Abstract

From observations and a variety of general circulation modeling evidence, it is suggested that the exceptionally cold weather experienced over much of the United States during some recent winter months (e.g., January 1985, December 1976–February 1977) was associated with enhanced latent heat release over the tropical West Pacific. The mechanism associated with such enhancement may not be unique.

Abstract

Long-standing systematic model errors in both tropics and extratropics of the ECMWF model run at a horizontal resolution typical for climate models are investigated. Based on the hypothesis that the misrepresentation of unresolved scales contributes to the systematic model error, three model refinements aimed at their representation—fluctuating or deterministically—are investigated.

Increasing horizontal resolution to explicitly simulate smaller-scale features, representing subgrid-scale fluctuations by a stochastic parameterization, and improving the deterministic physics parameterizations all lead to a decrease in the systematic bias of the Northern Hemispheric circulation. These refinements reduce the overly zonal flow and improve the model’s ability to capture the frequency of blocking. However, the model refinements differ greatly in their impact in the tropics. While improving the deterministic and introducing stochastic parameterizations reduces the systematic precipitation bias and improves the characteristics of convectively coupled waves and tropical variability in general, increasing horizontal resolution has little impact.

The fact that different model refinements can lead to reductions in systematic model error is consistent with the hypothesis that unresolved scales play an important role. At the same time, this degeneracy of the response to different forcings can lead to compensating model errors. Hence, if one takes the view that stochastic parameterization should be an important element of next-generation climate models, if only to provide reliable estimates of model uncertainty, then a fundamental conclusion of this study is that stochasticity should be incorporated within the design of physical process parameterizations and improvements of the dynamical core and not added a posteriori.

Abstract

In a, series of idealized numerical experiments, Butchart et al (1982) have recently established that the configuration of the mean zonal wind occurring immediately before the wavenumber-2 major stratospheric warming of February 1979 was crucial in subsequently focusing upward propagating planetary wave-activity into the high latitude stratosphere. In this sense, it was concluded that the stratospheric circumpolar flow should evolve to some preconditioned state before a wavenumber-2 major warming could occur.

In the present paper, the mechanisms responsible for the transition of the circumpolar flow from its normal midwinter state to this preconditioned state are investigated through a combination of observational numerical and theoretical studies. For the 1978–79 winter, this transition occurred during the substantial wavenumber-1 minor warming of January 1979, and the characteristic structure associated with the preconditioned mean zonal flow was established four days after the peak of this warming, during a period of intense high latitude acceleration. This latter phenomenon is referred to as a stratospheric sudden cooling. Observations of Eliassen-Palm flux cross-sections indicate that while wave, zonal mean-flow interaction theory could account for the qualitative evolution of the circumpolar flow during the warming, substantial nonlinear wave interactions were active during the cooling period, and these interactions significantly influenced the evolution of the circumpolar flow.

In a series of numerical experiments using a truncated semi-spectral model, we show that this sudden cooling phenomenon can be realistically reproduced in an idealized integration in which wave-wave interactions are present. By contrast, we were unable to simulate this phenomenon with these interactions removed.

Two different mechanisms are put forward to account for these nonlinearities. One mechanism is that of wave-breaking and associated potential vorticity mixing, as suggested by McIntyre (1982). The second mechanism is based on the notion of wave-activity, forced in the troposphere, propagating relative to isopleths of potential vorticity of some zonally asymmetric basic state.

Results of the observational and numerical study suggest that the first mechanism was dominant, and that potential vorticity mixing in the outer regions of the polar vortex was central to the process of preconditioning. Nevertheless, we believe that the second mechanism plays an important role in the dynamics of the stratosphere.

Abstract

Results from a set of 120-day ensemble integrations of a T63L19 version of the European Centre for Medium-Range Weather Forecasts (ECMWF) model are described. The integrations, started from observed initial conditions, used observed global sea surface temperature (SST) as a lower boundary condition. Each ensemble comprised three members initiated from consecutive analyses one day apart. The ensembles were analyzed over the last 90 days of the integration period, corresponding to conventional calendar seasons. Interannual variations in the atmosphere for the period 1986 to 1990 were studied in this way. The sign and magnitude of tropical Pacific SST anomalies were chosen to define an El Niño-Southern Oscillation (ENSO) index. Difference fields were formed from seasons in which this index was 1) large and of opposite sign and 2) small (and of opposite sign). The skill and spread of the ensemble simulations were determined over nine areas covering the globe. In general, the skill of the ensemble difference fields was higher for the strong ENSO-index years than for the weak ones, both in the tropics and the extratropics. In the northern extratropics, there was a tendency for the skill of the ensemble mean to be highest in the spring season. This was consistent with the fact that the internal spread of the ensemble also tended to be smallest in spring. Differences in zonally averaged zonal mean wind revealed that in the tropical and subtropical troposphere, the model simulations were quite accurate, particularly for the strong ENSO-index years. For both strong and weak ENSO-index years, the model correctly simulated differences in the tropical stratosphere associated with the quasi-biennial oscillation (QBO). Further experimentation confirmed that this was associated with a memory of initial conditions over the 120 days of the integration, and suggested some influence of the QBO in the upper tropical troposphere. From wind differences and analysis of changes to regime residence frequencies, it was concluded that while the SST anomalies associated with strong ENSO-index years had a significant influence on the extratropical circulation (including both North America and Europe), there was considerable intra-ensemble variability that affected the tropical Pacific area itself, including surface wind stress over the tropical Pacific. Intraensemble variability was also shown to be substantial in parts of the tropics associated with the summer monsoons over India and Southeast Asia. By contrast, rainfall over sub-Saharan Africa was more stable.

Abstract

In earlier work, it was proposed that the reliability of climate change projections, particularly of regional rainfall, could be improved if such projections were calibrated using quantitative measures of reliability obtained by running the same model in seasonal forecast mode. This proposal is tested for fast atmospheric processes (such as clouds and convection) by considering output from versions of the same atmospheric general circulation model run at two different resolutions and forced with prescribed sea surface temperatures and sea ice. Here output from the high-resolution version of the model is treated as a proxy for truth. The reason for using this approach is simply that the twenty-first-century climate change signal is not yet known and, hence, no climate change projections can be verified using observations. Quantitative assessments of reliability of the low-resolution model, run in seasonal hindcast mode, are used to calibrate climate change time-slice projections made with the same low-resolution model. Results show that the calibrated climate change probabilities are closer to the proxy truth than the uncalibrated probabilities. Given that seasonal forecasts are performed operationally already at several centers around the world, in a seamless forecast system they provide a resource that can be used without cost to help calibrate climate change projections and make them more reliable for users.

Abstract

Experiments with the atmospheric component of the ECMWF Integrated Forecasting System (IFS) have been carried out to study the origin of the atmospheric circulation anomalies that led to the unusually cold European winter of 2005/06. Experiments with prescribed sea surface temperature (SST) and sea ice fields fail to reproduce the observed atmospheric circulation anomalies suggesting that the role of SST and sea ice was either not very important or the atmospheric response to SST and sea ice was not very well captured by the ECMWF model. Additional experiments are carried out in which certain regions of the atmosphere are relaxed toward analysis data thereby artificially suppressing the development of forecast error. The relaxation experiments suggest that both tropospheric circulation anomalies in the Euro–Atlantic region and the anomalously weak stratospheric polar vortex can be explained by tropical circulation anomalies. Separate relaxation experiments for the tropical stratosphere and tropical troposphere highlight the role of the easterly phase of quasi-biennial oscillation (QBO) and, most importantly, tropospheric circulation anomalies, especially over South America and the tropical Atlantic. From the results presented in this study, it is argued that the relaxation technique is a powerful diagnostic tool to understand possible remote origins of seasonal-mean anomalies.

Abstract

Experiments with the ECMWF model are carried out to study the influence that a correct representation of the lower boundary conditions, the tropical atmosphere, and the Northern Hemisphere stratosphere would have on extended-range forecast skill of the extratropical Northern Hemisphere troposphere during boreal winter. Generation of forecast errors during the course of the integration is artificially reduced by relaxing the ECMWF model toward the 40-yr ECMWF Re-Analysis (ERA-40) in certain regions. Prescribing rather than persisting sea surface temperature and sea ice fields leads to a modest forecast error reduction in the extended range, especially over the North Pacific and North America; no beneficial influence is found in the medium range. Relaxation of the tropical troposphere leads to reduced extended-range forecast errors especially over the North Pacific, North America, and the North Atlantic. It is shown that a better representation of the Madden–Julian oscillation is of secondary importance for explaining the results of the tropical relaxation experiments. The influence from the tropical stratosphere is negligible. Relaxation of the Northern Hemisphere stratosphere leads to forecast error reduction primarily in high latitudes and over Europe. However, given the strong influence from the troposphere onto the Northern Hemisphere stratosphere it is argued that stratospherically forced experiments are very difficult to interpret in terms of their implications for extended-range predictability of the tropospheric flow. The results are discussed in the context of future forecasting system development.

Abstract

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.

Abstract

The sensitivity of forecast errors to initial conditions is used to examine the optimality of perturbations constructed from the singular vectors of the tangent propagator of the European Centre for Medium-Range Weather Forecasts model. Sensitivity and pseudo-inverse perturbations based on the 48-h forecast error are computed as explicit linear combinations of singular vectors optimizing total energy over the Northern Hemisphere. It is assumed that these perturbations are close to the optimal perturbation that can be constructed from a linear combination of these singular vectors. Optimality is measured primarily in terms of the medium-range forecast improvement obtained by adding the perturbations a posteriori to the initial conditions. Several issues are addressed in the context of these experiments, including the ability of singular vectors to describe forecast error growth beyond the optimization interval, the number of singular vectors required, and the implications of nonmodal error growth. Supporting evidence for the use of singular vectors based on a total energy metric for studying atmospheric predictability is also presented.

In general, less than 30 singular vectors capture a large fraction of the variance of the Northern Hemisphere sensitivity pattern obtained from a T63 adjoint model integration, especially in cases of low forecast skill. The sensitivity patterns for these cases tend to be highly localized with structures determined by the dominant singular vectors. Forecast experiments with these perturbations show significant improvements in skill in the medium range, indicating that singular vectors optimized for a short-range forecast continue to provide a useful description of error growth well beyond this time. The results suggest that ensemble perturbations based on 10–30 singular vectors should provide a reasonable description of the medium-range forecast uncertainty, although the inclusion of additional singular vectors is likely to be beneficial.

Nonmodality is a key consideration in the construction of optimal perturbations. There is virtually no projection between the contemporaneous unstable subspaces at the end of one forecast trajectory portion and the beginning of a second, consecutive portion. Sensitivity and ensemble perturbations constructed using the evolved singular vectors from a previous (day−2) forecast are suboptimal for the current (day+0) forecast initial conditions. It is argued that these results have implications for a range of issues in atmospheric predictability including ensemble weather prediction, data assimilation, and the development of adaptive observing techniques.

Abstract

It is now acknowledged that representing model uncertainty in atmospheric simulators is essential for the production of reliable probabilistic forecasts, and a number of different techniques have been proposed for this purpose. This paper presents new perturbed parameter schemes for use in the European Centre for Medium-Range Weather Forecasts (ECMWF) convection scheme. Two types of scheme are developed and implemented. Both schemes represent the joint uncertainty in four of the parameters in the convection parameterization scheme, which was estimated using the Ensemble Prediction and Parameter Estimation System (EPPES). The first scheme developed is a fixed perturbed parameter scheme, where the values of uncertain parameters are varied between ensemble members, but held constant over the duration of the forecast. The second is a stochastically varying perturbed parameter scheme. The performance of these schemes was compared to the ECMWF operational stochastic scheme, stochastically perturbed parameterization tendencies (SPPT), and to a model that does not represent uncertainty in convection. The skill of probabilistic forecasts made using the different models was evaluated. While the perturbed parameter schemes improve on the stochastic parameterization in some regards, the SPPT scheme outperforms the perturbed parameter approaches when considering forecast variables that are particularly sensitive to convection. Overall, SPPT schemes are the most skillful representations of model uncertainty owing to convection parameterization.