Predictability of weather and climate

Abstract:

In 2021, Canada experienced one of the most extreme heatwaves ever seen anywhere on the globe. We use a weather forecast model to attribute health impacts to climate change. We simulate the heatwave as a present-day forecast, a preindustrial-counterfactual scenario, and a future-counterfactual scenario. Despite the extremeness of the event, our analysis shows that, under current climate conditions, we could have still seen up to 30% more heat-related deaths than the number observed. We show that between 11 and 15% of the observed human mortality was attributable to climate change during this event, depending on the conditioning of the atmospheric circulation. We also show that, had "the same event" occurred in the future, the mortality toll is nonlinear compared with the warming trend, and so the future attribution would be even more extreme, 16 to 31%. We argue that this method gives particularly reliable impact attribution results and is therefore strongly defensible in decision-making and legal settings.

Abstract:

<jats:title>Abstract</jats:title> <jats:p>Atmospheric flow underpins virtually all meteorological and climatological phenomena, yet extracting meaningful features from its dynamics remains a major scientific challenge due to its high dimensionality, multi-scale behaviour, and inherent nonlinearity. In this study, we investigate the potential of a network-based framework to reveal the relationships between distinct flow structures. Specifically, we apply three techniques, independent of any particular phenomenon or model, to explore patterns of coherence and information transfer, vortical interactions, and Lagrangian coherent structures. We assess their utility using a rotating shallow-water model of the stratospheric polar vortex, which reproduces key aspects of wintertime dynamics, including sudden stratospheric warming split events. Our results support three central claims. First, the transformation of fluid flow data into a network representation preserves essential dynamical information. Second, this representation enables a more accessible and structured analysis of the underlying dynamical structures. Third, multiple types of networks can be constructed from atmospheric flow data, each offering distinct yet complementary insights into the system’s collective behaviour. Together, these findings highlight the potential of network-based approaches as valuable tools in atmospheric research.</jats:p>

Abstract:

Abstract. This study investigates Quasi-Biennial Oscillation (QBO) teleconnections and their modulation by the El Niño–Southern Oscillation (ENSO) using a multi-model ensemble from the Atmospheric Processes And their Role in Climate (APARC) QBO initiative (QBOi). Analyzing observed QBO–ENSO teleconnections is challenging because it is difficult to separate the respective influences of QBO and ENSO outside the QBO region due to aliasing in the historical record. To isolate these signals, simulations were conducted with annually repeating prescribed sea-surface temperatures (SSTs) representing idealized El Niño and La Niña conditions (the QBOi EN and LN experiments, respectively), and results are compared with the QBOi control experiment (CTL) under ENSO-neutral conditions. The strength of the Holton-Tan relationship between the phase of the QBO and the strength of the polar vortex seen in observations is reproduced in fewer than three models in CTL and by one model in EN. In LN, three out of nine models reproduce the observed Holton–Tan relationship, but with less than half of the observed amplitude. In the Arctic winter climate, sudden stratospheric warmings (SSWs) occur more frequently in EN than in LN; however, unlike in observations, there is no discernible difference in SSW frequency between QBO westerly (QBO-W) and QBO easterly (QBO-E) phases. The Asia-Pacific subtropical jet (APJ) shifts significantly equatorward during QBO-W compared to QBO-E in observations, but this shift is not robust across models, regardless of ENSO phases. In the tropics, the sign and spatial pattern of the QBO precipitation response vary widely across models and experiments, indicating that any potential QBO signal is strongly modulated by the prevailing ENSO phases. Overall, the QBOi models exhibit unrealistically weak QBO wind amplitudes in the lower stratosphere, which may explain the weak polar vortex and APJ responses, as well as the weak precipitation signals in the tropics. In contrast, the QBO teleconnection with the Walker circulation during boreal summer and autumn shows consistent signals in both observations and most models. Specifically, the QBO-W phase is characterized by upper-level westerly and lower-level easterly anomalies over the Indian Ocean–Maritime Continent relative to QBO-E, although the amplitude and timing of these anomalies remain model-dependent. Notably, the influence of QBO phase on the Walker circulation appears insensitive to the ENSO phase.

Abstract:

Plain Language Summary: The Quasi‐biennial Oscillation (QBO) dominates the variability of the tropical atmosphere between 16 and 50 km above the surface. It manifests most strongly as downward propagating zonal wind variations exceeding 25 m/s with an average period of ∼ ${\sim} $ 28 months. Twice in the past 10 years the QBO regular phase evolution has been disrupted after 60 years of no disruptions, motivating our analysis of the role of greenhouse gases, aerosols, ozone, volcanic eruptions, and solar variability for historical changes in the QBO. We find prominent roles for four of these five external forcings, and specifically both rising greenhouse gases and volcanic eruptions help induce disruption events.

Abstract:

Plain Language Summary: Climate model emulators are approximations of climate models that provide a quick and low‐cost alternative to exploring future climate scenarios. Traditional emulators generate large amounts of data covering the whole world, which still need to be condensed when exploring local and regional impacts. In this paper, we propose a new emulator based off image compression techniques. The setup allows one to “zoom” in and out from global to regional to local levels, providing user‐relevant information across scales. It furthermore conserves both large‐scale and local features and can be run in minutes. Given its versatile framework, the approach is easily extendable to new variables, and in this paper we demonstrate its ability to jointly capture temperature and relative humidity.