Tom K.R. Matthews

Communicating the deadly consequences of global warming for human heat stress

Significance Extremely hot weather can have deadly human consequences. As the climate warms, the frequency and intensity of such conditions are expected to increase—among the most certain negative impacts expected under global warming. Concerns about dangerous climate change have encouraged the international community to commit to limiting global temperature changes to below 2 °C above preindustrial. Although lauded as a great achievement to avoid dangerous climate change, we find that, even if such aspirations are realized, large increases in the frequency of deadly heat should be expected, with more than 350 million more megacity inhabitants afflicted by midcentury. Such conclusions underline the critical role for ambitious adaptation alongside these climate change mitigation targets. In December of 2015, the international community pledged to limit global warming to below 2 °C above preindustrial (PI) to prevent dangerous climate change. However, to what extent, and for whom, is danger avoided if this ambitious target is realized? We address these questions by scrutinizing heat stress, because the frequency of extremely hot weather is expected to continue to rise in the approach to the 2 °C limit. We use analogs and the extreme South Asian heat of 2015 as a focusing event to help interpret the increasing frequency of deadly heat under specified amounts of global warming. Using a large ensemble of climate models, our results confirm that global mean air temperature is nonlinearly related to heat stress, meaning that the same future warming as realized to date could trigger larger increases in societal impacts than historically experienced. This nonlinearity is higher for heat stress metrics that integrate the effect of rising humidity. We show that, even in a climate held to 2 °C above PI, Karachi (Pakistan) and Kolkata (India) could expect conditions equivalent to their deadly 2015 heatwaves every year. With only 1.5 °C of global warming, twice as many megacities (such as Lagos, Nigeria, and Shanghai, China) could become heat stressed, exposing more than 350 million more people to deadly heat by 2050 under a midrange population growth scenario. The results underscore that, even if the Paris targets are realized, there could still be a significant adaptation imperative for vulnerable urban populations.

Transferability of hydrological models and ensemble averaging methods between contrasting climatic periods

Understanding hydrological model predictive capabilities under contrasting climate conditions enables more robust decision making. Using Differential Split Sample Testing (DSST), we analyze the performance of six hydrological models for 37 Irish catchments under climate conditions unlike those used for model training. Additionally, we consider four ensemble averaging techniques when examining interperiod transferability. DSST is conducted using 2/3 year noncontinuous blocks of (i) the wettest/driest years on record based on precipitation totals and (ii) years with a more/less pronounced seasonal precipitation regime. Model transferability between contrasting regimes was found to vary depending on the testing scenario, catchment, and evaluation criteria considered. As expected, the ensemble average outperformed most individual ensemble members. However, averaging techniques differed considerably in the number of times they surpassed the best individual model member. Bayesian Model Averaging (BMA) and the Granger-Ramanathan Averaging (GRA) method were found to outperform the simple arithmetic mean (SAM) and Akaike Information Criteria Averaging (AICA). Here GRA performed better than the best individual model in 51%–86% of cases (according to the Nash-Sutcliffe criterion). When assessing model predictive skill under climate change conditions we recommend (i) setting up DSST to select the best available analogues of expected annual mean and seasonal climate conditions; (ii) applying multiple performance criteria; (iii) testing transferability using a diverse set of catchments; and (iv) using a multimodel ensemble in conjunction with an appropriate averaging technique. Given the computational efficiency and performance of GRA relative to BMA, the former is recommended as the preferred ensemble averaging technique for climate assessment.

Humid heat and climate change

Extreme heat events cause significant societal impacts, prompting much concern and research about possible changes to their frequency and intensity as the climate warms. However, to date, extremes in air temperature have been emphasised at the expense of ‘heat-humidity’ indices, measures which incorporate the effect of atmospheric latent heat content on heat stress and provide a more complete picture of the thermal environment for human thermoregulation. This progress report restores balance by reviewing recent developments in the understanding of how heat-humidity indices have changed, and may continue to, as the climate warms further. The literature indicates that a concurrent rise in temperature and absolute humidity has already increased the frequency of potentially deadly conditions, and has reduced labour potential worldwide. More serious consequences may result if mitigation efforts are unsuccessful. The energetic basis of a heat-humidity perspective has permitted researchers to identify, for example, that by the end of the century, substantial parts of the Earth’s surface may be too hot and humid for human thermoregulation. Such consequences are avoided for less pessimistic scenarios of climate warming, but the societal impacts may still be very severe, as densely-populated low-latitude environments emerge as particularly at risk when a humid heat perspective is adopted. Counter to air temperature, changes in mean heat-humidity indices are actually amongst the largest worldwide at lower latitudes, where only small increases in the mean may be required to substantially enhance the frequency of dangerous conditions. The report concludes by outlining areas requiring improved process understanding, and it highlights the urgent role for societal adaptation if the worst impacts from rising humid heat are to be avoided.