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The agricultural zoning of climate risk (AZCR) is a fundamental tool for agricultural activities, as it identifies regions and times of lower climatic risk for planting and sowing crops. An AZCR representative of large areas requires a network of meteorological stations with dense spatial distribution, routine, and accurate observations. In Brazil, there is a good spatial distribution of rain gauges, but there is a scarcity in the spatial distribution of meteorological stations necessary to conduct an AZCR. One way to overcome the lack of data observed in situ is to use reanalysis data. However, it is necessary to show that it is possible to perform a reliable AZCR using it. Therefore, the objective of this research is to elaborate an AZCR for corn in the state of Bahia using reanalysis data and quantifying its viability. The ERA5-Land reanalysis database was chosen. When performing the validation of the ERA5-Land reanalysis data, it was verified that rainfall was the only meteorological variable needed for an AZCR that did not present seasonal and interannual values and variability similar to those already observed. Therefore, it was decided to validate the rainfall data from the CPC/NOAA Precipitation Project. With data from the ERA5-Land and CPC/NOAA Precipitation Project reanalysis validated, the AZCR for corn was performed in the state of Bahia, leading to the conclusion that it is possible to develop a reliable and robust AZCR with reanalysis data. [ABSTRACT FROM AUTHOR]

Climate change is a pernicious and irrefutable reality. The objective of this work was to analyze trends in extreme temperature indices in Aguascalientes. With RClimdex 1.0 and data on daily maximum (Tmax) and minimum temperature (Tmin), 16 temperature indices were calculated. The trend in indices was determined with the non-parametric Mann-Kendall test (p ≤ 0.05), while the rate of change was obtained with Theil-Sen's trend estimator. Significant positive trends were observed in 72 time series of indices associated with Tmax and in 39 time series of indices associated with Tmin. Significant negative trends were observed in 22 time series of indices associated with Tmax, and in 45 time series of indices associated with Tmin. In some regions of Aguascalientes, diurnal warming is occurring; in others, warmer or less cold nights prevail. The changes in extreme temperature indices might have severe implications in the use of irrigation water, cause physiological stress in crops, promote respiratory and cardiac diseases, and improve the reproduction cycles and populations of insects. Also, the fruit production, such as guava, could be affected under the reduction of minimum temperature, and the increase in warm days where other fruit trees are cultivated can intensify the use of chemical compensators of cold. These results are of significance for long-term economic planning and design of strategies of adaptation/mitigation to climate change. In Aguascalientes, the changes observed in extreme temperature indices could be due to climate change of a bigger scale, either regional or at the watershed level. [ABSTRACT FROM AUTHOR]

A climate system is characterized to be a complex non-linear system. In order to describe the complex characteristics of precipitation series in Paraíba State, Brazil, we aim the use of sample entropy, a kind of entropy-based algorithm, to evaluate the complexity of precipitation series. Sixty-nine meteorological stations are distributed over four macroregions: Zona da Mata, Agreste, Borborema, and Sertão. The results of the analysis show that intricacies of monthly average precipitation have differences in the macroregions. Sample entropy is able to reflect the dynamic change of precipitation series providing a new way to investigate complexity of hydrological series. The complexity exhibits areal variation of local water resource systems which can influence the basis for utilizing and developing resources in dry areas. [ABSTRACT FROM AUTHOR]