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We evaluated the performance of the Thornthwaite (ThW) method using two gridded climate datasets to estimate monthly average daily potential evapotranspiration (PET). The PET estimated from two gridded series were compared to PET and to reference evapotranspiration (ETo) determined, respectively, through the ThW and Penman-Monteith model parameterized on Food and Agriculture Organization–Irrigation and Drainage paper No 56 (PM-FAO56) using data from weather stations. The PET by ThM was based on monthly air temperature series (1961–2010) from two gridded datasets (Global Historical Climatology Network-GHCN and University of Delaware-UDel) and 21 weather stations of the National Institute of Meteorology (INMET) located in Southeastern Brazil. The ETo PM-FAO56 used monthly climate series (1961–2010) on sunshine duration, air temperature, relative humidity, and wind speed from weather stations of the INMET. The PET estimated using UDel gridded series was better overall performance than the GHCN series. Differences in altitude, latitude, and longitude were the main geographic factors determining the performance of the PET estimates using gridded climate series. Depending on the factors, some locations require bias correction, especially locations more than 10 km away from the grid point. The gridded datasets are an alternative for locations without climatic series data or with low-quality non-continuous data series. [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate change affects the hydrological cycle and has a significant influence on water resources, which can lead to environmental and socioeconomic damage caused by droughts. This phenomenon has become more acute in recent years. Among the indices used to assess the extent of droughts, the Reconnaissance Drought Index (RDI) is being adopted throughout the world. The RDI requires a stationarity assumption in its statistical calculations; however, most of the hydro-meteorological time series show non-stationarity. Hence, this paper seeks to assess meteorological droughts by means of RDI by adopting both stationary and non-stationary approaches. Non-stationarity was assessed by applying the Mann–Kendall test for trend detection and the Pettitt test for change point detection. The Thornthwaite method was employed to estimate the potential evapotranspiration required for RDI application. The bias in the future series were corrected employing the Linear Scaling (LS) technique for precipitation series and the Empirical Quantile Mapping (EQM) technique for the temperature series. Historical and future simulated monthly temperature and precipitation data were obtained from 34 meteorological stations located within Parana State, Brazil. The results showed that the maximum drought magnitude, duration, and intensity have increased during the 21st Century. When compared with historical patterns up to 2100, the results showed that drought magnitude is expected to increase by 105%, while drought duration is expected to increase by 59% in meteorological drought projections. [ABSTRACT FROM AUTHOR]

Climate change has caused an increased occurrence of heat waves. As a result of rising temperatures, implications for health and the environment have been more frequently reported. Outdoor labour activities deserve special attention, as is the case with agricultural and construction workers exposed to extreme weather conditions, including intense heat. This paper presents an overview of heat stress conditions in Brazil from 1961 to 2010. It also presents computer‐simulated projections of heat stress conditions up to the late 21st century. The proposed climate analysis drew on historical weather data obtained from national weather stations and on reanalysis data, in addition to future projections with the ETA (regarding the model's unique vertical coordinate) regional forecast model. The projections took into consideration two Representative Concentration Pathways (RCP)—the 4.5 and 8.5 climate scenarios, namely, moderate and high emissions scenarios, respectively. Heat stress was inferred based on the wet‐bulb globe temperature (WBGT) index. The results of this climate analysis show that Brazilian outdoor workers have been exposed to an increasing level of heat stress. These results suggest that future changes in the regional climate may increase the probability of heat stress situations in the next decades, with expectations of WBGT values greater than those observed in the baseline period (1961–1990). In terms of spatial distribution, the Brazilian western and northern regions experienced more critical heat stress conditions with higher WBGT values. As a response to the increased frequency trends of hot periods in tropical areas, urgent measures should be taken to review public policies in Brazil. Such policies should include actions towards better working conditions, technological development to improve outdoor labour activities, and employment legislation reviews to mitigate heat impacts on occupational health. [ABSTRACT FROM AUTHOR]

Studies about evaluations of different rainfall estimation methods are important as they are usually applied in works related to water resources availability, public supply, watering, animal water supply, hydroelectric power generation, drought episodes' evaluation, among others. Studies that cover the entire area of the Brazilian semiarid within this scope are still scarce. In this context, the objective of this paper was to evaluate seven rain estimation methods, from different approaches, with the aid of statistical analysis. The focus was on the long term, using 30 years of data in monthly scale, in order to verify the methods performance in estimating the spatiotemporal behaviour of rainfall compared to data measured in situ, coming from rainfall and meteorological stations. The evaluation process was based on the random selection of training and testing stations, with the first being used to interpolate rainfall data using different methods, and the latter used to evaluate this estimates with the aid of statistical analysis. Finally, the results were standardized, interpreted and discussed. Of all the estimation methods evaluated, CHIRPS obtained the best performance when compared to field stations data used as test. From the results obtained, there is evidence that the best performance is due to the incorporation of several distinct data sources derived from in situ stations, geostationary satellite infrared sensor estimates and physiographic predictors. This information is not fully present in other evaluated methods. The worst estimation performances were in the eastern side of the Brazilian semiarid, an area that receives moisture from the Atlantic Ocean and has significant topographic variations, due to the set of the complex relief mountains present in the northeast coast of Brazil. [ABSTRACT FROM AUTHOR]

The study of climatic variables in large scales with surface meteorological stations is limited due to the low density of these stations in many regions, possible sources of errors related to missing data, and uncertainties about the calibration sensors. Global gridded data (GD) systems can minimize these problems. Thus, studies that validate GDs with "ground truth" are important for several applications such as climate change. The objective of this study was to compare long series of surface data with 10-day estimates of average air temperature (T) and precipitation (P) using data from the European Center for Medium-Range Weather Forecast (ECMWF) and the National Aeronautics and Space Administration (NASA) for important agricultural locations in the states of Minas Gerais and São Paulo in Brazil. Despite the different spatial resolutions between ECMWF and NASA, the purpose of this paper was to evaluate the two data sources as they are readily available. The GD performance was evaluated by linear regression analysis. Analyses were performed for each meteorological variable for entire years and separated by seasons. The estimates of T from both ECMWF and NASA systems were accurate with the minimum Willmott concordance index (d) and RMSEp of 0.86, 0.37 °C, respectively, and precision with R2 0.61. The estimates of P had a minimum R2, d, and RMSEp of 0.48, 0.79, 2.15 °C respectively. The decreasing orders of (R2) were autumn > winter > spring > summer for T and winter > autumn > spring > summer for P, varying from 0.93 to 0.61 for T and from 0.77 to 0.48 for P. [ABSTRACT FROM AUTHOR]

The south of Brazil is a territory where different weather systems act, contributing to a non-homogeneity of the rainfall distribution in the region. This paper presents a characterization of rainfall occurring in the Itajaí River Basin, Santa Catarina, located in the south of Brazil. Through the use of daily rainfall data, we propose a review of the rainfall analysis using 10 climatic indexes created by the ETCCDI (Expert Team, ET, On Climate Change Detection and Indexes). The time period data from 1983 to 2014, originated from 31 meteorological stations, were analysed after an intense quality control and accurate historical research. Cluster technical analysis was performed to identify climatic areas within the basin. The results indicate that three climatic regions were identified with similar total annual precipitation but different seasonal distribution in the studied area. The analysis performed by the climatic indices confirms that an increase in total precipitation was recorded in almost all stations analysed and extreme precipitation was the main contributor to such additions. In this sense, the significant increase in total annual precipitation is mainly related to values above 95‰, that is, higher rainfall rates, as well as higher precipitation events above 10 and 20 mm/day. The present article presented alarming results and the possibility of future studies and research on the effects of variability, climate change and assessment of the vulnerability of the Itajaí River Basin. [ABSTRACT FROM AUTHOR]

Montane climates are shaped by high spatial variability that depends on net radiation and synoptic weather, and much on elevation and topographic features of terrain. We measured near‐ground meteorological variables using a weather station network during 14 months, in a valley‐shaped basin in southeast Brazil, to address the spatiotemporal climate variability at the meso‐γ atmospheric scale. The terrestrial climatic gradients were evident in the cross‐valley direction of the basin, where the valley tended to warm/wet up at day and cool/dry down at night relatively from the slopes. The temperature at noon showed high variability and decreased at a mean gradients of about −0.7 °C (100 m)−1. The nocturnal air temperature increased with height up to a maximum at about 200 m (the thermal belt), and showed seasonal rates higher/less in dry/wet season of +1.1/+0.2 °C (100 m)−1 over the full altitude. The vapour pressure decreased from the valley bottom upwards, in general below −0.5 hPa (100 m)−1, whereas the wind speed increased at a rate of 0.9 m s−1 (100 m)−1. We noted significant differential warming along the valley and mountain sides. The middle valley was circumstantially colder at night and warmer at daytime, relatively to the upper catchment, under mean magnitudes below 1.0 °C. The west slope at upper catchment was slightly warmer at night, and colder in the afternoon, at magnitudes below 0.5 °C, highlighting the control of hills' aspect at daytime, and the sheltering to flow aloft in east side. The cross‐valley gradients appeared to be well associated with local circulation, where downslope wind and positive temperature gradients, as well as upslope wind and negative temperature gradients strictly coexisted during the morning. The terrestrial gradients and the thermal circulation were in general dampened by cloudiness and mechanical mixing. This paper presents the spatiotemporal variability of near‐surface temperature, specific humidity and wind across the landscape of a mesoscale basin in southeast Brazil. We show the daily and seasonal variation of climatic gradient across the catchment and the characteristics of the thermally driven wind circulation and highlighted the influence of the topography and synoptic weather conditions. [ABSTRACT FROM AUTHOR]

El Niño is generally associated with negative rainfall anomalies (below-average rainfall) in northern Northeast Brazil (NNEB). In 2019, however, the opposite rainfall pattern was observed during an El Niño episode. Here, we explore the mechanisms that overwhelmed typical El Niño-related conditions and resulted in positive rainfall anomalies (above-average rainfall) in NNEB. We focus on the austral autumn when El Niño is most prone to rainfall anomalies in the region. The analysis of several datasets, including weather station data, satellite data, reanalysis data, and modelled data derived from a dry linear baroclinic model, allowed us to identify that the austral autumn 2019 above-average rainfall in NNEB was likely associated with four combined factors; these are (1) the weak intensity of the 2019 El Niño; (2) the negative phase of the Atlantic Meridional Mode; (3) local and remote diabatic heating anomalies, especially over the western South Pacific and tropical South Atlantic, which resulted in anticyclonic and cyclonic circulations in the upper and lower troposphere, respectively, over the tropical South Atlantic; and (4) sub-seasonal atmospheric convection anomalies over the western South Pacific, which reinforced the low-frequency convection signal over that region. This latter factor suggests the influence of the Madden–Julian Oscillation on rainfall in NNEB during the first ten days of March 2019. We discuss these mechanisms in detail and provide evidence that, even during an El Niño event, above-average rainfall in NNEB in the austral autumn may occur, and its modulation is not limited to the influence of a single climate phenomenon. Our results may assist in the planning of several crucial activities, such as water resources management and agriculture. [ABSTRACT FROM AUTHOR]

Extreme precipitation events are becoming increasingly frequent and intense in southeastern Brazil, leading to socio-economic problems. While it is not possible to control these events, providing accurate weather forecasts can help society be better prepared. In this study, we assess the performance of the Weather Research and Forecasting (WRF) model in simulating a period of extreme precipitation from 31 December 2021 to 2 January 2022 in the southern region of Minas Gerais (SMG) state in southeastern Brazil. We conducted five simulations using two nested grids: a 12 km grid (coarse resolution) and a 3 km grid (high resolution). For the coarse resolution, we tested the performance of five cumulus convection parameterization schemes: Kain–Fritsch, Betts–Miller–Janjic, Grell–Freitas, Grell–Devenyi, and New Tiedke. We evaluated the impact of these simulations on driving the high-resolution simulations. To assess the performance of the simulations, we compared them with satellite estimates, in situ precipitation measurements from thirteen meteorological stations, and other variables from ERA5 reanalysis. Based on the results, we found that the Grell–Freitas scheme has better performance in simulating the spatial pattern and intensity of precipitation for the studied region when compared with the other four analyzed schemes. [ABSTRACT FROM AUTHOR]

The design charts for basic wind speeds currently in use in Brazil [1] were created in 1977, based on wind speed records from 1950 to 1974. The database covered up to 25 years of wind records obtained in 49 weather stations, totaling 919 station×years of data. Since 1974, additional 37 years of wind records became available, but have not been incorporated in the design code. Hence, the updated wind charts proposed in this paper are long overdue. In this paper, 62 years of wind records in Brazil are gathered in order to construct updated and more reliable wind charts. The original data by Padaratz [2] are complemented by data from 104 airport weather stations, made available through the Wolfram Research Database [3]. In total, 4142 station×years of data are used in the present study, hence providing much better cover in terms of space and time span. Maximum annual wind speeds for the individual stations are fitted to Gumbel distributions, from which basic wind speeds are evaluated (mean return period of 50 years). Basic wind speeds are used to build a non-linear regression model, using the p-value of the Anderson-Darling goodness- of-fit test as regression weight. This ensures that extreme value wind distributions for which a good fit is obtained are given more importance in the regression model, reducing the influence of spurious data. The regression model developed herein is used to plot a new design chart for basic wind speeds in Brazil. It is proposed that this new wind chart be incorporated in the Brazilian code for design of structures subject to wind [1]. In this regard, it is observed that basic wind speeds obtained herein are higher than the wind speeds of the current chart for significant parts of Brazil (notably the center, northeast and north), and are the same or smaller in some parts of the south and southeast. It is shown herein that the main differences between the current and the proposed charts are not due to different modeling assumptions, but are mainly due to the new data. The proposed chart is updated, and is more reliable than the chart currently in use, as it reflects 4142 station×years of data, and covers up to 62 years of wind records. [ABSTRACT FROM AUTHOR]

This paper addresses the retrospective detection of step changes at unknown time points in the correlation structure of two or more climate times series. Both the variance of individual series and the covariance between series are addressed. For a sequence of vector-valued observations with an approximate multivariate normal distribution, the proposed method is a parametric likelihood ratio test of the hypothesis of constant covariance against the hypothesis of at least one shift in covariance. The formulation of the test statistic and its asymptotic distribution are taken from Chen and Gupta (2000). This test is applied to the series comprised of the mean summer NINO3 index and the Indian monsoon rainfall index for the years 1871–2003. The most likely change point year was found to be 1980, with a resulting p-value of 0.12. The same test was applied to the series of NINO3 and Northeast Brazil rainfall observations from the years 1856–2001. A shift was detected in 1982 which is significant at the 1% level. Some or all of this shift in the covariance matrix can be attributed to a change in the variance of the Northeast Brazil rainfall. A variation of this methodology designed to increase power under certain multiple change point alternatives, specificallly when a shift is followed by a reversal, is also presented. Simulations to assess the power of the test under various alternatives are also included, in addition to a review of the literature on alternative methods. [ABSTRACT FROM AUTHOR]

The relationship between growing rates of urbanisation and city warming has been evaluated in a very large number of urban climate studies. The work detailed here has focused on remote-sensing data, looking at changes in urbanisation over time in one of the newest cities in Brazil, i.e. Palmas in the northern region of the country, which serves as capital city of Tocantins. The youngest state in Brazil, Tocantins was only founded in 1988, with the construction of Palmas as capital commencing in 1989. Measured meteorological data were used to assess local climate changes in typical years, whereas urbanisation levels, generated for stepwise increments of 10 years, were obtained from the identification of vegetated and built-up classes in satellite imagery. Results suggest that changes in local climate were not always related to ongoing urbanisation in Palmas. Equally, despite promising changes in patterns of distribution of vegetation in given areas of Palmas over time - with an increase in high NDVI levels in 2021 that would potentially ameliorate local climate - thermal benefits did not prove to be detectable at the reference meteorological station. [ABSTRACT FROM AUTHOR]

Heat waves (HWs) are atmospheric events of synoptic and global scale that negatively impact productive sectors and the population. This study aims to investigate HWs in the São Paulo (SP) State, Brazil, and describe their intensity, duration, spatial coverage and atmospheric characteristics. HWs were identified using observed data from 65 weather stations for the period 2000–2020. The NCEP‐DOE Reanalysis was used to determine synoptic and global scale circulation characteristics. The results showed that SP experiences different effects of thermal stress on maximum temperatures (Tmax), with the north and northwest sectors reaching the highest average values (38°C). The average temperature of HWs in the state was 34.9°C, with an average duration of 5.3 days and 92% of events taking place between 2010 and 2020. A greater number of events occurred in 2015, 2016 and 2019, mainly in the austral summer and spring. The following atmospheric characteristics were found to be associated with HWs in SP: an anomalous semistationary anticyclonic circulation at 500 hPa over the hinterland regions of Brazil, a thermal low at 1000 hPa over Paraguay, a Rossby wave train originating in the South Pacific Ocean and spreading to centre‐south Brazil, a positive sea surface temperature anomaly in the South Atlantic Ocean near the coast of Brazil and another over the South Pacific, and a negative pattern circling Antarctica. Apparently, there is a certain degree of coupling between sea surface temperature anomalies and the Rossby train, the former being the trigger of the event. [ABSTRACT FROM AUTHOR]

In this work, we used hourly data of high frequency of solar radiation from the entire Northeast region of Brazil. We used the Multifractal Detrended Fluctuation Analysis (MFDFA) method to analyze the characteristics of the solar radiation series in 137 meteorological stations from 2010 to 2022. For all analyzed series, the parameter α 0 > 0. 5 characterizes persistent series. The values of r > 1 reveal asymmetry to the right, indicating that large fluctuations contributed to the multifractality process. The states of Maranhão and Bahia presented the highest values of spectrum width W , indicating greater complexity. We found that long-range correlations are the leading cause of multifractality observed in the dynamics of the series of solar radiation anomalies. [ABSTRACT FROM AUTHOR]

The demand for meteorological gridded datasets has increased within the last few years to inform studies such those in climate, weather, and agriculture. These studies require those data to be readily usable in standard formats with continuous spatial and temporal coverage. Since 2016, Brazil has a daily gridded meteorological data set with spatial resolution of 0.25° × 0.25° from January 1, 1980 to December 31, 2013 which was well received by the community. The main objective of this work is to improve the Brazilian meteorological data set. We do this by increasing the resolution of the minimum and maximum temperature (Tmax and Tmin) gridded interpolations from 0.25° × 0.25° to 0.1° × 0.1° by incorporating data on topographic relief, and increasing the time period covered (January 1, 1961–July 31, 2020). Besides Tmax and Tmin, we also gridded precipitation (pr), solar radiation (Rs), wind speed (u2), and relative humidity (RH) using observed data from 11,473 rain gauges and 1,252 weather stations. By means of ranked cross‐validation statistics, we selected the best interpolation among inverse distance weighting and angular distance weighting methods. We determined that interpolations for Tmax and Tmin are improved by using the elevation of a query point, that accounts for topographic relief, and a temperature lapse rate. Even though this new version has ≈25 years more data relative to the previous one, statistics from cross‐validation were similar. To allow researchers to assess the performance of the interpolation relative to station data in the area, we provide two types of gridded controls. [ABSTRACT FROM AUTHOR]

For this study on urban climatology, the study area is the city of Balneário Camboriú, belonging to the Brazilian state of Santa Catarina (SC), located at 26°59′42″ south latitude and 48°37′46″ west longitude. As it is the most vertical city in the entire Southern Hemisphere, Balneário Camboriú was selected as the study area for the development of this climate analysis. Then, this study was concerned with analyzing the formation of urban heat islands throughout the daytime and nighttime in the city of Balneário Camboriú, Santa Catarina, Brazil, on some days in October 2020, from the perspective of the local climatic zones. Seven fixed sampling points and one official weather station were selected for this research. These points were selected in order to facilitate analysis of the climatic behaviour of the urban area throughout the day, comparing it with the other points, and also to verify possible changes in the local climate in the most diverse types of LCZ. At these same points, the Sky View Factor (SVF) measurements were taken. to elaborate the map of LCZ of Balneário Camboriú, the WUDAPT method was used. There was a great variation of the SVF between the collection points, and different LCZs were mapped, which contributed to the formation of urban heat islands whose maximum magnitude was 10.8 °C and islands with freshnesses of magnitudes of −4.5 °C. [ABSTRACT FROM AUTHOR]

Freshwater scarcity is a significant concern due to climate change in some regions of Brazil; likewise, evaporation rates have increased over the years. Floating photovoltaic systems can reduce water evaporation from reservoirs by suppressing the evaporating area on the water surface. This work evaluated the effects of floating photovoltaic systems on water evaporation rates in the Passaúna Reservoir, southeastern Brazil. Meteorological data such as temperature, humidity, wind speed, and solar radiation were used to estimate the rate of water evaporation using FAO Penman–Monteith, Linacre, Hargreaves–Samani, Rohwer, and Valiantzas methods. The methods were tested with the Kruskal–Wallis test, including measured evaporation from the nearest meteorological station to determine whether there were significant differences between the medians of the methods considering a 95% confidence level for hypothesis testing. All methods differed from the standard method recommended by the FAO Penman–Monteith. Simulations with more extensive coverage areas of the floating photovoltaic system were carried out to verify the relationship between the surface water coverage area and the evaporation reduction efficiency provided by the system and to obtain the avoided water evaporation volume. For the floating photovoltaic system with a coverage area of 1265.14 m2, an efficiency of 60.20% was obtained in reducing water evaporation; future expansions of the FPS were simulated with coverage areas corresponding to energy production capacities of 1 MWp, 2.5 MWp, and 5 MWp. The results indicated that for a floating photovoltaic system coverage area corresponding to 5 MWp of energy production capacity, the saved water volume would be enough to supply over 196 people for a year. More significant areas, such as covering up the entire available surface area of the Passaúna reservoir with a floating photovoltaic system, could save up to 2.69 hm3 of water volume annually, representing a more significant value for the public management of water resources. [ABSTRACT FROM AUTHOR]

The sudden increase in air temperature associated with strong gusty winds of northerly direction is a phenomenon occasionally observed during the cold season in the central region of Rio Grande do Sul (RS) state, located in extreme southern Brazil. This geophysical flow, which is known as Vento Norte (VNOR; Portuguese for "North Wind"), promotes temperature variations that depart significantly from the local cold-season climatology. In this study, eleven years of surface meteorological observations collected at seven weather stations distributed over central RS are employed to investigate the regional extension of the effects of the VNOR windstorm. The analysis revealed that the sharp increase in temperature and in wind magnitude caused by VNOR is observed over a rather wide region of central RS. However, it is in the vicinities of the city of Santa Maria, located just south of an abrupt drop in terrain elevation, that the most intense VNOR effects are observed suggesting a downslope enhancement of the windstorm. A detailed investigation of the meteorological data also showed that the duration of the VNOR windstorm is well correlated with the magnitude of the maximum wind gusts, with the most intense VNOR events also lasting longer. VNOR events occur more frequently in the period between the morning (0700 LST) and early afternoon (1400 LST). The onset of the windstorm is detected predominantly during overnight and morning hours, with 70% of VNOR cases initiating between 0000 and 1000 LST. Regarding the VNOR demise, 66% of the windstorms dissipate between early afternoon and early evening hours (1200–1900 LST). Results from this study are applicable in the areas of atmospheric diffusion and local weather forecasting. [ABSTRACT FROM AUTHOR]

Drought is a natural hazard with critical societal and economic consequences to millions of people around the world. In this paper, we present the climatology of severe drought events that occurred during the 20th century in the region of Sao Paulo, Brazil. To account for the effects of rainfall deficit and changes in temperature at a climatic timescale, we chose the Standardized Precipitation Evapotranspiration Index (SPEI) to identify severe droughts over the city of Sao Paulo, and the eastern and central-western regions of the state. Events were identified using weather station data and European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis data, in order to assess the representation of drought periods in both datasets. Results show that the reanalysis seems suitable to represent the number of events and their mean duration, severity and intensity, but the timing and characteristics of individual events are not well reproduced. The correlation between observation and reanalysis SPEI time series is low to moderate in all cases. A linear trend analysis between 1901 and 2010 shows a tendency of increasing (decreasing) severe drought events in the central and western (eastern) Sao Paulo state, according to observational data. This is in agreement with previous findings, and the reanalysis presents this same signal. The weakened trend values in the reanalysis may be associated with issues in representing precipitation in this dataset. [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Agricultura Irrigada - RBAI is the property of Revista Brasileira de Agricultura Irrigada - RBAI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study investigates an extreme rainfall event which occurred in Northern Brazil (NEB) between 20 and 30th 2017 May causing several deaths and making thousands homeless. Based on a suite of microphysics and planetary boundary layer (PBL) schemes based on the WRF model, it is demonstrated that anomalous weather conditions are characterized by significant upward and eastward wind flow. Omega differences with respect to climatological conditions showed values up to − 0.04 Pa/s and wind up to 6–8 m/s in consonance with higher precipitation in May in the NEB coast. The cumulative rainfall for 11 days was higher than 500 mm in some locations, as measured by weather stations. These conditions were simulated by the WRF model under different physics parameterization schemes. In total 24 experiments with WRF were implemented. Non-local PBL demonstrated better performance than the local PBL. Moreover, the rainfall was concentrated in small portions of the region, and the local scheme limited the WRF conditions to estimate the correct maximum precipitation location. The Morrison scheme performed better compared to the other schemes. Results presented here show that the correct choices of the microphysics and PBL parameterizations are fundamental to obtain good simulation/forecast, especially for extreme rainfall events. This study demonstrates that regional modeling is crucial to provide accurate information to forecasters and decision makers to plan actions which hamper catastrophic situations such as landslides and floods in high-risk regions. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ETo) is a fundamental parameter for hydrological studies and irrigation management. The Penman-Monteith method is the standard to estimate ETo and requires several meteorological elements. In developing countries, the number of weather stations is insufficient. Thus, free products of remote sensing with evapotranspiration information must be used for this purpose. In this context, the objective of this study was to estimate monthly ETo from potential evapotranspiration (PET) made available by MOD16 product. In this study, the monthly ETo estimated by Penman-Monteith method was considered as the standard. For this, data from 265 weather station of the National Institute of Meteorology (INMET), spread all over the Brazilian territory, were acquired for the period from 2000 to 2014 (15 years). For these months, monthly PET values from MOD16 product for all Brazil were also downloaded. By using machine learning algorithms and information from WorldClim as covariates, ETo was estimated through images from the MOD16 product. To perform the modeling of ETo, eight regression algorithms were tested: multiple linear regression; random forest; cubist; partial least squares; principal components regression; adaptive forward-backward greedy; generalized boosted regression and generalized linear model by likelihood-based boosting. Data from 2000 to 2012 (13 years) were used for training and data of 2013 and 2014 (2 years) were used to test the models. The PET made available by the MOD16 product showed higher values than those of ETo for different periods and climatic regions of Brazil. However, the MOD16 product showed good correlation with ETo, indicating that it can be used in ETo estimation. All models of machine learning were effective in improving the performance of the metrics evaluated. Cubist was the model that presented the best metrics for r2 (0.91), NSE (0.90) and nRMSE (8.54%) and should be preferred for ETo prediction. MOD16 product is recommended to be used to predict monthly ETo, which opens possibilities for its use in several other studies. [ABSTRACT FROM AUTHOR]

Local‐level understanding of within‐season rainfall variability and its relationship with the El Niño Southern Oscillation (ENSO) can shed light on crop yield variations and establish appropriate cropping calendars in rainfed systems. This requires information on the growing season, including its length, the total rainfall, the onset and cessation of rainfall, the number of wet and dry days, and the optimal sowing window. The objective of this study was to examine the onset and cessation of both the rainy and growing seasons using historical daily rainfall datasets (1980–2013) from 50 weather stations distributed across the main grain production region of Brazil. We then correlated the interannual variability of the climate variables and crop water availability with ENSO (using the Oceanic Niño Index, ONI). Across the study region, the onset of the rainy period ranged from late September to early November, and the cessation period ranged from late March to mid‐April. The onset of the growing season followed that of the rainy season, beginning across central and northern Mato Grosso in mid‐October, followed by Goiás and Tocantins, and finally Rondônia by the end of October. The length of the sowing window was reduced, and the mean optimal sowing date was delayed during La Niña years for most weather stations in the study region. Our results infer the need to adjust the cropping calendars for specific ENSO phases only in regions that conduct crop rotations. Based on rice crop model simulations of water availability, we propose a mean optimal crop sowing calendar for annual crops in Central Brazil. Highlights: We analysed the impact of El Niño Southern Oscillation (ENSO) on the growing season characteristics of Central Brazil.The length of the sowing period is markedly reduced during La Niña years across the region. We propose a mean optimal crop sowing calendar for Central Brazil based on crop modelling results of ENSO effects. [ABSTRACT FROM AUTHOR]

There is a wide variety of climates on the planet's surface, and climate classifications are tools for delimiting and describing prevailing climate types. Köppen classification relates types of climate to types of vegetation, while Camargo classification seeks to map climatic types based on thermal and water factors. In Brazil, the Midwest region is a major agricultural producer but still lacks detailed climate information. In this sense, we aimed to compare Köppen and Geiger (1928) with Camargo (1991) methods for climate classification in the Midwest of Brazil. For this purpose, we used data on daily global solar radiation; mean, maximum, and minimum air temperature; relative humidity; wind speed; and precipitation from 2160 weather stations, which were obtained from the NASA/POWER platform. Components of normal climatological water balance were calculated using the Thornthwaite and Mather (1955) method, with an available water capacity of 100 mm. Köppen and Geiger (1928) system uses data on mean annual temperature, annual precipitation, coldest month mean temperature, warmest month mean temperature, and driest month precipitation. The method of Camargo (1991), modified by Maluf (2000), uses the following meteorological elements: mean annual temperature, coldest month mean temperature, annual water surplus and deficit, and water deficit months. The similarity between classification methods was verified by agglomerative hierarchical clustering and Tukey's test at 95% reliability. The most predominant climate class according to Camargo (1991) was TR-UMi (humid tropical climate), representing 33.63% of the entire territory of the Midwest of Brazil. According to Köppen and Geiger (1928), six climate types were observed in the Midwest region, with a predominance of class Aw (tropical climate with dry winter), representing 58.50% of the entire region. While Köppen and Geiger (1928) showed a macroscale scope, Camargo (1991) classification had a mesoscale approach. The latter was more suitable for agricultural purposes, mainly because it provided information on prevailing water conditions in the region. [ABSTRACT FROM AUTHOR]

The interannual variability of the northern northeast Brazil (NNB) rainfall is directly affected by the dynamics of large-scale systems through atmospheric circulation. In this context, a hidden Markov model (HMM) was used to describe the daily rainfall occurrence and intensity at four meteorological stations of the Metropolitan Region of Fortaleza (MRF) in the NNB, and the global teleconnection patterns that influence precipitation regimes during the rainy season (February, March, April and May) from 1975 to 2013. An HMM with 4 states was set up and interpreted as: very rainy (1), rainy (2), less rainy (3), and dry (4) weather conditions. They agree satisfactorily with the interannual variability of the rainy season in this region. State 2 is the only one which showed a statistical trend, indicating a probable decrease of precipitation occurrence in the rainy season. Results also show that the meteorological weather associated with both states 2 and 4 is strongly related to the El Niño-Southern Oscillation (ENSO), the North Atlantic tripole and are intrinsically conditioned to the large-scale atmospheric teleconnections of the Northern Hemisphere. All those mechanisms modulate the shift of the Intertropical Convergence Zone (ITCZ) southward (state 2) or northward (state 4), thus affecting the precipitation occurrence over the NNB. State 1 is distinguished by the influence of the Atlantic Meridional Mode (AMM) and the ITCZ displacement further south, while state 3 is identified by the absence of teleconnection patterns. [ABSTRACT FROM AUTHOR]

The need to validate the quality of evapotranspiration estimates is essential for this parameter which has extended its use. For this, it is necessary to evaluate both new remote sensing products that expand the areas of estimated evapotranspiration and empirical equations that provide estimates with different data requirements. In order to examine this problem, the present study compared the estimates of evapotranspiration obtained by remote sensing of the MOD16A2 product and seven empirical equations with the estimates obtained through the FAO-56 reference method, with data obtained from six meteorological stations in the State of Rio de Janeiro, Brazil. Data cover the period from 2007 to 2013, which contains different phases of the El Niño–Southern Oscillation phenomenon. The methods proposed by Valiantzas were those that obtained the best performances when compared with FAO-56 with R2 over 90%. The non-parametric analysis of Mann-Kendall for the six seasons was mostly not significant; only the station of Resende showed a tendency of significant growth during the El Niño episode (Z = 0.283 and p value = 0.050). The mangrove and forest classes were the ones that obtained the highest averages (3.75 mm d−1 and 3.62 mm d−1), where the gradient of evapotranspiration can be observed in the South-Northeast portions. The MOD16A2 orbital product was inferior to the methods that used surface meteorological station data. [ABSTRACT FROM AUTHOR]

The reference evapotranspiration (ETo) has long been used as a climate parameter for many studies in climatology and hydrology. However, many regions suffer from shortage of both meteorological monitoring stations and historical information on ETo. Thus, the objective of this study was to develop a daily gridded reference evapotranspiration data set for Brazil that matches the period and grid cells of the Global Precipitation Measurement (GPM) data. ETo was calculated using data from 849 weather stations over the period from 1 June 2000 to 31 December 2018. The features used to model ETo were the GPM daily data set, WorldClim averages monthly, and two engineered features. Among the machine learning algorithms assessed, the Cubist presented the best performance‐computation cost trade‐off in a subset of the entire data and, therefore, was selected to model ETo daily. The developed data set presented root mean square error of 0.65 mm day−1, or 16% lower than previous ETo data set developed for Brazil using interpolation techniques. The GPM and engineered features showed higher importance for the models trained during the wet season, while the WorldClim maximum temperature averages monthly were more important during the dry and cold season. The new gridded reference evapotranspiration data set for Brazil (ETo‐Brazil) was made freely available to the community. Key Points: Daily reference evapotranspiration is modeled daily using machine learning and based on remote sensing and climate data setsThe importance of the variables for the models is assessed for all daily modelsThe developed data set covers the same period and matches the resolution and positioning of the Global Precipitation Measurement data [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Two long-lived bow echoes that produced extensive swaths of damaging winds in extreme southern Brazil are investigated; the first event occurred on 29 May 2013 (austral fall) and the second one on 18–19 October 2014 (austral spring). Three main aspects are addressed: analysis of the atmospheric environments in which the convective systems developed; documentation of the main morphological features accompanying the bow echoes; verification of whether the severe weather events satisfied the definition of a derecho. The evolution of the bow echoes is described utilizing data from an S-band Doppler weather radar from the Brazilian Air Force. Hourly wind gusts from surface automated weather stations operated by Brazil´s National Institute of Meteorology combined with damage reports obtained from the Civil Defense System of Rio Grande do Sul state and media clipping are employed to characterize the progression, intensity and extension of the damaging winds. Both events exhibited typical characteristics of derecho-producing bow echoes, including intense rear-inflow jets, rear-inflow notches in the reflectivity field trailing the bowing segments, and mesoscale convective vortices in the polar flank of the convective systems. One of the convective systems also developed the bow-and-arrow convective structure. The lack of an extensive post-storm damage survey precluded a more rigorous analysis of the concentration of damage reports. However, the chronological progression of the severe wind gusts and damage reports followed the path of the bow echoes for more than 400 km, and it is concluded that most likely both events represented the manifestation of derechos. The large-scale environment is analyzed with Climate Forecast System version-2 gridded data, whereas the near-storm environments are assessed with the aid of proximity soundings. [ABSTRACT FROM AUTHOR]

Snowfall is considered a natural disaster in southern Brazil, where a little infrastructure exists up to prevent against the damage it induces, making snowfall forecast a matter of great interest in this region. The present article aims to describe the mean behavior of low, mid, and high atmospheric levels during snowfall occurrences in southern Brazil. Sea-level pressure (SLP), 1000–500 hPa atmospheric thickness, geopotential height at 500 hPa, and wind speed at 200 hPa have been analyzed. One hundred and ninety-six snowfall records from the conventional surface meteorological stations have been selected for the period from 1979 to 2015. The surface synoptic pattern associated with snowfall occurrences has been obtained from ERA-Interim reanalysis data with horizontal spatial resolution of 0. 75 ∘ × 0. 75 ∘ and temporal resolution of 12 h. SLP fields show a high-pressure transient system displacement from the Pacific Ocean to northeastern Argentina. In addition, it is possible to relate snowfall with displacement of a low-pressure system on the coast of southern Brazil. Thickness fields indicate shallow cold air mass intrusions one day before snowfall. Such a cold air continues moving towards low latitudes during consecutive snowfall days and it may be responsible for frost events in climatologically warm regions. Finally, mid and high atmospheric levels show an eastward propagating wave amplified by the Andes. [ABSTRACT FROM AUTHOR]

Crowdsourcing as a method to obtain and apply vast datasets is rapidly becoming prominent in meteorology, especially for urban areas where routine weather observations are scarce. Previous studies showed that smartphone battery temperature readings can be used to estimate the daily and citywide air temperature via a direct heat transfer model. This work extends model estimates by studying smaller temporal and spatial scales. The study finds the number of battery readings influences the accuracy of temperature retrievals. Optimal results are achieved for 700 or more retrievals. An extensive dataset of over 10 million battery temperature readings for estimating hourly and daily air temperatures is available for São Paulo, Brazil. The air temperature estimates are validated with measurements from a WMO station, an Urban Flux Network site, and data from seven citizen weather stations. Daily temperature estimates are good (coefficient of determination ρ2 of 86%), and the study shows they improve by optimizing model parameters for neighborhood scales (<1 km2) as categorized in local climate zones (LCZs). Temperature differences between LCZs can be distinguished from smartphone battery temperatures. When validating the model for hourly temperature estimates, the model requires a diurnally varying parameter function in the heat transfer model rather than one fixed value for the entire day. The results show the potential of large crowdsourced datasets in meteorological studies, and the value of smartphones as a measuring platform when routine observations are lacking. [ABSTRACT FROM AUTHOR]

The objectives of this study are to use a clustering technique to identify homogeneous rainfall regions in the watersheds of the eastern region of the state of Paraná and to associate the spatial and temporal distribution of rainfall with the influences of orography, the ocean and regional atmospheric dynamics. Rainfall data were obtained from 54 pluviometric stations and from eight meteorological stations, which comprise the historical series from 1976 to 2015. A cluster analysis technique was used with the Euclidean distance for measuring proximity and Ward's method for hierarchical grouping. The Litorânea watershed exhibited the highest rainfall totals in the study area, and the annual average was 2551 mm for the homogeneous group with the highest rainfall. The Ribeira river watershed exhibited the lowest total rainfall (1488 mm); therefore, it was considered a rain shadow region with a more tropical climate due to the concentration of rainfall in the period from September to March. The Alto Iguaçu watershed was characterized by the smallest spatiotemporal variation in rainfall due to its flatter relief and the influence of the subtropical climate. [ABSTRACT FROM AUTHOR]

Leaf wetness duration (LWD) is recognized as a very important conditioner of crops and forests diseases, but clearly, there is a considerable gap in literature on temporal models for prediction of LWD in broad regions from standard meteorological data. The objective of this study was to develop monthly LWD models based on the relationship between hours of relative humidity (RH) ≥ 90 % and average RH for Brazil and based on these models to characterize the temporal and spatial LWD variability across the country. Two different relative humidity databases, being one in an hourly basis (RH) and another in a monthly basis (RH), were used. To elaborate the LWD models, 58 automatic weather stations distributed across the country were selected. Monthly LWD maps for the entire country were prepared, and for that, the RH from the 358 conventional weather stations were interpolated using geostatistical techniques. RH and LWD showed sigmoidal relationship with determination coefficient above 0.84 and were highly significant ( p < 0.0001). In relation to the validation of the LWD monthly models, a very good performance for all months was obtained, with very high precision with r between 0.92 and 0.96. Regarding the errors, mean error showed a slight tendency of overestimation during February (0.29 h day), May (0.31 h day), July (0.14 h day), and August (0.34 h day), whereas for the other months, the tendency was of underestimation like January (−0.27 h day) and March (−0.25 h day). Even as a first approach, the results presented here represent a great advance in the climatology of LWD for Brazil and will allow the development of studies related to crop and forest diseases control plans. [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This work assessed homogeneity of the Institute of Astronomy, Geophysics and Atmospheric Sciences (IAG) weather station climate series, using various statistical techniques. The record from this target station is one of the longest in Brazil, having commenced in 1933 with observations of precipitation, and temperatures and other variables later in 1936. Thus, it is one of the few stations in Brazil with enough data for long-term climate variability and climate change studies. There is, however, a possibility that its data may have been contaminated by some artifacts over time. Admittedly, there was an intervention on the observations in 1958, with the replacement of instruments, for which the size of impact has not been yet evaluated. The station transformed in the course of time from rural to urban, and this may also have influenced homogeneity of the observations and makes the station less representative for climate studies over larger spatial scales. Homogeneity of the target station was assessed applying both absolute, or single station tests, and tests relatively to regional climate, in annual scale, regarding daily precipitation, relative humidity, maximum (TMax), minimum (TMin), and wet bulb temperatures. Among these quantities, only precipitation does not exhibit any inhomogeneity. A clear signal of change of instruments in 1958 was detected in the TMax and relative humidity data, the latter certainly because of its strong dependence on temperature. This signal is not very clear in TMin, but it presents non-climatic discontinuities around 1953 and around 1970. A significant homogeneity break is found around 1990 for TMax and wet bulb temperature. The discontinuities detected after 1958 may have been caused by urbanization, as the observed warming trend in the station is considerably greater than that corresponding to regional climate. [ABSTRACT FROM AUTHOR]

The main goal of this work is to describe the diurnal and seasonal variations of the radiation balance components at the surface in the city of São Paulo based on observations carried out during 2004. Monthly average hourly values indicate that the amplitudes of the diurnal cycles of net radiation ( Q*), downwelling and upwelling shortwave radiation (SW, SW), and longwave radiations (LW, LW) in February were, respectively, 37%, 14%, 19%, 11%, and 5% larger than they were in August. The monthly average daily values indicate a variation of 60% for Q*, with a minimum in June and a maximum in December; 45% for SW, with a minimum in May and a maximum in September; 50% for SW, with a minimum in June and a maximum in September; 13% for LW, with a minimum in July and a maximum in January; and 9% for LW, with a minimum in July and a maximum in February. It was verified that the atmospheric broadband transmissivity varied from 0.36 to 0.57; the effective albedo of the surface varied from 0.08 to 0.10; and the atmospheric effective emissivity varied from 0.79 to 0.92. The surface effective emissivity remained approximately constant and equal to 0.96. The albedo and surface effective emissivity for São Paulo agreed with those reported for urban areas in Europe and North America cities. This indicates that material and geometric effects on albedo and surface emissivity in São Paulo are similar to ones observed in typical middle latitudes cities. On the other hand, it was found that São Paulo city induces an urban heat island with daytime maximum intensity varying from 2.6°C in July (16:00 LT) to 5.5°C in September (15:00 LT). The analysis of the radiometric properties carried out here indicate that this daytime maximum is a primary response to the seasonal variation of daily values of net solar radiation at the surface. [ABSTRACT FROM AUTHOR]

The collective impact of several environmental factors on the biocontrol activity of Trichoderma stromaticum ( Ts) against Moniliophthora perniciosa ( Mp), the cause of cacao witches’ broom disease, was assessed under field conditions of shaded cacao ( Theobroma cacao) in south-eastern Bahia, Brazil. Biocontrol experiments were performed adjacent to an automated weather station, with sensors and Ts-treated brooms placed at different canopy heights. Sporulation occurred at the same dates for all Ts isolates, but in different quantities. Broom moisture >30%, air temperature of approximately 23 ± 3°C, relative humidity >90%, solar radiation intensities <0·12 KW m−² and wind speed near zero were the key environmental parameters that preceded Ts sporulation events. A multiple logistic regression indicated that these weather variables combined were capable of distinguishing sporulation from non-sporulation events, with a significant effect of wind speed. Analyses of environmental factors at ground level indicated similar pre-sporulation conditions, with a soil moisture content above a threshold of 0·34 m3 m−3 preceding all sporulation events. The sporulation of five selected Ts isolates was compared at four different canopy heights. Isolates responded differently to weather variation in terms of sporulation and antagonism to Mp at different canopy levels, indicating that different microclimates are established along the vertical profile of a shaded cacao plantation. The potential of these findings for development of predictive mathematical models and disease-management approaches is discussed. [ABSTRACT FROM AUTHOR]

The regional Eta workstation (WS) model with horizontal resolution of 40 km has been integrated over South America for January 2003. The NCEP–DOE Reanalysis II was used for initial and lateral boundary conditions. The comparison of the model-simulated and satellite-derived values of monthly mean incident solar radiation at the surface demonstrates that the former values are larger by 20%–30% over the entire region. To improve the surface flux representation in the model, a new solar radiation scheme has been implemented in it. An offline comparison of the original and the new radiation schemes with the detailed line-by-line method demonstrates a higher accuracy for the new scheme. With the new scheme, the model-simulated incident solar radiation at the surface is in a better agreement with the satellite-derived data. Nevertheless, a noticeable systematic difference of 10%–20% still remains, probably because of the incorrect description of cloud parameters in the model. The lower incident solar radiation in the new version of the model causes a decrease of near-surface air temperature by 0.1°–1°C and a decrease of precipitation rate by up to 20%–30% over most of the continent. The increase in the simulated incident solar radiation and temperature is found in the region of the South Atlantic convergence zone, which is responsible for the enhanced cloudiness and precipitation in the central and southeastern parts of Brazil during summer. The model results are compared with observational data of meteorological stations, the Global Precipitation Climatology Project (GPCP), and the South American Low-Level Jet Experiment (SALLJEX) and are discussed. [ABSTRACT FROM AUTHOR]

Understanding the long-term behavior of rainfall and potential evapotranspiration (PET) over watersheds is crucial for the monitoring of hydrometeorological processes and climate change at the regional scale. The São Francisco watershed (SFW) in Brazil is an important hydrological system that transports water from humid regions throughout the Brazilian semiarid region. However, long-term, gapless meteorological data with good spatial coverage in the region are not available. Thus, gridded datasets, such as the Climate Research Unit TimeSeries (CRU TS), can be used as alternative sources of information, if carefully validated beforehand. The objective of this study was to assess CRU TS (v4.02) rainfall and PET data over the SFW, and to evaluate their long-term (1942–2016) climatological aspects. Point-based measurements retrieved from rain gauges and meteorological stations of national agencies were used for validation. Overall, rainfall and PET gridded data correlated well with point-based observations (r = 0.87 and r = 0.89), with a poorer performance in the lower (semiarid) portion of the SFW (r ranging from 0.50 to 0.70 in individual stations). Increasing PET trends throughout the entire SFW and decreasing rainfall trends in areas surrounding the semiarid SFW were detected in both gridded (smoother slopes) and observational (steeper slopes) datasets. This study provides users with prior information on the accuracy of long-term CRU TS rainfall and PET estimates over the SFW. [ABSTRACT FROM AUTHOR]

The Northeast region of Brazil (NRB) is the most populous semiarid area in the world and is extremely susceptible to droughts. The severity and duration of these droughts depend on several factors, and they do not necessarily follow the same behavior. The aim of this work is to evaluate the frequency of droughts in the NRB and calculate the return period of each drought event using the copula technique, which integrates the duration and severity of the drought in the NRB in a joint bivariate distribution. Monthly precipitation data from 96 meteorological stations spatially distributed in the NRB, ranging from 1961 to 2017, are used. The copula technique is applied to the Standardized Precipitation Index (SPI) on the three-month time scale, testing three families of Archimedean copula functions (Gumbel–Hougaard, Clayton and Frank) to reveal which model is best suited for the data. Averagely, the most frequent droughts observed in the NRB are concentrated in the northern sector of the region, with an observed duration varying from three and a half to five and a half months. However, the eastern NRB experiences the most severe droughts, lasting for 14 to 24 months. The probability distributions that perform better in modeling the series of severity and duration of droughts are exponential, normal and lognormal. The observed severity and duration values show that, for average values, the return period across the region is approximately 24 months. Still in this regard, the southernmost tip of the NRB stands out for having a return period of over 35 months. Regarding maximum observed values of severity and duration, the NRB eastern strip has the longest return period (>60 months), mainly in the southeastern portion where a return period above 90 months was observed. The northern NRB shows the shortest return period (~45 months), indicating that it is the NRB sector with the highest frequency of intense droughts. These results provide useful information for drought risk management in the NRB. [ABSTRACT FROM AUTHOR]