T. N. Palmer

Monsoons: Processes, predictability, and the prospects for prediction

The Tropical Ocean-Global Atmosphere (TOGA) program sought to determine the predictability of the coupled ocean-atmosphere system. The World Climate Research Programmes (WCRP) Global Ocean-Atmosphere-Land System (GOALS) program seeks to explore predictability of the global climate system through investigation of the major planetary heat sources and sinks, and interactions between them. The Asian-Australian monsoon system, which undergoes aperiodic and high amplitude variations on intraseasonal, annual, biennial and interannual timescales is a major focus of GOALS. Empirical seasonal forecasts of the monsoon have been made with moderate success for over 100 years. More recent modeling efforts have not been successful. Even simulation of the mean structure of the Asian monsoon has proven elusive and the observed ENSO-monsoon relationships has been difficult to replicate. Divergence in simulation skill occurs between integrations by different models or between members of ensembles of the same model. This degree of spread is surprising given the relative success of empirical forecast techniques. Two possible explanations are presented: difficulty in modeling the monsoon regions and nonlinear error growth due to regional hydrodynamical instabilities. It is argued that the reconciliation of these explanations is imperative for prediction of the monsoon to be improved. To this end, a thorough description of observed monsoon variability and the physical processes that are thought to be important is presented. Prospects of improving prediction and some strategies that may help achieve improvement are discussed.

DEVELOPMENT OF A EUROPEAN MULTIMODEL ENSEMBLE SYSTEM FOR SEASONAL-TO-INTERANNUAL PREDICTION (DEMETER)

A multi-model ensemble-based system for seasonal-to-interannual prediction has been developed in a joint European project known as DEMETER (Development of a European Multimodel Ensemble Prediction System for Seasonal to Interannual Prediction). The DEMETER system comprises seven global atmosphere–ocean coupled models, each running from an ensemble of initial conditions. Comprehensive hindcast evaluation demonstrates the enhanced reliability and skill of the multimodel ensemble over a more conventional single-model ensemble approach. In addition, innovative examples of the application of seasonal ensemble forecasts in malaria and crop yield prediction are discussed. The strategy followed in DEMETER deals with important problems such as communication across disciplines, downscaling of climate simulations, and use of probabilistic forecast information in the applications sector, illustrating the economic value of seasonal-to-interannual prediction for society as a whole.

Breaking planetary waves in the stratosphere

Satellite-borne IR radiometers are turning the Earths stratosphere into one of the best available outdoor laboratories for observing the large-scale dynamics of a rotating, heterogeneous fluid under gravity. New insight is being gained not only into stratospheric dynamics as such, with its implications for pollutant behaviour and the ozone layer, but also indirectly into the dynamics of the troposphere, with its implications for weather forecasting. Similar dynamical regimes occur in the oceans and in stellar interiors. A key development has been the construction of coarse-grain maps of the large-scale distribution of potential vorticity in the middle stratosphere. Potential vorticity is a conservable quantity which has a central role in the dynamical theory, but is difficult to calculate accurately from observational data. We present the first mid-stratospheric potential vorticity maps which appear good enough to make visible the ‘breaking’ of planetary or Rossby waves, a phenomenon ubiquitous in nature and arguably one of the most important dynamical processes affecting the stratosphere as a whole.

The singular-vector structure of the atmospheric global circulation

Abstract The local phase-space instability Of the atmospheric global circulation is Characterized by its (nonmodal) singular vectors. The formalism of singular vector analysis is described. The relations between singular vectors, normal modes, adjoint modes, Lyapunov vectors, perturbations produced by the so-called breeding method, and wave pseudomomentum are outlined. Techniques to estimate the dominant part of the singular spectrum using large-dimensional primitive equation models are discussed. These include the use of forward and adjoint tangent propagators with a Lanczos iterative algorithm. Results are described, based first on statistics of routine calculations made between December 1992 and August 1993, and second on three specific case studies. Results define three dominant geographical areas of instability in the Northern Hemisphere: the two regions of storm track cyclogenesis, and the North African subtropical jet Singular vectors can amplify as much as tenfold over 36 hours, and in winter ther...

Signature of recent climate change in frequencies of natural atmospheric circulation regimes

A crucial question in the global-warming debate concerns the extent to which recent climate change is caused by anthropogenic forcing or is a manifestation of natural climate variability. It is commonly thought that the climate response to anthropogenic forcing should be distinct from the patterns of natural climate variability. But, on the basis of studies of nonlinear chaotic models with preferred states or ‘regimes’, it has been argued, that the spatial patterns of the response to anthropogenic forcing may in fact project principally onto modes of natural climate variability. Here we use atmospheric circulation data from the Northern Hemisphere to show that recent climate change can be interpreted in terms of changes in the frequency of occurrence of natural atmospheric circulation regimes. We conclude that recent Northern Hemisphere warming may be more directly related to the thermal structure of these circulation regimes than to any anthropogenic forcing pattern itself. Conversely, the fact that observed climate change projects onto natural patterns cannot be used as evidence of no anthropogenic effect on climate. These results may help explain possible differences between trends in surface temperature and satellite-based temperature in the free atmosphere,,.

Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject

The ability of 15 atmospheric general circulation models (AGCM) to simulate the tropical intraseasonal oscillation has been studied as part of the Atmospheric Model Intercomparison Project (AMIP). Time series of the daily upper tropospheric velocity poential and zonal wind, averaged over the equatorial belt, were provided from each AGCM simulation. These data were analyzed using a variety of techniques such as time filtering and space-time spectral analysis to identify eastward and westward moving waves. The results have been compared with an identical assessment of the European Centre for Medium-range Weather Forecasts (ECMWF) analyses for the period 1982–1991. The models display a wide range of skill in simulating the intraseasonal oscillation. Most models show evidence of an eastward propagating anomaly in the velocity potential field, although in some models there is a greater tendency for a standing oscillation, and in one or two the field is rather chaotic with no preferred direction of propagation. Where a model has a clear eastward propagating signal, typical periodicities seem quite reasonable although there is a tendency for the models to simulate shorter periods than in the ECMWF analyses, where it is near 50 days. The results of the space-time spectral analysis have shown that no model has captured the dominance of the intraseasonal oscillation found in the analyses. Several models have peaks at intraseasonal time scales, but nearly all have relatively more power at higher frequencies (< 30 days) than the analyses. Most models underestimate the strength of the intraseasonal variability. The observed intraseasonal oscillation shows a marked seasonality in its occurrence with greatest activity during northern winter and spring. Most models failed to capture this seasonality. The interannual variability in the activity of the intraseasonal oscillation has also been assessed, although the AMIP decade is too short to provide any conclusive results. There is a suggestion that the observed oscillation was suppressed during the strong El Niño of 1982/83, and this relationship has also been reproduced by some models. The relationship between a models intraseasonal activity, its seasonal cycle and characteristics of its basic climate has been examined. It is clear that those models with weak intraseasonal activity tend also to have a weak seasonal cycle. It is becoming increasingly evident that an accurate description of the basic climate may be a prerequisite for producing a realistic intraseasonal oscillation. In particular, models with the most realistic intraseasonal oscillations appear to have precipitation distributions which are better correlated with warm sea surface temperatures. These models predominantly employ convective parameterizations which are closed on buoyancy rather than moisture convergence.

Quantifying the risk of extreme seasonal precipitation events in a changing climate

Increasing concentrations of atmospheric carbon dioxide will almost certainly lead to changes in global mean climate. But because—by definition—extreme events are rare, it is significantly more difficult to quantify the risk of extremes. Ensemble-based probabilistic predictions, as used in short- and medium-term forecasts of weather and climate, are more useful than deterministic forecasts using a ‘best guess’ scenario to address this sort of problem. Here we present a probabilistic analysis of 19 global climate model simulations with a generic binary decision model. We estimate that the probability of total boreal winter precipitation exceeding two standard deviations above normal will increase by a factor of five over parts of the UK over the next 100 years. We find similar increases in probability for the Asian monsoon region in boreal summer, with implications for flooding in Bangladesh. Further practical applications of our techniques would be helped by the use of larger ensembles (for a more complete sampling of model uncertainty) and a wider range of scenarios at a resolution adequate to analyse average-size river basins.

The rationale behind the success of multi‐model ensembles in seasonal forecasting – I. Basic concept

The DEMETER multi-model ensemble system is used to investigate the rationale behind the multi-model concept. A comprehensive documentation of the differences in the single and multi-model performance in the DEMETER hindcast data set is given. Both deterministic and probabilistic diagnostics are used and a variety of analyses demonstrate the improvements achieved by using multi-model instead of single-model ensembles. In order to understand the reason behind the multi-model superiority, basic scenarios describing how the multi-model approach can improve over singlemodel skill are discussed. It is demonstrated that multi-model superiority is caused not only by error compensation but in particular by its greater consistency and reliability.

The ‘surf zone’ in the stratosphere

Abstract Synoptic, coarse-grain, isentropic maps of Ertels potential vorticity Q for the northern middle stratosphere, estimated using a large-Richardson-number approximation, are presented for a number of days in January–February 1979, together with some related isentropic trajectory calculations The effects of substituting FGGE for NMC base data are noted, as well as some slight corrections to maps published earlier. The combined evidence from the observations and from dynamical models strongly indicates the existence of planetary-wave breaking, a process in which material contours are rapidly and irreversibly deformed. In the winter stratosphere this occurs most spectacularly in a gigantic ‘nonlinear critical layer’, or ‘surf zone’, which surrounds the main polar vortex, and which tends to erode the vortex when wave amplitudes become large. Some of the FGGE-based Q maps suggest that we may be seeing glimpses of local dynamical instabilities and vortex-rollup phenomena within breaking planetary waves. Related phenomena in the troposphere are discussed. An objective definition of the area A(t) of the main vortex, as it appears on isentropic Q maps, is proposed. A smoothed time series of daily values of A(t) should be a statistically powerful ‘circulation index’ for the state of the winter-time middle stratosphere, which avoids the loss of information incurred by Eulerian space and time averaging.

Singular Vectors, Metrics, and Adaptive Observations

Singular vectors of the linearized equations of motion have been used to study the instability properties of the atmosphere‐ocean system and its related predictability. A third use of these singular vectors is proposed here: as part of a strategy to target adaptive observations to ‘‘sensitive’’ parts of the atmosphere. Such observations could be made using unmanned aircraft, though calculations in this paper are motivated by the upstream component of the Fronts and Atlantic Storm-Track Experiment. Oceanic applications are also discussed. In defining this strategy, it is shown that there is, in principle, no freedom in the choice of inner product or metric for the singular vector calculation. However, the correct metric is dependent on the purpose for making the targeted observations (to study precursor developments or to improve forecast initial conditions). It is argued that for predictability studies, where both the dynamical instability properties of the system and the specification of the operational observing network and associated data assimilation system are important, the appropriate metric will differ from that appropriate to a pure geophysical fluid dynamics (GFD) problem. Based on two different sets of calculations, it is argued that for predictability studies (but not for GFD studies), a first-order approximation to the appropriate metric can be based on perturbation energy. The role of observations in data assimilation procedures (constraining large scales more than small scales) is fundamental in understanding reasons for the requirement for different metrics for the two classes of problems. An index-based tensor approach is used to make explicit the role of the metric. The strategy for using singular vectors to target adaptive observations is discussed in the context of other possible approaches, specifically, based on breeding vectors, potential vorticity diagnosis, and sensitivity vectors. The basic premises underlying the use of breeding and singular vectors are discussed. A comparison of the growth rates of breeding and singular vectors is made using a T21 quasigeostrophic model. Singular vectors and subjective potential vorticity (PV) diagnosis are compared for a particular case study. The areas of sensitivity indicated by the two methods only partially agree. Reasons for disagreement hinge around the fact that subjective PV diagnosis emphasizes Lagrangian advection, whereas singular vector analysis emphasizes wave propagation. For the latter, areas of sensitivity may be associated with regions of weak PV gradient, for example, mid to lower troposphere. Amplification of singular vectors propagating from regions of weak PV gradient to regions of strong PV gradient is discussed in terms of pseudomomentum conservation. Evidence is shown that analysis error may be as large in the lower midtroposphere as in the upper troposphere.