Predictability of weather and climate

Abstract:

Uncertainty in projections of future regional climate change remains large, driven by structural differences among Earth System Models and the influence of internal climate variability. Existing uncertainty-reduction approaches, including emergent constraints and Bayesian variants, primarily focus on forced climate responses derived from simple aggregate metrics, thereby requiring strong assumptions and exploiting only low-dimensional climate information. Here we propose a data-driven deep-learning framework that directly forecasts spatially and monthly resolved decadal mean climatologies of surface temperature anomalies from the 2030s to the 2090s, using only recent monthly trajectories spanning 1980-2025. The training ensemble contains 265 historical+SSP2-4.5 simulations, distributed across 40 ESMs from 25 different families (i.e., modelling centers) over which the cross validation is performed. The architecture couples pluri-annual to multi-decadal temporal convolutions with a spatial U-Net encoder-decoder and is evaluated on CMIP6 simulations using a leave-one-model-family-out cross-validation (LOMFO-CV) design to ensure generalisation across separately developed ESMs. Predictive uncertainty is quantified via LOMFO-CV errors, yielding conservative and reliable ranges that incorporate irreducible internal variability and systematic model shifts.To further evaluate the predictive capacity beyond the CMIP6 distribution, we evaluated the network on historical+SSP2-4.5 simulations from a recent HadGEM3-GC5 model hierarchy developed within the European Eddy-Rich ESMs (EERIE) project, the European contribution to HighResMIP2 for CMIP7. In particular, the eddy-rich GC5-HH configuration explicitly simulates mesoscale ocean dynamics that are absent in CMIP6-type models, providing a rigorous test of generalisation to richer and more realistic physical representations. Despite these substantial differences, the network successfully reproduces warming trajectories and future climate patterns for all three model configurations (GC5-LL, GC5-MM, GC5-HH), with forecast errors largely contained within empirically calibrated uncertainty bounds from the LOMFO-CV, both globally and locally. These results, notably for GC5-HH and its more realistic physics, strengthens confidence in the applicability of the framework to real-world data.When applied to observations, the extracted end-of-century global-mean surface temperature and its uncertainty range are consistent with prior estimates from Bayesian frameworks. At local scales, the network reduces uncertainty by 40% (2030s) to 30% (2090s) on average, and by up to 75% in some regions for all future decades. Importantly, these uncertainty estimates account not only for uncertainty in the forced response (as emergent constraint methods do), but also for errors associated with predicting different realisations of internal variability, providing a physically meaningful reduction of local and global climate uncertainty.

Abstract:

Negating the Measurement Independence assumption (MI) is often referred to as the ‘third way’ to account for the experimental violation of Bell’s inequality. However, this route is generally viewed as ludicrously contrived, implying some implausible conspiracy where experimenters are denied the freedom to choose measurement settings as they like. Here, a locally realistic model of quantum physics is developed (Rational Mechanics - RaQM - based on a gravitational discretisation of Hilbert Space) which violates MI without denying free will. Crucially, RaQM distinguishes experimenters’ ability to freely choose measurement settings to some nominal accuracy, from an inability to choose exact settings which were never under their control anyway. In RaQM, Hilbert states are necessarily undefined in bases where squared amplitudes and/or complex phases are irrational numbers. Such ‘irrational’ bases correspond to conceivable but necessarily impossible counterfactual measurements and are shown to play a ubiquitous role in the analysis of both single- and entangled-particle quantum physics. It is concluded that violation of Bell inequalities can be understood with none of the strange processes historically associated with it. Instead, using concepts from (non-classical) p-adic number theory, we relate RaQM to Bohm and Hiley’s concept of a holistic Machian-like Undivided Universe. If this interpretation of Bell’s Theorem is correct, building more and more energetic particle accelerators to probe smaller and smaller scales, in the search for a theory which synthesises quantum and gravitational physics and hence a Theory of Everything, may be a fruitless exercise.

Abstract:

The Quasi-Biennial Oscillation (QBO) is the dominant mode of tropical stratospheric variability that modulates global circulation and climate. Although a long-term weakening of QBO amplitude has been observed under global warming, the relative roles of different tropical oceans remain unclear. We perform sensitivity experiments forced by sea surface temperature perturbations over the tropical Pacific, Atlantic, and Indian Oceans, as well as their combined warming, to separate individual and joint effects. Pacific warming produces the strongest weakening and slowest descent of the QBO, whereas Atlantic warming slightly strengthens the amplitude and extends the vertical structure. Indian Ocean warming slightly weakens the amplitude and accelerates the descent. When all three oceans warm simultaneously, the QBO exhibits a weaker amplitude and faster descent, consistent in sign with the combined single-basin responses but with a reduced magnitude owing to diminished zonal and inter-basin SST gradients. Momentum budget analyses further show that basin-dependent competition between equatorial wave forcing and tropical upwelling underlies these contrasting responses.