Abstract
Combining individual forecasts is one of the practices used to improve weather prediction results. Identifying which combination of techniques results in a more accurate forecast is the subject of many comparative studies as well proposals for combined methods. Here we compare three combination techniques: (1) principal component regression (PCR), (2) convex combination by mean squared errors (MSE) and (3) ensemble average to combine six regional climate models of the Regional Climate Change Assessment for the La Plata Basin Project (CLARIS-LPB) for variable rainfall in three regions: Amazon (AMZ), Northeastern Brazil (NEB) and La Plata Basin (LPB), for the past (1961–1990) and future (2071–2100) climates. The results indicate that the average RMSE values showed improved representation of climate for LPB in some months, which is an important advance in climate studies. On the other hand, PCR presented greater accuracy (lower RMSE) than MSE in the AMZ and NEB regions. In winter months, both combinations presented lower RMSE results, mainly PCR in the three study regions. The correlation coefficient supports the results already found, namely, PCR obtained moderate to strong correlations, which were statistically significant at 5 % in both regions for all months, while MSE presented low to moderate correlations, which were statically significant at 5 % only in some months. Based on that, PCR achieved the best corrected forecast, as it was superior in forecasting precipitation due to the lower RMSE value. It is noteworthy that the PCR data were first subjected to principal component analysis (PCA) and the scores were used to perform the prediction.
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Chakraborty A, Krishnamurti TN, Gnanaseelan C (2007) Prediction of the diurnal cycle using a multimodel superensemble. Part II: Clouds. Mon Weather Rev 135:4097–4116
Christensen JH, Kjellström E, Giorgi F, Lenderink G, Rummukainen M (2010) Weight assignment in regional climate models. Clim Res 44(2-3):179–194
Chou SC, Lan C-W (2012) Changes in the annual range of precipitation under global warming. J Clim 25(1):222–235
Coppola E, Giorgi F, Raffaele F, Fuentes-Franco R, Giuliani G, LLopart-Pereira M, Torma C (2014) Present and future climatologies in the phase I CREMA experiment. Clim Change 125(1):23–38
Coutinho MM (1999) Previsão por conjuntos utilizando perturbações baseadas em componentes principais. São José dos Campos. Dissertação (Mestrado em Meteorologia) - Instituto Nacional de Pesquisas Espaciais, p 136
Coutinho EDC, Fisch G (2007) Distúrbios ondulatórios de leste (DOLs) na região do Centro de Lançamento de Alcântara-MA. Revis Bras de Meteorol 22(2):193–203
Coutinho MDL, Lima KC, Silva CMS (2016) Regional climate simulations of the changes in the components of the moisture budget over South America. Int J Climatol 36(3):1170–1183
Domínguez M, Gaertner MA, De Rosnay P, Losada T (2010) A regional climate model simulation over West Africa: parameterization tests and analysis of land-surface fields. Clim Dyn 35(1):249–265
Da Rocha RP, Morales CA, Cuadra SV, Ambrizzi T (2009) Precipitation diurnal cycle and summer climatology assessment over South America: an evaluation of regional climate model version 3 simulations. J Geophys Res: Atmos. doi:10.1029/2008JD010212
Da Rocha RP, Cuadra SV, Reboita MS, Krüger LF, Ambrizzi T, Krusche N (2012) Effects of RegCM3 parameterizations on simulated rainy season over South America. Clim Res 52:253–265
Da Silva AG, Silva CMS (2014) Improving regional dynamic downscaling with multiple kinear regression model using components principal analysis: precipitation over Amazon and Northeast Brazil. Adv Meteorol 2014
Ferraz SET, Pedroso D (2013) Sensitivity of REGCM3 simulated precipitation over southern Brazil with different boundary conditions: ENSO case. Adv Meteorol 2013
Goddard L, Mason SJ, Zebiak SE, Ropelewski CF, Basher R, Cane MA (2001) Current approaches to seasonal-tointerannual climate predictions. Int J Climatol 21:1111–1152
Hopkins WG (2009) Correlation coefficient. Disponível em: http://www.sportsci.org/resource/stats/correl.html. Acesso em: 20 fev. 2014
Jeong DI, Kim Y (2009) Combining single-value streamflow forecasts—a review and guidelines for selecting techniques. J Hydrol 377(3):284–299
Kendall MG (1957) A course in multivariate analysis. Griffin, London
Knutti R, Furrer R, Tebaldi C, Cermak J, Meehl GA (2010) Challenges in combining projections from multiple climate models. J Clim 23:2739–2758. doi:10.1175/2009JCLI3361.1
Krishnamurti TN, Kishtawal CM, Larow TE, Bachiochi DR, Zhang Z (1999) Improved weather and seasonal climate forecasts from multi-model superensemble. Science 285(5433):1548–1550
Krishnamurti TN, Kishtawal CM, Zhang Z, LaRow T, Bachiochi DR, Williford E, Gadgil S, Surendran S (2000a) Multimodel ensemble forecasts for weather and seasonal climate. J Clim 13:4196–4216. doi:10.1175/1520-0442(2000)013<4196:MEFFWA>2.0.CO;2
Krishnamurti TN, Kishtawal CM, Zhang Z, LaRow TE, Bachiochi DR, Williford CE, Gadgil S, Surendran S (2000b) Improving tropical precipitation forecasts from a multianalysis superensemble. J Clim 13:4217–4227
Krishnamurti TN, Sanjay J, Mitra AK, Vijaya Kumar TSV (2004) Determination of forecast errors arising from different components of model physics and dynamics. Mon Weather Rev 132(11):2570–2594
Krishnamurti TN, Mishra AK, Chakraborty A, Rajeevan M (2009) Improving global model precipitation forecasts over India using downscaling and the FSU superensemble, Part I: 1–5-Day forecasts. Mon Weather Rev 137:2713–2735
Kumar S, Tamura K, Jakobsen IB, Nei M (2001) MEGA2: molecular evolutionary genetics analysis software. Bioinformatics 17(12):1244–1245
Lee JA, Kolczynski WC, Mccandless TC, Haupt SE (2012) An objective methodology for configuring and down-selecting an nwp ensemble for low-level wind prediction. Mon Weather Rev 140(7):2270–2286
Lenartz F, Mourre B, Barth A, Beckers J-M, Vandenbulcke L, Rixen M (2010) Enhanced ocean temperature forecast skills through 3-D super-ensemble multi-model fusion. Geophys Res Lett 37(19). doi:10.1029/2010GL044591
Leung LR, Qian Y, Bian X, Washington WM, Han J, Roads JO (2004) Mid-century ensemble regional climate change scenarios for the western United States. Clim Change 62(1–3):75–113
Li L, Conil S (2003) Transient response to an atmospheric GCM to North Atlantic SST anomalies. J Clim 16:3993–3998
Majewski D (1991) The Europa-Modell of the Deutscher Wetterdienst. In: Seminar proceedings ECMWF, vol 2. pp 147–191
Marengo JA, Ambrizzi T, da Rocha RP, Alves LM, Cuadra SV, Valverde MC, Ferraz SET, Torres RR, Santos DC (2010) Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models. Clim Dyn 35(6):1073–1097
Martens H (1992) Multivariate calibration. Wiley, New York
Meehl GA, Stocker TF, Collins WD, Friedlingstein P, Gaye AT, Gregory JM, Zhao ZC (2007) Global climate projections. Clim Change 3495:747–845
Menéndez CG, De Castro M, Boulanger JP, D’Onofrio A, Sanchez E, Sörensson AA, Teichmann C (2010) Downscaling extreme month-long anomalies in southern South America. Clim Change 98(3–4):379–403
Misra V (2006) Understanding the predictability of seasonal precipitation over northeast Brazil. Tellus 58a:307–319
Mota GV (1997) Estudo observacional de distúrbios ondulatórios de leste no nordeste brasileiro. São Paulo. 92 p. Dissertação (Mestrado em Meteorologia) – Instituto Astronômico e Geofísico–USP
Moura AD, Shukla J (1981) On the dynamics of droughts in northeast Brazil: observations, theory and numerical experiments with a general circulation model. J Atmos Sci 38(7):2653–2675
Mullen S, Buizza R (2001) Quantitative precipitation forecasts over the United States by the ECMWF ensemble prediction system. Mon Weather Rev 129(4):638–663
Paiva EJ, Paiva AP, Ferreira JR, Balestrassi PP (2008) Otimização de múltiplas respostas baseada no Erro Quadrático Médio Multivariado. In: XXVIII Encontro Nacional de Engenharia de Produção. Rio de Janeiro
Pal et al (2007) Regional climate modeling for the developing world: The ICTP RegCM3 and RegCNET. Bull Am Meteorol Soc 88:1395–1409
Pesquero JF, Chou SC, Nobre CA, Marengo JA (2010) Climate downscaling over South America for 1961–1970 using the Eta Model. Theoret Appl Climatol 99(1–2):75–93
Phillips DL, Dolph J, Marks D (1992) A comparison of geostatistical procedures for spatial analysis of precipitations in mountainous terrain. Agric For Meteorol 58(1):119–141
Richardson DS (2001) Measures of skill and value of ensemble prediction systems, theirinter relationship and the effect of ensemble size. Q J R Meteorol Soc 127:2473–2489. doi:10.1002/qj.49712757715
Robertson AW, Lall U, Zebiak SE, Goddard L (2004) Improved combination of multiple atmospheric GCM ensembles for seasonal predition. Mon Weather Rev 132(12):2732–2744
Roggo Y, Chalus P, Maurer L, Lema-Martinez C, Edmond A, Jent N (2007) A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies. J Pharm Biomed Anal 44(3):683–700
Rozante JR, Moreira DR, Godoy RCM, Fernandes AA (2014) Multi-model ensemble: technique and validation. Geosci Model Dev Discuss 7(3):2933–2959
Sadourny R, Le Van P, Hourdin F (1995) Discrétisation des equations de la dynamique dans le modèle LMDZ. Internal report, Laboratoire de Météorologie Dynamique du CNRS, Paris, p 4
Salathé EP, Steed R, Mass CF, Zahn P (2008) A high-resolution climate model for the U.S. Pacific Northwest: mesoscale feedbacks and local responses to climate change. J Clim 21(21):5708–5726
Samuelsson P, Kourzeneva E, Mironov D (2010) The impact of lakes on the European climate as simulated by a regional climate model. Boreal Environ Res 15(2):113–129
Samuelsson P, Jones C, Willén U, Ullerstig A, Gollvik S, Hansson U, Jansson C, Kjellström E, Nikulin G, Wyser K (2011) The Rossby centre regional climate model RCA3: model description and performance. Tellus 63(1):4–23
Sancevero SS, Remacre AZ, Vidal AC, Portugal RS (2008) Aplicação de técnicas de estatística multivariada na definição da litologia a partir de perfis geofísicos de poços. Revis Bras Geosci 38(1):61–74
Sánchez E, Gaertner MA, Gallardo C, Padorno E, Arribas A, De Castro M (2007) Impacts of a change in vegetation description on simulated European summer present-day and future climates. Clim dyn 29(2–3):319–332
Sánchez E, Solman S, Remedio ARC, Berbery H, Samuelsson P, Da Rocha RP, Jacob D (2015) Regional climate modelling in CLARIS-LPB: a concerted approach towards twentyfirst century projections of regional temperature and precipitation over South America. Clim Dyn 45(7–8):2193–2212
Schneider U, Fuchs T, Meyer-Christoffer A, Rudolf B (2008) Global precipitation analysis products of the GPCC. Global Precipitation Climatology Centre (GPCC), DWD, Internet Publikation, pp 1–12
Solman SA, Sánchez E, Samuelsson P, Da Rocha RP, Li L, Marengo J, Jacob D (2013) Evaluation of an ensemble of regional climate model simulations over South America driven by the ERA-Interim reanalysis: model performance and uncertainties. Clim Dyn 41(5–6):1139–1157
Sörensson AA, Menéndez CG (2011) Summer soil-precipitation coupling in South America. Tellus 63(1):56–68
Stocker T, Qin D, Plattner GK, Tignor M, Midgley P (2010) Meeting report of the IPCC expert meeting on assessing and combining multi model climate projections. IPCC Working Group I Technical Support Unit, Berlin
Sun L, Li H, Zebiak SE, Moncunill DF, Filho FD, Moura AD (2006) An operational dynamical downscaling prediction system for Nordeste Brazil and the 2002–04 real-time forecast evaluation. J Clim 19(10):1990–2007
Tebaldi C, Smith RW, Nychka D, Mearns LO (2005) Quantifying uncertainty in projections of regional climate change: a bayesian approach to the analysis of multimodel ensembles. J Clim 18(10):1524–1540
Van Lier Walqui M, Vukicevic T, Posselt DJ (2012) Quantification of cloud microphysical parameterization uncertainty using radar reflectivity. Mon Weather Rev 140(11):3442–3466
Wang C (2002) Atlantic climate variability and its associated atmospheric circulation cells. J Clim 15:1516–1536
Wilks DS (2006) Statistical methods in the atmospheric sciences, 2nd edn. Academic Press, San Diego
Willmott CJ (1982) Some comments on the evaluation of model performance. Bull Am Meteorol Soc 63(11):1309–1313
Zhu H, Thorpe A (2006) The predictability of extra-tropical cyclones: the influence of the initial condition and model uncertainties. J Atmos Sci 63(5):1483–1497
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We would like to thank the CLARIS-LPB project for providing the outputs of the models and also the Office to Improve University Personnel (CAPES) for funding.
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Coutinho, M.D.L., Lima, K.C. & Santos e Silva, C.M. Improvements in precipitation simulation over South America for past and future climates via multi-model combination. Clim Dyn 49, 343–361 (2017). https://doi.org/10.1007/s00382-016-3346-6
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DOI: https://doi.org/10.1007/s00382-016-3346-6