PUBLICATIONS
Geophysical Research Letters
RESEARCH LETTER
10.1002/2017GL075034
Key Points:• Observational analysis reveals distinct
evolution of atmosphericteleconnections and U.S. precipitation
anomalies during multiyear La Niña
• La Niña teleconnections remainstrong from the ﬁrst to the second NH
winter despite weakening of theequatorial Paciﬁc cooling• Large-scale atmospheric circulation
appears more sensitive to broad
tropical Paciﬁc SST anomalies thanthose intensiﬁed at the equator

Supporting Information:• Supporting Information S1
Correspondence to:Y. M. Okumura,yukoo@ig.utexas.edu

Citation:
Okumura, Y. M., DiNezio, P., & Deser, C.
(2017). Evolving impacts of multiyear La
Niña events on atmospheric circulationand U.S. drought. Geophysical Research
Letters, 44, 11,614–11,623. https://doi.
org/10.1002/2017GL075034
Received 21 JUL 2017
Accepted 13 OCT 2017
Accepted article online 20 OCT 2017
Published online 27 NOV 2017

Evolving Impacts of Multiyear La Niña Eventson Atmospheric Circulation and U.S. Drought
Yuko M. Okumura1, Pedro DiNezio1, and Clara Deser2

1

Institute for Geophysics, Jackson School of Geosciences, University of Texas at Austin, Austin, TX, USA, 2Climate and Global
Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA

Abstract Wintertime precipitation over the southern U.S. is known to decrease with interannual cooling of
the equatorial Paciﬁc associated with La Niña, which often persists 2 years or longer. Composite analysis
based on a suite of observational and reanalysis data sets covering the period 1901–2012 reveals distinct
evolution of atmospheric teleconnections and U.S. precipitation anomalies during multiyear La Niña events.
In particular, atmospheric circulation anomalies strengthen and become more zonally elongated over the
North Paciﬁc in the second winter compared to the ﬁrst winter. U.S. precipitation deﬁcits also remain large,
while the region of reduced precipitation shifts northeastward in the second winter. This occurs despite asigniﬁcant weakening of the equatorial Paciﬁc cooling in the second winter and suggests that the large-scaleatmospheric circulation is more sensitive to tropical sea surface temperature anomalies of broader
meridional extent. Given the extended climatic impacts, accurate prediction of La Niña duration is crucial.

1. Introduction
The El Niño–Southern Oscillation (ENSO) phenomenon in the equatorial Paciﬁc is the dominant mode of climate variability on interannual time scales (e.g., Chang et al., 2006; Neelin et al., 1998; Wallace et al., 1998;
Wang & Picaut, 2004). Warm (El Niño) and cold (La Niña) phases of ENSO typically last 1–2 years and occur
approximately every 3–8 years. Both El Niño and La Niña exhibit strong seasonality and tend to develop in lateboreal spring/summer, peaking toward the end of the calendar year. El Niño and La Niña, however, are not a
simple mirror image and exhibit asymmetry in their spatial pattern and seasonal evolution, especially for strong
events, because of nonlinearities in the tropical ocean-atmosphere system (e.g., Burgers & Stephenson, 1999;
DiNezio & Deser, 2014; Dommenget et al., 2013; Hoerling et al., 1997; Hu et al., 2014; Kang & Kug, 2002;
Kessler, 2002; McGregor et al., 2013; McPhaden & Zhang, 2009; Ohba & Ueda, 2009; Okumura & Deser, 2010).
In particular, El Niño events tend to decay rapidly after the mature phase, but many La Niña events persist
through the following year and reintensify in the subsequent winter (Okumura & Deser, 2010).
The equatorial Paciﬁc sea surface temperature (SST) cooling associated with La Niña has been linked to wintertime precipitation deﬁcits over the southern U.S. (e.g., Dai et al., 1998; Kiladis & Diaz, 1989; Lau & Sheu,
1988; Mo & Schemm, 2008; Ropelewski & Halpert, 1989) (see Seager & Hoerling, 2014 and Schubert et al.,2016 for recent synthesis studies). The SST cooling suppresses atmospheric deep convection in the equatorial
Paciﬁc, and the related change in atmospheric heating forces a large-scale atmospheric Rossby wave into theNorthern Hemisphere (NH), displacing the subtropical jet and storm track to the north over the Paciﬁc andNorth America (e.g., Trenberth et al., 1998). The northward shift of storm track leads to a reduction in transientmoisture ﬂux convergence across the southern tier of the U.S. (Seager, Harnik, et al., 2005; Wang & Schubert,2014). Previous studies of La Niña teleconnections, however, did not distinguish between single-year andmultiyear events, and it is not clear how multiyear La Niña affects the evolution of atmospheric teleconnections and U.S. precipitation during the course of these events. It is crucial to understand the evolving impactsof multiyear La Niña events given their potential linkages to prolonged droughts and associated socioeconomic impacts (e.g., Cole et al., 2002; Hoerling & Kumar, 2003; Seager, Kushnir, et al., 2005).

©2017. American Geophysical Union.
All Rights Reserved.

OKUMURA ET AL.

The present study investigates the atmospheric teleconnections from the tropical Paciﬁc during the ﬁrst andsecond NH winters of multiyear La Niña events and their impacts on U.S. precipitation, using a suite of observational and reanalysis data sets covering the period 1901–2012. Atmospheric model experiments are also
compared with the observational results. Section 2 describes the data and methods used in this study.
Results from the observational analysis of multiyear La Niña events are reported in section 3. Section 4summarizes the main results and discusses the outstanding issues for future investigation.

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2. Data and Methods
In this study multiyear La Niña events are deﬁned based on monthly SST anomalies averaged in the Niño-3.4
region (5°S–5°N, 120°–170°W; the Niño-3.4 index) from the Hadley Centre Sea Ice and SST (HadISST) data set(Rayner et al., 2003) for 1900–2016. The monthly Niño-3.4 index is linearly detrended and smoothed with a
3 month running mean ﬁlter prior to deﬁning La Niña events. We denote the year when La Niña ﬁrst develops
as year 0 and the subsequent year as year 1. During multiyear La Niña events, equatorial SST cooling intensiﬁes every boreal winter and peak cooling often weakens after the ﬁrst winter. We identify a multiyear La
Niña event when the Niño-3.4 index falls below 0.75 standard deviations in any month during October(0) to February (1) and remains below 0.5 standard deviations in any month during October (1) toFebruary (2). (The standard deviation is calculated separately for each month.) Based on this criterion, we
identify 10 multiyear La Niña events between 1900 and 2016 (1908, 1916, 1949, 1954, 1970, 1973, 1983,
1998, 2007, and 2010 as year 0). Figure S1 in the supporting information shows the Niño-3.4 index and theselection of multiyear La Niña events. About half of all La Niña events last longer than 2 years. Composite evolution of the Niño-3.4 index for multiyear La Niña events is presented in Figure S2.
We form seasonal composites of SST, precipitation, and atmospheric circulation anomalies for the 10 multiyear La Niña events, using SSTs from HadISST on a 1° grid, terrestrial precipitation from the Global
Precipitation Climatology Centre (GPCC) version 7 on a 1.0° grid (Schneider et al., 2016), and sea level pressure(SLP), 200 hPa geopotential height (Z200) and zonal wind (U200), and precipitation from the TwentiethCentury Reanalysis (20CR) version 2 on a 2° grid (Compo et al., 2011). Monthly anomalies of these variables
are calculated for the common data period of 1901–2012 and linearly detrended prior to the analysis. It isnoted that the results of composite analysis are not affected by decadal variability that is present in thedetrended data. To reduce aliasing from subseasonal variability, the anomalies are averaged over extended
NH cold (November–April) and warm (May–October) seasons. Statistical signiﬁcance of the composite
anomalies is evaluated through a two-tailed t test at the 90% conﬁdence level. We also examine the robustness of the composites based on physical consistency between the different ﬁelds and whether the composites are replicated in different subsets and random samples of the events and in different data sets (National
Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis(Kalnay et al., 1996) for 1948–2012 and the National Oceanic and Atmospheric Administration (NOAA) optimum interpolation SST (OISST) version 2 (Reynolds et al., 2002) and the European Centre for MediumRange Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) (Dee et al., 2011) for 1982–2012). The
observational analysis is also compared with atmospheric model simulations forced with observed SSTs
(Hurrell et al., 2008; Huang et al., 2015) using the Community Atmosphere Model (CAM) versions 4 and 5(Hurrell et al., 2013) and the Geophysical Fluid Dynamics Laboratory (GFDL) Atmosphere Model version 2.1(AM2.1) (Li et al., 2010) (Text S1).

3. Results
Figure 1 shows composite anomalies of SST, SLP, terrestrial precipitation, and U200 for the ﬁrst and second
cold seasons of 10 multiyear La Niña events during 1901–2012. The main features of the teleconnection patterns are similar between the ﬁrst and second cold seasons. In both years, SLP increases over the central
North Paciﬁc in association with the tropical Paciﬁc SST cooling, weakening the wintertime Aleutian low.
SST warming on the southern ﬂank of this anomalous high pressure is consistent with inferred reduction
in surface winds. Over the U.S., upper tropospheric zonal wind anomalies show a meridional dipole pattern,indicative of a weakening and northward shift of the subtropical westerly jet. In association with theweakened westerly winds in the upper troposphere, precipitation decreases across the southern tier of the
U.S. These main features of cold season composite anomalies are statistically signiﬁcant at the 90%
conﬁdence level in both the ﬁrst and second years (Figures S3 and S4). During the warm season, on the other
hand, U.S. precipitation anomalies are not as large and geographically coherent as those for the cold season(Figure S5) and the lack of statistical signiﬁcance suggests limited predictability. Thus, we focus on theanalysis of cold season anomalies in the rest of the paper.
The composite analysis of cold season anomalies reveals not only the similarities but also notable differences
between the ﬁrst and second years of multiyear La Niña events (Figure 1). First, the peak SST cooling in thecentral equatorial Paciﬁc (150°W–180°) weakens by 28% ( 1.25 to 0.90°C) from the ﬁrst to the second cold
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Figure 1. Observed ocean-atmosphere anomaly patterns during the ﬁrst and second cold seasons of a composite
1
multiyear La Niña event. (a and b) SST (shading over the ocean, °C), terrestrial precipitation (shading over land, mm d ),and SLP (contours at intervals of 0.5 hPa) anomalies over the Paciﬁc-North American sector and (c and d) terrestrial
1
1
precipitation (shading over land, mm d ) and U200 (contours at intervals of 1 m s ) anomalies over the U.S. for
November (0) to April (1) (Figures 1a and 1c) and November (1) to April (2) (Figures 1b and 1d). Based on the HadISST, GPCC,
and 20CR data sets for 1901–2012.

season whereas it remains largely unchanged in the off-equatorial region of the tropical Paciﬁc (cf. Figure 2d).
The weaker equatorial SST cooling in the second year may be attributed to a slow recharge of the equatorial
ocean heat content and resultant weakening of the thermocline feedback (Choi et al., 2013; DiNezio & Deser,
2014; Nagura et al., 2008). Despite the signiﬁcant weakening of the equatorial cooling, both the North Paciﬁc
SLP and SST responses strengthen and show more zonally elongated patterns in the second year comparedto the ﬁrst year. Also, the precipitation reductions over the southern U.S. remain of similar amplitude in thetwo cold seasons, although they shift eastward and northward, consistent with a northeastward shift of
the anomalous easterly winds in the upper troposphere. The eastward shift of the region of reduced
precipitation is also associated with a change in sign of the local SLP response. La Niña’s impacts on North
Paciﬁc SST and SLP and southeastern U.S. precipitation become more statistically signiﬁcant in the second
cold season compared to the ﬁrst, although the differences between the 2 years are only marginallysigniﬁcant over limited regions (Figures S3 and S4). The fact that these features of the composite analysis
described above are robust to choice of data set and sampling of events (Figures S6 and S7) suggests that
there are explicit mechanisms underlying them.
What causes the differences in teleconnection patterns between the ﬁrst and second cold seasons of multiyear La Niña events? As shown in Figure 2, suppressed precipitation and resultant diabatic cooling in theequatorial Paciﬁc induce upper tropospheric cyclonic circulation anomalies on both sides of the equatorand emanation of a Rossby wave train into the NH. In the ﬁrst year, the wave train shows the classicalPaciﬁc-North American pattern that arches from the subtropical North Paciﬁc to the southeastern U.S.
(Figure 2a). In the second year, however, Z200 anomalies become more zonally elongated and the wave train
stretches more toward the pole compared to the ﬁrst year (Figure 2b). The Z200 anomaly pattern in the second year has some projection onto the northern annular mode (e.g., Thompson & Wallace, 2000) (Figure S8).
These changes in the zonal scale and raypath of the Rossby wave response between the ﬁrst and second
years are consistent with linear wave theory (Hoskins & Ambrizzi, 1993), which shows that the raypath radiusof curvature of a Rossby wave propagating into the extratropics is proportional to its zonal wavelength. The
relative increase in zonal length scale of the Z200 anomalies in the second cold season occurs in conjunction
with a relative increase in negative precipitation anomalies over the western tropical Paciﬁc (Figure 2c).

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Figure 2. Observed atmospheric anomaly patterns during the ﬁrst and second cold seasons of a composite multiyear La
1
Niña event. Precipitation (shading, mm d ) and Z200 (contours at intervals of 10 m) anomalies over the Paciﬁc-North
American sector for (a) November (0) to April (1), (b) November (1) to April (2), and (c) their difference (the second minus theﬁrst year). Based on the 20CR data set for 1901–2012. Meridional proﬁles of observed ocean-atmosphere anomalies in
the central Paciﬁc (150°W–180°) during the ﬁrst and second cold seasons of a composite multiyear La Niña event. (d) SST
1(°C), (e) precipitation (mm d ), and (f) Z200 anomalies (m) for November (0) to April (1) (blue solid line), November(1) to April (2) (blue dashed line), and their difference (the second minus the ﬁrst year; red). Based on the HadISST and 20CR
data sets for 1901–2012.

The Rossby wave raypath change does not explain why the North Paciﬁc atmospheric circulation response
becomes stronger and the subtropical westerly jet shifts farther to the north in the second cold season compared to the ﬁrst. However, concomitant changes in the meridional proﬁles of the tropical SST and precipitation responses may help to explain these extratropical changes. The main difference in tropical Paciﬁc SST
forcing between the ﬁrst and second years is the lack of sharp equatorial cooling in the second year
(Figure 2d). The relative equatorial warming in the second year is associated with precipitation increase in
the deep tropics (Figure 2e) and Z200 anomalies with meridional scales smaller than those in the ﬁrst year
(Figure 2f). These “short wave” Z200 anomalies expand subtropical anomalies to the north and enhance
extratropical anomalies in the second year compared to the ﬁrst, displacing the subtropical westerly jet
farther to the north and strengthening the Aleutian low response.
Intriguingly, Z200 differences between the ﬁrst and second years show a zonally symmetric pattern that
extends over the North America sector (Figure 2c). Previous studies of ENSO teleconnections show that in

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Figure 3. Pattern and time series associated with the ﬁrst SVD mode of cold season tropical Paciﬁc SST (20°S–20°N,
140°E–80°W) and North Paciﬁc Z200 (10°–70°N, 130°E–70°W) anomalies. Linear regressions on the Niño-3.4 index are
removed from both ﬁelds prior to the analysis. This mode explains 61% of the total squared covariance. The expansion
coefﬁcients are correlated at a coefﬁcient of 0.67. (a) Regression map of SST (shading, °C) and Z200 (contours at intervals of
2.5 m) based on the standardized SST expansion coefﬁcient. (b) Standardized time series of SST (green) and Z200
(purple) expansion coefﬁcients. Year 0 of multiyear La Niña events are indicated by gray dashed lines. Based on the HadISST
and 20CR data sets for 1901–2012.

addition to a Rossby wave forced by zonally asymmetric tropical heating, tropical-wide tropospheric temperature changes drive zonally symmetric circulation anomalies in the extratropics via changes in transient
eddy momentum ﬂuxes (L’Heureux & Thompson, 2006; Robinson, 2002; Seager et al., 2003). In the second
year of multiyear La Niña events, the tropical Atlantic cools signiﬁcantly while the equatorial Paciﬁc warms
compared to the ﬁrst year (Figure S3c). The resultant weakening of the zonal asymmetry in tropical SST
forcing may increase the relative importance of eddy-driven teleconnections although this mechanism does
not explain the change in meridional scale of the teleconnections. Signiﬁcant changes are also found in precipitation over the tropical Indian Ocean between the ﬁrst and second years of multiyear La Niña events(Figure S3l), which may affect the North Paciﬁc atmospheric circulation as suggested by previous studies(e.g., Alexander et al., 2002; Annamalai et al., 2007; Spencer et al., 2004). These changes in meridional andzonal structure of the teleconnections are evident for different data sets and analysis periods (not shown).
Whereas the changes in teleconnection patterns between the ﬁrst and second cold seasons of multiyear La
Niña events are robust in the observational composite analysis (Figures S6 and S7), atmospheric general circulation models forced with observed SSTs have difﬁculty reproducing the observed changes (Figures S7 andS9–S11). Extratropical atmospheric circulation anomalies show zonally elongated patterns in both the ﬁrst
and second cold seasons in all the simulations, and the Aleutian low response weakens in the second year
in all but the AM2.1 simulation (Figures S7 and S9). U.S. precipitation anomalies also show similar patterns
between the ﬁrst and second years, and the northeastward expansion of negative anomalies in the second
year is not reproduced except in CAM4 (Figure S9). Compared to observations, tropical Paciﬁc precipitation
anomalies simulated in the CAM are conﬁned more to the deep tropics in both years, and the difference inprecipitation response between the ﬁrst and second years shows meridional scales similar to those for theﬁrst and second years (Figures S10 and S11). The AM2.1 and one of the CAM5 experiments simulate theobserved change in the meridional scale of tropical precipitation anomalies, but only the AM2.1 reproduces
the zonally symmetric response to equatorial warming in the second year similar to observations. Further studies are needed to better understand the mechanisms of multiyear La Niña teleconnections and the causes ofmodel deﬁciencies. The strong zonal symmetry in both the ﬁrst and second years of multiyear La Niña eventsin CAM and AM2.1 suggests that eddy-driven teleconnections may be too strong in these models.

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Figure 4. Observed ocean-atmosphere anomaly patterns during the cold season for (a) the ENSO and (b) PDV.
1
November–April SST (shading over the ocean, °C), terrestrial precipitation (shading over land, mm d ), and SLP(contours at intervals of 0.5 hPa) anomalies over the Paciﬁc-North American sector. The ENSO pattern is based on linear
regressions on the standardized Niño-3.4 index. The PDV pattern is obtained by taking differences between the positive
and negative phases of PDV ((1925–1946, 1977–1997) minus (1901–1924, 1947–1976, 1998–2012)) based on Newman et al.
(2016). The sign is reversed in both the ENSO and PDV maps for a comparison with Figure 1. Differences of observed
ocean-atmosphere anomaly patterns during the cold season between (c) the ENSO and PDV and (d) the ﬁrst and second
years of a composite multiyear La Niña event (the second minus the ﬁrst year). November–April SST (shading, °C) and
Z200 (contours at intervals of 10 m) anomalies over the Paciﬁc-North American sector. In Figure 4c, the PDV pattern ismultiplied by a factor of 2 before taking differences with the ENSO pattern to better represent a change in the meridional
structure of tropical SST anomalies. Based on the HadISST, GPCC, and 20CR data sets for 1901–2012.

Based on the comparison of observed teleconnection patterns between the ﬁrst and second cold seasons ofmultiyear La Niña events, we postulate that the large-scale atmospheric circulation is more sensitive to broad
tropical SST anomalies than those intensiﬁed at the equator. To further understand how the spatial structureof tropical SST forcing inﬂuences NH teleconnections, we conduct a singular value decomposition (SVD) analysis (Bretherton et al., 1992) of cold season tropical Paciﬁc SST (20°S–20°N, 140°E–80°W) and North Paciﬁc
Z200 (10°–70°N, 130°E–70°W) anomalies (Figure 3). Prior to the SVD analysis, we remove the component linearly related to the Niño-3.4 index from both the SST and Z200 ﬁelds via regression analysis to highlight thedeviations from average ENSO pattern. The ﬁrst SVD mode, which explains 61% of the total squared covariance, clearly indicates a linkage between the equatorial intensiﬁcation of tropical Paciﬁc SST anomalies
and a zonally symmetric pattern of Z200 anomalies that has a meridional scale smaller than typical ENSO teleconnections (cf. Figure 2a). This mode shows that weaker amplitude SST cooling along the equator relative
to the subtropics (i.e., warming along the equator relative to off the equator) is associated with a decrease in
Z200 in the subtropics and an increase in midlatitudes across the Paciﬁc basin, consistent with the composite
analysis of multiyear La Niña teleconnections (Figure 4d). Similar Z200 and SST patterns appear as the ﬁrst
and second leading empirical orthogonal function modes of their individual ﬁelds, respectively (not shown).
The equatorward SST gradient associated with the SVD mode is also accompanied by precipitation increasein the central equatorial Paciﬁc and decrease over the Indo-Paciﬁc warm pool (Figure S12) as in the composite
analysis of multiyear La Niña (Figures 2c and S3l). The SST and Z200 expansion coefﬁcients of this SVD mode
are correlated at a coefﬁcient of 0.67, and both increase from the ﬁrst to the second year of a composite multiyear La Niña event although there are large variations among events (Figure 3b).
The SST and Z200 expansion coefﬁcients of the ﬁrst SVD mode exhibit distinct interdecadal variability withpredominantly negative phases from the mid-1920s to the mid-1940s and after the early 1980s and a

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positive phase between them (Figure 3b), roughly corresponding to the known phases of Paciﬁc decadal
variability (PDV) (e.g., Chen & Wallace, 2015; Deser et al., 2004; Garreaud & Battisti, 1999; Newman et al.,2016). As discussed by many previous studies, PDV shows a broader meridional structure of tropical Paciﬁc
SST anomalies than ENSO due to the absence of a narrow equatorial maximum. Figures 4a and 4b compare
the observed ENSO and PDV anomaly patterns of SST, SLP, and terrestrial precipitation for the NH coldseason. Despite much weaker equatorial SST anomalies, North Paciﬁc SLP and SST anomalies are large andmore zonally elongated for PDV compared to ENSO, similar to Figures 1a and 1b for multiyear La Niña events.
The differences in SST and Z200 anomaly patterns between the ENSO and PDV (Figure 4c) are also similar tothe differences between the ﬁrst and second years of multiyear La Niña events (Figure 4d) and to the leading
SVD pattern (Figure 3a) over the North Paciﬁc, although the zonal symmetry of Z200 anomalies is lesspronounced in the PDV-ENSO and SVD patterns. Thus, the mechanisms that modulate the teleconnection patterns between the ﬁrst and second cold seasons of multiyear La Niña events may also explain the differences
between the ENSO and PDV anomaly patterns. In support of this notion, the result of SVD analysis is insensitive
to temporal ﬁltering of the data (not shown). It should be noted, however, that the causality of tropical andextratropical anomalies for PDV remains subject to debate (e.g., Liu, 2012; Newman et al., 2016; Okumura,2013). Unlike ENSO, in which extratropical ocean-atmosphere anomalies are primarily driven by tropical SSTs,
stochastic atmospheric forcing in the extratropics may play a more important role for PDV. Our result
nonetheless suggests that the larger relative amplitude of extratropical ocean-atmosphere anomalies does
not necessarily indicate a lesser role of tropical SST forcing.

4. Summary and Discussion
Based on a composite analysis of observational and reanalysis data, we show that multiyear La Niña events
exert signiﬁcant impacts on the atmospheric circulation and drought conditions over the southern U.S. during the NH cold season. Although the equatorial Paciﬁc SST cooling weakens signiﬁcantly from the ﬁrst to thesecond year, La Niña teleconnections do not weaken proportionally. Compared to the ﬁrst year, extratropicalatmospheric circulation anomalies show a more zonally elongated pattern and become even larger over the
North Paciﬁc in the second year. Over the U.S., precipitation anomalies have similar magnitude in both years
and the region of reduced precipitation expands to the north and shifts eastward in the second year compared to the ﬁrst year in association with the farther northward displacement of the subtropical westerly
jet. These modulations of teleconnection patterns in the second year appear to be related to changes inthe zonal and meridional structures of tropical precipitation anomalies. While the increased zonal extent of
tropical precipitation and circulation anomalies may increase the raypath radius of curvature of the Rossby
wave response, the reduced equatorial precipitation anomalies associated with the weaker SST cooling seem
to shift the subtropical westerly jet farther to the north and enhance the Aleutian low response. We speculatethat the same mechanism may also apply to the differences between the ENSO and PDV patterns.
Given the extended impacts on droughts, it is important to be able to predict the duration of La Niña events.
An early warning of multiyear La Niña would allow us to take cautionary actions on water conservation andagricultural planning. The current operational ENSO forecasts are, however, limited to 8 months (Barnston
et al., 2012), precluding the predictions of multiyear La Niña events. Through idealized model experiments,
DiNezio, Deser, Okumura, et al. (2017) show that multiyear La Niña events can be predicted before the initialonset when they are preceded by strong El Niño events and associated large discharge of the equatorial
ocean heat content. It is interesting to note that multiyear La Niña events became more frequent after the
1970s along with an increase in ENSO amplitude (Figure S1), consistent with an analysis of a long climate
model simulation (Okumura et al., 2017). Further studies are needed to demonstrate the feasibility ofoperational predictions of La Niña duration (DiNezio, Deser, Karspeck, et al., 2017), as well as to understandthe processes affecting the duration of individual La Niña events.
For successful predictions of droughts driven by multiyear La Niña, we also need to address the uncertainty of
atmospheric teleconnections (e.g., Deser et al., 2017; Schubert et al., 2016; Seager & Hoerling, 2014). Although
the composite multiyear La Niña teleconnection patterns are robust across different data sets and samplingof events, individual events may deviate from this composite picture. For example, during the most recent
multiyear La Niña event of 2010–2012, the Aleutian low response weakened and precipitation increased overthe southeastern U.S. in the second cold season (Fernando et al., 2016). The event-to-event variations in

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teleconnections are likely to arise from both predictable and unpredictable factors. For the predictable component, variations in the pattern and magnitude of SST anomalies are likely to cause different teleconnections, which can be potentially simulated by atmospheric models with a large number of ensemble
members. In any single member of atmospheric model simulations, as well as in reality, the predictablecomponent can be obscured by internal variability of the atmosphere, which is unpredictable even with aperfect model. A more systematic and quantitative assessment is necessary to understand the predictabilityof La Niña teleconnections. We will also need to reevaluate the atmospheric models used for seasonal climate
forecasts for their ability to simulate the evolution of multiyear La Niña teleconnections.
Multiyear La Niña events have signiﬁcant impacts on precipitation over the southern U.S. mostly during the
NH cold season. It remains to be examined how the precipitation deﬁcit in cold season affects the onset andevolution of drought over the southern U.S. during the intervening seasons. For example, Anderson et al.
(2016) shows that ENSO-induced wintertime precipitation anomalies affect soil moisture and crop yield overthe southern Great Plain states in the following seasons. In addition to the soil moisture memory, positiveland-atmosphere feedback may also play an important role in perpetuating the drought (e.g., Hong &Kalnay, 2000; Koster et al., 2004; Lyon & Dole, 1995; Oglesby & Erickson, 1989; Schubert et al., 2004;
Trenberth & Branstator, 1992). The drier soil after the ﬁrst peak of La Niña is likely to increase surface airtemperatures by decreasing available moisture for evaporation and resultant latent heat loss. The increased
air temperatures would, in turn, enhance evaporation from the surface, further drying the soil. The return of
La Niña and associated dry winter conditions in the second year may thus have more severe impacts on theregional hydrological cycle and ecosystem than in the ﬁrst year. Further understanding of the mechanisms
and predictability of multiyear La Niña events and their impacts is critical to minimize the calamity ofpersistent droughts over the southern U.S.
Acknowledgments
The authors would like to thank John M.
Wallace and Weston Anderson for
helpful discussions and two anonymous
reviewers for their insightful comments
and constructive suggestions. The
observational data sets used in thisstudy are obtained online: HadISST from
the Met Ofﬁce Hadley Center (http://
www.metofﬁce.gov.uk/hadobs/); GPCC,
20CR, NCEP-NCAR, and OISST from the
NOAA Earth System ResearchLaboratory Physical Science Division(https://www.esrl.noaa.gov/psd/); andERA-Interim from the ECMWF (http://
www.ecmwf.int/). The CAM simulations
are available through the Climate
Variability and Change Working Groupof the Climate Earth System Model(http://www.cesm.ucar.edu/working_groups/CVC/). The GFDL AM2.1 simulation is provided by courtesy of Jian Lu
and Fanrong Zeng. This study is supported by the NOAA Climate Program
Ofﬁce Modeling, Analysis, Predictions,and Projections Program(NA14OAR4310227, NA14OAR4310228,
NA14OAR4310229, NA17OAR4310149,
and NA17OAR4310145). NCAR is sponsored by the National Science
Foundation.

OKUMURA ET AL.

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