Doug Smith

Skillful long‐range prediction of European and North American winters

This work was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101), the UK Public Weather Service research program, and the European Union Framework 7 SPECS project. Leon Hermanson was funded as part of his Research Fellowship by Willis as part of Willis Research Network (WRN).

Decadal climate prediction: An update from the trenches

This paper provides an update on research in the relatively new and fast-moving field of decadal climate prediction, and addresses the use of decadal climate predictions not only for potential users of such information but also for improving our understanding of processes in the climate system. External forcing influences the predictions throughout, but their contributions to predictive skill become dominant after most of the improved skill from initialization with observations vanishes after about 6–9 years. Recent multimodel results suggest that there is relatively more decadal predictive skill in the North Atlantic, western Pacific, and Indian Oceans than in other regions of the world oceans. Aspects of decadal variability of SSTs, like the mid-1970s shift in the Pacific, the mid-1990s shift in the northern North Atlantic and western Pacific, and the early-2000s hiatus, are better represented in initialized hindcasts compared to uninitialized simulations. There is evidence of higher skill in initialize...

Causes of the rapid warming of the North Atlantic ocean in the mid 1990s

AbstractIn the mid-1990s, the subpolar gyre of the North Atlantic underwent a remarkable rapid warming, with sea surface temperatures increasing by around 1°C in just 2 yr. This rapid warming followed a prolonged positive phase of the North Atlantic Oscillation (NAO) but also coincided with an unusually negative NAO index in the winter of 1995/96. By comparing ocean analyses and carefully designed model experiments, it is shown that this rapid warming can be understood as a delayed response to the prolonged positive phase of the NAO and not simply an instantaneous response to the negative NAO index of 1995/96. Furthermore, it is inferred that the warming was partly caused by a surge and subsequent decline in the meridional overturning circulation and northward heat transport of the Atlantic Ocean. These results provide persuasive evidence of significant oceanic memory on multiannual time scales and are therefore encouraging for the prospects of developing skillful predictions.

Distinguishing the Roles of Natural and Anthropogenically Forced Decadal Climate Variability: Implications for Prediction

Abstract Given that over the course of the next 10–30 years the magnitude of natural decadal variations may rival that of anthropogenically forced climate change on regional scales, it is envisioned that initialized decadal predictions will provide important information for climate-related management and adaptation decisions. Such predictions are presently one of the grand challenges for the climate community. This requires identifying those physical phenomena—and their model equivalents—that may provide additional predictability on decadal time scales, including an assessment of the physical processes through which anthropogenic forcing may interact with or project upon natural variability. Such a physical framework is necessary to provide a consistent assessment (and insight into potential improvement) of the decadal prediction experiments planned to be assessed as part of the IPCCs Fifth Assessment Report.

What is the current state of scientific knowledge with regard to seasonal and decadal forecasting

Environmental factors, such as the frequency, intensity and duration of extreme weather events, are important drivers of migration and displacement of people. There is therefore a growing need for regional climate predictions for the coming seasons to decades. This paper reviews the current state of the art of seasonal to decadal climate prediction, focusing on the potential sources of skill, forecasting techniques, current capability and future prospects.

Do seasonal‐to‐decadal climate predictions underestimate the predictability of the real world?

Seasonal-to-decadal predictions are inevitably uncertain, depending on the size of the predictable signal relative to unpredictable chaos. Uncertainties can be accounted for using ensemble techniques, permitting quantitative probabilistic forecasts. In a perfect system, each ensemble member would represent a potential realization of the true evolution of the climate system, and the predictable components in models and reality would be equal. However, we show that the predictable component is sometimes lower in models than observations, especially for seasonal forecasts of the North Atlantic Oscillation and multiyear forecasts of North Atlantic temperature and pressure. In these cases the forecasts are underconfident, with each ensemble member containing too much noise. Consequently, most deterministic and probabilistic measures underestimate potential skill and idealized model experiments underestimate predictability. However, skilful and reliable predictions may be achieved using a large ensemble to reduce noise and adjusting the forecast variance through a postprocessing technique proposed here.

Changes in global net radiative imbalance 1985–2012

Combining satellite data, atmospheric reanalyses, and climate model simulations, variability in the net downward radiative flux imbalance at the top of Earths atmosphere (N) is reconstructed and linked to recent climate change. Over the 1985–1999 period mean N (0.34 ± 0.67 Wm−2) is lower than for the 2000–2012 period (0.62 ± 0.43 Wm−2, uncertainties at 90% confidence level) despite the slower rate of surface temperature rise since 2000. While the precise magnitude of N remains uncertain, the reconstruction captures interannual variability which is dominated by the eruption of Mount Pinatubo in 1991 and the El Niño Southern Oscillation. Monthly deseasonalized interannual variability in N generated by an ensemble of nine climate model simulations using prescribed sea surface temperature and radiative forcings and from the satellite-based reconstruction is significantly correlated (r∼0.6) over the 1985–2012 period.

A comparison of full-field and anomaly initialization for seasonal to decadal climate prediction

There are two main approaches for dealing with model biases in forecasts made with initialized climate models. In full-field initialization, model biases are removed during the assimilation process by constraining the model to be close to observations. Forecasts drift back towards the model’s preferred state, thereby re-establishing biases which are then removed with an a posterior lead-time dependent correction diagnosed from a set of historical tests (hindcasts). In anomaly initialization, the model is constrained by observed anomalies and deviates from its preferred climatology only by the observed variability. In theory, the forecasts do not drift, and biases may be removed based on the difference between observations and independent model simulations of a given period. Both approaches are currently in use, but their relative merits are unclear. Here we compare the skill of each approach in comprehensive decadal hindcasts starting each year from 1960 to 2009, made using the Met Office decadal prediction system. Both approaches are more skilful than climatology in most regions for temperature and some regions for precipitation. On seasonal timescales, full-field initialized hindcasts of regional temperature and precipitation are significantly more skilful on average than anomaly initialized hindcasts. Teleconnections associated with the El Niño Southern Oscillation are stronger with the full-field approach, providing a physical basis for the improved precipitation skill. Differences in skill on multi-year timescales are generally not significant. However, anomaly initialization provides a better estimate of forecast skill from a limited hindcast set.

Predictability of the mid-latitude Atlantic meridional overturning circulation in a multi-model system

Assessing the skill of the Atlantic meridional overturning circulation (AMOC) in decadal hindcasts (i.e. retrospective predictions) is hampered by a lack of observations for verification. Models are therefore needed to reconstruct the historical AMOC variability. Here we show that ten recent oceanic syntheses provide a common signal of AMOC variability at 45°N, with an increase from the 1960s to the mid-1990s and a decrease thereafter although they disagree on the exact magnitude. This signal correlates with observed key processes such as the North Atlantic Oscillation, sub-polar gyre strength, Atlantic sea surface temperature dipole, and Labrador Sea convection that are thought to be related to the AMOC. Furthermore, we find potential predictability of the mid-latitude AMOC for the first 3–6 year means when we validate decadal hindcasts for the past 50 years against the multi-model signal. However, this predictability is not found in models driven only by external radiative changes, demonstrating the need for initialization of decadal climate predictions.

Predictability of the quasi‐biennial oscillation and its northern winter teleconnection on seasonal to decadal timescales

The predictability of the quasi-biennial oscillation (QBO) is examined in initialized climate forecasts extending out to lead times of years. We use initialized retrospective predictions made with coupled ocean-atmosphere climate models that have an internally generated QBO. We demonstrate predictability of the QBO extending more than 3 years into the future, well beyond timescales normally associated with internal atmospheric processes. Correlation scores with observational analyses exceed 0.7 at a lead time of 12 months. We also examine the variation of predictability with season and QBO phase and find that skill is lowest in winter. An assessment of perfect predictability suggests that higher skill may be achievable through improved initialization and climate modeling of the QBO, although this may depend on the realism of gravity wave source parameterizations in the models. Finally, we show that skilful prediction of the QBO itself does not guarantee predictability of the extratropical winter teleconnection that is important for surface winter climate prediction.