Preprints
https://doi.org/10.5194/egusphere-2022-1378
https://doi.org/10.5194/egusphere-2022-1378
02 Feb 2023
 | 02 Feb 2023

The KNMI Large Ensemble Time Slice (KNMI-LENTIS)

Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel

Abstract. Large-ensemble modelling has become an increasingly popular approach to study the mean climate and the climate system’s internal variability in response to external forcing. Here we present the KNMI Large ENsemble TIme Slice (KNMI-LENTIS): a new large ensemble data set produced with the re-turned version of the global climate model EC-Earth3. The ensemble consists of two distinct time slices of 10 year each: a present-day time slice and a +2 K warmer future time slice relative to 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 (160 x 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-annual 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 those 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 data set 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 KNMI-LENTIS for extreme and compound event research and for climate-impact modelling.

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Journal article(s) based on this preprint

11 Aug 2023
The KNMI Large Ensemble Time Slice (KNMI–LENTIS)
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel
Geosci. Model Dev., 16, 4581–4597, https://doi.org/10.5194/gmd-16-4581-2023,https://doi.org/10.5194/gmd-16-4581-2023, 2023
Short summary
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1378', Anonymous Referee #1, 24 Feb 2023
    • AC1: 'Reply on RC1', Laura Muntjewerf, 31 May 2023
  • RC2: 'Comment on egusphere-2022-1378', Dirk Olonscheck, 18 May 2023
    • AC2: 'Reply on RC2', Laura Muntjewerf, 31 May 2023

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1378', Anonymous Referee #1, 24 Feb 2023
    • AC1: 'Reply on RC1', Laura Muntjewerf, 31 May 2023
  • RC2: 'Comment on egusphere-2022-1378', Dirk Olonscheck, 18 May 2023
    • AC2: 'Reply on RC2', Laura Muntjewerf, 31 May 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Laura Muntjewerf on behalf of the Authors (31 May 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (02 Jun 2023) by Riccardo Farneti
RR by Anonymous Referee #2 (07 Jun 2023)
ED: Publish as is (19 Jun 2023) by Riccardo Farneti
AR by Laura Muntjewerf on behalf of the Authors (23 Jun 2023)

Journal article(s) based on this preprint

11 Aug 2023
The KNMI Large Ensemble Time Slice (KNMI–LENTIS)
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel
Geosci. Model Dev., 16, 4581–4597, https://doi.org/10.5194/gmd-16-4581-2023,https://doi.org/10.5194/gmd-16-4581-2023, 2023
Short summary
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel

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Latest update: 03 Sep 2024
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Short summary
The KNMI-LENTIS dataset is a large ensemble of global climate model simulations with model EC-Earth3. It covers two climate by focussing on two time slices: the present-day climate (defined as 2000–2009) and a future +2 K climate (defined as 2075–2084 in the SSP2-4.5 scenario). We have 1600 simulated years for the two climates with (sub)daily output frequency. The sampled climate variability allows for robust and in-depth research into (compound) extreme events such as heat waves and droughts.