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Independent Estimations of the Asymptotic Variability in an Ensemble Forecast System
Sveriges meteorologiska och hydrologiska institut (SMHI), Norrköping.
Stockholms universitet, Naturvetenskapliga fakulteten, Meteorologiska institutionen (MISU).
Stockholms universitet, Naturvetenskapliga fakulteten, Meteorologiska institutionen (MISU).
2008 (engelsk)Inngår i: Monthly Weather Review, ISSN 0027-0644, E-ISSN 1520-0493, Vol. 136, nr 11, s. 4105-4112Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

One desirable property within an ensemble forecast system is to have a one-to-one ratio between the root-mean-square error (rmse) of the ensemble mean and the standard deviation of the ensemble (spread). The ensemble spread and forecast error within the ECMWF ensemble prediction system has been extrapolated beyond 10 forecast days using a simple model for error growth. The behavior of the ensemble spread and the rmse at the time of the deterministic predictability are compared with derived relations of rmse at the infinite forecast length and the characteristic variability of the atmosphere in the limit of deterministic predictability. Utilizing this methodology suggests that the forecast model and the atmosphere do not have the same variability, which raises the question of how to obtain a perfect ensemble.

sted, utgiver, år, opplag, sider
2008. Vol. 136, nr 11, s. 4105-4112
Emneord [en]
Ensembles, Forecasting techniques
HSV kategori
Forskningsprogram
atmosfärvetenskap och oceanografi
Identifikatorer
URN: urn:nbn:se:su:diva-14999DOI: 10.1175/2008MWR2526.1ISI: 000260861900006OAI: oai:DiVA.org:su-14999DiVA, id: diva2:181519
Tilgjengelig fra: 2009-01-13 Laget: 2009-01-13 Sist oppdatert: 2017-12-13bibliografisk kontrollert
Inngår i avhandling
1. Sampling uncertainties in ensemble weather forecasting
Åpne denne publikasjonen i ny fane eller vindu >>Sampling uncertainties in ensemble weather forecasting
2009 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

The aim of ensemble weather forecasting is to provide probability forecasts for the occurrence of meteorological events. The ensembles are constructed by assembling several forecast realisations, each member of the ensemble being constructed to sample the uncertainties in the forecast. These originate from uncertainties in the initial conditions (the analysis) and imperfections of the numerical model. 

 In order to sample the initial uncertainties several techniques have been proposed. The singular-vector technique yields perturbations optimised to maximize the perturbation growth over a finite time interval, whereas the breeding method recycles the perturbations from the previous ensemble in order to sample growing modes.  The ensemble-transform method represents a further development of the breeding method. Here, to create initial perturbations independent of the current flow situation of the atmosphere, random perturbations are introduced by using the difference between two randomly chosen atmospheric states (i.e. analyses). The method produces dynamically balanced perturbations denoted Random Field perturbations (RF). 

 Our results show that the RF perturbations initially have the same dynamical properties as the variability of the atmosphere. After integration over a day the perturbations from all three methods (RF, singular vectors and ensemble transform perturbations) converge. The skill scores indicate a statistically significant advantage for the RF method during the first 2-3 days for most of the evaluated parameters. Over the medium range (3-8 days) the differences are very small. We also discuss the influence of the asymptotic variability of the forecasting model on the ensemble properties.

 

sted, utgiver, år, opplag, sider
Stockholm: Department of Meteorology, Stockholm University, 2009. s. 52
Emneord
Ensemble forecasting, Initial perturbation techniques
HSV kategori
Forskningsprogram
meteorologi
Identifikatorer
urn:nbn:se:su:diva-27021 (URN)978-91-7155-865-7 (ISBN)
Disputas
2009-06-05, William-Olssonsalen, Geovetenskapens hus, Svante Arrhenius väg 8 A, Stockholm, 10:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2009-05-14 Laget: 2009-04-22 Sist oppdatert: 2009-04-22bibliografisk kontrollert
2. On the Convective-Scale Predictability of the Atmosphere
Åpne denne publikasjonen i ny fane eller vindu >>On the Convective-Scale Predictability of the Atmosphere
2012 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

A well-represented description of convection in weather and climate models is essential since convective clouds strongly influence the climate system. Convective processes interact with radiation, redistribute sensible and latent heat and momentum, and impact hydrological processes through precipitation. Depending on the models’ horizontal resolution, the representation of convection may look very different. However, the convective scales not resolved by the model are traditionally parameterized by an ensemble of non-interacting convective plumes within some area of uniform forcing, representing the “large scale”. A bulk representation of the mass-flux associated with the individual plumes in the defined area provide the statistical effect of moist convection on the atmosphere. Studying the characteristics of the ECMWF ensemble prediction system it is found that the control forecast of the ensemble system is not variable enough in order to yield a sufficient spread using an initial perturbation technique alone. Such insufficient variability may be addressed in the parameterizations of, for instance, cumulus convection where the sub-grid variability in space and time is traditionally neglected. Furthermore, horizontal transport due to gravity waves can act to organize deep convection into larger scale structures which can contribute to an upscale energy cascade. However, horizontal advection and numerical diffusion are the only ways through which adjacent model grid-boxes interact in the models. The impact of flow dependent horizontal diffusion on resolved deep convection is studied, and the organization of convective clusters is found very sensitive to the method of imposing horizontal diffusion. However, using numerical diffusion in order to represent lateral effects is undesirable. To address the above issues, a scheme using cellular automata in order to introduce lateral communication, memory and a stochastic representation of the statistical effects of cumulus convection is implemented in two numerical weather models. The behaviour of the scheme is studied in cases of organized convective squall-lines, and initial model runs show promising improvements.

sted, utgiver, år, opplag, sider
Stockholm: Department of Meteorology, Stockholm University, 2012. s. 45
Emneord
Cumulus convection, cellular automata, model uncertainty, sub-grid scale processes, numerical weather prediction
HSV kategori
Forskningsprogram
atmosfärvetenskap och oceanografi
Identifikatorer
urn:nbn:se:su:diva-75195 (URN)978-91-7447-494-7 (ISBN)
Disputas
2012-05-25, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 10:00 (engelsk)
Opponent
Veileder
Merknad

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Submitted. 

Tilgjengelig fra: 2012-05-03 Laget: 2012-04-11 Sist oppdatert: 2013-04-10bibliografisk kontrollert

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