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A crucial aspect analysed during the last years, aiming to improve sugarcane production, is the impact of climate change on sugarcane productivity. One of the strategies to mitigate climate change's impact on sugarcane yield is the development of new varieties known to positively affect crop production. This paper analysed how climate change impacts sugarcane production regarding the different planted varieties. Data regarding sugarcane harvest were collected from a cooperative in the south of Goiás state—Brazil, the second biggest national sugarcane producer. Results indicate that climate impact on sugarcane yield is irrelevant when controlling for different varieties. Considering the results presented in this work, the Brazilian government should keep the incentives for the development of new sugarcane varieties and, at the same time, spur sugarcane producers to use the new sugarcane varieties. The results imply that if the variety is correctly chosen, sugarcane can be produced without harming the environment, contributing to reaching SDG 15. Moreover, it is less probable that an adverse climatic event will destroy the planted area, preventing sugarcane producers from severe loss and contributing to achieving SDGs number 1 and 2. [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]

The traditional approach to characterize extreme rainfall events is based on using past observed data to fit a probability distribution, which is used to associate a certain probability of occurrence to a rainfall magnitude, under a stationary assumption. Observed series, however, may exhibit trends and abrupt changes, resulting from the natural hydro climatic variability and the climate change context, which are not usually considered in the stationary modelling procedure and which may affect the characterization of extreme events. In this paper, it was evaluated the presence of these temporal changes in rainfall series and their impact to estimate design quantiles, using rainfall data of 317 stations, located in São Paulo State, Brazil. The results showed that extreme rainfall events are changing in the state. Low-return period events (up to 10 years) are intensifying. Moderate- and high-return period events, on the other hand, did not present a clear spatial pattern. Trends and abrupt changes may significantly influence the estimation of design quantiles. The presence of the former in rainfall series exhibited more influence on low-return period events, showing, however, no clear relationship with high-return period design quantiles. The presence of the latter seems to influence the characterization process, affecting estimated quantiles of all evaluated return periods. Such findings highlight the need to consider the presence of trends and abrupt changes and their influence on design quantiles for a more reliable characterization. [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]

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]

Both global climate change and urbanization trends will demand adaptation measures in cities. Large agglomerations and impacts on landscape and natural environments due to city growth will require guided densification schemes in urban areas, particularly in developing countries. Human biometeorological indices such as the Universal Thermal Climate Index (UTCI) could guide this process, as they provide a clear account of expected effects on thermal sensation from a given change in outdoor settings. However, an earlier step should optimally include an adequacy test of suggested comfort and thermal stress ranges with calibration procedures based on surveys with the target population. This paper compares obtained thermal comfort ranges for three different locations in Brazil: Belo Horizonte, 20° S, Aw climate type; Curitiba, 25.5° S, Cfb subtropical climate, both locations in elevation (above 900 m a.s.l.); and Pelotas, at sea level, latitude 32° S, with a Cfa climate type. In each city, a set of outdoor comfort field campaigns has been carried out according to similar procedures, covering a wide range of climatic conditions over different seasons of the year. Obtained results indicate a variation of neutral temperatures up to 3 °C (UTCI units) as a possible latitude and local climate effect between the southern locations relative to the northernmost location. Low UTCI values were found in the two subtropical locations for the lower threshold of the thermal comfort band as compared with the original threshold. A possible explanation for that is a longer exposure to cold conditions as buildings are seldom provided with heating systems. [ABSTRACT FROM AUTHOR]