ECMWF YOPP dataset, Scientific Data

Figure 1: Schematic of the YOPP dataset production framework: The initial conditions and ensemble forecasts are generated by ECMWF’s operational forecasting system based on ensembles of data assimilation and models. Atmosphere, land and ocean waves are separate from the ocean and sea-ice circulation...

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Main Authors: Bauer, Peter, Sandu, Irina, Magnusson, Linus, Mladek, Richard, Fuentes, Manuel
Format: Still Image
Language:unknown
Published: figshare 2020
Subjects:
Online Access:https://dx.doi.org/10.6084/m9.figshare.13085153.v1
https://figshare.com/articles/figure/ECMWF_YOPP_dataset_Scientific_Data/13085153/1
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spelling ftdatacite:10.6084/m9.figshare.13085153.v1 2023-05-15T15:10:56+02:00 ECMWF YOPP dataset, Scientific Data Bauer, Peter Sandu, Irina Magnusson, Linus Mladek, Richard Fuentes, Manuel 2020 https://dx.doi.org/10.6084/m9.figshare.13085153.v1 https://figshare.com/articles/figure/ECMWF_YOPP_dataset_Scientific_Data/13085153/1 unknown figshare https://dx.doi.org/10.6084/m9.figshare.13085153 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY Atmospheric Sciences FOS Earth and related environmental sciences Image Figure graphic ImageObject 2020 ftdatacite https://doi.org/10.6084/m9.figshare.13085153.v1 https://doi.org/10.6084/m9.figshare.13085153 2021-11-05T12:55:41Z Figure 1: Schematic of the YOPP dataset production framework: The initial conditions and ensemble forecasts are generated by ECMWF’s operational forecasting system based on ensembles of data assimilation and models. Atmosphere, land and ocean waves are separate from the ocean and sea-ice circulationin the data assimilation system, while the forecasts are fully coupled. Only the unperturbed control experiment output is ingested in the YOPP dataset from day 0 to day 15, and complemented by physical process tendency output from day 0 to day 2. Figure 2: Mean error as a function of lead time for 700hPa temperature forecastsfor 2018 averaged over the Arctic. The ECMWF HRES forecast (red) andthe ENS control forecast used in the YOPP dataset (black). Verification is performed against the operational ECMWF analysis (included as time step 0). Figure 3: Time series of model tendencies for temperature averaged over thefirst 24 forecast hours (top) and 24-hour temperature forecast errors (bottom),averaged between 850 hPa and 500 hPa. The top panel also includes the evolu-tion of the temperature over 24 hours. The bottom panel includes the forecasterror calculated from the 24-hour forecast output (black) and from the sum ofthe tendencies minus the evolution (grey dashed). A 30-day running mean isapplied to the time-series. All data is averaged inside a box between 75N-85N latitude and 110E-170E longitude. Figure 4: 24-hour temperature forecast errors, averaged between 850 hPa and 500 hPa for the period 1 July to 1 October 2018. Darker colours (top rightcolour bar) indicate statistical significance at the 95% level. Still Image Arctic Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Atmospheric Sciences
FOS Earth and related environmental sciences
spellingShingle Atmospheric Sciences
FOS Earth and related environmental sciences
Bauer, Peter
Sandu, Irina
Magnusson, Linus
Mladek, Richard
Fuentes, Manuel
ECMWF YOPP dataset, Scientific Data
topic_facet Atmospheric Sciences
FOS Earth and related environmental sciences
description Figure 1: Schematic of the YOPP dataset production framework: The initial conditions and ensemble forecasts are generated by ECMWF’s operational forecasting system based on ensembles of data assimilation and models. Atmosphere, land and ocean waves are separate from the ocean and sea-ice circulationin the data assimilation system, while the forecasts are fully coupled. Only the unperturbed control experiment output is ingested in the YOPP dataset from day 0 to day 15, and complemented by physical process tendency output from day 0 to day 2. Figure 2: Mean error as a function of lead time for 700hPa temperature forecastsfor 2018 averaged over the Arctic. The ECMWF HRES forecast (red) andthe ENS control forecast used in the YOPP dataset (black). Verification is performed against the operational ECMWF analysis (included as time step 0). Figure 3: Time series of model tendencies for temperature averaged over thefirst 24 forecast hours (top) and 24-hour temperature forecast errors (bottom),averaged between 850 hPa and 500 hPa. The top panel also includes the evolu-tion of the temperature over 24 hours. The bottom panel includes the forecasterror calculated from the 24-hour forecast output (black) and from the sum ofthe tendencies minus the evolution (grey dashed). A 30-day running mean isapplied to the time-series. All data is averaged inside a box between 75N-85N latitude and 110E-170E longitude. Figure 4: 24-hour temperature forecast errors, averaged between 850 hPa and 500 hPa for the period 1 July to 1 October 2018. Darker colours (top rightcolour bar) indicate statistical significance at the 95% level.
format Still Image
author Bauer, Peter
Sandu, Irina
Magnusson, Linus
Mladek, Richard
Fuentes, Manuel
author_facet Bauer, Peter
Sandu, Irina
Magnusson, Linus
Mladek, Richard
Fuentes, Manuel
author_sort Bauer, Peter
title ECMWF YOPP dataset, Scientific Data
title_short ECMWF YOPP dataset, Scientific Data
title_full ECMWF YOPP dataset, Scientific Data
title_fullStr ECMWF YOPP dataset, Scientific Data
title_full_unstemmed ECMWF YOPP dataset, Scientific Data
title_sort ecmwf yopp dataset, scientific data
publisher figshare
publishDate 2020
url https://dx.doi.org/10.6084/m9.figshare.13085153.v1
https://figshare.com/articles/figure/ECMWF_YOPP_dataset_Scientific_Data/13085153/1
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_relation https://dx.doi.org/10.6084/m9.figshare.13085153
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.6084/m9.figshare.13085153.v1
https://doi.org/10.6084/m9.figshare.13085153
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