Skip to main content

Advertisement

SpringerLink
Log in

The utility of seasonal hindcast database for the analysis of climate variability: an example

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

The purpose of this paper is to elucidate a potential use of the large samples of seasonal means that hindcasts provide for investigating different aspects of climate variability. This use of hindcasts complements their traditional uses in bias correction, real-time forecast calibration, and prediction skill assessment. For seasonal hindcast data from NCEP CFSv2 we show that a sample size 5208 for each target season is achievable. To demonstrate the utility of the proposed concept, we use this large sample dataset to illustrate how it could be used in documenting spatial variability in various moments of seasonal mean precipitation PDF over the US, and further, quantify nuances in the variations in precipitation PDF at different geographical locations with the amplitude of ENSO SSTs. It is our hope that analysis presented in this paper will accelerate utilization of seasonal hindcast datasets in furthering our understanding of different aspects of climate variability. With the advantage of the large sample size, we demonstrated that the precipitation PDF at the each grid of the CONUS can be represented by gamma distribution for a more concise and effective way to summarize precipitation variability. The availability of the large sample dataset also allowed us to analyze the statistical characteristic of the precipitation responses to the different amplitudes of ENSO SSTs. The results show that for strong warm events, enhancement in precipitation has larger amplitude than decrease in precipitation for cold events in the regions of Southern California and southeastern US. The variation of the precipitation signal over the other sub-regions including the southwestern US, mid-northwest, and mid-east shows more linear relationship with the ENSO SSTs. In response to anomalous ENSO SSTs, although the PDF of December–January–February seasonal mean precipitation anomaly is shifted from its climatological PDF, there is still a large overlap between precipitation PDFs for ENSO and its climatological counterpart. This uncertainty in seasonal mean outcomes of precipitation, therefore, limits the seasonal prediction skill.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • Abid MA, Kang IS, Almazroui M, Kucharski F (2015) Contribution of synoptic transients to the potential predictability of PNA circulation anomalies: El Niño versus La Niña. J Clim 28:8347–8362. doi:10.1175/JCLI-D-14-00497.1

    Article  Google Scholar 

  • Becker M, Dool HVE, Zhang Q (2014) Predictability and forecast skill in NMME. J Clim 27:5891–5906. doi:10.1175/JCLI-D-13-00597.1

    Article  Google Scholar 

  • Burgers G, Stephenson DB (1999) The “Normality” of El Niño. Geophys Res Lett 26:1027–1030

    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 

  • Dong B (2005) Asymmetry between El Niño and La Niña in a global coupled GCM with an eddy-permitting ocean resolution. J Clim 18:3373–3387

    Article  Google Scholar 

  • Frauen C, Dommenget D, Tyrrell N, Rezny M, Wales C (2014) Analysis of the nonlinearity of El Nino—Southern oscillation teleconnections. J Clim 27:6225–6244. doi:10.1175/JCLI-D-13-00757.1

    Article  Google Scholar 

  • Graham RJ et al (2011) Long-range forecasting and the global framework for climate services. Clim Res 47:47–55. doi:10.3354/cr00963

    Article  Google Scholar 

  • Griffies SM, Harrison MJ, Pacanowksi RC, Rosati A (2004) Technical guide to MOM4.GLDL Ocean Group Technical Rep. p 5337. Available online at http://www.gfdl.noaa.gov/fms

  • Groisman PY et al (1999) Changes in the probability of heavy precipitation: important indicators of climatic change. Clim Change 42:243–283

    Article  Google Scholar 

  • Hannachi A (2001) Toward a nonlinear identification of the atmospheric response to ENSO. J Clim 14:2138–2149

    Article  Google Scholar 

  • Hoerling MP, Kumar A, Zhong M (1997) El Nino, La Nina, and nonlinearity of their teleconnections. J Clim 10:1769–1786

    Article  Google Scholar 

  • Hoerling MP, Kumar A, Xu T-Y (2001) Robustness of the nonlinear climate response to ENSO’s extreme cases. J Clim 14:1277–1293

    Article  Google Scholar 

  • Husak GJ, Michaelsen J, Funk C (2006) Use of the gamma distribution to represent monthly rainfall in Africa for drought monitoring applications. Int J Climatol 27:935–944. doi:10.1002/joc.1441

    Article  Google Scholar 

  • Ison NT, Feyerherm AM, Bark LD (1971) Wet period precipitation and the gamma distributions. J Appl Meteorol 10:658–665

    Article  Google Scholar 

  • Janowiak JE, Xie P (1999) CAMS-OPI: a global satellite-rain gauge merged product for real time precipitation nonitoring application. J Clim 12:3335–3342

    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 height with ENSO SSTs. J Clim 22:1412–1423

    Article  Google Scholar 

  • Kirtman BP et al (2014) The North American Multi-Model Ensemble (NMME): phase-1 seasonal-to-interannual precipitation, phase-2 toward developing intra-seasonal precision. Bull Am Meteorol Soc 95:585–601. doi:10.1175/BAMS-D-12-000050.1

    Article  Google Scholar 

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

    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 

  • Phelps M, Kumar A, O’Brien J (2004) Potential predictability in the NCEP CPC dynamical seasonal forecast system. J Clim 17:3775–3785

    Article  Google Scholar 

  • Ropelewski CF, Halpert MS (1986) North American precipitation and temperature patterns associated with the El Nino/Southern Oscillation (ENSO). Mon Weather Rev 114:2352–2362

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Ropelewski CF, Janowiak JE, Halper MS (1985) The analysis and display of real-time surface climate data. Mon Weather Rev 113:1101–1106

    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 

  • Straus DM, Shukla J (2002) Does ENSO force the PNA? J Clim 15:2340–2358

    Article  Google Scholar 

  • Ting M, Wang H (1997) Summertime U.S. precipitation variability and its relation to Pacific sea surface temperature. J Clim 10:1853–1873

    Article  Google Scholar 

  • Tippett MK, Kleeman R, Tang Y (2004) Measuring the potential utility of seasonal climate predictions. Geophys Res Lett 31:L22201. doi:10.1029/2004GL021575

    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 

  • Wilks DS (1995) Statistical methods in the atmospheric sciences: an introduction. Academic Press, San Diego

    Google Scholar 

  • Wittenberg AT (2009) Are historical records sufficient to constrain ENSO simulations? Geophys Res Lett 36:L12702. doi:10.1029/2009GL038710

    Article  Google Scholar 

  • Yuan X, Wood E (2012) Downscaling precipitation or bias-correcting streamflow? Some implications for coupled general circulation model (CGCM)-based ensemble seasonal hydrologic forecast. Water Resour Res 48:w12519. doi:10.1029/2012WR012256

    Article  Google Scholar 

  • Yuan X, Wood E, Roundy JK, Pan M (2013) CFSv2-based seasonal hydroclimatic forecasts over the conterminous United States. J Clim 26:4828–4847. doi:10.1175/JCLI-D-12-00683.1

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Climate Prediction Center, National Centers for Environmental Prediction, National Oceanic and Atmospheric Administration, CPC/NCEP, RM#3011, W/NP52, 5830 University Research Court, College Park, MD, 20740-3818, USA

    Mingyue Chen & Arun Kumar

Authors
  1. Mingyue Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arun Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mingyue Chen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, M., Kumar, A. The utility of seasonal hindcast database for the analysis of climate variability: an example. Clim Dyn 48, 265–279 (2017). https://doi.org/10.1007/s00382-016-3073-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-016-3073-z

Keywords

Search

Navigation