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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]

Global warming is causing an intensification of extreme climate events with significant changes in frequency, duration, and intensity over many regions. Understanding the current and future influence of this warming in northeastern Brazil (NEB) is important due to the region's greater vulnerability to natural disasters, as historical records show. In this paper, characteristics of climate change projections (precipitation and air temperature) over NEB are analyzed using 15 models of Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathways (SSPs: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) scenarios. By using the Taylor diagram, we observed that the HadGEM3-GC31-MM model simulates the seasonal behavior of climate variables more efficiently. Projections for NEB indicate an irreversible increase in average air temperature of at least 1 °C throughout the 21st century, with a reduction of up to 30% in annual rainfall, as present in scenarios of regional rivalry (SSP3-7.0) and high emissions (SSP5-8.5). This means that a higher concentration of greenhouse gases (GHG) will increase air temperature, evaporation, and evapotranspiration, reducing rainfall and increasing drought events. The results obtained in this work are essential for the elaboration of effective strategies for adapting to and mitigating climate change for the NEB. [ABSTRACT FROM AUTHOR]

This paper aims to find probabilities of extreme values of the air temperature for the Cerrado, Pantanal and Atlantic Forest biomes in Mato Grosso do Sul in Brazil. In this case a maximum likelihood estimation was employed for the probability distributions fitting the extreme monthly air temperatures for 2007–2018. Using the Extreme Value Theory approach this work estimates three probability distributions: the Generalized Distribution of Extreme Values (GEV), the Gumbel (GUM) and the Log-Normal (LN). The Kolmogorov–Smirnov test, the corrected Akaike criterion AICc, the Bayesian information criterion BIC, the root of the mean square error RMSE and the determination coefficient R2 were applied to measure the goodness-of-fit. The estimated distributions were used to calculate the probabilities of occurrence of maximum monthly air temperatures over 28–32 °C. Temperature predictions were done for the 2-, 5-, 10-, 30-, 50- and 100-year return periods. The GEV and GUM distributions are recommended to be used in the warmer months. In the coldest months, the LN distribution gave a better fit to a series of extreme air temperatures. Deforestation, combustion and extensive fires, and the related aerosol emissions contribute, alongside climate change, to the generation of extreme air temperatures in the studied biomes. [ABSTRACT FROM AUTHOR]

Many regions around the world are facing climate changes, with substantial increase in air temperature over the past decades, which is mainly related to continental and global warming forced by the higher greenhouse gas (GHG) emissions. The objectives of this study were to use the Köppen climate classification to detect local climate change based on a historical series of 100 years and to assess if such change is related to those that are occurring in other spatial scales as a likely consequence of increasing GHG. This paper brings a content full of innovative results. The study area presented an average annual air temperature increase by 0.9 °C between 1917 and 2016, rising from 21.4 °C for the first climatological normal (1917–1946) to 22.3 °C for the last one (1987–2016). Furthermore, in the summer months, the temperature rose from 24.5 to 25.3 °C, and in the winter months, such increase was from 17.1 (1917–1946) to 18.3 °C (1987–2016). Our findings showed the subtropical conditions (Cfa in Köppen's classification) in the study area persisted from the beginning of the analysis (1917–1946) until the climatological normal of 1979–2008, with a clear tendency of tropicalization after that with a change in the climate type of Piracicaba from subtropical to tropical, which can now be classified as tropical with dry winter (Aw climate type). The local average air temperature showed concordances with the long-term air temperature anomalies from regional, continental, and global scales, indicating that all of them may be linked with increasing GHG emissions, since well-defined long-term linear relationships (r2 = 0.99) were observed between continental and global average air temperature anomalies and atmospheric CO2 concentration observed at the NOAA Lab in Mauna Loa in the last 59 years. While the local and regional forcing effects remain to be fully unraveled, our study provided a valid and strong scientific sound evidence that climate change occurred in Piracicaba, southeastern Brazil, in the last 100 years. [ABSTRACT FROM AUTHOR]

Currently, changes in rainfall regimes have intensified biomass burning in central Brazil. These fires, resulting mainly from anthropic action, emit large amounts of gases and aerosols into the atmosphere. The emission of these constituents in the dry season can drastically alter the functioning of ecosystems. In this work, it was verified that the high concentrations of Black Carbon (BC) have a direct relationship with the air temperature and influence the carbon capture process. This study was the result of a long-term campaign carried out in the northern region of the Brazilian Pantanal, between 2017 and 2019. Measurements of CO2 fluxes were evaluated together with measurements of temperature, radiation and BC concentrations. The results showed that in some episodes, the increase in BC concentration inhibits photosynthetically active radiation and increases air temperature. As a consequence of the increase in BC concentration, a reduction in carbon capture was observed. In a specific episode in October 2017, this work estimated a deficit of 1.65 kg.m−2 in CO2 capture due to the emission of BC in the Pantanal. [ABSTRACT FROM AUTHOR]

The air temperature anomaly was analysed in 16 consecutive winters from 2004 to 2019 in southern Brazil using reanalysis data and hourly atmospheric observations. In this study, 13 heat wave (HW) episodes were identified using the percentile methodology. All identified episodes are associated with the occurrence of a downslope windstorm known as Vento Norte (VNOR; Portuguese for 'North Wind'). The VNOR is characterized by a sharp increase in air temperature combined with constant, strong, gusty winds from the north and a drop in relative humidity. The average duration was about 5 days for HW and 18 h for VNOR being than in 59.5% of the HW hours, the VNOR windstorm was also detected. The main atmospheric variables were compared during the periods of winter, HW and the VNOR windstorm. The analysis showed that HW alters local weather and climate conditions, with the more pronounced features associated with the VNOR flow. A more detailed investigation comparing the atmospheric variables collected north and south of an abrupt change in terrain altitude (400 m) revealed that the main cause of the amplification of the atmospheric variable anomalies in the centre of the state of Rio Grande do Sul was the simultaneous occurrence of HW and VNOR. [ABSTRACT FROM AUTHOR]

Several atmospheric variables are directly influenced by oceanic conditions, mainly the sea surface temperature (SST). SST trends and variability over the southwestern Atlantic (SWA) have affected the South American climate, principally the monsoonal period (austral summer). This study analysed the SST trends over the SWA for all seasons. In addition, possible large‐scale triggers of the austral summer's warmest SST over the SWA and the straight impacts of these warmest SSTs on the South American climate were investigated. The results showed a significant positive SST trend of approximately 0.02°C·year−1 over the SWA for all seasons. Since 2000, positive SST anomalies have increased in frequency in all seasons, with the seven warmest summers occurring during the 2010s. The highest SST summers over the SWA have been related to four leading causes: (i) planetary waves triggered by warm anomalies over the subtropical South Pacific; (ii) an omega‐type blocking configuration over the South Atlantic; (iii) a Southern Annular Mode positive phase; and (iv) a strengthening of the Hadley Cell, responding to warm SST over tropical North Atlantic. They all reflected on intensification of the South Atlantic Subtropical High and the western boundary current, heating the SWA. The summer's warmest SST led to positive air temperature anomalies extending in almost all of eastern South America, with significantly highest temperatures over southeastern Brazil, northern Argentina and western Paraguay. Clouds decrease strengthen the incident shortwave in southeastern Brazil, warming the region. Significant reduction of cloudiness and precipitation indicate a low performance of the South Atlantic Convergence Zone. The comparison of the warmest summers in 1980s–1990s in the SWA ratified the role of SST intensification. In conclusion, the positive SST trends over the SWA are related to the summer's warmest SST after 2000s, causing heating and dryness in eastern South America, mainly over southeastern Brazil. [ABSTRACT FROM AUTHOR]

During the austral winter (June–August) of 2021, the meteorological services of Brazil, Argentina, Peru, Paraguay, Bolivia, and Chile all issued forecasts for unusually cold conditions. Record-low minimum temperatures and cold spells were documented, including one strong cold wave episode that affected 5 countries. In this study, we define a cold wave as a period in which daily maximum and minimum air temperatures are below the corresponding climatological 10th percentile for three or more consecutive days. The intense cold wave event in the last week of June, 2021, resulted in record-breaking minimum daily temperatures in several places in central South America and Chile. Several locations had temperatures about 10 °C below average, central South America had freezing conditions, and southern Brazil even saw snow. The cold air surge was characterized by an intense upper-air trough located close to 35° S and 70° W. The southerly flow to the west of this trough brought very cold air northward into subtropical and tropical South America. A northward flow between the lower-level cyclonic and anticyclonic perturbations caused the intense southerly flow between the upper-level ridge and trough. This condition facilitated the inflow of near-surface cold air from southern Argentina into southeastern Brazil and tropical South America east of the Andes. In the city of São Paulo, the cold wave caused the death of 13 homeless people from hypothermia. Frost and snow across southern and southeastern Brazil caused significant damage to coffee, sugarcane, oranges, grapes, and other fruit and vegetable crops. Wine and coffee production fell, the latter by 30%, and prices of food and commodities in the region rose. [ABSTRACT FROM AUTHOR]

Remotely sensed sea-surface temperature (SST) retrievals with a significant positive bias during the occurrence of upwelling phenomena along the southeastern coast of Brazil were reported in our companion paper. As a result, this paper proposes an automated bias correction algorithm to improve the MODIS long-wave multichannel SST (MCSST) retrievals during the abovementioned conditions in this region. In this paper, MODIS daytime SST data (SSTMODIS) and differences between brightness temperatures in MODIS channels 31 and 32 (BT31 − BT32) are analyzed simultaneously with hourly wind surface conditions, in situ SST at 0.3 and 10 m in depth (SSTbuoy03 and SSTbuoy10), and sensible and latent heat fluxes from the Cabo Frio buoy data (at 23° S, 42° W) during 2014. The obtained results show that some upwelling events present air temperature ($T_{\mathrm {air}}$) greater than SSTbuoy03 and low-atmospheric water vapor content. A simultaneous occurrence of these factors during upwelling conditions may lead to a warm-skin layer effect and may cause BT31 to be greater than SSTbuoy03 and BT31 − BT32 to be small (−0.18 °C ± 0.22 °C), affecting the MCSST performance. The proposed bias correction algorithm uses a least-squares curve between SSTbuoy03 and SSTMODIS retrievals when BT31 − BT32 ≤ 0.5 °C (i.e., dry atmospheric conditions). The bias correction algorithm has significantly improved the SSTMODIS bias (RMSE) from 1.43 °C to −0.2 °C (1.60 °C to 0.58 °C) when applied to 22 cloud-free pixels of MODIS during January–March of 2015. [ABSTRACT FROM AUTHOR]

This study examined the spatial and temporal patterns of the canopy layer urban heat islands (UHIUCL) in a small city in southeastern Brazil using the local climate zone (LCZ) system. We analysed the influence of weather conditions, LCZs characteristics, and local surface relief on the UHIUCL magnitudes. Mobile traverses were used to measure air temperatures during representative nights of wet and dry seasons. Daily maximum magnitudes were observed in compact classes (LCZs 3 and 7) under ideal weather conditions (dry, clear skies, and calm) and higher anthropogenic heat release (weekdays). Seasonal effects on LCZ thermal differences were negligible. The peripheral landscapes were warmer than the city centre in both seasons. Among the warmer areas in the city, magnitudes in compact LCZs 3 and 7 were consistently higher than in LCZ 6. In general, representative sites of the main 'built' LCZs in the study area exhibit similar inter‐zone temperature patterns to those reported for cities of different sizes from tropical and midlatitude regions. Thermal contrasts of ΔTLCZ 3 − D in the study area reveal significant evidence that small cities can have as strong heat islands as bigger cities. These findings highlight the importance of the LCZ system to identify the main controlling factors driving such thermal differences and the need to extend the application of this approach in other South American cities to yield systematic data of UHIUCL for urban planning given the coming challenges of climate change over the region. [ABSTRACT FROM AUTHOR]

This study aimed to assess monthly average daily global solar irradiation ( H g m) estimates in Southeastern Brazil from empirical models and artificial intelligence (AI) techniques using extreme air temperatures (maximum—Tx and minimum—Tn) and extraterrestrial solar irradiation ( H 0 m ) and evaluate the geographic and climate factors in the performance of the models or the AI techniques. The H g m , Tx and Tn data series from 95 automatic weather stations of the Brazilian National Institute of Meteorology (INMET) were used. The Hargreaves-Samani (HS) and Bristow-Campbell (BC) models were fitted, and AI techniques (artificial neural network—ANN and support vector machines—SVM) were trained, and assessed according to local climate conditions. Three input schemes in the AI techniques were assessed: (i) H 0 m , Tx, and Tn; (ii) H 0 m and air temperature amplitude (ΔT); and (iii) H 0 m , Tx, Tn, and ΔT. The coefficients of the HS (0.134 ≤ kr ≤ 0.262) and BC (0.539 ≤ β0 ≤ 0.796; 0.004 ≤ β1 ≤ 0.843; 0.35 ≤ β2 ≤ 2.60) models and their performance were influenced by climate, continentality/maritime effects, altitude and weather systems. The performance of the HS model was inferior to that of BC model and the SVM and ANN techniques. Overall, the SVN and ANN techniques performed better than the BC method. However, BC had similar or superior precision and accuracy to SVM and ANN for some climatic conditions and combinations of input variables. The quality of the H g m series, the combination of input variables, and climate influenced the estimates of the SVM and ANN techniques. [ABSTRACT FROM AUTHOR]

Studies of the anticipated consequences of climate change suggest that among all economic sectors, agriculture would be the most affected. In Brazil, this issue is particularly relevant, since the agricultural sector and its related activities account for a significant share of the country's GDP and employment. Using a fixed effects panel model and data from 1990 through 2012, this paper empirically analyzes the vulnerability of agriculture to climate variables in Brazil's ten main agricultural states and the possible resulting loss of agricultural value in the face of future climate change. Our work is differentiated from prior studies in that it employs state level annual data series, which allows the aggregation of a great deal of relevant current information to the analysis. The results indicate that climate variables have a significant impact on most of these states' agricultural production, especially air temperature, whose effects showed higher estimated magnitude than those from rainfall. Considering the estimated elasticities and climatic projections, the most severe damage to agriculture is expected in Espírito Santo, Minas Gerais, and Rio Grande do Sul. [ABSTRACT FROM AUTHOR]

Nitrogen (N) effect on crop yield depends on several factors such as soil type, climatic characteristics and orchard management, including plant density and N fertilization. These variables can be used to develop yield prediction models, which are scarce in the horticulture sector. This study aimed to evaluate the effect of nitrogen fertilization, orchards and cultivars and to predict the yields of 'Royal Gala' and 'Fuji Suprema' apples cultivated in a subtropical climate under different soil N availabilities. During the four seasons, nitrogen fertilization was applied a rates of 0, 25, 50, 100 and 150 kg N ha−1 year−1 for 'Royal Gala' and 'Fuji Suprema' apples located in southern Brazil. Yield, average fruit weight and leaf and fruit pulp N concentration were evaluated. Yield prediction models were developed based on the following variables: concentration of N in leaves and fruits, air temperature, chilling units, relative humidity and rainfall. "Cultivar" was the variable responsible for the greatest variation of yield, followed by "years/season", and then the "orchard management. The N rates applied in the four seasons did not predict crop yield. In the model, "orchard" was the greatest determinant for leaf N concentration, and "season" was the main determinant for fruit-pulp N concentration. Mathematical model (3), based on leaf and fruit pulp N concentration, and certain climatic variables (minimum air temperature, annual rainfall and chilling hours < 7.2 °C) had the greatest potential for predicting yield in orchards of 'Royal Gala' and 'Fuji Suprema'. [ABSTRACT FROM AUTHOR]

Air temperature and precipitation are the elements that most impact the development of plants and are essential for good agricultural planning. Thus, it aimed to evaluate climate change in Maranhão of Brazil using the Thornthwaite (Geographical Review 38:55–94, 1948) climate classification. It used historical series of precipitation and air temperature between 1980 and 2016, obtained by the National Institute of Meteorology of Brazil (INMET). Reference evapotranspiration (ETo) was estimated using the Thornthwaite (Geographical Review 38:55–94, 1948) method and thus calculated the water balance by Thornthwaite and Mather (Laboratory of Climatology 8:104) for all locations in the studied state. Thornthwaite (Geographical Review 38:55–94, 1948) moisture index was used to classify localities to their level of humidity or aridity. We used the scenarios RCP-2.6, RCP-4, RCP-6, and RCP-8.5 for analyzing twenty-first-century projections (2041–2060 and 2061–2080 periods). The average values of air temperature, rainfall, and reference evapotranspiration in the state of Maranhão were 27.30(± 0.53) °C, 1678.52 (± 377.70) mm, and 1067.98 (± 73.36) mm, respectively. The average annual climatic characterization of the state of Maranhão was 53.4 (± 38.6) mm of the soil water storage, 698.71 (81.07) mm of the water surplus, and 395.85 (± 65.91) mm of the water deficit. Maranhão had seven climatic indexes. The most prevalent in the state was the Humid (B1, B2, B3, and B4), with 61% of the entire territory. RCP2.6 and RCP 8.5 are the driest. RCP6.0 and RCP8.5 show the most significant changes in the current situation. The humidity index's reduction will harm various economic activities in Maranhão, such as agriculture, livestock, and fishing. [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 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]

Due to the huge variety of therapeutic properties found in plant leaves, many of these are widely used in traditional medicine. Among these plants, guaco, which has a rich in chlorogenic acids composition, is considered exotic in Brazil, being, therefore, an environmental problem. In this context, this study obtained the drying kinetics and the experimental equilibrium isotherms of guaco leaves, in the 40 to 70 °C range. Oswin's empirical model described 96% of the equilibrium data. The phenomenological mathematical model of distributed parameters, solved with the employment of thermo-physical properties, obtained from the centesimal composition, described 99% of the thin layer drying kinetics of guaco leaves. The heat of desorption, obtained by the Othmer method, ranged from 2375 to 3858 kJ kg−1, for the moisture in the range of 0.05 and 0.35 (d.b.). With the obtained results, it is possible to estimate both the drying time and the amount of energy needed to reach the final moisture which is safe for the storage of guaco leaves. [ABSTRACT FROM AUTHOR]

Brazil is one of the three largest beer producers in the world. Four basic ingredients are needed as raw material for the production of beer: water, malt, yeast, and hops (Humulus lupulus L.). Until recently, almost all of the hops in Brazil were imported from other countries. However, in the last decade, hop cultivation in Brazil has emerged due to the increase in the number of new craft breweries, which have demanded diversified raw material for the production of various types of beer. Hops is considered a short-day, temperate species, so the major challenge for the development of hop cultivation in Brazil, with high-yield capacity and with local typicity of bitterness and aroma, is the adaptation of cultivars to the photoperiod conditions in subtropical regions. This review addresses the history of hop cultivation in Brazil and characterizes the main climatic elements of three emerging subtropical growing regions located at different latitudes, such as air temperature, photoperiod, solar radiation, and water availability, to provide support for the development of new technologies for hop cultivation, including supplemental lighting, irrigation, and mulching. [ABSTRACT FROM AUTHOR]

During September–November 2020, the meteorological services of Brazil, Argentina, Peru, Paraguay, and Bolivia reported record‐high maximum temperatures in several warm spells during this season. Positive and significant trends in heat wave frequency, intensity, and duration have been recorded since the 1980s, particularly in large cities. In this study, a heat wave is defined as a period in which both daily maximum and minimum air temperatures exceed the corresponding climatological 90th percentile for three or more consecutive days during September–November 2020. In this period, an intense heat wave during the first half of October and two heat waves events in November resulted in record‐breaking daily maximum temperatures in several locations in central South America. Places experienced temperature of about 10°C above normal, and some locations reported maximum temperatures above 40°C for several days in a row. Because its intensity and geographical extension, affecting central South America from southern Peruvian Amazon to southeastern Brazil, the heat wave of September 23–October 15 was selected as a case study. This intense heat wave was due a persistent atmospheric blocking located starting in late September and lasting until middle October 2020, a continuous presence of a warm air mass for several consecutive days contributed to pronounced positive temperature anomalies, possibly reinforced by extremely low soil moisture. This makes it easier for these high‐pressure systems to generate extreme heat waves because more of the sun's energy is going into heating the atmosphere rather than evaporating non‐existent water in the soil. This heat wave aggravated the drought over the Pantanal and other regions in October 2020, increasing fires and impacts on natural and human systems, representing a severe drought‐heat compound event. This vicious cycle of drought and extreme heat is of the kind expected under a warming climate. [ABSTRACT FROM AUTHOR]

Providing comfortable thermal conditions for users of open spaces is vitally important for improving the quality of urban life. Thermal comfort can be defined through environmental, individual, and subjective variables. The Olgyay bioclimatic chart is an outdoor thermal comfort analysis tool, connecting temperature with relative humidity. The application of this tool is still limited to hot humid climates only where minimal differences between indoor and outdoor temperatures exist. The novelty of this work is to propose adaptations to the Olgyay bioclimatic chart, taking into consideration different climatic classifications. In addition, urban plantation is examined for its influence on thermal comfort through the bioclimatic chart. The method adopted in this research consists of field measurements of the microclimatic variables in the examined places. In response, a new graphic model is proposed with a range of thermal comfort zone and analysis of the data obtained. The neighborhood of Humaitá in Rio de Janeiro in Brazil is applied as a case study to validate the proposed approach. Insights into this work reveal that the urban plantation is contributing to the reduction of air temperature and the increase of relative air humidity; however, this contribution is insufficient to reach the thermal comfort conditions. [ABSTRACT FROM AUTHOR]

The São Francisco River Basin plays a critical role in the hydroelectrical operational planning of Brazil. Understanding the hydroclimatic dynamic regime and, consequently, related climate changes is essential for decision-makers of the hydroelectrical sector. In this context, the Xingó hydropower plant and its drainage area are taken as a reference for the hydroclimatic features analyzed in this research. Observed rainfall in the drainage basin and streamflow measurements in the power plant between 1975 and 2016 are used to assess the climatology of the region and to identify trends in the time series. In addition, a methodological framework based on numerical modeling of the hydroclimatic variables is employed to examine the representation of the present climate (1961 to 1990) and to investigate the future projections (2011 to 2100). The outputs from the Eta regional climate model runs driven by two global models are adopted in this case under the RCP4.5 and RCP8.5 IPCC scenarios along with the SMAP rainfall-runoff model. In Xingó, the average annual precipitation is about 978 mm and the average annual streamflow is 2,534 m3 s−1. The size of the Xingó HPP drainage area must be considered, as the rainfall that occurs in a given month can influence the streamflow of the following month. There is no trend regarding precipitation, while the streamflow time series show a statistically significant decreasing trend in the present climate. Climate projections point to an elevation in air temperature and a reduction in rainfall and streamflow by 2100. Most scenarios indicate that the average annual streamflow could be extremely low for nearly half of the twenty-first century. The results shown in this work may contribute to scenarios for operation of the Xingó HPP and support with information for planning decisions on country's energy security in the present and future climates. [ABSTRACT FROM AUTHOR]

BACKGROUND: The loss of coffee leaves caused by the attack of pests and diseases significantly reduces its production and bean quality. Thus this study aimed to estimate foliation for regions with the highest production of arabica coffee in Brazil using nonlinear models as a function of climate. A 25‐year historical series (1995–2019) of Coffea arabica foliation (%) data was obtained by the Procafé Foundation in cultivations with no phytosanitary treatment. The climate data were obtained on a daily scale by NASA/POWER platform with a temporal resolution of 33 years (1987–2019) and a spatial resolution of approximately 106 km, thus allowing the calculation of the reference evapotranspiration (PET). Foliation estimation models were adjusted through regression analysis using four‐parameter sigmoidal logistic models. The analysis of the foliation trend of coffee plantations was carried out from degrees‐day for 70 locations. RESULTS: The general model calibrated to estimate the arabica coffee foliation was accurate (mean absolute percentage error = 2.19%) and precise (R2adj = 0.99) and can be used to assist decision‐making by coffee growers. The model had a sigmoidal trend of reduction, with parameters ymax = 97.63%, ymin = 9%, Xo = 3517.41 DD, and p = 6.27%, showing that foliation could reach 0.009% if the necessary phytosanitary controls are not carried out. CONCLUSION: Locations with high air temperatures over the year had low arabica coffee foliation, as shown by the correlation of −0.94. Therefore, coffee foliation can be estimated using degree days with accuracy and precision through the air temperature. This represents great convenience because crop foliation can be obtained using only a thermometer. © 2021 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Studies that evaluate climate change projections over the whole of South America (SA) and including different seasons and models are scarce. In this context, the objective of this work is to assess climate projections for SA through the use of climatic indices, considering the entire continent, distinct seasons, and ensembles of models. Projections performed with the Eta regional climate model and its driving global climate models (GCMs) are analysed. From these projections, 19 climate indices based on daily precipitation and maximum and minimum temperature are computed. The results focus on two ensembles (GCMs and Eta), time slices (1980–2005 and 2050–2080), and scenarios (RCP4.5 and RCP8.5). In the validation of the present climate, it is shown that Eta adds value to GCMs. Future projections indicate, for both austral summer (DJF) and winter (JJA), an increase in the frequency and intensity of extreme events of daily rainfall over southeastern and extreme north of SA. Over the Amazon, during DJF, there is a statistically significant increase in the number of consecutive dry days and a decrease in the consecutive wet days. For northeastern Brazil, these features are more intense in JJA. The frequency of cold (warm) nights and days is projected to decrease (increase) over the whole continent and seasons. The climate change signal for the 19 climate indices is more intense under RCP8.5, and the regions more vulnerable to climate change are the Amazon, northeastern Brazil, and southeastern SA. Considering Brazil, the projections of precipitation and air temperature are also shown by biomes. [ABSTRACT FROM AUTHOR]

Seasonality and inter-annual variation of the energy balance of natural surfaces as the effect of conversion from natural to agricultural areas has been the object of much indepth research in South America. However, none has assessed the effect of conversion from native to an urbanized area. Current research was performed in the city of Cuiaba, in the Cerrado-Pantanal ecotone, state of Mato Grosso, central Brazil, featuring a tropical sub-humid climate (Aw). The paper investigates the pattern of energy fluxes exchanges in the rural and urban sites located in Brazilian savannah ecosystem. The heat stored inside the urban canopy (ΔQs) and within the rural area was obtained by the Objective Hysteresis Model (OHM) and by soil flux meter, respectively. Sensible (H) and latent (LE) heat fluxes were estimated by the Bowen Ratio Energy Balance (BREB). The rural and urban sites had different patterns in the micrometeorology variables: wind speed decreased while air temperature and vapor pressure deficit increased from rural to urban site. The urbanization also modified the energy fluxes partition of urban canopy by increasing ΔQs (12%) and H (60%) and by decreasing LE (29%), with β = 2.0, differentiating what was observed in the rural canopy, where the partition was 1.5%, 29%, 64% and β = 0.45, respectively. The ΔQs, H and LE were in phase with Rn, differing from what has been reported for sites in North America and Europe. [ABSTRACT FROM AUTHOR]

All methods for estimating evapotranspiration (ETo) require accurate and complete meteorological datasets. However, the common lack of such datasets in Brazil, as well as the definition of the method that best represents the spatiotemporal pattern of ETo, are the main challenges to assess and mitigate the effects of climate variability (natural or due to anthropogenic climate change) in the Brazilian agricultural production systems. In this sense, this work aims to assess the spatiotemporal pattern of ETo, identify, and select among twenty-nine methods the one that presents the best performance in estimating ETo for different regions of Brazil using a high-resolution gridded weather dataset (GWD). In this study, performance is evaluated by comparing the ETo results obtained through the different methods to that estimated by the Penman–Monteith method. The weather variables used were near surface air temperature (maximum and minimum), relative humidity, wind speed at 2 m, global solar radiation, ETo, and sea level pressure in a daily basis from 1980 to 2017. Through principal component analysis (PCA), the behavior of ETo was mainly influenced by the global solar radiation, maximum air temperature, and relative humidity. For this reason, the performance of the methods varied across the Brazilian regions and seasons. The Turc and Abtew methods showed the best performance in estimating daily ETo, with lower RMSE (~ 0.5 mm day−1) and MAPE (~ 12%) and higher c-index values (~ 0.75), with slight advantage of Turc method, for all Brazilian regions and seasons. Also, the ETo estimation by Turc and Abtew using the GWD dataset showed a good agreement with Penman–Monteith method. Finally, the Hargreaves, Penman Original, and Stephens Stewart methods stood out for the Brazilian Northeast region (mean RMSE of 0.7 mm day−1, mean MAPE of 14%, mean c-index of 0.7), in areas that presents predominantly arid and semiarid climate conditions. [ABSTRACT FROM AUTHOR]

We analyse seasonal and annual trends of extreme indices of air temperature and precipitation over Brazil during the period 1961–2018. The main goal is to investigate whether the climate is changing and if so, to explore if there is any marked seasonality in such changes. The daily observed datasets of maximum and minimum temperatures, and precipitation, are provided by the Brazilian National Institute of Meteorology and National Water Agency. We use the Sen Curvature and Mann‐Kendall statistical tests to compute the magnitudes and to evaluate the statistical significance of climate extremes trends, respectively. The results show that the warm extremes frequency of occurrence is increasing significantly while the opposite occurs for cold extremes, which reveals a very consistent and widespread warming over Brazil. The highest increases in warm extremes occur during austral spring and summer while for the cold extremes the greatest decreases are observed during austral winter. Unlike temperature, precipitation extremes show heterogeneous signals for most of the country. In Northeast Brazil, there are changes towards a drier climate, especially in summer and autumn. In the Southern region, the climate is becoming wetter, with a reduction in consecutive dry days, especially in spring. For the other regions, there is no strong clear change sign, but both positive and negative precipitation extreme trends, without statistical significance (mostly in Southeast Region). [ABSTRACT FROM AUTHOR]

The South American cucurbit fruit fly, Anastrepha grandis (Macquart) (Diptera: Tephritidae), is an economically important pest of cucurbits and is classified as a quarantine species in many countries. In Brazil, A. grandis has a limited distribution; it is absent from northern and northeastern Brazil and distributed discontinuously in other parts of the country. To indirectly evaluate the influence of climatic and edaphic variables on the occurrence of A. grandis, we used data based on 4 years of cucurbit fruit collections from all mesoregions of the state of São Paulo. Our results show evidence that A. grandis is constrained by a minimum air temperature above 12 °C, low (<20 °C) and high (>29 °C) maximum air temperature, and by low rainfall and relative humidity, occurring at altitudes from 520 to 780 m. More importantly, A. grandis was not collected in central to western São Paulo, where sandy soil and low soil water availability predominate and the climate is hot and dry. Our findings suggest that soil texture and moisture may be limiting factors for pupal survivorship of A. grandis, and consequently edaphic characteristics should be taken into account in studies on its geographical distribution. Based on our results, central to western São Paulo state can potentially be classified as an area of low pest prevalence. Moreover, in countries where cucurbit species are cultivated in such conditions, it is not likely that A. grandis could become established. [ABSTRACT FROM AUTHOR]

Brazil is the country with the highest social inequality in South America. This socioeconomic disparity reflects not only on the families' income but also on their spatial localization in the city, as well as on the urban design. These urban environments can alter the urban microclimate, and consequently, interfere in dwellers' thermal comfort. This research investigated the relationship between socio-spatial inequalities and thermal comfort in two different Local Climate Zones (LCZ) using a combination of measurement and modeling. Air temperature (Tair) was obtained by on-site measurements in compact high-rise (LCZ1) and compact low-rise buildings (LCZ3) and Mean radiant temperature (Tmrt) was simulated using SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG). The results indicated that in LCZ1 seafront-localized buildings, in which residents have a higher income, the temperature remains in a range classified as comfortable, mainly due to shading and sea breeze. On the other hand, LCZ3, located in the periphery of the city, in which the low-income population is concentrated and is marked by a precariousness urban environment, presented a higher air temperature and Tmrt values, exposing the dwellers to heat stress throughout the year, especially during the summer season. These observations suggested that public and private actions tend to promote better urban designs in areas with a higher concentration of income. Public reforms aimed at improving the urban environment and promoting thermal comfort should be a priority for the warmest LCZ, where the poorest residents live. Public agents should rethink the distribution of environmental resources to promote equitable urban spaces. [ABSTRACT FROM AUTHOR]

Bird vocal activity is affected by endogenous and exogenous factors. Owl surveys are mainly based on the detection of nocturnal calls, and therefore, the impact of exogenous factors on owls' vocal activity may have consequences in conservation planning and behavioural studies. However, our current knowledge about the impact of climatic factors and the moon phase on owl calling behaviour is very limited, especially in the Neotropics. We used autonomous recording units to evaluate the effect of air temperature, rainfall, relative air humidity, and percent of the moon illuminated on the vocal occurrence (active/inactive) of the Ferruginous pygmy-owl (Glaucidium brasilianum) over three consecutive moon cycles in the Brazilian Pantanal. Vocal activity was positively associated with the percent of the moon illuminated, with 75% of the nights on which the species was vocally active having a moon illumination percentage higher than 77%. The vocal activity of the species was negatively associated with the nocturnal air temperature, with more vocal activity observed on cooler nights. Relative air humidity and daily rainfall were not associated with the vocal activity of the Ferruginous pygmy-owl. Our study improves the knowledge about the impact of exogenous factors on the calling behaviour of Neotropical owls. We conclude that future surveys aiming to detect the Ferruginous pygmy-owl should be carried out on nights with a high percent of moon illumination (>75%) and nights with low average temperature (< 18 °C). [ABSTRACT FROM AUTHOR]

Improvement of planting season and crop growth time, considering climatic and soil needs of plants, is important to increase cassava (Manihot esculenta) production in Midwestern Brazil. Thus, we sought to develop an agricultural zoning for cassava cultivation in the Midwest of Brazil in different climate change scenarios. Mean air temperature and precipitation data from localities of the Midwest of Brazil were obtained from the Brazilian National Institute of Meteorology (INMET). Clay (%) data from localities of the Midwest of Brazil were obtained from SoilGrids. Regions where the air temperature was within the range from 20 to 27 °C were considered climatically favorable for commercial exploitation of cassava, in addition to precipitation between 1000 and 1500 mm year−1, and clay content was less than ≤ 35%. Moreover, regions with air temperature below 16 °C and above 38 °C, precipitation below 1000 mm and above 1500 mm year−1, and clay content > 35% were considered unsuitable for cassava cultivation. Raster or matrix images, corresponding to mean annual air temperature, annual precipitation, and clay (soil), were superimposed to create cassava suitability classes, according to crop requirements. The climate change scenarios were established by changing the air temperature (°C) and rainfall (mm). The air temperature was increased by 1.5, 3.0, 4.5, and 6.0 °C as adopted by Pirttioja et al. (Clim Res 65:87–105, 2015). We changed in precipitation − 30, − 15, + 15, and 30% according to the future projections simulated by the IPCC (2014). Maps were made using geographic information systems. In the states of Mato Grosso do Sul, Mato Grosso, and Goiás, mean precipitation was around 1200 to 4000 mm year−1. Northern Mato Grosso showed the highest annual precipitation, with values above 3500 mm. A large extension of the Midwest region of Brazil is climatically and soil favorable for cassava. The Midwest is a region with high rainfall, so we recommend planting in well-drained soils to avoid phytosanitary problems. Producers taking this care can plant cassava in 86.6% of the territory. The climate change scenarios demonstrated different Agriculture zonings for cassava in the Midwest of Brazil. With the increase in air temperature, greater marginal classes occurred, but cassava is resistant to this condition. But, this increase in temperature can reduce the cycle and consequently reduce production. [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]

Background: Extreme ambient temperatures and air quality have been directly associated with various human diseases from several studies around the world. However, few analyses involving the association of these environmental circumstances with mental and behavioral disorders (MBD) have been carried out, especially in developing countries such as Brazil.Methods: A time series study was carried out to explore the associations between daily air pollutants (SO2, NO2, O3, and PM10) concentrations and meteorological variables (temperature and relative humidity) on hospital admissions for mental and behavioral disorders for Curitiba, Brazil. Daily hospital admissions from 2010 to 2016 were analyzed by a semi-parametric generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM).Results: Significant associations between environmental conditions (10 μg/m3 increase in air pollutants and temperature °C) and hospitalizations by MBD were found. Air temperature was the environmental variable with the highest relative risk (RR) at 0-day lag for all ages and sexes analyzed, with RR values of 1.0182 (95% CI: 1.0009-1.0357) for men, and 1.0407 (95% CI: 1.0230-1.0587) for women. Ozone exposure was a risk for all women groups, being higher for the young group, with a RR of 1.0319 (95% CI: 1.0165-1.0483). Elderly from both sexes were more susceptible to temperature variability, with a RR of 1.0651 (95% CI: 1.0213-1.1117) for women, and 1.0215 (95% CI: 1.0195-1.0716) for men.Conclusions: This study suggests that temperatures above and below the thermal comfort threshold, in addition to high concentrations of air pollutants, present significant risks on hospitalizations by MBD; besides, there are physiological and age differences resulting from the effect of this exposure. [ABSTRACT FROM AUTHOR]

We grew leaves of Montrichardia arborescens in four microcosm chambers with different temperatures and CO2 concentrations simulating the scenarios of expected climate change. These leaves were used to feed shredders (Phylloicus) and to assess the effects of changes in leaf quality on their consumption. We also evaluated the effect of detritus conditioning by microorganisms on leaf consumption. We hypothesized that leaves of plants grown under different environmental conditions could offer substrata of different qualities to microorganisms colonizing them, and, consequently the shredder consumption rate would differ according to leaf conditioning. The microcosm chambers for plant growth simulated three different combined air temperature and CO2 scenarios, relative to the real-time (control) current conditions in Manaus-Brazil. The leaf consumption experiment was performed only in the control chamber. Specific leaf area was positively affected by predicted climate change, while tannins were detected only in leaves of plants grown in chambers simulating a changed climate. Other leaf detritus parameters were similar in all chambers. Shredders showed higher consumption rates in leaves developed under mild and intermediate conditions in relation to control. Shredder consumption was similar in conditioned and unconditioned treatments. Thus, shredder consumption was influenced more by the intrinsic quality of leaves than by microorganism conditioning, but we were not able to show effects of climate change on leaf quality that could explain differences in shredder consumption. [ABSTRACT FROM AUTHOR]

Urban climate studies can provide information necessary for the improvement of conditions of thermal comfort for people in cities in the Tropics. This paper presents thermal bioclimate analysis of a case study in Campinas, Brazil, using air temperature (T), mean radiant temperature (T), and Physiologically Equivalent Temperature (PET), which can be used as assessment factors for urban and architectural planning in tropical climate. The meteorological data air temperature, relative humidity, wind speed, and solar radiation for the period 2003 to 2010 were used to calculate T and PET using the RayMan Pro model. Simulations of shade and wind speed variations were performed to quantify changes in thermal bioclimate due to modifications in urban morphology. The results show that solar radiation and wind speed not only influence air temperature, but also more extensive thermal comfort and heat stress as well. Furthermore, the simulations of the variation of wind speed and shade conditions demonstrate that shade can improve thermal comfort situations in terms of PET above 35 °C. The improvement of outdoor thermal comfort is an important step in achieving sustainability of urban spaces and configurations. These results are valuable for architects, planners, and urban designers for the description of conditions and the development of possibilities for improving microclimatic conditions based on urban design and configurations. [ABSTRACT FROM AUTHOR]

A mangrove is a transitional coastal ecosystem between marine and terrestrial environments that is characterized by salinity and constant tidal flooding. Mangroves contain plant communities that are adapted to several physical constraints, including the climate. The purpose of this study was to analyze the variations in climatic attributes (air temperature, relative air humidity, global solar radiation, wind, and rainfall) in the mangroves located in the municipality of Iguape, on the southern coast of the state of São Paulo, Brazil. In addition, it was determined whether the existing variation is related to the presence of the canopy environment. A microclimate tower was installed with two weather stations to obtain an analysis of the variation of the climatic attributes above and below the canopy. The results indicate that global solar radiation had an average transmissivity of 26.8%. The air temperature at 10 m was higher than that at the sensor at 2 m. The average rainfall interception for the mangrove environment was 19.6%. Both the maximum gust and average wind speed decreased by approximately 63.7% at 2 m. The mangrove canopy was found to be an important control on the variation of climatic attributes. On a microclimatic scale, the climate attributes had a direct influence on the spatial distribution of vegetation. Additionally, characteristics of the canopy are the main control for this variation, especially for the distribution of rainfall and the amount of solar radiation below the canopy, which influence the distribution of plant species in the environment. [ABSTRACT FROM AUTHOR]

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Processes occurring in the tropical upper troposphere (UT), the Tropical Transition Layer (TTL), and the lower stratosphere (LS) are of importance for the global climate, for stratospheric dynamics and air chemistry, and for their influence on the global distribution of water vapour, trace gases and aerosols. In this contribution we present aerosol and trace gas (in-situ) measurements from the tropical UT/LS over Southern Brazil, Northern Australia, and West Africa. The instruments were operated on board of the Russian high altitude research aircraft M-55 "Geophysica" and the DLR Falcon-20 during the campaigns TROCCINOX (Araçatuba, Brazil, February 2005), SCOUT-O3 (Darwin, Australia, December 2005), and SCOUT-AMMA (Ouagadougou, Burkina Faso, August 2006). The data cover submicron particle number densities and volatility from the COndensation PArticle counting System (COPAS), as well as relevant trace gases like N2O, ozone, and CO. We use these trace gas measurements to place the aerosol data into a broader atmospheric context. Also a juxtaposition of the submicron particle data with previous measurements over Costa Rica and other tropical locations between 1999 and 2007 (NASA DC-8 and NASA WB-57F) is provided. The submicron particle number densities, as a function of altitude, were found to be remarkably constant in the tropical UT/LS altitude band for the two decades after 1987. Thus, a parameterisation suitable for models can be extracted from these measurements. Compared to the average levels in the period between 1987 and 2007 a slight increase of particle abundances was found for 2005/2006 at altitudes with potential temperatures, Θ, above 430 K. The origins of this increase are unknown except for increases measured during SCOUT-AMMA. Here the eruption of the Soufrière Hills volcano in the Caribbean caused elevated particle mixing ratios. The vertical profiles from Northern hemispheric mid-latitudes between 1999 and 2006 also are compact enough to derive a parameterisation. The tropical profiles all show a broad maximum of particle mixing ratios (between Θ≈340K and 390 K) which extends from below the TTL to above the thermal tropopause. Thus these particles are a "reservoir" for vertical transport into the stratosphere. The ratio of nonvolatile particle number density to total particle number density was also measured by COPAS. The vertical profiles of this ratio have a maximum of 50% above 370K over Australia and West Africa and a pronounced minimum directly below. Without detailed chemical composition measurements a reason for the increase of non-volatile particle fractions cannot yet be given. However, half of the particles from the tropical "reservoir" contain compounds other than sulphuric acid and water. Correlations of the measured aerosol mixing ratios with N2O and ozone exhibit compact relationships for the tropical data from SCOUT-AMMA, TROCCINOX, and SCOUT-O3. Correlations with CO are more scattered probably because of the connection to different pollution source regions. We provide additional data from the long distance transfer flights to the campaign sites in Brazil, Australia, and West-Africa. These were executed during a time window of 17 months within a period of relative volcanic quiescence. Thus the data represent a "snapshot picture" documenting the status of a significant part of the global UT/LS fine aerosol at low concentration levels 15 years after the last major (i.e., the 1991 Mount Pinatubo) eruption. The corresponding latitudinal distributions of the measured particle number densities are presented in this paper to provide data of the UT/LS background aerosol for modelling purposes. [ABSTRACT FROM AUTHOR]

The objective was to evaluate vaginal temperature as a thermoregulatory response of Nellore heifers under different microclimatic conditions. The study was conducted during one year in an experimental area located at 54°37′W, 20°27′S, and 530 m of altitude in Brazil. Twenty-four Nellore females were reared in integrated crop-livestock-forestry systems with different shading patterns. The randomized complete block experimental design was utilized with a sub subdivided plots scheme, with plot corresponding to the production systems, the subplot to the season of the year, and the sub subplot, the hours of the day. To characterize the microclimate, data regarding air and black globe temperatures, and air relative humidity were collected and from them, temperature-humidity index was calculated. Vaginal temperature was obtained by using a bottom-type temperature logger (i-button) attached to an adapted intravaginal device. The black-globe temperature explained the variation on vaginal temperature. Increases on vaginal temperature were only observed, on average, two hours after the increase of black-globe temperature. The microclimatic conditions found in the systems, resulting from the various tree densities, modify the vaginal temperature in different degrees, demonstrating that the shading effect is not always accompanied by improvements in thermal comfort. The system with intermediate density showed a better microclimatic condition and, consequently, a lower increase in vaginal temperature. The interaction between air temperature, humidity and solar radiation resulted in adverse environmental conditions, however, Nellore heifers showed good adaptation to the environment. In conclusion, vaginal temperature is a good indicator to evaluate the thermoregulatory response in Nellore heifers. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Herpetology is the property of Society for the Study of Amphibians & Reptiles 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.)

Sunflower is a species that is sensitive to local climate conditions. However, studies that use artificial neural networks (ANNs) to evaluate this influence and create tools such as agricultural zoning of climate risk (ZARC) have not been conducted for this species. Due to the importance of sunflower as a human food source and for biodiesel production, and also the necessity of conducting research to evaluate the suitability of this oleaginous species under different climatic conditions. Thus, we seek to construct a ZARC for sunflower in Brazil simulating sowing on different dates and using meteorological elements spatialized by ANNs. Climate data were used: air temperature (T), rainfall (P), relative air humidity (UR), solar radiation (MJ_m−2_d−1) and wind velocity (U2). Climatic regions considered suitable for the cultivation of sunflower had average annual values for T between 20 and 28°C, P between 500 and 1.500 mm per cycle, and soil water deficit (DEF) below 140 mm per cycle. A neural network is an efficient tool that can be used in spatialization of climate variables quickly and accurately. Sunflower sowing in the spring and summer are the ones that provide the largest suitable areas in southeastern Brazil, with 58.13 and 64.36% of suitable areas, respectively. [ABSTRACT FROM AUTHOR]

During the negotiations of the Kyoto Protocol the delegation of Brazil presented an approach for distributing the burden of emissions reductions among the Parties based on the effect of their cumulative historical emissions on the global-average near-surface temperature. The Letter to the Parties does not limit the emissions to be considered to be only greenhouse gas (GHG) emissions. Thus, in this paper we explore the importance of anthropogenic SOx emissions that are converted to sulfate aerosol in the atmosphere, together with the cumulative greenhouse gas emissions, in attributing historical temperature change. We use historical emissions and our simple climate model to estimate the relative contributions to global warming of the regional emissions by four Parties: OECD90, Africa and Latin America, Asia, and Eastern Europe and the Former Soviet Union. Our results show that for most Parties the large warming contributed by their GHG emissions is largely offset by the correspondingly large cooling by their SOx emissions. Thus, OECD90 has become the dominant contributor to recent global warming following its large reduction in SOx emissions after 1980. [ABSTRACT FROM AUTHOR]

We investigate whether the recently observed trends in daily maximum and minimum near-surface air temperature (Tmax and Tmin, respectively) over South America (SA) are consistent with the simulated response of Tmin and Tmax to anthropogenic forcing. Results indicate that the recently observed warming in the dry seasons is well beyond the range of natural (internal) variability. In the wet season the natural modes of variability explain a substantial portion of Tmin and Tmax variability. We demonstrate that the large-scale component of greenhouse gas (GHG) forcing is detectable in dry-seasonal warming. However, none of the global and regional climate change projections reproduce the observed warming of up to 0.6 K/Decade in Tmax in 1983-2012 over northern SA during the austral spring (SON). Thus, besides the global manifestation of GHG forcing, other external drivers have an imprint. Using aerosols-only forcing simulations, our results provide evidence that anthropogenic aerosols also have a detectable influence in SON and that the indirect effect of aerosols on cloud’s lifetime is more compatible with the observed record. In addition, there is an increasing trend in the observed incoming solar radiation over northern SA in SON, which is larger than expected from natural (internal) variability alone. We further show that in the dry seasons the spread of projected trends based on the RCP4.5 scenario derived from 30 CMIP5 models encompasses the observed area-averaged trends in Tmin and Tmax. This may imply that the observed excessive warming in the dry seasons serve as an illustration of plausible future expected change in the region. [ABSTRACT FROM AUTHOR]

The main objective of this research was to analyze the climate data for the host cities of the soccer World Cup held in Brazil in June and July 2014. A great deal of criticism was expressed about the Brazilian climate in the national and international press and media in the run-up to the competition, suggesting that the air temperature and relative air humidity would be the main adversaries of the soccer teams, especially those from Europe, during the competition. An analysis of the weather was done at the places and times of each of the 64 matches held. A human thermal comfort index was calculated (discomfort index (DI)) for each of the matches in order to discover the real climatic conditions in the host cities during the 2014 World Cup and their potential influence on the teams and human comfort in general. During the 2014 World Cup, only two matches were played at temperatures above 30 °C, representing a negligible percentage of the total number of matches. The air temperature for over half the matches (53%) was 20-25 °C. The results showed the air temperature and relative humidity data analyzed here both individually and in the form of an index indicate that the World Cup held in Brazil in 2014 did not put any of the players at risk due to extreme heat. [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]

This study investigates the effects of Lake Sobradinho, a large reservoir in Northeastern Brazil, on the local near-surface atmospheric and boundary layer conditions. For this purpose, simulations with the regional climate model COSMO-CLM are compared for two different scenarios: (1) with the lake being replaced by the average normal native vegetation cover and (2) with the lake as it exists today, for two different two-month periods reflecting average and very dry conditions, respectively. The performance of the simulation is evaluated against data from surface meteorological stations as well as satellite data in order to ensure the model's ability to capture atmospheric conditions in the vicinity of Lake Sobradinho. The obtained results demonstrate that the lake affects the near-surface air temperature of the surrounding area as well as its humidity and wind patterns. Specifically, Lake Sobradinho cools down the air during the day and warms it up during the night by up to several °C depending on the large-scale meteorological conditions. Moreover, the humidity is significantly increased as a result of the lake's presence and causes a lake breeze. The observed effects on humidity and air temperature also extend over areas relatively far away from the lake. [ABSTRACT FROM AUTHOR]

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The objective of this work was to develop and evaluate agrometeorological models to simulate the production of Guineagrass. For this purpose, we used forage yield from 54 growing periods between December 2004-January 2007 and April 2010-March 2012 in irrigated and non-irrigated pastures in São Carlos, São Paulo state, Brazil (latitude 21°57′42″ S, longitude 47°50′28″ W and altitude 860 m). Initially we performed linear regressions between the agrometeorological variables and the average dry matter accumulation rate for irrigated conditions. Then we determined the effect of soil water availability on the relative forage yield considering irrigated and non-irrigated pastures, by means of segmented linear regression among water balance and relative production variables (dry matter accumulation rates with and without irrigation). The models generated were evaluated with independent data related to 21 growing periods without irrigation in the same location, from eight growing periods in 2000 and 13 growing periods between December 2004-January 2007 and April 2010-March 2012. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, minimum temperature and potential evapotranspiration or degreedays) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on minimum temperature corrected by relative soil water storage, determined by the ratio between the actual soil water storage and the soil water holding capacity.irrigation in the same location, in 2000, 2010 and 2011. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, potential evapotranspiration or degree-days) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on degree-days corrected by the water deficit factor. [ABSTRACT FROM AUTHOR]

Air temperature is one of the main weather variables influencing agriculture around the world. Its availability, however, is a concern, mainly in Brazil where the weather stations are more concentrated on the coastal regions of the country. Therefore, the present study had as an objective to develop models for estimating monthly and annual mean air temperature for the Brazilian territory using multiple regression and geographic information system techniques. Temperature data from 2,400 stations distributed across the Brazilian territory were used, 1,800 to develop the equations and 600 for validating them, as well as their geographical coordinates and altitude as independent variables for the models. A total of 39 models were developed, relating the dependent variables maximum, mean, and minimum air temperatures (monthly and annual) to the independent variables latitude, longitude, altitude, and their combinations. All regression models were statistically significant ( α ≤ 0.01). The monthly and annual temperature models presented determination coefficients between 0.54 and 0.96. We obtained an overall spatial correlation higher than 0.9 between the models proposed and the 16 major models already published for some Brazilian regions, considering a total of 3.67 × 10 pixels evaluated. Our national temperature models are recommended to predict air temperature in all Brazilian territories. [ABSTRACT FROM AUTHOR]

This study is aimed at creating a stochastic model, named Brazilian Climate and Health Model (BCHM), through Poisson regression, in order to predict the occurrence of hospital respiratory admissions (for children under thirteen years of age) as a function of air pollutants, meteorological variables, and thermal comfort indices (effective temperatures, ET). The data used in this study were obtained from the city of S˜ao Paulo, Brazil, between 1997 and 2000. The respiratory tract diseases were divided into three categories: URI (Upper Respiratory tract diseases), LRI (Lower Respiratory tract diseases), and IP (Influenza and Pneumonia). The overall results of URI, LRI, and IP show clear correlation with SO2 and CO, PM10 and O3, and PM10, respectively, and the ETw4 (Effective Temperature) for all the three disease groups. It is extremely important to warn the government of the most populated city in Brazil about the outcome of this study, providing it with valuable information in order to help it better manage its resources on behalf of the whole population of the city of Sao Paulo, especially those with low incomes. [ABSTRACT FROM AUTHOR]