Assessing the robustness of multidecadal variability in Northern Hemisphere wintertime seasonal forecast skill
Quarterly Journal of the Royal Meteorological Society Wiley 146:733 (2020) qj.3890
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鈥恟unning atmospheric model ensembles. All ensembles are forced with observed SST and seaice boundary conditions. Analysis of large鈥恠cale 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鈥恈entury. 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鈥恠cale circulation skill between the skillful late period (as well as early period) and the less skillful mid鈥恈entury 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鈥恡o鈥恘oise ratio of the different ensembles, particularly the larger ensembles.Beyond skill scores: exploring sub鈥恠easonal forecast value through a case鈥恠tudy of French month鈥恆head energy prediction
Quarterly Journal of the Royal Meteorological Society Wiley 146:733 (2020) 3623-3637
Abstract:
We quantify the value of sub鈥恠easonal forecasts for a real鈥恮orld prediction problem: the forecasting of French month鈥恆head energy demand. Using surface temperature as a predictor, we construct a trading strategy and assess the financial value of using meteorological forecasts, based on actual energy demand and price data. We show that forecasts with lead times greater than two鈥墂eeks can have value for this application, both on their own and in conjunction with shorter鈥恟ange forecasts, especially during boreal winter. We consider a cost/loss framework based on this example, and show that, while it captures the performance of the short鈥恟ange forecasts well, it misses the marginal value present in medium鈥恟ange forecasts. We also contrast our assessment of forecast value to that given by traditional skill scores, which we show could be misleading if used in isolation. We emphasise the importance of basing assessment of forecast skill on variables actually used by end鈥恥sers.A Vision for Numerical Weather Prediction in 2030
ArXiv 2007.0483 (2020)
Short-term tests validate long-term estimates of climate change
Nature Springer Nature 582:7811 (2020) 185-186
Rethinking superdeterminism
Frontiers in Physics Frontiers 8 (2020) 139