2018 年 96 巻 6 号 p. 535-548
A new observational measure, the Morphological Index of Convective Aggregation (MICA), is developed to objectively detect the signs of convective self-aggregation on the basis of a simple morphological diagnosis of convective clouds in satellite imagery. The proposed index is applied to infrared imagery from the Meteosat-7 satellite and is assessed with sounding-array measurements in the tropics from Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY2011)/Dynamics of the Madden Julian Oscillation (MJO) (DYNAMO)/Atmospheric Radiation Measurement (ARM) MJO Investigation Experiment (AMIE). The precipitation events during the observational period are first classified by MICA into “aggregation events” and “nonaggregation events”. The large-scale thermodynamics implied from the sounding-array data are then examined, with a focus on the difference between the two classes. The composite time series show that drying proceeds over 6-12 h as precipitation intensifies in the aggregation events. Such drying is unclear in the nonaggregation events. The moisture budget balance is maintained in very different manners between the two adjacent sounding arrays for the aggregation events, in contrast to the nonaggregation events that lack such apparent asymmetry. These results imply the potential utility of the proposed metrics for future studies in search of convective self-aggregation in the real atmosphere.
