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Atmosphere and Ocean Origins of North American
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Droughts
Richard Seager
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∗
Lamont Doherty Earth Observatory of Columbia University, Palisades, New York
Martin Hoerling
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NOAA Earth System Research Laboratory, Boulder, Colorado
∗
Corresponding author address: Richard Seager, Lamont Doherty Earth Observatory of Columbia Uni-
versity, 61 Route 9W., Palisades, NY 10964. Email: [email protected]
Submitted to Journal of Climate June 2013. LDEO Contribution Number xxxx.
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ABSTRACT
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The atmospheric and oceanic causes of North American droughts are examined using ob-
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servations and ensemble climate simulations. The models indicate oceanic forcing of annual
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mean precipitation variability accounts for up to 40 percent of total variance in northeast-
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ern Mexico, the southern Great Plains and the Gulf Coast states but less than 10 percent
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in central and eastern Canada. Observations and models indicate robust tropical Pacific
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and tropical North Atlantic forcing of annual mean precipitation and soil moisture with the
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most heavily influenced areas being in southwestern North America and the southern Great
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Plains. In these regions, individual wet and dry years, droughts and decadal variations,
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are well reproduced in atmosphere models forced by observed SSTs. Oceanic forcing was
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important in causing multiyear droughts in the 1950s and at the turn of the 21st century,
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though a similar ocean configuration in the 1970s was not associated with drought due to an
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overwhelming influence of internal atmospheric variability. Up to half of the soil moisture
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deficits during severe droughts in the southeast U.S. in 2000, Texas in 2011, and the central
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Plains in 2012 were related to SST-forcing, although SST forcing was an insignificant factor
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for northern Plains drought in 1988. During the early 21st century, natural decadal swings
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in tropical Pacific and North Atlantic SSTs have contributed to a dry regime for the U.S.
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Long-term changes caused by increasing trace gas concentrations are now contributing to
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a modest signal of soil moisture depletion, mainly over the American Southwest, thereby
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prolonging the duration and severity of naturally occurring droughts.
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1. Introduction
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In a nation that has been reeling from one weather or climate disaster to another, with
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record tornado outbreaks, landfalling tropical storms and superstorms, record winter snow-
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falls and severe floods, persistent droughts appear almost prosaic. Droughts do not cause the
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mass loss of life and property destruction of floods and storms. They are instead slow-motion
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disasters whose beginnings and ends are even often hard to identify. However, while the so-
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cial and financial costs of hurricane, tornado and flood disasters are, of course, tremendous,
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droughts are one of the costliest of natural disasters in the U.S. Much of that cost is related
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to crop failure but droughts can also lead to spectacular events in the form of wildfires and
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the costs of fighting these are immense. Further, crop failures easily translate into spikes in
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food prices that, given the global food market, across the world. In one truly exceptional
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case - the 1930s Dust Bowl - drought led to millions in the Great Plains leaving their homes,
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hundreds of thousands migrating from the region, an unknown number of deaths from dust
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pneumonia and a permanent transformation in the agriculture, economy and society of the
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region and wider nation (Worster 1979). U.S. droughts more often than not appear as
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components of droughts that also impact Mexico and/or Canada. For example the 1950s
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southwest drought was also one of the worst that Mexico has experienced and Mexico has
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been struggling with ongoing drought since the mid 1990s (Seager et al. 2009b; Stahle et al.
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2009). Further the 1998 to 2004 drought in the U.S. which, for example, dropped Colorado
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River storage to record lows also severely impacted much of Canada (Stewart and Lawford
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2011; Bonsal et al. 2011). Given these trans-continental and multinational consequences of
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drought, considerable effort has been expended to attempt to understand why they occur
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and whether they can be predicted in advance. In recent years an increasing amount of this
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research effort has focused on whether, where and when droughts in the U.S. will become
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more common or severe due to climate change caused by rising greenhouse gases.
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Despite years of study, progress in understanding the causes of North American droughts
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only made serious headway in the last decade or so. By then the computational resources
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were widespread enough to make possible large ensembles of long simulations with atmo-
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sphere models forced by observed and idealized sea surface temperatures (SSTs). These
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were used to test hypotheses of oceanic forcing of drought-inducing atmospheric circulation
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anomalies. Links between North American precipitation variability and the El Niño-Southern
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Oscillation, with, in its El Niño phase, a tendency to increased winter precipitation across
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southern North America, had begun to be noticed in the 1970s and early 1980s (see Ras-
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musson and Wallace (1983)) and explained in terms of Rossby wave propagation forced by
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anomalous heat sources over the warm tropical Pacific SST anomalies (Hoskins and Karoly
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1981).
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to the ongoing La Niña event and Palmer and Brankovic (1988) claimed to be able to
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produce important elements of the same drought within the European Centre for Medium
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Range Weather Forecasts (ECMWF) numerical weather prediction model when forced by
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the observed SSTs (but see Section 8 below).
Trenberth et al. (1988) then applied linear wave theory to link the 1988 drought
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Explaining a seasonal drought is good progress but it is the multiyear droughts that can
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wreak the most damage. The Dust Bowl drought lasted about 8 years but was not unique in
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this regard. Western North America experienced a severe drought from 1998 to 2004 and a
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severe drought in the early and mid 1950s struck the southwest. Progress in understanding
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these multiyear droughts had to wait more than a decade. Indeed, as late as 2002, a National
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Research Council report on abrupt climate change attributed the Dust Bowl drought to
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atmosphere-land interaction with no role for the oceans (National Research Council 2002).
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However, in breakthrough studies, Schubert et al. (2004b) and Schubert et al. (2004a) used
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large ensembles of atmosphere model simulations forced by observed SSTs for the post 1930
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period to show that the model generated a 1930s drought with both persistent cold tropical
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Pacific and warm tropical North Atlantic SST anomalies being the drivers. Following up,
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Seager et al. (2005) and Herweijer et al. (2006) presented SST-forced atmosphere model
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simulations for the entire post 1856 period of instrumental SST observations and showed
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that the three observed 19th Century droughts, the Dust Bowl and the 1950s drought were
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all simulated by the model and argued that persistent La Niña states in the tropical Pacific
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Ocean were the essential cause of all. Tropical Pacific and Indian Ocean SST anomalies were
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also invoked as the cause of the multiyear drought that began after the 1997/98 El NIño
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(Hoerling and Kumar 2003; Seager 2007). The dynamical mechanisms that link tropical
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SSTs to drought-inducing circulation anomalies have also been studied and the situation of
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a cold tropical Pacific-warm tropical North Atlantic appears as ideal for inducing drought
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(Schubert et al. 2008, 2009).
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These studies represented considerable advances in understanding why multiyear droughts
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occur (even though the causes of the persistent tropical SST anomalies that were the drivers
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has been barely addressed). However these studies were in many ways broad brush. Long
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time series, often time-filtered, were used to show that the models produced dry conditions
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at the correct time but then precipitation, circulation, SSTs etc. were typically averaged over
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the whole drought period, perhaps by season, for comparing model and observed droughts.
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Such averaging will tend to emphasize the SST-forced component, which may be fundamen-
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tal, but prevents a complete analysis of drought onset, evolution and termination. As such
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it might prevent proper identification of non-SST forced components of the drought due to,
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for example, random atmospheric variations (weather).
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For example, during the 1930s Dust Bowl years, while there was no El Niño, the tropical
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Pacific SST anomalies were only modestly cool and not consistently so but a drought ex-
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tended from the southern Plains north to the Canadian Prairies and also towards the Pacific
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northwest and U.S. midwest. (Fye et al. 2003; Cook et al. 2007; Stahle et al. 2007; Bonsal
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and Regier 2007; Cook et al. 2011). Atmosphere models forced by observed SSTs do simulate
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a drought during the 1930s with both cooler than normal tropical Pacific and warmer than
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normal tropical North Atlantic SST anomalies being responsible. However, the droughts are
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centered in the southwest and not in the central Plains as observed and are also too weak
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(Schubert et al. 2004b,a; Seager et al. 2005, 2008; Hoerling et al. 2009). Two hypotheses
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have been advanced to explain the discrepancy. The first is that the 1930s drought was
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amplified and moved northwards by human-induced wind erosion and dust aerosol-radiation
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interactions (Cook et al. 2008, 2009, 2010) and the other is that, instead, the Dust Bowl
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drought contained a large component of internal atmospheric variability not linked to SST
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anomalies (Hoerling et al. 2009). Both groups of authors draw a distinction between the
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spatial extent and severity of the 1930s Dust Bowl drought and the 1950s southwest drought
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with the latter appearing to be more of a canonical SST-forced drought. Similarly, North
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America is currently within the third year of a drought that has brought successive summers
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(2011 and 2012) of intense heat and dry conditions to the central part of the continent, from
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eastern Mexico to Canada. While La Niña conditions prevailed during both summers, it is
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not at all clear that they alone were sufficient to cause such abnormal conditions with both
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modes of internal atmospheric variability and, perhaps, climate change having been invoked
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to provide a full explanation (Hoerling et al. 2013c,b; Seager et al. 2013a).
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Given this state of affairs it appears appropriate to move beyond invoking a general
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association of drought in southwestern North America and the Plains with, primarily, La
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Niña and, secondarily, warm tropical North Atlantic SST anomalies, to consider the causes
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of North American droughts in more detail including assessing the role of processes unrelated
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to ocean forcing. Of particular interest is the extent to which droughts are influenced or
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driven by internal atmospheric variability relative to being forced by changes in surface ocean
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conditions. This is important to the understanding of mechanisms but also has serious
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implications for predictability of droughts. SST anomalies in the tropical Pacific Ocean
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can be predicted up to a year in advance and, to the extent that they drive atmospheric
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circulation anomalies over North America, can be potentially exploited to provide seasonal
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forecasts of drought onset, evolution and termination. In contrast, aspects of droughts
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determined by internal atmospheric variability will be unpredictable beyond the weather
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prediction timescale.
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In addition to the potential of SST variability, internal atmosphere processes and land-
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atmosphere interaction to cause droughts we must also address the possibility that human-
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induced climate change is now impacting North American hydroclimate and the frequency
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and character of droughts. Seager et al. (2007) and Seager and Vecchi (2010) have shown
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that a shift towards a more arid climate in southwestern North America begins in the late
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20th Century although it is likely currently masked by natural variability (Hoerling et al.
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2011). Also, Hoerling et al. (2013c) have shown that the heat of the 2011 Texas heat wave
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and drought was likely aided by global warming while it was not clear that the precipitation
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reduction was outside the range of natural variability. Weiss et al. (2009) have also noted
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the impact of increasing temperatures on southwestern droughts, implying an emerging form
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of drought in which a warming trend exacerbates the impacts of precipitation reductions.
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These considerations motivate the current review paper to take three tacks:
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• What are the relative roles of internal atmospheric variability and oceanic forcing in
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generating droughts over North America? Is a general association between tropical SST
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anomalies and North American precipitation enough to explain the intensity, spatial
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coverage and timing of historical western North American droughts?
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• What does the answer imply about the predictability of droughts? Are the most
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devastating droughts, the most extensive ones that influence multiple nations and
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agricultural areas, and both upstream and downstream reaches of large river basins,
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ever simply the result of oceanic forcing or are they instead an unfortunate mix of SST
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forcing and internal atmospheric variability?
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• Even if we can answer the above question, is the scientific ground upon which we stand
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shifting? That is, are human-induced climate trends - both warming and changes in
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precipitation - already impacting the likelihood and severity of western North American
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droughts?
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To attempt to answer these questions we will use observations and a variety of model
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simulations. This is not a typical review in that most of the material presented will be
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new but it does seek to provide a broad review, motivated by recent research, of where we
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stand in terms of understanding the causes and mechanisms of North American droughts
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and to what extent we can anticipate hydroclimate variability and change, and in particular
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droughts, in the coming seasons to decades.
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This review is being performed under the auspices of the Global Drought Information
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System (GDIS) which is under the World Climate Research Program (WCRP) umbrella.
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Hence we aim to contribute to challenges identified at the July 2012 WCRP meeting including
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under, ‘Provision of skillful future climate information on regional scales’, to ‘Identify and
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understand phenomena that offer some degree of intra-seasonal to inter-annual predictability’
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and ‘Identify and understand phenomena that offer some degree of decadal predictability’.
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Further we aim to contribute to the goal under ‘Interactions across multiplicity of drivers
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and feedbacks at the regional scale’ to ‘Provide increased understanding of the interplay across
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the different drivers, processes and feedbacks that characterize regional climate at different
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spatial and temporal scales. Consider interactions across greenhouse gas forcings, natural
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modes of variability, land use changes and feedbacks, aerosols, tropospheric constituents.’
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Models and data used are described next followed by an analysis in Sections 3 through 7 of
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the roles of the ocean and atmosphere in explaining North American precipitation variability
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over the past century. Section 8 then focuses in on post 1979 period in the U.S. Conclusions
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are offered in Section 9.
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2. Observed data and models used
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The observed precipitation is the latest version of the Mitchell and Jones (2005) Uni-
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versity of East Anglia (UEA) Climatic Research Unit data at 1 degree resolution (CRU
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TS3p1). SST data in the observational analysis comes from the Hadley Center (Kennedy
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et al. 2011a,b). The soil moisture data are an estimate of 1.6-meter depth soil moisture in
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which a leaky bucket model is driven with observed monthly surface temperature and pre-
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cipitation and have the spatial resolution of the U.S.Climate Divisions (Huang et al. 1993).
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Observed geopotential height anomalies are taken from the National Centers For Environ-
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mental Prediction-National Center for Atmospheric Research (NCEP-NCAR) Reanalysis
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(Kistler et al. 2001).
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We use three sets of atmosphere model simulations of the type referred to as ‘AMIP
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(Atmospheric Model Intercomparison Project)’ experiments, which are designed to determine
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the sensitivity of the atmosphere to, and the extent to which its temporal evolution is
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constrained by, known boundary forcings. These are as follows.
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• The first ensemble is used for the analysis of the variance of observed and modeled
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precipitation histories for 1901 to 2008. This is a 16 member ensemble of SST-forced
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atmosphere General Circulation Model simulations for the 1856 to 2011 period. The
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model used was the National Center for Atmospheric Research Community Climate
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Model 3 (NCAR CCM3, Kiehl et al. (1998)). The only time varying forcing was the
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SST which was from Kaplan et al. (1998) within the tropical Pacific and the Hadley
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Centre data elsewhere (see Seager et al. (2005) for more details). The ensemble mean
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of these simulations closely isolates the SST-forced variations that are common to the
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ensemble members by averaging over the uncorrelated weather variations within the
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individual ensemble members which begin from different initial conditions on January
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1 1856. Hence by subtracting the ensemble mean from each ensemble member we also
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retrieve 16 records of modeled internal atmospheric variability.
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• In addition, to focus on variations, especially of soil moisture, in the post 1979 period
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we use two global atmospheric models with SST, sea ice, and external radiative forcing
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specified as monthly time evolving boundary conditions from January 1979 to Decem-
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ber 2012. One model used is the NCAR Community Atmosphere Model 4 (CAM4)
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global climate model (Gent and co authors 2011), with the simulations performed at a
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1◦ resolution and 26 atmospheric levels, and for which a 20-member ensemble is avail-
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able. The second global climate model used is the European Center Hamburg model
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version 5 (ECHAM5; Roeckner et al. (2003)), with simulations performed at T159
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resolution and 31 atmospheric levels, and for which a 10-member ensemble is avail-
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able. Each realization differs from another only in the initial atmospheric conditions
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in January 1979, but uses identical time evolving specified forcings. For both models,
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monthly varying SSTs and sea ice and the external radiative forcings consisting of
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greenhouse gases (e.g. CO2 , CH4 , NO2 , O3 , CFCs) are specified. The CAM4 runs also
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specify varying anthropogenic, solar, and volcanic aerosols.
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• In order to address possible effects of long-term climate change on U.S. drought vari-
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ability during 1979-2012, an additional 10-member ensemble of ECHAM5 simulations
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is performed that uses late-19th century boundary and external radiative forcings. In
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these so-called ECHAM5-PI experiments, trace gas forcings are set to climatological
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1880 conditions and held fixed throughout the simulation period. Also, the 1880-2012
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linear trend in SSTs is removed from the monthly SST variability. This sets the clima-
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tological SSTs to values representative of 1880. The SSTs during 1979-2012 otherwise
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vary identically to those in the AMIP simulations. Two intercomparisons of these par-
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allel simulations are conducted. One is a simple difference of their mean climates to
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illustrate the signal of long-term change. The second is a comparison of each models
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interannual variability during 1979-2012 to illustrate how temporal variability of U.S.
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drought may have been affected by long-term change.
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For CAM4, column integrated soil moisture to a depth of 0.5m is used (though results
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are mostly insensitive to using different soil moisture depths). For ECHAM5 the total
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column soil moisture is available for diagnosis. To facilitate comparison of observed and
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modeled soil moisture, the monthly and annual variations are standardized by each models
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climatological variability. When comparing to climate division data, model output data has
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been interpolated onto the U.S. climate divisions.
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3. An estimate of the relative roles of the oceans and
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atmosphere in generating North American precipi-
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tation variability
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Various factors have contributed to historical North American precipitation variability on
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seasonal and longer time scales. These include sensitivity to global sea surface temperature
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variability, local land surface feedbacks including persistent soil moisture states and land
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use changes, the effects of internal atmosphere variability such as expressed by prolonged
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circulation states associated with blocking and storm track shifts, and a sensitivity to global
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warming resulting from changes in external radiative forcing. It is difficult to quantify
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the contributions of individual factors from the observational record alone, and ensemble
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climate simulations become a critical diagnostic tool. In this section, two of these factors
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are isolated, while section 8 also examines the effects of long-term climate change on recent
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droughts. Here we use the 16 member AMIP simulations of CCM3. The ensemble mean
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provides an estimate of the variations common to all ensemble members due to the SST
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forcing, while the deviations of individual realizations from the ensemble mean provides an
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estimate of the effects of internal atmosphere variability. While definitions of drought differ,
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there is broad agreement that a reduction of precipitation is typically required and hence we
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begin by analyzing precipitation (section 8 will analyze soil moisture variability). In order
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to address timescales long enough to be relevant to severe sustained drought, we analyze
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annual mean precipitation.
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Figure 1 shows the variance of observed annual mean precipitation. This is greatest, as
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expected, where the precipitation is greatest, in the Pacific Northwest and the Southeast
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U.S. with some other regions of high variance such as the coastal northeast and the Mexican
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monsoon region. Also shown is the average of the variances of the individual CCM3 ensemble
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members. This very roughly captures the observed variances in amplitude and spatial pattern
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although with too low variance in the southeast U.S. and the eastern coastal states and
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excess variance in Mexico. Figure 1 also shows the variance of the model ensemble mean
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which, as expected, is everywhere much lower than the total model variance. This SST-
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forced variance has maxima in Mexico and the south and central Plains. Finally the ratio
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within the model of the SST-forced to the total variance is also shown. This has maxima
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in northern Mexico, the south to central Plains and Gulf states. Here, rather remarkably,
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up to about 40% of the model total annual mean precipitation variance is caused by SST
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variations. Everywhere else in North America SST forcing accounts for less than a third
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of total annual mean precipitation variance (with the lowest values in central and eastern
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Canada) indicating that the detailed year-to-year variations of precipitation are heavily
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influenced by internal atmospheric variability. Sustained drought on longer time scales could
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nonetheless be appreciably influenced by ocean conditions to the extent that the latter
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are of low frequency and that North American climate is sensitive to temporally coherent
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patterns of such oceanic forcing. Similar conclusions were reached based on simulations with
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a different model by Hoerling and Schubert (2010).
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4. Modes of continental scale precipitation variability
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Cook et al. (2011) conducted an Empirical Orthogonal Function (EOF) analysis of
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the tree ring derived North American Drought Atlas (Cook et al. 2007) which provides
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annual estimates of the Palmer Drought Severity Index (PDSI) reflecting surface moisture
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availability in the spring to summer growing season. They found that the first 5 modes
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explained 62% of the variance in the complete record. Of those 5 modes the first correlated
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well with tropical Pacific SST variations while the second appeared to be related to North
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Pacific atmosphere-ocean variability (not necessarily ocean-forced) and the third to tropical
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North Atlantic SST variations. The correlations of the PCs to SSTs was strongest in the
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tropical Pacific Ocean. These results suggested a modest, but important, amount of influence
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of SSTs on continental scale modes of hydroclimate variability.
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We conduct the same analysis here using annual mean precipitation anomalies. Figure
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2 (top row) shows the first three EOFs of the observed detrended annual standardized
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precipitation variability (see Ruff et al. (2012)). These explain a large fraction of the
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contiguous US region variability, though they collectively account for only about 30% of
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the total variability over all of North America. The first pattern has same sign anomalies
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across almost all of the U.S. and Mexico with maximum strength in the southwest (where
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it explains over 30% of the total precipitation variance) and opposite sign anomalies in the
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Pacific northwest. The second pattern has a dipole pattern with centers in the Texas-north
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Mexico region and the far west where about 20% of the local variability is explained. The
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third pattern describes an out-of-phase relationship between annual precipitation variability
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over the monsoon region that encompasses northwest Mexico and the American Southwest
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and the central Great Plains, reminiscent of a summertime pattern described by Douglas
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and Englehart (1996) and Higgins et al. (1999).
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Figure 2 also shows the same analysis for one simulation of the climate model with global
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SST forcing and, in addition, for the ensemble mean of the simulations. The analysis of the
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single run should be analogous to the analysis of observations since it contains a mix of
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ocean-forced and internal atmospheric variability and, indeed, the first two EOFs are very
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similar to those observed and even the third pattern has some similarities. The analysis of
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the ensemble mean isolates the ocean-forced component in the model. The first ocean-forced
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pattern is very similar to the observed one suggesting that this pattern does indeed arise in
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nature from ocean forcing. The second pattern also contains the north-south dipole along
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the western coast between Mexico and the U.S. seen in the observed analysis but has wrong
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sign anomalies in the southern Plains.
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Figure 3 shows the correlation of the principal components of these patterns with global
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SST anomalies. The first pattern is clearly the El Niño-Southern Oscillation (ENSO) while
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the second pattern appears to represent a relationship between dry in Mexico and the south-
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ern Plains and warm tropical North Atlantic SSTs. This is so in the observations, the model
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ensemble mean and the single ensemble member which indicates that these relations between
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precipitation and tropical Pacific and Atlantic SSTs are quite robust. The SST relations for
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the third precipitation PC are not consistent across observations and models. On the ba-
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sis of these results for precipitation variability a cold tropical Pacific-warm tropical North
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Atlantic emerges as a particularly effective ocean state for forcing drought in the interior
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southwest and Plains in agreement with Schubert et al. (2009). A similar link will be shown
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in section 8 based on analysis of soil moisture variability. As noted in Figure 2, the first
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EOFs explain 15% and 23% of the total variance for the observations and the single model
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run, respectively and the second mode 8% and 11%. These modest values of the two clearly
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SST-associated modes are consistent with the results shown in Figure 1. For the ensemble
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mean the variances explained by the SST-forced modes are much higher because the inter-
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nal atmosphere variability is largely, but not entirely, missing due to the averaging across
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ensemble members.
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5. Observed and modeled precipitation variations in
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the Great Plains and southwest North America over
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the past century
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From what has been presented so far we would expect that the atmosphere model forced
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by historical observed SSTs would, by simulating the ocean-forced component, capture some,
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but by no mean all, of the observed history of precipitation over western and central regions
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of North America. Figure 4 shows comparisons of modeled and observed precipitation for
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both the Great Plains region (here defined as 30◦ − 50◦ N, 110◦ − 90◦ W , land areas only) and
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southwest North America (SWNA, here defined as 25◦ − 40◦ N, 125◦ W − 95◦ W , land areas
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only). The model ensemble mean represents the SST-forced component and the shading
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around it is the plus and minus two standard deviation of the ensemble spread and shows
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whether the observed precipitation anomalies ever fall outside the range of the model en-
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semble. The best model reproduction of the observed history is in SWNA where about a
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quarter of the observed variance of annual means can be explained in terms of SST forcing.
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Individual wet and dry years are quite well simulated as well as the longer term variability
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such as the wet 1980s and 1990s and the dry 1950s. The model-observations comparison for
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the Great Plains is not quite so impressive but, given the similarity of the observed SWNA
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and Plains records, many of the same points hold true.
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The lower two panels of Figure 4 explain much of why the model is capable of reproducing
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important features of Great Plains and SWNA precipitation history by plotting together the
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observed precipitation history with that of SST averaged over 5◦ S − 5◦ N and 180◦ W −
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90◦ W (the tropical Pacific, TP, index). TP correlates with Plains precipitation at 0.40 and
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with SWNA precipitation at 0.52. The 1980s and 1990s were a time of warm El Niño-like
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conditions (as noted first by Zhang et al. (1997)) while the dry conditions between the 1930s
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and 1950s correspond to overall cooler La Niña-like conditions with the exception of the early
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1940s El Niño which caused striking wet conditions in both the Plains and SWNA that are
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well reproduced by the model. In both regions, most dry years were associated with cold TP
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SSTs but there are exceptions to this (2003 is one) and there are also cold tropical Pacific
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years that were not dry years. The model-tropical Pacific SSTs agreement is good (see also
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Schubert et al. (2008)) given that we know that internal atmospheric variability accounts
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for a larger proportion of precipitation variability than does ocean-forcing and, even for the
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latter, the tropical Atlantic SSTs play an important role too (McCabe et al. 2004; Schubert
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et al. 2008; Kushnir et al. 2010; Nigam et al. 2011). It is obvious that the tropical Pacific
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Ocean is a major orchestrator of North American hydroclimate.
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Comparisons of modeled and simulated precipitation that extend back a century or more
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are still relatively rare but the ones that do exist confirm what would be expected on the
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basis of Figure 1. For example, SST-forced models can reproduce precipitation history across
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Mexico with some fidelity (Seager et al. 2009b) but the skill in the southeast U.S. is decidedly
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low and confined to the winter season (Seager et al. 2009a) and nonexistent in the northeast
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U.S. (Seager et al. 2012).
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6. Hydroclimate variability due to internal atmospheric
variability
368
While there seems no doubt that variations in tropical Pacific SSTs can force drought
369
conditions over western and central North America it is also clear that the actual drought
370
history cannot be explained entirely in this way. While, for the special case of the Dust
371
Bowl, land surface degradation and dust storms likely played an important role in shaping
372
the drought (Cook et al. 2008, 2009, 2010), more general is the likelihood that droughts
373
were initiated, evolved and terminated by some mix of SST-forced circulation anomalies
374
and internal atmospheric variability (e.g.
375
address a simpler question: what would hydroclimate and drought variability be like in the
376
absence of any ocean forcing of variability? To get an idea of this we show in Figures 5 the
377
time series of observed precipitation anomalies for SWNA together with the 16 individual
378
CCM3 runs from each of which the ensemble mean has been subtracted. Since the model
379
simulations in this case represent internal atmospheric variability only we do not expect
380
any match whatsoever with the observed record. The two are plotted together simply to
381
provide a straightforward visual comparison of the amplitude and temporal behavior of the
382
modeled precipitation variability due to atmospheric variability and that in nature which
383
arises from both atmosphere and ocean variability. For SWNA the most obvious feature
384
in the observed time seres is the early to mid 1950s drought. Such a strong sustained
385
precipitation drop exceeds those in the 16 time series of atmosphere-only variability with
386
the sole exception of a drought that occurred in the late 19th Century of ensemble member
387
two (upper right panel). Quite a few model time series are capable of matching the obvious
388
observed pluvial in the 1980s. For all 16 ensemble members the atmosphere-only generated
389
variability in the model is less than that observed (not shown). This however may not be
390
a true measure of atmospheric variability since it is constructed from simulations in which
391
the model atmosphere was aware of SST variability but with the latter influence removed
392
after the fact. It could be that, in the true absence of SST-forced variability, the internal
393
atmospheric variability would increase to re-establish the same total variability.
Hoerling et al. (2009)). To assess this we first
14
394
395
7. Simulation of two historical droughts and one mystery event
396
So, given these general measures of temporal and spatial variability of annual mean
397
precipitation over North America, can actually occurring multiyear droughts be explained in
398
terms of ocean forcing and, to rephrase the question, does the existence of ocean conditions
399
conducive to drought, guarantee that a drought will, in fact, occur? To assess this we focus
400
on two historical multiyear drought periods: 1952-6 which is core to a decade-long period
401
considered the drought of record for portions of the southern Great Plains (e.g. Hoerling
402
et al. (2013c)) and 1999-2002 which constitutes the first several years of a decade long drought
403
epoch, especially effecting southwest North America, that began after the 1997/98 El Niño
404
(Hoerling and Kumar 2003; Lau et al. 2006; Seager 2007). Figure 7 shows the observed
405
anomalies of near-global SST, 200 hPa heights (from the NCEP-NCAR Reanalysis) and
406
North American precipitation averaged over these events. Generally warm SST anomalies
407
and positive heights in the latter period are evidence of global warming. However, cool
408
tropical Pacific anomalies are evident in both periods as well as relatively low geopotential
409
heights over the tropics. In the extratropics of the northern hemisphere there are wide areas
410
of high pressure - effecting North America in both cases - an expected response to cool
411
tropical Pacific SST anomalies (e.g. Seager et al. (2003); Lu et al. (2008); L’Heureux and
412
Thompson (2006)). (The southern hemisphere height anomalies are probably dominated by
413
trends caused by, primarily, ozone depletion (Cai and Cowan 2007; Son et al. 2009; Polvani
414
et al. 2011) and do not clearly show the La Niña pattern.) The observed drought in 1952-6
415
was striking in its severity encompassing the southwest, Plains, southeast and midwest. The
416
1999-2002 drought was modest by comparison and more focused in the entire west of North
417
America including Canada.
418
Figure 8 shows the model simulation of these two droughts. Again the general tendency
419
to rising heights associated with the warming oceans is evident but the relatively low trop-
420
ical heights forced by the cool SSTs are evident. The model also produces modest ridges
421
in northern mid-latitudes, including over North America, as in the observations. The ex-
422
tratropical ridges are more clear in the turn-of-the-century drought as in observations. The
15
423
model does a credible job of simulating the spatial extent of each drought although the
424
1950s one is clearly weaker than observed. The comparisons of heights and precipitation for
425
both droughts are consistent with ocean forcing generating the droughts but with a large
426
additional role for internal atmosphere variability in determining the details.
427
The middle panels of Figure 6 and 7 show the case of the mystery event of 1973-5. This
428
was a period of an extended La Niña between the 1972/3 and 1976/7 El Niños. The low
429
tropical heights expected are clearly seen as well as a well developed wave train extending into
430
the southern hemisphere but the northern hemisphere height anomalies show a circulation
431
pattern distinctly un-La Niña-like. Consistent with the circulation anomalies there was little
432
evidence of the normal La Niña-induced drying with just a patch of reduced precipitation in
433
the southwest. The model simulations (Figure 8) however show, as expected, a classical La
434
Nina-induced pattern of circulation anomalies including a (relative) ridge across the North
435
Pacific and North America and, consistently, widespread precipitation reduction across North
436
America (see also Figure 4). The model therefore suggests that the early 1970s should have
437
been a multiyear drought much like that in the 1950s and at the turn of the century - not
438
surprising given the strong La Niña - but apparently other sources of atmospheric variability
439
were, for this event, able to overcome the influence of the tropical Pacific Ocean. The
440
model simulations presented by Schubert et al. (2004a) and Lau et al. (2006) contain a
441
similar discrepancy. The cold tropical Atlantic and Indian Ocean SSTs may have played a
442
role with this influence being missed or too weak in the models (see Lau et al. (2006) for
443
a discussion of the relative influences of equatorial east Pacific and Indo-west Pacific SST
444
anomalies). However it is also likely that random internal atmospheric variability could have
445
overwhelmed ocean nudging towards dry conditions in 1973-5 consistent with the analysis
446
of the probability distributions of SST-forced ensembles to be presented in Section 8.
447
The better model-observed geopotential height agreement for the turn-of-the-century
448
drought than for the 1950s one might be because of problems with the data in the pre-
449
satellite era and, indeed, the height anomalies in the Twentieth Century Reanalysis (Compo
450
et al. 2011), the only other Reanalysis to cover the 1950s, are different (not shown). For the
451
remainder of the paper we focus in on the drought record for the well-observed period since
452
1979 to develop a closer look at recent and ongoing events.
16
453
454
8. U.S. drought variability since 1979
455
The post-1979 period corresponds to a well observed period after the introduction of
456
satellite data in the 1970s. This is also a period of substantial global warming and contains
457
several severe drought events over the contiguous U.S. We conduct an analysis of soil mois-
458
ture variability during this last 34 year period in order to assess the integrated effects of
459
temperature and precipitation on drought. Availability of quality soil moisture data means
460
that this analysis is restricted to the contiguous U.S.
461
a. Leading patterns of U.S. soil moisture variability
462
We begin, as for precipitation, by determining the leading patterns of soil moisture vari-
463
ability using an EOF analysis. The principal component (PC) time series associated with
464
the spatial structures are then regressed with SSTs to identify connections to ocean vari-
465
ability. Figures 8, 9 and 10 show the first three EOFs of monthly soil moisture variability,
466
which together explain about 46% of the total monthly contiguous U.S. soil moisture vari-
467
ability. (This percent of variance explained is higher than that found for the precipitation
468
analysis in Figure 2. This is probably because soil moisture integrates precipitation minus
469
surface evaporation in time, effectively averaging over the highest frequency precipitation
470
variations generated by internal atmospheric variability.) The leading structure describes a
471
nationwide pattern of like-signed anomalies with maxima over the central Great Plains, Ohio
472
and lower Mississippi River Valleys (Figure 8). Its PC time series suggests national-scale
473
drought conditions occurred only sporadically and briefly in the 1980s and 1990s, whereas
474
an abrupt change from moist to dry conditions in the late 1990s led to a predominately dry
475
state during the last decade. The monthly time variability of this pattern is significantly
476
correlated with Pacific Ocean variability resembling El Nino/Southern Oscillation (ENSO;
477
Figure 8, top right), a relationship also found between the leading North American pattern
478
of precipitation variability and SSTs (see Fig. 3). Cold phases of an ENSO-like pattern are
17
479
correlated with low U.S. soil moisture and also with warm U.S surface temperatures. An
480
additional, though weaker SST correlation occurs between warm phases of the North At-
481
lantic SSTs and dry/warm states of U.S. monthly climate. These Pacific and Atlantic SST
482
correlations, though each explaining only a modest fraction of the monthly variance of U.S.
483
soil moisture associated with EOF1, are consistent with an interpretation of oceanic forcing
484
as supported by empirical analysis using century-long data sets (e.g. McCabe et al. (2004)
485
and climate model simulation studies (e.g.
486
(2010)).
Schubert et al. (2009); Findell and Delworth
487
The second EOF (Figure 9) explains large variance in soil moisture over the northern
488
Plains/Upper Midwest region and also over the eastern U.S. Though exhibiting a dipole
489
structure, subsequent analysis will clarify that monthly soil moisture variability over the
490
northern Plains is not temporally anticorrelated with that occurring in the east. This pat-
491
tern’s PC time series captures variability associated with a particularly dominant northern
492
Plains drought event that occurred during the 1988-1990 period. The negative values of the
493
PC time series of 2003-2005 primarily describe an unusually wet period that occurred over
494
the eastern U.S., as revealed by inspection of annual rainfall anomaly maps, rather than a
495
severe drought epoch of the northern Plains (not shown). The principal component time
496
series of this second EOF exhibits little significant or spatially coherent SST relationship
497
(Figure 9, top right). There is a hint that cold states of the central equatorial Pacific may
498
be linked with the dry soil moisture conditions in the northern U.S. This correlation owes
499
principally to the fact that the late-1980s northern U.S. drought occurred during a strong
500
La Niña event, an association that was initially conjectured to denote a cause-effect linkage
501
(e.g. Trenberth et al. (1988); Palmer and Brankovic (1988)) but which was refuted by sub-
502
sequent studies (Lyon and Dole 1995; Liu et al. 1998; Chen and Newman 1998; Bates et al.
503
2001). Consistent with the results of these later studies, northern Plains precipitation has
504
been above average during the several La Niña events that occurred since 1988, including
505
during 1999-2000, 2007-08, and 2010-11.
506
Finally, shown in Figure 10 is the third EOF structure of monthly soil moisture variability.
507
This describes locally strong variance over the southern Great Plains, the Pacific Northwest
508
and northeast U.S., a pattern similar to the second EOF of annual precipitation (see Figure.
18
509
2). A principal drought event described by this pattern occurred during 2011 and was
510
centered over Texas. The PC time series of EOF3 is correlated with a tropical Pacific
511
SST pattern resembling ENSO, with cold ENSO phases related to southern Plains low soil
512
moisture. Such a relationship is indicative of a forcing-response relationship as suggested
513
by modeling studies linking the prolonged cold state of the tropical Pacific during the late
514
1940s to mid-1950s to protracted severe southern Plains drought (e.g. Seager et al. (2005);
515
Hoerling et al. (2009))and also linking the strong La Nina event of 2011 with the southern
516
Plains drought (Hoerling et al. 2013c,b; Seager et al. 2013a). We also note that dry southern
517
Plains conditions are weakly correlated with warm states of the tropical North Atlantic,
518
consistent with a similar relationship between the second EOF of precipitation and Atlantic
519
SSTs during the longer historical record (see Figure 3).
520
We would not expect the EOF analyses of soil moisture here and of SSTs in Section 4 to
521
completely agree since soil moisture does not have a simple relationship to precipitation and
522
the periods covered are also different. However it is clear that the first EOFs do actually
523
agree on the tropical Pacific SST influence on widespread continental scale dry anomalies
524
and that the second precipitation EOF and third soil moisture EOF are related and point
525
out the influence of a cold tropical Pacific-warm North Atlantic SST pattern on dry in the
526
northern Mexico-southern Plains region and wet in the Pacific northwest.
527
b. Diagnosis of individual extreme drought events during 1979-2012
528
Here two particular aspects of U.S. drought variability are diagnosed. One seeks to ex-
529
plain occurrences of individual severe events during 1979-2012, and we explore the extent
530
to which the timing and location of these can be reconciled with climate signals forced by
531
varying global sea surface temperatures, sea ice, and atmospheric trace gases. The question
532
addresses potential predictability of such discrete drought events, as inferred from a diagno-
533
sis of the factors that may have caused them. A second seeks to explain the broader national
534
scale context of drought variability, and we explore the temporal evolution of drought cov-
535
erage averaged over the entire contiguous U.S. during 1979-2012. The question addressed is
536
the role of longer-term climate variability and change in U.S. drought variability as a whole.
19
537
Four of the principal U.S. droughts since 1979 are identified from the PC time series
538
of soil moisture variability, and the spatial maps of their soil moisture departures are pre-
539
sented in Figure 11 (left side). For simplicity, annually-averaged soil moisture departures
540
are presented, and while realistically describing the spatial coverage of drought associated
541
with each case, these analyses do not necessarily capture the peak intensity of drought dur-
542
ing each event. For instance, the 1988 and 2012 events have been characterized as flash
543
droughts having in both cases witnessed sudden onset in late spring followed by a rapid
544
intensification during summer (e.g. Chen and Newman (1998); Hoerling et al. (2013b)). In
545
contrast, the 2000 and 2011 droughts spanned multiple seasons (Hoerling and Kumar 2003;
546
Hoerling et al. 2013c; Seager et al. 2013a) and were comparatively more long-lived events.
547
Before diagnosing the role of forcing in these four events, we assess the typical spatial
548
scale of soil moisture variations associated with droughts over these geographical regions.
549
Figure 11 (right panels) shows the result of a one-point correlation between monthly soil
550
moisture variability at each climate division with the variability of a soil moisture index that
551
samples each of the four regions having severe drought events (outlined by dark contours
552
on the maps in the left column of Figure 11). Soil moisture variations over these drought-
553
prone areas have a distinct regional scale that is mostly uncorrelated with soil moisture
554
variations over the rest of the U.S. As such, dipole patterns of opposite signed soil moisture
555
extremes indicated by the EOF analysis appear not to be a general condition. In particular,
556
the empirical patterns of U.S. soil moisture variability identified by EOF2 (Figure 9) and
557
EOF3 (Figure 10) should not be interpreted as preferred physical patterns of soil moisture
558
variability over the U.S. as a whole. On the other hand, the one-point correlation results do
559
suggest that a simple index of contiguous U.S. area-averaged soil moisture would typically
560
be a meaningful indicator of regional drought events, consistent with inferences drawn from
561
the leading EOF pattern of soil moisture variability (Figure 8).
562
The question of whether particular oceanic and external radiative forcings may have ex-
563
erted a substantial influence on these four drought events is addressed using the 40-member
564
ensemble of two different models run over the period 1979-2012. Figure 12 presents two
565
particular aspects of the simulated sensitivity. The spatial plots (left) present annual mean,
566
ensemble averaged soil moisture departures for each of the 4 cases, whereas the probability
20
567
distributions (PDFs, right) summarize the 40-member range of simulated soil moisture de-
568
partures. These have been spatially averaged over the drought regions outlined in the left
569
side panels.
570
The climate simulations indicate a general absence of forced drying over the northern
571
Plains/Midwest drought area during 1988 (Figure 12, top). Consistent with prior climate
572
model studies of the 1988 period, these new simulations indicate that any mean forced
573
response was either negligible or not detectable and the 1988 drought resulted largely from
574
internal atmospheric variability. By contrast, the model simulations indicate that each of the
575
subsequent drought events had substantial forced components. Signals of dry soil moisture
576
occur over each of the regions that experienced severe drought in 2000, 2011, and 2012
577
(Figure 12, lower three panels) with magnitudes of about 1 to 1.5 standardized departures.
578
The spatial patterns of those signals are quite similar to one another; more so than the
579
observed patterns of soil moisture anomalies for these events. The evidence from these
580
simulations is nonetheless strong that particular conditions of ocean states and/or external
581
radiative forcing during those years significantly increased probabilities for severe drought
582
to occur over the areas that indeed experienced severe drought.
583
Several lines of evidence indicate that the forced signal of dryness and the associated
584
increase in severe drought risk in these three years was mostly due to natural oceanic vari-
585
ability. Consider first the SST correlations with the PC time series of soil moisture EOF1
586
and EOF3 (see Figure 8 and 10); both indicate significant tropical Pacific SST links to soil
587
moisture variability over portions of the Great Plains and southern U.S. Results in Sections
588
4, 5 and 8a and from prior modeling studies reveal that drought is more likely over these
589
regions when tropical Pacific SSTs are cold (e.g. Seager et al. (2005); Schubert et al. (2009)).
590
The drought years of 2000 and 2011 indeed occurred in concert with strong La Niña events.
591
The results of the new climate simulations presented here, when taken together with such
592
prior modeling and empirical evidence, therefore support the argument that the droughts
593
resulted in part from strong La Niña-related forcing. By contrast, the 2012 ocean conditions
594
were only modestly cold in the tropical Pacific. However, tropical North Atlantic conditions
595
were especially warm that year (not shown, and they were also warm during 2000 and 2011).
596
The simulated 2012 dryness may thus have also been influenced by North Atlantic SST
21
597
conditions.
598
Natural states of SST forcing represent one contributing factor to the recent drought
599
events, and may provide the best prospects for long-lead drought prediction. However, the
600
spread of the PDFs in Figure 12 is considerable and caused by an appreciable intensity
601
of internal atmospheric variations even on annual time scales which limits the long-lead
602
predictability
603
c. Diagnosis of contiguous U.S. drought variability during 1979-2012
604
Contiguous U.S. drought variability is diagnosed for the observations by calculating the
605
percent area covered with soil moisture deficits less than 1 standardized departure. Figure
606
13 shows the resulting monthly time series (brown shading) for the period January 1979
607
through December 2012. The individual regional drought events that were diagnosed in the
608
previous subsection can be readily identified as peaks in the time evolving U.S. drought
609
coverage. Also evident is an overall enlarged drought coverage during 1999-2012 compared
610
to the preceding period of 1979-1998. A similar shift toward increased U.S. drought was also
611
evident in the PC time series of the leading EOF of monthly soil moisture (see Figure 8).
612
Superposed on the plot of the observed drought time series are results of the same cal-
613
culation using soil moisture from the various forced climate simulations. Drought areas are
614
calculated for the ensemble members and Figure 13 shows the ensemble means of these for
615
the CAM4 (blue curve), ECHAM5 (red curve), and the ECHAM5-preindustrial (PI) simula-
616
tions (green curve). There are several features of the model simulations that provide insight
617
into interpreting the observed drought time series. First, the three models are generally
618
in strong agreement with each other concerning the time evolution of U.S drought signals.
619
Second, the rather abrupt observed increase in U.S. drought coverage after the late 1990s is
620
well captured by the models indicating this to be a forced signal. Throughout the 1999-2012
621
period, all three model ensembles indicate a consistently expanded drought coverage relative
622
to the 1979-1998 period. Indeed, very few episodes of drought events before 1999 induce a
623
U.S. areal extent of drought comparable to the sustained high coverage that exists post-1998.
624
A third feature of significance is that the two time series of U.S drought coverage based
22
625
on the parallel ECHAM5 runs are almost indistinguishable. Recalling that the ECHAM5
626
runs differ from each other in that trace gases in the PI runs are set to 1880 values and
627
SST variability is adjusted by removing the observed long-term 1880-2012 trends (Section
628
2), their similarity suggests that the time variability of U.S. drought since 1979 has not been
629
appreciably determined by long-term changes in forcing associated with climate change. In
630
particular, the parallel runs permit an interpretation that the sudden increase in observed
631
U.S. drought coverage after the late-1990s, while being strongly forced, was principally forced
632
by natural decadal states in ocean conditions. A similar result was recently found for a study
633
of summer central Great Plains precipitation (Hoerling et al. 2013b) and in studies of post
634
1979 trends in North American hydroclimate (Hoerling et al. 2010; Seager and Vecchi 2010).
635
This drying over recent decades is consistent with the warm state of the North Atlantic Ocean
636
(which developed after the late-1990s) and the overall cool state of the tropical Pacific since
637
the 1997/98 El Niño (e.g. Schubert et al. (2009); Kushnir et al. (2010))
638
d. Climate change forcing of U.S. droughts during 1979-2012
639
Next we pose the question of how large the human-influence on U.S. drought may have
640
been, when referenced to a longer period of the climate record. The diagnosis involves
641
intercomparison of the two parallel 10-member ensembles of ECHAM5 experiments. Shown
642
in Figure 14 is the difference between their annual mean climatological precipitation (top),
643
soil moisture (middle), and surface air temperature (bottom). The cause for these differences
644
is entirely due to the models sensitivity to the change in global sea surface temperature and
645
external radiative forcing since 1880. A weak signal of reduced annual precipitation ( 0.25
646
standardized departure of the variability in annual precipitation) occurs over the American
647
Southwest, with virtually no mean precipitation signal over other portions of the U.S. This
648
is quite consistent with the regional scale drying signal in the southwest U.S. projected in
649
the CMIP3 (Coupled Model Intercomparison Project Three) simulations (e.g. Seager et al.
650
(2007, 2013b)) to begin in the late 20th Century and strengthen over the current century
651
but, as of now, to be of modest strength. Hence, in so far as the drought events in 1988,
652
2000, 2011, and 2012 were principally the consequence of failed rains, and not centered in the
23
653
southwest, this assessment indicates that long term climate change was unlikely a substantial
654
player for these events.
655
Soil moisture is also sensitive to temperature, however, and the model simulations reveal
656
a strong warming of U.S. annual temperatures in response to the long-term change in forcing
657
since the late 19th Century (Figure 14, bottom). The strongest signal occurs, once again,
658
over the American Southwest where the simulated warming magnitude is 1.5-2.0 standard
659
deviations of the annually averaged variability. Warming of weaker magnitude is simulated
660
over much of the remaining U.S., with a distinct minimum over the southeast U.S. This
661
spatial pattern of temperature change, with strong magnitude over the southwest, is quite
662
consistent with that observed over the last century (Hoerling et al. 2013a).
663
Principally as a consequence of this warming, the models’ soil moisture declines over most
664
of the western and northern U.S., with magnitudes mostly near 0.25 standardized departures
665
(Figure 14, middle). The implied increase in area-coverage of low soil moisture over the U.S.
666
as a whole is qualitatively consistent with an estimated increase in the area affected by severe
667
to extreme drought over the U.S. during 1950-2006 (Easterling et al. 2007). The empirical
668
estimates of long-term change have relied on analysis of long term trends in the Palmer
669
Drought Severity Index (PDSI), yet that index is known to exaggerate the deterioration of
670
surface moisture conditions in response to temperature warming (e.g.
671
(2011); Hoerling et al. (2012)). It is therefore difficult to verify the quantitative veracity of
672
simulated long-term soil moisture change from observations alone. However, the magnitude
673
of the ECHAM5 simulated signal is consistent with results from soil moisture responses in
674
CMIP3 models which show limited changes to date (Sheffield and Wood 2008).
Milly and Dunne
675
To answer the question of how large the contribution of human-induced climate change
676
was during the severe drought events of 1988, 2000, 2011, and 2012, we spatially average the
677
simulated long-term soil moisture changes over the prior assessed four drought regions. The
678
thin gray bars on the PDFs of Figure 12 summarize the results. In all cases, the estimated
679
long-term change signal is about an order of magnitude smaller than the event magnitude
680
itself. Note furthermore that the magnitude of the long-term climate change signal to date
681
is small compared to the spread of each PDF, attesting both to its small role relative to
682
natural internal variability of the atmosphere alone, and to its limited detectability as of now,
24
683
consistent with the conclusions of Sheffield and Wood (2008). And, lastly, it is instructive
684
to compare how large the current climate change signal is relative to a signal associated with
685
natural oceanic boundary forcings. For the 2011 and 2012 droughts, for instance, the natural
686
ocean-forced signal is about a factor of 5 greater than the signal of long term change. It is also
687
important to emphasize that the long-term climate change signal does not inform as to when
688
severe droughts are likely to occur, whereas time evolving natural states of the oceans can.
689
Useful interannual predictability of drought events for specific locations thus continues to
690
hinge critically on the predictability of such natural variations in ocean states. An intriguing
691
aspect of the estimated long-term change in soil moisture due to global warming (Figure 14)
692
is that owing to a regional specificity in signal—-with greater temperature rises over the
693
southwestern U.S. together with greater reduction in precipitation— drought events there
694
are likely to be more severe now and sustained compared to events elsewhere in the U.S.
695
9. Conclusions
696
We have reviewed various lines of evidence for the origins of North American drought
697
variability over the last century, with a more detailed examination of U.S. drought variability
698
during the last three decades. While this assessment introduces several new model simu-
699
lations updated to include recent (2012) conditions, it incorporates methods (AMIP-style
700
simulations with large ensembles) that have been widely utilized in numerous prior investi-
701
gations on factors causing drought. Integrating these new experiments with the extensive
702
literature, the following synthesis of the various factors responsible for North American
703
drought is offered:
704
• Generation by SST variability of atmospheric circulation anomalies that affect precipi-
705
tation over North America accounts for a modest fraction of annual mean precipitation
706
variability. Up to 40% of annual mean precipitation variability in northeastern Mexico,
707
Texas, the southern Plains and the Gulf coast states is caused by ocean forcing, but
708
less than 20% of the variability is SST driven across much of the remainder of North
709
America with the weakest ocean influence occurring over central and eastern Canada.
710
While the ocean-forced component is potentially predictable (e.g. related to ENSO),
25
711
and hence receives much deserved attention, the assessment implies that even perfect
712
SST prediction would likely capture much less than half the total variance in annual
713
precipitation over North America.
714
• In spite of the modest role of the ocean variability in conditioning overall North Amer-
715
ican hydroclimate variability, the observed time histories of annual mean precipitation
716
since 1901 in select regions — especially the southern Great Plains and southwest
717
North America — can be reproduced with notable fidelity within atmosphere models
718
forced by observed SSTs. Individual wet and dry years as well as extended droughts
719
and pluvials can be simulated in this way even if the detailed time evolution or extreme
720
magnitude of such events cannot. In this case the ocean forcing can be considered as
721
an effective nudging influence on the atmosphere creating at times conditions con-
722
ducive for drought (or pluvial) while internal atmospheric variability either amplifies
723
or opposes the SST-forced signal.
724
• Ocean nudging of the atmospheric state was a contributing factor in the multi-year
725
southern U.S. droughts of the 1950s and at the turn of the century. However a striking
726
exception is the 1973-5 period when an extended La Nina generated a severe and sus-
727
tained southern U.S. drought in the model simulations but no such drought occurred
728
in nature most probably due to opposing and overwhelming influences of internal at-
729
mospheric variability. While biases in SST sensitivity within the current state of the
730
art atmospheric models cannot be discounted, the assessment of model and observa-
731
tional data points to a commonality of strong ENSO sensitivity, a potentially modest
732
sensitivity to tropical Atlantic conditions, but only weak overall sensitivity to other
733
ocean conditions.
734
• Estimated U.S. soil moisture variability since 1979 exhibits a similar relationship to
735
SST variability that was found to occur for North American precipitation variability
736
for the longer historical record since 1901. The temporal and regional articulations of
737
several severe droughts since 1979 were significantly conditioned by SST forcing, most
738
notably the southeast drought of 2000, the Texas drought of 2011, and the central
739
Great Plains drought of 2012. In the case of the severe northern Great Plains drought
26
740
of 1988, no appreciable SST conditioning appeared to occur, and that event most
741
likely resulted primarily from internal atmospheric variability. Even in the other three
742
events, the ocean forced signal of low soil moisture was typically a factor of 2 weaker
743
than the observed soil moisture deficits, affirming again that a complete explanation of
744
these droughts must invoke not just the ocean forcing but also the particular sequence
745
of internal atmospheric variability - weather - during the event.
746
• Temporal variability of estimated contiguous U.S. soil moisture shows a sharp de-
747
crease in the late 1990s, and the percent of the U.S. experiencing moderate to severe
748
drought suddenly increased and remained at elevated levels during the first decade of
749
the 21st Century. Atmospheric climate models simulate this abrupt change quite well
750
as a response to changes in SSTs. Our assessment of known SST relationships with
751
U.S. drought, and a diagnosis of additional climate simulations that exclude long-term
752
trends in boundary and external radiative forcing lead to a conclusion that natural
753
modes of decadal SST variability have been of primary importance. This includes a
754
cooling of the tropical Pacific associated with increased occurrences of La Nina events
755
post-1998 and an enhanced decadal warming of the tropical North Atlantic, both con-
756
ditions conducive for reduced U.S. precipitation, increased surface temperature, and
757
reduced soil moisture.
758
• Diagnosis of model simulations of the effects of long-term changes in observed global
759
SSTs, sea ice, and trace gas concentrations since 1880 indicate a strong signal of U.S.
760
warming having maximum amplitude over the southwestern U.S. consistent in spatial
761
pattern and magnitude with historical observations. The warming leads to a simulated
762
long-term reduction in soil moisture, which though of weak magnitude compared to soil
763
moisture deficits induced by naturally occurring droughts in the southwest U.S.,would
764
imply that drought conditioning may be entered more quickly and alleviated more
765
slowing due to long-term warming. Long-term annual mean precipitation changes
766
in response the changes in forcing are small and mostly undetectable at this time
767
compared to natural variability.
27
768
To conclude, North America has an impressive, varied and never-ending history of droughts.
769
Much of this history can be explained in terms of forcing of atmospheric circulation anoma-
770
lies from the tropical Pacific and Atlantic Oceans. This component is potentially predictable
771
although tropical Pacific predictability is limited to at most one year and tropical Atlantic
772
predictions essentially rely on persistence. SST prediction can provide some measure of
773
atmospheric prediction though more so in the winter than the summer half year. In addi-
774
tion, the details of any one drought or any one year will be heavily influenced by internal
775
atmospheric variability that is unpredictable beyond the timescale of numerical weather pre-
776
diction. Such atmosphere-only variability lends the extreme character to particular events
777
like the droughts of 2011 and 2012, even though these were at least in some way influenced
778
by La Niña conditions and can, on occasion prevent a widespread drought occurring even
779
when ocean conditions were apparently ripe to generate a drought, as in 1973-5. As such,
780
drought predictability will remain limited for the foreseeable future and probably for ever.
781
Radiative forcing of the climate system is another source of predictability, though not re-
782
ally a welcome one, and rising greenhouse gases will lead to a steady drying of southwest
783
North America. However this is a change that is only now beginning to emerge and cur-
784
rently is exerting less influence on precipitation variability than ocean variability or internal
785
atmospheric variability.
786
Acknowledgments.
787
RS was supported by NOAA awards NA10OAR4310137 (Global Decadal Hydroclimate
788
Variability and Change) and NA08OAR4320912. We thank Jennifer Nakamura for con-
789
ducting statistical analyses and preparing figures, Naomi Henderson and Dong Eun Lee for
790
conducting the CCM3 integrations, Dr. XiaoWei Quan and Phil Pegion for various model
791
simulations and Jon Eischeid for data analysis and the NOAA Climate Program Office for
792
support.
28
793
794
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980
List of Figures
1
The variance of annual mean observed precipitation (top left) and that sim-
981
ulated by the CCM3 model forced by observed historical SSTs (upper right).
982
The variance of the ensemble mean modeled annual mean precipitation, that
983
is the SST-forced variance (lower left) and the ratio of the modeled SST-forced
984
to total variance (bottom right).
985
2
40
The first three EOFs of standardized annual mean precipitation anomalies
986
for observations (top), a single run of the climate model (middle) and the
987
ensemble mean of the model simulations (bottom). The percentage of total
988
variance explained is noted on each panel.
989
3
The correlation of SST anomalies with the PCs associated with the EOF
990
patterns shown in Figure 2. Results for observations are in the top row, for a
991
single run of the climate model in the middle row and for the ensemble mean
992
of the model simulations in the bottom row.
993
4
standard deviation ensemble spread shown by shading) history of annual mean
995
precipitation for the Great Plains (top) and southwest North America (upper
996
middle). The observed annual mean precipitation for the Great Plains (lower
997
middle) and southwest North America (bottom) together with the tropical
998
Pacific SST history.
5
42
The observed (solid line) and modeled (ensemble mean as dashed line with two
994
999
41
43
Annual mean precipitation anomalies across southwest North America com-
1000
puted from 16 simulations of an atmosphere model forced by observed SSTs
1001
and with the ensemble mean subtracted from each in order to emphasize vari-
1002
ations due to internal atmospheric variability. The observed history since
1003
1901 is also plotted on each for reference although no correspondence in time
1004
is expected.
44
37
1005
6
The observed SST, 200hPa geopotential height and North American precip-
1006
itation anomalies during droughts in 1953-6 and 1999-2002 and the 1973-5
1007
event. Units are Kelvin, geopotential meters and mm per month.
45
46
1008
7
Same as Figure 6 but for the model simulation.
1009
8
The spatial pattern (top, left) and PC time series (bottom) of the first em-
1010
pirical orthogonal function (EOF1) of monthly soil moisture. Analysis is of
1011
the correlation matrix of 408 monthly samples of CPC estimated soil mois-
1012
ture during January 1979-December 2012. U.S. map plots the local correla-
1013
tion of monthly soil moisture with the PC time series. (top, right) Monthly
1014
correlation of the PC time series with observed surface temperatures during
1015
1979-2012.
47
1016
9
Same as Figure 8 but for the second EOF.
48
1017
10
Same as Figure 8 but for the third EOF.
49
1018
11
Estimate of annually averaged soil moisture departures (mm, left) for 1988
1019
(top), 2000 (second), 2011 (third), and 2012 (bottom). Outline highlights
1020
core region for each drought event. One point correlation maps (right) of the
1021
monthly soil moisture variability at all 344 U.S. climate divisions with the
1022
1979-2012 time series of soil moisture averaged for each of the four drought
1023
regions.
1024
12
50
Simulated annually averaged soil moisture departures (mm, left) for 1988
1025
(top), 2000 (second), 2011 (third), and 2012 (bottom) based on a 40-member
1026
ensemble mean of models forced by the observed SST, sea, ice, and atmo-
1027
spheric trace gas variability. Outline highlights core region for each observed
1028
drought event. Soil moisture probability distribution functions of the 40 sep-
1029
arate climate simulations (red), with the observed (black bar) and estimate
1030
long-term climate change (see text) departures.
38
51
1031
13
Monthly time series of the percent area of the contiguous U.S. with estimate
1032
soil moisture anomalies less than 1 standardized departure (brown). Sam anal-
1033
ysis based on the ensemble averaged of fully forced CAM4 simulations (blue),
1034
fully forced ECHAM5 simulations (red), and a parallel ensemble of ECHAM5
1035
(ECHAM5-PI) simulations in which trace gas forcings are set to climatologi-
1036
cal 1880 conditions and the 1880-2012 linear trend in SSTs is removed from
1037
the monthly SST variability.
1038
14
52
Simulated long-term change in annual mean climatological precipitation (top),
1039
soil moisture (middle), and surface temperature (bottom). Computed from
1040
the difference between fully-forced ECHAM5 simulations for 1979-2012 and
1041
the ECHAM5-PI runs in which trace gas forcings are set to climatological
1042
1880 conditions and the 1880-2012 linear trend in SSTs is removed from the
1043
monthly SST variability.
53
39
Annual Mean Precipitation Variance (mm2 month−2) 1901-2009
30˚N
30˚N
latitude
Latitude
60˚N
b) CCM3 Average of Members
60˚N
a) Observed
150˚W
120˚W
90˚W
60˚W
150˚W
120˚W
longitude
90˚W
60˚W
Longitude
0
50
100
150
200
250
300
Precip Variance [mm^2 month^-2]
d) Ratio of c to b
30˚N
30˚N
latitude
latitude
60˚N
60˚N
c) CCM3 Mean
150˚W
120˚W
90˚W
150˚W
60˚W
120˚W
0
50
100
150
90˚W
60˚W
longitude
longitude
200
250
300
Precip Variance [mm^2 month^-2]
0
0.04
0.08
0.12
0.16
0.2
0.24
0.28
0.32
0.36
0.4
Precip variance ratio
Fig. 1. The variance of annual mean observed precipitation (top left) and that simulated
by the CCM3 model forced by observed historical SSTs (upper right). The variance of the
ensemble mean modeled annual mean precipitation, that is the SST-forced variance (lower
left) and the ratio of the modeled SST-forced to total variance (bottom right).
40
0.44
0.48
EOF 1
90˚W
80˚W
70˚W
60˚W
60˚N
130˚W
120˚W
110˚W
100˚W
90˚W
80˚W
110˚W
100˚W
90˚W
80˚W
70˚W
60˚W
100˚W
90˚W
80˚W
70˚W
60˚W
70˚W
60˚W
15%
130˚W
120˚W
110˚W
100˚W
90˚W
80˚W
70˚W
60˚W
60˚N
50˚N
40˚N
30˚N
130˚W
120˚W
110˚W
100˚W
90˚W
80˚W
70˚W
60˚W
10%
130˚W
-20%
-10%
0%
10%
20%
120˚W
110˚W
100˚W
90˚W
80˚W
70˚W
longitude
longitude
-30%
60˚W
latitude
50˚N
40˚N
30˚N
15%
20˚N
80˚W
70˚W
longitude
latitude
40˚N
90˚W
longitude
80˚W
60˚N
110˚W
60˚N
60˚N
50˚N
latitude
30˚N
100˚W
90˚W
8% 15%
longitude
20˚N
110˚W
100˚W
40˚N
120˚W
38%
120˚W
110˚W
latitude
130˚W
longitude
130˚W
120˚W
30˚N
11%
20˚N
120˚W
130˚W
50˚N
60˚N
50˚N
30˚N
40˚N
latitude
50˚N
40˚N
latitude
30˚N
20˚N
130˚W
20˚N
60˚W
longitude
23%
GOGA
Mean
70˚W
longitude
60˚N
longitude
20˚N
100˚W
6%
20˚N
110˚W
30˚N
40˚N
latitude
50˚N
60˚N
50˚N
40˚N
latitude
120˚W
8%
20˚N
20˚N
15%
130˚W
GOGA 1
EOF 3
30˚N
40˚N
30˚N
Observed
latitude
50˚N
60˚N
EOF 2
30%
Precipitation
Fig. 2. The first three EOFs of standardized annual mean precipitation anomalies for
observations (top), a single run of the climate model (middle) and the ensemble mean of the
model simulations (bottom). The percentage of total variance explained is noted on each
panel.
41
60˚W
EOF 1
60˚E
90˚E
120˚E
150˚E
180˚
150˚W 120˚W
90˚W
60˚W
30˚W
0˚
60˚N
60˚S
30˚S
0˚
latitude
30˚N
60˚N
30˚N
0˚
latitude
60˚S
30˚E
30˚E
60˚E
90˚E
120˚E
150˚E
180˚
90˚W
60˚W
30˚W
0˚
60˚E
90˚E
120˚E
150˚E
180˚
150˚W 120˚W
90˚W
60˚W
30˚W
150˚E
180˚
150˚W 120˚W
90˚W
60˚W
30˚W
90˚W
60˚W
30˚W
0˚
30˚E
60˚E
-0.8
0˚
90˚E
120˚E
150˚E
180˚
150˚W 120˚W
90˚W
60˚W
30˚W
90˚W
60˚W
30˚W
60˚N
30˚N
0˚
30˚S
60˚S
0˚
30˚E
60˚E
90˚E
120˚E
150˚E
180˚
150˚W 120˚W
90˚W
60˚W
30˚W
0˚
30˚E
60˚E
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
90˚E
120˚E
150˚E
180˚
150˚W 120˚W
longitude
longitude
-1
30˚W
latitude
30˚N
150˚W 120˚W
60˚W
longitude
0˚
180˚
longitude
90˚W
60˚N
120˚E
30˚S
150˚E
150˚W 120˚W
0˚
90˚E
60˚S
120˚E
180˚
latitude
60˚E
latitude
0˚
90˚E
150˚E
30˚S
30˚E
60˚N
60˚N
30˚N
latitude
30˚S
60˚E
120˚E
longitude
60˚S
30˚E
90˚E
60˚S
0˚
longitude
0˚
60˚E
30˚N
60˚N
30˚N
0˚
30˚S
60˚S
30˚E
30˚E
longitude
latitude
30˚N
0˚
latitude
30˚S
60˚S
0˚
GOGA
Mean
150˚W 120˚W
longitude
60˚N
longitude
GOGA 1
EOF 3
30˚S
0˚
60˚S
30˚S
Observed
latitude
30˚N
60˚N
EOF 2
0.8
1
correlation
Fig. 3. The correlation of SST anomalies with the PCs associated with the EOF patterns
shown in Figure 2. Results for observations are in the top row, for a single run of the climate
model in the middle row and for the ensemble mean of the model simulations in the bottom
row.
42
Observed (solid) and GOGA model (dash) +/− 2 STD (grey) Great Plains Precipitation
0.32
0.5
0
−0.5
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
Observed (solid) GOGA model (dash) +/− 2 STD (grey) Southwest Precipitation
0.48
0.5
0
−0.5
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
Observed Great Plains Precipitation (solid) and Tropical Pacific SST (dashed)
1.5
0.40
1
0.5
0
−0.5
−1
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
Observed Southwest Precipitation (solid) and Tropical Pacific SST (dashed)
1.5
0.52
1
0.5
0
−0.5
−1
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
Time
Fig. 4. The observed (solid line) and modeled (ensemble mean as dashed line with two
standard deviation ensemble spread shown by shading) history of annual mean precipitation
43
for the Great Plains (top) and southwest North
America (upper middle). The observed
annual mean precipitation for the Great Plains (lower middle) and southwest North America
(bottom) together with the tropical Pacific SST history.
1900
1950
1950
20
10
0
−10
20
10
0
−10
20
10
0
−10
20
10
0
−10
20
10
0
−10
2000
2000
2000
2000
2000
2000
2000
20
10
0
−10
16
15
1900
1950
2
13
20
10
0
−10
1900
1950
4
11
20
10
0
−10
1900
1950
6
9
20
10
0
−10
1900
1950
20
10
0
−10
8
7
20
10
0
−10
1900
1950
10
5
20
10
0
−10
1900
12
3
20
10
0
−10
20
10
0
−10
14
1
20
10
0
−10
1900
1950
2000
1900
1950
2000
1900
1950
2000
1900
1950
2000
1900
1950
2000
1900
1950
2000
1900
1950
2000
1900
1950
2000
1900
1950
2000
20
10
0
−10
Fig. 5. Annual mean precipitation anomalies across southwest North America computed
from 16 simulations of an atmosphere model forced by observed SSTs and with the ensemble
mean subtracted from each in order to emphasize variations due to internal atmospheric
variability. The observed history since 1901 is also plotted on each for reference although no
correspondence in time is expected.
44
Observed
SSTA and 200 mb Heights
Precipitation
-15
-22.5
-15
-15
30˚S
-7.5
-7.5
-75
60˚S
30˚E
60˚E
-52.5
-67.5
-60
-52.5
90˚E
120˚E
150˚E
180˚
-7.5
-22.5
-45 -30
-37.5-30
-52.5
-37.5
-45
-22.5
-15
-7.5
0
7.5
15
37.522.5
150˚W 120˚W
-7.5
-60-67.5
-75
-67.5-60
-75
-82.5
-7.5 7.5
0
90˚W
60˚W
40˚N
0
-7.5
latitude
0˚
-7.5
50˚N
0
-15
30˚N
30˚N
7.5
22.515
0
30˚W
15
20˚N
60˚N
15
4537.5
30
Latitude
60˚N
1952-1956
52.5 60
0˚
30˚E
130˚W
Longitude
120˚W
110˚W
100˚W
90˚W
80˚W
70˚W
60˚W
90˚W
80˚W
70˚W
60˚W
90˚W
80˚W
70˚W
60˚W
longitude
50˚N
-7.5
-15
-7.5
-15
-15
-22.5
-15
-15
0˚
-30
-15
-30
-22.5
-15
0
0
30˚E
-7.5
-37.5
-30
-22.5
-15
60˚E
90˚E
120˚E
150˚E
180˚
150˚W 120˚W
90˚W
60˚W
-7.5
20˚N
60˚S
15
-22.5
-7.5-15
30˚N
30
40˚N
-30 -22.5
30˚N
0
-7.5
0 -7.5
latitude
60˚N
-30
-22.5
-30
30˚S
Latitude
60˚N
1973-1975
-45
30˚W
0˚
30˚E
130˚W
Longitude
120˚W
110˚W
100˚W
longitude
60˚N
7.5
-7.5
0
7.5
7.5
22.5
50˚N
22.5
0
-15
0
22.5
60˚S
157.5
30˚E
60˚E
0
90˚E
120˚E
150˚E
15
0
180˚
150˚W 120˚W
7.5
90˚W
22.5
30
30
37.5
30˚N
15
45 37.5
30
37.5
7.5
60˚W
30˚W
40˚N
7.5
20˚N
0˚
0
latitude
-7.5
7.5
30˚S
Latitude
30˚N
15
15
15
0
-7.5
60˚N
1999-2002
0˚
30˚E
130˚W
Longitude
-0.8˚C
-0.6˚C
-0.4˚C
-0.2˚C
0˚C
0.2˚C
120˚W
110˚W
100˚W
longitude
0.4˚C
0.6˚C
0.8˚C
-20
SSTA
-16
-12
-8
-4
0
4
8
12
precipitation [mm/month]
Fig. 6. The observed SST, 200hPa geopotential height and North American precipitation
anomalies during droughts in 1953-6 and 1999-2002 and the 1973-5 event. Units are Kelvin,
geopotential meters and mm per month.
45
16
20
GOGA Mean
SSTA and 200 mb Heights
Precipitation
60˚N
60˚N
1952-1956
0
-7.5
0
50˚N
latitude
0˚
-15
-15
30˚N
-15
-7.5
60˚E
-22.5
-15
90˚E
120˚E
150˚E
180˚
20˚N
60˚S
-7.5
30˚E
40˚N
30˚N
-7.5
30˚S
latitude
0
0
150˚W 120˚W
90˚W
60˚W
30˚W
0˚
30˚E
130˚W
longitude
120˚W
110˚W
100˚W
90˚W
80˚W
70˚W
60˚W
90˚W
80˚W
70˚W
60˚W
90˚W
80˚W
70˚W
60˚W
longitude
60˚N
60˚N
1973-1975
-15
-15
0
0
-7.5
7.5
50˚N
-15
7.5
60˚S
30˚N
-7.5
7.5
0
15
0
-7.5
20˚N
-22.5 -15
40˚N
-15
latitude
0˚
-22.5
-30
30˚S
latitude
30˚N
0
30˚E
60˚E
90˚E
120˚E
150˚E
180˚
150˚W 120˚W
90˚W
60˚W
30˚W
0˚
30˚E
130˚W
longitude
120˚W
110˚W
100˚W
longitude
0
30
22.5
22.5
50˚N
30˚N
22.5
22.5
0˚
latitude
0
15
7.5
15
15
22.5
30˚N
30˚S
60˚S
7.5
-7.5
30˚E
60˚E
90˚E
120˚E
150˚E
180˚
150˚W 120˚W
0
0
90˚W
60˚W
30˚W
20˚N
latitude
60˚N
15
15
40˚N
60˚N
1999-2002
0˚
30˚E
130˚W
longitude
-0.8˚C
-0.6˚C
-0.4˚C
-0.2˚C
0˚C
120˚W
110˚W
100˚W
longitude
0.2˚C
0.4˚C
0.6˚C
0.8˚C
-20
SSTA
-16
-12
-8
-4
0
4
precipitation [mm/month]
Fig. 7. Same as Figure 6 but for the model simulation.
46
8
12
16
20
Fig. 8. The spatial pattern (top, left) and PC time series (bottom) of the first empirical
orthogonal function (EOF1) of monthly soil moisture. Analysis is of the correlation matrix of
408 monthly samples of CPC estimated soil moisture during January 1979-December 2012.
U.S. map plots the local correlation of monthly soil moisture with the PC time series. (top,
right) Monthly correlation of the PC time series with observed surface temperatures during
1979-2012.
47
Fig. 9. Same as Figure 8 but for the second EOF.
48
Fig. 10. Same as Figure 8 but for the third EOF.
49
Fig. 11. Estimate of annually averaged soil moisture departures (mm, left) for 1988 (top),
2000 (second), 2011 (third), and 2012 (bottom). Outline highlights core region for each
drought event. One point correlation maps (right) of the monthly soil moisture variability
50
at all 344 U.S. climate divisions with the 1979-2012 time series of soil moisture averaged for
each of the four drought regions.
Fig. 12. Simulated annually averaged soil moisture departures (mm, left) for 1988 (top),
2000 (second), 2011 (third), and 2012 (bottom) based on a 40-member ensemble mean of
models forced by the observed SST, sea, ice, and atmospheric trace gas variability. Outline
highlights core region for each observed drought event. Soil moisture probability distribution
51
functions of the 40 separate climate simulations (red), with the observed (black bar) and
estimate long-term climate change (see text) departures.
Fig. 13. Monthly time series of the percent area of the contiguous U.S. with estimate
soil moisture anomalies less than 1 standardized departure (brown). Sam analysis based
on the ensemble averaged of fully forced CAM4 simulations (blue), fully forced ECHAM5
simulations (red), and a parallel ensemble of ECHAM5 (ECHAM5-PI) simulations in which
trace gas forcings are set to climatological 1880 conditions and the 1880-2012 linear trend in
SSTs is removed from the monthly SST variability.
52
Fig. 14. Simulated long-term change in annual mean climatological precipitation (top),
soil moisture (middle), and surface temperature (bottom). Computed from the difference
between fully-forced ECHAM5 simulations for 1979-2012 and the ECHAM5-PI runs in which
trace gas forcings are set to climatological 1880 conditions and the 1880-2012 linear trend in
SSTs is removed from the monthly SST variability.
53