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by Anthony Barnston
Washington DC (SPX) Aug 21, 2014
In our post last month, we introduced and defined several climate patterns other than ENSO that impact United States winter climate. But how useful are these climate patterns in predicting U.S. temperature and precipitation in winter and other seasons? How do they stack up against ENSO, for example?
In the U.S. the average warming was most pronounced during the 1980s and 1990s, and has plateaued since around the turn of the century. This plateau has been most pronounced during winter, slight cooling has even been observed in some regions (Cohen et al. 2012).
During the periods of most rapid warming, forecasts for above normal temperature were often skillful no matter what the ENSO situation was, although ENSO continued to show its familiar winter pattern superimposed over warming conditions. Climate forecasters monitor trends over the recent 10 to 15 years at each location and each season (1), factoring them into their forecasts along with statistical and dynamical climate prediction models.
The North Atlantic Oscillation (NAO)/ Arctic Oscillation (AO)
A problem with the NAO/AO is that while its winter climate effects are strong and well known over the eastern U.S., until recently the pattern itself has generally been considered to be poorly predicted and commonly considered a "wild card" by climate forecasters-in sharp contrast to ENSO.
Recently, there has been research suggesting there may be some predictability for the wintertime NAO/AO (Riddle et al. 2013; Kang et al. 2014; Scaife et al. 2014), though the possible factors leading to this skill are hotly debated.
Such possible factors are the extent of Siberian snow cover in the preceding autumn, Arctic sea ice, and Atlantic or Pacific sea surface temperatures. It is also possible that the apparent wintertime seasonal skill of the NAO/AO is arising by chance and there are no significant skill sources (e.g. DelSole and Shukla 2009).
Pacific Decadal Oscillation (PDO)
Consistent with this, a recent study (Lyon et al. 2013) has implicated a PDO-like pattern in the recent persistent drought in the Southwest U.S., at least during spring. The PDO was in positive phase during 1924-1945, negative phase during 1946-1976, positive 1977-1998, and negative since 1999. The PDO pattern overlaps with the ENSO pattern in the tropical Pacific (i.e., a positive phase PDO meshes with El Nino, negative phase with La Nina).
So, while the PDO has been in negative phase in the recent decade, there has been a slight tendency toward more La Nina than El Nino events (2). A debate continues about the nature of the relationship between ENSO and the PDO, including evidence that the PDO is mostly a consequence of ENSO (Newman et al., 2003).
A recent study suggests that the climate impacts of the PDO are hard to use as a prediction for 3-month, seasonal periods, because other sources of variability, mainly faster-acting ones, easily overshadow the PDO's effect (Kumar et al 2013). This means that the PDO impact is more noticeable over longer periods (i.e., decadal, and not seasonal), or when averaged over adjacent years having the same PDO phase.
The Bottom Line
Because El Nino and La Nina events often develop during late spring or summer and last through the forthcoming winter, the effects of ENSO on U.S. winter climate can often be predicted, making for a fairly reliable source of mainly winter predictive skill in the U.S. (Ropelewski and Halpert 1986; Barnston 1994; Livezey and Timofeyeva 2008). Of course, not all El Nino and La Nina events produce the average expected effects, so the forecasts still have uncertainty.
The next most important predictable influence, mainly for temperature, is trends; these apply to all seasons. Next, the NAO/AO produces a huge influence on temperature and precipitation in the eastern half of the U.S., mainly during winter. But the NAO/AO is unable to be predicted with very much confidence.
Finally, the PDO may have its own impacts on decadal timescales, mainly in winter and spring in the southwestern U.S., but it can be difficult to distinguish its seasonal impacts in the midst of other sources of variability, and also difficult to distinguish its impacts from those of ENSO.
Today's climate models are most adept at predicting the year-to-year climate fluctuations associated with ENSO, next best at predicting trends related to climate change, and least effective in reproducing the observed changes in the NAO/AO and the decadal-scale PDO. Clearly, we have a long way to go in improving climate prediction models for seasonal timescales.
(2) Based on the Oceanic Nino Index (3-month averages in the Nino-3.4 region) historical episodes of El Nino and La Nina can be identified. In the last ten years, for example, we have seen 5 La Nina episodes and 3 El Nino episodes.
Cohen, J. L., J. C. Furtado, M. Barlow, V. A. Alexeev, and J. E Cherry, 2012: Asymmetric seasonal temperature trends. Geophys. Res. Lett., 39, 4, DOI: 10.1029/2011GL050582.
Dai, A., 2013: The influence of the inter-decadal Pacific oscillation on U.S. precipitation during 1923-2010. Clim. Dyn., 41, 633-646.
DelSole, T., and J. Shukla, 2009: Artificial skill due to predictor screening. J. Climate, 22, 331-345.
Fan, Y. and H. van den Dool, 2008: A global monthly land surface air temperature analysis for 1948-present. J. Geopohys. Res., 113, doi:10.1029/2007JD008470.
Huang, J., H. M. Van den Dool, and A. G. Barnston, 1996: Long-lead seasonal temperature prediction using optimal climate normal. J. Climate, 9, 809-817.
Kang, D, M.-I. Lee, J. Im, D. Kim, H.-M. Kim, H.-S. Kang, S. D. Schubert, A. Arribas, and C. MacLachlan, 2014, Prediction of the Arctic Oscillation in boreal winter by dynamical seasonal forecasting systems. Geophys. Res. Lett., 41, 3577-3585. doi:10.1002/2014GL060011.
Kumar, A., H. Wang, W. Wang, Y. Xue, and Z.-Z. Hu, 2013: Does knowing the oceanic PDO phase help predict the atmospheric anomalies in subsequent months? J. Climate, 26, 1268-1285.
Livezey, R. E., and M. M. Timofeyeva, 2008: The first decade of long-lead U.S. seasonal forecasts: Insights from a skill analysis. Bull.. Amer. Meteor. Soc., 89, 843-854.
Lyon, B., A.G. Barnston, and D.G. DeWitt, 2013: Tropical Pacific forcing of a 1998-99 climate shift: Observational analysis and climate model results for the boreal spring season. Climate Dyn., dpi 10.1007/s00382-013-1891-9.
Newman, Matthew, Gilbert P. Compo, Michael A. Alexander, 2003: ENSO-Forced Variability of the Pacific Decadal Oscillation. J. Climate, 16, 3853-3857.
Riddle, E. E., A. H. Butler, J. C. Furtado, J. L. Cohen, and A. Kumar, 2013: CFSv2 ensemble prediction of the wintertime Arctic Oscillation Clim. Dyn., 41, 1099-1116.
Ropelewski and Halpert, 1986: North American precipitation and temperature patterns associated with the El Nino Southern Oscillation (ENSO). Mon. Wea. Rev., 114, 2352-2362.
Scaife, A. A., and Coauthors, 2014: Skillful long range prediction of European and North America winters. Geophy. Res. Lett., 41, 2514-2519. DOI: 10.1002/2014GL059637.
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