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Precursors of deep moist convection in a subkilometer global simulation
Author(s) -
Miyamoto Yoshiaki,
Yamaura Tsuyoshi,
Yoshida Ryuji,
Yashiro Hisashi,
Tomita Hirofumi,
Kajikawa Yoshiyuki
Publication year - 2016
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2016jd024965
Subject(s) - convection , convective available potential energy , convective inhibition , climatology , atmospheric sciences , environmental science , geology , predictability , meteorology , natural convection , combined forced and natural convection , mathematics , geography , statistics
Deep moist convection in the atmosphere plays an important role in cloudy weather disturbances, such as hurricanes, and even in the global climate. The convection often causes disastrous heavy rainfall, and predicting such convection is therefore critical for both disaster prevention and climate projection. Although the key parameters for convection have been pointed out, understanding the preprocesses of convection is a challenging issue. Here we identified the precursors of convection by analyzing a global simulated data set with very high resolution in time and space. We found that the mass convergence near the Earth's surface changed significantly several minutes before the initiation of early convection (the formation of cumulus clouds), which occurred with the increase in the convective available potential energy (CAPE). Decomposition of the statistical data revealed that a higher‐CAPE environment resulted in stronger convection than in the stronger‐convergence case. Furthermore, for the stronger‐convergence case, the precursor was detected earlier than the total average (10–15 min before the initiation), whereas the amplitude of maximum velocity was not so strong as the higher‐CAPE case. This suggests that the strength of convection is connected with CAPE, and the predictability is sensitive to the convergence.