The KNMI Large Ensemble Time Slice (KNMI-LENTIS)

Large-ensemble modelling has become an increasingly popular approach to studying the mean climate and the climate system's internal variability in response to external forcing. Here we present the Royal Netherlands Meteorological Institute (KNMI) Large Ensemble Time Slice (KNMI-LENTIS): a new l...

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Published in:Geoscientific Model Development
Main Authors: Muntjewerf, Laura, Bintanja, Richard, Reerink, Thomas, Van Der Wiel, Karin
Format: Article in Journal/Newspaper
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/11370/e911cc87-05b3-4dfa-921f-c09c2345f599
https://research.rug.nl/en/publications/e911cc87-05b3-4dfa-921f-c09c2345f599
https://doi.org/10.5194/gmd-16-4581-2023
https://pure.rug.nl/ws/files/790624282/gmd-16-4581-2023.pdf
http://www.scopus.com/inward/record.url?scp=85171130819&partnerID=8YFLogxK
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spelling ftunigroningenpu:oai:pure.rug.nl:publications/e911cc87-05b3-4dfa-921f-c09c2345f599 2024-09-15T17:46:27+00:00 The KNMI Large Ensemble Time Slice (KNMI-LENTIS) Muntjewerf, Laura Bintanja, Richard Reerink, Thomas Van Der Wiel, Karin 2023-08-11 application/pdf https://hdl.handle.net/11370/e911cc87-05b3-4dfa-921f-c09c2345f599 https://research.rug.nl/en/publications/e911cc87-05b3-4dfa-921f-c09c2345f599 https://doi.org/10.5194/gmd-16-4581-2023 https://pure.rug.nl/ws/files/790624282/gmd-16-4581-2023.pdf http://www.scopus.com/inward/record.url?scp=85171130819&partnerID=8YFLogxK eng eng https://research.rug.nl/en/publications/e911cc87-05b3-4dfa-921f-c09c2345f599 info:eu-repo/semantics/openAccess Muntjewerf , L , Bintanja , R , Reerink , T & Van Der Wiel , K 2023 , ' The KNMI Large Ensemble Time Slice (KNMI-LENTIS) ' , Geoscientific Model Development , vol. 16 , no. 15 , pp. 4581-4597 . https://doi.org/10.5194/gmd-16-4581-2023 article 2023 ftunigroningenpu https://doi.org/10.5194/gmd-16-4581-2023 2024-07-01T14:49:22Z Large-ensemble modelling has become an increasingly popular approach to studying the mean climate and the climate system's internal variability in response to external forcing. Here we present the Royal Netherlands Meteorological Institute (KNMI) Large Ensemble Time Slice (KNMI-LENTIS): a new large ensemble produced with the re-tuned version of the global climate model EC-Earth3. The ensemble consists of two distinct time slices of 10 years each: a present-day time slice and a +2ĝ€¯K warmer future time slice relative to the present day. The initial conditions for the ensemble members are generated with a combination of micro- and macro-perturbations. The 10-year length of a single time slice is assumed to be too short to show a significant forced climate change signal, and the ensemble size of 1600 years (160ĝ€¯×ĝ€¯10 years) is assumed to be sufficient to sample the full distribution of climate variability. The time slice approach makes it possible to study extreme events on sub-daily timescales as well as events that span multiple years such as multi-year droughts and preconditioned compound events. KNMI-LENTIS is therefore uniquely suited to study internal variability and extreme events both at a given climate state and resulting from forced changes due to external radiative forcing. A unique feature of this ensemble is the high temporal output frequency of the surface water balance and surface energy balance variables, which are stored in 3-hourly intervals, allowing for detailed studies into extreme events. The large ensemble is particularly geared towards research in the land-atmosphere domain. EC-Earth3 has a considerable warm bias in the Southern Ocean and over Antarctica. Hence, users of KNMI-LENTIS are advised to make in-depth comparisons with observational or reanalysis data, especially if their studies focus on ocean processes, on locations in the Southern Hemisphere, or on teleconnections involving both hemispheres. In this paper, we will give some examples to demonstrate the added value of ... Article in Journal/Newspaper Antarc* Antarctica Southern Ocean University of Groningen research database Geoscientific Model Development 16 15 4581 4597
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description Large-ensemble modelling has become an increasingly popular approach to studying the mean climate and the climate system's internal variability in response to external forcing. Here we present the Royal Netherlands Meteorological Institute (KNMI) Large Ensemble Time Slice (KNMI-LENTIS): a new large ensemble produced with the re-tuned version of the global climate model EC-Earth3. The ensemble consists of two distinct time slices of 10 years each: a present-day time slice and a +2ĝ€¯K warmer future time slice relative to the present day. The initial conditions for the ensemble members are generated with a combination of micro- and macro-perturbations. The 10-year length of a single time slice is assumed to be too short to show a significant forced climate change signal, and the ensemble size of 1600 years (160ĝ€¯×ĝ€¯10 years) is assumed to be sufficient to sample the full distribution of climate variability. The time slice approach makes it possible to study extreme events on sub-daily timescales as well as events that span multiple years such as multi-year droughts and preconditioned compound events. KNMI-LENTIS is therefore uniquely suited to study internal variability and extreme events both at a given climate state and resulting from forced changes due to external radiative forcing. A unique feature of this ensemble is the high temporal output frequency of the surface water balance and surface energy balance variables, which are stored in 3-hourly intervals, allowing for detailed studies into extreme events. The large ensemble is particularly geared towards research in the land-atmosphere domain. EC-Earth3 has a considerable warm bias in the Southern Ocean and over Antarctica. Hence, users of KNMI-LENTIS are advised to make in-depth comparisons with observational or reanalysis data, especially if their studies focus on ocean processes, on locations in the Southern Hemisphere, or on teleconnections involving both hemispheres. In this paper, we will give some examples to demonstrate the added value of ...
format Article in Journal/Newspaper
author Muntjewerf, Laura
Bintanja, Richard
Reerink, Thomas
Van Der Wiel, Karin
spellingShingle Muntjewerf, Laura
Bintanja, Richard
Reerink, Thomas
Van Der Wiel, Karin
The KNMI Large Ensemble Time Slice (KNMI-LENTIS)
author_facet Muntjewerf, Laura
Bintanja, Richard
Reerink, Thomas
Van Der Wiel, Karin
author_sort Muntjewerf, Laura
title The KNMI Large Ensemble Time Slice (KNMI-LENTIS)
title_short The KNMI Large Ensemble Time Slice (KNMI-LENTIS)
title_full The KNMI Large Ensemble Time Slice (KNMI-LENTIS)
title_fullStr The KNMI Large Ensemble Time Slice (KNMI-LENTIS)
title_full_unstemmed The KNMI Large Ensemble Time Slice (KNMI-LENTIS)
title_sort knmi large ensemble time slice (knmi-lentis)
publishDate 2023
url https://hdl.handle.net/11370/e911cc87-05b3-4dfa-921f-c09c2345f599
https://research.rug.nl/en/publications/e911cc87-05b3-4dfa-921f-c09c2345f599
https://doi.org/10.5194/gmd-16-4581-2023
https://pure.rug.nl/ws/files/790624282/gmd-16-4581-2023.pdf
http://www.scopus.com/inward/record.url?scp=85171130819&partnerID=8YFLogxK
genre Antarc*
Antarctica
Southern Ocean
genre_facet Antarc*
Antarctica
Southern Ocean
op_source Muntjewerf , L , Bintanja , R , Reerink , T & Van Der Wiel , K 2023 , ' The KNMI Large Ensemble Time Slice (KNMI-LENTIS) ' , Geoscientific Model Development , vol. 16 , no. 15 , pp. 4581-4597 . https://doi.org/10.5194/gmd-16-4581-2023
op_relation https://research.rug.nl/en/publications/e911cc87-05b3-4dfa-921f-c09c2345f599
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op_doi https://doi.org/10.5194/gmd-16-4581-2023
container_title Geoscientific Model Development
container_volume 16
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