Impacts of climate change on drought: changes to drier conditions at the beginning of the crop growing season in southern Brazil

Pereira, Vânia Rosa; Blain, Gabriel Constantino; Ávila, Ana Maria Heuminski de; Pires, Regina Célia de Matos; Pinto, Hilton Silveira

doi:10.1590/1678-4499.2017007

Cited by 28 publications

(19 citation statements)

References 44 publications

(46 reference statements)

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“…Both precipitation and minimum air temperature data obtained from the weather station of Campinas presented significant increasing trends respectively at 5 and 10% significance level (Mann-Kendall test; Table 1). This result is consistent with previous studies describing signs of climate change in the location of Campinas (Blain 2011;Pereira et al 2018). For both climate models, such a trend could only…”

Section: Control Run (1961-2005) Trend and Stationary Testsupporting

confidence: 93%

“…The observational data (Campinas, São Paulo, Brazil; 22°54' S, 47°05' W and 669 m) were obtained from the Agronomic Institute of Campinas (IAC/APTA/SAA). This weather station has been selected because it presents no missing data and its consistency was evaluated in previous studies (Pereira et al 2018;Blain et al 2018). There were considered daily extremes of precipitation (Pre), minimum (Tmin) and maximum (Tmax) air temperature data.…”

Section: Methodsmentioning

confidence: 99%

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Using climate change models to assess the probability of weather extremes events: a local scale study based on the generalized extreme value distribution

et al. 2019

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Regional climate models (e.g. Eta) nested to global climate models (e.g. HadGEM2-ES and MIROC5) have been used to assess potential impacts of climate change at regional scales. This study used the generalized extreme value distribution (GEV) to evaluate the ability of two nested models (Eta-HadGEM2-ES and Eta-MIROC5) to assess the probability of daily extremes of air temperature and precipitation in the location of Campinas, state of São Paulo, Brazil. Within a control run (1961-2005), correction factors based on the GEV parameters have been proposed to approach the distributions generated from the models to those built from the weather station of Campinas. Both models were also used to estimate the probability of daily extremes of air temperature (maximum and minimum) and precipitation for the 2041-2070 period. Two concentration paths of greenhouse gases (RCP 4.5 and 8.5) have been considered.

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Section: Control Run (1961-2005) Trend and Stationary Testsupporting

confidence: 93%

Section: Methodsmentioning

confidence: 99%

Using climate change models to assess the probability of weather extremes events: a local scale study based on the generalized extreme value distribution

et al. 2019

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“…This significative decreasing in April can be related to the standardized precipitation index and standardized precipitation drought evapotranspiration Index/0 trend values studied by the Pereira et al . (). The cited authors evaluated the trends of both indexes on a monthly scale.…”

Section: Resultsmentioning

confidence: 97%

Stationary and non‐stationary detection of extreme precipitation events and trends of average precipitation from 1980 to 2010 in the Paraná River basin, Brazil

Xavier

Rudke

Fujita

et al. 2019

Intl Journal of Climatology

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The main objective of this study was to investigate the trends on average and extreme events in time series of daily precipitation from 1980 to 2010 in the Paraná River basin, Brazil. The nonparametric Mann–Kendall test was applied to detect monotonic trend in the precipitation series. The occurrence of extreme values was analysed based on three generalized extreme values (GEV) models: Model 1 (stationary), Model 2 (non‐stationary for location parameter), and Model 3 (non‐stationary for location and scale parameters). The GEV parameters were estimated by the Generalized Maximum Likelihood method (GMLE) and for the non‐stationary models, the parameters were estimated as linear functions of time. To choose the most suitable model, the maximum likelihood ratio test (D) was used. From the results observed at the monthly scale, it was possible to infer that the months with the highest probability of an extreme weather event occurrence are February (climates Aw and Cfa), July (Cfa and Cfb), and October (Aw, Cfa, and Cfb). Approximately 90% of the 1,112 stations presented no trend regarding the GEV parameters. The non‐stationarity showed by other stations (Models 2 and 3) might be associated with several factors, such as the alteration of land use due to the north expansion of the agricultural border of the Paraná River basin.

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“…SPEI was calculated using the timescales of 3, 12 and 48 months, and according to each timescale used, the calculated drought indexes received the appropriate designation of SPEI 3, SPEI 12 and SPEI 48. A timescale of 3 months was chosen to represent drought impacts on agriculture such as dryness during the growing season [17] and management practices [29]. The selection of a 12-month timescale aimed to reflect hydrological consequences of drought such as energy production decreasing [29].…”

Section: Methodsmentioning

confidence: 99%

“…They found very little influence of the El Niño Southern Oscillation in drought frequency, and no significant trends. More recently, Pereira et al [17] used SPI and SPEI to identify an increase in drought events over Sao Paulo state during the first months of rainy season, with serious consequences on agriculture.…”

Section: Introductionmentioning

confidence: 99%

Climatology and Trend of Severe Drought Events in the State of Sao Paulo, Brazil, during the 20th Century

et al. 2019

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

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Impacts of climate change on drought: changes to drier conditions at the beginning of the crop growing season in southern Brazil

Cited by 28 publications

References 44 publications

Using climate change models to assess the probability of weather extremes events: a local scale study based on the generalized extreme value distribution

Using climate change models to assess the probability of weather extremes events: a local scale study based on the generalized extreme value distribution

Stationary and non‐stationary detection of extreme precipitation events and trends of average precipitation from 1980 to 2010 in the Paraná River basin, Brazil

Climatology and Trend of Severe Drought Events in the State of Sao Paulo, Brazil, during the 20th Century

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