Evaluation and incorporation of the presence of climate change in the probability of occurrence of extreme weather

• Grant number: 13/21914-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: March 01, 2014
• End date: February 29, 2016
• Field of knowledge: Agronomical Sciences - Agronomy - Agricultural Meteorology
• Principal Investigator: Gabriel Constantino Blain
• Grantee: Monica Cristina Meschiatti
• Host Institution: Instituto Agronômico (IAC). Agência Paulista de Tecnologia dos Agronegócios (APTA). Secretaria de Agricultura e Abastecimento (São Paulo - Estado). Campinas , SP, Brazil

Abstract

The increase of the magnitude and the frequency of occurrence of extreme weather events due to the current climate change is of major concern. In addition, it is well known that investigating climate trends at regional scale is a fundamental step for understanding the potential agricultural impacts of the Global warming. Thus, it becomes evident the need to evaluate the presence of climate trends in the probability of occurrence of weather events that may cause damage to the agricultural production. The aim of this study is to apply the so-called non stationary general extreme value distributions (GEV) in order to (i) detect the presence of climate trends in meteorological series of the State of São Paulo and to (ii) incorporate these possible trends on the assessment of the probability of occurrence of extreme meteorological events. It will be used daily rainfall (Pre) and maximum (Tmax) and minimum (Tmin) air temperature data obtained from X weather stations of the State of São Paulo, Brazil (1951-2013). The fit of the data to the GEV distribution will be assessed by using the Lilliefors and Anderson - Darling tests, quantil-quantil plots and the Akaike's information criterion. The likelihood ratio test will be applied to evaluate the presence of temporal trends in the parameters of the GEV distributions. This latter test will also allow us to verify if (and how) the probabilistic structure of the Pre, Tmax, Tmin series significantly change over the time. In other words, besides providing statistical evidences regarding the presence of climate change in the State of São Paulo, this study will be capable of describing and hence quantifying the influence of such changes on the frequency of occurrence of extreme weather events (Pre, Tmax and Tmin) observed in the 8 locations.