Extratropical low-frequency variability in a three-level quasi-geostrophic atmospheric model with different spectral resolution
Journal of Geophysical Research D: Atmospheres 108 (2003) ACL 8-1 ACL 8-20-
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.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 128 (2002) 1641-1670
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 128 (2002) 747-774
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.
MONTHLY WEATHER REVIEW 129 (2001) 2226-2248
ATMOSPHERIC SCIENCE LETTERS 2 (2001) 72-80
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.
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
JOURNAL OF CLIMATE 14 (2001) 3212-3226
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 127 (2001) 709-731
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 127 (2001) 685-708
Atmospheric Science Letters 2 (2001) LI-LIX
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.
Niederfrequente Variabilität großräumiger atmosphärischer Zirkulationsstrukturen in spektralen Modellen niederer Ordnung. Reports on Polar Research.
AWI (2000) 356
TELLUS SERIES A-DYNAMIC METEOROLOGY AND OCEANOGRAPHY 52 (2000) 391-411
REPORTS ON PROGRESS IN PHYSICS 63 (2000) 71-116
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 126 (2000) 2035-2067
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 126 (2000) 2013-2033
METEOROLOGICAL APPLICATIONS 7 (2000) 163-175
JOURNAL OF THE ATMOSPHERIC SCIENCES 57 (2000) 1327-1340