Classification of Tropics Based on the Spatio-Temporal Dynamics of the Intertropical Convergence Zone from a Complex Networks Perspective

Using complex network analysis, we present a novel classification of the tropics based on the distinct spatio-temporal characteristics of the intertropical convergence zone (ITCZ). The ITCZ is a narrow tropical belt of high convection driven by the differential solar heating and convergence of moisture-laden trade winds from the Northern and Southern hemispheres. The ITCZ is popularly referred to as the ascending branch of the Hadley cell. As the moisture-laden winds convect to higher altitudes, condensation leads to the formation of deep clouds, resulting in high cloudiness and precipitation. In a seasonal cycle, the ITCZ migrates in the meridional direction towards the warming hemisphere. The ITCZ is a critical feature in tropical meteorology since it contributes towards maintaining the Earth-Atmosphere energy balance, and its position and structure are closely linked to the equatorial energy balance. The ITCZ has a significant impact on the society since several monsoon systems are dependent on the precipitation in the ITCZ. However, cloudiness and precipitation exhibit high variability across the ITCZ because they are sensitive to the local geophysical and meteorological phenomena. Furthermore, the extent of migration of the ITCZ and its structure are not uniform across the tropics. Therefore, classifying tropics based on the spatio-temporal dynamics of the ITCZ is a challenging yet necessary task as it will not only further our understanding of the underlying physics but also provide a basis for improving the performance of reduced-order and weather forecast models. The ITCZ dynamics is sensitive to phenomena occurring in decadal temporal scales, which enhances the complexity of the problem at hand. Complex networks are an appropriate and efficient approach to address the problem of classifying such complex systems and analysing their behavior across multiple temporal scales.

We construct functional complex networks where geographical locations are nodes that are connected if the dynamics of ITCZ at these locations are correlated. We use outgoing longwave radiation (OLR), which is a good proxy for cloudiness, to quantify the ITCZ dynamics. We consider the spatio-temporal OLR data from fifth-generation ECMWF atmospheric reanalysis dataset. The spatial resolution of the data is 1^o×1^o, and the temporal resolution is three hours. The correlation is estimated using Pearson’s correlation coefficient, and links are established when the correlation is higher than a predefined threshold and is statistically significant. To classify the tropics we perform community detection on the network, where communities refer to a group of nodes that are densely connected. While connections between nodes of different communities are sparse.

Community detection on the network reveals seven dominant communities corresponding to distinct annual ITCZ dynamics primarily driven by local topography, air-land interactions, and air-sea interactions. We perform community detection using Louvain’s method, which is a modularity-optimizing algorithm. The two largest communities in the network represent regions affected by the ITCZ during the northern and southern hemisphere summer seasons. These communities have dense connections, which is indicative of coherent ITCZ dynamics. The central and eastern equatorial Pacific and equatorial Atlantic oceans emerge as a separate community since these regions are affected by equatorial upwelling that suppresses convection along the equator and pushes the ITCZ northward. The Indian ocean community is found to have relatively sparse connectivity revealing that the ITCZ dynamics is incoherent and inhomogeneous over this region.

Through our analysis, we provide a simple and concise representation of the complex spatio-temporal dynamics of the ITCZ. The community structure and long-range teleconnections resulting from the spatio-temporal dynamics of the ITCZ indicate that it plays a crucial role in stabilizing the climate system. Long-range connections and localized community structure imply that perturbations from local geophysical processes are not localized but rather dispersed swiftly and uniformly across the globe. These characteristics enable suppressing prolonged hazardous weather conditions and ensure stability in the climate system.

We construct the proposed network using thirty years of data from 1991-2021. Therefore, the network is a robust benchmark to study the effects of phenomena occurring in global scales such as El-Niño Southern oscillations and also in decadal time-scales such as anthropogenic climate change. We explore the evolution of the network structure in decadal time scales and observe that connectivity in the network improves with time especially in the past two decades. We observe that certain regions in tropics where connectivity has improved corresponds to those where the ITCZ has strengthened and spatially enlarged because of increase in the surface temperature possibly due to anthropogenic factors.