Journal of the Atmospheric Sciences 61 (2004) 1726-1739
This paper discusses results from a series of direct numerical simulations of the microscale cloud-clear air mixing, set forth in the idealized scenario of decaying moist turbulence. In the moist case, kinetic energy of microscale motions comes not only from the classical downscale energy cascade, but it can also be generated internally due to the evaporation of cloud droplets. Three sets of numerical simulations are performed for three intensities of initial large-scale eddies. In each set, a control dry simulation is performed, as well as two moist simulations applying either bulk or detailed representation of cloud microphysics. Model results suggest that, as far as the evolutions of enstrophy and turbulent kinetic energy are concerned, the most significant impact of moist processes occurs at the low intensity of initial large-scale eddies (the input turbulent kinetic energy of 2 X 10-4 m2 s-2 resulting in the maximum eddy dissipation rate of 5 X 10-4 m2 s-3). In such a case, mixing and homogenization are dominated by the kinetic energy generated as a result of evaporation of cloud water and its impact on the microscale buoyancy. Detailed microphysics, which explicitly treat the size dependence of cloud droplet sedimentation and evaporation, appear to have a comparatively small effect, although this result might be an artifact of a coarse grid resolution used in the simulations. High anisotropy, also observed in laboratory experiments with mixing, between cloudy and cloud-free air, prevails even at the high intensity of initial large-scale eddies (the input turbulent kinetic energy of 2 X 10-2 m2 s-2, the maximum eddy dissipation rate of 7 × 10-3 m2 s-3), despite the fact that mixing and homogenization proceed in a similar manner in moist and dry simulations. Impact on cloud microphysics is also quantified. Cloud droplet spectra at the end of simulations correspond to neither the extremely inhomogeneous nor homogeneous mixing scenarios-the two asymptotic limits where, respectively, either the cloud droplet size or the number of cloud droplets remain constant. The shift from low to high intensity of initial large-scale eddies shifts the mixing scenario toward the homogeneous case, corroborating the classical argument based on scale analysis. © 2004 American Meteorological Society.
Physica D: Nonlinear Phenomena 190 (2004) 153-166
Shadowing trajectories can play an important role in assessing the reliability of forecasting models, they can also play an important role in providing state estimates for ensemble forecasts. Gradient descent methods provide one approach for obtaining shadowing trajectories, which have been shown to have many useful properties. There remains the important question whether shadowing trajectories can be found in very high-dimensional systems, like weather and climate models. The principle impediment is the need to compute the derivative (or adjoint) of the system dynamics. In this paper we investigate gradient descent methods that use limited derivative information. We demonstrate the methods with an application to a moderately high-dimensional system using no derivative information at all. © 2003 Elsevier B.V. All rights rserved.
Appl Opt 42 (2003) 5891-5896
A number of techniques to track rainfall patterns by use of radar observations have been developed over the years. We present a method for radar-echo tracking based on Hu invariant moments. The method has been tried on several sequences of test images, and the derived displacement fields were in good agreement with the real motions of the tested objects. For the real data obtained from the conventional meteorological radar in Legionowo the method occasionally failed when changes in the radar echo between observations were too large.
REALIZING TERACOMPUTING (2003) 1-18
Extratropical low-frequency variability in a three-level quasi-geostrophic atmospheric model with different spectral resolution
Journal of Geophysical Research D: Atmospheres 108 (2003)
Apart from variations of external forcing components and interactions between climate subsystems, natural atmospheric fluctuations with periods of years, decades and centuries can also be generated by inherent atmospheric dynamical instabilities of the flow. The objective of this study is to investigate the spatial and temporal structure of internal low-frequency atmospheric variability of the Northern Hemisphere using a minimum-complexity model of the extratropical circulation. Here, the main focus is the influence of varying spectral horizontal resolution on the formation of dominant patterns of variability. For this purpose, a three-level quasi-geostrophic atmospheric model with idealized thermal and orographic forcing has been integrated over 1,000 years under perpetual winter conditions with T5, T10, T15, and T21 resolutions. It has been shown that for the crude resolution T5 a rather strong bias occurs, whereas starting with T1O resolution, the nonlinear feedback between large- and small-scale features is reasonably well described. At this resolution a sort of plateau in the model performance has been reached, in respect to both the model climatology and the spatiotemporal structure of variability. Ultralow-frequency variability is most pronounced in the model's stratosphere and is associated with changes in the polar vortex strength and shape caused by vertically propagating planetary waves. Rossby wave trains in the lee of the model large-scale orography are the most dominant structures of long-period fluctuations in the middle troposphere. The results show that interannual- and decadal-scale variations can, in substantial part, be considered as a manifestation of the natural variability of the extratropical atmosphere. The inclusion of a seasonal cycle of the model's diabatic heating increases the interannual and interdecadal variability.
FIRST CHAMP MISSION RESULTS FOR GRAVITY, MAGNETIC AND ATMOSPHERIC STUDIES (2003) 441-446
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 129 (2003) 2401-2423
Benefits of increased resolution in the ECMWF ensemble system and comparison with poor-man's ensembles
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 129 (2003) 1269-1288
Nature 415 (2002) 512-514
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.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 128 (2002) 1641-1670
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 128 (2002) 747-774
MONTHLY WEATHER REVIEW 129 (2001) 2226-2248
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 127 (2001) 685-708
JOURNAL OF CLIMATE 14 (2001) 3212-3226
Nonlinear Processes in Geophysics 8 (2001) 357-371
Operational forecasting is hampered both by the rapid divergence of nearby initial conditions and by error in the underlying model. Interest in chaos has fuelled much work on the first of these two issues; this paper focuses on the second. A new approach to quantifying state-dependent model error, the local model drift, is derived and deployed both in examples and in operational numerical weather prediction models. A simple law is derived to relate model error to likely shadowing performance (how long the model can stay close to the observations). Imperfect model experiments are used to contrast the performance of truncated models relative to a high resolution run, and the operational model relative to the analysis. In both cases the component of forecast error due to state-dependent model error tends to grow as the square-root of forecast time, and provides a major source of error out to three days. These initial results suggest that model error plays a major role and calls for further research in quantifying both the local model drift and expected shadowing times.
ATMOSPHERIC SCIENCE LETTERS 2 (2001) 72-80
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 127 (2001) 709-731
Atmospheric Science Letters 2 (2001)
In order to investigate whether climate models of different complexity have the potential to simulate natural atmospheric circulation regimes, 1000-year-long integrations with constant external forcing have been analysed. Significant non-Gaussian uni-, bi-, and trimodal probability density functions have been found in 100-year segments. © 2001 Royal Meteorological Society.
A nonlinear dynamical perspective on model error: A proposal for non-local stochastic-dynamic parametrization in weather and climate prediction models
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 127 (2001) 279-304
METEOROLOGICAL APPLICATIONS 7 (2000) 163-175