Constraining projections using decadal predictions
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.Assessing the robustness of multidecadal variability in Northern Hemisphere wintertime seasonal forecast skill
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.Beyond skill scores: exploring sub‐seasonal forecast value through a case‐study of French month‐ahead energy prediction
Abstract:
We quantify the value of sub‐seasonal forecasts for a real‐world prediction problem: the forecasting of French month‐ahead 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 weeks can have value for this application, both on their own and in conjunction with shorter‐range 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‐range forecasts well, it misses the marginal value present in medium‐range 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‐users.Revisiting the identification of wintertime atmospheric circulation regimes in the Euro‐Atlantic sector
Abstract:
Atmospheric circulation is often clustered in so‐called circulation regimes, which are persistent and recurrent patterns. For the Euro‐Atlantic sector in winter, most studies identify four regimes: the Atlantic Ridge, Scandinavian Blocking and the two phases of the North Atlantic Oscillation. These results are obtained by applying k‐means clustering to the first several empirical orthogonal functions (EOFs) of geopotential height data. Studying the observed circulation in reanalysis data, it is found that when the full field data are used for the k‐means cluster analysis instead of the EOFs, the optimal number of clusters is no longer four but six. The two extra regimes that are found are the opposites of the Atlantic Ridge and Scandinavian Blocking, meaning they have a low‐pressure area roughly where the original regimes have a high‐pressure area. This introduces an appealing symmetry in the clustering result. Incorporating a weak persistence constraint in the clustering procedure is found to lead to a longer duration of regimes, extending beyond the synoptic time‐scale, without changing their occurrence rates. This is in contrast to the commonly used application of a time‐filter to the data before the clustering is executed, which, while increasing the persistence, changes the occurrence rates of the regimes. We conclude that applying a persistence constraint within the clustering procedure is a better way of stabilizing the clustering results than low‐pass filtering the data.Seasonal forecasts of the 20th century
Abstract:
New seasonal retrospective forecasts for 1901-2010 show that skill for predicting ENSO, NAO and PNA is reduced during mid-century periods compared to earlier and more recent high-skill decades.
Forecasts of seasonal climate anomalies using physically-based global circulation models are routinely made at operational meteorological centers around the world. A crucial component of any seasonal forecast system is the set of retrospective forecasts, or hindcasts, from past years which are used to estimate skill and to calibrate the forecasts. Hindcasts are usually produced over a period of around 20-30 years. However, recent studies have demonstrated that seasonal forecast skill can undergo pronounced multi-decadal variations. These results imply that relatively short hindcasts are not adequate for reliably testing seasonal forecasts and that small hindcast sample sizes can potentially lead to skill estimates that are not robust. Here we present new and unprecedented 110-year-long coupled hindcasts of the next season over the period 1901 to 2010. Their performance for the recent period is in good agreement with those of operational forecast models. While skill for ENSO is very high during recent decades, it is markedly reduced during the 1930s to 1950s. Skill at the beginning of the 20th Century is, however, as high as for recent high-skill periods. Consistent with findings in atmosphere-only hindcasts, a mid-century drop in forecast skill is found for a range of atmospheric fields including large-scale indices such as the NAO and the PNA patterns. As with ENSO, skill scores for these indices recover in the early 20th Century suggesting that the mid-century drop in skill is not due to lack of good observational data.
A public dissemination platform for our hindcast data is available and we invite the scientific community to explore them.