David Fereday

The Summer North Atlantic Oscillation: Past, Present, and Future

Summer climate in the North Atlantic‐European sector possesses a principal pattern of year-to-year variability that is the parallel to the well-known North Atlantic Oscillation in winter. This summer North Atlantic Oscillation (SNAO) is defined here as the first empirical orthogonal function (EOF) of observed summertime extratropical North Atlantic pressure at mean sea level. It is shown to be characterized by a more northerly location and smaller spatial scale than its winter counterpart. The SNAO is also detected by cluster analysis and has a near-equivalent barotropic structure on daily and monthly time scales. Although of lesser amplitude than its wintertime counterpart, the SNAO exerts a strong influence on northern European rainfall, temperature, and cloudiness through changes in the position of the North Atlantic storm track. It is, therefore, of key importance in generating summer climate extremes, including flooding, drought, and heat

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).

The GloSea4 Ensemble Prediction System for Seasonal Forecasting

AbstractSeasonal forecasting systems, and related systems for decadal prediction, are crucial in the development of adaptation strategies to climate change. However, despite important achievements in this area in the last 10 years, significant levels of skill are only generally found over regions strongly connected with the El Nino–Southern Oscillation. With the aim of improving the skill of regional climate predictions in tropical and extratropical regions from intraseasonal to interannual time scales, a new Met Office global seasonal forecasting system (GloSea4) has been developed. This new system has been designed to be flexible and easy to upgrade so it can be fully integrated within the Met Office model development infrastructure. Overall, the analysis here shows an improvement of GloSea4 when compared to its predecessor. However, there are exceptions, such as the increased model biases that contribute to degrade the skill of Nino-3.4 SST forecasts starting in November. Global ENSO teleconnections an...

Climate change projections and stratosphere-troposphere interaction

Climate change is expected to increase winter rainfall and flooding in many extratropical regions as evaporation and precipitation rates increase, storms become more intense and storm tracks move polewards. Here, we show how changes in stratospheric circulation could play a significant role in future climate change in the extratropics through an additional shift in the tropospheric circulation. This shift in the circulation alters climate change in regional winter rainfall by an amount large enough to significantly alter regional climate change projections. The changes are consistent with changes in stratospheric winds inducing a change in the baroclinic eddy growth rate across the depth of the troposphere. A change in mean wind structure and an equatorward shift of the tropospheric storm tracks relative to models with poor stratospheric resolution allows coupling with surface climate. Using the Atlantic storm track as an example, we show how this can double the predicted increase in extreme winter rainfall over Western and Central Europe compared to other current climate projections.

A quantification of uncertainties in historical tropical tropospheric temperature trends from radiosondes

The consistency of tropical tropospheric temperature trends with climate model expectations remains contentious. A key limitation is that the uncertainties in observations from radiosondes are both substantial and poorly constrained. We present a thorough uncertainty analysis of radiosonde‐based temperature records. This uses an automated homogenization procedure and a previously developed set of complex error models where the answer is known a priori. We perform a number of homogenization experiments in which error models are used to provide uncertainty estimates of real‐world trends. These estimates are relatively insensitive to a variety of processing choices. Over 1979–2003, the satellite‐equivalent tropical lower tropospheric temperature trend has likely (5–95% confidence range) been between −0.01 K/decade and 0.19 K/decade (0.05–0.23 K/decade over 1958–2003) with a best estimate of 0.08 K/decade (0.14 K/decade). This range includes both available satellite data sets and estimates from models (based upon scaling their tropical amplification behavior by observed surface trends). On an individual pressure level basis, agreement between models, theory, and observations within the troposphere is uncertain over 1979 to 2003 and nonexistent above 300 hPa. Analysis of 1958–2003, however, shows consistent model‐data agreement in tropical lapse rate trends at all levels up to the tropical tropopause, so the disagreement in the more recent period is not necessarily evidence of a general problem in simulating long‐term global warming. Other possible reasons for the discrepancy since 1979 are: observational errors beyond those accounted for here, end‐point effects, inadequate decadal variability in model lapse rates, or neglected climate forcings.

Cluster Analysis of North Atlantic–European Circulation Types and Links with Tropical Pacific Sea Surface Temperatures

Abstract Observed atmospheric circulation over the North Atlantic–European (NAE) region is examined using cluster analysis. A clustering algorithm incorporating a “simulated annealing” methodology is employed to improve on solutions found by the conventional k-means technique. Clustering is applied to daily mean sea level pressure (MSLP) fields to derive a set of circulation types for six 2-month seasons. A measure of the quality of this clustering is defined to reflect the average similarity of the fields in a cluster to each other. It is shown that a range of classifications can be produced for which this measure is almost identical but which partition the days quite differently. This lack of a unique set of circulation types suggests that distinct weather regimes in NAE circulation do not exist or are very weak. It is also shown that the stability of the clustering solution to removal of data is not maximized by a suitable choice of the number of clusters. Indeed, there does not appear to be any robust...

Multi-model assessment of the impact of soil moisture initialization on mid-latitude summer predictability

Land surface initial conditions have been recognized as a potential source of predictability in sub-seasonal to seasonal forecast systems, at least for near-surface air temperature prediction over the mid-latitude continents. Yet, few studies have systematically explored such an influence over a sufficient hindcast period and in a multi-model framework to produce a robust quantitative assessment. Here, a dedicated set of twin experiments has been carried out with boreal summer retrospective forecasts over the 1992–2010 period performed by five different global coupled ocean–atmosphere models. The impact of a realistic versus climatological soil moisture initialization is assessed in two regions with high potential previously identified as hotspots of land–atmosphere coupling, namely the North American Great Plains and South-Eastern Europe. Over the latter region, temperature predictions show a significant improvement, especially over the Balkans. Forecast systems better simulate the warmest summers if they follow pronounced dry initial anomalies. It is hypothesized that models manage to capture a positive feedback between high temperature and low soil moisture content prone to dominate over other processes during the warmest summers in this region. Over the Great Plains, however, improving the soil moisture initialization does not lead to any robust gain of forecast quality for near-surface temperature. It is suggested that models biases prevent the forecast systems from making the most of the improved initial conditions.

Comments on “Multiyear Predictions of North Atlantic Hurricane Frequency: Promise and Limitations”

Vecchi et al. (2013, hereafter V13) show that retrospective decadal predictions (reforecasts) of multiyear North Atlantic hurricane frequency have high correlations with observations, in agreement with an earlier study (Smith et al. 2010, hereafter S10). However, V13 state that ‘‘the skill in the initialized forecasts comes in large part from the persistence of a mid-1990s shift by the initialized forecasts, rather than from predicting its evolution.’’ Here, we provide a different interpretation of the Met Office Decadal Prediction System (DePreSys) reforecasts, showing that these would have provided clear evidence for an impending reversal to a period of above average hurricane frequency had they been available in 1994, before the observed increase occurred. This is illustrated in Fig. 1a, which shows the information that would have been available in 1994. DePreSys reforecasts starting from 1991 onward clearly predict an increase in hurricane numbers, in fact to levels higher than ever simulated before by this modeling system, while observed counts remained low (including each individual year from 1991 to 1994; not shown). The conclusion in V13 that DePreSys did not predict the 1995 shift is partly based on their analysis of the difference in storm counts averaged over years 2–6 minus the first year of each forecast (Fig. 7 in V13; cf. Fig. 1c). V13 argue that observations straddling the 1995 shift (green triangles in Fig. 1c) are unusually large in this statistic, whereas the DePreSys forecasts are not (blue histogram in Fig. 1c). However, in DePreSys, this statistic is particularly sensitive to the forecast initialized in 1990, which erroneously predicted a very active hurricane season for 1991. Furthermore, this forecast was unaware of the eruption of Mount Pinatubo in June 1991, which likely suppressed hurricane numbers in that year (Evan 2012) and of course was unpredictable. If we exclude 1990 and consider the forecasts starting after Pinatubo, between 1991 and 1993, then DePreSys (red histogram in Fig. 1c) hindcasts predicted an increase similar to that observed. How much confidence could we have had in the DePreSys forecasts of a shift in hurricane frequency? Assessment of previous reforecasts is inconclusive: the decline from the mid-1960s was successfully captured, but the maximum in the late 1970s was not predicted (Fig. 1a) and forecasts beginning in the late 1970s incorrectly predicted an increase (although these were unaware of the impending eruption of El Chich on, which likely decreased hurricane numbers; Evan 2012). We therefore examine the physical mechanisms driving the increased hurricane numbers predicted during Corresponding author address: Doug Smith, Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, United Kingdom. E-mail: doug.smith@metoffice.gov.uk 1 JANUARY 2014 CORRES PONDENCE 487

Atmospheric Dynamics is the Largest Source of Uncertainty in Future Winter European Rainfall

AbstractThe IPCC Fifth Assessment Report highlighted large uncertainty in European precipitation changes in the coming century. This paper investigates the sources of intermodel differences using CMIP5 model European precipitation data. The contribution of atmospheric circulation to differences in precipitation trends is investigated by applying cluster analysis to daily mean sea level pressure (MSLP) data. The resulting classification is used to reconstruct monthly precipitation time series, thereby isolating the component of precipitation variability directly related to atmospheric circulation. Reconstructed observed precipitation and reconstructions of simulated historical and projection data are well correlated with the original precipitation series, showing that circulation variability accounts for a substantial fraction of European precipitation variability. Removing the reconstructed precipitation from the original precipitation leaves a residual component related to noncirculation effects (and any...

How Persistent Are North Atlantic–European Sector Weather Regimes?

AbstractPersistent weather regimes in daily North Atlantic–European winter mean sea level pressure (MSLP) fields from the 140-yr Twentieth Century Reanalysis are investigated. The phase space is divided into discrete cells based on quantiles of empirical orthogonal function (EOF) principal components; the cells are thus approximately equally populated. An estimate of persistence is provided in terms of the number of different cells visited for a given trajectory duration. This technique is also applied to the well-known Lorenz63 system, which clearly exhibits two regimes, and the more complex Lorenz96 system where the regime structure is less pronounced. While the analysis identifies the two regimes of both the Lorenz63 and Lorenz96 systems, evidence for comparable regimes in the MSLP data is weaker. Recurrent weather regimes produced by k-means clustering might be expected to be clearly linked to slower-moving regions of phase space, but this is shown not to be the case. Only the region of phase space as...