Half a degree and rapid socioeconomic development matter for heatwave risk

Russo, Simone; Sillmann, Jana; Sippel, Sebastian; Barcikowska, Monika; Ghisetti, Claudia; Šmíd, Marek; O’Neill, Brian C.

doi:10.1038/s41467-018-08070-4

Cited by 101 publications

(65 citation statements)

References 33 publications

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“…King and Harrington (2018) indicated that the ratios of annual mean temperature differences (2.0°C minus 1.5°C) and the internal variability are larger in lower-income countries. Russo et al (2019) suggested that heatwave exposure and an illustrative heatwave risk index (the product of the probability of heatwave occurrence, exposure and a proxy for vulnerability) at the 1.5°C warming level for the population living in low development countries is expected to be greater than those at the 2°C warming level for the population living in very high development countries. Döll et al (2018) showed that the effect on ΔQ 7hf of meeting the 1.5°C goal rather than the 2.0°C would be felt more strongly in the low-income country groups than other country groups.…”

Section: Summary and Discussionmentioning

confidence: 99%

“…Some studies have suggested that the frequencies of hot days will increase more rapidly in the poorest countries in the tropics than in countries in mid-tohigh-latitude regions (Mahlstein et al 2011, Harrington et al 2016, Hoegh-Guldberg et al 2018. It has been suggested that 1.5°C-2°C differences of increases in heatwave exposure (Russo et al 2019), high streamflow (Döll et al 2018) and multi-sector (water, energy, food and environment) risks (Byers et al 2018) are larger for low-income countries/populations than high-income countries/populations.…”

Section: Introductionmentioning

confidence: 99%

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Limiting global warming to 1.5 °C will lower increases in inequalities of four hazard indicators of climate change

Shiogama

Hasegawa

Fujimori

et al. 2019

Environ. Res. Lett.

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Clarifying characteristics of hazards and risks of climate change at 2°C and 1.5°C global warming is important for understanding the implications of the Paris Agreement. We perform and analyze large ensembles of 2°C and 1.5°C warming simulations. In the 2°C runs, we find substantial increases in extreme hot days, heavy rainfalls, high streamflow and labor capacity reduction related to heat stress. For example, about half of the world's population is projected to experience a present day 1-in-10 year hot day event every other year at 2°C warming. The regions with relatively large increases of these four hazard indicators coincide with countries characterized by small CO 2 emissions, low-income and high vulnerability. Limiting global warming to 1.5°C, compared to 2°C, is projected to lower increases in the four hazard indicators especially in those regions.

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Section: Summary and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Limiting global warming to 1.5 °C will lower increases in inequalities of four hazard indicators of climate change

Shiogama

Hasegawa

Fujimori

et al. 2019

Environ. Res. Lett.

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“…Reliable forecasting of air temperature at 2 m above the land surface plays a significant role when preparing for potential weather‐related disasters, such as heat waves (i.e., maximum daytime air temperature) and cold spells (i.e., minimum nighttime air temperature). Extreme air temperatures can also cause various social and economic problems such as heat‐related disease and high energy consumption (Klinenberg, 2015; Russo et al, 2019). In particular, the increasing intensity, frequency and duration of extreme air temperatures during the summer season (Perkins et al, 2012), and the fact that more than half of the Earth's population now lives in cities (Schulze & Langenberg, 2014) suggest that accurate air temperature forecasting is essential for urban areas.…”

Section: Introductionmentioning

confidence: 99%

Comparative Assessment of Various Machine Learning‐Based Bias Correction Methods for Numerical Weather Prediction Model Forecasts of Extreme Air Temperatures in Urban Areas

Cho

Yoo

et al. 2020

Earth and Space Science

123

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Forecasts of maximum and minimum air temperatures are essential to mitigate the damage of extreme weather events such as heat waves and tropical nights. The Numerical Weather Prediction (NWP) model has been widely used for forecasting air temperature, but generally it has a systematic bias due to its coarse grid resolution and lack of parametrizations. This study used random forest (RF), support vector regression (SVR), artificial neural network (ANN) and a multi-model ensemble (MME) to correct the Local Data Assimilation and Prediction System (LDAPS; a local NWP model over Korea) model outputs of next-day maximum and minimum air temperatures (T maxtþ1 and T mintþ1 ) in Seoul, South Korea. A total of 14 LDAPS model forecast data, the daily maximum and minimum air temperatures of in-situ observations, and five auxiliary data were used as input variables. The results showed that the LDAPS model had an R 2 of 0.69, a bias of −0.85°C and an RMSE of 2.08°C for T maxtþ1 forecast, whereas the proposed models resulted in the improvement with R 2 from 0.75 to 0.78, bias from −0.16 to −0.07°C and RMSE from 1.55 to 1.66°C by hindcast validation. For forecasting T mintþ1 , the LDAPS model had an R 2 of 0.77, a bias of 0.51°C and an RMSE of 1.43°C by hindcast, while the bias correction models showed R 2 values ranging from 0.86 to 0.87, biases from −0.03 to 0.03°C, and RMSEs from 0.98 to 1.02°C. The MME model had better generalization performance than the three single machine learning models by hindcast validation and leave-one-station-out cross-validation.

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“…The most direct impacts of climate change are increases in the frequency and intensity of extreme weather events (or natural disasters), such as heatwaves, droughts, wildfire, storms, and sea‐level rise (Field, Barros, Stocker, & Dahe, ). Projected frequency of extreme heat waves at 1.5 or 2°C of warming is drastically higher for Africa, Latin America, Middle East, and some Southeast Asian countries than for other parts of the world (Russo et al., ). In particular, heatwaves in Africa have accelerated in the last few decades and are projected to occur regularly by 2040 if the current trend of emissions continues (Russo, Marchese, Sillmann, & Immé, ).…”

Section: Climate Change Impacts and Adaptation In Developing Countriesmentioning

confidence: 99%

Toward sustainable climate change adaptation

Yang

Liu

Wang

et al. 2020

J of Industrial Ecology

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Industrial ecology (IE) has made great contributions to climate change mitigation research, in terms of its systems thinking and solid methodologies such as life cycle assessment, material flow analysis, and environmentally extended input-output analysis. However, its potential contribution to climate change adaptation is unclear. Adaptation has become increasingly urgent in a continuously changing climate, especially in developing countries, which are projected to bear the brunt of climate-change-related damages. On the basis of a brief review of climate change impacts and adaptation literature, we suggest that IE can play an important role in the following two aspects.First, with the emphasis on a systems perspective, IE can help us determine how climate change interacts with our socio-economic system and how the interactions may aggravate (or moderate) its direct impacts or whether they may shift burden to other environmental impacts. Second, IE methodologies can help us quantify the direct and indirect environmental impacts of adaptation activities, identify mitigation opportunities, and achieve sustainable adaptation. Further, we find that substantial investment is needed to increase the resilience of infrastructure (e.g., transport, energy, and water supply) and agriculture in developing countries. Because these sectors are also the main drivers of environmental degradation, how to achieve sustainable climate-resilient infrastructure and agriculture in developing countries deserves special attention in future IE studies. Overall, IE thinking and methodologies have great potential to contribute to climate change adaptation research and policy questions, and exploring this growing field will, in turn, inspire IE development.

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Half a degree and rapid socioeconomic development matter for heatwave risk

Cited by 101 publications

References 33 publications

Limiting global warming to 1.5 °C will lower increases in inequalities of four hazard indicators of climate change

Limiting global warming to 1.5 °C will lower increases in inequalities of four hazard indicators of climate change

Comparative Assessment of Various Machine Learning‐Based Bias Correction Methods for Numerical Weather Prediction Model Forecasts of Extreme Air Temperatures in Urban Areas

Toward sustainable climate change adaptation

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