Climate dynamics

Abstract:

The climatological atmospheric circulation is key to establishing the tropical “pattern effect”, whereby cloud feedbacks induced by sea surface temperature (SST) warming depend on the spatial structure of that warming. But how patterned warming‐induced circulation changes affect cloud responses is less clear. Here we use idealized simulations with prescribed SST perturbations to understand the contributions to changes in tropical‐mean cloud radiative effects (CRE) from different circulation regimes. We develop a novel framework based on moist static energy to understand the circulation response, targeting in particular the bulk circulation metric of ascent fraction. Warming concentrated in regions of ascent leads to a strong “upped‐ante” effect and spatial contraction of the ascending region. Our framework reveals substantial contributions to tropical‐mean CRE changes not only from traditional “pattern effect” regimes, but also from the intensification of convection in ascent regions as well as a smaller contribution from cloud changes in convective margins.

Abstract:

Tropical cloud feedbacks are an important source of uncertainty in estimates of climate sensitivity. The extent to which changes in atmospheric circulation contribute to these feedbacks remains an open question. Here, all-sky radiative flux observations and an atmospheric reanalysis are used to estimate tropical cloud feedbacks from multi-decadal trends (1985 – 2020) in cloud radiative effect and surface temperature. We decompose the observed feedbacks into dynamic and non-dynamic components to quantify the impact of circulation trends. Narrowing and strengthening of tropical ascent lead to substantial dynamic feedbacks on regional scales that are similar in magnitude to the non-dynamic feedbacks. However, as previously shown for high- and low-resolution climate models, large dynamic feedbacks in different circulation regimes are connected by the atmospheric mass budget and approximately cancel when averaged across the tropics due the quasi-linear relationship between cloud radiative effect and vertical velocity. This results in small dynamic contributions to the tropical-mean net, longwave and shortwave feedbacks. We suggest that this result will hold in future and thus that isolating the non-dynamic components associated with individual cloud types can provide important insights into the processes controlling the tropical-mean cloud feedback and its uncertainty. Additionally, we show that feedbacks estimated from multi-decadal trends differ from those estimated from inter-annual variability. We demonstrate that, for dynamic feedbacks, this is because changes are controlled by different mechanisms and this leads to a differing spatial distribution of temperature sensitivity. Finally we provide new estimates of the uncertain combined tropical anvil area and albedo feedback using both multi-decadal trends and inter-annual variability.

Abstract:

<jats:title>Abstract</jats:title> <jats:p>Arctic amplification (AA), the phenomenon by which Arctic surface temperatures are warming faster than the global average, may have significant unexplored impacts on temperature-related mortality in human populations across Canada. We explore the role of Arctic sea ice loss, a key driver of AA, in changing cold temperature extremes across Canada and their impact on human mortality. We use a multi-model ensemble of climate simulations from the Polar Amplification Model Intercomparison Project and a distributed lag nonlinear mortality model in 27 regions covering Canada to quantify the role of Arctic sea ice loss in changing human mortality in the cold season. We find that despite a robust increase in 5th percentile temperatures across eastern Canada, there is no detectable decrease in mortality associated with the most extreme cold, due to mortality in many regions having low sensitivity to warming of cold extremes. The study attributes the temperature-related mortality impact of a physical process, namely Arctic sea ice loss, and highlights Canada’s robust adaptation to extreme cold.</jats:p>