MONTHLY WEATHER REVIEW 138 (2010) 3157-3174
Bulletin of the American Meteorological Society 91 (2010) 1357-1363
The EC-Earth consortium is a grouping of meteorologists and Earth-system scientists from 10 European countries, put together to face the challenges of climate and weather forecasting. The NWP system of the European Centre for Medium-Range Weather Forecasts (ECWMF) forms the basis of the EC-Earth Earth-system model. NWP models are designed to accurately capture short-term atmospheric fluctuations. They are used for forecasts at daily-to-seasonal time scales and include data assimilation capabilities. Climate models are designed to represent the global coupled ocean-atmosphere system. The atmospheric model of EC-Earth version 2, is based on ECMWF's Integrated Forecasting System (IFS), cycle 31R1, corresponding to the current seasonal forecast system of ECMWF. The EC-Earth consortium and ECMWF are collaborating on development of initialization procedures to improve long-term predictions. The EC-Earth model displays good performance from daily up to inter-annual time scales and for long-term mean climate.
Impact of 2007 and 2008 Arctic ice anomalies on the atmospheric circulation: Implications for long-range predictions
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 136 (2010) 1655-1664
Journal of Geophysical Research: Atmospheres 115 (2010)
Lagrangian Cloud Model (LCM) is a mixed Eulerian/Lagrangian approach to atmospheric large eddy simulation (LES), with two-way coupling between Eulerian dynamics and thermodynamics and Lagrangian microphysics. Since Lagrangian representation of microphysics does not suffer from numerical diffusion in the radius space and solves full droplet growth equations, it may be considered an alternative for the bin approach. This paper documents the development of LCM to include collision/coalescence processes. The proposed algorithm maps Lagrangian parcels collision/coalescence events on the specified two-dimensional grid, with the first dimension spanning aerosol radius and the second dimension spanning the cloud droplet radius. The proposed approach is capable of representation of aerosol activation, deactivation, transport inside the droplets, and processing by clouds and in the future may be used to investigate details of these processes. As an illustration, LCM with collision/coalescence is used to investigate effects of aerosols on cloud microphysics and dynamics for a marine stratocumulus cloud. Two extreme cases are considered that represent low and high aerosol concentrations. It is shown that the aerosol type significantly affects cloud microphysics as well as cloud dynamics. In agreement with previous studies, a larger entrainment rate is simulated for the high aerosol concentration. For the low aerosol concentration, intense collision/coalescence and drizzle modify the aerosol size distribution, reducing the concentration in the dry radius range of 0.02 to 0.2 m and increasing the concentration for dry radii larger than 0.3 m. © Copyright 2010 by the American Geophysical Union.
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 91 (2010) 1493-U121
Forecast quality assessment of the ENSEMBLES seasonal-to-decadal Stream 2 hindcasts. ECMWF Tech Memo.
ECMWF (2010) 621
Decadal climate prediction with the ECMWF coupled forecast system: Impact of ocean observations. ECMWF Tech Memo.
ECMWF Newsletter ECMWF 122 (2010) 21-26
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
in Stochastic Physics and Climate Modelling, Cambridge University Press (2009) 15
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.
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)
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.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 135 (2009) 1117-1132
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.
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