Marcio Cataldi

A multi-model approach for long-term runoff modeling using rainfall forecasts

This work presents the development of a rainfall-runoff model for the Iguacu River basin in the south of Brazil. The model was developed to support the operational planning of hydroelectric power plants and is intended to compute natural flow predictions based on meteorological rain forecasts. A recurrent fuzzy system model was employed, with parameters estimated by a genetic algorithm using observed rainfall as input. This work presents the recurrent fuzzy model within a multi-model approach, where the input data are furnished as an envelope, resulting in a prediction envelope that has demonstrated the ability to produce robust results.

Estudo da influência das anomalias da TSM do Atlântico Sul extratropical na região da Confluência Brasil-Malvinas no regime hidrometeorológico de verão do Sul e Sudeste do Brasil

This study analyses the influence of the extratropical South Atlantic sea surface temperature (SST) anomalies in the Southern and Southeastern Brazilian hydrometeorological pattern. The Brazil-Malvinas Confluence (BMC) is one of the most important South Atlantic Ocean features. This region is characterized by a strong thermal front formed by the confluence between the warm waters transported by the Brazil Current (BC) and the cold waters carried by the Malvinas Current (MC). The knowledgement of its dynamics could represent an important advance to understand its connection with locally and remotely generated ocean and atmospheric processes. This investigation is made with computational modeling using a Community Atmosphere Model (CAM 2.01). The spatial and time SST anomalies were numerically generated inside the model code in such a way to reproduce the summer 2005 event. Significant changes were observed in this experiment in the vertical atmospheric circulation pattern. The precipitation over South Brazil region decreased and more favorable conditions to the South Atlantic Convergence Zone (SACZ) formation appeared over the northern part of the Southeastern Brazil region. These model generated patterns were similar to those observed during the summer 2005, especially the precipitation anomalies results.

Climate downscaling over South America for 1971–2000: application in SMAP rainfall-runoff model for Grande River Basin

This paper aims to validate inflow simulations concerning the present-day climate at Água Vermelha Hydroelectric Plant (AVHP—located on the Grande River Basin) based on the Soil Moisture Accounting Procedure (SMAP) hydrological model. In order to provide rainfall data to the SMAP model, the RegCM regional climate model was also used working with boundary conditions from the MIROC model. Initially, present-day climate simulation performed by RegCM model was analyzed. It was found that, in terms of rainfall, the model was able to simulate the main patterns observed over South America. A bias correction technique was also used and it was essential to reduce mistakes related to rainfall simulation. Comparison between rainfall simulations from RegCM and MIROC showed improvements when the dynamical downscaling was performed. Then, SMAP, a rainfall-runoff hydrological model, was used to simulate inflows at Água Vermelha Hydroelectric Plant. After calibration with observed rainfall, SMAP simulations were evaluated in two different periods from the one used in calibration. During calibration, SMAP captures the inflow variability observed at AVHP. During validation periods, the hydrological model obtained better results and statistics with observed rainfall. However, in spite of some discrepancies, the use of simulated rainfall without bias correction captured the interannual flow variability. However, the use of bias removal in the simulated rainfall performed by RegCM brought significant improvements to the simulation of natural inflows performed by SMAP. Not only the curve of simulated inflow became more similar to the observed inflow, but also the statistics improved their values. Improvements were also noticed in the inflow simulation when the rainfall was provided by the regional climate model compared to the global model. In general, results obtained so far prove that there was an added value in rainfall when regional climate model was compared to global climate model and that data from regional models must be bias-corrected so as to improve their results.

Local indices for the South American monsoon system and its impacts on Southeast Brazilian precipitation patterns

The South American monsoon system (SAMS) plays a fundamental role in the precipitation regime of the most populous and economically important regions in Brazil. The South Atlantic Convergence Zone (SACZ) is a main component of the SAMS, characterizing its active phase, and is often associated with intense rainfall events: Strong and persistent episodes cause severe floods and landslides, while weak and sparse episodes are associated with droughts. The variability of the convergence zone caused great natural disasters in Southeast Brazil, associated with extreme precipitation conditions: 3562 landslides killed 947 people in Rio de Janeiro state in 2011, while a shortage of water in São Paulo affected around 20 million people between 2014 and 2015. In the present study, we build SACZ configuration series for the period between January 2000 and June 2014 and use them as indicators for the SAMS to quantify its influence on several atmospheric variables. Based on a principal component analysis, we present indices that identify the configuration of the SACZ in a local scale. The indices reached strong accuracy rates, especially for identifying days of extreme rainfall events associated with the SAMS and may, thus, serve as decision-making tools to help prepare for their impacts. Furthermore, the indices are composed by common variables simulated by numerical weather and climate models, other than precipitation, which is often a not very reliable output. The applied methodology is easily reproducible and different variables may be used to compose indices for different regions—an advantage of this local-scale approach.

Influência dos parâmetros de configuração do modelo CALMET sobre a simulação da circulação atmosférica na região metropolitana do Rio de Janeiro

The aim of this study is to analyze the effects of configuration parameters of the CALMET model on the simulation of atmospheric circulation over the surface at Air basins I and III on the Metropolitan Region of Rio de Janeiro (RMRJ). The study was conducted in a period when the RMRJ was under a high-pressure acting system, which not strongly influenced the local circulation over the region. The joint analysis of all results show that the best configuration for wind field simulations at the RMRJ, with the combined MM5/CALMET modeling is obtained using the value of 10 km for the TERRAD parameter and between 7 and 10 km for the influence radius.

Dynamics-based regression models for the South Atlantic Convergence Zone

The South Atlantic Convergence Zone (SACZ) plays a key role in the South American monsoon system (SAMS) precipitation regime, and accounts for around 25% of the rainfall volume over Southeast Brazil between October and April, on average, with peaks of 56% in March and 41% in January. Due to its often varying position and multi-variable structure, diagnosing or quantifying SACZ episodes may lie on subjective criteria. The present study provides a climatological characterization of different SACZ types, based on their position, and differences in dynamics analysed from 19 SAMS wet periods. A cycle in SACZ configurations is identified during the rainy season: northernmost (southernmost) episodes are more likely to occur during the onset/demise (peak) months of the SAMS. Objective SACZ indices are developed taking the principal components of the dynamics of the SACZ as explanatory variables, not including precipitation. The most sensitive threshold proposed for the identification of mean SACZ type yields simultaneous true positive rate of 86%, false alarm rate of 28%, true negative rate of 72% and false negative rate of 15%, for example. The indices have potential to bring gains in predictability to SACZ-related precipitation in Southeast Brazil, apart from allowing the objective diagnosis of SACZ episodes. The indices are also correlated with the South American precipitation dipole and may be used to identify anomalous SAMS precipitation at longer time scales as well.

Management of non-structural measures in the prevention of flash floods: a case study in the city of Duque de Caxias, state of Rio de Janeiro, Brazil

In the last years, natural hazards related to flash floods have caused serious damage and losses to the population of the state of Rio de Janeiro. This research discusses the importance of implementing a methodology for the prevention of flash floods, by comparing the methods applied since 2013 in the city of Duque de Caxias, in the Baixada Fluminense region of the state of Rio de Janeiro, Brazil, and the major prevention actions suggested by the Flash Flood Early Warning System Reference Guide from the National Oceanic and Atmospheric Administration, questioning civil defense professionals about the importance of each method to vulnerable communities. Even without the occurrence of an extreme event that proves the effectiveness of the method between 2014 and 2016, the population will certainly be better prepared to face the risks of disasters in the city in the future. In addition, the study also underscores an approach of approximation between academic studies and operational activities, which is still very incipient in Brazil.

EVALUATION OF THE ENSEMBLE OF PHYSICAL PARAMETERIZATIONS OF THE MM5 MODEL IN THE EVENT OF INTENSE RAINFALL OCCURRED BETWEEN THE 5TH AND THE 6TH OF APRIL OF 2010 IN THE RIO DE JANEIRO CITY

The city of Rio de Janeiro is often affected by meteorological systems that cause intense rainfalls. These events bring about economic and social disruptions of significant magnitude. This paper analyses the meteorological event occurred between the 05th and 06th of April 2010 in the city of Rio de Janeiro, using numerical modelling by MM5 model (PSU/NCAR Mesoscale Model). From 20h of the 5th until 8h of the 6th there was on average 178 mm of rainfall in the this city, almost twice the expected for April, bringing about floods, landslides, and many deaths. In this study, eight parameterization groups were used, with different configurations of cloud microphysics, cumulus and atmospheric boundary layer. Two simulation rounds were performed, starting at different times and the simulation results were compared with the observed precipitation data, obtained from pluviometric stations from the “Alerta-Rio” system. Thus, it was possible to analyse the effectiveness of the MM5 model for prognosticate extreme rainfall events as some of the model configurations have captured the position and/or intensity of the cores with intense rainfall with a three-hour time gap in some cases. Therefore, this prognostic model had proven that it can be a useful tool to forecast and reduce the consequences of extreme rainfall events in Rio de Janeiro city.

REPRESENTATION OF ATMOSPHERIC PATTERNS RELATED TO THE SOUTH ATLANTIC CONVERGENCE ZONE BY AN ATMOSPHERE-BIOSPHERE COUPLED MODEL

Extreme weather events are becoming more prominent in academic discussions and media articles, such as South Atlantic Convergence Zone (SACZ), which is a major weather system that influences rainfall in Brazil during the summer months. The relevance of the phenomenon makes it an important process to be mapped and understood. This work seeks to understand how the biosphere-atmosphere coupled model CCM3-IBIS represents the climatology of the SACZ occurrence and formation, and its behavior patterns at different atmospheric levels. The control simulation was run for a period of 50 years, and average monthly maps of the following environmental variables were elaborated: Wind, Divergence, Specific Humidity, Omega, Outgoing Longwave Radiation, Cloudiness and Precipitation. The CCM3-IBIS model represented satisfactorily the characteristics of the SACZ, where areas of low level convergence, negative speed Omega in average levels, divergence at high levels, and high values of specific surface moisture appear on phase, i.e., spatially agreeing with each other, confirming the presence of convective clouds associated with low values of outgoing longwave radiation and high precipitation rates, oriented NW-SE from the convective region of the Amazon to southeastern South America, reaching the extratropical Atlantic Ocean.

PERFORMANCE ASSESSMENT OF GENERATION OF SCENARIOS FOR RESERVOIR INFLOWS USING ENSEMBLE RAINFALL FORECASTS

The electric energy planning of the National Interconnected System SIN has a close correlation between present stocks of water in the reservoirs of hydroelectric plants and future inflows. For time periods above one month, inflows scenarios are generated without incorporating any kind of climate information. The inclusion of such information can improve the representation of future hydrological conditions. The objective of this study is to evaluate the gain that can be achieved with the use of precipitation information on generating reservoir inflows scenarios. We generated reservoir inflows scenarios to the Grande River basin using univariate autoregressive modeling – AR, which considers only past inflows, and multivariate modeling – ARx, which also considers precipitation information. Statistical indices were calculated to evaluate the performance of the scenarios generated using the two types of autoregressive models by comparing the predicted inflow with the observed inflow. The results highlighted that both the univariate and multivariate modeling represented well the seasonal behavior of the inflows, however the univariate methodology presented difficulties in capturing the corresponding natural variability. Statistical indices showed the best performance of the ARx model, indicating that the inclusion of the precipitation information proved to be an important addition to generate reservoir inflows scenarios.