Gross Moist Stability Analysis: Assessment of Satellite-Based Products in the GMS Plane

Kuniaki Inoue NOAA/GFDL, Princeton, New Jersey

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Larissa E. Back University of Wisconsin–Madison, Madison, Wisconsin

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Abstract

New diagnostic applications of the gross moist stability (GMS) are proposed with demonstrations using satellite-based data. The plane of the divergence of column moist static energy (MSE) against the divergence of column dry static energy (DSE), referred to as the GMS plane here, is utilized. In this plane, one can determine whether the convection is in the amplifying phase or in the decaying phase; if a data point lies below (above) a critical line in the GMS plane, the convection is in the amplifying (decaying) phase. The GMS plane behaves as a phase plane in which each convective life cycle can be viewed as an orbiting fluctuation around the critical line, and this property is robust even on the MJO time scale. This phase-plane behavior indicates that values of the GMS can qualitatively predict the subsequent convective evolution. This study demonstrates that GMS analyses possess two different aspects: time-dependent and quasi-time-independent aspects. Transitions of time-dependent GMS can be visualized in the GMS plane as an orbiting fluctuation around the quasi-time-independent GMS line. The time-dependent GMS must be interpreted differently from the quasi-time-independent one, and the latter is the GMS relevant to moisture-mode theories. The authors listed different calculations of the quasi-time-independent GMS: (i) as a regression slope from a scatterplot and (ii) as a climatological quantity, which is the ratio of climatological MSE divergence to climatological DSE divergence. It is revealed that the latter, climatological GMS, is less appropriate as a diagnostic tool. Geographic variations in the quasi-time-independent GMS are plotted.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Kuniaki Inoue, kuniaki.inoue@noaa.gov

Abstract

New diagnostic applications of the gross moist stability (GMS) are proposed with demonstrations using satellite-based data. The plane of the divergence of column moist static energy (MSE) against the divergence of column dry static energy (DSE), referred to as the GMS plane here, is utilized. In this plane, one can determine whether the convection is in the amplifying phase or in the decaying phase; if a data point lies below (above) a critical line in the GMS plane, the convection is in the amplifying (decaying) phase. The GMS plane behaves as a phase plane in which each convective life cycle can be viewed as an orbiting fluctuation around the critical line, and this property is robust even on the MJO time scale. This phase-plane behavior indicates that values of the GMS can qualitatively predict the subsequent convective evolution. This study demonstrates that GMS analyses possess two different aspects: time-dependent and quasi-time-independent aspects. Transitions of time-dependent GMS can be visualized in the GMS plane as an orbiting fluctuation around the quasi-time-independent GMS line. The time-dependent GMS must be interpreted differently from the quasi-time-independent one, and the latter is the GMS relevant to moisture-mode theories. The authors listed different calculations of the quasi-time-independent GMS: (i) as a regression slope from a scatterplot and (ii) as a climatological quantity, which is the ratio of climatological MSE divergence to climatological DSE divergence. It is revealed that the latter, climatological GMS, is less appropriate as a diagnostic tool. Geographic variations in the quasi-time-independent GMS are plotted.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Kuniaki Inoue, kuniaki.inoue@noaa.gov
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