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New approaches to representing cloud and boundary layer dynamics in climate models

Applicant Schneider Tapio
Number 156109
Funding scheme Project funding
Research institution Geologisches Institut ETH Zürich
Institution of higher education ETH Zurich - ETHZ
Main discipline Climatology. Atmospherical Chemistry, Aeronomy
Start/End 01.11.2014 - 31.10.2017
Approved amount 400'000.00
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All Disciplines (3)

Discipline
Climatology. Atmospherical Chemistry, Aeronomy
Condensed Matter Physics
Meteorology

Keywords (7)

Climate modeling; Convection; Large-eddy simulation; Turbulence closure; Turbulence ; Clouds ; Subgrid-scale parameterization

Lay Summary (German)

Lead
Die grössten Unsicherheiten in Klimaprojektionen stammen daher, dass es unklar ist, wie sich Wolken mit dem Klima verändern. Niedere Wolken modulieren den Strahlungshaushalt der Erde primär indem sie Sonnenlicht reflektieren. Vergrösseren sich niedere Wolkenfelder, dämpft das die globale Erwärmung. Verkleinern sie sich, verstärkt das die globale Erwärmung. Ziel dieses Projektes ist es, die Repräsentation von Wolken in Klimamodellen zu verbessern und so Unsicherheiten in Klimaprojektionen zu reduzieren.
Lay summary

Wolken in Klimamodellen zu repräsentieren ist schwierig, weil die Grössenskalen der Wolkendynamik (zwischen Metern und Kilometern) viel kleiner sind als die Auflösung von Klimamodellen (ungefähr 100 km). Deshalb muss man Wolkendynamiken vereinfacht und empirisch in Klimamodellen darstellen. Grosse Fortschritte dabei sind jetzt möglich: Dank moderner Hochleistungsrechner ist es jetzt einerseits möglich, rechnerisch aufwändigere Wolkendarstellungen in Klimamodellen zu benutzten als die derzeit üblichen. Andrerseits ist es auch möglich, Wolkendynamiken detailgetreu und zuverlässig in begrenzten Regionen (etwa 100 km breit) zu simulieren. Dieses Projekt wird neue und effizientere Methoden entwickeln, Wolken im Detail zu simulieren und wird diese Simulationen nutzen, verbesserte Darstellungen von Wolken für Klimamodelle zu entwickeln. 

 

Direct link to Lay Summary Last update: 26.09.2014

Responsible applicant and co-applicants

Employees

Publications

Publication
Large-eddy simulation of subtropical cloud-topped boundary layers: 2. Cloud response to climate change
Tan Zhihong, Schneider Tapio, Teixeira João, Pressel Kyle G. (2017), Large-eddy simulation of subtropical cloud-topped boundary layers: 2. Cloud response to climate change, in Journal of Advances in Modeling Earth Systems, 9(1), 19-38.
Numerics and subgrid-scale modeling in large eddy simulations of stratocumulus clouds
Pressel Kyle G., Mishra Siddhartha, Schneider Tapio, Kaul Colleen M., Tan Zhihong (2017), Numerics and subgrid-scale modeling in large eddy simulations of stratocumulus clouds, in Journal of Advances in Modeling Earth Systems, 9(2), 1342-1365.
Constraints on Climate Sensitivity from Space-Based Measurements of Low-Cloud Reflection
Brient Florent, Schneider Tapio (2016), Constraints on Climate Sensitivity from Space-Based Measurements of Low-Cloud Reflection, in Journal of Climate, 29(16), 5821-5835.
Cumulant expansions for atmospheric flows
Ait-Chaalal Farid, Schneider Tapio, Meyer Bettina, Marston J. B. (2016), Cumulant expansions for atmospheric flows, in New Journal of Physics, 18, 025019.
Large-eddy simulation of subtropical cloud-topped boundary layers: 1. A forcing framework with closed surface energy balance
Tan Zhihong, Schneider Tapio, Teixeira Joao, Pressel Kyle G. (2016), Large-eddy simulation of subtropical cloud-topped boundary layers: 1. A forcing framework with closed surface energy balance, in Journal of Advances in Modeling Earth Systems, 8(4), 1565-1585.
Narrowing of the ITCZ in a warming climate: Physical mechanisms
Byrne Michael P., Schneider Tapio (2016), Narrowing of the ITCZ in a warming climate: Physical mechanisms, in Geophysical Research Letters, 43(21), 11350-11357.
Relation of the double-ITCZ bias to the atmospheric energy budget in climate models
Adam Ori, Schneider Tapio, Brient Florent, Bischoff Tobias (2016), Relation of the double-ITCZ bias to the atmospheric energy budget in climate models, in Geophysical Research Letters, 43(14), 7670-7677.
Large-eddy simulation in an anelastic framework with closed water and entropy balances
Pressel Kyle G., Kaul Colleen M., Schneider Tapio, Tan Zhihong, Mishra Siddhartha (2015), Large-eddy simulation in an anelastic framework with closed water and entropy balances, in Journal of Advances in Modeling Earth Systems, 7(3), 1425-1456.

Collaboration

Group / person Country
Types of collaboration
Dr. Joao Teixeira, NASA Jet Propulsion Laboratory United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
ETH Zurich, Siddartha Mishra Switzerland (Europe)
- Publication

Scientific events



Self-organised

Title Date Place
Cloud and Boundary Layer Dynamics: The Next Decade 13.06.2016 Zurich, Switzerland

Associated projects

Number Title Start Funding scheme
168356 Cloud and boundary layer closures: the next 10 years 01.05.2016 International Exploratory Workshops

Abstract

The largest contributor to uncertainties in climate change projections are clouds and particularly low clouds. If low cloud cover increases as the climate warms, the increased planetary albedo implies a mitigating feedback on climate changes; if low cloud cover decreases as the climate warms, the reduced albedo implies an amplifying feedback. Existing theories and models do not agree on the sign or magnitude of low cloud cover changes as the climate warms. Representing low clouds in climate models is difficult primarily because the turbulent dynamics governing them have scales of meters, while the resolution of climate models typically is of order hundred kilometers. Thus, cloud-scale turbulent dynamics must be represented parametrically in terms of the resolved large-scale dynamics of climate models. Approaches to do so generally represent second-order turbulent fluxes in terms of first-order quantities, often using second-order equations to estimate closure parameters that arise in the flux closures. For example, when turbulent fluxes are represented as diffusion down mean gradients, diffusivities are often estimated with the help of a (second-order) turbulent kinetic energy equation. But the second-order equations typically are local in space, disregarding non-local spatial correlations that we know to be important, for example, in convective plumes.Now is the time for fundamental progress on the problem of representing cloud-scale turbulent dynamics in climate models, for three reasons. (1) We are in a golden age of Earth observations, with space-based measurements that give us unprecedentedly detailed data. (2) Large-eddy simulations (LES) have become reliable enough to faithfully simulate cloud-scale turbulent dynamics (modulo microphysical processes such as raindrop formation). (3) High-performance computing (HPC) has reached the critical point at which we can conduct statistically steady LES of cloud-scale dynamics in domains the size of a typical climate model grid box. The research we propose will leverage these three advances to develop new and unified representations of turbulence in clouds and boundary layers, with the long-term goal to reduce uncertainties about cloud feedbacks in climate change projections. We are proposing a three-pronged approach: (1) We will develop a new LES code and validate it with observational data. (2) We will then use LES with representations of large-scale dynamics to obtain statistically steady states of clouds and boundary layers. We will vary the climate and region represented systematically, to study physical mechanisms of how clouds are maintained and respond to climate changes. (3) We will develop new and unified closures of the turbulent dynamics of clouds and boundary layers for large-scale climate models, using LES to test them systematically. First, the development of closures will focus on eddy diffusion/mass flux approaches, which hold promise for unified representations of all subgrid-scale turbulence in climate models, from boundary layers to deep convection. Then, we will use more sophisticated approaches in which the closure of turbulent dynamics is achieved at second order and non-local spatial correlations are retained explicitly. This obviates the need, for example, to specify entrainment rates---which are uncertain and contribute to uncertainties about the cloud response to climate changes. Such approaches have the promise to deliver more accurate closures, with reduced needs to specify arbitrary closure parameters, at the expense of increased computational cost, which, however, can be borne with today's HPC platforms.This research will be directed by Professor Tapio Schneider and will involve one PhD student and a postdoctoral fellow with extensive experience in high-performance computational fluid dynamics.
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