Robust projections of combined humidity and temperature extremes
E. M. Fischer* and R. Knutti
Impacts of climate change such as the effects on human discomfort, morbidity and mortality often depend on multiple climate variables. Thus, a comprehensive impact assessment is challenging and uncertainties in all contributing variables need to be taken into account. Here we show that uncertainties in some impact-relevant metrics such as extremes of health indicators are substantially smaller than generally anticipated. Models that project greater warming also show a stronger reduction in relative humidity. This joint behaviour of uncertainties is particularly pronounced in mid-continental land regions of the subtropics and mid-latitudes where the greatest changes in heat extremes are expected. The uncertainties in health-related metrics combining temperature and humidity are much smaller than if uncertainties in the two variables were independent. Such relationships also exist under present-day conditions where the effect of model biases in temperature and relative humidity largely cancel for combined quantities. Our results are consistent with thermodynamic first principles. More generally, the findings reveal a large potential for joint assessment of projection uncertainties in different variables used in impact studies.
During recent major summer heatwaves, such as in 2003 in central and western Europe and 2010 in Russia, the mortality locally increased by tens of thousands of additional casualties1. Apart from excessive temperature anomalies, other factors such as humidity, radiation, low winds and air pollution potentially contributed to the enhanced mortality and more generally to the human discomfort. Likewise, many other socio-economic or ecological climate impacts, for example on agricultural production, forest fires, glacier retreat, river runoff or energy production, depend on more than one climate variable. Consequently, for a comprehensive assessment of climate change impacts it is imperative to take into account the uncertainties in all contributing variables.
In many cases the different climate variables are linked through first principles or basic mechanisms that are well understood, for example, warmer air being able to hold more moisture, or soil moisture variations affecting the partitioning of sensible and latent heat. The relationships depend on the temporal resolution of the variables considered and may vary across different quantiles2,3. In many cases they have been found to be relatively well captured by models, for example, for temperature and precipitation4,5. Despite the knowledge about the relationships across variables, they are often ignored in the context of projections. The Fourth Assessment Report of the Intergovernmental Panel on Climate Change6, for example, provides projections of many variables, but each of those is discussed separately. Recently some studies have quantified how relationships across variables evolve into the future7,8 or how their often correlated uncertainties can be transformed into joint probabilistic projections9,10. However, there is a serious lack of research addressing joint projections in variables other than temperature and precipitation.
NATURE CLIMATE CHANGE LETTERS
PUBLISHED ONLINE: 2 SEPTEMBER 2012 | DOI: 10.1038/NCLIMATE1682
ADVANCE ONLINE PUBLICATION j www.nature.com/natureclimatechange
