Recent Very Hot Summers in Northern Hemispheric Land Areas Measured by Wet Bulb Globe Temperature Will Be the Norm Within 20 Years

Li, Chao; Zhang, Xuebin; Zwiers, Francis W.; Fang, Yuanyuan; Michalak, A. M.

doi:10.1002/2017ef000639

Cited by 47 publications

(44 citation statements)

References 38 publications

(72 reference statements)

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“…The hottest month was identified based on the climatology of ERA-Interim monthly temperature data. Although the effectiveness of bias adjustment is typically evaluated outside the calibration period (Maraun, 2013), here we focus our analysis completely on the selected 15-year period. This allows for a separate assessment of the effect of bias adjustment on univariate versus multivariate impacts independently from other effects such as cross-validation error.…”

Section: Datamentioning

confidence: 99%

The effect of univariate bias adjustment on multivariate hazard estimates

2019

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Abstract. Bias adjustment is often a necessity in estimating climate impacts because impact models usually rely on unbiased climate information, a requirement that climate model outputs rarely fulfil. Most currently used statistical bias-adjustment methods adjust each climate variable separately, even though impacts usually depend on multiple potentially dependent variables. Human heat stress, for instance, depends on temperature and relative humidity, two variables that are often strongly correlated. Whether univariate bias-adjustment methods effectively improve estimates of impacts that depend on multiple drivers is largely unknown, and the lack of long-term impact data prevents a direct comparison between model outputs and observations for many climate-related impacts. Here we use two hazard indicators, heat stress and a simple fire risk indicator, as proxies for more sophisticated impact models. We show that univariate bias-adjustment methods such as univariate quantile mapping often cannot effectively reduce biases in multivariate hazard estimates. In some cases, it even increases biases. These cases typically occur (i) when hazards depend equally strongly on more than one climatic driver, (ii) when models exhibit biases in the dependence structure of drivers and (iii) when univariate biases are relatively small. Using a perfect model approach, we further quantify the uncertainty in bias-adjusted hazard indicators due to internal variability and show how imperfect bias adjustment can amplify this uncertainty. Both issues can be addressed successfully with a statistical bias adjustment that corrects the multivariate dependence structure in addition to the marginal distributions of the climate drivers. Our results suggest that currently many modeled climate impacts are associated with uncertainties related to the choice of bias adjustment. We conclude that in cases where impacts depend on multiple dependent climate variables these uncertainties can be reduced using statistical bias-adjustment approaches that correct the variables' multivariate dependence structure.

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Section: Datamentioning

confidence: 99%

The effect of univariate bias adjustment on multivariate hazard estimates

2019

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“…Using such a scaling approach to constrain the future projections is based on the assumption that if a model overestimates a magnitude of historical climate change, the future climate change will be overestimated in a proportional amount (Stott and Kettleborough 2002, Mueller et al 2016, Shiogama et al 2016, Li et al 2017. This approach can be applied to both global mean changes as well as spatio-temporal changes (Shiogama et al 2016) under scenarios where radiative forcing is increasing over time, and the relative contribution of the anthropogenic forcing remains constant over time, which is not the case in all RCP scenarios (Li et al 2017). We applied this approach to the Representative Concentration Pathway (RCP) 8.5 scenario (Vuuren et al 2011), which entails high levels of greenhouse-gas radiative forcings that continually increase over time, and RCP 4.5 scenario, where greenhouse-gas radiative forcings increase at a lower rate and start to stabilize before the year 2100 ( figure S7).…”

Section: Anthropogenic Contributions To Future Thermosteric Sea Levelmentioning

confidence: 99%

Quantifying human contributions to past and future ocean warming and thermosteric sea level rise

Tokarska

Hegerl

Schurer

et al. 2019

Environ. Res. Lett.

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More than 90% of the Earth's energy imbalance is stored by the ocean. While previous studies have shown that changes in the ocean warming are detectable and distinct from internal variability of the climate system, an estimate of separate contributions by natural and individual anthropogenic forcings (such as greenhouse gases and aerosols) remains outstanding. Here we investigate anthropogenic and greenhouse-gas contributions to past ocean warming, and estimate their contributions to future sea level rise by the year 2100. By applying detection and attribution framework (regularized optimal fingerprinting), we show that ocean warming in the historical period is detectable and attributable to contributions from the aggregate anthropogenic forcing as well as greenhouse gas forcing alone. We also discuss the role of natural forcing on the ocean volumeaveraged temperature and examine the impact of volcanic activity from the three main volcanoes occurring in the historical period 1955-2012. Our results suggest that estimated anthropogenic and greenhouse-gas contributions to ocean warming are consistent with observations, and observationally-constrained future thermosteric sea level rise projections support the central and lower part of the multi-model mean projection range distribution.

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“…Exact identification of 0.5°C-added hot spots matters for guiding adaptation and mitigation priorities toward regions with the greatest need, in a post-Paris era (Piontek et al, 2014). However, other quantities including historically unprecedented events/types/regimes of extremes and their emergence timings are equivalently or even more relevant to characterize 0.5°C-added hot spots and yet have been much less considered (Li et al, 2017;Scherer & Diffenbaugh, 2014;Williams et al, 2007;Zampieri et al, 2019). However, other quantities including historically unprecedented events/types/regimes of extremes and their emergence timings are equivalently or even more relevant to characterize 0.5°C-added hot spots and yet have been much less considered (Li et al, 2017;Scherer & Diffenbaugh, 2014;Williams et al, 2007;Zampieri et al, 2019).…”

Section: 1029/2019ef001202mentioning

confidence: 99%

“…Frequency and intensity of extremes are preferentially taken as representative quantities in existing studies. However, other quantities including historically unprecedented events/types/regimes of extremes and their emergence timings are equivalently or even more relevant to characterize 0.5°C-added hot spots and yet have been much less considered (Li et al, 2017;Scherer & Diffenbaugh, 2014;Williams et al, 2007;Zampieri et al, 2019).…”

Section: 1029/2019ef001202mentioning

confidence: 99%

Half‐a‐Degree Matters for Reducing and Delaying Global Land Exposure to Combined Daytime‐Nighttime Hot Extremes

et al. 2019

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The Paris Agreement has motivated rapid analysis differentiating changes in frequency/intensity of weather and climate extremes in 1.5 versus 2°C warmer worlds. However, implications of these global warming levels on locations, spatial scales, and emergence timings of hot spots to extremes are more relevant to policy-making but remain strikingly under-addressed. Based on a bivariate definitional framework, we show that compared to 2°C, the 1.5°C target could avoid a transition of prevailing type of summertime hot extremes from daytime-/nighttime-only events to combined daytime-nighttime hot extremes in approximately 18% of global continents and protect 14-26% of land areas from seeing over threefold-totenfold increases in occurrence of combined hot extremes. This half-a-degree reduction also matters for around 21% of global lands, mostly within the tropics, in constraining historically unprecedented combined hot extremes from becoming the new norm within just one to three decades ahead. By contrast, previous analyses based on univariate-defined hot days substantially underestimate the magnitude, areal extent, and emergence rate of 0.5°C-caused aggravation of summertime hot extremes. These projected changes of bivariate-classified hot extremes, therefore, underline not only the imperative but also the urgency of striving for the lower Paris target.Plain Language Summary Since the milestone Paris Agreement, policymakers are eager to know the extent to which and the time when their own regions will suffer from consequences associated with pertinent global warming levels (1.5 and 2°C). We show that even the aspirational 1.5°C target would still be translated into huge threats from summertime hot extremes to the tropics, as manifested by a type transition toward health-damaging daytime-nighttime combined heat and threefold-to-tenfold increases in its occurrence. Further rise to 2°C would put an extra 20% of global continents at risk from similar transitions and increases. Unexpectedly, despite involving substantial reduction in carbon emissions, the 2°C-compatible development pathway would bring about a rapidly emerging novel era of hot extremes for most tropical countries, where historically unprecedented daytime-nighttime combined heat will be registered every other year within the next one to three decades and thereafter. Our results highlight that the extra 0.5°C of global warming, from 1.5 to 2°C, would impose the earliest and severest heat-related consequences on the least-developed regions, whose adaptive capacity is unfortunately very limited.

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Recent Very Hot Summers in Northern Hemispheric Land Areas Measured by Wet Bulb Globe Temperature Will Be the Norm Within 20 Years

Cited by 47 publications

References 38 publications

The effect of univariate bias adjustment on multivariate hazard estimates

The effect of univariate bias adjustment on multivariate hazard estimates

Quantifying human contributions to past and future ocean warming and thermosteric sea level rise

Half‐a‐Degree Matters for Reducing and Delaying Global Land Exposure to Combined Daytime‐Nighttime Hot Extremes

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