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Claudia K. Parise, Luciano P. Pezzi, Kevin I. Hodges, and Flavio Justino


The study analyzes the sensitivity and memory of the Southern Hemisphere coupled climate system to increased Antarctic sea ice (ASI), taking into account the persistence of the sea ice maxima in the current climate. The mechanisms involved in restoring the climate balance under two sets of experiments, which differ in regard to their sea ice models, are discussed. The experiments are perturbed with extremes of ASI and integrated for 10 yr in a large 30-member ensemble. The results show that an ASI maximum is able to persist for ~4 yr in the current climate, followed by a negative sea ice phase. The sea ice insulating effect during the positive phase reduces heat fluxes south of 60°S, while at the same time these are intensified at the sea ice edge. The increased air stability over the sea ice field strengthens the polar cell while the baroclinicity increases at midlatitudes. The mean sea level pressure is reduced (increased) over high latitudes (midlatitudes), typical of the southern annular mode (SAM) positive phase. The Southern Ocean (SO) becomes colder and fresher as the sea ice melts mainly through sea ice lateral melting, the consequence of which is an increase in the ocean stability by buoyancy and mixing changes. The climate sensitivity is triggered by the sea ice insulating process and the resulting freshwater pulse (fast response), while the climate equilibrium is restored by the heat stored in the SO subsurface layers (long response). It is concluded that the time needed for the ASI anomaly to be dissipated and/or melted is shortened by the sea ice dynamical processes.

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Joey J. Voermans, Alexander V. Babanin, Cagil Kirezci, Jonas T. Carvalho, Marcelo F. Santini, Bruna F. Pavani, and Luciano P. Pezzi


Quality control measures for ocean waves observations are necessary to give confidence of their accuracy. It is common practice to detect anomalies or outliers in surface displacement observations by applying a standard deviation threshold. Besides being a purely statistical method, this quality control procedure is likely to flag extreme wave events erroneously, thereby impacting higher-order descriptions of the wave field. In this paper we extend the use of the statistical phase-space threshold, an established outlier detection method in the field of turbulence, to detect anomalies in a wave record. We show that a wave record in phase space (here defined as a diagram of displacement against acceleration) can be enclosed by a predictable ellipse where the major and minor axes are defined by the spectral properties of the wave field. By using the parameterized ellipse in phase space as a threshold to identify wave anomalies, this is a semiphysical filtering method. Wave buoy data obtained from a mooring deployed near King George Island, Antarctica [as part of the Antarctic Modeling Observation System (ATMOS)], and laser altimeter data obtained at the Northwest Shelf of Australia were used to demonstrate the functioning of the filtering methodology in identifying wave anomalies. Synthetic data obtained using a high-order spectral model are used to identify how extreme waves are positioned in phase space.

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Iracema F. A. Cavalcanti, José A. Marengo, Prakki Satyamurty, Carlos A. Nobre, Igor Trosnikov, José Paulo Bonatti, Antonio Ocimar Manzi, Tatiana Tarasova, Luciano P. Pezzi, Cassiano D'Almeida, Gilvan Sampaio, Christopher C. Castro, Marcos B. Sanches, and Hélio Camargo


The Center for Weather Forecasting and Climate Studies–Center for Ocean–Land–Atmosphere Studies (CPTEC–COLA) atmospheric general circulation model (AGCM) is integrated with nine initial conditions for 10 yr to obtain the model climate in an ensemble mode. The global climatological characteristics simulated by the model are compared with observational data, and emphasis is given to the Southern Hemisphere and South America. Evaluation of the model's performance is presented by showing systematic errors of several variables, and anomaly correlation and reproducibility are applied to precipitation. The model is able to simulate the main features of the global climate, and the results are consistent with analyses of other AGCMs. The seasonal cycle is reproduced well in all analyzed variables, and systematic errors occur at the same regions in different seasons. The Southern Hemisphere convergence zones are simulated reasonably well, although the model overestimates precipitation in the southern portions and underestimates it in the northern portions of these systems. The high- and low-level main circulation features such as the subtropical highs, subtropical jet streams, and storm tracks are depicted well by the model, albeit with different intensities from the reanalysis. The stationary waves of the Northern and Southern Hemispheres are weaker in the model; however, the dominant wavenumbers are similar to the observations. The energy budget analysis shows values of some radiative fluxes that are close to observations, but the unbalanced fluxes in the atmosphere and at the surface indicate that the radiation and cloud scheme parameterizations need to be improved. Besides these improvements, changes in the convection scheme and higher horizontal resolution to represent orographic effects better are being planned to improve the model's performance.

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