Identifying efficient ensemble perturbations for initializing subseasonal-to-seasonal prediction

  title={Identifying efficient ensemble perturbations for initializing subseasonal-to-seasonal prediction},
  author={Jonathan Demaeyer and Stephen G. Penny and St{\'e}phane Vannitsem},
The prediction of the weather at subseasonal-to-seasonal (S2S) timescales is dependent on both initial and boundary conditions. An open question is how to best initialize a relatively small-sized ensemble of numerical model integrations to produce reliable forecasts at these timescales. Reliability in this case means that the statistical properties of the ensemble forecast are consistent with the actual uncertainties about the future state of the geophysical system under investigation. In the… 


The ECMWF Ensemble Prediction System: Methodology and validation
The European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) is described. In addition to an unperturbed (control) forecast, each ensemble comprises 32 10-day
Ensemble forecasting
The extent to which the current ECMWF ensemble prediction system is capable of predicting flow-dependent variations in uncertainty is assessed for the large-scale flow in mid-latitudes.
Climate-mode initialization for decadal climate predictions
The climate-mode initialization method tested by which ocean ORAS4 reanalysis is projected onto dominant modes of variability of the Earth System Model shows improved surface temperature skill, particularly over the tropical Pacific Ocean at seasonal-to-interannual timescales associated with the improved zonal momentum balance.
Ensemble Forecasting at NCEP and the Breeding Method
The breeding method has been used to generate perturbations for ensemble forecasting at the National Centers for Environmental Prediction (formerly known as the National Meteorological Center) since
A Comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction Systems
Abstract The present paper summarizes the methodologies used at the European Centre for Medium-Range Weather Forecasts (ECMWF), the Meteorological Service of Canada (MSC), and the National Centers
Coupled Data Assimilation and Ensemble Initialization with Application to Multiyear ENSO Prediction
It is found that bred vectors specific to tropical Pacific thermocline variability were the most effective choices for ensemble initialization and ENSO forecasting.
Predictability of Weather and Climate: The Liouville equation and atmospheric predictability
Introduction and motivation It is widely recognised that weather forecasts made with dynamical models of the atmosphere are inherently uncertain. Such uncertainty of forecasts produced with numerical
Stochastic parametrization of subgrid‐scale processes in coupled ocean–atmosphere systems: benefits and limitations of response theory
A stochastic subgrid-scale parameterization based on the Ruelle's response theory and proposed inWouters and Lucarini (2012) is tested in the context of a low-order coupled ocean-atmosphere model for
The Modular Arbitrary-Order Ocean-Atmosphere Model: MAOOAM v1.0
This paper describes a reduced-order quasi-geostrophic coupled ocean-atmosphere model that allows for an arbitrary number of atmospheric and oceanic modes to be retained in the spectral
An OSSE-Based Evaluation of Hybrid Variational-Ensemble Data Assimilation for the NCEP GFS. Part II: 4DEnVar and Hybrid Variants
It is found that by going from 3D to 4D, analysis error is reduced for most variables and levels and the inclusion of a time-invariant static covariance when used without a normal mode–based strong constraint is found to have a small, positive impact on the analysis.