Accounting for Pacific climate variability increases projected global warming.

Observational constraint methods based on the relationship between the past global warming trend and projected warming across climate models were used to reduce uncertainties in projected warming by the Intergovernmental Panel on Climate Change. Internal climate variability in the eastern tropical Pacific associated with the so-called pattern effect weakens this relationship and has reduced the observed warming trend over recent decades. Here we show that regressing out this variability before applying the observed global mean warming trend as a constraint results in higher and narrower twenty-first century warming ranges than other methods.

An Observational Constraint on Aviation-Induced Cirrus From the COVID-19-Induced Flight Disruption.

Global aviation dropped precipitously during the covid-19 pandemic, providing an unprecedented opportunity to study aviation-induced cirrus (AIC). AIC is believed to be responsible for over half of aviation-related radiative forcing, but until now, its radiative impact has only been estimated from simulations. Here, we show that satellite observations of cirrus cloud do not exhibit a detectable global response to the dramatic aviation reductions of spring 2020.

The H domain of syntaxin 3 is a ubiquitin binding domain.

Syntaxins are a family of membrane-anchored SNARE proteins that are essential components required for membrane fusion in eukaryotic intracellular membrane trafficking pathways. Syntaxins contain an N-terminal regulatory domain, termed the H domain that is not highly conserved at the primary sequence level but folds into a three-helix bundle that is structurally conserved among family members. The syntaxin H domain has previously been found to be structurally very similar to the GAT domain present in GGA family members and related proteins that are otherwise completely unrelated to syntaxins.

Bispectral unfolding of the skewness of correlated additive and multiplicative noise processes.

Correlated additive and multiplicative (CAM) noise processes are well-established as general "null hypothesis" models of non-Gaussian variability in atmospheric and oceanic quantities. In this study, analytic expressions for the bispectral density (which partitions the third statistical moment into triad frequency interactions in a manner analogous to the partitioning of variance by the spectral density) are developed for discrete and continuous-time CAM processes. It is then demonstrated that under lowpass filtering, while the absolute skewness of a discrete-time CAM process may increase or decrease with decreasing cutoff frequency, the absolute skewness of continuous-time CAM processes decreases monotonically.

Reduced α-stable dynamics for multiple time scale systems forced with correlated additive and multiplicative Gaussian white noise.

Stochastic averaging problems with Gaussian forcing have been the subject of numerous studies, but far less attention has been paid to problems with infinite-variance stochastic forcing, such as an α-stable noise process. It has been shown that simple linear systems driven by correlated additive and multiplicative (CAM) Gaussian noise, which emerge in the context of reduced atmosphere and ocean dynamics, have infinite variance in certain parameter regimes. In this study, we consider the stochastic averaging of systems where a linear CAM noise process in the infinite variance parameter regime drives a comparatively slow process.

How close are time series to power tail Lévy diffusions?

This article presents a new and easily implementable method to quantify the so-called coupling distance between the law of a time series and the law of a differential equation driven by Markovian additive jump noise with heavy-tailed jumps, such as α-stable Lévy flights. Coupling distances measure the proximity of the empirical law of the tails of the jump increments and a given power law distribution. In particular, they yield an upper bound for the distance of the respective laws on path space.

Optimally coherent sets in geophysical flows: a transfer-operator approach to delimiting the stratospheric polar vortex.

The "edge" of the Antarctic polar vortex is known to behave as a barrier to the meridional (poleward) transport of ozone during the austral winter. This chemical isolation of the polar vortex from the middle and low latitudes produces an ozone minimum in the vortex region, intensifying the ozone hole relative to that which would be produced by photochemical processes alone. Observational determination of the vortex edge remains an active field of research.

Transport in time-dependent dynamical systems: finite-time coherent sets.

We study the transport properties of nonautonomous chaotic dynamical systems over a finite-time duration. We are particularly interested in those regions that remain coherent and relatively nondispersive over finite periods of time, despite the chaotic nature of the system. We develop a novel probabilistic methodology based upon transfer operators that automatically detect maximally coherent sets.

Stochastic models of the meridional overturning circulation: time scales and patterns of variability.

The global meridional overturning circulation (MOC) varies over a wide range of space and time scales in response to fluctuating 'weather' perturbations that may be modelled as stochastic forcing. This study reviews model studies of the effects of climate noise on decadal to centennial MOC variability, on transitions between the MOC regimes and on the dynamics of Dansgaard-Oeschger events characteristic of glacial periods.