Numerical Simulations of Cold Air Outbreaks Using a Multi-Scale Modeling Framework
Active Dates | 9/1/2020-8/14/2024 |
---|---|
Program Area | Atmospheric System Research |
Project Description
Cold air outbreaks (CAOs) over high-latitude oceans are characterized by a rapid transition of stably
stratified
boundary-layer (BL) flows to a convective BL, due to surface heat
fluxes
driven by the contrast in temperature between the atmosphere and the ocean surface. Structures in the BL are defined by a combination of large wind shear and a deepening BL in which momentum is mixed by moist
convection.
Such conditions result in nearly streamwise helical roll structures that widen as the BL evolves and grows downstream from the ice edge. Convective cells align to form cloud streets in the roll convergence zones. The BL evolution is characterized by continuous changes in the streamwise direction, including a weakening of the vertical wind shear, surface heat fluxes, and convective mixing, and a transition from linear to cellular cloud organization. Accurate numerical simulations of the CAO cloud regime therefore rely on capturing the fetch-dependent surface exchange, dynamic, thermodynamic, and cloud processes in the streamwise direction.
Climate and weather models, with parameterized PBL exchanges, fail to capture fundamental aspects of this cloud regime even when run at high resolution, including wind speed, surface fluxes, the aspect ratio of cloud streets, the transition from linear to cellular convection, and the coupling between the surface and cloud layers. This proposal posits that this failure is due to incorrect interaction between cloud and BL processes in these models. Recent advances in modelling capabilities and recent ARM observations - especially in the 2019-20 COMBLE (Cold-air Outbreaks in the Marine BL Experiment) - allow us to conduct, for the first time, an observationally constrained, large-eddy-resolving, multi-scale simulation study spanning surface-atmosphere interactions, BL turbulence, cloud and radiative processes, and mesoscale dynamics. The overarching goal of this study is to improve fundamental understanding of the CAO cloud regime, such that it can be represented more accurately in climate models. Specifically, we will focus on the multi-scale interactions between dynamics/turbulence and the macro- and micro-physical properties of marine BL clouds, in order to address the following questions:
1. How do multi-scale interactions – ranging from synoptic scale forcing down to BL turbulent, cloud, radiative, and surface processes – drive the organization of mesoscale convective circulations during CAOs over open water?
2. What is the role of mixed-phase cloud processes in the context of mesoscale cellular convection structure and evolution? How do synoptic scale and surface forcings influence this relationship?
Broader impact: The Arctic has been experiencing an amplified response to global warming and rapid warm-season sea ice loss, a trend that is expected to continue. A key question remains how these high-latitude changes connect to those in the mid-latitudes and the global climate system. This combined modeling-observational study of a poorly documented cloud regime will aid the understanding of the high-latitude climate system and its changes, and the prediction of the often inclement weather associated with CAOs. High-latitude CAOs have a significant effect on the Earth’s global energy balance, due to large ocean heat and moisture fluxes, effective transfer across the marine BL, and cloud-radiative effects. This study will support a graduate student and deliver a fine-scale LES model dataset, combined with an observational dataset, of the CAO cloud regime.
Climate and weather models, with parameterized PBL exchanges, fail to capture fundamental aspects of this cloud regime even when run at high resolution, including wind speed, surface fluxes, the aspect ratio of cloud streets, the transition from linear to cellular convection, and the coupling between the surface and cloud layers. This proposal posits that this failure is due to incorrect interaction between cloud and BL processes in these models. Recent advances in modelling capabilities and recent ARM observations - especially in the 2019-20 COMBLE (Cold-air Outbreaks in the Marine BL Experiment) - allow us to conduct, for the first time, an observationally constrained, large-eddy-resolving, multi-scale simulation study spanning surface-atmosphere interactions, BL turbulence, cloud and radiative processes, and mesoscale dynamics. The overarching goal of this study is to improve fundamental understanding of the CAO cloud regime, such that it can be represented more accurately in climate models. Specifically, we will focus on the multi-scale interactions between dynamics/turbulence and the macro- and micro-physical properties of marine BL clouds, in order to address the following questions:
1. How do multi-scale interactions – ranging from synoptic scale forcing down to BL turbulent, cloud, radiative, and surface processes – drive the organization of mesoscale convective circulations during CAOs over open water?
2. What is the role of mixed-phase cloud processes in the context of mesoscale cellular convection structure and evolution? How do synoptic scale and surface forcings influence this relationship?
Broader impact: The Arctic has been experiencing an amplified response to global warming and rapid warm-season sea ice loss, a trend that is expected to continue. A key question remains how these high-latitude changes connect to those in the mid-latitudes and the global climate system. This combined modeling-observational study of a poorly documented cloud regime will aid the understanding of the high-latitude climate system and its changes, and the prediction of the often inclement weather associated with CAOs. High-latitude CAOs have a significant effect on the Earth’s global energy balance, due to large ocean heat and moisture fluxes, effective transfer across the marine BL, and cloud-radiative effects. This study will support a graduate student and deliver a fine-scale LES model dataset, combined with an observational dataset, of the CAO cloud regime.
Award Recipient(s)
- University of Wyoming Laramie (PI: Geerts, Bart)