The 2016 southeastern US drought: an extreme departure from centennial wetting and cooling

Abstract

The fall 2016 drought in the southeastern United States (SE US) appeared exceptional based on its widespread impacts, but the current monitoring framework that only extends from 1979-present does not readily facilitate evaluation of soil-moisture anomalies in a centennial context. A new method to extend monthly gridded soil-moisture estimates back to 1895 is developed, indicating that since 1895, October-November 2016 soil moisture (0-200 cm) in the SE US was likely the second lowest on record, behind 1954. This severe drought developed rapidly and was brought on by low September-November precipitation and record-high September-November daily maximum temperatures (Tmax). Record Tmax drove record-high atmospheric moisture demand, accounting for 28% of the October-November 2016 soil-moisture anomaly. Drought and heat in fall 2016 contrasted with 20^th-century wetting and cooling in the region, but resembled conditions more common from 1895-1956. Dynamically, the exceptional drying in fall 2016 was driven by anomalous ridging over the central United States that reduced south-southwesterly moisture transports into the SE US by approximately 75%. These circulation anomalies were likely promoted by a moderate La Niña and warmth in the tropical Atlantic, but these processes accounted for very little of the SE US drying in fall 2016, implying a large role for internal atmospheric variability. The extended analysis back to 1895 indicates that SE US droughts as strong as the 2016 event are more likely than indicated from a shorter 60-year perspective, and continued multi-decadal swings in precipitation may combine with future warming to further enhance the likelihood of such events.

1. Introduction

The southeast United States (SE US) experienced an exceptional drought in the fall of 2016. According to the United States Drought Monitor [Svoboda et al., 2002], which assesses drought severity based on a range of metrics, 92% of the area within Georgia, Alabama, Mississippi, and Tennessee was in a state of “severe drought” or worse as of November 29, 2016. The event peaked in October-November (Oct-Nov) and caused hundreds of millions of dollars of losses in crop sales [USDA, 2017a], major degradation of pasture and rangeland [USDA, 2017b], reservoir shortages leading to interstate disagreements over water rights [Samuel, 2016], and widespread wildfires [NASA, 2016]. Regarding wildfires specifically, satellite data indicate that the SE US likely had substantially more forest area burned in 2016 than in any other year since at least 1984 (Fig. 1). In Gatlinburg, Tennessee, three fires in November 2016 burned over 11,000 ha, damaging or destroying more than 2,460 structures and leading to 14 fatalities [Ahillen, 2016]. Prior to 2016, other notable SE US droughts occurred in 1954 [Chen et al., 2012a], 1986 [Cook et al., 1988; Trenberth et al., 1988], 2000 [Klos et al., 2009], and 2007 [Seager et al., 2009]. The combined effects of the 2016 drought in the SE US indicate that this may have been among the most severe droughts of the past century, but direct comparison of this event to earlier droughts is not straightforward due to a lack of long-term assessments of the regional moisture balance. For instance, the US Drought Monitor data only extend from the year 2000 to present and the drought-classification methodology has varied over time. Alternative approaches are therefore necessary to assess the 2016 SE drought in a centennial context to assess its severity, identify the dynamics that force such droughts, and improve SE US drought predictability.

Figure 1.

Satellite-derived annual forest-fire area in the SE US from 1984-2016 according to (red dots) the version 6 burned area product from the Moderate Resolution Infrared Spectrometer (MODIS; [Roy et al., 2008]) and (yellow dots) the record of large (≥202 ha) fires from the US Forest Service Monitoring Trends in Burn Severity product (MTBS; [Eidenshink et al., 2007]). MTBS records do not yet extend through 2016. Burned area is aggregated within 1/120° grid cells that are defined as having ≥75% forest cover according to the LANDFIRE Environmental Site Potential dataset (www.landfire.gov). The SE US region is outlined in the map inset, which also shows the US Drought Monitor (USDM) drought classifications on Nov 29, 2016, where white, yellow, beige, orange, red and dark red indicate no drought, abnormally dry moderate drought, severe drought, extreme drought, or exceptional drought, respectively.

For multi-decade evaluations of historical drought variability, land-surface models (LSMs; [e.g., Wood et al., 1992; Koster and Suarez, 1994; Ek et al., 2003]) are powerful tools for assessing historical drought events, quantifying the relative contributions of various components of the water balance to these droughts, and monitoring drought severity operationally [e.g., Livneh and Hoerling, 2016]. To assist with assessment of historical and ongoing hydrological variations, the 2^nd phase of the National Land Data Assimilation (NLDAS2) provides publicly available hourly grids of outputs (including soil moisture at various depths) from three LSMs covering the period from 1979 to present across the continental US, northern Mexico, and southern Canada [Xia et al., 2012a; Xia et al., 2012b]. NLDAS2 data are updated daily and are key considerations in the weekly drought assessments produced by the US Drought Monitor.

The NLDAS2 period from 1979-present is not ideal for capturing a comprehensive range of drought variability, however, because low-frequency (decadal to centennial) climate variations such as the Interdecadal Pacific Oscillation and the Atlantic Multidecadal Oscillation (AMO) are likely to cause hydroclimate variability that is not well represented in a given 30-40 year period [McCabe et al., 2004]. For the SE US, the lack of NLDAS2 simulations prior to 1979 is particularly problematic because recent decades have been wet and cool relative to the early 21^st century, perhaps causing the 2016 event to appear less likely than a longer perspective would suggest [Higgins et al., 2000; Pan et al., 2004; Wang et al., 2009; Seager et al., 2012]. Additionally, the NLDAS2 does not include supplemental simulations necessary for the attribution of observed soil-moisture anomalies to individual components of the moisture balance [e.g., Williams et al., 2015; Livneh and Hoerling, 2016]. For a longer-term perspective on historical drought variability and efficient decomposition of this variability into contributions from various drivers, bucket-type water-balance indices such as the Palmer Drought Severity Index (PDSI; [Palmer, 1965]) and the Standardized Precipitation-Evaporation Index [Vicente-Serrano et al., 2010] are often considered [e.g., Cook et al., 2014; Williams et al., 2015], but these metrics are less physically representative [e.g., Koster and Suarez, 1994] and some practitioners find standardized drought metrics less useful than more tangible quantifications such as soil-moisture content [e.g., Steinemann, 2014; 2015]. In this paper, we investigate centennial drought variability while attempting to strike a balance between the rigor of an LSM and the efficient applicability of a bucket-type water-balance calculation.

In addition to better understanding the historical context and local causes of the recent SE US drought, there is also interest in its large-scale dynamical drivers and potential links to sea surface temperature (SST) patterns relevant for hydroclimatic forecasting [e.g., Seager et al., 2009; Li et al., 2011; Nigam et al., 2011]. To date, little research has been done to better understand SE US hydroclimatic variability during the fall season specifically, when the 2016 drought impacts were most severe. While weeks or months with a high frequency of rain-free days are common in the western US, such a situation is relatively rare in the SE US [e.g., Gershunov and Cayan, 2003; Dai et al., 2007] and can therefore, at any time of year, have serious consequences for dense forests, rain-fed agriculture, and shallow reservoirs that are reliant on regular precipitation. Adding to the pace of drought onset, temperatures and solar intensity in the region are relatively high, in turn leading to relatively high evaporative demand throughout the year. The serious consequences of the SE US drought in fall 2016 therefore incentivize deeper understanding of the drought’s evolution, historical context, and causes.

In this study, we improve our understanding of the fall 2016 drought in the SE US in terms of its long-term context and dynamical drivers. We first establish a novel approach to use gridded monthly climate datasets to reliably derive estimates of soil-moisture anomalies simulated by a complex LSM back to 1895. The established record of estimated soil moisture then allows us to address the following questions:

1. Relative to 1979-2016, how do LSMs characterize 2016 soil-moisture anomalies in terms of location, severity, and timing of the SE US drought?

2. In a centennial context, how anomalous were the SE US surface-climate conditions that caused the 2016 drought and how did they relate to previously established trends?

3. What was the centennial context of 2016 soil-moisture anomalies and what were the roles of precipitation and evaporation?

4. What were the dynamical drivers of the drought and were these drivers associated with well-known modes of global climate variability?

2. Data and Methods

2.1. Study region

We define the SE US study region as the green polygon shown in Figure 1; the geographic coordinates of the four corners of the region are (northwest) 37°N, 89°W; (northeast) 37°N, 80°W; (southeast) 31°N, 83°W; and (southwest) 31°N, 92°W. The region excludes the area of anomalous moisture associated with Hurricane Matthew in early October 2016 and broadly bounds the zone of anomalous drought in fall 2016 based on the NLDAS2 modeled soil moisture described below.

2.2. Modeled soil moisture

Hourly modeled soil moisture gridded at 1/8° geographic resolution for 1979-2016 come from the NLDAS2 [Xia et al., 2012b] Noah LSM [Ek et al., 2003; Niu et al., 2011]. Analyses reported in this paper are for soil moisture within the 0-200 cm soil column. The 0-200 cm layer extends to the deepest model layer, most comprehensively representing the soil-moisture balance of the region. Hereinafter, Noah 0-200 cm soil moisture is referred to as SM_Noah. For each grid cell, daily and monthly relative SM_Noah anomalies (fraction of the mean) are expressed relative to the 1979-2016 mean annual cycle of daily values.

2.3. Surface climate data for 1895-present

We use records of precipitation and reference evapotranspiration (ETo; also commonly referred to as potential evapotranspiration) gridded at 1/8° geographic resolution for January 1895 through June 2017. We calculate ETo using the physically based Penman-Monteith formula [Monteith, 1965] following Allen et al. [1998], which requires monthly means of daily maximum temperature (Tmax), daily minimum temperature (Tmin), vapor pressure, 2-m wind speed, and solar radiation at the surface. Data on precipitation, Tmax, and Tmin for the continental US are from the National Oceanic and Atmospheric Administration (NOAA) Climgrid dataset [Vose et al., 2014]. Vapor pressure is calculated from PRISM gridded dew-point data [Daly et al., 2008]. Climgrid and PRISM have 1/24° geographic resolution that we aggregate to the NLDAS2 resolution of 1/8°. For wind velocity and solar radiation, we use a combination of the 1/8° resolution NLDAS2 meteorological forcing and the 1/2° Princeton Global Forcing version 2 (PGFv2; [Sheffield et al., 2006]), bilinearly downscaled to 1/8° resolution and rescaled temporally to match the mean climatology of NLDAS2 during overlapping years. Notably, there are a range of gridded climate data products available for the US. Our chosen climate datasets are generally within the range of inter-dataset variability for the SE US region, particularly for precipitation and Tmax, which are the primary drivers of interannual drought variability (Fig. S1; [Rodell et al., 2004; Daly et al., 2008; Compo et al., 2011; Rohde et al., 2013; Harris et al., 2014; Schneider et al., 2014; Oyler et al., 2015]). Additional details about the surface climate datasets are available in the Supporting Text S1 and Supporting Table S1.

We evaluate climate trends using the non-parametric Theil-Sen estimator [Sen, 1968], which is more robust to outliers than linear regression. Trend significance is considered at the p<0.05 level according to the Kendall’s Tau test and following adjustment for reductions in effective sample size due to first-order autocorrelation.

2.4. Centennial soil-moisture estimates

The relatively short NLDAS2 record inhibits characterization of soil-moisture anomalies in a long-term (centennial) context. To assess variations in the soil-moisture balance from 1895-present, we estimate records of monthly mean soil moisture at 1/8° geographic resolution based on monthly gridded records of precipitation and ETo. These estimates are based on a new monthly Model Calibrated Drought Index (MCDI) that we introduce here, which reliably replicates the soil-moisture outputs from the Noah LSM that is traditionally forced by high-frequency (30 minute) meteorological data. The ability to reliably estimate LSM soil moisture from monthly climate data is therefore an advance that allows us to temporally extend our evaluation of SE US drought for periods that are beyond the NLDAS2 record and for which high-frequency meteorological datasets are limited while saving on computational costs. The basis of the MCDI is a relatively simple bucket model, but for each grid cell the monthly persistence of the MCDI is tuned to reflect the monthly persistence characteristics of 0-200 cm soil-moisture anomalies from the more complex Noah LSM. This marks an important advance beyond the traditional bucket-model approach to moisture-balance accounting [e.g., Williams et al., 2015] because the Noah LSM accounts for complexities such as geographically varying soil compositions (affecting drainage rate and storage capacity), geographically and temporally varying vegetation types (affecting evapotranspiration rates), storage of above- and below-ground moisture in frozen form (affecting seasonality of infiltration, evapotranspiration and runoff), and moisture exchange between near-surface soil and the underlying aquifer (affecting drainage rate) [Niu et al., 2011]. Here we describe the methodology behind the MCDI and demonstrate its ability to use monthly gridded precipitation and ETo to reliably estimate monthly soil-moisture records generated by the more complex Noah LSM across much of the continental US, including all of the SE US.

The basis of the MCDI is the Palmer Z-index, which is a standardized record of monthly changes in the near-surface moisture balance based on a simple 2-layer bucket model, where monthly inputs are deposited via precipitation and monthly withdrawals are a function of ETo and the fraction of available moisture ([Palmer, 1965]; Supporting Text S2 for more details). From the Z-index, we calculated monthly MCDI as a linear combination of prior month MCDI and current month Z-index:

$${\text{MCDI}}_m=P\left({\text{MCDI}}_{m-1}\right)+\left(1-P\right)\left(\mathrm{Z}-{\text{index}}_m\right),$$ (eqn. 1)

where P is a persistence term between 0-1 describing the influence of prior-month (subscript m-1) soil-moisture anomalies on current month (subscript m) soil-moisture anomalies. This is similar to the PDSI framework, but in the PDSI algorithm P is constant throughout the year and across space (0.73). In contrast to this traditional PDSI approach, we derive P directly from the Noah model for each grid cell and month, allowing P to vary seasonally and geographically. Seasonal and geographic variations in P are reasonable because the persistence of soil moisture is dependent on the seasonality of climate (e.g., spring soil-moisture anomalies persist through summer in locations with little summer precipitation) and geographic variation in soil type and vegetation cover (e.g., soil-moisture anomalies may be less persistent in shallow soils or densely vegetated forests with high evapotranspiration rates). For each grid cell, and for each of the 12 months, we determined P empirically by finding the value between 0.005 and 0.995 (in steps of 0.005) that optimizes the interannual correlation between MCDI and SM_Noah anomalies when the MCDI calculation is forced by NLDAS2 climate data.

The optimal mean monthly persistence (averaged for the 12 months) for the SE US is 0.51 (95% of grid cells: 0.33-0.64), indicating substantially less persistence in the Noah model than is assumed in the PDSI calculation. This monthly persistence varies seasonally, reaching an annual minimum in spring (regionally averaged persistence: 0.39 in Mar-May) and an annual maximum in fall (regionally averaged persistence is 0.63 in Oct-Dec) (Fig. S2a). Low monthly persistence in spring indicates that modeled soil moisture correlates strongly with concurrent precipitation (Fig. S2b). Precipitation in the SE US has low monthly autocorrelation and peaks in spring, often leading to soil saturation (as evidenced by an annual peak in modeled daily aboveground runoff), diminishing the impacts of antecedent conditions. Higher monthly persistence occurs in fall when precipitation totals are lower and soil moisture is more heavily influenced by precipitation from antecedent months.

Spatially, persistence strongly varies across the continental US and throughout the SE US (Fig. S2c,d). Among SE US grid cells, mean monthly persistence is dictated more by soil characteristics than by climate, where areas with more permeable, well-drained soils experience less persistent soil-moisture anomalies. This interpretation is supported by a strong spatial correlation (r = −0.91) between annually averaged persistence values and the fraction of total precipitation that is lost through belowground runoff (Fig. S2c,d).

For each grid cell and each of the 12 months, the MCDI values derived from NLDAS2 climate were linearly regressed against SM_Noah anomalies (Fig. S3); the regression parameters were saved for later estimation of soil-moisture anomalies based on MCDI calculated from non-NLDAS2 climate data. To test the utility of MCDI as a proxy for SM_Noah, we performed “leave-one-out” cross-validation [Michaelsen, 1987] for the entire parameterization process: for each year we recalculated cross-validated monthly persistence parameters based all other years, recalculated MCDI records from these cross-validated persistence parameters, and calculated new estimations of SM_Noah based on the cross-validated MCDI values.

Based on cross-validation, modeled variations in monthly SM_Noah in the SE US can be reliably estimated from variations in MCDI. Cross-validated correlations between regionally averaged SE US SM_Noah anomalies and MCDI are particularly strong in summer and fall (Fig. S3) and reach 0.97 for Oct-Nov (Fig. 2a). Cross-validated correlations for Oct-Nov are also high at the grid-cell level throughout the SE US (mean: 0.93). Beyond the SE US, cross-validated correlations are high throughout the continental US (mean: 0.89), allowing for comparison of soil-moisture conditions in the SE US to those outside that region (Fig. 2b). Cross-validated correlations are also strong across much of the US in other seasons, with the lowest performance occurring in seasons and regions when and where snow melt dynamics are important (Fig. S4). Strong cross-validated correlation confirms the utility of the MCDI to extend Oct-Nov SM_Noah anomalies prior to the NLDAS2 period based on the linear relationships between these variables. To distinguish from SM_Noah, we refer to our MCDI-based estimates of soil moisture as SM_MCDI Notably, 20^th century increases in the density of the SE US weather-station network could affect the temporal variability of regionally averaged SM_MCDI, but we find no trends in the spatial variability of SE US SM_MCDI to support this.

Figure 2.

Cross-validated (CV) correlation between 0-200 cm modeled soil moisture (SM_Noah) anomalies and the model calibrated drought index (MCDI) during Oct-Nov for (a) the SE US region and (b) across the continental US. Dotted lines in (a) bound the 95% cross-validated confidence intervals for sample prediction. Correlation coefficients indicate the cross-validated Pearson’s correlation (r_cv). Green polygon in (b) bounds the SE US study region. Blue areas indicate lakes and coastal regions within the continental US for which there are no SM_Noah records. MCDI was calculated from NLDAS2 climate data.

To better understand the relative influences of precipitation versus ETo in driving SE US drought variability, we decomposed SM_MCDI anomalies into contributions from precipitation versus ETo. The contribution of precipitation is determined by re-calculating MCDI and SM_MCDI anomalies for an idealized case in which only precipitation varies and ETo is held at 1921-2000 climatology. The contribution of ETo is then the difference between the original SM_MCDI estimates and SM_MCDI recalculated only based on precipitation variability [e.g., Williams et al., 2015]. This approach requires that SM_MCDI anomalies driven by ETo are linearly additive to those driven by precipitation. Indeed, SM_MCDI in the SE US responds as expected when ETo anomalies are artificially reduced to 25%, 50%, and 75% of observed (Fig. S5).

2.5. Climate dynamics analysis

To investigate the large-scale climate processes driving SE US hydroclimatic variability, we used the National Aeronautical and Space Agency (NASA) second phase of the Modern Era Retrospective Analysis for Research (MERRA-2) reanalysis dataset for 1980-2016 [Rienecker et al., 2011; Molod et al., 2015]. For maps of geopotential height anomalies, geopotential heights were adjusted to remove positive trends associated with the mean global warming trend during the MERRA-2 record and resultant thermal expansion of the atmosphere ([Li et al., 2011]; Supporting Text S3 for details).

3. Results

3.1. Relative to 1979-2016, how do LSMs characterize 2016 soil-moisture anomalies in terms of location, severity, and timing of the SE US drought?

The SM_Noah record indicates strong soil drying during summer and fall 2016 throughout much of the SE US, reaching a minimum in late November (Fig. 3). Mean Oct-Nov SM_Noah was below the 1979-2016 average across all of the SE US and was driest on record across 50% of the region (Fig. 3a). Averaged across the SE US, the mean Oct-Nov SM_Noah in 2016 was the lowest on record (over the NLDAS2 interval), 27.5% (−2.32 σ) below the 1979-2016 mean. On a daily basis, SE US mean SM_Noah broke daily records in 2016 for all 31 days from Oct 31-Nov 30 (Fig. 3b,c). The second most severe drought in the SM_Noah record peaked in fall 2007 with mean Oct-Nov SM_Noah 19.7% below the 1979-2016 mean.

Figure 3.

Noah modeled 0-200 cm soil moisture (SM_Noah forced by NLDAS2 meteorology: 1979-2016. (a) Oct-Nov 2016 SM_Noah anomalies relative to the 1979-2016 mean. Green polygon: Southeast US (SE US) study region. (b) Daily and Oct-Nov relative SM_Noah anomalies. Vertical shaded lines indicate Oct-Nov periods and year ticks on the x-axis represent January 1. (c) Deviation of 2016 daily SM_Noah (red) from the mean 1979-2016 annual cycle (thick black). Dashed black lines: one standard deviation (σ) from the mean. Blue lines: 1979-2015 record high and low values.

2016 was also exceptional in terms of timing and rate of drying. SM_Noah in the SE US usually increases in November as evaporative demand declines, but 2016 SM_Noah reached its annual minimum on Nov 27, the latest annual minimum on record and 57 days later than the 1979-2015 median (Fig. 3c). Furthermore, the record low SM_Noah in late November came only 98 days after being near normal (2.4% below average) on August 22 and less than 11 months after achieving record-high daily values on January 1-2 (Fig. 3c).

3.2. In a centennial context, how abnormal were the SE US surface climate conditions that caused the 2016 drought and how did they relate to previously established trends?

In Figure 4 we evaluate surface climate variability in the SE US from 1895-2016. With more temporal coverage than was possible from NLDAS2 data, anomalies are now reported with respect to long-term mean conditions during a baseline period of 1921-2000, which was also the calibration interval in our calculation of the Palmer Z-index (Supporting Text S2). Additionally, Figure 4 focuses specifically on September-November (Sep-Nov) because this was the period of extreme drying that culminated in record-breaking low SM_Noah values in October and November 2016 (Fig. 3c). In Sep-Nov 2016, the SE US regional average precipitation was 45.5% (−145 mm) below the long-term mean (Fig. 4a). This was the 3^rd most negative precipitation anomaly on record; only 1939 and 1904 were lower. Prior to 2016, the last time the Sep-Nov precipitation total fell below 65% of average was in 1978.

Figure 4.

Observed Sep-Nov climate anomalies relative to 1921-2000 means. (Maps) 2016 anomalies. Green polygons: SE US study region. (Time series plots) Anomalies within the SE US. Note that (a) shows relative anomalies (% of mean) in the map and absolute anomalies in the time series. Red lines indicate significant Theil-Sen trends for 1895-2015.

Sep-Nov 2016 atmospheric aridity was also the highest within the 1895-2016 interval, as indicated by ETo (Fig. 4b), which was 22.0% (+61 mm) above the mean, largely due to record-high mean daily maximum temperatures (Tmax; Fig. 4c), due in part to high solar radiation (Fig. 4d). The Sep-Nov 2016 Tmax anomaly was +3.10°C, slightly warmer than the second highest Tmax anomaly in 1931 (+3.09°C). Mean daily minimum temperature (Tmin) was less extreme (1.61°C above average) and was the 11^th warmest over the 1895-2016 interval. The warmth of Sep-Nov 2016 combined with near-normal vapor pressure to yield a record-high vapor-pressure deficit (VPD), 38.7% higher than the mean (Fig. 4e). Wind speed, which multiplies the influence of VPD on ETo, was near normal (Fig. 4f).

The near record-low precipitation and record-high ETo, Tmax, and VPD in Sep-Nov 2016 are particularly notable because they were in contrast to established centennial trends toward wetting and cooling in the SE US (Fig. 4a-c,e). From 1895-2015, Sep-Nov precipitation increased in the region significantly (p<0.001) by 47.9% (+96 mm), ETo decreased significantly (p<0.05) by 4.6% (−13 mm), and Tmax decreased significantly (p<0.05) by 0.77°C. The decrease in ETo was largely due to a significant (p<0.001) cooling-induced decrease in VPD of 12.0%. Furthermore, although the Sep-Nov 2016 precipitation anomaly was not a record-breaking event in an absolute sense, the deviation between the observed precipitation total and that expected from trends shown in Figure 4a was by far the most negative on record (as was ETo and Tmax).

3.3. What was the centennial context of 2016 soil-moisture anomalies and what were the roles of precipitation and evaporation?

To evaluate the centennial context of the 2016 SE US drought, we use SM_MCDI as the monthly mean soil-moisture estimate for the extended period of January 1895 through June 2017 based on the climate datasets from Figure 4 (development of the MCDI and SM_MCDI is described in section 2.4). As with the climate data, SM_MCDI anomalies are expressed as relative (%) departures from the 1921-2000 mean climatology. Similar to the results from SM_Noah results, 2016 monthly SM_MCDI reached its annual minima in Oct (relative anomaly) and Nov (absolute anomaly), each ranking among the lowest monthly averages over the 1895-2016 interval (Fig. 5a,b). Considering annual Oct-Nov means, the only year with a more negative mean SE US SM_MCDI anomaly was 1954 (−26.0%; 2016: −22.9%) (Fig. 5c). Accounting for uncertainties (Fig. 2a), however, this is not a statistically significant difference at the 95% confidence level and there were 7 additional years when mean Oct-Nov SM_MCDI was wetter than in 2016, but not significantly so (shown in Figure 6). Most of these dry fall seasons occurred in the first half of the record, however, and 2007 was the only year since 1954 with Oct-Nov SM_MCDI comparable to that of 2016. Importantly, the near record-dry SM_MCDI in Oct-Nov 2016 followed a significant (p < 0.01) positive trend (increase of 8.9%) during 1895-2015 (Fig. 5c) and the 2016 anomaly marked the furthest deviation on record from this trend (as was the case for precipitation, Tmax, VPD, and ETo), though the 2016 SM_MCDI departure from the trend was not significantly (p<0.05) more negative than those in 1954 or 2007.

Figure 5.

SE US SM_MCDI for January 1895 through June 2017. (a and b) relative anomalies and absolute values, respectively. (c) Mean Oct-Nov anomalies expressed as (left axis) absolute and (right axis) relative departures from the mean. Dark green line in (c) indicates 1895-2015 trend. Shading in (a-c) bounds cross-validated 95% confidence intervals, graduating from (darker) lower to (lighter) higher confidence. (d) Map of Oct-Nov 2016 relative SM_MCDI anomalies. Anomalies are departures from the 1921-2000 mean. Green polygon in (d) bounds the SE US study region.

Figure 6.

Maps of Oct-Nov drought ranking (based on SM_MCDI) for the 9 driest Oct-Nov periods during 1895-2016. Lower values indicate more severe drought. Inset graph: Annual percentage of SE US experiencing lowest ranked SM_MCDI among all Oct-Nov periods during 1895-2016.

In terms of drought length, there have been several other SE US drought events that dwarfed the 2016 event. The longest periods without two consecutive months of above average SM_MCDI were August 1953 through March 1957 (44 months) and November 2005 through April 2009 (42 months). By the same measure, the recent event lasted just 13 months (April 2016 through April 2017).

In terms of spatial extent across the whole of the continental US, the drought in Oct-Nov 2016 was much less expansive than in the other biggest drought years of the past century (Fig. 6). In particular, the Oct-Nov drought conditions in 1952-1954 consumed much of the continental US (Fig. 6). On the other hand, Oct-Nov 2016 SM_MCDI was lowest on record across 27.8% of the SE US region (largest proportion of any year on record), with the record-breaking drought area focused across much of the southern Appalachians, where high forest-fire forest fire activity was also concentrated in 2016. It should be noted, however, that fine-scale geographic variations in sub-regional hydroclimate anomalies and trends are prone to large uncertainties due to lack of station coverage and sensitivity to methodology regarding spatial interpolation of climate data [e.g., Wang et al., 2017].

Importantly, the SE US region considered in this study was explicitly chosen to bound the 2016 drought area and Oct-Nov is most extensively evaluated because this is when the 2016 drought was most intense. Comparisons of year-to-year drought severity and extent are sensitive to such choices. For example, the 1954 drought peaked in September-October and considering those months, 1954 had by far the most SE US area experiencing record-low SM_MCDI (51.5%); 2016 is ranked third (6.5%) using the September-October window.

In comparison to other droughts, the rate at which SM_MCDI declined in fall 2016 was particularly rapid. Similar to SM_Noah, SM_MCDI in Oct 2016 was a record 19.5% drier than the near-normal levels in August 2016. The second most rapid relative difference between August and October SM_MCDI occurred in 1904 (18.7%).

To contextualize the rapid SE US drying in late summer and fall 2016, it is useful to compare the climatological evolution of the fall 2016 drought to other similar fall droughts. Figure 7 compares 2016 with the five other years since 1895 with the lowest mean SE US Oct-Nov SM_MCDI. Among these years, all had anomalously low precipitation in all Sep-Nov months (Fig. 7b) and 1904 was remarkably similar to 2016 in terms of the sequencing of monthly precipitation totals during May-Dec. Consequently, 1904 and 2016 followed similar SM_MCDI trajectories throughout summer and fall, and 1904 ranked second to 2016 in terms of relative decrease in SM_MCDI from August to October (18.7%). The two years diverge in November, when 1904 SM_MCDI recovered slightly due, in part, to an additional 13 mm of precipitation beyond the Nov 2016 total.

Figure 7.

Comparison of 2016 climate to other drought years. Monthly SE US (a) SM_MCDI, (b) precipitation, and (c) reference evapotranspiration (ETo) for 2016 and the other five years with similarly dry Oct-Nov SM_MCDI. In (a-c): Black bold curves and shading: 1921-2000 monthly means plus and minus one standard deviation. (d and e) Scatter plots of annual Sep-Nov ETo versus (d) precipitation and (e) SM_MCDI anomalies during the same period. Colors in (d and e) correspond to the legend in (a) and 2016 is represented by the large red dot. Black lines in (d and e) represent linear and exponential regression fits and values in these panels are anomalies with respect to the 1921-2000 means.

Additionally, all years in Figure 7 experienced positive ETo anomalies throughout much of late summer and fall (Fig. 7c), largely due to anomalously high VPD. In 2016, ETo was above average in all months after January, highest on record in November, and highest on record when averaged over Sep-Nov. While high ETo is to be expected in drought years due to increased solar radiation from reduced cloud cover and enhanced sensible heat flux at the expense of latent heat flux [e.g., Koster et al., 2009; Seneviratne et al., 2010; Yin et al., 2014], the record-high ETo anomaly in Sep-Nov 2016 was considerably larger than that expected based on established relationships with Sep-Nov precipitation and SM_MCDI (Fig. 7d,e).

Very high ETo values and rapid soil drying in fall 2016 motivate an evaluation of the degree to which the record-high ETo enhanced the drought conditions in 2016. To estimate the effect of evaporative demand on soil moisture, we decomposed annual Oct-Nov SM_MCDI anomalies into contributions from precipitation and ETo anomalies (Fig. 8). Not including impacts of precipitation on ETo, this analysis indicates that anomalously low precipitation forced SE US Oct-Nov SM_MCDI in 2016 by −66 mm (a −16.6% deviation from the 1921-2000 mean). Anomalously high ETo negatively forced 2016 Oct-Nov SM_MCDI by an additional −26 mm (−6.4%). Together, the total Oct-Nov SE US SM_MCDI anomaly is 72% attributed to low precipitation and 28% attributed to high ETo. These results were nearly identical when the analysis was repeated while only holding ETo at climatology for 2016 instead of for all years.

Figure 8.

Effect of (blue) precipitation and (red) ETo anomalies on (bars) Oct-Nov SE US SM_MCDI from 1895-2016. SM_MCDI anomalies are departures from the 1921-2000 mean and displayed in (left-hand axis) absolute and (right-hand axis) relative units.

Over the 122-year record, declining ETo due to cooling contributed modestly to the positive SM_MCDI trend from the early 1900s through the 1970s. Since the 1970s, however, increasing ETo due to increasing temperature, solar radiation, and wind speed have forced a negative SM_MCDI trend beyond that caused by declining fall precipitation (Figs. 4,8). As mentioned previously, however, ETo effects on soil moisture are not independent from precipitation effects and this experiment’s decoupling of the two processes is idealized.

3.4. What were the dynamical drivers of the drought and were these drivers associated with well-known modes of global climate variability?

Here we investigate the large-scale atmosphere and ocean circulation patterns that correspond to changes in SE US SM_MCDI during fall and their roles in the extreme 2016 soil drying. To avoid detecting correlations driven by the extreme 2016 conditions, correlation analyses in this section represent 1980-2015, the period of the MERRA-2 reanalysis that excludes 2016.

Figure 9a shows the mean climatology of Sep-Nov precipitation and vertically integrated atmospheric moisture transports over North America and the surrounding areas. During fall, southwesterly winds on the western flank of the subtropical Atlantic high bring moisture to the SE US from the Gulf of Mexico and southwest of North America. Southwesterly moisture transport into the SE US is therefore likely an important driver of variability in Sep-Nov soil drying in the region. The correlation map in Figure 9b shows how interannual variability in Sep-Nov precipitation and moisture transports correlate with fall soil drying from 1980-2015; we define “fall soil drying” as the negative of the mean monthly Palmer’s Z-index from Sep-Nov. Fall soil drying is driven largely by reductions in precipitation that are promoted by north-northeasterly circulation anomalies that suppress south-southwesterly moisture inflow from the Gulf and southwest. Sep-Nov 2016 appears as a particular case of this general fall drying configuration (Fig. 9c). South-southwesterly moisture transports into the southern portion of the SE US (south of 35°N) correlated significantly and negatively with Sep-Nov soil drying in 1980-2015 (−r = 0.71, p<0.001) and were lowest on record in 2016, only 24% of the 1980-2016 average.

Figure 9.

MERRA-2 Sep-Nov atmospheric circulation versus SE US drying. (a-c) Precipitation and (vectors) vertically integrated moisture transports. (d-f) 200 hPa geopotential height (Z) and (vectors) 200 hPa wind velocity. Maps show the (a and d) 1980-2016 mean climatology, (b and e) correlation with Sep-Nov soil drying during 1980-2015, and (c and f) the 2016 anomaly. In (b and c), precipitation anomalies are expressed as the standardized precipitation index (SPI). Green polygon bounds the SE US study region. Yellow polygon in (d-f) bounds the region where 200 hPa north-northeasterly winds correlate positively with SE US drying and negatively with south-southwesterly moisture transports into the SE US.

For both Sep-Nov 2016 and the general case of soil drying (Fig. 9b,c), the 200hPa height anomaly maps indicate an upper-level anticyclonic circulation anomaly over North America and, on the east side of the anticyclone, northeasterly 200 hPa wind anomalies across much of the eastern US. It is these wind anomalies, and associated upper-level convergence and subsidence over the SE US, that inhibit southerly moisture transports into the region, moisture convergence, and precipitation. As such, for the general case of SE US drying, north-northeasterly 200 hPa wind anomalies within the yellow region in Figure 9d-f were strongly and negatively correlated with south-southwesterly moisture transports in the southern SE US (r = −0.71, p < 0.001). Comparing the correlation maps in Figure 9b,e to the 2016 anomalies in Figure 9c,f, it appears that the exact position of a North American ridge can vary substantially while still suppressing moisture transports into the SE US from the Gulf of Mexico.

We next evaluate how global patterns of Sep-Nov 200 hPa geopotential height and wind velocity, precipitation, and surface temperature correspond to Sep-Nov soil drying in the SE US (Fig. 10). For the general case, Sep-Nov drying is promoted by La Niña-like SST, precipitation, and geopotential height patterns over the tropical Pacific Ocean, indicative of the cold phase of the El Niño-Southern Oscillation (ENSO) (Fig. 10a,c,e). In the extra-tropics, SE US drying is associated with a wave train that appears to propagate from the North Pacific across North America to the North Atlantic. It has a higher zonal wavenumber character that is distinct from the more canonical, larger scale, Pacific-North America wave train associated with La Niña during winter, but consistent with prior analyses of La Niña impacts in Sep-Nov [Seager et al., 2014]. Additionally, the general case of SE US drying is associated with warm SST anomalies in the tropical North Atlantic (Fig. 10e), consistent with previous findings [Kushnir et al., 2010; Wang et al., 2010; Nigam et al., 2011; Ting et al., 2014]. Indeed, the geopotential height anomalies associated with the general case of SE US drying (Fig. 10a) are broadly consistent over North America with those associated with a warm AMO during fall [Nigam et al., 2011]. Figure 10b,d,f indicates that during Sep-Nov 2016, SST anomalies were broadly reflective of conditions expected of La Niña conditions in the tropical Pacific and a warm tropical North Atlantic, but the La Niña-like anomalies were less striking in 2016 than those generally associated with SE US drying. Global 200 hPa height anomalies in 2016 (Fig. 10b) also bore some resemblance to the pattern expected from the general drying case, albeit with differences in the specific locations of ridges and troughs in the Pacific-North America-Atlantic wave train.

Figure 10.

MERRA-2 global climate versus Sep-Nov drying in the SE US. (Left) Correlation between global climate and soil drying during 1980-2015. (Right) Standardized global climate anomalies in Sep-Nov 2016 relative to a 1980-2016 baseline. (Top row) 200 hPa (vectors) wind velocity and (background) geopotential height (Z). (Middle row) Precipitation, as represented by the standardized precipitation index (SPI). (Bottom row) Surface temperature (T).

To further investigate the potential forcing by ENSO and tropical North Atlantic SSTs, we relate MERRA-2 200 hPa geopotential heights globally to ENSO and the Tropical North Atlantic index (TNA; [Enfield et al., 1999]) for Sep-Nov 1980-2015 (Fig. 11). The atmospheric component of ENSO is represented by the first principal component of Sep-Nov tropical precipitation totals (data from the Global Precipitation Climatology Project; [Adler et al., 2003]). We refer to this atmospheric component of ENSO as “ENSO P” and positive values represent La Niña-like conditions. Standardized time series of Sep-Nov ENSO P and TNA for 1980-2016 are shown in Figure 11a,b, verifying that both modes were anomalously positive (La Niña-like, warm tropical North Atlantic) in 2016, but not exceptionally so (~ +1 σ). The upper-tropospheric responses to ENSO P and TNA (Fig. 11c,d) resemble the patterns associated with fall drying in the SE US (Fig. 10a) in terms of a northward displacement of the jet over the US, a ridge over central North America, and lower heights over the east coast of the US and the western subtropical North Atlantic which, as shown in Figure 9, would suppress southerly moisture transports to the SE US from the Gulf of Mexico.

Figure 11.

ENSO, tropical North Atlantic SSTs, and their correlations with MERRA-2 global 200 hPa geopotential height (Z) in Sep-Nov 1980-2015. ENSO is represented by the first principal component of tropical Sep-Nov precipitation totals (ENSO P). North Atlantic SSTs are represented by the Tropical North Atlantic (TNA) index.

Importantly, the correlations in Figure 11c,d over the northern Hemisphere extra-tropics are relatively weak, especially over North America. Impacts on SE US fall hydroclimate would therefore only be substantial when ENSO P or TNA anomalies are quite strong, which was not the case in 2016. While La Niña conditions and warm tropical North Atlantic SSTs in fall do indeed tend to correspond to reduced precipitation, higher ETo, and soil drying in the SE US (Fig. 12a-f), the positive ENSO P and TNA anomalies in 2016 were simply too weak to account for a large proportion of the observed SE US hydroclimate anomalies (Fig. 12g-l). It has been suggested before that a negative state of the North Pacific Oscillation (NPO) may modulate the effect of La Niña on eastern US precipitation [Gershunov and Barnett, 1998], but we find no such effect. To investigate the potential for SST teleconnection effects not captured by our correlation approach, we evaluated results of a 16-member simulation of the NCAR Community Atmospheric Model version 5.3 (CAM5.3) forced by observed SSTs for 1979-2016 (run at LDEO). Consistent with the results of our correlation-based results, the ensemble mean did not indicate a SE US precipitation shortfall in Sep-Nov 2016.

Figure 12.

Impacts of ENSO and tropical North Atlantic SSTs on Sep-Nov surface climate across the continental US. Columns represent (left) standardized Precipitation Index (SPI) and MERRA-2 vertically integrated moisture transports, (middle) reference evapotranspiration (ETo), and soil drying. The top two rows indicate how each of these three variables correlated with the atmospheric component of ENSO (ENSO P) and the Tropical North Atlantic (TNA) index, respectively, in 1980-2015. The third row shows estimates of the three variables for 2016 based on a multiple-linear regression with ENSO P and TNA for 1980-2015 (combined effects of ENSO P and TNA are referred to as “combo.” In the figure). The bottom row shows the anomalies for the three variables in 2016 that were not accounted for by the multiple regression with ENSO P and TNA. Green polygon bounds the SE US study region.

Additionally, there is no clear evidence for tropical teleconnections driving the low-frequency SE US wetting trend observed over the course of the 20^th century. If linked to a tropical teleconnection, 20^th-century wetting would be expected to correspond to trends toward more El Niño-like SST patterns in the tropical Pacific and/or cooler SSTs in the tropical Atlantic, but this was not the case. Likewise, comparison between 1895-1956 (when 68% of fall seasons had below-average SM_MCDI) and 1957-2016 (when 45% of fall seasons had-below average SM_MCDI) indicates essentially no difference between the frequency of fall seasons experiencing La Niña conditions (negative Niño 3.4 SST anomaly), warm tropical Atlantic SSTs (positive TNA anomaly), or a combination of these two (1895-2016 SST data from Rayner et al. [2006]).

4. Discussion

According to land-surface modeling over the relatively short period of 1979-2016, fall 2016 was exceptional in terms of soil dryness, rate of drying, and timing of peak dryness. Estimating soil moisture (SM_MCDI) back to 1895, we find several other periods, mostly concentrated in the first half of 1895-2016, when regionally averaged SE US fall soil-moisture deficits were similar to those of 2016 and soil-moisture deficits in 1954 were likely more severe. In terms of duration and extent, the drought of 1953-1957 dwarfed the 2016 event and tree-ring records indicate droughts in the middle of the last millennium that were far longer still [Seager et al., 2009]. The centennial perspective presented in this paper highlights that extreme droughts like the 2016 event may be more likely than suggested by an evaluation that only considers the past 30-60 years. It is notable, however, that on the sub-regional scale, the fall 2016 drought may have still been the most severe on record across much of the southern Appalachians, where high forest-fire activity occurred. Further, the 2016 drought may have been particularly surprising because it was in stark contrast to significant trends over the past century toward wetter and cooler conditions in the SE US.

While the 2016 SE US drought was primarily driven by a precipitation shortfall, an important secondary contributor was record-high atmospheric moisture demand during Sep-Nov, brought on by record-high daytime temperatures. This raises questions as to the potential contribution of anthropogenic radiative forcing to SE US drought in 2016. Importantly, 20^th-century cooling in the SE US, and indeed across much of the eastern US, was counter to the expected warming based on climate-model simulations. Possible contributors to cooling were mid-century increases in aerosol loading, low-frequency oscillations in the Pacific and North Atlantic basins, and enhanced evapotranspiration due to increased precipitation, forest cover, and irrigation [Baidya Roy et al., 2003; Pan et al., 2004; Kunkel et al., 2006; Chen et al., 2012b; Leibensperger et al., 2012a; Leibensperger et al., 2012b; Misra et al., 2012; Yu et al., 2014; Ellenburg et al., 2016; Mascioli et al., 2017]. However, the SE US and much of the rest of the eastern US has warmed since the 1970s, particularly at night, potentially signifying an emergence of projected trends, but also likely associated with multi-decade variability in tropical Atlantic SSTs and reductions in aerosol load. While unresolved questions regarding the drivers of wetting and cooling in the SE US preclude us from carrying out an attribution of the anthropogenic forcing on drought intensity in 2016 [e.g., Williams et al., 2015], the secondary effect of record-high temperatures on drought in 2016 serve as an important reminder that extreme warmth can push a somewhat severe drought to record or near-record levels and promote the rapid development of so-called “flash drought” events [Hobbins et al., 2016; Wang et al., 2016].

Increased soil moisture during 1895-2015 was primarily driven by increasing precipitation, and this precipitation trend was largely driven by a nearly 50% increase in fall. The increase in fall precipitation may be in part related to general fall-wetting trends across much of the eastern US. For the Northeast US, the increase occurred as an as-yet undiagnosed wet shift following a drought in the 1960s [Seager et al., 2012]. For the SE US, a wide range of factors are suggested to have contributed to the wetting trends, including decreased aerosol concentrations since the 1970s [Leibensperger et al., 2012a; Diem, 2013b; Westervelt et al., 2017], 20^th-century reforestation [Baidya Roy et al., 2003; Chen et al., 2012b], irrigation [Ozdogan et al., 2010; Puma and Cook, 2010], multi-decadal oscillations in large-scale ocean and atmospheric circulation [McCabe et al., 2004; Wang et al., 2009; Nigam et al., 2011; Meehl et al., 2012], increased specific humidity due to greenhouse forcing [Diem, 2013a], changes in the position of the subtropical Atlantic high that may or may not be related to anthropogenic forcing [Li et al., 2011; Li et al., 2012; Diem, 2013a; Li et al., 2013], and internal atmospheric variability [Seager et al., 2012]. Future work is needed to better understand the reasons for the increase in SE US precipitation over the past century in order to guide expectations of precipitation trends in the coming decades.

In 2016, the primary cause of the precipitation shortfall was a suppression of southerly moisture transports into the SE US from the Gulf of Mexico, caused by northerly wind anomalies throughout the atmospheric column over the eastern US. These northerly wind anomalies were driven largely by an anomalous ridge centered over the central US that was, in part, promoted by hemispheric-scale circulation anomalies associated with both La Niña conditions and warm SSTs in the tropical and subtropical Atlantic. The teleconnection between fall drying in the SE US and the cold Pacific/warm Atlantic combination is consistent in sign with observational and model results presented by many others, particularly for the winter half of the year [Ropelewski and Halpert, 1986; Ropelewski and Halpert, 1996; Gershunov and Cayan, 2003; Wu et al., 2005; Tootle and Piechota, 2006; Kurtzman and Scanlon, 2007; Mo and Schemm, 2008; Seager et al., 2009; Kushnir et al., 2010; Wang et al., 2010; Nigam et al., 2011; Wise et al., 2015]. However, based on our correlation analysis, the tropical Pacific and Atlantic SST anomalies in 2016 were not strong enough to account for a sizable proportion of the extreme SE US drying in fall 2016. This suggests that the atmospheric circulation anomalies that suppressed precipitation and enhanced evaporative demand in the SE US in fall 2016 were primarily driven by internal atmospheric variability and only slightly amplified by teleconnections to the tropics. This result is consistent with prior findings that the teleconnection between the tropics and SE US hydroclimate are often overwhelmed by internal atmospheric variability [Seager et al., 2009]. The dominant role of internal atmospheric variability was supported by the SST-forced CAM5.3 simulations that we evaluated.

Regarding the future, Earth System Models (ESMs) tend to project moderately negative trends in mean SE US soil moisture over the 21^st century [Cook et al., 2015; Berg et al., 2016]. The projected reductions in mean SE US soil moisture occur despite projected increases in mean annual precipitation and are likely driven by warming, decreased summer precipitation, and a trend toward heavier precipitation over fewer days, which may reduce infiltration [Polade et al., 2014; Berg et al., 2016]. These projections combine with our observations of a non-negligible impact of warmth on SE US drought severity and the ability of undiagnosed low-frequency precipitation variability to cause multi-decade periods of frequent SE US drought, even in the absence of warming, to motivate our conclusion that severe SE US droughts will likely be more probable in the coming decades than would be suggested by an analysis of only the past 30-60 years.

We also note that there are important caveats to our conclusions, however. An aspect that complicates comparison of the 2016 drought to historical droughts is the major reforestation of the SE US, and indeed much of the eastern US, over the past century following massive deforestation during the 1600s through 1800s for agriculture and logging [Steyaert and Knox, 2008]. Vegetation affects evapotranspiration rates and other surface processes such as above- and below-ground runoff. Throughout our study period of 1895-2016, we assume stationary surface resistance in the ETo calculation and a constant annual cycle in soil-moisture persistence derived from NLDAS2 data. In reality, changes in vegetation cover [Nowacki and Abrams, 2008; Oudin et al., 2008; Mankin et al., 2017], atmospheric carbon dioxide [Farquhar, 1997; Swann et al., 2016; Keller et al., 2017], nitrogen deposition [Magnani et al., 2007], ozone pollution [Felzer et al., 2004], rain acidity [Driscoll et al., 2001], urban cover [Scalenghe and Marsan, 2009], and interactions among these factors [e.g., Reich et al., 2006] affect how a given climatological event affects soil moisture via their influences on evapotranspiration. How these factors combined to affect soil moisture in 2016 is a complex question worthy of future research involving coupled ESMs and interpretations of their representation of the plant hydraulic response to changes in biogeochemistry and resultant land-atmosphere feedbacks [Quillet et al., 2010]. Currently, LSM simulations of historical soil-moisture variability [e.g., Mao et al., 2015; Shukla et al., 2015; Livneh and Hoerling, 2016], including those done through the NLDAS2, do not account for how changes in land-surface characteristics or atmospheric chemistry would have modulated the effects of precipitation and ETo anomalies on soil moisture.

5. Conclusions

Our analysis of climatologically driven changes in SE US soil moisture and the dynamical processes that drive these changes indicate that the climatological drought in the fall of 2016 was the most severe on record during the short period of 1979-2016 during which LSMs are used for operational monitoring. Expanding to a longer perspective from 1895-present, however, indicates that several droughts of comparable magnitude have occurred over that time span, including a far longer and more spatially extensive drought from 1953-1957. The clustering of strong fall drought events between 1895 and 1956, and a dearth of similar events between 1957 and 2015, was due to an as-yet undiagnosed shift in the SE US toward increased precipitation, particularly in fall, and decreased daytime temperatures. Record-high temperatures in fall 2016 aided the intensification of the drought by producing record-high levels of atmospheric moisture demand.

The drought in the fall of 2016 was promoted by La Niña-like conditions in the tropical Pacific and warm conditions in the tropical Atlantic that combined to limit moisture transports and promote warmth in the SE US, but these tropical anomalies were not strong enough in fall 2016 to account for the extreme hydroclimate anomalies observed in the SE US. The majority of the extreme SE US soil drying that occurred in fall 2016 therefore appears to have arisen as a result of internal atmospheric variability, with only a small additional influence from tropical teleconnections.

While extreme drought has been rare in the SE US over the past half century, the intensity and rapid onset of the SE US drought in 2016, and its destructive impacts on wildfire and human water resources, should motivate the region’s population to be prepared for reoccurrences of droughts of similar or stronger magnitude, particularly in light of both model projections of future warming and reduced soil moisture and tree-ring evidence that attests to much longer SE US droughts in the middle of the last millennium. The 2016 SE US drought also provides motivation to better understand the causes of the significant increase in SE US precipitation over the past century and what the fate of this trend will be in the coming decades.

Key Points.

• New gridded monthly soil-moisture estimates indicate the southeast US drought in fall 2016 was the second most severe since at least 1895.

• The driver was low precipitation but record-high evaporative demand also contributed. Both countered centennial trends in the region.

• These conditions were caused by internal atmospheric variability and were only modestly aided, if at all, by tropical teleconnections.