Earth system model results by the MPI-ESM-LR of the MiKlip Decadal climate prediction experiment improved by ocean ensemble dispersion filtering, links to NetCDF files

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Autores principales: Kadow, Christopher, Illing, Sebastian, Kröner, Igor, Ulbrich, Uwe, Cubasch, Ulrich
Formato: Dataset Open Access
Lenguaje:en
Publicado: PANGAEA 2017
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author Kadow, Christopher
Illing, Sebastian
Kröner, Igor
Ulbrich, Uwe
Cubasch, Ulrich
author_facet Kadow, Christopher
Illing, Sebastian
Kröner, Igor
Ulbrich, Uwe
Cubasch, Ulrich
collection Datos científicos de ciencias marinas y ambientales
contents Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two timescales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state towards the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering towards the ensemble mean.
format Dataset Open Access
id pangaea_https___doi_org_10_1594_PANGAEA_874231
institution PANGAEA
language en
publishDate 2017
publisher PANGAEA
record_format pangaea
spellingShingle Earth system model results by the MPI-ESM-LR of the MiKlip Decadal climate prediction experiment improved by ocean ensemble dispersion filtering, links to NetCDF files
Kadow, Christopher
Illing, Sebastian
Kröner, Igor
Ulbrich, Uwe
Cubasch, Ulrich
File content; File format; File name; File size; Uniform resource locator/link to file
Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two timescales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state towards the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering towards the ensemble mean.
title Earth system model results by the MPI-ESM-LR of the MiKlip Decadal climate prediction experiment improved by ocean ensemble dispersion filtering, links to NetCDF files
topic File content; File format; File name; File size; Uniform resource locator/link to file
url https://doi.org/10.1594/PANGAEA.874231