Predictability of weather and climate

Abstract:

Model representations of the stratospheric semi-annual oscillation (SAO) show a common easterly bias, with a weaker westerly phase and stronger easterly phase compared to observations. Previous studies have shown that both resolved and parameterized tropical waves in the upper stratosphere are too weak. These waves propagate vertically through the underlying region dominated by the stratospheric quasi-biennial oscillation (QBO) before reaching the SAO altitudes. The influence of biases in the modelled QBO on the representation of the SAO is therefore explored. Correcting the QBO biases helps to reduce the SAO easterly bias through improved filtering of resolved and parameterized waves that contribute to improving both the westerly and the easterly phases of the SAO. The time-averaged zonal-mean zonal winds at SAO altitudes change by up to 25 % in response to the QBO bias corrections. The annual cycle in the equatorial upper stratosphere is improved as well. Most of the improvements in the SAO occur during the QBO easterly phase, coinciding with the period when the model's QBO exhibits the largest bias. Nevertheless, despite correcting for the QBO bias, there remains a substantial easterly bias in the SAO, suggesting that westerly wave forcing in the upper stratosphere and lower mesosphere is still severely under-represented.

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.