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G. Delgado, Luiz A. T. Machado, Carlos F. Angelis, Marcus J. Bottino, Á. Redaño, J. Lorente, L. Gimeno, and R. Nieto

Abstract

This paper discusses the basis for a new rainfall estimation method using geostationary infrared and visible data. The precipitation radar on board the Tropical Rainfall Measuring Mission satellite is used to train the algorithm presented (which is the basis of the estimation method) and the further intercomparison. The algorithm uses daily Geostationary Operational Environmental Satellite infrared–visible (IR–VIS) cloud classifications together with radiative and evolution properties of clouds over the life cycle of mesoscale convective systems (MCSs) in different brightness temperature (Tb) ranges. Despite recognition of the importance of the relationship between the life cycle of MCSs and the rainfall rate they produce, this relationship has not previously been quantified precisely. An empirical relationship is found between the characteristics that describe the MCSs’ life cycle and the magnitude of rainfall rate they produce. Numerous earlier studies focus on this subject using cloud-patch or pixel-based techniques; this work combines the two techniques. The algorithm performs reasonably well in the case of convective systems and also for stratiform clouds, although it tends to overestimate rainfall rates. Despite only using satellite information to initialize the algorithm, satisfactory results were obtained relative to the hydroestimator technique, which in addition to the IR information uses extra satellite data such as moisture and orographic corrections. This shows that the use of IR–VIS cloud classification and MCS properties provides a robust basis for creating a future estimation method incorporating humidity Eta field outputs for a moisture correction, digital elevation models combined with low-level moisture advection for an orographic correction, and a nighttime cloud classification.

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Luis Gustavo G. de Goncalves, William J. Shuttleworth, Daniel Vila, Eliane Larroza, Marcus J. Bottino, Dirceu L. Herdies, Jose A. Aravequia, Joao G. Z. De Mattos, David L. Toll, Matthew Rodell, and Paul Houser

Abstract

The definition and derivation of a 5-yr, 0.125°, 3-hourly atmospheric forcing dataset that is appropriate for use in a Land Data Assimilation System operating across South America is described. Because surface observations are limited in this region, many of the variables were taken from the South American Regional Reanalysis; however, remotely sensed data were merged with surface observations to calculate the precipitation and downward shortwave radiation fields. The quality of this dataset was evaluated against the surface observations available. There are regional differences in the biases for all variables in the dataset, with volumetric biases in precipitation of the order 0–1 mm day−1 and RMSE of 5–15 mm day−1, biases in surface solar radiation of the order 10 W m−2 and RMSE of 20 W m−2, positive biases in temperature typically between 0 and 4 K depending on the region, and positive biases in specific humidity around 2–3 g kg−1 in tropical regions and negative biases around 1–2 g kg−1 farther south.

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Simone M. S. Costa, Renato G. Negri, Nelson J. Ferreira, Timothy J. Schmit, Nelson Arai, Wagner Flauber, Juan Ceballos, Daniel Vila, Jurandir Rodrigues, Luiz A. Machado, Sérgio Pereira, Marcus Jorge Bottino, Raffi Agop Sismanoglu, and Pedro Langden

Abstract

This paper summarizes the successful use of Geostationary Operational Environmental Satellite-10 (GOES-10) and -12 (GOES-12), mainly beyond their retirement as operational satellites in the United States, in support of meteorological activities in South America (SA). These satellites were maneuvered by the National Oceanic and Atmospheric Administration (NOAA) to approximately 60°W, enabling other countries in Central and South America to benefit from their ongoing measurements. The extended usefulness of GOES-10 and -12 was only possible as a result of a new image geolocalization system developed by NOAA for correcting image distortions and evaluated in collaboration with the Brazilian National Institute for Space Research. The extension allowed GOES-10 and -12 to monitor SA for an additional 7 years proving the efficiency of this navigation capability implemented for the first time in the GOES series well beyond the expected satellites’ lifetime. Such successful capability is incorporated in the new-generation GOES-R series. This practical and technological experience shows the importance of communication between scientists from the United States and SA for advancing Earth’s monitoring system through the development of novel software and derived products. For SA in particular, GOES-10 and -12 were employed operationally to monitor dry spells, relevant for agriculture and forest fire management and to nowcast severe weather for flash flood warnings. Additionally, GOES-12 detected the first registered tropical hurricane over the Brazilian coast. This paper describes some of the technical and operational challenges faced in extending the GOES-10 and -12 missions to provide coverage over South America and emphasizes the usefulness of their ongoing measurements benefiting Brazilian environmental monitoring.

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Paulo Nobre, Leo S. P. Siqueira, Roberto A. F. de Almeida, Marta Malagutti, Emanuel Giarolla, Guilherme P. Castelão, Marcus J. Bottino, Paulo Kubota, Silvio N. Figueroa, Mabel C. Costa, Manoel Baptista Jr., Luiz Irber Jr., and Gabriel G. Marcondes

Abstract

The response of the global climate system to atmospheric CO2 concentration increase in time is scrutinized employing the Brazilian Earth System Model Ocean–Atmosphere version 2.3 (BESM-OA2.3). Through the achievement of over 2000 yr of coupled model integrations in ensemble mode, it is shown that the model simulates the signal of recent changes of global climate trends, depicting a steady atmospheric and oceanic temperature increase and corresponding marine ice retreat. The model simulations encompass the time period from 1960 to 2105, following the phase 5 of the Coupled Model Intercomparison Project (CMIP5) protocol. Notwithstanding the accurate reproduction of large-scale ocean–atmosphere coupled phenomena, like the ENSO phenomena over the equatorial Pacific and the interhemispheric gradient mode over the tropical Atlantic, the BESM-OA2.3 coupled model shows systematic errors on sea surface temperature and precipitation that resemble those of other global coupled climate models. Yet, the simulations demonstrate the model’s potential to contribute to the international efforts on global climate change research, sparking interest in global climate change research within the Brazilian climate modeling community, constituting a building block of the Brazilian Framework for Global Climate Change Research.

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