A kinetic energy backscatter algorithm for use in ensemble prediction systems

By G. Shutts. 2005

512 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/a0cfa38320dd5c3551d2e021885c2dcd4b2cd889

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Citations in the corpus

The forecast skill horizon (2015, background): “The stochastic back-scatter (SKEB: Shutts, 2005) scheme simulates the upscale energy transfer induced by the unresolved scales on the resolved scales.”
Stochastic climate theory and modeling (2015, unknown): “Furthermore, while current deterministic parameterization schemes are inconsistent with the observed power-law scaling of the energy spectrum 5,142 new statistical dynamical approaches that are un-51 derpinned by exact stochastic model representations have emerged that overcome this limitation.”
Toward a stochastic parameterization of ocean mesoscale eddies (2014, background): “center models (e.g., Frederiksen and Davies, 1997; Shutts, 2005; Bowler et al., 2009).”
SEAS5: the new ECMWF seasonal forecast system (2018, background): “The stochastic kinetic energy backscatter (SKEB) scheme aims at improving the upscale energy cascade from the sub-grid scales to the resolved scales (Shutts, 2005), but has been found to have a smaller overall impact in the ECMWF system (Weisheimer et al.”
The pros and cons of diffusion, filters and fixers in Atmospheric General Circulation Models (2011, methodology): “An alternative energy backscattering method was also presented by Shutts (2005). In order to maintain the energy balance, the globally averaged inherent dissipative heating can be determined via a residual calculation. The heating is then added to the temperature field in the thermodynamic equation.”
Performance of the New NCEP Global Ensemble Forecast System in a Parallel Experiment (2017, background): “…physics suite has three components, including 1) stochastically perturbed physics tendencies (SPPTs; Buizza et al. 1999; Palmer 1997, 2001), 2) stochastically perturbed planetary boundary layer humidity (SHUM), and 3) stochastic kinetic energy backscatter (SKEB; Berner et al. 2009; Shutts 2005).”
GSI 3DVar-Based Ensemble-Variational Hybrid Data Assimilation for NCEP Global Forecast System: Single-Resolution Experiments (2013, methodology): “1999) and Stochastic Kinetic energy backscatter schemes 356 (Shutts 2005) to account for model errors.”
A review of operational methods of variational and ensemble‐variational data assimilation (2017, background): “…multiple physical parametrization schemes (Stensrud et al., 2000; Berner et al., 2011), using the stochastic kinetic energy backscatter scheme (Shutts, 2005), perturbing physics tendencies (Buizza et al., 1999; Bouttier et al., 2012; Fresnay et al., 2012), or perturbing physics parameters…”
Impact of Stochastic Physics in a Convection-Permitting Ensemble (2012, background): “Suggested stochastic backscatter algorithms include the stochastic kinetic energy backscatter (SKEB), e.g. (Shutts 2005, Bowler 2009a), stochastic convective vorticity (SCV), e.g. Bowler (2008), and cellular automata, e.g. (Palmer 2001, Shutts 2005, Bengtsson 2011).”
The local ETKF and SKEB: Upgrades to the MOGREPS short‐range ensemble prediction system (2009, background): “As argued by Shutts (2005) (S05 hereafter), numerical advection errors, horizontal diffusion and parametrization schemes (e.g. gravity wave drag, convection) act as energy sinks in global circulation models, making energy dissipation excessive.”
Ensemble flood forecasting: a review. (2009, background): “Some EPS also additionally incorporate parameter uncertainty in the generation of the ensemble forecasts (Buizza et al., 1999; Houtekamer and Lefaivre, 1997; Shutts, 2005).”
Ensemble forecasting (2008, methodology): “A more sophisticated scheme based on the idea of backscattering of kinetic energy dissipated by the model [87] has been shown to be capable of ameliorating some of the more robust systematic errors in climate models associated with mid-latitude blocking [88].”
A Spectral Stochastic Kinetic Energy Backscatter Scheme and Its Impact on Flow-Dependent Predictability in the ECMWF Ensemble Prediction System (2009, methodology): “Here, we follow Shutts (2005) and propose the use of an improved stochastic kinetic energy backscatter scheme to account for model error in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system.”
Ensemble Kalman filtering (2005, background): “One could, for instance, use stochastic physics (Buizza et al. 1999; Shutts 2005) or an ensemble of differently configured forecast models (Houtekamer et al. 1996) to simulate the occurrence of model error with an ensemble of integrations.”
Stochastic parametrization and model uncertainty (2009, methodology): “…and 1 unperturbed analyses were generated by randomly perturbing the observations in each single assimilation cycle at TL399L91 resolution, with a 12-hour 4D-Var with TL159L91 inner loops, and by including a version of the stochastic backscatter scheme (Shutts, 2005; Berner et al., 2009b).”