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SIAM J. Sci. Comput., 39(5), A2257–A2286.
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Maksimova, E. V. (2018). A conceptual view on inertial internal waves in relation to the subinertial flow on the central west Florida shelf.
Sci Rep, 8(1), 15952.
Abstract: The study reported here focuses on inertial internal wave currents on the west Florida midshelf in 50 m depth. In situ observations showed that the seasonal shifts in stratification change both the frequency range of inertial internal waves and their modulation time scales. According to the analysis, the subinertial flow evolution time scales also undergo compatible seasonal variations, and the inertial internal wave currents appear to be temporally and spatially related to the subinertial flow. Specifically, the subinertial flow evolving on frontal-/quasi-geostrophic time scales appears to be accompanied by the near-inertial oscillations/inertia-gravity waves in corresponding small/finite Burger number regimes, respectively. The quasi-geostrophic subinertial currents on the west Florida shelf are probably associated with the synoptic wind-forced flow, whereas the frontal-geostrophic currents are related to the evolution of density fronts. Further details of this conceptual view should, however, be elucidated in the future.
Maksimova, E. V. (2017). On the observed synoptic signal in the Mississippi-Alabama slope flow.
J. Geophys. Res. Oceans, 122(1), 185–192.
Maloney, E. D., Gettelman, A., Ming, Y., Neelin, J. D., Barrie, D., Mariotti, A., et al. (2019). Process-Oriented Evaluation of Climate and Weather Forecasting Models.
Bull. Amer. Meteor. Soc., 100(9), 1665–1686.
Abstract: Realistic climate and weather prediction models are necessary to produce confidence in projections of future climate over many decades and predictions for days to seasons. These models must be physically justified and validated for multiple weather and climate processes. A key opportunity to accelerate model improvement is greater incorporation of process-oriented diagnostics (PODs) into standard packages that can be applied during the model development process, allowing the application of diagnostics to be repeatable across multiple model versions and used as a benchmark for model improvement. A POD characterizes a specific physical process or emergent behavior that is related to the ability to simulate an observed phenomenon. This paper describes the outcomes of activities by the Model Diagnostics Task Force (MDTF) under the NOAA Climate Program Office (CPO) Modeling, Analysis, Predictions and Projections (MAPP) program to promote development of PODs and their application to climate and weather prediction models. MDTF and modeling center perspectives on the need for expanded process-oriented diagnosis of models are presented. Multiple PODs developed by the MDTF are summarized, and an open-source software framework developed by the MDTF to aid application of PODs to centers' model development is presented in the context of other relevant community activities. The paper closes by discussing paths forward for the MDTF effort and for community process-oriented diagnosis.
Manghnani, V. (2003). Numerical simulation of seasonal and interannual Indian Ocean upper layer circulation using Miami Isopycnic Coordinate Ocean Model.
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Manghnani, V., Morrison, J. M., Xie, L., & Subrahmanyam, B. (2002). Heat transports in the Indian Ocean estimated from TOPEX/POSEIDON altimetry and model simulations.
Deep Sea Research Part II: Topical Studies in Oceanography, 49(7-8), 1459–1480.
Marengo, J. A., Liebmann, B., Grimm, A. M., Misra, V., Silva Dias, P. L., Cavalcanti, I. F. A., et al. (2012). Recent developments on the South American monsoon system.
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