Atmospheric seasonal forecasts of the twentieth century: multi‐decadal variability in predictive skill of the winter North Atlantic Oscillation (NAO) and their potential value for extreme event attribution

Abstract

Based on skill estimates from hindcasts made over the last couple of decades, recent studies have suggested that considerable success has been achieved in forecasting winter climate anomalies over the Euro-Atlantic area using current-generation dynamical forecast models. However, previous-generation models had shown that forecasts of winter climate anomalies in the 1960s and 1970s were less successful than forecasts of the 1980s and 1990s. Given that the more recent decades have been dominated by the North Atlantic Oscillation (NAO) in its positive phase, it is important to know whether the performance of current models would be similarly skilful when tested over periods of a predominantly negative NAO. To this end, a new ensemble of atmospheric seasonal hindcasts covering the period 1900-2009 has been created, providing a unique tool to explore many aspects of atmospheric seasonal climate prediction. In this study we focus on two of these: multi-decadal variability in predicting the winter NAO, and the potential value of the long seasonal hindcast datasets for the emerging science of probabilistic event attribution. The existence of relatively low skill levels during the period 1950s-1970s has been confirmed in the new dataset. The skill of the NAO forecasts is larger, however, in earlier and later periods. Whilst these inter-decadal differences in skill are, by themselves, only marginally statistically significant, the variations in skill strongly co-vary with statistics of the general circulation itself suggesting that such differences are indeed physically based. The mid-century period of low forecast skill coincides with a negative NAO phase but the relationship between the NAO phase/amplitude and forecast skill is more complex than linear. Finally, we show how seasonal forecast reliability can be of importance for increasing confidence in statements of causes of extreme weather and climate events, including effects of anthropogenic climate change.

Inconsistent Wind Speed Trends in Current Twentieth Century Reanalyses

“…The biggest positive NAO trends associated with its multidecadal fluctuations were observed between 1960 and 1995 (Omrani et al, ), and the expansion of the period to 1948–2014 will counteract the positive NAO trend due to the recent negative NAO trend since 1990s. The significance of these NAO fluctuations is supported by studies showing that the decadal variations in seasonal forecast skill are linked to it (Scaife et al, ; Weisheimer et al, ). The long‐term trends in winds identified here are not likely caused by the multidecadal variability: the trend has much larger amplitude than expected from the muldtidecadal variations (see Figure ).…”

A Simple Pedagogical Model Linking Initial-Value Reliability with Trustworthiness in the Forced Climate Response

“…Are there other diagnostics that can help determine the trustworthiness of regional climate projections or attributions of observed extreme weather events? One possible diagnostic is the statistical reliability of initial-value ensemble forecasts (Wilks 2011;Weisheimer and Palmer 2014) that relate forecast probability with frequency of occurrence. The possible link between initial-value reliability and the trustworthiness of the forced response was first proposed by Palmer et al (2008, hereafter P08), who discussed how information from a multimodel ensemble of initialized coupled seasonal forecasts can be used to constrain the trustworthiness of the regional projection of precipitation.…”

“…Seasonal climate forecasts are increasingly being used across a range of application sectors, and reliable inputs are essential for any forecast-based decision-making. Weisheimer and Palmer (2014) characterized the reliability of regional temperature and precipitation forecasts from ECMWF's operational seasonal forecast system 4 in terms of usefulness and found a wide range of rankings, depending on region and variable. Most of the temperature forecasts over land were found to be at least marginally useful in terms of reliability.…”

“…It is exactly those areas that our analysis above suggests that the response to forcing is untrustworthy. Weisheimer et al (2017) have proposed the use of reliability information from a 110-yr-long dataset of seasonal retrospective forecasts of extreme events on the seasonal time scale to contrast the reliability of forecast probabilities at the beginning of the twentieth century, indicative of a "pre-climate change" period, with the reliability of forecast probabilities for more recent decades, indicative of a "post-climate change" period. Consistent with the discussion here, they conclude that such information can be important for increasing the confidence in attribution statements of extreme weather and climate events.…”

Causal Pathways for Temperature Predictability from Snow Depth

“…Recently, dynamical subseasonal-to-seasonal (S2S) forecast model systems have achieved impressive skill (Saha et al, 2013;Domeisen et al, 2014;Scaife et al, 2014;Dunstone et al, 2016;Weisheimer et al, 2017). One reason is improvements of the representations of initial states.…”