Abstract. This paper employs a complex network approach to determine the topology and evolution of the network of extreme precipitation that governs the organization of extreme rainfall before, during, and after the Indian Summer Monsoon (ISM) season. We construct networks of extreme rainfall events during the ISM (June-September), post-monsoon (October-December), and pre-monsoon (March-May) periods from satellite-derived (Tropical Rainfall Measurement Mission, TRMM) and rain-gauge interpolated (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE) data sets. The structure of the networks is determined by the level of synchronization of extreme rainfall events between different grid cells throughout the Indian subcontinent. Through the analysis of various complex-network metrics, we describe typical repetitive patterns in North Pakistan (NP), the Eastern Ghats (EG), and the Tibetan Plateau (TP). These patterns appear during the pre-monsoon season, evolve during the ISM, and disappear during the post-monsoon season. These are important meteorological features that need further attention and that may be useful in ISM timing and strength prediction.

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Ocean-atmosphere coupling modifies the variability of Earth’s climate over a wide range of timescales. However, attribution of the processes that generate this variability remains an outstanding problem. In this manuscript, air-sea coupling is investigated in an eddy-resolving, medium-complexity, idealized, ocean-atmosphere model. The model is run in three configurations: fully coupled, partially coupled (where the effect of the ocean geostrophic velocity on the sea surface temperature field is minimal), and atmosphere-only. A surface boundary layer temperature variance budget analysis computed in the frequency domain is shown to be a powerful tool for studying air-sea interactions, as it differentiates the relative contributions to the variability in the temperature field from each process across a range of timescales (from daily to multidecadal). This method compares terms in the ocean and atmosphere across the different model configurations to infer the underlying mechanisms driving temperature variability. Horizontal advection plays a dominant role in driving temperature variance in both the ocean and atmosphere, particularly at timescales shorter than annual. At longer timescales, the temperature variance is dominated by strong coupling between atmosphere and ocean. Furthermore, the Ekman transport contribution to the ocean’s horizontal advection is found to underlie the low-frequency behavior in the atmosphere. The ocean geostrophic eddy field is an important driver of ocean variability across all frequencies and is reflected in the atmospheric variability in the western boundary current separation region at longer timescales.

The geographical variability, frequency content, and vertical structure of near-surface oceanic kinetic energy (KE) are important for air-sea interaction, marine ecosystems, operational oceanography, pollutant tracking, and interpreting remotely sensed velocity measurements. Here, KE in high-resolution global simulations (HYbrid Coordinate Ocean Model; HYCOM, and Massachusetts Institute of Technology general circulation model; MITgcm), at the sea surface (0 m) and at 15 m, are compared with KE from undrogued and drogued surface drifters, respectively. Global maps and zonal averages are computed for low-frequency (<0.5 cpd), near-inertial, diurnal, and semidiurnal bands. Both models exhibit low-frequency equatorial KE that is low relative to drifter values. HYCOM near-inertial KE is higher than in MITgcm, and closer to drifter values, probably due to more frequently updated atmospheric forcing. HYCOM semidiurnal KE is lower than in MITgcm, and closer to drifter values, likely due to inclusion of a parameterized topographic internal wave drag. A concurrent tidal harmonic analysis in the diurnal band demonstrates that much of the diurnal flow is nontidal. We compute simple proxies of near-surface vertical structure-the ratio 0 m KE/(0 m KE + 15 m KE) in model outputs, and the ratio undrogued KE/(undrogued KE + drogued KE) in drifter observations. Over most latitudes and frequency bands, model ratios track the drifter ratios to within error bars. Values of this ratio demonstrate significant vertical structure in all frequency bands except the semidiurnal band. Latitudinal dependence in the ratio is greatest in diurnal and low-frequency bands. Plain Language SummaryIt is important to map and understand ocean surface currents because they affect climate and marine ecosystems. Recent advances in global ocean models include the addition of astronomical tidal forcing alongside atmospheric forcing and the usage of more powerful computers that can resolve finer features. Here, we evaluate ocean surface currents in high-resolution simulations of two different ocean models through comparison with observations from surface drifting buoys. We examine near-inertial motions, forced by fast-changing winds; semidiurnal tides, forced by the astronomical tidal potential; diurnal motions, arising from tidal and other sources; and low-frequency currents and eddies, forced by atmospheric fields. Global patterns in the models and drifters are broadly consistent. The two models differ in their degree of proximity to drifter measurements in the near-inertial band, most likely due to different update intervals for atmospheric forcing and in the semidiurnal band, most likely due to different damping schemes. A simple proxy for vertical structure of the currents, measured by differences in drifter flows at the surface versus 15 m depth, is tracked reasonably well by the models. Discrepancies between models and observations motivate future improvements in the models.