C
Cintia Bertacchi Uvo
Researcher at Kansas Department of Agriculture, Division of Water Resources
Publications - 102
Citations - 2961
Cintia Bertacchi Uvo is an academic researcher from Kansas Department of Agriculture, Division of Water Resources. The author has contributed to research in topics: Precipitation & Climate change. The author has an hindex of 26, co-authored 97 publications receiving 2538 citations. Previous affiliations of Cintia Bertacchi Uvo include Columbia University & Kyushu University.
Papers
More filters
Journal ArticleDOI
Climate change impacts on groundwater and dependent ecosystems
Bjørn Kløve,Pertti Ala-aho,Guillaume Bertrand,Jason J. Gurdak,Hans Kupfersberger,Jens Kværner,Timo Muotka,Timo Muotka,Heikki Mykrä,Elena Preda,Pekka M. Rossi,Cintia Bertacchi Uvo,Elzie M. Velasco,Manuel Pulido-Velazquez +13 more
TL;DR: In this paper, a review examines climate change effects on groundwater and dependent ecosystems, focusing on the impacts of changes to groundwater on GDE biodiversity and future threats posed by climate change.
Journal ArticleDOI
The relationships between tropical Pacific and Atlantic SST and northeast Brazil monthly precipitation
TL;DR: In this article, the monthly patterns of northeast Brazil (NEB) precipitation are analyzed in relation to sea surface temperature (SST) in the tropical Pacific and Atlantic Oceans, using singular value decomposition.
Journal ArticleDOI
Analysis and regionalization of northern european winter precipitation based on its relationship with the North Atlantic oscillation
TL;DR: In this paper, an analysis of the regional variability of the influence of the North Atlantic oscillation on winter precipitation in northern Europe is developed using empirical orthogonal function analysis, cluster analysis and simple correlation.
Journal ArticleDOI
Exploring the impacts of the tropical Pacific SST on the precipitation patterns over South America during ENSO periods
TL;DR: In this paper, the authors used Singular Value Decomposition (SVD) and Simple Linear Correlation (SLC) to identify which regions in the Central and East Pacific ocean are better correlated with the South America precipitation during extreme ENSO events, and also which are the transition regions of the precipitation signal over South America during these events.
Journal ArticleDOI
Neural Networks for Rainfall Forecasting by Atmospheric Downscaling
Jonas Olsson,Cintia Bertacchi Uvo,Kenji Jinno,Akira Kawamura,Koji Nishiyama,Nobukazu Koreeda,T. Nakashima,O. Morita +7 more
TL;DR: In this article, two NNs were used in series to determine rainfall occurrence and intensity during rainy periods and classify rainfall into intensity categories and train the NN to reproduce these rather than actual intensities.