A machine learning-based approach to quantify ENSO sources of predictability
Geophysical Research Letters American Geophysical Union 51:13 (2024) e2023GL105194
Abstract:
A machine learning method is used to identify sources of long-term ENSO predictability in the ocean (sea surface temperature (SST) and heat content) and the atmosphere (near-surface zonal wind (U10)). Tropical SST represents the primary source of predictability skill. While U10 does not increase the skill when associated with SST, our analysis suggests U10 alone has a predictive skill comparable to that of SST between 11 and 21 months in advance, from late fall up to late spring. The long-lead signal originates from coupled wind-SST interactions across the Indian Ocean (IO) and propagates across the Pacific via an atmospheric bridge mechanism. A linear correlation analysis supports this mechanism, suggesting a precursor link between anomalies in SST in the western and wind in the eastern IO. Our results have important implications for ENSO predictions beyond 1 year ahead and identify the key role of U10 over the IO.
The Link between Gulf Stream Precipitation and European Blocking in General Circulation Models and the Role of Horizontal Resolution
(2024)
Physical and Unphysical Causes of Nonstationarity in the Relationship Between Barents‐Kara Sea Ice and the North Atlantic Oscillation
Geophysical Research Letters Wiley Open Access 51:11 (2024) e2023GL107609
Abstract:
The role of internal variability in generating an apparent link between autumn Barents‐Kara sea (BKS) ice and the winter North Atlantic Oscillation (NAO) has been intensely debated. In particular, the robustness and causality of the link has been questioned by showing that BKS‐NAO correlations exhibit nonstationarity in both reanalysis and climate model simulations. We show that the lack of ice observations means nonstationarity cannot be confidently assessed using reanalysis prior to 1961. Model simulations are used to corroborate an argument that forced nonstationarity could result from ice edge changes due to global warming. Consequently, the observed change in BKS‐NAO correlations since 1960 might not be purely a result of internal variability and may also reflect that the ice edge has moved. The change could also reflect the availability of more accurate ice observations. We discuss potential implications for analysis based on coupled climate models, which exhibit large ice edge biases.
Divergent convective outflow in ICON deep-convection-permitting and parameterised deep convection simulations
Weather and Climate Dynamics 5:2 (2024) 779-803
Abstract:
Upper-tropospheric deep convective outflows during an event on 10–11 June 2019 over central Europe are analysed in ensembles of the operational Icosahedral Nonhydrostatic (ICON) numerical weather prediction model. Both a parameterised and an explicit representation of deep convective systems is studied. Near-linear response of deep convective outflow strength to net latent heating is found for parameterised convection, while different but physically coherent patterns of outflow variability are found in convection-permitting simulations at 1 km horizontal grid spacing. We investigate if the conceptual model for outflow strength proposed in our previous idealised large-eddy simulation (LES) study is able to explain the variation in outflow strength in a real-case scenario. Convective organisation and aggregation induce a non-linear increase in the magnitude of deep convective outflows with increasing net latent heating in convection-permitting simulations, consistent with the conceptual model. However, in contrast to expectations from the conceptual model, a dependence of the outflow strength on the dimensionality of convective overturning (two-dimensional versus three-dimensional) cannot be fully corroborated from the real-case simulations.
Our results strongly suggest that the interactions between gravity waves emitted by heating in individual deep convective elements within larger organised convective systems are of prime importance for the representation of divergent outflow strength from organised convection in numerical models.
Our results strongly suggest that the interactions between gravity waves emitted by heating in individual deep convective elements within larger organised convective systems are of prime importance for the representation of divergent outflow strength from organised convection in numerical models.
Recovering p-adic valuations from pro-p Galois groups
Journal of the London Mathematical Society Wiley 109:5 (2024) e12901