Predictability of weather and climate

Abstract:

Understanding changes in precipitation is crucial for society and ecosystems^1,2. Studies have documented the respective contributions of anthropogenic forcing and internal variability to precipitation trends^3,4, yet discrepancies persist between observed and simulated patterns. In Northern Hemisphere winter, these mismatches are often attributed to unforced internal variability that dominates observed trends⁵. However, growing evidence also indicates that climate models underestimate the total response of precipitation to human forcings^6-8. Here we show that the thermodynamic contribution is broadly reproduced by climate models, whereas the dynamic contribution can diverge more substantially. Our approach disentangles the anthropogenic forced thermodynamic and dynamic components from internal variability in winter precipitation trends (1950-2022) to investigate their contribution to the trend discrepancies. In the Mediterranean, the forced dynamic signal from model simulations explains only about 10% of the observed dynamic trend, making detection challenging. Under continued anthropogenic emissions, the projected circulation response intensifies and more closely resembles observed trend patterns. Although internal variability in the observed record may contribute to this similarity, the results indicate an uncertain yet potentially emerging role of dynamic response in shaping regional winter precipitation trends. A reliable representation of the forced large-scale circulation response in climate models remains key for increasing confidence in regional precipitation projections.

Abstract:

The North Atlantic sector has been identified as a region where the 11‐year solar cycle has small but potentially non‐negligible impacts on winter climate, but a debate persists about the robustness of such impacts. This work explores the signatures of the 11‐year solar cycle over the North Atlantic in the ERA5 and 20th Century Reanalysis datasets. The results confirm previous studies with a robust positive boreal winter response in mean‐sea‐level pressure (mslp) in the region of the Azores at lags of three years after solar maximum. The spatial evolution of the response is examined in detail by first decomposing the mslp time series into the dominant modes of North Atlantic winter mslp variability, including the North Atlantic Oscillation (NAO), the East Atlantic (EA) and the Scandinavian patterns, before performing a multilinear regression analysis. We find that the maximum 11‐year solar response in the December–January–February (DJF) average does not project directly onto the NAO. However, when the early/late‐winter responses are examined separately, a statistically significant NAO response is seen in late winter (January–February) at lag 0–1 years and a statistically significant NAO response is also seen at lag +3 years in early winter (November–December). These results are consistent with predicted responses from previously proposed top‐down influences from the stratosphere in late winter followed by the re‐emergence of a signal from underlying sea surface temperatures in early winter. However, the NAO response is not the primary contributor to the total DJF response at lag +3 years. A previously unidentified solar‐cycle response in the EA pattern is found in late winter at lag +3 years with larger amplitude than the NAO response. The evolution of the DJF mslp response over the Azores region can thus be understood as a summation of the NAO and EA patterns at lag +3 years.

Abstract:

Motivated in part by John Wheeler's assertion that the continuum nature of Hilbert Space conceals the "it-from-bit" information-theoretic character of the quantum wavefunction, a theory of quantum physics (Rational Quantum Mechanics-RaQM) is proposed based on a specific discretization of complex Hilbert Space. The Schrödinger equation is not modified in RaQM, even during measurement. However, the bases in which the quantum state is defined must satisfy certain rational-number constraints. These constraints lead to the notion of finite qubit information capacity [Formula: see text]: For any [Formula: see text] qubit state, there is insufficient information in the [Formula: see text] qubits (linearly growing in [Formula: see text]) to allocate even one bit to each of all [Formula: see text] continuum degrees of freedom (exponentially growing in [Formula: see text]) associated with quantum mechanics/theory (QM, where [Formula: see text]). It is proposed that the discretization of Hilbert Space in RaQM is due to gravity, hence QM is the (singular) continuum limit of RaQM at [Formula: see text]. On this basis, it is estimated that [Formula: see text] lies between about 200 and 400 for current qubit technologies, and will never exceed 1,000. While QM and RaQM are experimentally indistinguishable for small numbers of qubits, RaQM predicts that the exponential advantage of quantum algorithms which, like Shor's, require bases with maximal [Formula: see text]-qubit superposition/entanglement, will have saturated at 1,000 perfect qubits. Hence, insofar as a classical computer will never factor a 2,048-bit RSA integer, RaQM predicts that a quantum computer will not either. This predicted breakdown of QM could be testable in less than 5 y.

Abstract:

Machine-learnt weather prediction (MLWP) models are now well established as being competitive with conventional numerical weather prediction (NWP) models in the medium range. However, there is still much uncertainty as to how this performance extends to longer timescales, where interactions with slower components of the earth system become important. We take GenCast, a state-of-the-art probabilistic MLWP model, and apply it to the task of seasonal forecasting with prescribed sea surface temperature (SST), by providing anomalies persisted over climatology (GenCast-Persisted) or forcing with observed SSTs (GenCastForced). The forecasts are compared to the European Centre for Medium-Range Weather Forecasts seasonal forecasting system, SEAS5. Our results indicate that, despite being trained at short timescales, GenCast-Persisted produces much of the correct precipitation patterns in response to El Ni˜no and La Ni˜na events, with several erroneous patterns in GenCast-Persisted corrected with GenCast-Forced. The uncertainty in precipitation response, as represented by the ensemble, compares favourably to SEAS5. Whilst SEAS5 achieves superior skill in the tropics for 2-metre temperature and mean sea level pressure (MSLP), GenCast-Persisted achieves higher skill in some areas in higher latitudes, including mountainous areas, with notable improvements for MSLP in particular; this is reflected in a slightly higher correlation with the observed NAO index. Reliability diagrams indicate that GenCast-Persisted has little skill relative to climatology, whilst GenCast-Forced produces forecasts with reliability comparable to SEAS5. These results provide an indication of the potential of MLWP models similar to GenCast for the ‘full’ seasonal forecasting problem, where the atmospheric model is coupled to ocean, land and cryosphere models.