![sfgate precipitation totals sfgate precipitation totals](https://s.hdnux.com/photos/01/06/37/04/18477361/3/1200x0.jpg)
Daily rainfall indices suggest an increase of precipitation during the rainy days, but a reduction in the number of rainy days in both locations. In the Metropolitan Region of Baixada Santista, the precipitation increase is projected to all seasons, except JJA, when there is higher uncertainty. The projections show precipitation increase in the Metropolitan Region of Campinas during DJF for the near and distant future, while there are more uncertainties in the other seasons. Uncertainties are discussed based on the standard deviation among the model spread. Simulations and projections obtained from four integrations of the Regional Eta model are analyzed to investigate the model behavior during the period of 1961-1990 and the projections within the period of 2011-2100. Extreme precipitation impacts such as landslides and flooding with implications to vulnerability and adaptation are discussed for two regions of the state of Sao Paulo: the Metropolitan Region of Campinas and the Metropolitan Region of the Baixada Santista, located in southeastern South America. However, the frequency and intensity of precipitation extremes have increased in the globe following the global warming.
![sfgate precipitation totals sfgate precipitation totals](https://s.hdnux.com/photos/56/56/35/12248921/3/920x920.jpg)
Weather and climate extremes are part of the natural variability. This is one of the prediction and forecast figures that we obtained using VARMAX procedure. Results compared with GEV distribution fitting and better results are obtained by VARMAX model. The existence of autocorrelation and spatial dependence of stations are considered by vector ARIMA with exogenous variables model. Maximum precipitation amount is analysed by extreme value theory and multivariate time series. The obtained forecast results are promising in terms of accurately defining future precipitation amounts.
SFGATE PRECIPITATION TOTALS SERIES
It was discovered that the time series model that takes into account the autocorrelation structure of the series performed better than a probabilistic approach using the extreme value theory. We also considered a multivariate time series model with exogenous variables using the selected locations for a short‐term forecast of the maximum precipitation amount. We quantified the change in extreme precipitation for each location and derived estimates of return levels for monthly precipitation amounts. First, the generalized extreme value (GEV) distribution was fitted using the location parameter of the GEV distribution as a function of several explanatory variables that affect the maximum precipitation. Monthly maximum precipitation amounts for the period 1950–2010 were modelled for seven climatological stations in the western Black Sea subregion of Turkey using a distributional and time series analysis approach.