Dr Daniel Befort

Abstract:

Abstract In this study, Tropical Cyclones (TC) over the Western North Pacific (WNP) and North Atlantic (NA) basins are analysed in seasonal forecasting models from five European modelling centres. Most models are able to capture the observed seasonal cycle of TC frequencies over both basins; however, large differences for numbers and spatial track densities are found. In agreement with previous studies, TC numbers are often underestimated, which is likely related to coarse model resolutions. Besides shortcomings in TC characteristics, significant positive skill (deterministic and probabilistic) in predicting TC numbers and accumulated cyclone energy is found over both basins. Whereas the predictions of TC numbers over the WNP basin are mostly unreliable, most seasonal forecast provide reliable predictions for the NA basin. Besides positive skill over the entire NA basin, all seasonal forecasting models are skillful in predicting the interannual TC variability over a region covering the Caribbean and North American coastline, suggesting that the models carry useful information, e.g. for adaptation and mitigation purposes ahead of the upcoming TC season. However, skill in all forecast models over a smaller region centred along the Asian coastline is smaller compared to their skill in the entire WNP basin.

Abstract:

We assess the capability of decadal prediction simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) archive to predict European summer temperature during the period 1970–2014. Using a multi-model ensemble average, we show that Southern European (SEU) summer temperatures are highly predictable for up to ten years in CMIP6. Much of this predictive skill, is related to the externally forced response: historical simulations explain about 90% of observed SEU summer temperature variance. Prediction skill for the unforced signal of SEU summer temperature is low: initialized model simulations explain less than 10% of observed variance after removing the externally forced response. An observed link between unforced SEU summer temperature and preceding spring Eastern North Atlantic—Mediterranean sea surface temperature (SST) motivates the application of a dynamical-statistical model to overcome the low summer temperature skill over Europe. This dynamical-statistical model uses dynamical spring SST predictions to predict European summer temperature, and significantly increases decadal prediction skill of unforced European summer temperature variations, showing significant prediction skill for unforced Southern European summer temperature 2–9 years ahead. As a result, dynamical-statistical models can benefit the decadal prediction of variables with initially limited skill beyond the forcing, such as summer temperature over Europe.

Abstract:

There is increasing demand for robust, reliable and actionable climate information for the next 1 to 50 years. This is challenging for the scientific community as the longest initialized predictions are limited to 10 years (decadal predictions). Thus, to provide seamless information for the upcoming 50 years, information from decadal predictions and uninitialized projections need to be merged. In this study, the ability to obtain valuable climate information beyond decadal time-scales by constraining uninitialized projections using decadal predictions is assessed. The application of this framework to surface temperatures over the North Atlantic Subpolar Gyre region, shows that the constrained uninitialized sub-ensemble has higher skill compared to the overall projection ensemble also beyond ten years when information from decadal predictions is no longer available. Though showing the potential of such a constraining approach to obtain climate information for the near-term future, its utility depends on the added value of initialization.

Abstract:

Recent studies have found evidence of multidecadal variability in northern hemisphere wintertime seasonal forecast skill. Here we assess the robustness of this finding by extending the analysis to analysing a diverse set of ensemble atmospheric model simulations. These simulations differ in either numerical model or type of initialisation and include atmospheric model experiments initialised with reanalysis data and free‐running atmospheric model ensembles. All ensembles are forced with observed SST and seaice boundary conditions. Analysis of large‐scale Northern Hemisphere circulation indicesover the Northern Hemisphere (namely the North Atlantic Oscillation, Pacific North American pattern and the Arctic Oscillation) reveals that in all ensembles there is larger correlation skill in the late century periods than during periods in the mid‐century. Similar multidecadal variability in skill is found in a measure of total skill integrated over the whole of the extratropics. Most of the differences in large‐scale circulation skill between the skillful late period (as well as early period) and the less skillful mid‐century period seem to be due to a reduction in skill over the North Pacific and a disappearance in skill over North America and the North Atlantic. The results are robust across different models and different types of initialisation, indicating that the multidecadal variability in Northern Hemisphere winter skill is a robust feature of 20th century climate variability. Multidecadal variability in skill therefore arises from the evolution of the observed SSTs, likely related to a weakened influence of ENSO on the predictable extratropical circulation signal during the middle of the 20th century, and is evident in the signal‐to‐noise ratio of the different ensembles, particularly the larger ensembles.