Description:
<jats:title>Abstract</jats:title><jats:p>We study the convective boundary layer (CBL) through low-order topological properties of updrafts and downdrafts, that is, based solely on the sign of the vertical velocity. The geometric representation of the CBL as a pair of two-dimensional cubical complexes, one each for updrafts and downdrafts, is exemplarily obtained from two simulations of the CBL, a realistic daily cycle and an idealized quasi-steady CBL growing into linear stratification. Each cubical complex is defined as a set of grid cells that have the same sign of vertical velocity, either positive or negative. Low-order topological invariants, namely the Betti numbers of the cubical complexes, are found to capture key aspects of the boundary-layer organization and evolution over the diurnal cycle. An unsupervised-learning algorithm is trained using the topological invariants in order to classify the spatio–temporal evolution of convection over a whole day. The successful classification of the CBL by using this approach illustrates the potential of such simplified representation of turbulent flow for data reduction and boundary-layer parametrization approaches.
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