Climate predictability and prediction skill on seasonal time scales over South America from CHFP models
- 203 Downloads
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.
KeywordsSouth America Seasonal predictability El Niño Southern Oscillation Precipitation Temperature
We acknowledge the WCRP/CLIVAR Working Group on Seasonal to Interannual Prediction (WGSIP) for establishing the Climate-system Historical Forecast Project (CHFP, see Kirtman and Pirani 2009) and the Centro de Investigaciones del Mar y la Atmósfera (CIMA) for providing the model output http://chfps.cima.fcen.uba.ar/DS. We also thank the data providers for making the model output available through CHFP. This research was supported by UBACyT 20020100100434, CONICET/PIP 112-20120100626CO, PIDDEF 2014/2017 No 15, ANR-15-JCL/-0002-01 “CLIMAX”. M.O. is supported by a Ph.D grant from CONICET, Argentina.
- Barreiro M, Chang P, Saravanan R (2002) Variability of the South Atlantic convergence zone simulated by an atmospheric general circulation model. J Clim. doi: 10.1175/1520-0442(2002)015<0745:VOTSAC>2.0.CO;2
- Colman R, Deschamps L, Naughton M, Rikus L, Sulaiman A, Puri K, Roff G, Sun Z, Embury G (2005) BMRC atmospheric model (BAM) version 3.0: comparison with mean climatology. BMRC research report no. 108, Bur Met, Melbourne, AustraliaGoogle Scholar
- Misra V, Li H, Wu Z, Di Napoli S (2014) Global seasonal climate predictability in a two tiered forecast system: part I: boreal summer and fall seasons. Clim Dyn 42:1425. doi: 10.1007/s00382-013-1812-y
- Molteni F, Stockdale T, Balmaseda M, Balsamo G, Buizza R, FerrantiL, Magnusson L, Mogensen K, Palmer T, Vitart F (2011) The new ECMWF seasonal forecast system (System 4). ECMWF Technical Memorandum 656Google Scholar
- National Research Council (2010) Assessment of intraseasonal to interannual climate prediction and predictability. The National Academies Press, WashingtonGoogle Scholar
- Nobre P et al (2004) Seasonal-to-decadal predictability and prediction of South American climate. White Paper prepared for the CLIVAR Workshop on Atlantic Predictability Reading, UK, 19–23 April 2004Google Scholar
- Schiller A, Godfrey JS, McIntosh PC, Meyers G, Smith NR, Alves O, Wang G, Fiedler R (2002) A new version of the Australian community ocean model for seasonal climate prediction. CSIRO marine research report no. 240Google Scholar
- Van den Dool H (2007) Empirical methods in short-term climate prediction. Oxford University Press, OxfordGoogle Scholar
- Yukimoto S, Adachi Y, Hosaka M, Sakami T, Yoshimura H, Hirabara M, Tanaka YT, Shindo E, Tsujino H, Deushi M, Mizuta R, Yabu S, Obata A, Nakano H, Koshiro T, Ose T, Kitoh A (2012) A new global climate model of the Meteorological Research Institute: MRI-CGCM3—model description and basic performance. J Meterol Soc Jpn 90A:23–64. doi: 10.2151/jmsj.2012-A02 CrossRefGoogle Scholar