Predictability of weather and climate

Abstract:

Emulators of Earth system models (ESMs) are statistical models that approximate selected outputs of ESMs. Owing to their runtime efficiency, emulators are especially useful when large amounts of data are required, for example, for in-depth exploration of the emission space, for investigating high-impact low-probability events, or for estimating uncertainties and variability. This paper introduces an emulation framework that allows us to emulate gridded monthly mean precipitation fields using gridded monthly mean temperature fields as forcing. The emulator is designed as an extension of the Modular Earth System Model Emulator (MESMER) framework, and its core relies on the concepts of generalised linear models (GLMs). Precipitation at each (land) grid point and for each month is approximated as a multiplicative model with two factors. The first factor entails the temperature-driven precipitation response and is assumed to follow a gamma distribution with a logarithmic link function. The second factor is the residual variability in the precipitation field, which is assumed to be independent of temperature but may still possess spatial precipitation correlations. Therefore, the monthly residual field is decomposed into independent principal components and subsequently approximated and sampled using a kernel density estimation with a Gaussian kernel. The emulation framework is tested and validated using 24 ESMs from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). For each ESM, we train on a single-ensemble member across scenarios and evaluate the emulator performance using simulations with historical and Shared Socioeconomic Pathways (SSP5-8.5) forcing. We show that the framework captures grid-point-specific precipitation characteristics, such as variability, trend, and temporal auto-correlations. In addition, we find that emulated spatial (cross-variable) characteristics are consistent with those of ESMs. The framework is also able to capture compound hot-dry and cold-wet extremes, although it systematically underestimates their occurrence probabilities. The emulation of spatially explicit coherent monthly temperature and precipitation time series is a major step towards a computationally efficient representation of impact-relevant variables of the climate system. Copyright:

Abstract:

Current implementations of superconducting qubits are often limited by the low fidelities of multi-qubit gates. We present a reproducible and runtime-efficient pulse-level approach for calibrating an improved cross-resonance gate CR(θ) for arbitrary θ. This CR(θ) gate can be used to produce a wide range of other two-qubit gates via the application of standard single-qubit gates. By performing an interleaved randomised benchmarking sequence, we demonstrate that our approach leads to significantly lower incoherent errors than the circuit-level approach currently used by IBM. Hence, our procedure provides a genuine improvement for applications where noise remains a limiting factor.

Abstract:

The Quasi-Biennial Oscillation (QBO) is one of the most cyclic phenomena in the atmosphere except for the annular and diurnal cycles, which provide the predictability source for subseasonal-to-seasonal forecasts on the globe. The QBO is generated by the interaction between the background circulation and the equatorial waves, which cover a wide spectrum consisting of those that are eastward- and westward-propagating. The QBO can affect the climate in both the Northern and Southern Hemispheres through at least three dynamic pathways, including the stratospheric polar vortex pathway, the subtropical downward-arching zonal wind pathway, and the tropical convection pathway. The impact of the QBO on the extratropics is projected to strengthen in future scenario experiments, although the maximum QBO wind magnitude gradually decreased in recent decades. As a newly emerging feature, the QBO disruption during the westerly phase is mainly caused by the extremely active Rossby waves from the extratropics. The QBO disruptions are likely to increase in a warmer climate background.

Abstract:

Understanding the predictability drivers for the North Atlantic Oscillation (NAO) during boreal winter at seasonal time scales remains challenging. This study uses large ensembles with the ECMWF seasonal forecasting system to investigate the relative impact of tropical Indian and Pacific heating on NAO predictability by examining the tropical forcing, teleconnection pathways, and sources of uncertainty. We select three case studies ‐ 1997/98, 2015/16 and 2019/20 ‐ with strong Indian Ocean heating anomalies, but with different El Niño conditions. We show that in 2019/20, with neutral ENSO conditions, Indian Ocean SSTs favor a positive NAO response via stratospheric and tropospheric pathways. In the cases with strong El Niño, we find contrasting results: in 1997/98, the Pacific forcing dominates, producing a negative NAO. In 2015/16, despite the strong El Niño, the Indian Ocean forcing dominates, leading to a positive NAO via intensification of the stratospheric polar vortex (SPV). While the stratospheric pathway exhibits varying responses to Indian Ocean forcing ‐ being weaker in 1997/98 and strongest in 2015/16, the Indian Ocean‐related tropospheric pathway remains robust along the Pacific subtropical jet across years. However, there is destructive interference between teleconnections from Indian and Pacific SST anomalies in both the tropospheric and stratospheric pathways. The competing effects of tropical heating in both basins, uncertainties in the Rossby wave response to tropical heating and SPV variability contribute to uncertainty in seasonal NAO predictions. The flow‐dependent nature of the stratospheric pathway underscores the complexity of seasonal forecast predictability, and the existence of windows of opportunity.