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WP6-WP9: Project management

Author

Roberto Buizza

2016, Presentation

File

16315-wp6-wp9-project-management.pdf

WP5: Service developments

Author

Manuel Fuentes

2016, Presentation

File

16314-wp5-service-developments.pdf

WP4: Quantifying and reducing uncertainties

Author

L Haimberger

2016, Presentation

File

16313-wp4-quantifying-and-reducing-uncertainties.pdf

WP3: Earth system observations

Author

S Broennimann

2016, Presentation

File

16312-wp3-earth-system-observations.pdf

WP2: Future coupling methods

Author

M Martin

2016, Presentation

File

16311-wp2-future-coupling-methods.pdf

WP1: Global 20th century reanalysis

Author

Patrick Laloyaux

2016, Presentation

File

16310-wp1-global-20th-century-reanalysis.pdf

Workshop on numerical and computational methods for simulation of all-scale geophysical flows - Welcome

Author

Erland Kallen

2016, Presentation

File

16672-workshop-numerical-and-computational-methods-simulation-all-scale-geophysical-flows-welcome.pdf

Working group 3: What are and how do we measure the pros and cons of existing approaches?

Author

Carolyn Reynolds

Martin Leutbecher

2016, Conference Paper, ECMWF/WWRP Workshop: Model Uncertainty

File

79971-working-group-3-what-are-and-how-do-we-measure-pros-and-cons-existing-approaches.pdf

Working group 2: How can we improve the diagnosis of model error?

Author

Heinli Wernli

2016, Conference Paper, ECMWF/WWRP Workshop: Model Uncertainty

File

79622-working-group-2-how-can-we-improve-diagnosis-model-error.pdf

Working group 1: What are the sources of model error?

Author

Richard Forbes

2016, Conference Paper, ECMWF/WWRP Workshop: Model Uncertainty

File

79621-working-group-1-what-are-sources-model-error.pdf

Wind turning in the boundary layer

Author

Jenny Lindvall

2016, Presentation

File

16644-wind-turning-boundary-layer.pdf

What conditions led to the Draupner freak wave?

Author

Jean-Raymond Bidlot

Luigi Cavaleri

Luciana Bertotti

Francesco Barbariol

Alvise Benetazzo

Peter Janssen

Nils Wedi

2016, Newsletter Feature Article, ECMWF Newsletter

File

18039-what-conditions-led-draupner-freak-wave.pdf

Weather prediction in a world of uncertainties: should we care about model uncertainty?

Author

Roberto Buizza

2016, Conference Paper, ECMWF/WWRP Workshop: Model Uncertainty

File

79559-weather-prediction-world-uncertainties-should-we-care-about-model-uncertainty.pdf

Weather prediction in a world of uncertainties: should we care about model uncertainty?

Author

Roberto Buizza

2016, Presentation

File

16719-weather-prediction-world-uncertainties-should-we-care-about-model-uncertainty.pdf

Water infiltration and redistribution in Land Surface Models

Author

Anna Mueller-Quintino

Emanuel Dutra

Hannah Cloke

A. Verhoef

Gianpaolo Balsamo

Florian Pappenberger

2016, Technical memorandum, ECMWF Technical Memoranda

File

16903-water-infiltration-and-redistribtuion-land-surface-models.pdf

Verification of Relative-Extreme Events

Author

Michael Sharpe

2016, Presentation

File

16420-verification-relative-extreme-events.pdf

Verification of precipitation and drought indices forecasts at subseasonal to seasonal time scales

Author

Christoph Spirig

2016, Presentation

File

uef2016spirig.pdf

Verification of FC Flood Risk Forecasts

Author

Julia Perez

2016, Presentation

File

16446-verification-fc-flood-risk-forecasts.pdf

Verification challenges in developing tropical cyclone response procedures based on ensemble guidance – an oil and gas industry perspective

Author

Grant Elliott

2016, Presentation

File

16432-verification-challenges-developing-tropical-cyclone-response-procedures-based-ensemble.pdf

Using stratospheric wind observations along long-duration balloon flights to validate NWP models

Author

Riwal Plougonven

2016, Presentation

File

16867-using-stratospheric-wind-observations-along-long-duration-balloon-flights-validate-nwp-models.pdf

Using ICON-LES to constrain drag in global simulations

Author

M Köhler

2016, Presentation

File

16603-using-icon-les-constrain-drag-global-simulations.pdf

Using forecast temporal variability to evaluate model behaviour

Author

Carolyn Reynolds

2016, Conference Paper, ECMWF/WWRP Workshop: Model Uncertainty

File

79564-using-forecast-temporal-variability-evaluate-model-behaviour.pdf

Using forecast temporal variability to evaluate model behaviour

Author

Carolyn Reynolds

E. Satterfield

C. Bishop

2016, Presentation

File

17081-using-forecast-temporal-variability-evaluate-model-behaviour.pdf

Using ensemble data assimilation to diagnose model uncertainty

Author

Elias Hólm

Munehiko Yamaguchi

2016, Presentation

File

16732-using-ensemble-data-assimilation-diagnose-model-uncertainty.pdf

Search ECMWF publications

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WP6-WP9: Project management

WP5: Service developments

WP4: Quantifying and reducing uncertainties

WP3: Earth system observations

WP2: Future coupling methods

WP1: Global 20th century reanalysis

Workshop on numerical and computational methods for simulation of all-scale geophysical flows - Welcome

Working group 3: What are and how do we measure the pros and cons of existing approaches?

Working group 2: How can we improve the diagnosis of model error?

Working group 1: What are the sources of model error?

Wind turning in the boundary layer

What conditions led to the Draupner freak wave?

Weather prediction in a world of uncertainties: should we care about model uncertainty?

Weather prediction in a world of uncertainties: should we care about model uncertainty?

Water infiltration and redistribution in Land Surface Models

Verification of Relative-Extreme Events

Verification of precipitation and drought indices forecasts at subseasonal to seasonal time scales

Verification of FC Flood Risk Forecasts

Verification challenges in developing tropical cyclone response procedures based on ensemble guidance – an oil and gas industry perspective

Using stratospheric wind observations along long-duration balloon flights to validate NWP models

Using ICON-LES to constrain drag in global simulations

Using forecast temporal variability to evaluate model behaviour

Using forecast temporal variability to evaluate model behaviour

Using ensemble data assimilation to diagnose model uncertainty

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