipitation Extremes

Dittus, Andrea J.; Karoly, David J.; Lewis, Sophie C.; Alexander, Lisa V.

doi:10.1175/jcli-d-14-00753.1

Cited by 30 publications

(40 citation statements)

References 30 publications

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“…To interpolate data to a grid cell, in situ data from locations within a gauge-dependent decorrelation length scale are used. To take advantage of GHCNDEX but alleviate data gaps, we use a merged product (GHCNDEX-merged) that supplements GHCNDEX with HadEX2 where data in the former are missing [Dittus et al, 2015]. The Global Historical Climatology Network's (GHCN's) daily precipitation data set is a rain gauge product that covers a substantial amount of the global land surface [Menne et al, 2012] and is largely independent of the rain gauge networks used in HadEX2.…”

Section: Methodsmentioning

confidence: 99%

How much does it rain over land?

Herold

Alexander

Donat

et al. 2016

Geophysical Research Letters

126

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Despite the availability of several observationally constrained data sets of daily precipitation based on rain gauge measurements, remote sensing, and/or reanalyses, we demonstrate a large disparity in the quasi‐global land mean of daily precipitation intensity. Surprisingly, the magnitude of this spread is similar to that found in the Coupled Model Intercomparison Project Phase 5 (CMIP5). A weakness of reanalyses and CMIP5 models is their tendency to over simulate wet days, consistent with previous studies. However, there is no clear agreement within and between rain gauge and remotely sensed data sets either. This large discrepancy highlights a shortcoming in our ability to characterize not only modeled daily precipitation intensities but even observed precipitation intensities. This shortcoming is partially reconciled by an appreciation of the different spatial scales represented in gridded data sets of in situ precipitation intensities and intensities calculated from gridded precipitation. Unfortunately, the spread in intensities remains large enough to prevent us from satisfactorily determining how much it rains over land.

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Section: Methodsmentioning

confidence: 99%

How much does it rain over land?

Herold

Alexander

Donat

et al. 2016

Geophysical Research Letters

126

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“…To facilitate the investigation of observed and projected changes in climate extremes, the Expert Team on Climate Change Detection and Indices (ETCCDI) (Klein Tank et al, 2009) defined a set of indices for describing extreme events, which have been widely used to investigate climate extremes using observations (e.g. You et al, 2011;Donat et al, 2013;Dittus et al, 2015;Sun et al, 2016a) and simulations (e.g. Fischer et al, 2013;Kharin et al, 2013;Sillmann et al, 2013aSillmann et al, , 2013bZhou et al, 2014;Sun, 2015a, 2015b;Jiang et al, 2015;Sun et al, 2016b).…”

Section: Introductionmentioning

confidence: 99%

Projected signals in climate extremes over China associated with a 2 °C global warming under two RCP scenarios

Sui

Lang

Jiang

2018

Intl Journal of Climatology

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Using daily output from 29 climate models provided by the Coupled Model Intercomparison Project Phase 5, we project signals in 12 extreme temperature indices and 12 extreme precipitation indices relative to 1986–2005 over China associated with a 2 °C global warming above pre‐industrial levels under representative concentration pathways 4.5 (RCP4.5) and 8.5 (RCP8.5). The model output reflects the following projected changes: (1) It is robust and statistically significant that warm extremes are more frequent, more persistent, and more intense than those during the baseline period of 1986–2005, and local signals emerge from natural internal variability over most of China. In particular, southern China faces severe heat stress in summer based on warm extreme indices. (2) It is robust and statistically significant that there are fewer cold extremes in China. Most models show no significant changes in the longest duration and intensity of most cold extremes in southern China and northwest China. (3) The multi‐model median shows that more frequent and more intense wet extremes that deliver greater amounts of extreme precipitation occur in China, with a regional mean increase of 16.7–42.8 mm (8–42%) in total amount of annual wet extremes, but these changes are not significant and do not exceed natural internal variability over most of the country. Spatially, the Tibetan Plateau and northeast China have robust and significant changes in part of precipitation extremes, and some changes begin to emerge from natural internal variability at local scale. There are benefits to limiting global warming for China, including less frequent and less persistent warm extremes when comparing 1.5 °C with 2 °C of global warming and a later occurrence of significant changes in climate extremes when compared an intermediate mitigation scenario RCP4.5 with a high emission scenario RCP8.5.

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“…Climate change observed in recent years is associated primarily with increasing global temperature, but there is evidence that the hydrological cycle is affected as well. Analyses of observed precipitation data show increases in mean precipitation in the Tropics and high latitudes and decreases in the subtropics (Frich et al, 2002;Alexander et al, 2006), and intensification of precipitation even in regions where mean precipitation declines (Alexander et al, 2006;Donat et al, 2013;Madsen et al, 2014;Dittus et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Climate change scenarios of convective and large‐scale precipitation in the Czech Republic based on EURO‐CORDEX data

Rulfová

Beranová

Kyselý

2016

Intl Journal of Climatology

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There is growing evidence that the hydrological cycle is affected by climate change. Many studies have dealt with evaluation of precipitation characteristics in regional climate models (RCMs) and their projected changes. However, little attention has been given to possible differences between scenarios of convective and stratiform precipitation and changes in their proportions on total amounts, although climate models simulate convective (subgrid) and stratiform (large‐scale) precipitation separately through deep (precipitating) convection and large‐scale precipitation parameterizations. In this study, we analyse outputs of four RCMs (CCLM, HIRHAM, RACMO2, and RCA4) from the EURO‐CORDEX project. The RCM simulations for 1989–2008 driven by ERA‐Interim reanalysis with two horizontal resolutions (0.44° and 0.11°) are evaluated against observed data in Central Europe, and projected changes of precipitation characteristics (2071–2100 vs 1971–2000) simulated by the RCMs with 0.11° horizontal resolution driven by the EC‐EARTH global climate model are then examined. We find that mean convective and large‐scale precipitation amounts tend to increase in all seasons except summer when large‐scale precipitation amounts decrease. Extreme precipitation is projected to increase in the late 21st century time slice for both convective and large‐scale precipitation. The changes of precipitation characteristics are more pronounced in simulations driven by the RCP8.5 scenario, with a larger increase of temperature, and these changes are larger for precipitation with higher intensity. Increasing proportion of convective precipitation in summer and generally increasing intensity of precipitation may have important consequences, e.g. for soil erosion, replenishment of soil moisture, and occurrence of flash floods and droughts.

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A Multiregion Assessment of Observed Changes in the Areal Extent of Temperature and Precipitation Extremes

Cited by 30 publications

References 30 publications

How much does it rain over land?

How much does it rain over land?

Projected signals in climate extremes over China associated with a 2 °C global warming under two RCP scenarios

Climate change scenarios of convective and large‐scale precipitation in the Czech Republic based on EURO‐CORDEX data

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