Large contribution from anthropogenic warming to an emerging North American megadrought

Abstract

A trend of warming and drying
Global warming has pushed what would have been a moderate drought in southwestern North America into megadrought territory. Williams et al. used a combination of hydrological modeling and tree-ring reconstructions of summer soil moisture to show that the period from 2000 to 2018 was the driest 19-year span since the late 1500s and the second driest since 800 CE (see the Perspective by Stahle). This appears to be just the beginning of a more extreme trend toward megadrought as global warming continues.
Science , this issue p. 314 ; see also p. 238

Full text

DROUGHT
Large contribution from anthropogenic warming
to an emerging North American megadrought
A. Park Williams
1
*, Edward R. Cook
1
, Jason E. Smerdon
1
, Benjamin I. Cook
1,2
, John T. Abatzoglou
3,4
,
Kasey Bolles
1
, Seung H. Baek
1,5
, Andrew M. Badger
6,7,8
, Ben Livneh
6,9
Severe and persistent 21st-century drought in southwestern North America (SWNA) motivates
comparisons to medieval megadroughts and questions about the role of anthropogenic climate change.
We use hydrological modeling and new 1200-year tree-ring reconstructions of summer soil moisture
to demonstrate that the 2000–2018 SWNA drought was the second driest 19-year period since
800 CE, exceeded only by a late-1500s megadrought. The megadrought-like trajectory of 2000–2018
soil moisture was driven by natural variability superimposed on drying due to anthropogenic
warming. Anthropogenic trends in temperature, relative humidity, and precipitation estimated from
31 climate models account for 47% (model interquartiles of 35 to 105%) of the 2000–2018 drought
severity, pushing an otherwise moderate drought onto a trajectory comparable to the worst SWNA
megadroughts since 800 CE.
Southwestern North America (SWNA; west-
ern United States and northern Mexico:
30°N to 45°N, 105°W to 125°W) has been
anomalously dry and warm in the 21st
centuryrelativetothe20thcentury(1–3).
The 21st-century drought severity has been re-
flected in reduced snowpack (4), reduced river
flow and lake levels (5), declines in ground-
water availability (6,7), shifts in agricultural
activities (8), forest drought stress (9), increased
wildfire activity (10), and reduced vegetation
carbon uptake (11).
Paleoclimatic proxies indicate that SWNA
experienced many severe swings in hydrocli-
mate before the observed period. In particular,
tree-ring records reveal several megadrought
events during the Medieval era and subse-
quent centuries (~850–1600 CE) that dwarfed
all droughts in the following 400 years in in-
tensity and duration (12). These megadroughts
were likely associated with cool eastern trop-
ical Pacific sea surface temperatures, which pro-
mote an atmospheric wave train that blocks
Pacific storms from reaching SWNA (13–15).
Any attribution of recent drought to anthro-
pogenic climate change must consider this re-
gion’s capacity for large internal hydroclimatic
variability (16,17). Although 21st-century drought
conditions have been clearly promoted by nat-
ural Pacific Ocean variability (18–20), certain
elements are also consistent with projected
drying due to anthropogenic radiative forcing
(21–23). Cold-season precipitation deficits across
the southwestern United States and north-
ern Mexico are consistent with modeled pole-
ward expansion of the subtropics, albeit with
large uncertainties in models and observa-
tions (24,25). Observed warming since the
early 1900s is more uniformly consistent with
model simulations of anthropogenic trends,
decreasing SWNA runoff and warm-season
soil moisture by reducing snowpack and in-
creasing evaporative demand (26–28). Mod-
els project that 21st-century SWNA summer
droughts will intensify owing to declining
spring precipitation in the southern portion of
the region and continued warming-induced
reductions of summer runoff and soil mois-
ture (22–24,29).
Here, we use 1586 tree-ring chronologies
to reconstruct 0- to 200-cm summer (June to
August) soil moisture and snow water equiva-
lent (hereinafter termed “soil moisture”collec-
tively) anomalies on a 0.5° latitude-longitude grid
back to 800 CE across western North America
[(30); Fig. 1]. Soil-moisture anomalies are
standardized relative to the entire 800–2018
CE period, and the magnitude of negative
anomalies indicates drought severity. The soil-
moisture record targeted in the reconstruction
covers 1901–2018 and is referred to as Noah-
calibrated soil moisture (31).Becausetrueob-
servations of soil moisture do not exist, this
soil-moisture record is modeled based on ob-
served climate. Monthly precipitation, temper-
ature, humidity, wind speed, and radiation
data are used to force a bucket-type water-
balance model with intermonth persistence
tuned to emulate the Community Noah land-
surface model (32) (fig. S1). The reconstruction
method is the same method that has been
used to develop previous continental drought
atlases (16). Reconstruction skill is evaluated
as the squared Pearson’s correlation (R
2
) be-
tween observations during the 1901–1983
calibration period and out-of-sample recon-
struction values that were calculated by using
leave-10-out cross-validation (30). Reconstruc-
tion skill is highly significant (P< 0.01) across
much of SWNA (Fig. 1A). The cross-validated
R
2
for the SWNA regionally averaged recon-
struction is 0.86 back to 1700 CE (Fig. 1B). Skill
reduces back in time owing to loss of tree-ring
chronologies but remains above 0.73, even
when using the subset of tree-ring chronolo-
gies extending back to 800 CE (Fig. 1B).
We evaluated 19-year running means of
reconstructed and observed soil-moisture
anomalies for explicit contextualization of the
dry 2000–2018 period. Running-mean values
are assigned to the final year in each 19-year
window. During 800–2018 CE, there were 40
prolonged drought events with more than one
negative SWNA 19-year running-mean soil-
moisture anomaly. We rank the severity of
each prolonged drought event based on the
event’s most negative 19-year soil-moisture
anomaly. Definitions of megadrought vary,
but in North America, they generally refer to
multidecade drought events that contained
periods of very high severity and were longer
lasting than any event observed in the 19th
or 20th centuries (12). Here we identify the
strongest SWNA megadroughts in the recon-
struction as the prolonged drought events
that contained at least one 19-year anomaly
that was 0.25 standard deviations (s)moreneg-
ative than any observed in the 20th century.
The regionally averaged SWNA reconstruction
(Fig. 1C) reveals four megadroughts that sat-
isfy this criterion in the late 800s, mid-1100s,
1200s, and late 1500s.
The 21st-century prolonged drought event
(still ongoing as of 2020 given our definition)
registered its first negative SWNA 19-year
anomaly in 1996–2014, and its most negative
anomaly (2000–2018) was −0.74 s; the late-
1500s megadrought was the only reconstructed
event with a more negative 19-year soil-m oisture
anomaly than that in 2000–2018 (Fig. 1C).
ThemostsevereSWNA19-yearsoil moisture
anomaly during the late-1500s megadrought
was −0.80 sin 1575–1593. The 2000–2018
drought severity was nevertheless within the
uncertainty ranges of several other 19-year
drought severities, and the late-1500s event
contained six 19-year anomalies more nega-
tive than that in 2000–2018. Within SWNA,
local drought rankings during the 21st-century
event were generally not as high as the rank-
ing of the regionally averaged drought (Fig.
1D). Only 37% of SWNA experienced a local
19-year drought severity that ranked among
the top five since 800 CE, a smaller aerial
extent of high-ranking drought than occurred
RESEARCH
Williams et al., Science 368, 314–318 (2020) 17 April 2020 1of5
1
Lamont-Doherty Earth Observatory of Columbia
University, Palisades, NY 10964, USA.
2
NASA Goddard
Institute of Space Studies, New York, NY 10025, USA.
3
Department of Geography, University of Idaho, Moscow,
ID 83844, USA.
4
Management of Complex Systems
Department, UC Merced, Merced, CA 95343, USA.
5
Department of Earth and Environmental Sciences,
Columbia University, New York, NY 10027, USA.
6
Cooperative Institute for Research in Environmental
Sciences, University of Colorado Boulder, Boulder, CO
80302, USA.
7
Universities Space Research Association,
Columbia, MD 21046, USA.
8
NASA Goddard Space Flight
Center,Greenbelt,MD,USA20771,USA.
9
Civil,
Environmental, and Architectural Engineering, University
of Colorado Boulder, Boulder, CO 80309, USA.
*Corresponding author. Email: williams@ldeo.columbia.edu
on April 17, 2020 http://science.sciencemag.org/Downloaded from

during any of the four most severe reconstructed
megadroughts (Fig. 1D). Notably, the four mega-
droughts in Fig. 1 were longer than the 21st-
century drought thus far, giving grid cells more
chances to register high-ranking 19-year drought
severities. Conversely, the 21st-century drought
is the only event in which all SWNA grid cells
registered at least one below-average 19-year
soil-moisture anomaly.
The above results are consistent across alter-
nate reconstructions with longer calibration
periods that extend beyond 1983 (using fewer
tree-ring records), with 2000–2018 always rank-
ing second driest (fig. S2A). The above results are
also consistent with alternate reconstruc-
tions of the self-calibrated Palmer Drought
Severity Index [scPDSI; (33)] and soil mois-
ture simulated by the Variable Infiltration
Capacity hydrological model [VIC; (34)], but
the reconstruction targeting VIC soil moisture
has considerably less skill than the reconstruc-
tions targeting Noah-calibrated soil moisture or
scPDSI [(30); fig. S2, B and C]. The alternate
reconstructions of scPDSI and VIC soil mois-
ture agree with our primary reconstruction in
placing 2000–2018 within the two most severe
prolonged SWNA droughts in at least 1200 years
(fig. S2, B and C).
To address the contribution of anthropo-
genic climate change, we evaluated 1901–2018
trends in precipitation, temperature, and rela-
tive humidity simulated with 31 climate mod-
els in the fifth phase of the Coupled Model
Intercomparison Project (CMIP5). During
2000–2018, the multimodel mean anthropo-
genic warming in SWNA was 1.2°C [model
interquartiles (IQs): 1.0° to 1.5°C], with all
models simulating warming (Fig. 2A). Anthro-
pogenic warming increased the annual mean
atmospheric vapor-pressure deficit by 9.6%
(IQs: 8.4 to 11.3%), which increased the mean
annual total evaporative demand (as estimated
by the Penman-Monteith reference evapotran-
spiration) by 59 mm, or 4.5% (IQs: 53 to 73 mm,
4.1 to 5.5%) (Fig. 2, B and C). Models disagree
on anthropogenic precipitation trends, with a
slight multimodel mean increase in the SWNA
annual total (6 mm, 1.2%; IQs: −6 to 12 mm,
−2.5 to 2.2%) (Fig. 2D).
In Fig. 2, E to H, we estimate the effect of
these anthropogenic climate trends on soil
moisture as the difference between observed
soil-moisture anomalies and those recalculated
after removing model-estimated anthropogenic
trends from the observed climate records [e.g.,
(3, 10)]. The positive effect of the slight multi-
model mean precipitation increase in northern
SWNA (Fig. 2E) is overwhelmed by the spa-
tially ubiquitous drying effect of increasing
vapor-pressure deficit simulated by all models
(Fig. 2F). Notably, the high intermodel spread
in anthropogenic precipitation trends causes
high spread among estimated soil-moisture
trends (Fig. 2, D and E), and the true uncer-
tainty may be even larger than suggested here
owing to systematic model biases (25,35).
Combined, the multimodel mean estimates of
anthropogenic trends in precipitation, temper-
ature, and humidity force a 2000–2018 SWNA
regionally averaged summer soil-moisture
anomaly of −0.35 s(IQs: −0.26 to −0.78 s)(Fig.
2G). This accounts for 47% (IQs: 35 to 105%)
of the observed anomaly (Fig. 2H). Of the 31
CMIP5 models considered, 28 (90%) simulated
climate trends that promoted SWNA drought
during 2000–2018 based on our water-balance
estimates. Twenty-five models (81%) indicated
that this altered baseline in mean climate
Williams et al., Science 368, 314–318 (2020) 17 April 2020 2of5
Fig. 1. Summer soil-
moisture reconstruction
for SWNA. (A) Cross-
validated reconstruction
skill (R
2
) using tree-ring
records that extend to 800
and 1700 CE (green con-
tour: R
2
≥0.5; gray: recon-
struction does not extend
to 800 CE; yellow box:
SWNA). (B) Time-resolved
cross-validated R
2
of the
SWNA regional reconstruc-
tion. The inset shows
observations versus cross-
validated reconstructions
during the 1901–1983
calibration interval using
tree-ring records extending
back to 800 and 1700 CE.
(C) Time series of recon-
structed (red) and ob-
served (blue) 19-year
running-mean standardized
SWNA soil moisture (gray:
95% reconstruction confi-
dence interval; blue hori-
zontal line: 2000–2018
mean; pink and green
shading: the five drought
and pluvial periods with
the most-negative and most-
positive 19-year soil-moisture
anomalies, respectively).
(D) Maps of the local rank of the most negative 19-year anomaly to occur during each of the five drought events highlighted in (C). In the maps, the aqua color indicates no
negative 19-year anomaly, and numbers in the top left corners indicate the rank of the most negative regionally averaged 19-year anomaly during each drought event.
RESEARCH |REPORT
on April 17, 2020 http://science.sciencemag.org/Downloaded from

accounted for >25% of the observed 2000–2018
SWNA soil-moisture anomaly. This net an-
thropogenic drying effect is corroborated by
the tree-ring records themselves. Reconstruc-
tion of an alternate summer soil-moisture
record recalculated after removal of CMIP5
ensemble mean temperature and relative hu-
midity trends reduces validation skill because
the recalculated soil moisture is too wet relative
to the reconstruction in recent decades (fig. S3).
When repeated for scPDSI and VIC soil
moisture, the CMIP5 multimodel mean con-
tribution to SWNA 2000–2018 drought se-
verity was 47 and 30%, respectively (fig. S4).
The weaker anthropogenic drying effect in
the VIC simulation was primarily due to desert
areas: (i) In high desert, warming reduces win-
ter snow sublimation and increases infiltra-
tion; (ii) where vegetation is sparse, increased
winter precipitation and minimal transpira-
tion enhance deep moisture storage; and (iii)
in more vegetated desert areas, soils dry to the
wilting point in summer regardless of anthro-
pogenic climate trends, erasing all soil-moisture
memory of warming-induced drying in spring
(supplementary text S1 and figs. S5 to S10).
Outside of deserts, and particularly in forested
areas, the VIC model simulates summer soil
drying driven by anthropogenic warming
through enhanced evapotranspiration and
early loss of snowpack (fig. S11).
Given known disagreement among land-
surface models in deserts where small anom-
alies are substantial relative to dry climatologies
(36) and the inherently better representation
of forested areas by the tree-ring network, we
repeated our reconstructions to target for-
ested areas only. All forest-only reconstruc-
tions still estimate 2000–2018 to be among
the two driest 19-year drought periods since
800 CE for SWNA (fig. S12, A to C). Consid-
ering SWNA forested areas only, the contri-
bution of anthropogenic climate trends to
2000–2018 drought severity increased slightly
for Noah-calibrated soil moisture and scPDSI
(to 57 and 51%, respectively) and dramatically
(to 83%) for VIC soil moisture (fig. S12, D to
F). This stronger anthropogenic effect in the
VIC simulation is likely due to the additional
effect of warming-driven snowpack loss, which
is not accounted for directly in the Noah-
calibrated soil moisture or scPDSI. The VIC
simulations indicate a steady warming-driven
reduction to SWNA spring snowpack over the
past century that accounts for the majority of
the simulated spring snowpack anomaly in
2000–2018 (fig. S13).
Williams et al., Science 368, 314–318 (2020) 17 April 2020 3of5
Fig. 2. Effects of anthropogenic climate trends.
(Ato G) Time series plots showing the 19-year
running-mean observed anomalies (black lines) in
SWNA (yellow box in maps) for mean annual
temperature (T) (A), mean annual vapor pressure
deficit (VPD) (B), annual reference evapotranspi-
ration (ETo) (C), annual precipitation (P) (D),
and soil moisture [(E) to (G)]. Solid and dotted
colored lines represent 19-year running-mean CMIP5
multimodel mean and IQ trends, respectively
(gray lines: trends from 31 models). CMIP5 trends
are evaluated for P, T, and relative humidity (RH). In
(E) to (G), CMIP5 trends show contributions to
observed soil-moisture anomalies since 1901. The
maps show CMIP5 multimodel mean contributions to
2000–2018 anomalies (dots: >75% model agree-
ment on sign; gray: masked out because recon-
struction does not extend to 800 CE). (H) Percent
contribution of CMIP5 (bars) multimodel mean
climate trends to the 2000–2018 SWNA soil-
moisture anomaly (whiskers: model IQs). Anomalies
are relative to 1921–2000 in (A) to (D) and
800–2018 CE in (E) to (G).
Fig. 3. Development of the most severe
19-year droughts since 800 CE. Time
series of cumulative SWNA summer soil-
moisture anomalies for the 20 prolonged
droughts with the most-negative 19-year
soil-moisture anomalies. The drought
periods analyzed here begin 18 years before
the most-negative 19-year anomaly. The
dark blue line shows 2000–2018 cumulative
anomalies after removing CMIP5 multi-
model mean climate trends. The shaded
regions represent 95% confidence intervals
for the four reconstructed megadroughts
shown with the light colored lines.
RESEARCH |REPORT
on April 17, 2020 http://science.sciencemag.org/Downloaded from

The 2000–2018 drought was preceded by
the wettest 19-year period (1980–1998) in at
least 1200 years (Fig. 1C). Climate models proj-
ect enhanced precipitation variability across
much of the globe as a result of anthropogenic
climate change, and this includes a slight 21st-
century trend toward greater decadal precip-
itation swings in SWNA (37). This tendency is
also apparent in model simulations of summer
0- to 200-cm soil moisture, but this simulated
effect does not emerge until the second half
of the 21st century (fig. S14). Regardless of the
anthropogenic impact on multidecadal varia-
bility, the 1980–2018 wet-to-dry transition was
hastened by the background drying forced
from anthropogenic warming.
Figure 3 shows that the 2000–2018 drought
was on a megadrought-like trajectory through-
out its development. In the absence of anthro-
pogenic climate trends, 2000–2018 would still
rank among the 11 most severe prolonged
droughts in the reconstruction (dark blue line
in Fig. 3), but anthropogenic warming was crit-
ical for placing 2000–2018 on a trajectory con-
sistent with the most severe past megadroughts.
These results are robust regardless of the drought
metric used or whether only forested areas are
considered (fig. S15).
The results above do not account for the pos-
sibility that increased atmospheric carbon di-
oxide concentration ([CO
2
]) has ameliorated
soil-water loss by allowing plants to reduce
stomatal conductance and use water more ef-
ficiently through increased surface resistance
(r
s
) to transpiration (38). Although the effects
of enhanced [CO
2
] on vegetation and surface
water fluxes are highly uncertain (39), we ex-
plore how our results would be affected by a r
s
response to [CO
2
] as simulated by current
Earth system models. Repeating our study with
an adjusted calculation of reference evapotrans-
piration that assumes the CMIP5 multimodel
mean r
s
response to [CO
2
](40) reduces 2000–
2018 drought severity by about 20% (to −0.61 s).
This prolonged drought ranks fifth in the revised
reconstruction, still in line with the megadroughts
(fig. S16). Even with the assumed increase in r
s
,
30% of the 2000–2018 drought ’sseverityis
attributed to anthropogenic climate trends, with
81% of models simulating some degree of an-
thropogenic drying. Importantly, the potency
of the [CO
2
] effect on r
s
varies by a factor of
three among CMIP5 models (40), highlighting
considerable uncertainty in this effect.
Our relatively simple hydrological modeling
approach also does not account for coupled
land-atmosphere interactions or dynamic
vegetation responses to climate. It has been
argued that hydrological effects of anthro-
pogenic climate change are better addressed
with coupled Earth system models that di-
rectly simulate land-atmosphere coupling and
vegetation responses to changes in climate
and [CO
2
](38,41). Figure 4 shows that, of the
26 CMIP5 models with soil-moisture data avail-
able for historical and 21st-century climate sce-
narios, 23 (88%) simulate negative soil-moisture
anomalies in SWNA during 2000–2018, with
a multimodel mean of −0.50 s(IQs: −1.38 to
−0.17 s) relative to a 1850–2018 CE baseline.
Because each model simulation has its own
internal climate variability, intermodel agree-
ment on dry soil during 2000–2018 arises from
the common anthropogenic forcing. The multi-
model mean 2000–2018 anomaly derived di-
rectly from CMIP5 soil-moisture simulations is
somewhat larger than the anthropogenic effect
of −0.41 sfound when the previously calcu-
lated anthropogenic effect shown in Fig. 2G is
rescaled relative to 1850–2018 CE. The stron-
ger anthropogenic soil drying simulated by the
CMIP5 models is likely due to reduced spring-
summer mountain snowpack and enhanced
vegetation water use caused by lengthened
growing seasons and increased leaf area due
to CO
2
fertilization (39). Notably, the sim-
ulated ability for vegetation to survive and
perpetuate these modeled soil-moisture de-
clinesmaybeunrealisticbecausecurrent
Earth system models inadequately represent
nutrient and moisture limitations on vegeta-
tion activity (42–44).
The tree-ring record serves as an ominous
reminder that natural climate variability can
drive SWNA megadroughts that are as severe
and longer than the 21st-century drought thus
far. The atmosphere and ocean anomalies that
drove past megadroughts very likely dwarfed
those that occurred during 2000–2018, but
superposition of the 2000–2018 climate dy-
namics on background anthropogenic soil
drying put an otherwise moderately severe
soil-moisture drought onto a trajectory char-
acteristic of the megadroughts of 800–1600 CE.
Critical to the megadrought-like trajectory of
the 21st-century event were enhanced evapora-
tive demand, early snowpack loss, and a broad
spatial extent, all promoted by anthropogenic
warming. Natural variability may very well end
the early 21st-century drought in the coming
years, and this transition may be under way
after a wet 2019. However, our work demon-
strates that the magnitude of background an-
thropogenic soil drying is already substantial
relative to the range of natural multidecadal
variability. Furthermore, anthropogenic global
warming and its drying influence in SWNA
are likely still in their infancy. The magnitude
of future droughts in North America and else-
where will depend greatly on future rates of
anthropogenic greenhouse gas emissions glob-
ally. The effects of future droughts on hu-
mans will be further dependent on sustainable
resource use because buffering mechanisms
such as ground water and reservoir storage
are at risk of being depleted during dry times.
REFERENCES AND NOTES
1. K. M. Andreadis, E. A. Clark, A. W. Wood, A. F. Hamlet,
D. P. Lettenmaier, J. Hydrometeorol. 6, 985–1001 (2005).
2. M. Hoerling et al., Bull. Am. Meteorol. Soc. 95, 269–282 (2014).
3. A. P. Williams et al., Geophys. Res. Lett. 42, 6819–6828 (2015).
4. P. W. Mote, S. Li, D. P. Lettenmaier, M. Xiao, R. Engel,
NPJ Clim. Atmos. Sci. 1, 2 (2018).
5. M. Xiao, B. Udall, D. P. Lettenmaier, Water Resour. Res. 54,
6739–6756 (2018).
6. M. Rodell et al., Nature 557, 651–659 (2018).
7. C. C. Faunt, M. Sneed, J. Traum, J. T. Brandt, Hydrogeol. J. 24,
675–684 (2016).
8. R. Howitt, J. Medellin-Azuara, D. MacEwan, J. Lund,
D. A. Sumner, “Economic analysis of the 2014 drought for
California agriculture”(UC Davis Center for Watershed
Sciences, Davis, CA, 2014).
9. A. P. Williams et al., Nat. Clim. Chang. 3, 292–297 (2013).
10. J. T. Abatzoglou, A. P. Williams, Proc. Natl. Acad. Sci. U.S.A.
113, 11770–11775 (2016).
11. C. R. Schwalm et al., Nat. Geosci. 5, 551–556 (2012).
12. B. I. Cook et al., Wiley Interdiscip. Rev. Clim. Change 7, 411–432
(2016).
13. R. Seager et al., Quat. Sci. Rev. 26, 2322–2336 (2007).
14. B. I. Cook et al., J. Geophys. Res.Atmos. 123, 11307–11320 (2019).
15. N. J. Steiger et al., Sci. Adv. 5, eaax0087 (2019).
16. E. R. Cook et al., J. Quaternary Sci. 25,48–61 (2010).
17. C. A. Woodhouse, D. M. Meko, G. M. MacDonald, D. W. Stahle,
E. R. Cook, Proc.Natl. Acad.Sci.U.S.A.107,21283–21288 (2010).
18. T. L. Delworth, F. Zeng, A. Rosati, G. A. Vecchi, A. T. Wittenberg,
J. Clim. 28, 3834–3845 (2015).
19. R. Seager, M. Ting, Curr. Clim. Change Rep. 3,141–149 (2017).
20. F. Lehner, C. Deser, I. R. Simpson, L. Terray, Geophys. Res.
Lett. 45, 6251–6261 (2018).
21. R. Seager et al., Science 316, 1181–1184 (2007).
22. B. I. Cook, T. R. Ault, J. E. Smerdon, Sci. Adv. 1,e1400082(2015).
23. T. R. Ault, J. S. Mankin, B. I. Cook, J. E. Smerdon, Sci. Adv. 2,
e1600873 (2016).
24. M. Ting, R. Seager, C. Li, H. Liu, N. Henderson, J. Clim. 31,
4265–4279 (2018).
25. R. Seager et al., Nat. Clim. Chang. 9, 517–522 (2019).
26. T. P. Barnett et al., Science 319, 1080–1083 (2008).
27. G. J. McCabe, D. M. Wolock, G. T. Pederson, C. A. Woodhouse,
S. McAfee, Earth Interact. 21,1–14 (2017).
28. P. C. D. Milly, K. A. Dunne, Science 367, 1252–1255 (2020).
29. D. R. Cayan et al., Proc. Natl. Acad. Sci. U.S.A. 107,
21271–21276 (2010).
30. Materials and methods are available as supplementary materials.
31. A. P. Williams et al., J. Geophys. Res. Atmos. 122,
10888–10905 (2017).
32. M. B. Ek et al., J. Geophys. Res. Atmos. 108, 8851 (2003).
Williams et al., Science 368, 314–318 (2020) 17 April 2020 4of5
Fig. 4. Trends in summer soil
moisture simulated directly from
coupled models. (Left) CMIP5
19-year running-mean 0- to 200-cm
summer soil-moisture anomalies
for historical (1850–2005) and
21st-century (2006–2018) scenarios
(standardization relative to
1850–2018; gray represents
26 models; brown represents multi-
model mean, IQs). (Right)Multimodel
mean anomalies in 2000–2018 (dots represent >75% model agreement on sign; yellow box indicates SWNA).
RESEARCH |REPORT
on April 17, 2020 http://science.sciencemag.org/Downloaded from

33. N. Wells, S. Goddard,M. J. Hayes, . J. Clim. 17,2335–2351(2004).
34. X. Liang, D. P. Lettenmaier, E. F. Wood, S. J. Burges,
J. Geophys. Res. Atmos. 99, 14415–14428 (1994).
35. I. R. Simpson, R. Seager, M. Ting, T. A. Shaw, Nat. Clim. Chang.
6,65–70 (2016).
36. R. D. Koster et al., J. Clim. 22, 4322–4335 (2009).
37. A. G. Pendergrass, R. Knutti, F. Lehner, C. Deser,
B. M. Sanderson, Sci. Rep. 7, 17966 (2017).
38. A. L. S. Swann, F. M. Hoffman, C. D. Koven, J. T. Randerson,
Proc. Natl. Acad. Sci. U.S.A. 113, 10019–10024 (2016).
39. J. S. Mankin, R. Seager, J. E. Smerdon, B. I. Cook,
A. P. Williams, Nat. Geosci. 12, 983–988 (2019).
40. Y. Yang, M. L. Roderick, S. Zhang, T. R. McVicar, R. J. Donohue,
Nat. Clim. Chang. 9,44–48 (2019).
41. A. Berg, J. Sheffield, Curr. Clim. Change Rep. 4, 180–191 (2018).
42. W. K. Smith et al., Nat. Clim. Chang. 6, 306–310 (2015).
43. W. R. Wieder, C. C. Cleveland, W. K. Smith, K. Todd-Brown,
Nat. Geosci. 8, 441–444 (2015).
44. W. Yuan et al., Sci. Adv. 5, eaax1396 (2019).
45. P. Williams, Large contribution from anthropogenic warming to
an emerging North American megadrought (NCEI Accession
0209529). NOAA National Centers for Environmental
Information (2020); doi:10.25921/2vbe-8092.
ACKNOW LEDGM ENTS
This work would not be possible without the tree-ring data from
many gracious contributors, largely through the International
Tree-Ring Databank hosted by the Nati onal Oceanic and Atmospheric
Administration (NOAA). Thanks to R. Seager for helpful feedback.
Funding: Funding came from NSF AGS-1703029 (A.P.W., E.R.C.,
and K.B.), AGS-1602581 (J.E.S., A.P.W., and E.R.C.), AGS-1805490
(J.E.S.), and AGS-1243204 (J.E.S.); NASA 16-MAP16-0081 (A.P.W.
and B.I.C.); NOAA NA15OAR4310144 and NA16OAR4310132 (A.M.B.
and B.L.); and Columbia University’s Center for Climate and Life
(A.P.W.). This work utilized the Summit supercomputer, which
is supported by the National Science Foundation (awards
ACI-1532235 and ACI-1532236), the University of Colorado Boulder,
and Colorado State University. Author contributions: The
study was conceived by A.P.W., E.R.C., J.E.S., B.I.C., J.T.A., and
S.H.B. Methods were developed by all authors. Analysis was
carried out by A.P.W., J.T.A., K.B., and A.M.B. The original manuscript
was written by A.P.W., and all authors edited subsequent drafts.
Competing interests: The authors declare no competing interests.
Data and materials availability: The observed and reconstructed
climate and drought data are available at (45). LDEO contribution
number is 8392.
SUPPLEMENTARY MATERIALS
science.sciencemag.org/content/368/6488/314/suppl/DC1
Materials and Methods
Supplementary Text
Figs. S1 to S21
Tables S1 and S2
References (46–90)
23 October 2019; accepted 10 March 2020
10.1126/science.aaz9600
Williams et al., Science 368, 314–318 (2020) 17 April 2020 5of5
RESEARCH |REPORT
on April 17, 2020 http://science.sciencemag.org/Downloaded from

Large contribution from anthropogenic warming to an emerging North American megadrought
Andrew M. Badger and Ben Livneh
A. Park Williams, Edward R. Cook, Jason E. Smerdon, Benjamin I. Cook, John T. Abatzoglou, Kasey Bolles, Seung H. Baek,
DOI: 10.1126/science.aaz9600
(6488), 314-318.368Science
, this issue p. 314; see also p. 238Science
trend toward megadrought as global warming continues.
the second driest since 800 CE (see the Perspective by Stahle). This appears to be just the beginning of a more extreme
summer soil moisture to show that the period from 2000 to 2018 was the driest 19-year span since the late 1500s and
used a combination of hydrological modeling and tree-ring reconstructions ofet al.megadrought territory. Williams
Global warming has pushed what would have been a moderate drought in southwestern North America into
A trend of warming and drying
ARTICLE TOOLS http://science.sciencemag.org/content/368/6488/314
MATERIALS
SUPPLEMENTARY http://science.sciencemag.org/content/suppl/2020/04/15/368.6488.314.DC1
CONTENT
RELATED
http://science.sciencemag.org/content/sci/368/6488/252.full
http://science.sciencemag.org/content/sci/368/6488/251.2.full
http://science.sciencemag.org/content/sci/368/6488/251.1.full
http://science.sciencemag.org/content/sci/368/6488/250.full
http://science.sciencemag.org/content/sci/368/6488/238.full
http://science.sciencemag.org/content/sci/368/6488/274.full
http://science.sciencemag.org/content/sci/368/6488/270.full
http://science.sciencemag.org/content/sci/368/6488/266.full
http://science.sciencemag.org/content/sci/368/6488/261.full
http://science.sciencemag.org/content/sci/368/6488/256.full
http://science.sciencemag.org/content/sci/368/6488/234.full
http://science.sciencemag.org/content/sci/368/6488/226.full
http://science.sciencemag.org/content/sci/368/6488/254.full
REFERENCES http://science.sciencemag.org/content/368/6488/314#BIBL
This article cites 89 articles, 17 of which you can access for free
Terms of ServiceUse of this article is subject to the
is a registered trademark of AAAS.ScienceScience, 1200 New York Avenue NW, Washington, DC 20005. The title
(print ISSN 0036-8075; online ISSN 1095-9203) is published by the American Association for the Advancement ofScience
Science. No claim to original U.S. Government Works
Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of
on April 17, 2020 http://science.sciencemag.org/Downloaded from

PERMISSIONS http://www.sciencemag.org/help/reprints-and-permissions
Terms of ServiceUse of this article is subject to the
is a registered trademark of AAAS.ScienceScience, 1200 New York Avenue NW, Washington, DC 20005. The title
(print ISSN 0036-8075; online ISSN 1095-9203) is published by the American Association for the Advancement ofScience
Science. No claim to original U.S. Government Works
Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of
on April 17, 2020 http://science.sciencemag.org/Downloaded from