Climate dynamics

Abstract:

Sea ice and snow are crucial components of the cryosphere and the climate system. Both sea ice and spring snow in the Northern Hemisphere (NH) have been decreasing at an alarming rate in a changing climate. Changes in NH sea ice and snow have been linked with a variety of climate and weather extremes including cold spells, heatwaves, droughts and wildfires. Understanding of these linkages will benefit the predictions of climate and weather extremes. However, existing work on this has been largely fragmented and is subject to large uncertainties in physical pathways and methodologies. This has prevented further substantial progress in attributing climate and weather extremes to sea ice and snow change, and will potentially risk the loss of a critical window for effective climate change mitigation. In this review, we synthesize the current progress in attributing climate and weather extremes to sea ice and snow change by evaluating the observed linkages, their physical pathways and uncertainties in these pathways, and suggesting ways forward for future research efforts. By adopting the same framework for both sea ice and snow, we highlight their combined influence and the cryospheric feedback to the climate system. We suggest that future research will benefit from improving observational networks, addressing the causality and complexity of the linkages using multiple lines of evidence, adopting large-ensemble approaches and artificial intelligence, achieving synergy between different methodologies/disciplines, widening the context, and coordinated international collaboration.

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.