scholarly journals What Controls the Water Vapor Isotopic Composition Near the Surface of Tropical Oceans? Results From an Analytical Model Constrained by Large‐Eddy Simulations

2020 ◽  
Vol 12 (8) ◽  
Author(s):  
Camille Risi ◽  
Caroline Muller ◽  
Peter Blossey
Keyword(s):  
Water Vapor ◽  
Isotopic Composition ◽  
Analytical Model ◽  
Large Eddy Simulations ◽  
Tropical Oceans ◽  
Large Eddy

scholarly journals Controls on the water vapor isotopic composition near the surface of tropical oceans and role of boundary layer mixing processes

2019 ◽  
Author(s):  
Camille Risi ◽  
Joseph Galewsky ◽  
Gilles Reverdin ◽  
Florent Brient
Keyword(s):  
Water Vapor ◽  
Isotopic Composition ◽  
General Circulation ◽  
Model Simulation ◽  
Circulation Model ◽  
Sea Surface ◽  
Trade Wind ◽  
Mixing Processes ◽  
Tropical Oceans ◽  
Air Mixing

Abstract. Understanding what controls the water vapor isotopic composition of the sub-cloud layer (SCL) over tropical oceans (δD0) is a first step towards understanding the water vapor isotopic composition everywhere in the troposphere. We propose an analytical model to predict δD0 as a function of sea surface conditions, humidity and temperature profiles, and the altitude from which the free tropospheric air originates (zorig). To do so, we extend previous studies by (1) prescribing the shape of δD0 vertical profiles, and (2) linking δD0 to zorig. The model relies on the hypotheses that δD0 profiles are steeper than mixing lines and no clouds are precipitating. We show that δD0 does not depend on the intensity of entrainment, dampening hope that δD0 measurements could help constrain this long-searched quantity. Based on an isotope-enabled general circulation model simulation, we show that δD0 variations are mainly controlled by mid-tropospheric depletion and rain evaporation in ascending regions, and by sea surface temperature and zorig in subsiding regions. When the air mixing into the SCL is lower in altitude, it is moister, and thus it depletes more efficiently the SCL. In turn, could δD0 measurements help estimate zorig and thus discriminate between different mixing processes? Estimates that are accurate enough to be useful would be difficult to achieve in practice, requiring measuring daily δD profiles, and measuring δD0 with an accuracy of 0.1 ‰ and 0.4 ‰ in trade-wind cumulus and strato-cumulus clouds respectively.

Is the water vapor supersaturation distribution Gaussian?

2021 ◽  
Author(s):  
Subin Thomas ◽  
Prasanth Prabhakaran ◽  
Will Cantrell ◽  
Raymond A. Shaw
Keyword(s):  
Water Vapor ◽  
Large Eddy Simulation ◽  
Gaussian Distribution ◽  
Numerical Study ◽  
Mixing Model ◽  
Large Eddy Simulations ◽  
Mixing Processes ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Vapor Supersaturation

AbstractWater vapor supersaturation in the atmosphere is produced in a variety of ways, including the lifting of a parcel or via isobaric mixing of parcels. However, irrespective of the mechanism of production, the water vapor supersaturation in the atmosphere has typically been modeled as a Gaussian distribution. In the current theoretical and numerical study, the nature of supersaturation produced by mixing processes is explored. The results from large eddy simulation and a Gaussian mixing model reveal the distribution of supersaturations produced by mixing to be negatively skewed. Further, the causes of skewness are explored using large eddy simulations (LES) and the Gaussian mixing model (GMM). The correlation in forcing of temperature and water vapor fields is recognized as playing a key role.

scholarly journals Near-Surface Intensification of Tornado Vortices

2007 ◽  
Vol 64 (7) ◽  
pp. 2176-2194 ◽  
Author(s):  
D. C. Lewellen ◽  
W. S. Lewellen
Keyword(s):  
Analytical Model ◽  
Broad Class ◽  
Surface Flow ◽  
Large Eddy Simulations ◽  
Fine Tuning ◽  
Near Surface ◽  
Corner Flow ◽  
Large Eddy ◽  
End Wall ◽  
Corner Flows

Abstract An idealized analytical model and numerical large-eddy simulations are used to explore fluid-dynamic mechanisms by which tornadoes may be intensified near the surface relative to conditions aloft. The analytical model generalizes a simple model of Barcilon and Fiedler and Rotunno for a steady supercritical end-wall vortex to more general vortex corner flows, angular momentum distributions, and time dependence. The model illustrates the role played by the corner flow swirl ratio in determining corner flow structure and intensification; predicts an intensification of near-surface swirl velocities relative to conditions aloft of Iυ ∼ 2 for supercritical end-wall vortices in agreement with earlier analytical, numerical, and laboratory results; and suggests how larger intensification factors might be achieved in some more general corner flows. Examples of the latter are presented using large-eddy simulations. By tuning the lateral inflow boundary conditions near the surface, quasi-steady vortices exhibiting nested inner and outer corner flows and Iυ ∼ 4 are produced. More significantly, these features can be produced without fine tuning, along with an additional doubling (or more) of the intensification, in a broad class of unsteady evolutions producing a dynamic corner flow collapse. These scenarios, triggered purely by changes in the far-field near-surface flow, provide an attractive mechanism for naturally achieving an intense near-surface vortex from a much larger-scale less-intense swirling flow. It is argued that, applied on different scales, this may sometimes play a role in tornadogenesis and/or tornado variability. This phenomenon of corner flow collapse is considered further in a companion paper.

scholarly journals Controls on the water vapor isotopic composition near the surface of tropical oceans and role of boundary layer mixing processes

2019 ◽  
Vol 19 (19) ◽  
pp. 12235-12260 ◽  
Author(s):  
Camille Risi ◽  
Joseph Galewsky ◽  
Gilles Reverdin ◽  
Florent Brient
Keyword(s):  
Water Vapor ◽  
Isotopic Composition ◽  
General Circulation ◽  
Model Simulation ◽  
Circulation Model ◽  
Horizontal Distribution ◽  
Mixing Processes ◽  
Horizontal Advection ◽  
Tropical Oceans ◽  
Stratocumulus Clouds

Abstract. Understanding what controls the water vapor isotopic composition of the sub-cloud layer (SCL) over tropical oceans (δD0) is a first step towards understanding the water vapor isotopic composition everywhere in the troposphere. We propose an analytical model to predict δD0 motivated by the hypothesis that the altitude from which the free tropospheric air originates (zorig) is an important factor: when the air mixing into the SCL is lower in altitude, it is generally moister, and thus it depletes the SCL more efficiently. We extend previous simple box models of the SCL by prescribing the shape of δD vertical profiles as a function of humidity profiles and by accounting for rain evaporation and horizontal advection effects. The model relies on the assumption that δD profiles are steeper than mixing lines, and that the SCL is at steady state, restricting its applications to timescales longer than daily. In the model, δD0 is expressed as a function of zorig, humidity and temperature profiles, surface conditions, a parameter describing the steepness of the δD vertical gradient, and a few parameters describing rain evaporation and horizontal advection effects. We show that δD0 does not depend on the intensity of entrainment, in contrast to several previous studies that had hoped that δD0 measurements could help estimate this quantity. Based on an isotope-enabled general circulation model simulation, we show that δD0 variations are mainly controlled by mid-tropospheric depletion and rain evaporation in ascending regions and by sea surface temperature and zorig in subsiding regions. In turn, could δD0 measurements help estimate zorig and thus discriminate between different mixing processes? For such isotope-based estimates of zorig to be useful, we would need a precision of a few hundred meters in deep convective regions and smaller than 20 m in stratocumulus regions. To reach this target, we would need daily measurements of δD in the mid-troposphere and accurate measurements of δD0 (accuracy down to 0.1 ‰ in the case of stratocumulus clouds, which is currently difficult to obtain). We would also need information on the horizontal distribution of δD to account for horizontal advection effects, and full δD profiles to quantify the uncertainty associated with the assumed shape for δD profiles. Finally, rain evaporation is an issue in all regimes, even in stratocumulus clouds. Innovative techniques would need to be developed to quantify this effect from observations.

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