Jeff R. Knight

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).

A stratospheric influence on the winter NAO and North Atlantic surface climate

[1] The North Atlantic Oscillation (NAO) has a profound effect on winter climate variability around the Atlantic basin. Strengthening of the NAO in recent decades has altered surface climate in these regions at a rate far in excess of global mean warming. However, only weak NAO trends are reproduced in climate simulations of the 20th Century, even with prescribed climate forcings and historical sea-surface conditions. Here we show that the unexplained strengthening of the NAO can be fully simulated in a climate model by imposing observed trends in the lower stratosphere. This implies that stratospheric variability needs to be reproduced in models to fully simulate surface climate variations in the North Atlantic sector. Despite having little effect on global mean warming, we show that downward coupling of observed stratospheric circulation changes to the surface can account for the majority of change in regional surface climate over Europe and North America between 1965 and 1995.

Decadal to multidecadal variability and the climate change background

(1) Three prominent quasi-global patterns of variability and change are observed using the Met Offices sea surface temperature (SST) analysis and almost independent night marine air temperature analysis. The first is a global warming signal that is very highly correlated with global mean SST. The second is a decadal to multidecadal fluctuation with some geographical similarity to the El Nino-Southern Oscillation (ENSO). It is associated with the Pacific Decadal Oscillation (PDO), and its Pacific-wide manifestation has been termed the Interdecadal Pacific Oscillation (IPO). We present model investigations of the relationship between the IPO and ENSO. The third mode is an interhemispheric variation on multidecadal timescales which, in view of climate model experiments, is likely to be at least partly due to natural variations in the thermohaline circulation. Observed climatic impacts of this mode also appear in model simulations. Smaller-scale, regional atmospheric phenomena also affect climate on decadal to interdecadal timescales. We concentrate on one such mode, the winter North Atlantic Oscillation (NAO). This shows strong decadal to interdecadal variability and a correspondingly strong influence on surface climate variability which is largely additional to the effects of recent regional anthropogenic climate change. The winter NAO is likely influenced by both SST forcing and stratospheric variability. A full understanding of decadal changes in the NAO and European winter climate may require a detailed representation of the stratosphere that is hitherto missing in the major climate models used to study climate change.

European Climate Extremes and the North Atlantic Oscillation

The authors estimate the change in extreme winter weather events over Europe that is due to a long-term change in the North Atlantic Oscillation (NAO) such as that observed between the 1960s and 1990s. Using ensembles of simulations from a general circulation model, large changes in the frequency of 10th percentile temperature and 90th percentile precipitation events over Europe are found from changes in the NAO. In some cases, these changes are comparable to the expected change in the frequency of events due to anthropogenic forcing over the twenty-first century. Although the results presented here do not affect anthropogenic interpretation of global and annual mean changes in observed extremes, they do show that great care is needed to assess changes due to modes of climate variability when interpreting extreme events on regional and seasonal scales. How changes in natural modes of variability, such as the NAO, could radically alter current climate model predictions of changes in extreme weather events on multidecadal time scales is also discussed.

Atmospheric Blocking and Mean Biases in Climate Models

Models often underestimate blocking in the Atlantic and Pacific basins and this can lead to errors in both weather and climate predictions. Horizontal resolution is often cited as the main culprit for blocking errors due to poorly resolved small-scale variability, the upscale effects of which help to maintain blocks. Although these processes are important for blocking, the authors show that much of the blocking error diagnosed using common methods of analysis and current climate models is directly attributable to the climatological bias of the model. This explains a large proportion of diagnosed blocking error in models used in the recent Intergovernmental Panel for Climate Change report. Furthermore, greatly improved statistics are obtained by diagnosing blocking using climate model data corrected to account for mean model biases. To the extent that mean biases may be corrected in low-resolution models, this suggests that such models may be able to generate greatly improved levels of atmospheric blocking.

The global signal of the 11-year solar cycle in the stratosphere: observations and models

Abstract Earlier studies used the data from four solar cycles, to examine the global structure of the signal of the 11-year sunspot cycle (SSC) in the stratosphere and troposphere, using correlations between the solar cycle and heights and temperatures at different pressure levels. Here, this work is expanded in Part I to show the differences of geopotential heights and temperatures between maxima and minima of the SSC. This study puts the earlier work on a firmer ground and gives quantitative values for comparisons with models. In Part II, two general circulation models (GCMs) with coupled stratospheric chemistry are used to simulate the impact of changes in solar output. This paper is not intended as a review of the whole topic of solar impacts, but provides some results recently obtained in observations and modelling. Comparisons between the GCM results and observations show that the differences between solar maximum and solar minimum for temperature and ozone are generally smaller than observed. In the middle and upper stratosphere, models are closer to agreeing with observations of temperature, but a significant observed temperature difference near 100 hPa is not reproduced in the models. Also, model predictions of the shape of the vertical profile of the ozone difference do not agree with observations and the comparisons are hindered by large statistical uncertainties in both models and observations. Nonetheless, the results are an improvement on 2-D model results in showing a larger ozone signal in the lower stratosphere.

The Atlantic Multidecadal Oscillation Inferred from the Forced Climate Response in Coupled General Circulation Models

Abstract Instrumental sea surface temperature records in the North Atlantic Ocean are characterized by large multidecadal variability known as the Atlantic multidecadal oscillation (AMO). The lack of strong oscillatory forcing of the climate system at multidecadal time scales and the results of long unforced climate simulations have led to the widespread, although not ubiquitous, view that the AMO is an internal mode of climate variability. Here, a more objective examination of this hypothesis is performed using simulations with natural and anthropogenic forcings from the Coupled Model Intercomparison Project phase 3 (CMIP3) database. Ensemble means derived from these data allow an estimate of the response of models to forcings, as averaging leads to cancellation of the internal variability between ensemble members. In general, the means of individual model ensembles appear to be inconsistent with observed temperatures, although small ensemble sizes result in uncertainty in this conclusion. Combining the ...

Systematic Estimates of Initial-Value Decadal Predictability for Six AOGCMs

Initial-value predictability measures the degree to which the initial state can influence predictions. In this paper, the initial-value predictability of six atmosphere–ocean general circulation models in the North Pacific and North Atlantic is quantified and contrasted by analyzing long control integrations with time invariant external conditions. Through the application of analog and multivariate linear regression methodologies, average predictability properties are estimated for forecasts initiated from every state on the control trajectories. For basinwide measures of predictability, the influence of the initial state tends to last for roughly a decade in both basins, but this limit varies widely among the models, especially in the North Atlantic. Within each basin, predictability varies regionally by as much as a factor of 10 for a given model, and the locations of highest predictability are different for each model. Model-to-model variations in predictability are also seen in the behavior of prominent intrinsic basin modes. Predictability is primarily determined by the mean of forecast distributions rather than the spread about the mean. Horizontal propagation plays a large role in the evolution of these signals and is therefore a key factor in differentiating the predictability of the various models.

A New HadGEM3-A-Based System for Attribution of Weather- and Climate-Related Extreme Events

AbstractA new system for attribution of weather and climate extreme events has been developed based on the atmospheric component of the latest Hadley Centre model. The model is run with either observational data of sea surface temperature and sea ice or estimates of what their values would be without the effect of anthropogenic climatic forcings. In that way, ensembles of simulations are produced that represent the climate with and without the effect of human influences. A comparison between the ensembles provides estimates of the change in the frequency of extremes due to anthropogenic forcings. To evaluate the new system, reliability diagrams are constructed, which compare the model-derived probability of extreme events with their observed frequency. The ability of the model to reproduce realistic distributions of relevant climatic variables is another key aspect of the system evaluation. Results are then presented from analyses of three recent high-impact events: the 2009/10 cold winter in the United K...