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The present paper aims to compute climatological zones apt for the cultivation of pitaya based on trends in the occurrence of climate change events from the IPCC (Intergovernmental Panels on Climate Change) in Brazil. We used temperature and precipitation data from 4942 cities collected on the NASA/POWER platform (National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources) from 1990 to 2020 to elaborate on the current scenario. The climate change scenarios were obtained using the CHELSA platform (Climatologies at high resolution for the earth's land surface areas) and corresponded to the periods 2041–2060 and 2061–2080 associated with four IPCC climate change scenarios. The spatialization of the data occurred according to the bioclimatic classes designed to meet the thermal and water needs of the crop. In the current scenario, class B5 has a predominance of 37.07% of the country, characterizing the Midwest, Southeast, and Northeast regions, as well as the state of Paraná, as suitable for the cultivation of pitaya. Projections of temperature increase and reduction of accumulated rainfall were found throughout Brazil, but with greater impact in the North and Northeast regions, which had the greatest reduction of areas suitable for the cultivation of pitaya with a greater predominance of classes B8 and B9. In the South and Southeast regions, class B5 makes up a large part of the areas that remained suitable for the production of this fruit until 2080. The results suggest that climate change does not benefit the cultivation of pitaya in some regions of Brazil because the dimensions of the areas suitable for economic production are restricted. [ABSTRACT FROM AUTHOR]

The intermediate disturbance hypothesis (IDH) has been thoroughly investigated, but much controversy has been found for supporting its assumptions, which rely largely on the nature of the disturbance, spatial scale, and biological predictors tested. In this paper, richness of native and non-native species along a suite of Neotropical aquatic ecosystems across a broad latitudinal and geographical range was used to test the IDH predictions. An extensive literature survey was performed to compile native species richness and the occurrence of several taxonomic groups listed as non-native for twenty-four coastal rivers and bays evenly distributed into three climatic zones (tropical, transitional, and subtropical). The climatic gradient was confirmed by NMDS and PERMANOVA, but IDH predictions were only significantly supported for native and total species richness in the coastal bays. The distribution patterns of non-native marine species showed a linear instead unimodal pattern of increase with latitudinal climatic gradient, but the responses are complex and dependent of many non-exclusive factors, such as the sampling effort per ecosystem and the potential interference of other disturbance gradients that should be further addressed to unravel the role of IDH for non-native species distribution. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of pluviometric precipitation time series obtained from 45 data collection points, with daily rain measurements (in mm), from 45 counties within the nine climatic regions of the state of São Paulo, mostly for the period of 1950–1997. São Paulo State (Brazil) is situated between the inter-tropical climatic zone, dominated by tropical and equatorial masses, and the sub-tropical climatic zone controlled by tropical and polar air masses. Due to this location the State can be divided into three climatic zones: south-east and south-west, which are permanently humid, and north with a well defined dry period. Rescaled range analysis, or R/S analysis, has been used to investigate the scale properties of the time series. We found two clear values for the Hurst exponent, one for a period of 10 to 200 days (H1), and another for a period above 210 days (H2). The value of H1 lies between 0.6 to 0.7 for all climatic zones indicating characteristics of persistence. However, H2 is (i) close to 0.5 for the littoral area, showing random characteristics, (ii) close to 0.6 for mountain areas, indicating persistence characteristics, and (iii) close to 0.4 for the plane area, irrespective of whether the climate is dry or humid, and shows anti-persistence characteristics. [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]

• An innovative framework for energy benchmarking of buildings is proposed. • Entropy and cluster analysis reduced uncertainty in setting parameters of archetypes. • The machine learning technique used as a benchmarking tool showed high performance. • The benchmarking applied in actual buildings showed a high inefficiency ratio. Energy benchmarking of buildings has an important role in improving energy performance by establishing a reference for the energy efficiency of the building stock. The simulation of archetypes followed by a generalisation model has been widely used to obtain benchmarks. However, even though archetypes summarise the main features of the building stock, the uncertainties must be accounted for in the modelling process. Moreover, testing the response of the benchmarking model using the actual building stock data supports the reliability of the method. This paper aims to propose an innovative framework to reduce the uncertainty of archetypes for benchmarking buildings. A standard framework for data compiling is proposed and an assessment of the uncertainty of variables using entropy and cluster analysis allowed to obtain representative archetypes. An Artificial Neural Network (ANN) was used as a predictive tool, and it was applied to benchmark a sample of actual buildings. Also, the simulation outcomes were used to determine energy end-uses according to the climatic zones. The framework proposition is presented alongside with a practical application. The result is an unprecedented benchmarking model: the archetype considers more variation in parameters of the building stock with higher uncertainties. Additionally, the modelling process showed to be robust for combining different datasets, and the ANN achieved high-performance metrics. Conclusion indicates the potential of using the framework for other typologies. Moreover, the framework demonstration is used for a school stock in Brazil, showing a trend to the inefficiency while a specific case study was explored, showing the potential of the method to find faults in the building energy use. [ABSTRACT FROM AUTHOR]

Southern Brazil has recently been the subject of many major natural hazards from weather and climatic origin, including violent floods in 2016 caused by very heavy rains. It has also experienced episodes of droughts and heat waves in recent years. The state of Paraná, located at the climatic transition zone, has densely populated urban areas, vast cultivation areas, and hydro-electric reservoirs (more than 20), so those extreme events are letting local populations vulnerable to the vagaries of the climate and their impacts on community, infrastructure, and ecosystem. This study analyzes climatic variability and trends of about ten climatic indices (with RClimDex), calculated by using daily thermal data of ten stations spread mainly in two geographic regions of Paraná. The Mann-Kendall and Pettitt tests were applied for trends analysis and determine the presence of breakpoints in the time series (1971–2014). Our results showed that for the various thermal indices, there is a reduction of the cold days on all the stations, indicating a more pronounced increase of the indices based on the maximum temperatures (TX), especially in the north. On the other hand, the indexes based on minimum temperatures (TN) show a more modest and partial increase, varying accordingly to the location of the stations. Regionally, the trends calculated were similar, that is, North region presents a more expressive increase of the indices of heat whereas in the east predominates a reduction. [ABSTRACT FROM AUTHOR]

Climate regulates the fern phenology and climatic triggers influence plants from tropical and subtropical regions differently. Ferns depend on climate to regulate their life cycle, because they do not require animal interaction to reproduce. Through the pioneering study of the phenology of Araucaria forest understory in subtropical climate of Brazil, our main aims were (i) to verify which climatic variables influenced the phenological pattern of the community, (ii) to identify the differences in seasonality of ferns in distinct climatic zones of Brazil, and (iii) to compare the phenological pattern of ferns growing in other subtropical regions of the world. In an Araucaria forest fragment, we monitored the phenology of the fern community (leaf production, leaf senescence, and sporangium formation) over 2 years. At the same time, we collected photoperiod, temperature, and precipitation data. Ferns phenology was classified as continuous, discontinuous, regular, and irregular. Our results showed photoperiod and mean temperature as the best predictors for phenology. The reproductive event was seasonal, and the fern community presented themselves as continuous, irregular (activity index), and regular (intensity index) phenophases. Unlike ferns from tropical regions that generally regulate themselves by the rainfall, some ferns in a non-seasonal environment have seasonal behavior in their phenophases due to the greater amplitude of photoperiod and temperature. The community showed the same pattern of leaf production observed in populations of other subtropical regions in the world. This behavior represented the biological response of the vegetation dynamics in relation to the climatic variability of subtropical environment. [ABSTRACT FROM AUTHOR]

Clouds persistently engulf many tropical mountains at elevations cool enough for clouds to form, creating isolated areas with frequent fog and mist. Under these isolated conditions, thousands of unique species have evolved in what are known as tropical montane cloud forests (TMCF) and páramo. Páramo comprises a set of alpine ecosystems that occur above TMCF from about 11° N to 9° S along the Americas continental divide. TMCF occur on all continents and island chains with tropical climates and mountains and are increasingly threatened by climate and land-use change. Climate change could impact a primary feature distinguishing these ecosystems, cloud immersion. But where and in what direction cloud immersion of TMCF and páramo will change with climate are fundamental unknowns. Prior studies at a few TMCF sites suggest that cloud immersion will increase in some places while declining in others. Other unknowns include the extent of deforestation in protected and unprotected cloud forest climatic zones, and deforestation extent compared with projected climate change. Here we use a new empirical approach combining relative humidity, frost, and novel application of maximum watershed elevation to project change in TMCF and páramo for Representative greenhouse gas emissions Concentration Pathways (RCPs) 4.5 and 8.5. Results suggest that in <25–45 yr, 70–86% of páramo will dry or be subject to tree invasion, and cloud immersion declines will shrink or dry 57–80% of Neotropical TMCF, including 100% of TMCF across Mexico, Central America, the Caribbean, much of Northern South America, and parts of Southeast Brazil. These estimates rise to 86% of Neotropical TMCF and 98% of páramo in <45–65 yr if greenhouse gas emissions continue rising throughout the 21st century. We also find that TMCF zones are largely forested, but some of the most deforested areas will undergo the least climate change. We project that cloud immersion will increase for only about 1% of all TMCF and in only a few places. Declines in cloud immersion dominate TMCF change across the Neotropics. [ABSTRACT FROM AUTHOR]

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The knowledge of the climatic conditions of a region is crucial for its agricultural development. It is also extremely important for understanding the fact that certain cultures have to develop under prevailing temperature and humidity conditions and assist in the adoption of a suitable irrigation technique, as well as its management and operationalization. The Köppen system of climate classification is widely used for the identification of homogeneous climate zones as it considers only rainfall and temperature as the meteorological elements for classification. For this study, we used climatic databases of rainfall and temperature in a raster format, with a spatial resolution of 30″ of arc (an approximate area of 0.86 km pixel), from 1961 to 1990. Through geoprocessing techniques, we obtained a map of climatic classification for the state of Minas Gerais. We found that the state has the following three major climatic groups: A, B and C, which correspond to tropical rainy, dry and warm temperate climates, respectively. The climate classes obtained were Aw, Am, BSh, Cwa and Cwb, with Aw, Cwa and Cwb classes occupying 99.89% of the territorial area of the state. The validation of the results showed a satisfactory agreement, with 93.75% reliability. [ABSTRACT FROM AUTHOR]