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What is the variability in US west coast winter precipitation during strong El Niño events?

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Abstract

Motivated by the fact that the spatial pattern of the observed precipitation anomalies during 2015/16 winter (a year of strong El Niño) over the west coast of the US and that of the El Niño composite precipitation pattern had considerable differences, the variability in the winter precipitation during strong El Niño events is assessed. The analysis is based on a set of hindcasts (1982–2011) and real-time forecasts (2012–2015) from NCEP Climate Forecast System version 2 (CFSv2), and the following aspects for seasonal mean precipitation variability were examined: (1) the mean signal during strong El Niño based on the composite analysis, and further, the variability from the composite on an event-to-event basis; (2) probability of occurrence for precipitation anomalies to be opposite to the signal (inferred as the composite mean); (3) the probability to have precipitation anomaly in different categories varying from wet to dry; and (4) variations in the characteristics of precipitation from OND, NDJ, to DJF (early to late boreal winter). The results show that the model forecasted seasonal mean precipitation composite for strong El Niño was similar to the linear regression signal with the Niño 3.4 index in observations, with negative anomalies over the Pacific Northwest and positive anomalies over California. However, although in response to an El Niño event, the California precipitation PDF was shifted towards positive values relative to the climatological PDF, the overlap between climatological PDF and the PDF for El Niño events was considerable. This is because of the large variability in seasonal mean outcomes of precipitation from one forecast to another, and therefore, chances to have precipitation anomalies with their sign opposite to the composite El Niño signal remain appreciable. In this paradigm, although the seasonal mean precipitation during 2015/16 winter over the west coast of the US differed from the mean signal for a strong El Niño event, the observed anomalies were well within the envelope of possible outcomes. This has significant implications for seasonal predictability and prediction skill, and further, poses challenges for decision makers in the uptake of seasonal forecast information.

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References

  • Bond NA, Cronin MF, Freeeland H, Mantua N (2015) Causes and impacts of the 2014 warm anomaly in the NE Pacific. Geophys Res Lett 42:3414–3420. doi:10.1002/2015GL063306

    Article  Google Scholar 

  • Chen M, Kumar A (2015) Influence of ENSO SSTs on the spread of the probability density function for precipitation and land surface temperature. Clim Dyn 45:965–974. doi:10.1007/s00382-014-2336-9

    Article  Google Scholar 

  • Chen M, Kumar A (2016) The utility of seasonal hindcast database for the analysis of climate variability: an example. Clim Dyn doi:10.1007/s00382-016-3073-z

    Google Scholar 

  • Chen M, Xie P, Janowiak JE, Arkin PA (2002) Global land precipitation: a 50-yr monthly analysis based on gauge observations. J Hydrometeor 3:249–266

    Article  Google Scholar 

  • DelSole T, Shukla J (2006) Specification of wintertime North American surface temperature. J Clim 38:2691–2716

    Article  Google Scholar 

  • DelSole T, Kumar A, Jha B (2013) Potential seasonal predictability: Comparison between empirical and dynamical model estimates. Geophys Res Lett 40:3200–3206. doi:10.1002/grl.50581

    Article  Google Scholar 

  • Hoerling MP, Kumar A (1997) Origins of extreme climate states during the 1982-83 ENSO winter. J Clim 7:745–766

    Article  Google Scholar 

  • Jha B, Kumar A (2009) A comparative analysis of change in the first and second moment of the PDF of seasonal mean 200-mb-heights with ENSO SSTs. J Clim 22:1412–1423

    Article  Google Scholar 

  • Jha B, Kumar A, Hu Z-Z (2016) An update on the estimate of predictability of seasonal mean atmospheric variability using North American Multi-Model Ensemble. Clim Dyn (under review)

  • Kahneman D, Slovi P, Tversky A (1982). Judgment under uncertainty: Heuristics and biases (1st edition). Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Kirtman BP et al (2014) The North American Multimodel Ensemble: phase-1 seasonal to interannual prediction; phase-2 toward developing intraseasonal prediction. Bull Am Meteor Soc 95:85–601. doi:10.1175/BAMS-D-12-00050.1

    Article  Google Scholar 

  • Kumar A (2010) On the assessment of the value of the seasonal forecast information. Meteorol Appl 17:385–392. doi:10.1002/met.167

    Google Scholar 

  • Kumar A, Chen M (2015) Inherent predictability, requirement on the ensemble size, and complementarity. Mon Weather Rev 143:3192–3203. doi:10.1175/MWR-D-15-0022.1

    Article  Google Scholar 

  • Kumar A, Hoerling M (1995) Prospects and limitations of seasonal atmospheric GCM predictions. Bull Am Meteor Soc 76:335–345

    Article  Google Scholar 

  • Kumar A, Hoerling M (1997) Interpretation and implications of observed inter-El Niño variability. J Clim 10:83–91

    Article  Google Scholar 

  • Kumar A, Hoerling M (1998) Annual cycle of Pacific-North American predictability associated with different phases of ENSO. J Clim 11:3295–3308

    Article  Google Scholar 

  • Kumar A, Hoerling MP (2000) Analysis of a conceptual model of seasonal climate variability and implication for seasonal prediction. Bull Am Meteor Soc 81:255–264

    Article  Google Scholar 

  • Kumar A, Hu Z-Z (2014) How variable is the uncertainty in ENSO sea surface temperature prediction? J Clim 27:2779–2788

    Article  Google Scholar 

  • Kumar A, Murtugudde R (2013) Predictability and uncertainty: A unified perspective to build a bridge from weather to climate. Curr Opin Environ Sustain 5:327–333. doi:10.1016/j.cosust.2013.05.009

    Article  Google Scholar 

  • Kumar A, Barnston AG, Peng P, Hoerling MP, Goddard L (2000) Changes in the spread of the variability of the seasonal atmospheric states associated with ENSO. J Clim 13:3139–3151

    Article  Google Scholar 

  • Kumar A, Jha B, Zhang Q, Bounoua L (2007) A new methodology for estimating the unpredictable component of seasonal atmospheric variability. J Clim 20:3888–3901. doi:10.1175/JCLI4216.1

    Article  Google Scholar 

  • Kumar A, Jha B, L’Heureux M (2010) Are tropical SST trends changing the global teleconnection during La Niña?. Geophys Res Lett 37:L12702. doi:10.1029/2010GL043394

    Google Scholar 

  • Kumar A et al (2012) An analysis of the nonstarionarity in the bias of sea surface temperature forecasts for the NCEP Climate Forecast System (CFS) version 2. Mon Weather Rev 140:3003–3016. doi:10.1175/MWR-D-11-00335.1

    Article  Google Scholar 

  • Kumar A, Chen M, Hoerling MP, Eischeid J (2013) Do extreme climate events require extreme forcings. Geophys Res Lett 40:3440–3445. doi:10.1002/grl.50657

    Article  Google Scholar 

  • Larkin NK, Harrison DE (2002) ENSO warm (El Nino) and cold (La Nina) event lift cycles: Ocean surface anomaly patterns, their symmetries, asymmetries, and implications. J Clim 15:1118–1140. doi:10.1175/1520-0442(2002)015<1118:EWENOA>2.0.CO;2

    Article  Google Scholar 

  • Madden R A (1976) Estimates of natural variability of time-averaged sea level pressures. Mon Weather Rev 104: 942–952

    Article  Google Scholar 

  • National Research Council (2010) Assessment of Intra seasonal to Inter annual Climate Prediction and Predictability. National Academies Press, Washington DC 199 pp

    Google Scholar 

  • Nicholls N (1999) Cognitive illusions, heuristics, and climate prediction. Bull Amer Meteor Soc 80:1385–1397

    Article  Google Scholar 

  • Peng P, Kumar A (2005) A large ensemble analysis of the influence of tropical SSTs on seasonal atmospheric variability. J Clim 18:1068–1085

    Article  Google Scholar 

  • Peng P, Kumar A, Wang W (2011) An analysis of seasonal predictability in coupled model forecasts. Clim Dyn 36:419–430

    Article  Google Scholar 

  • Peng P, Kumar A, Halpert M S, Barnston A (2012) An analysis of CPC’s operational seasonal outlooks. Weather Forecast 26:898–917

    Article  Google Scholar 

  • Rasmusson E, Carpenter T (1982) Variations in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation/EL Nino. Mon Weather Rev 110:354–384. doi:10.1175/1520-0493(1982)110<0354:VITTSST>2.0.CO;2

    Article  Google Scholar 

  • Ropelewski C F, Halper M S (1987) Global and regional scale precipitation patterns associated with the El Nino/Southern Oscillation. Mon Weather Rev 115:1606–1626

    Article  Google Scholar 

  • Ropelewski CF, Halpert MS (1986) North America precipitation and temperature associated with the El Nino/Southern Oscillation (ENSO). Mon Weather Rev 114: 2352–62

    Article  Google Scholar 

  • Ropelewskil CF, Halpert MS (1989) Precipitation patterns associated with the high index phase of the Southern Oscillation. J Clim 2:268–284

    Article  Google Scholar 

  • Saha S et al (2010) The NCEP climate forecast system reanalysis. Bull Am Meteor Soc 91:1015–1057. doi:10.1175/2010BAMS3001.1

    Article  Google Scholar 

  • Saha S et al (2014) The NCEP climate forecast system version 2. J Clim 27:2185–2208. doi:10.1175/JCLI-D-12-00823.1

    Article  Google Scholar 

  • Sardeshmukh PD, Compo GP, Penland C (2000) Changes of probability associated with EL Niño. J Clim 13:4268–4286

    Article  Google Scholar 

  • Seager R et al (2015) Causes of the 2011–2014 California Drought. J Clim 28:6997–7024. doi:10.1175/JCLI-D-14-00860.1

    Article  Google Scholar 

  • Shukla J, Wallace M (1983) Numerical simulation of the atmospheric response to equatorial Pacific seas surface temperature anomalies. J Atmos Sci 40:1613–1630

    Article  Google Scholar 

  • Trenberth EK, Branstrator QW, Karoly D, Kumar A, Lau N-C, Ropelewski C (1998) Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperature. J Geophys Res 103(C7):14291–14324

    Article  Google Scholar 

  • Weaver SJ, Kumar A, Chen M (2014) Recent increases in extreme temperature occurrence over land. Geophys Res Lett 41:4669–4675. doi:10.1002/2014GL060300

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Climate Prediction Center, NCEP/NWS/NOAA, 5830 University Research Court, College Park, MD, 20740, USA

    Arun Kumar & Mingyue Chen

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  1. Arun Kumar
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  2. Mingyue Chen
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Correspondence to Mingyue Chen.

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Kumar, A., Chen, M. What is the variability in US west coast winter precipitation during strong El Niño events?. Clim Dyn 49, 2789–2802 (2017). https://doi.org/10.1007/s00382-016-3485-9

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  • DOI: https://doi.org/10.1007/s00382-016-3485-9

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