The Added Value of Large-eddy and Storm-resolving Models for Simulating Clouds and Precipitation
Bjorn Stevens
(1)
,
Claudia Acquistapace
(2)
,
Akio Hansen
(3)
,
Rieke Heinze
(4)
,
Carolin Klinger
(5)
,
Daniel Klocke
(6)
,
Harald Rybka
(7)
,
Wiebke Schubotz
(4)
,
Julia Windmiller
(4)
,
Panagiotis Adamidis
(8)
,
Ioanna Arka
(9)
,
Vasileios Barlakas
(10)
,
Joachim Biercamp
(8)
,
Matthias Brueck
(4)
,
Sebastian Brune
(11)
,
Stefan A. Buehler
(3)
,
Ulrike Burkhardt
(9)
,
Guido Cioni
(4)
,
Montserrat Costa-Surós
(2)
,
Susanne Crewell
(2)
,
Traute Crüger
(4)
,
Hartwig Deneke
(12)
,
Petra Friederichs
(11)
,
Cintia Carbajal Henken
(13)
,
Cathy Hohenegger
(4)
,
Marek Jacob
(2)
,
Fabian Jakub
(5)
,
Norbert Kalthoff
(14)
,
Martin Köhler
(7)
,
Thirza W. van Laar
(2)
,
Puxi Li
(15, 16)
,
Ulrich Löhnert
(2)
,
Andreas Macke
(12)
,
Nils Madenach
(13)
,
Bernhard Mayer
(5)
,
Christine Nam
(17)
,
Ann Kristin Naumann
(4)
,
Karsten Peters
(4)
,
Stefan Poll
(11)
,
Johannes Quaas
(18)
,
Niklas Röber
(8)
,
Nicolas Rochetin
(4)
,
Leonhard Scheck
(7)
,
Vera Schemann
(2)
,
Sabrina Schnitt
(19)
,
Axel Seifert
(7)
,
Fabian Senf
(12)
,
Metodija Shapkalijevski
(13)
,
Clemens Simmer
(11)
,
Shweta Singh
(14)
,
Odran Sourdeval
(20, 18)
,
Dela Spickermann
(8)
,
Johan Strandgren
(9)
,
Octave Tessiot
(21)
,
Nikki Vercauteren
(13)
,
Jessica Vial
(4)
,
Aiko Voigt
(14, 22)
,
Günter Zängl
(7)
1
MPI-M -
Max Planck Institute for Meteorology
2 Universität zu Köln = University of Cologne
3 UHH - Universität Hamburg
4 MPI-M - Max-Planck-Institut für Meteorologie
5 LMU - Ludwig-Maximilians University [Munich]
6 Hans Ertel Zentrum für Wetterforschung [Offenbach]
7 DWD - Deutscher Wetterdienst [Offenbach]
8 DKRZ - Deutsches Klimarechenzentrum [Hamburg]
9 DLR - Deutsches Zentrum für Luft- und Raumfahrt
10 TROPOS - Leibniz-Institut für Troposphärenforschung
11 Universität Bonn = University of Bonn
12 TROPOS - Leibniz Institute for Tropospheric Research
13 Freie Universität Berlin
14 KIT - Karlsruher Institut für Technologie
15 CAMS - Chinese Academy of Meteorological Sciences
16 CAS - Chinese Academy of Sciences [Beijing]
17 GERICS - Climate Service Center [Hambourg]
18 Universität Leipzig
19 IEK-8 - Institut für Energie- und Klimaforschung - Troposphäre
20 LOA - Laboratoire d’Optique Atmosphérique - UMR 8518
21 ENS Paris Saclay - Ecole Normale Supérieure Paris-Saclay
22 LDEO - Lamont-Doherty Earth Observatory
2 Universität zu Köln = University of Cologne
3 UHH - Universität Hamburg
4 MPI-M - Max-Planck-Institut für Meteorologie
5 LMU - Ludwig-Maximilians University [Munich]
6 Hans Ertel Zentrum für Wetterforschung [Offenbach]
7 DWD - Deutscher Wetterdienst [Offenbach]
8 DKRZ - Deutsches Klimarechenzentrum [Hamburg]
9 DLR - Deutsches Zentrum für Luft- und Raumfahrt
10 TROPOS - Leibniz-Institut für Troposphärenforschung
11 Universität Bonn = University of Bonn
12 TROPOS - Leibniz Institute for Tropospheric Research
13 Freie Universität Berlin
14 KIT - Karlsruher Institut für Technologie
15 CAMS - Chinese Academy of Meteorological Sciences
16 CAS - Chinese Academy of Sciences [Beijing]
17 GERICS - Climate Service Center [Hambourg]
18 Universität Leipzig
19 IEK-8 - Institut für Energie- und Klimaforschung - Troposphäre
20 LOA - Laboratoire d’Optique Atmosphérique - UMR 8518
21 ENS Paris Saclay - Ecole Normale Supérieure Paris-Saclay
22 LDEO - Lamont-Doherty Earth Observatory
Odran Sourdeval
- Fonction : Auteur
- PersonId : 170775
- IdHAL : odran-sourdeval
- ORCID : 0000-0002-2822-5303
- IdRef : 169251578
Résumé
More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short), the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similarly to past studies we
found an improved representation of precipitation at kilometer scales, as compared to models with parameterized convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simulations in these respects. It does, however, lead to a reduction in the precipitation on the time-scales considered
– most notably over the ocean in the tropics. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hectometer scales. Hectometer scales appear to be more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, and to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when one reduces the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct connection between the circulation and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with already improved simulation as compared to more parameterized models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change.
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