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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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 |
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DataCite Metadata Store (German National Library of Science and Technology) |
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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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1766341861434195968 |