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Generated using version 3.1.1 of the official AMS LATEX template 1 Atmosphere and Ocean Origins of North American 2 Droughts Richard Seager 3 ∗ Lamont Doherty Earth Observatory of Columbia University, Palisades, New York Martin Hoerling 4 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. 1 5 ABSTRACT 6 The atmospheric and oceanic causes of North American droughts are examined using ob- 7 servations and ensemble climate simulations. The models indicate oceanic forcing of annual 8 mean precipitation variability accounts for up to 40 percent of total variance in northeast- 9 ern Mexico, the southern Great Plains and the Gulf Coast states but less than 10 percent 10 in central and eastern Canada. Observations and models indicate robust tropical Pacific 11 and tropical North Atlantic forcing of annual mean precipitation and soil moisture with the 12 most heavily influenced areas being in southwestern North America and the southern Great 13 Plains. In these regions, individual wet and dry years, droughts and decadal variations, 14 are well reproduced in atmosphere models forced by observed SSTs. Oceanic forcing was 15 important in causing multiyear droughts in the 1950s and at the turn of the 21st century, 16 though a similar ocean configuration in the 1970s was not associated with drought due to an 17 overwhelming influence of internal atmospheric variability. Up to half of the soil moisture 18 deficits during severe droughts in the southeast U.S. in 2000, Texas in 2011, and the central 19 Plains in 2012 were related to SST-forcing, although SST forcing was an insignificant factor 20 for northern Plains drought in 1988. During the early 21st century, natural decadal swings 21 in tropical Pacific and North Atlantic SSTs have contributed to a dry regime for the U.S. 22 Long-term changes caused by increasing trace gas concentrations are now contributing to 23 a modest signal of soil moisture depletion, mainly over the American Southwest, thereby 24 prolonging the duration and severity of naturally occurring droughts. 1 25 1. Introduction 26 In a nation that has been reeling from one weather or climate disaster to another, with 27 record tornado outbreaks, landfalling tropical storms and superstorms, record winter snow- 28 falls and severe floods, persistent droughts appear almost prosaic. Droughts do not cause the 29 mass loss of life and property destruction of floods and storms. They are instead slow-motion 30 disasters whose beginnings and ends are even often hard to identify. However, while the so- 31 cial and financial costs of hurricane, tornado and flood disasters are, of course, tremendous, 32 droughts are one of the costliest of natural disasters in the U.S. Much of that cost is related 33 to crop failure but droughts can also lead to spectacular events in the form of wildfires and 34 the costs of fighting these are immense. Further, crop failures easily translate into spikes in 35 food prices that, given the global food market, across the world. In one truly exceptional 36 case - the 1930s Dust Bowl - drought led to millions in the Great Plains leaving their homes, 37 hundreds of thousands migrating from the region, an unknown number of deaths from dust 38 pneumonia and a permanent transformation in the agriculture, economy and society of the 39 region and wider nation (Worster 1979). U.S. droughts more often than not appear as 40 components of droughts that also impact Mexico and/or Canada. For example the 1950s 41 southwest drought was also one of the worst that Mexico has experienced and Mexico has 42 been struggling with ongoing drought since the mid 1990s (Seager et al. 2009b; Stahle et al. 43 2009). Further the 1998 to 2004 drought in the U.S. which, for example, dropped Colorado 44 River storage to record lows also severely impacted much of Canada (Stewart and Lawford 45 2011; Bonsal et al. 2011). Given these trans-continental and multinational consequences of 46 drought, considerable effort has been expended to attempt to understand why they occur 47 and whether they can be predicted in advance. In recent years an increasing amount of this 48 research effort has focused on whether, where and when droughts in the U.S. will become 49 more common or severe due to climate change caused by rising greenhouse gases. 50 Despite years of study, progress in understanding the causes of North American droughts 51 only made serious headway in the last decade or so. By then the computational resources 52 were widespread enough to make possible large ensembles of long simulations with atmo- 53 sphere models forced by observed and idealized sea surface temperatures (SSTs). These 2 54 were used to test hypotheses of oceanic forcing of drought-inducing atmospheric circulation 55 anomalies. Links between North American precipitation variability and the El Niño-Southern 56 Oscillation, with, in its El Niño phase, a tendency to increased winter precipitation across 57 southern North America, had begun to be noticed in the 1970s and early 1980s (see Ras- 58 musson and Wallace (1983)) and explained in terms of Rossby wave propagation forced by 59 anomalous heat sources over the warm tropical Pacific SST anomalies (Hoskins and Karoly 60 1981). 61 to the ongoing La Niña event and Palmer and Brankovic (1988) claimed to be able to 62 produce important elements of the same drought within the European Centre for Medium 63 Range Weather Forecasts (ECMWF) numerical weather prediction model when forced by 64 the observed SSTs (but see Section 8 below). Trenberth et al. (1988) then applied linear wave theory to link the 1988 drought 65 Explaining a seasonal drought is good progress but it is the multiyear droughts that can 66 wreak the most damage. The Dust Bowl drought lasted about 8 years but was not unique in 67 this regard. Western North America experienced a severe drought from 1998 to 2004 and a 68 severe drought in the early and mid 1950s struck the southwest. Progress in understanding 69 these multiyear droughts had to wait more than a decade. Indeed, as late as 2002, a National 70 Research Council report on abrupt climate change attributed the Dust Bowl drought to 71 atmosphere-land interaction with no role for the oceans (National Research Council 2002). 72 However, in breakthrough studies, Schubert et al. (2004b) and Schubert et al. (2004a) used 73 large ensembles of atmosphere model simulations forced by observed SSTs for the post 1930 74 period to show that the model generated a 1930s drought with both persistent cold tropical 75 Pacific and warm tropical North Atlantic SST anomalies being the drivers. Following up, 76 Seager et al. (2005) and Herweijer et al. (2006) presented SST-forced atmosphere model 77 simulations for the entire post 1856 period of instrumental SST observations and showed 78 that the three observed 19th Century droughts, the Dust Bowl and the 1950s drought were 79 all simulated by the model and argued that persistent La Niña states in the tropical Pacific 80 Ocean were the essential cause of all. Tropical Pacific and Indian Ocean SST anomalies were 81 also invoked as the cause of the multiyear drought that began after the 1997/98 El NIño 82 (Hoerling and Kumar 2003; Seager 2007). The dynamical mechanisms that link tropical 83 SSTs to drought-inducing circulation anomalies have also been studied and the situation of 3 84 a cold tropical Pacific-warm tropical North Atlantic appears as ideal for inducing drought 85 (Schubert et al. 2008, 2009). 86 These studies represented considerable advances in understanding why multiyear droughts 87 occur (even though the causes of the persistent tropical SST anomalies that were the drivers 88 has been barely addressed). However these studies were in many ways broad brush. Long 89 time series, often time-filtered, were used to show that the models produced dry conditions 90 at the correct time but then precipitation, circulation, SSTs etc. were typically averaged over 91 the whole drought period, perhaps by season, for comparing model and observed droughts. 92 Such averaging will tend to emphasize the SST-forced component, which may be fundamen- 93 tal, but prevents a complete analysis of drought onset, evolution and termination. As such 94 it might prevent proper identification of non-SST forced components of the drought due to, 95 for example, random atmospheric variations (weather). 96 For example, during the 1930s Dust Bowl years, while there was no El Niño, the tropical 97 Pacific SST anomalies were only modestly cool and not consistently so but a drought ex- 98 tended from the southern Plains north to the Canadian Prairies and also towards the Pacific 99 northwest and U.S. midwest. (Fye et al. 2003; Cook et al. 2007; Stahle et al. 2007; Bonsal 100 and Regier 2007; Cook et al. 2011). Atmosphere models forced by observed SSTs do simulate 101 a drought during the 1930s with both cooler than normal tropical Pacific and warmer than 102 normal tropical North Atlantic SST anomalies being responsible. However, the droughts are 103 centered in the southwest and not in the central Plains as observed and are also too weak 104 (Schubert et al. 2004b,a; Seager et al. 2005, 2008; Hoerling et al. 2009). Two hypotheses 105 have been advanced to explain the discrepancy. The first is that the 1930s drought was 106 amplified and moved northwards by human-induced wind erosion and dust aerosol-radiation 107 interactions (Cook et al. 2008, 2009, 2010) and the other is that, instead, the Dust Bowl 108 drought contained a large component of internal atmospheric variability not linked to SST 109 anomalies (Hoerling et al. 2009). Both groups of authors draw a distinction between the 110 spatial extent and severity of the 1930s Dust Bowl drought and the 1950s southwest drought 111 with the latter appearing to be more of a canonical SST-forced drought. Similarly, North 112 America is currently within the third year of a drought that has brought successive summers 113 (2011 and 2012) of intense heat and dry conditions to the central part of the continent, from 4 114 eastern Mexico to Canada. While La Niña conditions prevailed during both summers, it is 115 not at all clear that they alone were sufficient to cause such abnormal conditions with both 116 modes of internal atmospheric variability and, perhaps, climate change having been invoked 117 to provide a full explanation (Hoerling et al. 2013c,b; Seager et al. 2013a). 118 Given this state of affairs it appears appropriate to move beyond invoking a general 119 association of drought in southwestern North America and the Plains with, primarily, La 120 Niña and, secondarily, warm tropical North Atlantic SST anomalies, to consider the causes 121 of North American droughts in more detail including assessing the role of processes unrelated 122 to ocean forcing. Of particular interest is the extent to which droughts are influenced or 123 driven by internal atmospheric variability relative to being forced by changes in surface ocean 124 conditions. This is important to the understanding of mechanisms but also has serious 125 implications for predictability of droughts. SST anomalies in the tropical Pacific Ocean 126 can be predicted up to a year in advance and, to the extent that they drive atmospheric 127 circulation anomalies over North America, can be potentially exploited to provide seasonal 128 forecasts of drought onset, evolution and termination. In contrast, aspects of droughts 129 determined by internal atmospheric variability will be unpredictable beyond the weather 130 prediction timescale. 131 In addition to the potential of SST variability, internal atmosphere processes and land- 132 atmosphere interaction to cause droughts we must also address the possibility that human- 133 induced climate change is now impacting North American hydroclimate and the frequency 134 and character of droughts. Seager et al. (2007) and Seager and Vecchi (2010) have shown 135 that a shift towards a more arid climate in southwestern North America begins in the late 136 20th Century although it is likely currently masked by natural variability (Hoerling et al. 137 2011). Also, Hoerling et al. (2013c) have shown that the heat of the 2011 Texas heat wave 138 and drought was likely aided by global warming while it was not clear that the precipitation 139 reduction was outside the range of natural variability. Weiss et al. (2009) have also noted 140 the impact of increasing temperatures on southwestern droughts, implying an emerging form 141 of drought in which a warming trend exacerbates the impacts of precipitation reductions. 142 These considerations motivate the current review paper to take three tacks: 143 • What are the relative roles of internal atmospheric variability and oceanic forcing in 5 144 generating droughts over North America? Is a general association between tropical SST 145 anomalies and North American precipitation enough to explain the intensity, spatial 146 coverage and timing of historical western North American droughts? 147 • What does the answer imply about the predictability of droughts? Are the most 148 devastating droughts, the most extensive ones that influence multiple nations and 149 agricultural areas, and both upstream and downstream reaches of large river basins, 150 ever simply the result of oceanic forcing or are they instead an unfortunate mix of SST 151 forcing and internal atmospheric variability? 152 • Even if we can answer the above question, is the scientific ground upon which we stand 153 shifting? That is, are human-induced climate trends - both warming and changes in 154 precipitation - already impacting the likelihood and severity of western North American 155 droughts? 156 To attempt to answer these questions we will use observations and a variety of model 157 simulations. This is not a typical review in that most of the material presented will be 158 new but it does seek to provide a broad review, motivated by recent research, of where we 159 stand in terms of understanding the causes and mechanisms of North American droughts 160 and to what extent we can anticipate hydroclimate variability and change, and in particular 161 droughts, in the coming seasons to decades. 162 This review is being performed under the auspices of the Global Drought Information 163 System (GDIS) which is under the World Climate Research Program (WCRP) umbrella. 164 Hence we aim to contribute to challenges identified at the July 2012 WCRP meeting including 165 under, ‘Provision of skillful future climate information on regional scales’, to ‘Identify and 166 understand phenomena that offer some degree of intra-seasonal to inter-annual predictability’ 167 and ‘Identify and understand phenomena that offer some degree of decadal predictability’. 168 Further we aim to contribute to the goal under ‘Interactions across multiplicity of drivers 169 and feedbacks at the regional scale’ to ‘Provide increased understanding of the interplay across 170 the different drivers, processes and feedbacks that characterize regional climate at different 171 spatial and temporal scales. Consider interactions across greenhouse gas forcings, natural 172 modes of variability, land use changes and feedbacks, aerosols, tropospheric constituents.’ 6 173 Models and data used are described next followed by an analysis in Sections 3 through 7 of 174 the roles of the ocean and atmosphere in explaining North American precipitation variability 175 over the past century. Section 8 then focuses in on post 1979 period in the U.S. Conclusions 176 are offered in Section 9. 177 2. Observed data and models used 178 The observed precipitation is the latest version of the Mitchell and Jones (2005) Uni- 179 versity of East Anglia (UEA) Climatic Research Unit data at 1 degree resolution (CRU 180 TS3p1). SST data in the observational analysis comes from the Hadley Center (Kennedy 181 et al. 2011a,b). The soil moisture data are an estimate of 1.6-meter depth soil moisture in 182 which a leaky bucket model is driven with observed monthly surface temperature and pre- 183 cipitation and have the spatial resolution of the U.S.Climate Divisions (Huang et al. 1993). 184 Observed geopotential height anomalies are taken from the National Centers For Environ- 185 mental Prediction-National Center for Atmospheric Research (NCEP-NCAR) Reanalysis 186 (Kistler et al. 2001). 187 We use three sets of atmosphere model simulations of the type referred to as ‘AMIP 188 (Atmospheric Model Intercomparison Project)’ experiments, which are designed to determine 189 the sensitivity of the atmosphere to, and the extent to which its temporal evolution is 190 constrained by, known boundary forcings. These are as follows. 191 • The first ensemble is used for the analysis of the variance of observed and modeled 192 precipitation histories for 1901 to 2008. This is a 16 member ensemble of SST-forced 193 atmosphere General Circulation Model simulations for the 1856 to 2011 period. The 194 model used was the National Center for Atmospheric Research Community Climate 195 Model 3 (NCAR CCM3, Kiehl et al. (1998)). The only time varying forcing was the 196 SST which was from Kaplan et al. (1998) within the tropical Pacific and the Hadley 197 Centre data elsewhere (see Seager et al. (2005) for more details). The ensemble mean 198 of these simulations closely isolates the SST-forced variations that are common to the 199 ensemble members by averaging over the uncorrelated weather variations within the 200 individual ensemble members which begin from different initial conditions on January 7 201 1 1856. Hence by subtracting the ensemble mean from each ensemble member we also 202 retrieve 16 records of modeled internal atmospheric variability. 203 • In addition, to focus on variations, especially of soil moisture, in the post 1979 period 204 we use two global atmospheric models with SST, sea ice, and external radiative forcing 205 specified as monthly time evolving boundary conditions from January 1979 to Decem- 206 ber 2012. One model used is the NCAR Community Atmosphere Model 4 (CAM4) 207 global climate model (Gent and co authors 2011), with the simulations performed at a 208 1◦ resolution and 26 atmospheric levels, and for which a 20-member ensemble is avail- 209 able. The second global climate model used is the European Center Hamburg model 210 version 5 (ECHAM5; Roeckner et al. (2003)), with simulations performed at T159 211 resolution and 31 atmospheric levels, and for which a 10-member ensemble is avail- 212 able. Each realization differs from another only in the initial atmospheric conditions 213 in January 1979, but uses identical time evolving specified forcings. For both models, 214 monthly varying SSTs and sea ice and the external radiative forcings consisting of 215 greenhouse gases (e.g. CO2 , CH4 , NO2 , O3 , CFCs) are specified. The CAM4 runs also 216 specify varying anthropogenic, solar, and volcanic aerosols. 217 • In order to address possible effects of long-term climate change on U.S. drought vari- 218 ability during 1979-2012, an additional 10-member ensemble of ECHAM5 simulations 219 is performed that uses late-19th century boundary and external radiative forcings. In 220 these so-called ECHAM5-PI experiments, trace gas forcings are set to climatological 221 1880 conditions and held fixed throughout the simulation period. Also, the 1880-2012 222 linear trend in SSTs is removed from the monthly SST variability. This sets the clima- 223 tological SSTs to values representative of 1880. The SSTs during 1979-2012 otherwise 224 vary identically to those in the AMIP simulations. Two intercomparisons of these par- 225 allel simulations are conducted. One is a simple difference of their mean climates to 226 illustrate the signal of long-term change. The second is a comparison of each models 227 interannual variability during 1979-2012 to illustrate how temporal variability of U.S. 228 drought may have been affected by long-term change. 229 For CAM4, column integrated soil moisture to a depth of 0.5m is used (though results 8 230 are mostly insensitive to using different soil moisture depths). For ECHAM5 the total 231 column soil moisture is available for diagnosis. To facilitate comparison of observed and 232 modeled soil moisture, the monthly and annual variations are standardized by each models 233 climatological variability. When comparing to climate division data, model output data has 234 been interpolated onto the U.S. climate divisions. 235 3. An estimate of the relative roles of the oceans and 236 atmosphere in generating North American precipi- 237 tation variability 238 Various factors have contributed to historical North American precipitation variability on 239 seasonal and longer time scales. These include sensitivity to global sea surface temperature 240 variability, local land surface feedbacks including persistent soil moisture states and land 241 use changes, the effects of internal atmosphere variability such as expressed by prolonged 242 circulation states associated with blocking and storm track shifts, and a sensitivity to global 243 warming resulting from changes in external radiative forcing. It is difficult to quantify 244 the contributions of individual factors from the observational record alone, and ensemble 245 climate simulations become a critical diagnostic tool. In this section, two of these factors 246 are isolated, while section 8 also examines the effects of long-term climate change on recent 247 droughts. Here we use the 16 member AMIP simulations of CCM3. The ensemble mean 248 provides an estimate of the variations common to all ensemble members due to the SST 249 forcing, while the deviations of individual realizations from the ensemble mean provides an 250 estimate of the effects of internal atmosphere variability. While definitions of drought differ, 251 there is broad agreement that a reduction of precipitation is typically required and hence we 252 begin by analyzing precipitation (section 8 will analyze soil moisture variability). In order 253 to address timescales long enough to be relevant to severe sustained drought, we analyze 254 annual mean precipitation. 255 Figure 1 shows the variance of observed annual mean precipitation. This is greatest, as 256 expected, where the precipitation is greatest, in the Pacific Northwest and the Southeast 9 257 U.S. with some other regions of high variance such as the coastal northeast and the Mexican 258 monsoon region. Also shown is the average of the variances of the individual CCM3 ensemble 259 members. This very roughly captures the observed variances in amplitude and spatial pattern 260 although with too low variance in the southeast U.S. and the eastern coastal states and 261 excess variance in Mexico. Figure 1 also shows the variance of the model ensemble mean 262 which, as expected, is everywhere much lower than the total model variance. This SST- 263 forced variance has maxima in Mexico and the south and central Plains. Finally the ratio 264 within the model of the SST-forced to the total variance is also shown. This has maxima 265 in northern Mexico, the south to central Plains and Gulf states. Here, rather remarkably, 266 up to about 40% of the model total annual mean precipitation variance is caused by SST 267 variations. Everywhere else in North America SST forcing accounts for less than a third 268 of total annual mean precipitation variance (with the lowest values in central and eastern 269 Canada) indicating that the detailed year-to-year variations of precipitation are heavily 270 influenced by internal atmospheric variability. Sustained drought on longer time scales could 271 nonetheless be appreciably influenced by ocean conditions to the extent that the latter 272 are of low frequency and that North American climate is sensitive to temporally coherent 273 patterns of such oceanic forcing. Similar conclusions were reached based on simulations with 274 a different model by Hoerling and Schubert (2010). 275 4. Modes of continental scale precipitation variability 276 Cook et al. (2011) conducted an Empirical Orthogonal Function (EOF) analysis of 277 the tree ring derived North American Drought Atlas (Cook et al. 2007) which provides 278 annual estimates of the Palmer Drought Severity Index (PDSI) reflecting surface moisture 279 availability in the spring to summer growing season. They found that the first 5 modes 280 explained 62% of the variance in the complete record. Of those 5 modes the first correlated 281 well with tropical Pacific SST variations while the second appeared to be related to North 282 Pacific atmosphere-ocean variability (not necessarily ocean-forced) and the third to tropical 283 North Atlantic SST variations. The correlations of the PCs to SSTs was strongest in the 284 tropical Pacific Ocean. These results suggested a modest, but important, amount of influence 10 285 of SSTs on continental scale modes of hydroclimate variability. 286 We conduct the same analysis here using annual mean precipitation anomalies. Figure 287 2 (top row) shows the first three EOFs of the observed detrended annual standardized 288 precipitation variability (see Ruff et al. (2012)). These explain a large fraction of the 289 contiguous US region variability, though they collectively account for only about 30% of 290 the total variability over all of North America. The first pattern has same sign anomalies 291 across almost all of the U.S. and Mexico with maximum strength in the southwest (where 292 it explains over 30% of the total precipitation variance) and opposite sign anomalies in the 293 Pacific northwest. The second pattern has a dipole pattern with centers in the Texas-north 294 Mexico region and the far west where about 20% of the local variability is explained. The 295 third pattern describes an out-of-phase relationship between annual precipitation variability 296 over the monsoon region that encompasses northwest Mexico and the American Southwest 297 and the central Great Plains, reminiscent of a summertime pattern described by Douglas 298 and Englehart (1996) and Higgins et al. (1999). 299 Figure 2 also shows the same analysis for one simulation of the climate model with global 300 SST forcing and, in addition, for the ensemble mean of the simulations. The analysis of the 301 single run should be analogous to the analysis of observations since it contains a mix of 302 ocean-forced and internal atmospheric variability and, indeed, the first two EOFs are very 303 similar to those observed and even the third pattern has some similarities. The analysis of 304 the ensemble mean isolates the ocean-forced component in the model. The first ocean-forced 305 pattern is very similar to the observed one suggesting that this pattern does indeed arise in 306 nature from ocean forcing. The second pattern also contains the north-south dipole along 307 the western coast between Mexico and the U.S. seen in the observed analysis but has wrong 308 sign anomalies in the southern Plains. 309 Figure 3 shows the correlation of the principal components of these patterns with global 310 SST anomalies. The first pattern is clearly the El Niño-Southern Oscillation (ENSO) while 311 the second pattern appears to represent a relationship between dry in Mexico and the south- 312 ern Plains and warm tropical North Atlantic SSTs. This is so in the observations, the model 313 ensemble mean and the single ensemble member which indicates that these relations between 314 precipitation and tropical Pacific and Atlantic SSTs are quite robust. The SST relations for 11 315 the third precipitation PC are not consistent across observations and models. On the ba- 316 sis of these results for precipitation variability a cold tropical Pacific-warm tropical North 317 Atlantic emerges as a particularly effective ocean state for forcing drought in the interior 318 southwest and Plains in agreement with Schubert et al. (2009). A similar link will be shown 319 in section 8 based on analysis of soil moisture variability. As noted in Figure 2, the first 320 EOFs explain 15% and 23% of the total variance for the observations and the single model 321 run, respectively and the second mode 8% and 11%. These modest values of the two clearly 322 SST-associated modes are consistent with the results shown in Figure 1. For the ensemble 323 mean the variances explained by the SST-forced modes are much higher because the inter- 324 nal atmosphere variability is largely, but not entirely, missing due to the averaging across 325 ensemble members. 326 5. Observed and modeled precipitation variations in 327 the Great Plains and southwest North America over 328 the past century 329 From what has been presented so far we would expect that the atmosphere model forced 330 by historical observed SSTs would, by simulating the ocean-forced component, capture some, 331 but by no mean all, of the observed history of precipitation over western and central regions 332 of North America. Figure 4 shows comparisons of modeled and observed precipitation for 333 both the Great Plains region (here defined as 30◦ − 50◦ N, 110◦ − 90◦ W , land areas only) and 334 southwest North America (SWNA, here defined as 25◦ − 40◦ N, 125◦ W − 95◦ W , land areas 335 only). The model ensemble mean represents the SST-forced component and the shading 336 around it is the plus and minus two standard deviation of the ensemble spread and shows 337 whether the observed precipitation anomalies ever fall outside the range of the model en- 338 semble. The best model reproduction of the observed history is in SWNA where about a 339 quarter of the observed variance of annual means can be explained in terms of SST forcing. 340 Individual wet and dry years are quite well simulated as well as the longer term variability 341 such as the wet 1980s and 1990s and the dry 1950s. The model-observations comparison for 12 342 the Great Plains is not quite so impressive but, given the similarity of the observed SWNA 343 and Plains records, many of the same points hold true. 344 The lower two panels of Figure 4 explain much of why the model is capable of reproducing 345 important features of Great Plains and SWNA precipitation history by plotting together the 346 observed precipitation history with that of SST averaged over 5◦ S − 5◦ N and 180◦ W − 347 90◦ W (the tropical Pacific, TP, index). TP correlates with Plains precipitation at 0.40 and 348 with SWNA precipitation at 0.52. The 1980s and 1990s were a time of warm El Niño-like 349 conditions (as noted first by Zhang et al. (1997)) while the dry conditions between the 1930s 350 and 1950s correspond to overall cooler La Niña-like conditions with the exception of the early 351 1940s El Niño which caused striking wet conditions in both the Plains and SWNA that are 352 well reproduced by the model. In both regions, most dry years were associated with cold TP 353 SSTs but there are exceptions to this (2003 is one) and there are also cold tropical Pacific 354 years that were not dry years. The model-tropical Pacific SSTs agreement is good (see also 355 Schubert et al. (2008)) given that we know that internal atmospheric variability accounts 356 for a larger proportion of precipitation variability than does ocean-forcing and, even for the 357 latter, the tropical Atlantic SSTs play an important role too (McCabe et al. 2004; Schubert 358 et al. 2008; Kushnir et al. 2010; Nigam et al. 2011). It is obvious that the tropical Pacific 359 Ocean is a major orchestrator of North American hydroclimate. 360 Comparisons of modeled and simulated precipitation that extend back a century or more 361 are still relatively rare but the ones that do exist confirm what would be expected on the 362 basis of Figure 1. For example, SST-forced models can reproduce precipitation history across 363 Mexico with some fidelity (Seager et al. 2009b) but the skill in the southeast U.S. is decidedly 364 low and confined to the winter season (Seager et al. 2009a) and nonexistent in the northeast 365 U.S. (Seager et al. 2012). 13 366 367 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. 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Climate, 10, 1004–1020. 36 979 980 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