54 resultados para weather systems


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There is widely believed to be a link between stratospheric flow variability and stationary, persistent “blocking” weather systems, but the precise nature of this link has proved elusive. Using data from the ERA-40 Reanalysis and an atmospheric general circulation model (GCM) with a well-resolved stratosphere (HadGAM), it is shown that there are in fact several different highly significant associations, with blocking in different regions being related to different patterns of stratospheric variability. This is true in both hemispheres and in both data sets. The associations in HadGAM are shown to be very similar to those in ERA-40, although the model has a tendency to underestimate both European blocking and the wave number 2 stratospheric variability to which this is related. Although the focus is on stratospheric variability in general, several of the blocking links are seen to occur in association with the major stratospheric sudden warmings. In general, the direction of influence appears to be upward, as blocking anomalies are shown to modify the planetary stationary waves, leading to an upward propagation of wave activity into the stratosphere. However, significant correlations are also apparent with the zonal mean flow in the stratosphere leading the occurrence of blocking at high latitudes. Finally, the underestimation of blocking is an enduring problem in GCMs, and an example has recently been given in which improving the resolution of the stratosphere improved the representation of blocking. Here, however, another example is given, in which increasing the stratospheric resolution unfortunately does not lead to an improvement in blocking.

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The winter climate of Europe and the Mediterranean is dominated by the weather systems of the mid-latitude storm tracks. The behaviour of the storm tracks is highly variable, particularly in the eastern North Atlantic, and has a profound impact on the hydroclimate of the Mediterranean region. A deeper understanding of the storm tracks and the factors that drive them is therefore crucial for interpreting past changes in Mediterranean climate and the civilizations it has supported over the last 12 000 years (broadly the Holocene period). This paper presents a discussion of how changes in climate forcing (e.g. orbital variations, greenhouse gases, ice sheet cover) may have impacted on the ‘basic ingredients’ controlling the mid-latitude storm tracks over the North Atlantic and the Mediterranean on intermillennial time scales. Idealized simulations using the HadAM3 atmospheric general circulation model (GCM) are used to explore the basic processes, while a series of timeslice simulations from a similar atmospheric GCM coupled to a thermodynamic slab ocean (HadSM3) are examined to identify the impact these drivers have on the storm track during the Holocene. The results suggest that the North Atlantic storm track has moved northward and strengthened with time since the Early to Mid-Holocene. In contrast, the Mediterranean storm track may have weakened over the same period. It is, however, emphasized that much remains still to be understood about the evolution of the North Atlantic and Mediterranean storm tracks during the Holocene period.

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The background error covariance matrix, B, is often used in variational data assimilation for numerical weather prediction as a static and hence poor approximation to the fully dynamic forecast error covariance matrix, Pf. In this paper the concept of an Ensemble Reduced Rank Kalman Filter (EnRRKF) is outlined. In the EnRRKF the forecast error statistics in a subspace defined by an ensemble of states forecast by the dynamic model are found. These statistics are merged in a formal way with the static statistics, which apply in the remainder of the space. The combined statistics may then be used in a variational data assimilation setting. It is hoped that the nonlinear error growth of small-scale weather systems will be accurately captured by the EnRRKF, to produce accurate analyses and ultimately improved forecasts of extreme events.

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Interest in attributing the risk of damaging weather-related events to anthropogenic climate change is increasing1. Yet climate models used to study the attribution problem typically do not resolve the weather systems associated with damaging events2 such as the UK floods of October and November 2000. Occurring during the wettest autumn in England and Wales since records began in 17663, 4, these floods damaged nearly 10,000 properties across that region, disrupted services severely, and caused insured losses estimated at £1.3 billion (refs 5, 6). Although the flooding was deemed a ‘wake-up call’ to the impacts of climate change at the time7, such claims are typically supported only by general thermodynamic arguments that suggest increased extreme precipitation under global warming, but fail8, 9 to account fully for the complex hydrometeorology4, 10 associated with flooding. Here we present a multi-step, physically based ‘probabilistic event attribution’ framework showing that it is very likely that global anthropogenic greenhouse gas emissions substantially increased the risk of flood occurrence in England and Wales in autumn 2000. Using publicly volunteered distributed computing11, 12, we generate several thousand seasonal-forecast-resolution climate model simulations of autumn 2000 weather, both under realistic conditions, and under conditions as they might have been had these greenhouse gas emissions and the resulting large-scale warming never occurred. Results are fed into a precipitation-runoff model that is used to simulate severe daily river runoff events in England and Wales (proxy indicators of flood events). The precise magnitude of the anthropogenic contribution remains uncertain, but in nine out of ten cases our model results indicate that twentieth-century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales in autumn 2000 by more than 20%, and in two out of three cases by more than 90%.

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This paper will introduce the Baltex research programme and summarize associated numerical modelling work which has been undertaken during the last five years. The research has broadly managed to clarify the main mechanisms determining the water and energy cycle in the Baltic region, such as the strong dependence upon the large scale atmospheric circulation. It has further been shown that the Baltic Sea has a positive water balance, albeit with large interannual variations. The focus on the modelling studies has been the use of limited area models at ultra-high resolution driven by boundary conditions from global models or from reanalysis data sets. The programme has further initiated a comprehensive integration of atmospheric, land surface and hydrological modelling incorporating snow, sea ice and special lake models. Other aspects of the programme include process studies such as the role of deep convection, air sea interaction and the handling of land surface moisture. Studies have also been undertaken to investigate synoptic and sub-synoptic events over the Baltic region, thus exploring the role of transient weather systems for the hydrological cycle. A special aspect has been the strong interests and commitments of the meteorological and hydrological services because of the potentially large societal interests of operational applications of the research. As a result of this interests special attention has been put on data-assimilation aspects and the use of new types of data such as SSM/I, GPS-measurements and digital radar. A series of high resolution data sets are being produced. One of those, a 1/6 degree daily precipitation climatology for the years 1996–1999, is such a unique contribution. The specific research achievements to be presented in this volume of Meteorology and Atmospheric Physics is the result of a cooperative venture between 11 European research groups supported under the EU-Framework programmes.

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The purpose of this lecture is to review recent development in data analysis, initialization and data assimilation. The development of 3-dimensional multivariate schemes has been very timely because of its suitability to handle the many different types of observations during FGGE. Great progress has taken place in the initialization of global models by the aid of non-linear normal mode technique. However, in spite of great progress, several fundamental problems are still unsatisfactorily solved. Of particular importance is the question of the initialization of the divergent wind fields in the Tropics and to find proper ways to initialize weather systems driven by non-adiabatic processes. The unsatisfactory ways in which such processes are being initialized are leading to excessively long spin-up times.

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Changes in the frequency and intensity of cyclones and associated windstorms affecting the Medi-terranean region simulated under enhanced Greenhouse Gas forcing conditions are investigated. The analysis is based on 7 climate model integrations performed with two coupled global models (ECHAM5 MPIOM and INGV CMCC), comparing the end of the twentieth century and at least the first half of the twenty-first century. As one of the models has a considerably enhanced resolution of the atmosphere and the ocean, it is also investigated whether the climate change signals are influenced by the model resolution. While the higher resolved simulation is closer to reanalysis climatology, both in terms of cyclones and windstorm distributions, there is no evidence for an influence of the resolution on the sign of the climate change signal. All model simulations show a reduction in the total number of cyclones crossing the Mediterranean region under climate change conditions. Exceptions are Morocco and the Levant region, where the models predict an increase in the number of cyclones. The reduction is especially strong for intense cyclones in terms of their Laplacian of pressure. The influence of the simulated positive shift in the NAO Index on the cyclone decrease is restricted to the Western Mediterranean region, where it explains 10–50 % of the simulated trend, depending on the individual simulation. With respect to windstorms, decreases are simulated over most of the Mediterranean basin. This overall reduction is due to a decrease in the number of events associated with local cyclones, while the number of events associated with cyclones outside of the Mediterranean region slightly increases. These systems are, however, less intense in terms of their integrated severity over the Mediterranean area, as they mostly affect the fringes of the region. In spite of the general reduction in total numbers, several cyclones and windstorms of intensity unknown under current climate conditions are identified for the scenario simulations. For these events, no common trend exists in the individual simulations. Thus, they may rather be attributed to long-term (e.g. decadal) variability than to the Greenhouse Gas forcing. Nevertheless, the result indicates that high-impact weather systems will remain an important risk in the Mediterranean Basin.

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We investigate baroclinic instability in flow conditions relevant to hot extrasolar planets. The instability is important for transporting and mixing heat, as well as for influencing large-scale variability on the planets. Both linear normal mode analysis and non-linear initial value cal- culations are carried out – focusing on the freely-evolving, adiabatic situation. Using a high- resolution general circulation model (GCM) which solves the traditional primitive equations, we show that large-scale jets similar to those observed in current GCM simulations of hot ex- trasolar giant planets are likely to be baroclinically unstable on a timescale of few to few tens of planetary rotations, generating cyclones and anticyclones that drive weather systems. The growth rate and scale of the most unstable mode obtained in the linear analysis are in qual- itative, good agreement with the full non-linear calculations. In general, unstable jets evolve differently depending on their signs (eastward or westward), due to the change in sign of the jet curvature. For jets located at or near the equator, instability is strong at the flanks – but not at the core. Crucially, the instability is either poorly or not at all captured in simulations with low resolution and/or high artificial viscosity. Hence, the instability has not been observed or emphasized in past circulation studies of hot extrasolar planets.

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TIGGE was a major component of the THORPEX (The Observing System Research and Predictability Experiment) research program, whose aim is to accelerate improvements in forecasting high-impact weather. By providing ensemble prediction data from leading operational forecast centers, TIGGE has enhanced collaboration between the research and operational meteorological communities and enabled research studies on a wide range of topics. The paper covers the objective evaluation of the TIGGE data. For a range of forecast parameters, it is shown to be beneficial to combine ensembles from several data providers in a Multi-model Grand Ensemble. Alternative methods to correct systematic errors, including the use of reforecast data, are also discussed. TIGGE data have been used for a range of research studies on predictability and dynamical processes. Tropical cyclones are the most destructive weather systems in the world, and are a focus of multi-model ensemble research. Their extra-tropical transition also has a major impact on skill of mid-latitude forecasts. We also review how TIGGE has added to our understanding of the dynamics of extra-tropical cyclones and storm tracks. Although TIGGE is a research project, it has proved invaluable for the development of products for future operational forecasting. Examples include the forecasting of tropical cyclone tracks, heavy rainfall, strong winds, and flood prediction through coupling hydrological models to ensembles. Finally the paper considers the legacy of TIGGE. We discuss the priorities and key issues in predictability and ensemble forecasting, including the new opportunities of convective-scale ensembles, links with ensemble data assimilation methods, and extension of the range of useful forecast skill.

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Three land-fast ice stations (one of them was the Finnish research ice breaker Aranda) and the German research aircraft Falcon were applied to measure the turbulent and radiation fluxes over the ice edge zone in the northern Baltic Sea during the Baltic Air-Sea-Ice Study (BASIS) field experiment from 16 February to 6 March 1998. The temporal and spatial variability of the surface fluxes is discussed. Synoptic weather systems passed the experimental area in a rapid sequence and dominated the conditions (wind speed, airsurface temperature difference, cloud field) for the variability of the turbulent and radiation fluxes. At the ice stations, the largest upward sensible heat fluxes of about 100 Wm�2 were measured during the passage of a cold front when the air cooled faster (�5 K per hour) than the surface. The largest downward flux of about �200 Wm�2 occurred during warm air advection when the air temperature reached +10�C but the surface temperature remained at 0�C. Spatial variability of fluxes was observed from the small scale (scale of ice floes and open water spots) to the mesoscale (width of the ice edge zone). The degree of spatial variability depends on the synoptic situation: during melting conditions downward heat fluxes were the same over ice and open water, whereas during strong cold-air advection upward heat fluxes differed by more than 100 Wm�2. A remarkable amount of grey ice with intermediate surface temperature was observed. The ice in the Baltic Sea cannot be described by one ice type only.

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The prediction of extratropical cyclones by the European Centre for Medium Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) Ensemble Prediction Systems (EPS) has been investigated using an objective feature tracking methodology to identify and track the cyclones along the forecast trajectories. Overall the results show that the ECMWF EPS has a slightly higher level of skill than the NCEP EPS in the northern hemisphere (NH). However in the southern hemisphere (SH), NCEP has higher predictive skill than ECMWF for the intensity of the cyclones. The results from both EPS indicate a higher level of predictive skill for the position of extratropical cyclones than their intensity and show that there is a larger spread in intensity than position. Further analysis shows that the predicted propagation speed of cyclones is generally too slow for the ECMWF EPS and show a slight bias for the intensity of the cyclones to be overpredicted. This is also true for the NCEP EPS in the SH. For the NCEP EPS in the NH the intensity of the cyclones is underpredicted. There is small bias in both the EPS for the cyclones to be displaced towards the poles. For each ensemble forecast of each cyclone, the predictive skill of the ensemble member that best predicts the cyclones position and intensity was computed. The results are very encouraging showing that the predictive skill of the best ensemble member is significantly higher than that of the control forecast in terms of both the position and intensity of the cyclones. The prediction of cyclones before they are identified as 850 hPa vorticity centers in the analysis cycle was also considered. It is shown that an indication of extratropical cyclones can be given by at least 1 ensemble member 7 days before they are identified in the analysis. Further analysis of the ECMWF EPS shows that the ensemble mean has a higher level of skill than the control forecast, particularly for the intensity of the cyclones, 2 from day 3 of the forecast. There is a higher level of skill in the NH than the SH and the spread in the SH is correspondingly larger. The difference between the ensemble mean and spread is very small for the position of the cyclones, but the spread of the ensemble is smaller than the ensemble mean error for the intensity of the cyclones in both hemispheres. Results also show that the ECMWF control forecast has ½ to 1 day more skill than the perturbed members, for both the position and intensity of the cyclones, throughout the forecast.

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We unfold a profound relationship between the dynamics of finite-size perturbations in spatially extended chaotic systems and the universality class of Kardar-Parisi-Zhang (KPZ). We show how this relationship can be exploited to obtain a complete theoretical description of the bred vectors dynamics. The existence of characteristic length/time scales, the spatial extent of spatial correlations and how to time it, and the role of the breeding amplitude are all analyzed in the light of our theory. Implications to weather forecasting based on ensembles of initial conditions are also discussed.

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The application of particle filters in geophysical systems is reviewed. Some background on Bayesian filtering is provided, and the existing methods are discussed. The emphasis is on the methodology, and not so much on the applications themselves. It is shown that direct application of the basic particle filter (i.e., importance sampling using the prior as the importance density) does not work in high-dimensional systems, but several variants are shown to have potential. Approximations to the full problem that try to keep some aspects of the particle filter beyond the Gaussian approximation are also presented and discussed.