Climate predictability and prediction skill on seasonal time scales over South America from CHFP models

This work presents an assessment of the predictability and skill of climate anomalies over South America. The study was made considering a multi-model ensemble of seasonal forecasts for surface air temperature, precipitation and regional circulation, from coupled global circulation models included i...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autor principal: Osman, M.
Otros Autores: Vera, C.S
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: Springer Verlag 2017
Materias:
Acceso en línea:Registro en Scopus
DOI
Handle
Registro en la Biblioteca Digital
Aporte de:Registro referencial: Solicitar el recurso aquí
LEADER 13742caa a22011057a 4500
001 PAPER-15561
003 AR-BaUEN
005 20230518204619.0
008 190410s2017 xx ||||fo|||| 00| 0 eng|d
024 7 |2 scopus  |a 2-s2.0-84996490461 
040 |a Scopus  |b spa  |c AR-BaUEN  |d AR-BaUEN 
100 1 |a Osman, M. 
245 1 0 |a Climate predictability and prediction skill on seasonal time scales over South America from CHFP models 
260 |b Springer Verlag  |c 2017 
270 1 0 |m Osman, M.; Ciudad Universitaria, Pabellón II-2do. Piso, Argentina; email: osman@cima.fcen.uba.ar 
506 |2 openaire  |e Política editorial 
504 |a Arora, V., Scinocca, J., Boer, G., Christian, J., Denman, K.L., Flato, G., Kharin, V., Merryfield, W., Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases (2011) Geophys Res Lett, 38, p. L05805 
504 |a Barreiro, M., Influence of ENSO and the South Atlantic Ocean on climate predictability over Southeastern South America (2010) Clim Dyn, 35, pp. 1493-1508 
504 |a Barreiro, M., Chang, P., Saravanan, R., Variability of the South Atlantic convergence zone simulated by an atmospheric general circulation model. J Clim (2002) doi:10.1175/1520-0442(2002)015<0745:VOTSAC>2.0.CO;2 
504 |a Barreiro, M., Chang, P., Saravanan, R., Simulated precipitation response to SST forcing and potential predictability in the region of the South Atlantic convergence zone (2005) Clim Dyn 
504 |a Becker, E., van den Dool, H., Zhang, Q., Predictability and forecast skill in NMME (2014) J Clim, 27, pp. 5891-5906 
504 |a Chaves, R.R., Nobre, P., Interactions between the South Atlantic Ocean and the atmospheric circulation over South America (2004) Geophys Res Lett, 31, p. L03204 
504 |a Colman, R., Deschamps, L., Naughton, M., Rikus, L., Sulaiman, A., Puri, K., Roff, G., Embury, G., BMRC atmospheric model (BAM) version 3.0: comparison with mean climatology. BMRC research report no. 108 (2005) Bur Met, , Melbourne, Australia 
504 |a DelSole, T., Kumar, A., Jha, B., Potential seasonal predictability: comparison between empirical and dynamical model estimates (2013) Geophys Res Lett, 40, pp. 3200-3206 
504 |a Feng, X., DelSole, T., Houser, P., Bootstrap estimated seasonal potential predictability of global temperature and precipitation (2011) Geophys Res Lett, 38, p. L07702 
504 |a Feng, X., DelSole, T., Houser, P., A method for estimating potential seasonal predictability: analysis of covariance (2012) J Clim, 25, pp. 5292-5308 
504 |a Frumkin, A., Misra, V., Predictability of dry season reforecasts over the tropical and the sub-tropical South American region (2013) Int J Climatol, 33, pp. 137-1247 
504 |a Gueremy, J.F., Deque, M., Brau, A., Piedelievre, J.P., Actual and potential skill of seasonal predictions using the CNRM contribution to DEMETER: coupled versus uncoupled model (2005) Tellus, 57A, pp. 308-319 
504 |a Hagedorn, R., Doblas-Reyes, F.J., Palmer, T.N., The rationale behind the success of multi-model ensembles in seasonal forecasting—I. Basic concept (2005) Tellus A, 57, pp. 219-233 
504 |a Hagedorn, R., Doblas-Reyes, F.J., Palmer, T.N., DEMETER and the application of seasonal forecasts (2006) Predictability of weather and climate, pp. 674-692. , Palmer T, Hagendom R, (eds), Cambridge University Press, Cambridge 
504 |a Jha, B., Kumar, A., A comparative analysis of change in the first and second moment of the PDF of seasonal mean 200-mb heights with ENSO SSTs (2009) J Clim, 22, pp. 1412-1423 
504 |a Kalnay, The NCEP/NCAR 40-year reanalysis project (1996) Bull Am Meteorol Soc, 77, pp. 437-470 
504 |a Kirtman, B., Pirani, A., The state of the art of seasonal prediction: outcomes and recommendations from the first world climate research program workshop on seasonal prediction (2009) Bull Am Meteorol Soc, 90, pp. 455-458 
504 |a Kumar, A., Hoerling, M.P., Annual cycle of Pacific-North American seasonal predictability associated with different phases of ENSO (1998) J Clim, 11, pp. 3295-3308 
504 |a Kumar, A., Jha, B., Zhang, Q., Bounoua, L., A new methodology for estimating the unpredictable component of seasonal atmospheric variability (2007) Mon Weather Rev, 20, pp. 3888-3901 
504 |a Landman, W.A., Goddard, L., Statistical recalibration of GCM forecasts over Southern Africa using model output statistics (2002) J Clim, 15, pp. 2038-2055 
504 |a Li, H., Misra, V., Global seasonal climate predictability in a two tiered forecast system. Part II: boreal winter and spring seasons (2014) Clim Dyn, 42, p. 1449 
504 |a Marsland, S., Haak, H., Jungclaus, J.H., Latif, M., Röske, F., The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates (2003) Ocean Model, 5 (2), pp. 91-127 
504 |a Misra, V., An evaluation of the predictability of austral summer season precipitation over South America (2004) J Clim, 17, pp. 1161-1175 
504 |a Misra, V., Li, H., Wu, Z., Di Napoli, S., Global seasonal climate predictability in a two tiered forecast system: part I: boreal summer and fall seasons (2014) Clim Dyn, 42, p. 1425 
504 |a Molteni, F., Stockdale, T., Balmaseda, M., Balsamo, G., Buizza, R., The new ECMWF seasonal forecast system (System 4) (2011) ECMWF Technical Memorandum, p. 656 
504 |a (2010) Assessment of intraseasonal to interannual climate prediction and predictability, , The National Academies Press, Washington 
504 |a Nobre, P., Seasonal-to-decadal predictability and prediction of South American climate. White Paper prepared for the CLIVAR Workshop on Atlantic Predictability Reading (2004) UK, 19–23 April, p. 2004 
504 |a Osman, M., Vera, C.S., Doblas-Reyes, F.J., Predictability of the tropospheric circulation in the Southern Hemisphere from CHFP models (2016) Clim Dyn, 46 (7), pp. 2423-2434 
504 |a Peng, P., Kumar, A., Wang, W., An analysis of seasonal predictability in coupled model forecasts (2011) Clim Dyn, 36, pp. 637-648 
504 |a Quan, X.W., Webster, P.J., Moore, A.M., Chang, H.R., Seasonality in SST-forced atmospheric short-term climate predictability (2004) J Clim, 17, pp. 3090-3108 
504 |a Rowell, D.P., Assessing potential seasonal predictability with an ensemble of multidecadal GCM simulations (1998) J Clim, 11, pp. 109-120 
504 |a Saha, S., Nadiga, S., Thiaw, C., Wang, J., Wang, W., Zhang, Q., Van den Dool, H.M., Xie, P., The NCEP climate forecast system (2006) J Clim, 19, pp. 3483-3517 
504 |a Scaife, A.A., Skillful long-range prediction of European and North American winters (2014) Geophys Res Lett, 41, pp. 2514-2519 
504 |a Schiller, A., Godfrey, J.S., McIntosh, P.C., Meyers, G., Smith, N.R., Alves, O., Wang, G., Fiedler, R., A new version of the Australian community ocean model for seasonal climate prediction (2002) CSIRO marine research report no, p. 240 
504 |a Schubert, S.D., Suarez, M.J., Pegion, P.J., Kistler, M.A., Kumar, A., Predictability of zonal means during boreal summer (2002) J Clim, 15, pp. 420-434 
504 |a Scinocca, J.F., McFarlane, N.A., Lazare, M., Li, J., The CCCma third generation AGCM and its extension into the middle atmosphere (2008) Atmos Chem Phys, 8, pp. 7055-7074 
504 |a Smith, D., Scaife, A.A., Kirtman, B.P., What is the current state of scientific knowledge with regard to seasonal and decadal forecasting? (2012) Environ Res Lett, 7, p. 15602 
504 |a Stefanova, L., Misra, V., O’Brien, J.J., Hindcast skill and predictability for precipitation and two-meter air temperature anomalies in global circulation models over the Southeast United States (2012) Clim Dyn, 38, p. 161 
504 |a Stevens, The atmospheric component of the MPI earth system model: ECHAM6 (2013) J Adv Model Earth Syst 
504 |a Stockdale, T.N., Anderson, D.L.T., Balmaseda, M.A., Doblas-Reyes, F.J., Ferranti, L., Mogensen, K., Palmer, T.N., Vitart, F., ECMWF seasonal forecast system 3 and its prediction of sea surface temperature (2011) Clim Dyn 
504 |a Taschetto, A.S., Wainer, I., Reproducibility of South American Precipitation due to Subtropical South Atlantic SSTs (2008) J Clim 
504 |a Van den Dool, H., (2007) Empirical methods in short-term climate prediction, , Oxford University Press, Oxford 
504 |a Vera, C., Baez, J., Douglas, M., Emmanuel, C.B., Marengo, J., Meitin, J., Nicolini, M., Zipser, E., The South American low-level jet experiment (2006) Bull Am Meteorol Soc, 87, pp. 63-77 
504 |a Vera, C., Higgins, W., Amador, J., Ambrizzi, T., Garreaud, R., Gochis, D., Gutzler, D., Zhang, C., Toward a unified view of the American monsoon systems (2006) J Clim, 19, pp. 4977-5000 
504 |a Watanabe, M., Improved climate simulation by MIROC5: mean states, variability, and climate sensitivity (2010) J Clim, 23, pp. 6312-6335 
504 |a Wu, R., Kirtman, B.P., Changes in spread and predictability associated with ENSO in an ensemble coupled GCM (2006) J Clim, 19, pp. 4378-4396 
504 |a Yukimoto, S., Adachi, Y., Hosaka, M., Sakami, T., Yoshimura, H., Hirabara, M., Tanaka, Y.T., Kitoh, A., A new global climate model of the Meteorological Research Institute: MRI-CGCM3—model description and basic performance (2012) J Meterol Soc Jpn, 90A, pp. 23-64 
504 |a Zipser, E.J., Cecil, D.J., Liu, C., Nesbitt, S.W., Yorty, D.P., Where are the most intense thunderstorms on earth? (2006) Bull Am Meteorol Soc, 87, pp. 1057-1071 
504 |a Zwiers, F.W., Wang, X.L., Sheng, J., Effects of specifying bottom boundary conditions in an ensemble of atmospheric GCM simulations (2000) J Geophys Res Atmos, 105, pp. 7295-7315 
520 3 |a This work presents an assessment of the predictability and skill of climate anomalies over South America. The study was made considering a multi-model ensemble of seasonal forecasts for surface air temperature, precipitation and regional circulation, from coupled global circulation models included in the Climate Historical Forecast Project. Predictability was evaluated through the estimation of the signal-to-total variance ratio while prediction skill was assessed computing anomaly correlation coefficients. Both indicators present over the continent higher values at the tropics than at the extratropics for both, surface air temperature and precipitation. Moreover, predictability and prediction skill for temperature are slightly higher in DJF than in JJA while for precipitation they exhibit similar levels in both seasons. The largest values of predictability and skill for both variables and seasons are found over northwestern South America while modest but still significant values for extratropical precipitation at southeastern South America and the extratropical Andes. The predictability levels in ENSO years of both variables are slightly higher, although with the same spatial distribution, than that obtained considering all years. Nevertheless, predictability at the tropics for both variables and seasons diminishes in both warm and cold ENSO years respect to that in all years. The latter can be attributed to changes in signal rather than in the noise. Predictability and prediction skill for low-level winds and upper-level zonal winds over South America was also assessed. Maximum levels of predictability for low-level winds were found were maximum mean values are observed, i.e. the regions associated with the equatorial trade winds, the midlatitudes westerlies and the South American Low-Level Jet. Predictability maxima for upper-level zonal winds locate where the subtropical jet peaks. Seasonal changes in wind predictability are observed that seem to be related to those associated with the signal, especially at the extratropics. © 2016, Springer-Verlag Berlin Heidelberg.  |l eng 
593 |a Ciudad Universitaria, Pabellón II-2do. Piso, Buenos Aires, C1428EGA, Argentina 
593 |a Centro de Investigaciones del Mar y la Atmósfera (CIMA/CONICET-UBA), UMI IFAECI/CNRS, Buenos Aires, Argentina 
593 |a Facultad de Ciencias Exactas y Naturales, Departamento de Ciencias de la Atmósfera y los Océanos, Universidad de Buenos Aires, Buenos Aires, Argentina 
690 1 0 |a EL NIÑO SOUTHERN OSCILLATION 
690 1 0 |a PRECIPITATION 
690 1 0 |a SEASONAL PREDICTABILITY 
690 1 0 |a TEMPERATURE 
690 1 0 |a AIR TEMPERATURE 
690 1 0 |a CLIMATE MODELING 
690 1 0 |a CLIMATE VARIATION 
690 1 0 |a CORRELATION 
690 1 0 |a EL NINO-SOUTHERN OSCILLATION 
690 1 0 |a ENSEMBLE FORECASTING 
690 1 0 |a PRECIPITATION (CLIMATOLOGY) 
690 1 0 |a PREDICTION 
690 1 0 |a SEASONAL VARIATION 
690 1 0 |a ZONAL WIND 
651 4 |a SOUTH AMERICA 
651 4 |a SOUTH AMERICA 
700 1 |a Vera, C.S. 
773 0 |d Springer Verlag, 2017  |g v. 49  |h pp. 2365-2383  |k n. 7-8  |p Clim. Dyn.  |x 09307575  |w (AR-BaUEN)CENRE-567  |t Climate Dynamics 
856 4 1 |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-84996490461&doi=10.1007%2fs00382-016-3444-5&partnerID=40&md5=4afbb8f3ba200932da14b336c320230c  |y Registro en Scopus 
856 4 0 |u https://doi.org/10.1007/s00382-016-3444-5  |y DOI 
856 4 0 |u https://hdl.handle.net/20.500.12110/paper_09307575_v49_n7-8_p2365_Osman  |y Handle 
856 4 0 |u https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_09307575_v49_n7-8_p2365_Osman  |y Registro en la Biblioteca Digital 
961 |a paper_09307575_v49_n7-8_p2365_Osman  |b paper  |c PE 
962 |a info:eu-repo/semantics/article  |a info:ar-repo/semantics/artículo  |b info:eu-repo/semantics/publishedVersion 
963 |a VARI 
999 |c 76514