• Barnston, A. G., and T. M. Smith, 1996: Specification and prediction of global surface temperature and precipitation from global SST using CCA. J. Climate, 9, 26602697, https://doi.org/10.1175/1520-0442(1996)009<2660:SAPOGS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barsugli, J. J., and P. D. Sardeshmukh, 2002: Global atmospheric sensitivity to tropical SST anomalies throughout the Indo-Pacific basin. J. Climate, 15, 34273442, https://doi.org/10.1175/1520-0442(2002)015<3427:GASTTS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Becker, E., and H. van den Dool, 2016: Probabilistic seasonal forecasts in the North American Multimodel Ensemble: A baseline skill assessment. J. Climate, 29, 30153026, https://doi.org/10.1175/JCLI-D-14-00862.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bond, N. A., M. F. Cronin, H. Freeland, and N. Mantua, 2015: Causes and impacts of the 2014 warm anomaly in the NE Pacific. Geophys. Res. Lett., 42, 34143420, https://doi.org/10.1002/2015GL063306.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, M., and A. Kumar, 2015: Influence of ENSO SSTs on the spread of the probability density function for precipitation and land surface temperature. Climate Dyn., 45, 965974, https://doi.org/10.1007/s00382-014-2336-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, M., W. Wang, and A. Kumar, 2010: Prediction of monthly mean temperature: The roles of atmospheric and land initial condition and sea surface temperature. J. Climate, 23, 717725, https://doi.org/10.1175/2009JCLI3090.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DelSole, T., and J. Shukla, 2006: Specification of wintertime North American surface temperature. J. Climate, 19, 26912716, https://doi.org/10.1175/JCLI3704.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., A. S. Phillips, C. Bourdette, and H. Teng, 2012: Uncertainty in climate change projections: The role of internal variability. Climate Dyn., 38, 527546, https://doi.org/10.1007/s00382-010-0977-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dole, R., and et al. , 2014: The making of an extreme event: Putting the pieces together. Bull. Amer. Meteor. Soc., 95, 427440, https://doi.org/10.1175/BAMS-D-12-00069.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guo, P., P. A. Dirmeyer, and T. DelSole, 2011: Land surface impacts on subseasonal and seasonal predictability. Geophys. Res. Lett., 38, L24812, https://doi.org/10.1029/2011GL049945.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hartmann, D. L., 2015: Pacific sea surface temperature and the winter of 2014. Geophys. Res. Lett., 42, 18941902, https://doi.org/10.1002/2015GL063083.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoerling, M., and A. Kumar, 2002: Atmospheric response patterns associated with tropical forcing. J. Climate, 15, 21842203, https://doi.org/10.1175/1520-0442(2002)015<2184:ARPAWT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoerling, M., and et al. , 2013: Anatomy of an extreme event. J. Climate, 26, 28112832, https://doi.org/10.1175/JCLI-D-12-00270.1.

  • Horel, J. D., and J. M. Wallace, 1981: Planetary-scale atmospheric phenomenon associated with the Southern Oscillation. Mon. Wea. Rev., 109, 20802092, https://doi.org/10.1175/1520-0493(1981)109<2080:ARPCAO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, Z.-Z., A. Kumar, and B. Huang, 2012: An analysis of forced and internal variability in a warmer climate in CCSM3. J. Climate, 25, 23562373, https://doi.org/10.1175/JCLI-D-11-00323.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, Z.-Z., A. Kumar, B. Jha, J. Zhu, and B. Huang, 2017: Persistence and predictions of the remarkable warm anomaly in the northeastern Pacific Ocean during 2014–16. J. Climate, 30, 689702, https://doi.org/10.1175/JCLI-D-16-0348.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Janowiak, J. E., and P. Xie, 1999: CAMS-OPI: A global satellite-rain gauge merged product for real-time precipitation monitoring applications. J. Climate, 12, 33353342, https://doi.org/10.1175/1520-0442(1999)012<3335:COAGSR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jha, B., A. Kumar, and Z.-Z. Hu, 2018: An update on the estimate of predictability of seasonal mean atmospheric variability using North American Multi-Model Ensemble. Climate Dyn., https://doi.org/10.1007/s00382-016-3217-1, in press.

    • Search Google Scholar
    • Export Citation
  • Kirtman, B. P., and et al. , 2014: The North American Multimodel Ensemble: Phase-1 seasonal-to-interannual prediction; phase-2 toward developing intraseasonal prediction. Bull. Amer. Meteor. Soc., 95, 585601, https://doi.org/10.1175/BAMS-D-12-00050.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. P. Hoerling, 1995: Prospects and limitations of seasonal atmospheric GCM predictions. Bull. Amer. Meteor. Soc., 76, 335345, https://doi.org/10.1175/1520-0477(1995)076<0335:PALOSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. Hoerling, 1997: Interpretation and implications of observed inter-El Niño variability. J. Climate, 10, 8391, https://doi.org/10.1175/1520-0442(1997)010<0083:IAIOTO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. Hoerling, 1998: Annual cycle of Pacific–North American seasonal predictability associated with different phase of ENSO. J. Climate, 11, 32953308, https://doi.org/10.1175/1520-0442(1998)011<3295:ACOPNA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., and R. Murtugudde, 2013: Predictability, uncertainty and decision making: A unified perspective to build a bridge from weather to climate. Curr. Opin. Environ. Sustainability, 5, 327333, https://doi.org/10.1016/j.cosust.2013.05.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., and H. Wang, 2015: On the potential of extratropical SST anomalies for improving climate predictions. Climate Dyn., 44, 25572569, https://doi.org/10.1007/s00382-014-2398-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. Chen, 2015: Inherent predictability, requirements on the ensemble size, and complementarity. Mon. Wea. Rev., 143, 31923203, https://doi.org/10.1175/MWR-D-15-0022.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. Chen, 2017: What is the variability in US west coast winter precipitation during strong El Niño events? Climate Dyn., 49, 27892802, https://doi.org/10.1007/s00382-016-3485-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., A. G. Barnston, P. Peng, M. P. Hoerling, and L. Goddard, 2000: Changes in the spread of the variability of the seasonal mean atmospheric states associated with ENSO. J. Climate, 13, 31393151, https://doi.org/10.1175/1520-0442(2000)013<3139:CITSOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., B. Jha, Q. Zhang, and L. Bounoua, 2007: A new methodology for estimating the unpredictable component of seasonal atmospheric variability. J. Climate, 20, 38883901, https://doi.org/10.1175/JCLI4216.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., B. Jha, and M. L’Heureux, 2010: Are tropical SST trends changing the global teleconnection during La Niña? Geophys. Res. Lett., 37, L12702, https://doi.org/10.1029/2010GL043394.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., M. Chen, L. Zhang, W. Wang, Y. Xue, C. Wen, L. Marx, and B. Huang, 2012: An analysis of the nonstarionarity in the bias of sea surface temperature forecasts for the NCEP Climate Forecast System (CFS) version 2. Mon. Wea. Rev., 140, 30033016, https://doi.org/10.1175/MWR-D-11-00335.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., M. Chen, M. P. Hoerling, and J. Eischeid, 2013: Do extreme climate events require extreme forcings. Geophys. Res. Lett., 40, 34403445, https://doi.org/10.1002/grl.50657.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lau, N.-C., 1997: Interaction between global SST anomalies and midlatitude atmospheric circulation. Bull. Amer. Meteor. Soc., 78, 2124, https://doi.org/10.1175/1520-0477(1997)078<0021:IBGSAA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Livezey, R. E., M. Masutani, A. Leetmaa, H. Rui, M. Ji, and A. Kumar, 1997: Teleconnective response of the Pacific–North American region atmosphere to large central equatorial Pacific SST anomalies. J. Climate, 10, 17871820, https://doi.org/10.1175/1520-0442(1997)010<1787:TROTPN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Madden, R. A., 1976: Estimates of the natural variability of time-averaged sea-level pressure. Mon. Wea. Rev., 104, 942952, https://doi.org/10.1175/1520-0493(1976)104<0942:EOTNVO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • National Research Council, 2010: Assessment of Intra-Seasonal to Inter-Annual Climate Prediction and Predictability. National Academics Press, 199 pp.

  • Paek, H., J.-Y. Yu, and C. Qian, 2017: Why were the 2015/2016 and 1997/1998 extreme El Niños different? Geophys. Res. Lett., 44, 18481856, https://doi.org/10.1002/2016GL071515.

    • Search Google Scholar
    • Export Citation
  • Peng, P., and A. Kumar, 2005: A large ensemble analysis of the influence of tropical SSTs on seasonal atmospheric variability. J. Climate, 18, 10681085, https://doi.org/10.1175/JCLI-3314.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peng, P., A. Kumar, and W. Wang, 2011: An analysis of seasonal predictability in coupled model forecasts. Climate Dyn., 36, 637648, https://doi.org/10.1007/s00382-009-0711-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peng, P., A. G. Barnston, and A. Kumar, 2013: A comparison of skill between two versions of the NCEP Climate Forecast System (CFS) and CPC’s operational short-lead seasonal outlooks. Wea. Forecasting, 28, 445462, https://doi.org/10.1175/WAF-D-12-00057.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Quan, X., M. Hoerling, L. Smith, J. Perlwitz, T. Zhang, A. Hoell, K. Wolter, and J. Eischeid, 2018: Extreme California rains during winter 2015/16: A change in El Niño teleconnection? Bull. Amer. Meteor. Soc., 99 (Suppl)., https://doi.org/10.1175/BAMS-D-17-0118.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey, and M. G. Schlax, 2007: Daily high-resolution-blended analyses for sea surface temperature. J. Climate, 20, 54735496, https://doi.org/10.1175/2007JCLI1824.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Robinson, W., 2000: Review of WETS—The Workshop on Extra-Tropical SST anomalies. Bull. Amer. Meteor. Soc., 81, 567577, https://doi.org/10.1175/1520-0477(2000)081<0567:ROWTWO>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ropelewski, C. F., and M. S. Halpert, 1986: North America precipitation and temperature associated with the El Niño/Southern Oscillation (ENSO). Mon. Wea. Rev., 114, 23522362, https://doi.org/10.1175/1520-0493(1986)114<2352:NAPATP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ropelewski, C. F., and M. S. Halpert, 1987: Global and regional scale precipitation patterns associated with the El Niño/Southern Oscillation. Mon. Wea. Rev., 115, 16061626, https://doi.org/10.1175/1520-0493(1987)115<1606:GARSPP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ropelewski, C. F., and M. S. Halpert, 1989: Precipitation patterns associated with the high index phase of the Southern Oscillation. J. Climate, 2, 268284, https://doi.org/10.1175/1520-0442(1989)002<0268:PPAWTH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saha, S., and et al. , 2010: The NCEP Climate Forecast System Reanalysis. Bull. Amer. Meteor. Soc., 91, 10151057, https://doi.org/10.1175/2010BAMS3001.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saha, S., and et al. , 2014: The NCEP Climate Forecast System version 2. J. Climate, 27, 21852208, https://doi.org/10.1175/JCLI-D-12-00823.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., M. Hoerling, S. Schubert, H. Wang, B. Lyon, A. Kumar, J. Nakamura, and N. Henderson, 2015: Causes of the 2011–14 California drought. J. Climate, 28, 69977024, https://doi.org/10.1175/JCLI-D-14-00860.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shukla, J., and M. Wallace, 1983: Numerical simulation of the atmospheric response to equatorial Pacific sea surface temperature anomalies. J. Atmos. Sci., 40, 16131630, https://doi.org/10.1175/1520-0469(1983)040<1613:NSOTAR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Siler, N, Y. Kosaka, S.-P. Xie, and X. Li, 2017: Tropical ocean contributions to California’s surprisingly dry El Niño of 2015/16. J. Climate, 30, 10 06710 079, https://doi.org/10.1175/JCLI-D-17-0177.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tippett, M. K., R. Kleeman, and Y. Tang, 2004: Measuring the potential utility of seasonal climate prediction. Geophys. Res. Lett., 31, L22201, https://doi.org/10.1029/2004GL021575.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., G. W. Branstrator, D. Karoly, A. Kumar, N.-C. Lau, and C. Ropelewski, 1998: Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J. Geophys. Res., 103, 14 29114 324, https://doi.org/10.1029/97JC01444.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, W., and A. Kumar, 1998: A GCM assessment of atmospheric seasonal predictability associated with soil moisture anomalies over North America. J. Geophys. Res., 103, 28 63728 646, https://doi.org/10.1029/1998JD200010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weisheimer, A., N. Schaller, C. O’Reilly, D. A. MacLeod, and T. N. Palmer, 2017: Atmospheric seasonal forecasts of the twentieth century: Multi-decadal variability in predictive skill of the winter North Atlantic Oscillation (NAO) and their potential for extreme event attribution. Quart. J. Roy. Meteor. Soc., 143, 917926, https://doi.org/10.1002/qj.2976.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, Y., M. Chen, A. Kumar, Z.-Z. Hu, and W. Wang, 2013: Prediction skill and bias of tropical Pacific seas surface temperature in the NCEP Climate Forecast System version 2. J. Climate, 26, 53585378, https://doi.org/10.1175/JCLI-D-12-00600.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 66 66 8
PDF Downloads 51 51 4

Winter 2015/16 Atmospheric and Precipitation Anomalies over North America: El Niño Response and the Role of Noise

View More View Less
  • 1 Climate Prediction Center, NOAA/NWS/NCEP, College Park, Maryland
© Get Permissions
Restricted access

Abstract

The possible causes for the observed winter 2015/16 precipitation anomalies, which were opposite to the mean El Niño signal over the U.S. Southwest, are analyzed based on the ensemble of forecasts from the NCEP Climate Forecast System, version 2 (CFSv2). The analysis focuses on the role of anomalous sea surface temperature (SST) forcing and the contributions of atmospheric internal variability. The model-predicted ensemble mean forecast for December–January–February 2015/16 (DJF 2015/16) North American atmospheric anomalies compared favorably with the El Niño composite, although some difference existed. The predicted pattern was also like that in the previous strong El Niño events of 1982/83 and 1997/98. Therefore, the model largely predicted the teleconnection and precipitation response pattern in DJF 2015/16 like the mean El Niño signal. The observed negative precipitation anomalies over the U.S. Southwest in DJF 2015/16 were not consistent either with the observed or with the model-predicted El Niño composite. Analysis of the member-to-member variability in the ensemble of forecast anomalies allowed quantification of the contribution of atmospheric internal variability in shaping seasonal mean anomalies. There were considerable variations in the outcome of DJF 2015/16 precipitation over North America from one forecast to another even though the predicted SSTs were nearly identical. The observed DJF 2015/16 precipitation anomalies were well within the envelope of possible forecast outcomes. Therefore, the atmospheric internal variability could have played a considerable role in determining the observed DJF 2015/16 negative precipitation anomalies over the U.S. Southwest, and its role is discussed in the context of differences in response.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/MWR-D-17-0116.s1.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Mingyue Chen, mingyue.chen@noaa.gov

Abstract

The possible causes for the observed winter 2015/16 precipitation anomalies, which were opposite to the mean El Niño signal over the U.S. Southwest, are analyzed based on the ensemble of forecasts from the NCEP Climate Forecast System, version 2 (CFSv2). The analysis focuses on the role of anomalous sea surface temperature (SST) forcing and the contributions of atmospheric internal variability. The model-predicted ensemble mean forecast for December–January–February 2015/16 (DJF 2015/16) North American atmospheric anomalies compared favorably with the El Niño composite, although some difference existed. The predicted pattern was also like that in the previous strong El Niño events of 1982/83 and 1997/98. Therefore, the model largely predicted the teleconnection and precipitation response pattern in DJF 2015/16 like the mean El Niño signal. The observed negative precipitation anomalies over the U.S. Southwest in DJF 2015/16 were not consistent either with the observed or with the model-predicted El Niño composite. Analysis of the member-to-member variability in the ensemble of forecast anomalies allowed quantification of the contribution of atmospheric internal variability in shaping seasonal mean anomalies. There were considerable variations in the outcome of DJF 2015/16 precipitation over North America from one forecast to another even though the predicted SSTs were nearly identical. The observed DJF 2015/16 precipitation anomalies were well within the envelope of possible forecast outcomes. Therefore, the atmospheric internal variability could have played a considerable role in determining the observed DJF 2015/16 negative precipitation anomalies over the U.S. Southwest, and its role is discussed in the context of differences in response.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/MWR-D-17-0116.s1.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Mingyue Chen, mingyue.chen@noaa.gov

Supplementary Materials

    • Supplemental Materials (DOCX 254.47 KB)
Save