BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 91 (2010) 1493-U121
Impact of a quasi-stochastic cellular automaton backscatter scheme on the systematic error and seasonal prediction skill of a global climate model
in Stochastic Physics and Climate Modelling, Cambridge University Press (2009) 15
Revolution in climate prediction is both necessary and possible: A declaration at the world modelling summit for climate prediction
Bulletin of the American Meteorological Society 90 (2009) 175-178
Addressing the global climate change, the World climate Research Program (WCRP) held a World Modeling summit for Climate Prediction on 6-9 May 2008 in Reading, England, to develop a strategy in revolutionizing prediction of the climate. The summit was cosponsored by the World Weather Research Program (WWRP) and the International Geosphere-Biosphere Program (IGBP). The event has given emphasis on the simulation and prediction of the physical climate system. The summit tried to identify challenges which are grouped into following areas such as process-based model evaluation; data assimilation, analysis, and initialization; detection and attribution of climate events; and ensembles.
Journal of the Atmospheric Sciences 66 (2009) 2493-2500
This note presents an analysis of several dozens of direct numerical simulations of the cloud - clear air mixing in a setup of decaying moist turbulence with bin microphysics. The goal is to assess the instantaneous relationship between the homogeneity of mixing and the ratio of the time scales of droplet evaporation and turbulent homogenization. Such a relationship is important for developing improved microphysical parameterizations for large-eddy simulation of clouds. The analysis suggests a robust relationship for the range of time scale ratios between 0.5 and 10. Outside this range, the scatter of numerical data is significant, with smaller and larger time scale ratios corresponding to mixing scenarios that approach the extremely inhomogeneous and homogeneous limits, respectively. This is consistent with the heuristic argument relating the homogeneity of mixing to the time scale ratio. © 2009 American Meteorological Society.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 135 (2009) 1117-1132
The Invariant Set Postulate: a new geometric framework for the foundations of quantum theory and the role played by gravity
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES 465 (2009) 3165-3185
ENSEMBLES: A new multi-model ensemble for seasonal-to-annual predictions - Skill and progress beyond DEMETER in forecasting tropical Pacific SSTs
Geophysical Research Letters 36 (2009)
A new 46-year hindcast dataset for seasonal-to-annual ensemble predictions has been created using a multi-model ensemble of 5 state-of-the-art coupled atmosphere-ocean circulation models. The multi-model outperforms any of the single-models in forecasting tropical Pacific SSTs because of reduced RMS errors and enhanced ensemble dispersion at all lead-times. Systematic errors are considerably reduced over the previous generation (DEMETER). Probabilistic skill scores show higher skill for the new multi-model ensemble than for DEMETER in the 4-6 month forecast range. However, substantially improved models would be required to achieve strongly statistical significant skill increases. The combination of ENSEMBLES and DEMETER into a grand multi-model ensemble does not improve the forecast skill further. Annual-range hindcasts show anomaly correlation skill of ∼0.5 up to 14 months ahead. A wide range of output from the multi-model simulations is becoming publicly available and the international community is invited to explore the full scientific potential of these data. Copyright 2009 by the American Geophysical Union.
Toward Seamless Prediction: Calibration of Climate Change Projections Using Seasonal Forecasts Reply
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 90 (2009) 1551-1554
Proceedings of the XXVII International Symposium on Lattice Field Theory ‘Lattice 2009' (2009)
A Spectral Stochastic Kinetic Energy Backscatter Scheme and Its Impact on Flow-Dependent Predictability in the ECMWF Ensemble Prediction System
JOURNAL OF THE ATMOSPHERIC SCIENCES 66 (2009) 603-626
Quarterly Journal of the Royal Meteorological Society 135 (2009) 1538-1559
The relative merits of three forecast systems addressing the impact of model uncertainty on seasonal/annual forecasts are described. One system consists of a multi-model, whereas two other systems sample uncertainties by perturbing the parametrization of reference models through perturbed parameter and stochastic physics techniques. Ensemble reforecasts over 1991 to 2001 were performed with coupled climate models started from realistic initial conditions. Forecast quality varies due to the different strategies for sampling uncertainties, but also to differences in initialisation methods and in the reference forecast system. Both the stochastic-physics and perturbed-parameter ensembles improve the reliability with respect to their reference forecast systems, but not the discrimination ability. Although the multi-model experiment has an ensemble size larger than the other two experiments, most of the assessment was done using equally-sized ensembles. The three ensembles show similar levels of skill: significant differences in performance typically range between 5 and 20%. However, a nine-member multi-model shows better results for seasonal predictions with lead times shorter than five months, followed by the stochastic-physics and perturbed-parameter ensembles. Conversely, for seasonal predictions with lead times longer than four months, the perturbed-parameter ensemble gives more often better results. All systems suggest that spread cannot be considered a useful predictor of skill. Annual-mean predictions showed lower forecast quality than seasonal predictions. Only small differences between the systems were found. The full multi-model ensemble has improved quality with respect to all other systems, mainly from the larger ensemble size for lead times longer than four months and annual predictions. © 2009 Royal Meteorological Society and Crown Copyright.
The Microscope McCrone Research Institute 4 (2009) 157-163
We describe laboratory-grown snow crystals that exhibit a triangular, plate-like morphology, and we show that the occurrence of these crystals is much more frequent than one would expect from random growth perturbations of the more-typical hexagonal forms. We then describe an aerodynamic model that explains the formation of these crystals. A single growth perturbation on one facet of a hexagonal plate leads to air flow around the crystal that promotes the growth of alternating facets. Aerodynamic effects thus produce a weak growth instability that can cause hexagonal plates to develop into triangular plates. This mechanism solves a very old puzzle, as observers have been documenting the unexplained appearance of triangular snow crystals in nature for nearly two centuries.
Quarterly Journal of the Royal Meteorological Society 135 (2009) 1095-1103
There is a growing interest in using stochastic parametrizations in numerical weather and climate prediction models. Previously, Palmer (2001) outlined the issues that give rise to the need for a stochastic parametrization and the forms such a parametrization could take. In this article a method is presented that uses a comparison between a standard-resolution version and a high-resolution version of the same model to gain information relevant for a stochastic parametrization in that model. A correction term that could be used in a stochastic parametrization is derived from the thermodynamic equations of both models. The origin of the components of this term is discussed. It is found that the component related to unresolved wave-wave interactions is important and can act to compensate for large parametrized tendencies. The correction term is not proportional to the parametrized tendency. Finally, it is explained how the correction term could be used to give information about the shape of the random distribution to be used in a stochastic parametrization. © 2009 Royal Meteorological Society.
Impact of a quasi-stochastic cellular automaton backscatter scheme on the systematic error and seasonal prediction skill of a global climate model.
Philos Trans A Math Phys Eng Sci 366 (2008) 2561-2579
The impact of a nonlinear dynamic cellular automaton (CA) model, as a representation of the partially stochastic aspects of unresolved scales in global climate models, is studied in the European Centre for Medium Range Weather Forecasts coupled ocean-atmosphere model. Two separate aspects are discussed: impact on the systematic error of the model, and impact on the skill of seasonal forecasts. Significant reductions of systematic error are found both in the tropics and in the extratropics. Such reductions can be understood in terms of the inherently nonlinear nature of climate, in particular how energy injected by the CA at the near-grid scale can backscatter nonlinearly to larger scales. In addition, significant improvements in the probabilistic skill of seasonal forecasts are found in terms of a number of different variables such as temperature, precipitation and sea-level pressure. Such increases in skill can be understood both in terms of the reduction of systematic error as mentioned above, and in terms of the impact on ensemble spread of the CA's representation of inherent model uncertainty.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 134 (2008) 1789-1799
The potential impacts of pollution on a nondrizzling stratus deck: Does aerosol number matter more than type?
Journal of Geophysical Research D: Atmospheres 113 (2008)
In this paper results from a cloud-resolving model that can efficiently examine the impact of aerosol on nondrizzling stratus clouds will be shown. Because the model tracks aerosol and cloud droplets in a Lagrangian framework, it does not suffer from numerical errors associated with advection, and unlike most Eulerian approaches, the method can track cloud boundaries as they move across a grid cell. After illustrating the capability of the model to reproduce various observed cloud statistics such as the cloud water mixing ratio and the mean cloud droplet radius from the DYCOMS-II field program, the ability of the model to assess the impact of changes in aerosol number and composition on a stratus deck will be highlighted. Specifically, by using activation curves appropriate for. soluble, insoluble, or a mixture of both types of aerosol and for certain extreme aerosol regimes, i.e., a majority of the aerosol are hydrophobic carbon aerosol, limiting situations were examined to bound their impact on clouds. However, though these situations may be somewhat extreme, they could occasionally occur in the atmosphere, e.g., an oceanic stratus field downwind of a large ship or an urban area. Not unexpectedly, results from these simulations support previous ship track observations that for increasing aerosol numbers, cloud droplet number concentrations increase, whereas cloud droplet radii decrease. However, these simulations also suggest that the correlation between cloud droplet number concentration and aerosol number concentration may be not only a function of aerosol number concentration but also aerosol types and/or cloud dynamics.