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The Brazilian Pantanal is a remarkable ecosystem, encompassing vital aspects such as fish, fruit, and grain production, greenhouse gas emission regulation, temperature and precipitation modulation, and groundwater recharge. However, 2019 and 2020 experienced prolonged and severe drought that profoundly impacted the Pantanal region. Although these impacts are still under review, their effects on wildlife, vegetation, and the local population are undeniable. To enhance our understanding of the magnitude and consequences of the 2019/2020 drought, the present study conducted a comprehensive evaluation of drought occurrences in the Pantanal biome. Utilizing two well-established drought indices, the standard precipitation index (SPI) and the standard precipitation evapotranspiration index (SPEI), we analyzed the available observational data provided by the Climate Research Unit (CRU). Additionally, we endeavored to project droughts throughout the 21st century, thereby facilitating the visualization of potential reoccurrences of hazardous events in the Pantanal area. Two regional climate model (RCM) ensembles, the Eta ensemble (E1) and CORDEX ensemble (E2), along with representative concentration pathways (RCP4.5 and RCP8.5 scenarios) were used to project the severity of droughts in the Brazilian Pantanal until 2098/2099. The findings indicate that the hydrological year of 2019/2020 was the driest on record in the Pantanal over the past 80 years. The E1 ensemble did not project such an extreme event, whereas the E2 ensemble forecasted extreme droughts before the 2040s under the RCP4.5 and RCP8.5 scenarios. Using the SPEI, both ensembles showed similar results, with extreme droughts projected toward the end of the 21st century. Notably, the SPI demonstrated effectiveness in detecting short-term droughts, while the SPEI was more efficient for long-term assessments, projecting extreme drought events for the last two decades. The SPEI, employed with the Eta and CORDEX ensembles, can provide valuable insights into drought projections. Moreover, the potential recurrence of extreme droughts, characterized by significant below-average precipitation spanning vast areas throughout the hydrological year, poses a severe threat to the Pantanal biome in this century.

The Madeira River, a major tributary of the Amazon River, often undergoes severe flood and drought conditions. This study seeks to investigate the climate processes associated with the opposing extreme precipitation events in the Madeira River basin and to relate them to river discharge variability based on a flood awareness dataset. Despite the uncertainty in the observational datasets, the annual precipitation cycle exhibits a rainy season from November to March. A significant result is the high correlation between the rainy season variability in the Madeira River basin and the sea surface temperature (SST) anomalies in the tropical North Atlantic Ocean and the southwestern South Atlantic Ocean. This result indicates that improving the Atlantic SST representation in climate modeling allows for capturing extreme precipitation events in the region. In addition to this impact, certain Madeira River tributaries present significant climate trends. The river discharge variability reveals an increase in hydrological extremes in recent years in the upper sector, but more significantly, in the lower basin, where it has reduced by more than 400 m3/s per decade. These findings highlight the need to improve in situ data and climate and hydrological modeling, with a focus on describing the intense climate variability and trends in river discharges.

The coast of São Paulo, Brazil, is exposed to storm surges that can cause damage and floods. These storm surges are produced by slowly traveling cyclone–anticyclone systems. The motivation behind this work was the need to evaluate high-resolution forecasts of the mean sea-level pressure and 10 m winds, which are the major drivers of the wave model. This work is part of the activity in devising an early warning system for São Paulo coastal storm surges. For the evaluation, four case studies that had a major impact on the coast of São Paulo in 2020 were selected. Because storm surges that reach the coast may cause coastal flooding, precipitation forecasts were also evaluated. The mesoscale Eta model produces forecasts with a 5 km resolution for up to an 84 h lead time. The model was set up in a region that covers part of southeast and south Brazil. The ERA5 reanalysis was used to describe the large-scale synoptic conditions and to evaluate the weather forecasts. The cases showed a region in common between 35° S, 40° S and 35° W, 45° W where the low-pressure center deepened rapidly on the day before the highest waves reached the coast of São Paulo, with a mostly eastward, rather than northeastward, displacement of the associated surface cyclone and minimal or no tilt with height. The winds on the coast were the strongest on the day before the surge reached the coast of São Paulo, and then the winds weakened on the day of the maximum wave height. The pattern of the mean sea-level pressure and 10 m wind in the 36 h, 60 h, and 84 h forecasts agreed with the ERA5 reanalysis, but the pressure was slightly underestimated. In contrast, the winds along the coast were slightly overestimated. The 24 h accumulated precipitation pattern was also captured by the forecast, but was overestimated, especially at high precipitation rates. The 36 h forecasts showed the smallest error, but the growth in the error for longer lead times was small, which made the 84 h forecasts useful for driving wave models and other local applications, such as an early warning system.

Transmission line towers are highly exposed to weather hazards. In southern Brazil, several damages to transmission lines have been reported due to severe weather events. Climate change projections indicate that the frequency and magnitude of extreme events may increase, making planning and adaptation of the transmission system exposure even more critical. In this work, we propose a severe weather index (SWI) as a proxy for detecting severe storms that can potentially result in extreme weather events. The SWI combines thresholds of instability indices based on observed severe events around the transmission tower-line systems. These indices were calculated using the downscaling by the Eta model at 20 km resolution of three global climate model projections and at 5 km of one global climate model for the historical period and the near future. The results show that the SWI captures the severe storms observed in the region. All downscaling projections agree with the increase of extreme weather events in the near future and the expansion of vulnerable areas. The constructed index can be employed to assess the risks and to plan the power transmission system better.

Southern Brazil is a region strongly influenced by the occurrence of extratropical cyclones. Some of them go through a rapid and intense deepening and are known as explosive cyclones. These cyclones are associated with severe weather conditions such as heavy rainfall, strong winds, and lightning, leading to various natural disasters and causing socioeconomic losses. This study investigated the interaction between atmospheric and oceanic conditions that contributed to the rapid intensification of the cyclone that occurred near the coast of South Brazil from 29 June to 3 July 2020, causing significant havoc. Hourly atmospheric and oceanic data from the ERA5 reanalysis were employed in this analysis. The results showed that warm air and moisture transportation were key contributors to these phenomena. In addition, the interaction between the jet stream and the cyclone’s movement played a crucial role in cyclone formation and intensification. Positive sea surface temperature anomalies also fueled the cyclone’s intensification. These anomalies increased the surface heat fluxes, making the atmosphere more unstable and promoting a strong upward motion. Due to the strong winds and the heavy rainfall, the explosive cyclone caused substantial impacts on the power services, resulting in widespread power outages, damaged infrastructure, and interruptions in energy distribution. This work describes in detail the cyclone development and intensification and aims at the understanding of these storms, which is crucial for minimizing their aftermaths, especially on energy distribution.

The objective of this work was to study climate variability and its impacts on the temperature of Sobradinho Lake in Northeast Brazil. Surface weather station data and lake measurements were used in this study. The model applied in this work is FLake, which is a one-dimensional model used to simulate the vertical temperature profile of freshwater lakes. First, the climate variability around Sobradinho Lake was analyzed. Observations showed a reduction in precipitation during 1991–2020 compared to 1981–2010. To study climate variability impacts on Sobradinho Lake, the years 2013, 2015, and 2020 were selected to characterize normal, dry, and rainy years, respectively. In addition, the months of January, April, July, and October were analyzed for rainy months, rainy–dry transitions, dry months, and dry–rainy transitions. Dry years showed higher incoming solar radiation at the surface and, consequently, higher 2 m air temperatures. A characteristic of the normal years was more intense surface winds. October presented the highest incoming solar radiation, the highest air temperature, and the most intense winds at the surface. The lowest incoming solar radiation at the surface was observed in January, and the lightest wind was observed in April. To assess the effects of these atmospheric conditions on the thermodynamics of Sobradinho Lake, the FLake model was forced using station observation data. The thermal amplitude of the lake surface temperature (LST) varied by less than 1 °C during the four months. This result was validated against surface lake observations. FLake was able to accurately reproduce the diurnal cycle variation in sensible heat fluxes (H), latent heat fluxes, and momentum fluxes. The sensible heat flux depends directly on the difference between the LST and the air temperature. During daytime, however, Flake simulated negative values of H, and during nighttime, positive values. The highest values of latent heat flux were simulated during the day, with the maximum value was simulated at 12:00 noon. The momentum flux simulated a similar pattern, with the maximum values simulated during the day and the minimum values during the night. The FLake model also simulated the deepest mixing layer in the months of July and October. However, our results have limitations due to the lack of observed data to validate the simulations.

This study aims to assess the changes in the atmospheric conditions favorable to storm surges over the Santos Coast in Southeast Brazil. Storm surges can favor high sea level rises and coastal erosion, affecting people and strategic structures in coastal areas. The assessment of the atmospheric conditions was based on the downscaling of climate simulations of the Brazilian Earth System Model by the Eta regional climate model at higher spatial resolution. The detection scheme used by the model was able to reproduce the three observed atmospheric patterns favorable to storm surges found by recent studies: Pattern 1 is characterized by a cyclone on the synoptic scale over the ocean; Pattern 2 presents an intense wind fetch from the southeast; Pattern 3 is characterized by winds parallel to the coast. The simulations underestimated the number of cases in Patterns 1 and 2. However, it overestimated the number of days in Pattern 3. The model presented more intense winds in the three patterns. The storm surges characterized by Pattern 1 will become more intense. However, it will be equal to or less frequent. In Pattern 2, the number of events will decrease. Nevertheless, these episodes will be associated with more precipitation along the coastline. Pattern 3 will have a similar number of storm surges.

Paleoclimate simulations are generally performed using coarse global climate models. However, validation of these simulations using a local dataset may be penalized by the coarse grid of the global models. Using a regional climate model, which benefits from the use of higher resolution in a limited area and specific period of time, may help improve the validation of the simulations and help to understand the climate of the past. The objective of this study is to evaluate the Mid-Holocene (MH) simulations for Brazil at 20 km spatial resolution using the regional Eta Model. The simulations are produced by nesting the Eta Model to the National Institute for Space Research (INPE) Global Spectral Atmospheric Model at T062 resolution and 28 vertical levels. Both global and regional models used the same orbital parameters to produce the Milankovic Cycles based on the Berger parameterization. The models adopted the typical carbon dioxide values for the present time and the MH. Downscaling simulations were performed with the Eta Model, resulting in simulations of 2 periods of time, the Eta 0k (present) and the Eta 6k (MH), each 10 years long. The evaluation compares these simulations against proxy data and other paleoclimate model simulations for the region. The difference between the two simulations, 6k and 0k, provides the changes between the two climatic periods. The Eta simulations indicate that the climate during MH was more humid over Northeast Brazil; this agrees partially with paleoclimate data in eastern Northeast Brazil. The Amazon region simulations were mostly drier during MH, in agreement with the paleoclimate data. A weaker convergence of winds in the MH, with winds blowing from the Amazon toward Southeast Brazil, affected the formation and the positioning of the South Atlantic Convergence Zone. Consequently, the associated moisture transport toward the Southeast was smaller; this reduced precipitation in the Brazilian southeastern, central-west, and southern regions, which agrees with the proxy data. The Eta Model simulated a cooler climate for the MH over the Northeast, Central, Southeast, and South Brazil. However, this simulated temperature showed less agreement against proxy data. The Amazon region was slightly warmer, and other transition regions showed no climate change. Overall, the results show that this modified version of the Eta Model is suitable for paleoclimate studies and provides added value over the driver model.

Este artigo examina a capacidade do conjunto de 40 modelos climáticos do Coupled Model Intercomparison Projects Generation 6 - CMIP6, conjunto MOD, para simular a temperatura do ar e a precipitação médias do período de janeiro de 1985 a dezembro de 2014 em cada estado do Brasil. Apesar dos vieses nas simulações, o subconjunto do CMIP6 conseguiu simular satisfatoriamente o ciclo anual e sazonal da temperatura e precipitação, bem como captar a tendência das variáveis analisadas no Brasil. Em relação a temperatura do ar à superfície, o subconjunto do CMIP6 apresentou o melhor desempenho para as Regiões Sul e Sudeste do Brasil, com destaque para os estados do Paraná, Santa Catarina e São Paulo. O melhor desempenho para a precipitação, com o subconjunto do CMIP6 foi verificado sobre a Região Centro-Oeste. Em relação às tendências de aquecimento no período de 30 anos do estudo, 1985-2014, todos estados do Brasil apresentaram tendência de aquecimento, tanto para os dados do subconjunto do CMIP6, quanto para os dados observados. A precipitação na região Norte e Sudeste, não exibiu tendências claras para o período analisado, alguns estados apresentaram aumento e outros redução da precipitação. Nas Regiões Centro-Oeste e Nordeste todos estados apresentam tendência de redução da chuva. Na Região Sul, os três estados mostram tendência de aumento na chuva tanto no observado quanto no simulado. No entanto, além das incertezas inerentes a modelagem climática e vieses detectados, este estudo é relevante para indicar o comportamento dos modelos em simular o clima presente. A avaliação apresentada neste trabalho estabeleceu níveis de confiança no uso deste subconjunto de simulações de modelos para estudos do clima futuro, conforme detalhado no texto.

The goal of this work is to assess the precipitation and temperature trends in climate change projections in the state of Minas Gerais in Brazil, with emphasis on the Doce River basin, using high resolution climate projections suitable for the scale of the basin. Tailored impact assessment of climate change on eucalyptus plantation in terms of thermal and water stress is provided for the basin. We analyzed the downscaling of climate change projections produced by the Eta regional model at 20-km nested to three global models, CanESM2-ES, HadGEM2-ES and MIROC5, and at 5-km resolutions nested to HadGEM2-ES. In historical period, the temperature and precipitation patterns are reproduced by the Eta model. The 5-km Eta simulations provides more spatial detail of the maximum precipitation near the regions of high topography, although in these areas, precipitation is overestimated with respect to the WorldClim data. All projections agree with a warmer climate in the basin until 2070. Precipitation projections indicate a decrease in future periods. The analysis of extreme temperature indices shows an increase in warm days and warm nights and a decrease in cold days and in cold nights until 2070. Future projections indicate trends of reduction in annual rainfall and increase in consecutive dry days. Regarding the eucalyptus, future productivity may be at risk, as most locations will meet more frequently the water stress conditions. Six locations may meet both thermal and water stress conditions and become unsuitable for eucalyptus plantation if only climate factors are considered.

Resumo Simulações climáticas para o clima presente (1960-2005) utilizando o Modelo Climático Regional Eta e o Modelo Hidrológico de Grandes Bacias (MGB), forçado com o Brazilian Earth System Model Ocean-Atmosphere (BESM-AO 2.5) foram realizadas. O objetivo deste trabalho é avaliar o desempenho do Modelo Regional Eta e o Modelo Hidrológico de Grandes Bacias (MGB) na representação dos componentes do balanço de água (precipitação, evapotranspiração, convergência de umidade, vazão, cota e área de inundação) sobre a bacia do rio Madeira. A característica de sumidouro de umidade (P > E) foi simulada pelo modelo regional. Entretanto, o modelo subestimou a precipitação (33%), a evapotranspiração (12%) e a convergência de umidade (6%). O MGB-IPH conseguiu representar o ciclo anual das vazões, níveis do rio (cota) e área de inundação. Também conseguiu reproduzir a translação e amplitude das ondas de cheia, e o atraso de 3 meses entre os máximos da área de inundação e a precipitação sobre a bacia do Madeira. O MGB-IPH mostrou-se uma ferramenta útil para estudos de variabilidade climática, mudanças no clima e no uso da terra, e também para sistemas operacionais de previsão hidrológica na bacia Amazônica.

Abstract The present study gives evidence of the occurrence of foehn-like wind on the eastern slopes of the mountains at Southeastern Brazil. A particular case was detected based on observational evidence on 4 July 2015 near the city of Cruzeiro, state of Sao Paulo, on the Serra da Mantiqueira mountains. Results obtained from numerical simulations are consistent with the foehn wind occurrence deducted from the analysis of regional patterns and time series of selected meteorological parameters.

Resumo Nesse estudo avaliou-se os impactos do aumento dos GEE's (cenário RCP 8.5) e dos desflorestamentos no ciclo da água na bacia do rio Madeira, utilizando o Modelo Regional Eta e o Modelo Hidrológico de Grandes Bacias (MGB), forçado com o Brazilian Earth System Model Ocean-Atmosphere versão 2.5 (BESM-OA 2.5). No cenário RCP 8.5, o modelo apresentou sensibilidade sobre toda a bacia do Madeira, com aumento da ordem de 4.0 °C na temperatura. O aumento foi intensificado com os cenários de desflorestamentos de 2050 (4.8 °C) e 2100 (6.2 °C). Nos cenários de desflorestamento predominou-se o Mecanismo de Retroalimentação Negativo, pois embora haja reduções na precipitação e evapotranspiração, a convergência de umidade aumentou em todos os cenários. Observou-se aumento das descargas na maioria das estações para todos os cenários futuros RCP 8.5 e desflorestamento. O aumento da precipitação na estação seca explicou em parte o aumento das vazões e na área de inundação sobre a bacia do Madeira. O aumento na precipitação à montante da bacia e a mudança nos parâmetros do solo, associada às alterações no uso da terra, contribuíram para o aumento da vazão e área de inundação sobre a bacia do Madeira. As alterações nas descargas e na área de inundação podem ter efeitos negativos, com prejuízos e danos ao meio ambiente, nos recursos hídricos, nos principais setores da economia, afetando de forma direta as comunidades que vivem às margens dos rios, principalmente as populações vulneráveis da bacia do Madeira.

Este trabalho analisa as climatologias da temperatura do ar e da precipitação da Bacia do rio Paraíba do Sul (BRPS), localizada na Região Sudeste do Brasil. A precipitação anual varia entre 1000 mm no norte do estado do Rio de Janeiro e 2000 mm sobre a Serra da Mantiqueira. Aproximadamente 80% da precipitação da bacia concentra-se nos meses de outubro a março, sugerindo um regime monçônico na região. A média anual da temperatura média diária varia entre 16°C no extremo sudoeste e 22°C no extremo norte da BRPS. Essa grande variação se deve a localização da BRPS na região de transição entre latitudes médias e tropicais. O efeito da passagem de frentes frias sobre a temperatura e o efeito da atuação da Zona de Convergência do Atlântico Sul sobre a precipitação podem ser observados na distribuição espacial e temporal das variáveis estudadas

Abstract Ten-year seasonal climate reforecasts over South America are obtained using the Eta Regional Climate Model at 40 km resolution, driven by the large-scale forcing from the global atmospheric model of the Center for Weather Forecasts and Climate Studies. The objective of this work is to evaluate these regional reforecasts. The dataset is comprised of four-month seasonal forecasts performed on a monthly basis between 2001 and 2010. An ensemble of five members is constructed from five slightly different initial conditions to partially reduce the uncertainty in the seasonal forecasts. The seasonal mean precipitation and 2-meter temperature forecasts are compared with the observations. The comparison shows that, in general, forecasted precipitation is underestimated in the central part of the continent in the austral summer, whereas the forecasted 2 meter temperature is underestimated in most parts of the continent and throughout the year. Skill scores show higher skill in the northern part of the continent and lower skill in the southern part of the continent, but mixed skill signs are seen in the central part of the continent. During the El Niño and La Niña seasons, the forecast skill scores clearly increase. The downscaling of the Eta model seasonal forecasts provides added value over the driver global model forecasts, especially during rainy periods.

In this paper, we evaluate temperature and precipitation trends over South America (SA), simulated by the regional Eta model with 20-km horizontal resolution nested to three global models: The Canadian Earth System Model Second Generation (CanESM2-ES), The Met Office Hadley Centre Global Environmental Model - Earth System (HadGEM2-ES) and the Model for Interdisciplinary Research on Climate version 5 (MIROC5). The simulated trends are compared to observed trends (OBS) using six (four) extreme temperature (precipitation) indices recommended by the Expert Team on Climate Change Detection and Indices. In both simulations and OBS, extreme temperature trends over Amazon (AMZ) and Northeast Brazil (NEB) are higher than over South East SA (SESA) and West SA (WSA). Also, trends based on maximum temperatures are, in general, smaller than those based on minimum temperatures. The three downscaling simulations reproduce these features. The temperature simulations of the Eta-CanESM2 (Eta-MIROC5) show the largest (smallest) trends among the three simulations. The Eta-MIROC5, performs better than the other two simulations, reproducing the signals and the magnitudes of the extreme temperature trends, and some cooling trends over SESA, as shown in the observation. Precipitation trends from the three simulations do not compare well with observations, such as temperature trends. However, Eta-MIROC5 presents the best simulations, showing increase in the magnitude of the precipitation extremes over most of SA. The results from the three simulations presented here will be further used for the assessment of climate change projections in the SA region.

In this work, the use of adaptive filters for reducing forecast errors produced by a Regional Climate Model (RCM) is investigated. Seasonal forecasts are compared against the reanalysis data provided by the National Centers for Environmental Prediction. The reanalysis is used to train adaptive filters based on the Recursive Least Squares algorithm in order to reduce the forecast error. The K-means unsupervised learning algorithm is used to obtain the number of filters to employ from the climate variables. The proposed approach is applied to some climate variables such as the meridional wind, zonal wind, and the geopotential height. The forecast is produced by the Eta RCM at 40-km resolution in a domain covering most of Brazil. Results show that the proposed approach is capable of reducing the forecast errors, according to evaluation metrics such as normalized mean square error, maximum absolute error, and maximum normalized absolute error, thus improving the seasonal climate forecasts.

ABSTRACT: Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was forced with initial and boundary conditions provided by CFSR and the Eta regional climate model driven by the historical simulation of HadGEM2-ES. These simulations were validated using the Santarém tower data. In the second part, we assess the impact of a future climate change on the Amazon biome by applying the Inland model forced with regional climate change projections. The projections show that some areas of rainforest in the Amazon region are replaced by deciduous forest type and grassland in RCP4.5 scenario and only by grassland in RCP8.5 scenario at the end of this century. The model indicates a reduction of approximately 9% in the area of tropical forest in RCP4.5 scenario and a further reduction in the RCP8.5 scenario of about 50% in the eastern region of Amazon. Although the increase of CO2 atmospheric concentration may favour the growth of trees, the projections of Eta-HadGEM2-ES show increase of temperature and reduction of rainfall in the Amazon region, which caused the forest degradation in these simulations.

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961-1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021-2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021-2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario.

A previsão de níveis de rios é um elemento importante de um sistema de alertas de desastres associados com eventos hidrológicos extremos. Neste trabalho é apresentado o uso de previsões de tempo de curto e médio prazo e de previsões climáticas sazonais por conjunto para monitoramento de cheias extremas em grandes bacias hidrográï¬cas. Os resultados do estudo de caso da cheia no Rio Madeira em Porto Velho no ano hidrológico 2013-2104, que teve seu pico em 30 de março de 2014, apresentam um bom desempenho do acoplamento entre o modelo atmosférico Eta-INPE e o modelo hidrológico MHD-INPE para as previsões de vazões. As análises sugerem que as previsões sazonais podem ser utilizadas para indicar a potencial ocorrência de um evento acima dos limiares de alerta e de emergência, enquanto que as previsões de tempo auxiliam na estimativa dos valores extremos uma vez estabelecida a onda de cheia. Este tipo de utilização conjunta de previsões em diferentes escalas permite focalizar com maior antecedência as regiões de impacto potencial.

Visando a previsão hidrológica de eventos extremos, serão apresentados neste trabalho resultados obtidos com a aplicação do modelo hidrológico distribuído MHD-INPE para eventos extremos ocorridos em São Luís do Paraitinga, SP. As previsões meteorológicas foram obtidas através do modelo atmosférico Eta-INPE, considerando altas resoluções espaciais (1 e 5 km). Os resultados indicam que a maior resolução das previsões meteorológicas resultam em precipitações mais intensas. Consequentemente, o modelo hidrológico tende a prever maiores níveis para o rio. Esse comportamento aumenta a assertividade de eventos acima do limiar de alerta, sendo assim, adequado para a previsão de eventos extremos, visto que tais eventos normalmente são consequentes de chuvas intensas e localizadas.

La "Serra do Mar" es una estrecha cadena montañosa costera, localizada en el sudeste de Brasil, que abriga importantes ciudades, puertos, industrias y vías de comunicación. Esta región resulta muy vulnerable a las avalanchas de lodo y piedras, debido a sus inclinadas laderas y a las frecuentes e intensas lluvias. En el presente trabajo se estudia un caso de ocurrencia de avalanchas durante el período de invierno, es decir durante la estación seca, que sorprendió a las autoridades de la Defensa Civil y provocó la muerte de varias personas. El objetivo de la investigación es indagar las causas que condujeron a las avalanchas, con el fin de apoyar la tarea de los pronosticadores y los organismos tomadores de decisiones. Las lluvias fueron de tipo estratiforme y estuvieron asociadas a la presencia de un frente frío relativamente intenso que permaneció en la región alrededor de 6 días. Ese sistema se tornó estacionario en la costa del Estado de San Pablo, mientras que el anticiclón post–frontal, inicialmente frío, fue adquiriendo paulatinamente características barotrópicas. Esa situación originó vientos persistentes del sur y sudeste en superficie, que eran ascendidos por la Serra do Mar. El pasaje de una vaguada de onda relativamente corta en los niveles altos de la atmósfera, si bien no fue la causa principal de las lluvias, contribuyó a incrementar la inestabilidad termodinámica y, por lo tanto, a aumentar la intensidad de las lluvias creando condiciones favorables para la ocurrencia de avalanchas. doi: https://doi.org/10.22201/igeof.00167169p.2011.50.1.121

Este trabalho tem por objetivo avaliar a precipitação pluvial e as temperaturas máximas e mínimas previstas pelo Modelo Eta para até 120 dias de previsão em 24 localidades distribuídas na região Centro-Sul do Brasil. A avaliação se baseia na comparação de séries históricas de chuva e temperaturas de 1997 a 2002, com as previsões de 30, 60 e 120 dias de antecedência do Modelo Eta para as 24 localidades. Foram utilizados valores de média, mediana e desvio padrão nesta avaliação. Os resultados indicam que estas previsões geralmente subestimam as chuvas e a amplitude térmica nestas localidades. Os menores erros de precipitação pluvial se localizam mais destacadamente em Itumbiara e Rio Verde, enquanto que os maiores, em Porangatu e Manduri. Por outro lado, os menores erros de temperatura máxima se localizam destacadamente em Brasília, Manduri e Piracicaba, enquanto que os maiores ocorrem em Barreiras e Porangatu. Apesar de o modelo apresentar erros sistemáticos nas previsões de temperaturas, estes erros podem ser removidos para que os valores corrigidos possam ser introduzidos nos modelos de culturas.The objective of this study was to evaluate the 120-day precipitation and maximum and minimum temperature forecasts by Eta Model over 24 locations around the Mid-Southern of Brazil. The evaluation was based on comparing observed time series of precipitation and temperatures from 1997 to 2002 to 30, 60 and 120-day forecasts of Eta Model over these 24 locations. Mean, median and standard deviation were used in the evaluation. The results show that these forecasts generally underestimate rain and temperature range. The smallest precipitation errors occurred in Itumbiara and Rio Verde, whereas the largest errors occurred in Porangatu and Manduri. The smallest maximum temperature errors occurred in Brasília, Manduri and Piracicaba whereas the largest errors in Barreiras and Porangatu. Despite the systematic errors exhibited by the precipitation and temperature forecasts, these errors can be removed and the corrected values input into the crop models.

Previsões de temperatura do Modelo Eta de 40 km de resolução são refinadas para produzir previsões em pontos localizados em sete cidades da região Nordeste: Salvador, Maceió, Recife, Natal, Fortaleza, São Luís e Teresina. O esquema de refinamento empregado é o Model Output Calibration (MOC) que se baseia em regressão linear do erro da previsão com as variáveis previstas pelo modelo. O esquema apresenta a vantagem de empregar período curto de treinamento, neste caso foi usado o período de somente 28 dias. A seleção dos preditores se baseou em correlação maior que 0,6. Os testes foram realizados com dados horários de temperatura do mês de setembro de 2003. Os erros sistemáticos das previs��es foram substancialmente reduzidos para valores menores que 0,5 °C em média. Os erros quadráticos que eram da ordem de 2 °C passaram para valores em torno de 1 °C em média. As correlações entre as séries refinadas e as séries observadas foram geralmente mantidas altas e semelhantes às correlações entre as séries previstas pelo Modelo Eta e as séries observadas, indicando que a aplicação do esquema não prejudicou as tendências horárias da temperatura nas estações. As temperaturas de cidades onde as amplitudes dos ciclos diurnos não foram bem previstas pelo Eta, foram refinadas pelo esquema.Statistical downscaling of 2 m air temperature forecasts from the Eta Model at 40 km resolution were carried out for 7 sites located in Northeast Brazil. The downscaling method was the Model Output Calibration (MOC), which is based on the linear regression between the forecast error and model output variables. One feature of the scheme is the use of short training period, in this work only 28 days was the chosen period. The model output variables with correlation higher than 0.6 were selected as predictors of the regression equation. The scheme was tested for one-month hourly forecasts in September 2003. Model systematic errors were strongly reduced to values below |0.5| °C on average. The root mean square errors, which initially were of the order of 2 °C, were reduced to about 1 °C. The linear correlation between the observations and Eta forecasts were generally kept the same after applying the downscaling scheme. Temperature forecasts with greatest errors in the amplitude of the diurnal cycle were corrected accordingly.

Modelos numéricos têm importante papel na previsão de tempo e clima, amparando assim as tomadas de decisões em diversos setores. O aprimoramento destes modelos pode ser feito a partir de parametrizações de processos de superfície, como o balanço de umidade do solo. Esse balanço é obtido a partir de parâmetros hidrológicos definidos para cada tipo de solo, e pela umidade inicial inserida no modelo. O objetivo desse trabalho é estudar a influência das condições iniciais do solo e do tipo de solo na previsão sazonal do modelo Eta. São realizados dois experimentos (ETA1 e ETA2) a partir de integrações do modelo Eta, com 4 meses e meio de integração e utilizando reanálises como condições inicial e de contorno. O período analisado são as estações secas e chuvosas no Brasil, entre 1979 e 2012. ETA1 foi realizado como uma simulação controle, com umidade inicial do solo climatológica e nove tipos de solo. Em ETA2, utilizou-se umidade inicial do solo calculada e 26 tipos de solo. Para analisar a climatologia simulada, dados de reanálises permitiram a avaliação dos erros de algumas variáveis do modelo. A partir da análise dos experimentos, conclui-se que o modelo Eta manifesta sensibilidade a alterações no solo quando diferentes condições de solo são utilizadas na integração do modelo. ETA2 simula temperaturas sistematicamente mais baixas e precipitação mais acurada em algumas regiões do Brasil.

En este artículo se compara el desempeño de dos versiones del modelo regional Eta utilizado en el CPTEC. La segunda variante, que es una actualización de la empleada en forma operativa hasta el momento, presenta un dominio de integración mayor, un tope más elevado e incluye una representación del suelo y la vegetación. El modelo de suelo/vegetación posee dos capas subterráneas y una canopia vegetal. La evaluación del modelo se llevó a cabo comparando los errores medios y cuadráticos medios de diversas variables sobre un conjunto de 15 situaciones meteorológicas. Esta comparación se realizó utilizando los análisis del NCEP y datos aerológicos y pluviométricos de algunas estaciones de América del Sur. Los pronósticos de precipita- ción fueron evaluados por medio del bias (BIAS) y el equitable threat score (ETS). Los errores medios no difieren notablemente para ambas variantes del modelo durante las primeras 24 horas de previsión, excepto por la temperatura de superficie que es pronosticada con mayor acierto por la versión actualizada. Sin embargo las diferencias se hacen mucho más notables para los pronósticos mayores de 48 horas, donde la nueva versión logra un grado de verificación mucho mayor para la temperatura y la humedad. Estas diferencias se amplían sobre las grandes áreas forestadas de la América del Sur subtropical. Los contrastes son menores para la altura geopotencial y prácticamente nulos para las componentes zonal y meridional del viento. Los pronósticos de precipitación mostraron que durante las primeras 24 horas la nueva versión del modelo produce ETS ligeramente más elevados y BIAS similares, pero que luego de 48 horas éste tiende a sobrestimar en mayor medida la precipitación, sin alterar su verificación espacial. doi: https://doi.org/10.22201/igeof.00167169p.2001.40.3.324

A comparison of performance of two versions of the Eta/CPTEC model is presented. The new version is an update of an earlier operational one and includes representation of soil and vegetation types. The soil/vegetation model contains two underground layers and a canopy layer. Evaluation was carried out by comparing the mean and root mean square errors of several variables for an ensemble of 15 meteorological situations, using the NCEP analyses, upper air soundings and precipitation data over South America. Precipitation forecasts were evaluated by the equitable threat score (ETS) and the bias score (BIAS).The mean errors from both versions show similarities during the first 24 hours of forecast, but surface temperature is more accurately predicted by the updated model. After 48 hours, temperature and humidity forecasts show better skill in the new version too. Over subtropical South America differences are more evident in temperature and humidity, less so for geopotential heights and practically nonexistent for horizontal winds. The precipitation forecasts for the updated version have equitable threat scores slightly higher and similar bias scores during the first 24 hours. After 48 hours this version tends to overestimate the rainfall, while its spatial distribution remains unaffected.

Comparações entre as previsões do modelo Eta-5km e observações nas Plataformas de Coleta de Dados meteorológicas em Cunha, Curucutu, Itanhaém, Paraibuna, Picinguaba, Santa Virgínia e São José dos Campos, localizadas na região da Serra do Mar (SP), são realizadas para o ano de 2008. A temperatura a 2 m, pressão atmosférica ao nível da estação, ventos a 10 m e precipitação são avaliados para as previsões de 24, 48 e 72 horas. Os resultados mostraram que a pressão atmosférica ao nível da estação foi subestimada (superestimada) em Paraibuna e Picinguaba (Cunha e Curucutu), devido a diferenças entre a altitude do modelo e a altitude real da estação, porém os ciclos diurnos foram bem previstos, apresentando dois máximos (0 e 12 Z) e dois mínimos (6 e 18 Z), como observados. Para a pressão atmosférica a performance do modelo é superior na previsão de 48-h. O ciclo diurno da temperatura do ar foi muito bem previsto em todas as localidades. Os valores de correlação temporal entre as previsões e observações foram bem elevados, oscilando entre 73 e 91%. Para algumas localidades verificou-se que ocorre superestimativa da temperatura do ar (cerca de 3ºC em Curucutu e Santa Virgínia e 2ºC em Itanhaém), e que tal erro é sistemático. A previsão de temperatura do ar com 24-h de antecedência foi superior às demais. De forma geral o modelo apresentou uma tendência de subestimar (superestimar) a freqüência de ocorrência de ventos calmos cuja velocidade é inferior a 1 m.s-1 (fortes – superior a 7 m.s-1). A direção dos ventos é a variável mais difícil de prever devido provavelmente às diferenças entre a topografia do modelo e a topografia real, contudo nota-se que o modelo produz o giro característico na direção ao longo do dia, provocado pelo aquecimento diurno. Os totais pluviométricos mensais são bem previstos para a maior parte das localidades, contudo em Itanhaém, Paraibuna e principalmente em Picinguaba os totais mensais foram superestimados. Da análise da precipitação diária conclui-se que em geral o modelo superestima a frequência de ocorrência de eventos de chuva (valores diários maiores ou iguais a 0,3 mm). Por outro lado, o modelo apresenta a melhor performance também para prever tais eventos, com maiores valores de ETS, BIAS e índice de acerto (cerca de 90%). As análises mostram que uma das fontes de erro do modelo está relacionada à sua topografia.

ABSTRACT Climate change impacts need to be considered in water resource planning. This work aims to study of the impacts climate change on Lavrinha headwater watershed, located in the Mantiqueira Range, southeastern Brazil. The impacts from climate change (RCP 8.5 scenario) in the Lavrinha watershed runoff were analyzed based on the "Distributed Hydrology Soil Vegetation Model" (DHSVM), forced with the climate simulated for this future climate change scenario. These simulations, in turn, were generated by the Eta regional climate model coupled to Global Climate Model (GCM) HadGEM2-ES for the 2011-2040, 2041-2070 and 2071-2099 periods. The results of this study showed that the runoff is very sensitive to rising temperatures and reduced precipitation, both projected for the RCP 8.5 scenario. The hydrological simulation projected a reduction in the monthly streamflow between 20 and 77% over the twenty-first century (2011-2099), corresponding to drastic reductions in the runoff behavior and consequently in the water production capacity of the region.

Resumo O modelo regional ETA do Instituto Nacional de Pesquisas Espaciais (INPE) foi utilizado para avaliar o papel das mudanças nos usos e cobertura da terra na reciclagem de precipitação na bacia amazônica através de cenários de desflorestamento referente ao estado atual e projeções futuras. A reciclagem de precipitação aumentou de sudeste para norte-noroeste sobre a bacia, com valores variando entre 20% a 40%, estando diretamente relacionado à intensificação no transporte de umidade no sentido leste-oeste. As mudanças significativas na reciclagem ocorreram nos cenários de 2050 e 2100, enquanto que, para a situação atual, as mudanças não foram intensas suficientes para afetar o regime de precipitação na bacia. As reduções na reciclagem de precipitação (9% e 30% para os cenários de 2050 e 2100, respectivamente) foram explicadas pela redução na evapotranspiração e aumento no transporte de umidade; entretanto, a redução na evapotranspiração teve papel preponderante. A redução na precipitação total foi determinada pela redução da precipitação advectada (68%) e local (32%). Se as atividades antropogênicas não permitirem que haja a regeneração ambiental, o equilíbrio clima-vegetação será afetado, conduzindo a uma condição mais quente e seca, que por sua vez, implicará em graves consequências para os ecossistemas da Amazônia.

Resumo O objetivo deste estudo é avaliar o desempenho das simulações por conjunto do modelo Eta-5km do Instituto Nacional de Pesquisas Espaciais para um caso de chuva intensa ocorrido na Bacia do Rio Paraíba do Sul em janeiro de 2000, durante um evento de Zona de Convergência do Atlântico Sul. O conjunto de simulações é formado por 5 membros, denominados de acordo com suas parametrizações convectiva (Betts-Miller-Janjic - BMJ ou Kain-Fritsch - KF) e de microfísica (Ferrier ou Zhao): CNTRL (BMJ/Ferrier); KF (KF/Ferrier); KFMX (KF com fluxo de momentum/Ferrier); KFMXP (KF com fluxo de momentum e força do gradiente da perturbação da pressão/Ferrier) e ZHAO (BMJ/Zhao). As simulações são realizadas com horizontes de 24 até 120 h e condições de contorno inicial e lateral provenientes do “Climate Forecast System Reanalysis”. Os resultados indicam que todos os membros são capazes de posicionar a banda de chuva aproximadamente na mesma localização observada. O modelo, apesar de subestimar os valores das maiores pluviometrias diárias, simula uma frequência maior de eventos de chuva forte. Em geral, a média do conjunto apresenta melhor performance do que cada um dos membros isoladamente e as simulações com 48 h de antecedência são superiores às demais.

ABSTRACT Hydrological Ensemble Prediction Systems (HEPS) play an important role on operational flood forecasting. Unlike in deterministic approach, which relies on a single prediction of future river flows, these systems can represent the forecast uncertainty and provide a better detection of extreme hydro-meteorological events. In this context, the present study aimed to assess both the quality of ensemble flood forecasts on Taquari-Antas basin and its potential to provide additional information to a local Flood Alert System. The hydrological model MGB-IPH was coupled to the high-resolution meteorological EPS Eta model with five members of different parameterization schemes and boundary conditions, as well as to the deterministic version of Eta regional model. On a single event evaluation, the peak discharge was reasonable well predicted by at least one ensemble member, in nearly all forecasts, with a good prediction of the flood timing for the considered lead times. In a comparison with deterministic forecasts, the ensemble ones showed higher accuracy and higher probability of detection (POD) for the reference thresholds, preserving false alarm rates at reasonably low levels. An overall tendency of underestimation was also identified, with most observations falling between the higher ranks of the ensemble. Furthermore, the combination of previous forecasts (t-12h) with the recent ones leads to a slight increase of ensemble spread and POD, despite the performance reduction in terms of accuracy and bias for the ensemble mean. Results suggest that there is a benefit in having hydrological ensemble forecasts obtained from the high resolution EPS Eta model, which can be used as a complementary information to a local Flood Alert System supporting pre-alert issues and Civil Defense internal planning actions.

The Brazilian Pantanal is a remarkable ecosystem, encompassing vital aspects such as fish, fruit, and grain production, greenhouse gas emission regulation, temperature and precipitation modulation, and groundwater recharge. However, 2019 and 2020 experienced prolonged and severe drought that profoundly impacted the Pantanal region. Although these impacts are still under review, their effects on wildlife, vegetation, and the local population are undeniable. To enhance our understanding of the magnitude and consequences of the 2019/2020 drought, the present study conducted a comprehensive evaluation of drought occurrences in the Pantanal biome. Utilizing two well-established drought indices, the standard precipitation index (SPI) and the standard precipitation evapotranspiration index (SPEI), we analyzed the available observational data provided by the Climate Research Unit (CRU). Additionally, we endeavored to project droughts throughout the 21st century, thereby facilitating the visualization of potential reoccurrences of hazardous events in the Pantanal area. Two regional climate model (RCM) ensembles, the Eta ensemble (E1) and CORDEX ensemble (E2), along with representative concentration pathways (RCP4.5 and RCP8.5 scenarios) were used to project the severity of droughts in the Brazilian Pantanal until 2098/2099. The findings indicate that the hydrological year of 2019/2020 was the driest on record in the Pantanal over the past 80 years. The E1 ensemble did not project such an extreme event, whereas the E2 ensemble forecasted extreme droughts before the 2040s under the RCP4.5 and RCP8.5 scenarios. Using the SPEI, both ensembles showed similar results, with extreme droughts projected toward the end of the 21st century. Notably, the SPI demonstrated effectiveness in detecting short-term droughts, while the SPEI was more efficient for long-term assessments, projecting extreme drought events for the last two decades. The SPEI, employed with the Eta and CORDEX ensembles, can provide valuable insights into drought projections. Moreover, the potential recurrence of extreme droughts, characterized by significant below-average precipitation spanning vast areas throughout the hydrological year, poses a severe threat to the Pantanal biome in this century. [ABSTRACT FROM AUTHOR]

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