Precipitation Extremes Analysis over the Brazilian Northeast via Logistic Regression
Author(s)
Washington Luiz Félix Correia Filho,
Paulo Sérgio Lucio,
Maria Helena Constantino Spyrides
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.
Cite this paper
W. Filho, P. Lucio and M. Spyrides, "Precipitation Extremes Analysis over the Brazilian Northeast via Logistic Regression," Atmospheric and Climate Sciences, Vol. 4 No. 1, 2014, pp. 53-59. doi: 10.4236/acs.2014.41007.
W. Filho, P. Lucio and M. Spyrides, "Precipitation Extremes Analysis over the Brazilian Northeast via Logistic Regression," Atmospheric and Climate Sciences, Vol. 4 No. 1, 2014, pp. 53-59. doi: 10.4236/acs.2014.41007.
References
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http://dx.doi.org/10.1175/2011JCLI4070.1 [24] R. R. Chaves and I. F. A. Cavalcanti, “Atmospheric Circulation Features Associated with Rainfall Variability over Southern Northeast Brazil,” Monthly Weather Review, Vol. 129, No. 10, 2001, pp. 2614-2626. http://dx.doi.org/10.1175/1520-0493(2001)129<2614:ACFAWR>2.0.CO;2 [25] L. M. V. Carvalho, C. Jones and B. Liebmann, “The South Atlantic Convergence Zone: Intensity, Form, Persistence, and Relationships with Intraseasonal to Interannual Activity and Extreme Rainfall,” Journal of Climate, Vol. 17, 2004, pp. 88-108. http://dx.doi.org/10.1175/1520-0442(2004)017<0088: TSACZI>2.0.CO;2 [26] S. K. Mishra, V. B. Rao and M. A. Gan, “Structure and Evolution of the Large-Scale Flow and an Embedded Upper-Tropospheric Cyclonic Vortex over Northeast Brazil,” Monthly weather review, Vol. 129, No. 7, 2001, pp. 1673-1688. http://dx.doi.org/10.1175/1520-0493(2001)129<1673:SAEOTL >2.0.CO;2 [27] M. Chen, W. Shi, P. Xie, V. Silva, V. E. Kousky, R. Wayne Higgins and J. E. Janowiak, “Assessing Objective Techniques for Gauge-Based Analyses of Global Daily Precipitation,” Journal of Geophysical Research: Atmospheres (1984-2012), Vol. 113, No. D4, 2008. [28] 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 [29] B. Liebmann and C. A. Smith, “Description of a Complete (Interpolated) Outgoing Longwave Radiation Dataset,” Bulletin of the American Meteorological Society, Vol. 77, 1996, pp. 1275-1277. [30] D. W. Hosmer, S. Taber and S. Lemeshow, “The Importance of Assessing the Fit of Logistic Regression Models: A Case Study,” American Journal of Public Health, Vol. 81, No. 12, 1991, pp. 1630-1635. http://dx.doi.org/10.2105/AJPH.81.12.1630 [31] S. H. Park, “Receiver Operating Characteristic (ROC) Curve?: Practical Review,” Vol. 5, 2004, pp. 11-18. [32] T. Fawcett, “An Introduction to ROC Analysis,” Pattern Recognition Letters, Vol. 27, No. 8, 2006, pp. 861-874. http://dx.doi.org/10.1016/j.patrec.2005.10.010 [33] R Development Core Team and Others, “R: A Language and Environment for Statistical Computing,” 2013. [34] W. N. Venables, and B. D. Ripley, “Modern Applied Statistics with S-PLUS,” Vol. 250, Springer-Verlag, New York, 1994. http://dx.doi.org/10.1007/978-1-4899-2819-1 [35] T. Sing, O. Sander, N. Beerenwinkel and T. Lengauer, “ROCR: Visualizing Classifier Performance in R,” Bioinformatics, Vol. 21, No. 20, 2005, pp. 3940-3941. http://dx.doi.org/10.1093/bioinformatics/bti623 [36] B. Carstensen, M. Plummer, E. Laara and M. Hills, “{Epi}: A Package for Statistical Analysis in Epidemiology,” 2013. [37] S. Sandeep and F. Stordal, “Use of Daily Outgoing Longwave Radiation (OLR) Data in Detecting Precipitation Extremes in the Tropics,” Remote Sensing Letters, Vol. 4, No. 6, 2013, pp. 570-578. http://dx.doi.org/10.1080/2150704X.2013.769284 [38] K. E. Trenberth, A. Dai, R. M. Rasmussen and D. B. Parsons, “The Changing Character of Precipitation,” Bulletin of the American Meteorological Society, Vol. 84, No. 9, 2003, pp. 1205-1217. http://dx.doi.org/10.1175/BAMS-84-9-1205 [39] S. C. Liu, C. Fu, C.-J. Shiu, J.-P. Chen and F. Wu, “Temperature Dependence of Global Precipitation Extremes,” Geophysical Research Letters, Vol. 36, No. 17, 2009, Article ID: L17702.
http://dx.doi.org/10.1029/2009GL040218
[1] T. R. Karl and D. R. Easterling, “Climate Extremes: Selected Review and Future Research Directions,” Climatic Change, Vol. 42, 1999, pp. 209-325. [2] G. C. Blain, “Modeling Extreme Minimum Air Temperature Series under Climate Change Conditions,” Ciência Rural, Vol. 41, 2011, pp. 1877-1883. http://dx.doi.org/10.1590/S0103-84782011001100005 [3] A. M. Grimm and R. G. Tedeschi, “ENSO and Extreme Rainfall Events in South America,” Journal of Climate, Vol. 22, No. 7, 2009, pp. 1589-1609. http://dx.doi.org/10.1175/2008JCLI2429.1 [4] P. Friederichs, M. Gober, S. Bentzien, A. Lenz and R. Krampitz, “A Probabilistic Analysis of Wind Gusts Using Extreme Value Statistics,” Meteorologische Zeitschrift, Vol. 18, No. 6, 2009, pp. 615-629. http://dx.doi.org/10.1127/0941-2948/2009/0413 [5] G. A. M. Silva and D. Mendes, “Comparison Results for the CFSv2 Hindcasts and Statistical Downscaling over the Northeast of Brazil,” Advances in Geosciences, Vol. 35, 2013, pp. 79-88. http://dx.doi.org/10.5194/adgeo-35-79-2013 [6] P. Willems, K. Arnbjerg-Nielsen, J. Olsson and V. T. V. Nguyen, “Climate Change Impact Assessment on Urban Rainfall Extremes and Urban Drainage: Methods and Shortcomings,” Atmospheric Research, Vol. 103, 2012, pp. 106-118. http://dx.doi.org/10.1016/j.atmosres.2011.04.003 [7] R. A. Houze Jr., “Orographic Effects on Precipitations Clouds,” Reviews of Geophysics, Vol. 50, 2012, Article ID: GR1001. [8] F. Kucharski, D. Polzin and S. Hastenrath, “Teleconnection Mechanisms of Northeast Brazil Droughts?: Modeling and Empirical Evidence,” Revista Brasileira de Meteorologia, Vol. 23, No. 2, 2008, pp. 115-125. http://dx.doi.org/10.1590/S0102-77862008000200001 [9] P. A. O. Gorman and T. Schneider, “The Physical Basis for Increases in Precipitation Extremes in Simulations of 21st-Century Climate Change,” Proceedings of the National Academy of Sciences, Vol. 106, 2009, pp. 14773-14777. http://dx.doi.org/10.1073/pnas.0907610106 [10] P. Berg, C. Moseley, and J. O. Haerter, “Strong Increase in Convective Precipitation in Response to Higher Temperatures,” Nature Geoscience, Vol. 6, No. 3, 2013, pp. 181-185. http://dx.doi.org/10. 1038/ngeo1731 [11] M. D. Oyama and C. A. Nobre, “Climatic Consequences of a Large-Scale Desertification in Northeast Brazil: A GCM Simulation Study,” Journal of Climate, Vol. 17, No. 16, 2004, pp. 3203-3213.
http://dx.doi.org/10.1175/1520-0442(2004)017<3203:CCOALD>2.0.CO;2 [12] B. Liebmann, G. N. Kiladis, D. Allured, C. S. Vera, C. Jones, L. M. V. Carvalho, I. Bladé and P. L. M. Gonzáles, “Mechanisms Associated with Large Daily Rainfall Events in Northeast Brazil,” Journal of Climate, Vol. 24, No. 2, 2011, pp. 376-396. http://dx.doi.org/10.1175/2010JCLI3457.1 [13] Y. K. Kouadio, J. Servain, L. A. T. Machado and C. A. D. Lentini, “Heavy Rainfall Episodes in the Eastern Northeast Brazil Linked to Large-Scale Ocean-Atmosphere Conditions in the Tropical Atlantic,” Advances in Meteorology, Vol. 2012, 2012, pp. 1-16. http://dx.doi.org/10.1155/2012/ 369567 [14] S. Hastenrath, “Exploring the Climate Problems of Brazil’s Nordeste: A Review,” Climatic Change, Vol. 112, No. 2, 2011, pp. 243-251. http://dx.doi.org/10.1007/s10584-011-0227-1 [15] A. J. A. Nelder and R. W. M. Wedderburn, “Generalized Linear Models,” Journal of the Royal Statistical Society. Series A (General), Vol. 135, No. 3, 1972, pp. 370-384. http://dx.doi.org/10.2307/2344614 [16] Z. Yan, S. Bate, R. E. Chandler, V. Isham and H. Wheater, “Changes in Extreme Wind Speeds in NW Europe Simulated by Generalized Linear Models,” Theoretical and Applied Climatology, Vol. 83, No. 1-4, 2005, pp. 121-137. [17] J. Abaurrea and J. Asín, “Forecasting Local Daily Precipitation Patterns in a Climate Change Scenario,” Climate Research, Vol. 28, 2005, pp. 183-197. http://dx.doi.org/10.3354/cr028183 [18] M. K. Tippett, A. G. Barnston and A. W. Robertson, “Estimation of Seasonal Precipitation Tercile-Based Categorical Probabilities from Ensembles,” Journal of Climate, Vol. 20, No. 10, 2007, pp. 2210-2228. http://dx.doi.org/10.1175/JCLI4108.1 [19] T. M. Hamill, J. S. Whitaker and X. Wei, “Ensemble Reforecasting: Improving Medium-Range Forecast Skill Using Retrospective Forecasts,” Monthly Weather Review, Vol. 132, No. 6, 2004, pp. 1434-1447. http://dx.doi.org/10.1175/1520-0493(2004)132<1434:ERIMFS>2.0.CO;2 [20] V. E. Kousky, “Frontal Influences on Northeast Brazil,” Monthly Weather Review, Vol. 107, No. 9, 1979, pp. 1140-1153. http://dx.doi.org/10.1175/1520-0493(1979)107<1140:FIONB>2.0.CO;2 [21] L. C. B. Molion and S. de O. Bernardo, “Uma Revis?o da Dinamica das Chuvas no Nordeste Brasileiro,” Revista Brasileira de Meteorologia, Vol. 17, No. 1, 2002, pp. 1-10. http://dx.doi.org/10.1590/S0102-76382002000100002 [22] R. R. Torres and N. J. Ferreira, “Case Studies of Easterly Wave Disturbances over Northeast Brazil Using the Eta Model,” Weather and Forecasting, Vol. 26, No. 2, 2011, pp. 225-235.
http://dx.doi.org/10.1175/2010WAF2222425.1 [23] H.-Y. Ma, X. Ji, J. D. Neelin and C. R. Mechoso, “Mechanisms for Precipitation Variability of the Eastern Brazil/SACZ Convective Margin,” Journal of Climate, Vol. 24, No. 13, 2011, pp. 3445-3456.
http://dx.doi.org/10.1175/2011JCLI4070.1 [24] R. R. Chaves and I. F. A. Cavalcanti, “Atmospheric Circulation Features Associated with Rainfall Variability over Southern Northeast Brazil,” Monthly Weather Review, Vol. 129, No. 10, 2001, pp. 2614-2626. http://dx.doi.org/10.1175/1520-0493(2001)129<2614:ACFAWR>2.0.CO;2 [25] L. M. V. Carvalho, C. Jones and B. Liebmann, “The South Atlantic Convergence Zone: Intensity, Form, Persistence, and Relationships with Intraseasonal to Interannual Activity and Extreme Rainfall,” Journal of Climate, Vol. 17, 2004, pp. 88-108. http://dx.doi.org/10.1175/1520-0442(2004)017<0088: TSACZI>2.0.CO;2 [26] S. K. Mishra, V. B. Rao and M. A. Gan, “Structure and Evolution of the Large-Scale Flow and an Embedded Upper-Tropospheric Cyclonic Vortex over Northeast Brazil,” Monthly weather review, Vol. 129, No. 7, 2001, pp. 1673-1688. http://dx.doi.org/10.1175/1520-0493(2001)129<1673:SAEOTL >2.0.CO;2 [27] M. Chen, W. Shi, P. Xie, V. Silva, V. E. Kousky, R. Wayne Higgins and J. E. Janowiak, “Assessing Objective Techniques for Gauge-Based Analyses of Global Daily Precipitation,” Journal of Geophysical Research: Atmospheres (1984-2012), Vol. 113, No. D4, 2008. [28] 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 [29] B. Liebmann and C. A. Smith, “Description of a Complete (Interpolated) Outgoing Longwave Radiation Dataset,” Bulletin of the American Meteorological Society, Vol. 77, 1996, pp. 1275-1277. [30] D. W. Hosmer, S. Taber and S. Lemeshow, “The Importance of Assessing the Fit of Logistic Regression Models: A Case Study,” American Journal of Public Health, Vol. 81, No. 12, 1991, pp. 1630-1635. http://dx.doi.org/10.2105/AJPH.81.12.1630 [31] S. H. Park, “Receiver Operating Characteristic (ROC) Curve?: Practical Review,” Vol. 5, 2004, pp. 11-18. [32] T. Fawcett, “An Introduction to ROC Analysis,” Pattern Recognition Letters, Vol. 27, No. 8, 2006, pp. 861-874. http://dx.doi.org/10.1016/j.patrec.2005.10.010 [33] R Development Core Team and Others, “R: A Language and Environment for Statistical Computing,” 2013. [34] W. N. Venables, and B. D. Ripley, “Modern Applied Statistics with S-PLUS,” Vol. 250, Springer-Verlag, New York, 1994. http://dx.doi.org/10.1007/978-1-4899-2819-1 [35] T. Sing, O. Sander, N. Beerenwinkel and T. Lengauer, “ROCR: Visualizing Classifier Performance in R,” Bioinformatics, Vol. 21, No. 20, 2005, pp. 3940-3941. http://dx.doi.org/10.1093/bioinformatics/bti623 [36] B. Carstensen, M. Plummer, E. Laara and M. Hills, “{Epi}: A Package for Statistical Analysis in Epidemiology,” 2013. [37] S. Sandeep and F. Stordal, “Use of Daily Outgoing Longwave Radiation (OLR) Data in Detecting Precipitation Extremes in the Tropics,” Remote Sensing Letters, Vol. 4, No. 6, 2013, pp. 570-578. http://dx.doi.org/10.1080/2150704X.2013.769284 [38] K. E. Trenberth, A. Dai, R. M. Rasmussen and D. B. Parsons, “The Changing Character of Precipitation,” Bulletin of the American Meteorological Society, Vol. 84, No. 9, 2003, pp. 1205-1217. http://dx.doi.org/10.1175/BAMS-84-9-1205 [39] S. C. Liu, C. Fu, C.-J. Shiu, J.-P. Chen and F. Wu, “Temperature Dependence of Global Precipitation Extremes,” Geophysical Research Letters, Vol. 36, No. 17, 2009, Article ID: L17702.
http://dx.doi.org/10.1029/2009GL040218