D. P. Dee, S. M. Uppala, A. J. Simmons, P. Berrisford, P. Poli, S. Kobayashi, U. Andrae, M. A. Balmaseda, G. Balsamo, P. Bauer, P. Bechtold, A. C. M. Beljaars, L. Van De Berg, J. Bidlot, N. Bormann, C. Delsol, R. Dragani, M. Fuentes and A. J. Geer, “The ERA-Interim Reanalysis?: Configuration and Performance of the Data Assimilation System,” Quarterly Journal of the Royal Meteorology Society, Vol. 137, 2011, pp. 553-597. http://dx.doi.org/10.1002/qj.828

has been cited by the following article:

• TITLE: Precipitation Extremes Analysis over the Brazilian Northeast via Logistic Regression

  AUTHORS: Washington Luiz Félix Correia Filho, Paulo Sérgio Lucio, Maria Helena Constantino Spyrides

  KEYWORDS: Odds Ratio; ROC Curve; Outgoing Longwave Radiation; Semiarid Region

  JOURNAL NAME: Atmospheric and Climate Sciences, Vol.4 No.1, December 20, 2013

  ABSTRACT: This work diagnosed the precipitation extremes over the Brazilian Northeast (NEB) based on logistic regression for obtaining associations between precipitation extremes and the meteorological variables by Odd Ratio (OR). Data of ten meteorological variables to the NEB (North (NNEB), East (ENEB), South (SNEB) and Semiarid (SANEB)) were used daily. The OR results evidenced that the outgoing longwave radiation was the key variable on the precipitation extremes detection in three sub-regions: ENEB with 2.91 times (95% confidence interval (CI): 2.11, 4.02), NNEB with 3.63 times (95% CI: 1.93, 6.83), and SANEB with 5.40 times (95% CI: 3.04, 9.61); while on SNEB, it was relative humidity with 3.88 times (95% CI: 2.89, 5.20) more chance to favor the precipitation extremes. The maximum temperature, zonal wind component, evaporation, specific humidity and RH also had influence on these extremes. Goodness-of-fit and ROC analysis demonstrated that all models had a good fit and good predictive capability.