global trends and variability in soil moisture and …blyon/references/p28.pdfchanges in soil...

Global Trends and Variability in Soil Moisture and Drought Characteristics, 1950–2000,from Observation-Driven Simulations of the Terrestrial Hydrologic Cycle

JUSTIN SHEFFIELD AND ERIC F. WOOD

Department of Civil Engineering, Princeton University, Princeton, New Jersey

(Manuscript received 15 December 2006, in final form 13 June 2007)

ABSTRACT

Global and regional trends in drought for 1950–2000 are analyzed using a soil moisture–based droughtindex over global terrestrial areas, excluding Greenland and Antarctica. The soil moisture fields are derivedfrom a simulation of the terrestrial hydrologic cycle driven by a hybrid reanalysis–observation forcingdataset. Drought is described in terms of various statistics that summarize drought duration, intensity, andseverity. There is an overall small wetting trend in global soil moisture, forced by increasing precipitation,which is weighted by positive soil moisture trends over the Western Hemisphere and especially in NorthAmerica. Regional variation is nevertheless apparent, and significant drying over West Africa, as driven bydecreasing Sahel precipitation, stands out. Elsewhere, Europe appears to have not experienced significantchanges in soil moisture, a trait shared by Southeast and southern Asia. Trends in drought duration,intensity, and severity are predominantly decreasing, but statistically significant changes are limited in arealextent, of the order of 1.0%–7.0% globally, depending on the variable and drought threshold, and aregenerally less than 10% of continental areas. Concurrent changes in drought spatial extent are evident, witha global decreasing trend of between �0.021% and �0.035% yr�1. Regionally, drought spatial extent overAfrica has increased and is dominated by large increases over West Africa. Northern and East Asia showpositive trends, and central Asia and the Tibetan Plateau show decreasing trends. In South Asia all trendsare insignificant. Drought extent over Australia has decreased. Over the Americas, trends are uniformlynegative and mostly significant.

Within the long-term trends there are considerable interannual and decadal variations in soil moistureand drought characteristics for most regions, which impact the robustness of the trends. Analysis of de-trended and smoothed soil moisture time series reveals that the leading modes of variability are associatedwith sea surface temperatures, primarily in the equatorial Pacific and secondarily in the North Atlantic.Despite the overall wetting trend there is a switch since the 1970s to a drying trend, globally and in manyregions, especially in high northern latitudes. This is shown to be caused, in part, by concurrent increasingtemperatures. Although drought is driven primarily by variability in precipitation, projected continuation oftemperature increases during the twenty-first century indicate the potential for enhanced drought occur-rence.

1. Introduction

Drought can be regarded as one of the most damag-ing of natural disasters in human, environmental, andeconomic terms. It occurs as a result of extremes inclimate that are driven by natural variability but maybe exacerbated or dampened by anthropogenic influ-ences. The variability of global climate is driven in themain by El Niño–Southern Oscillation (ENSO), whichimpacts the tropics and many regions in midlatitudes

(Ropelewski and Halpert 1987). Other climate oscilla-tions and modes of large-scale variability, such as theNorth Atlantic Oscillation (NAO), the Pacific decadaloscillation (PDO), and the Atlantic Multidecadal Os-cillation (AMO), act on generally longer time scalesand interact with ENSO or are the primary climatedrivers elsewhere and more regional in their impacts.For example, the NAO is known to affect climate ineastern North America and Europe (Hurrell and Van-Loon 1997) as well as North Africa (Wang 2003). ThePDO (Mantua et al. 1997) is a primary driver of climatearound the Pacific basin and interacts with ENSO, re-sulting in modifications of climate globally (Newman etal. 2003; Verdon and Franks 2006). The AMO (Kerr

Corresponding author address: Justin Sheffield, Department ofCivil Engineering, Princeton University, Princeton, NJ 08544.E-mail: [email protected]

432 J O U R N A L O F C L I M A T E VOLUME 21

DOI: 10.1175/2007JCLI1822.1

© 2008 American Meteorological Society

JCLI1822

2000) impacts on the North Atlantic and especially onNorth American (Enfield et al. 2001; McCabe et al.2004) and European climate (Sutton and Hodson2005), and is a potential modulating force of ENSO(Dong et al. 2006).

Of considerable interest is the change in variabilityand extremes under recent and future global warmingand the potential acceleration of the water cycle, whichmay act to alter the occurrence and severity of drought.As temperatures rise, the capacity of the atmosphere tohold moisture would increase as governed by the Clau-sius–Clapeyron equation (Held and Soden 2000), withpotential for increased evaporation and/or precipitation(Trenberth 1999), although these may be limited byother factors such as available energy and aerosol con-centration. Climate model studies have shown that vari-ability is likely to increase under plausible future cli-mate scenarios (Wetherald and Manabe 2002), depen-dent upon climate sensitivity, with large regionalchanges in the water cycle. The potential for moredroughts and of greater drought severity is a worrisomepossibility (Wetherald and Manabe 1999; Wang 2005).

Huntington (2006) reviews the observational evi-dence so far for water cycle intensification to date andconcludes that, despite some contradictions, the overallpicture points toward intensification. For drought spe-cifically, trends have been analyzed over the past 50–100 yr at regional (e.g., Lloyd-Hughes and Saunders2002; Rouault and Richard 2005; Andreadis andLettenmaier 2006) and global scales (Dai et al. 2004).When analyzing the Palmer Drought Severity Index(PDSI) and the Standardized Precipitation Index (SPI)over Europe, Lloyd-Hughes and Saunders (2002) foundinsignificant change in the proportion of land experi-encing medium to extreme drought during the twenti-eth century. A drought analysis of South African SPI byRouault and Richard (2005) found a substantial in-crease in 2-yr droughts since the 1970s. They also foundinterdecadal variability in the spatial extent of droughtsince the beginning of the century, the most severe ofwhich is associated with ENSO. Andreadis and Letten-maier (2006) analyzed a long-term (1915–2003) hydro-logical simulation over the United States and found ageneral increasing trend in soil moisture, with concur-rent decrease in drought duration and extent, exceptfor the Southwest and parts of the West. Dai et al.(2004) showed the global pattern of trends in annualPDSI and found that generally drier conditions haveprevailed since the 1970s.

In this paper, we investigate variability and trends insoil moisture and drought characteristics, globally andregionally over the second half of the twentieth cen-tury. The analysis is based on a global soil moisture

dataset derived from a model simulation of the terres-trial hydrologic cycle. The simulation is driven by ahybrid observation–reanalysis-based meteorologicaldataset and provides a globally consistent and physi-cally based view of moisture availability. As droughtcan be described by any one or a combination of char-acteristics, and these are important to varying degreesdepending on the situation, we are interested inchanges in a number of aspects of drought. These in-clude duration, intensity, and severity, which are de-pendent on the threshold for defining drought that isspecific to the application. We focus on how soil mois-ture and drought characteristics vary at annual to deca-dal time scales, and whether there are any significanttrends over the second half of the twentieth century.Intuitively, changes in precipitation will be the primarydriver of variability in drought but will be modified bytemperature changes, which is especially relevant givenrecent and potential future increases in surface air tem-perature. We therefore investigate the direct (precipi-tation, temperature) and indirect (large-scale climateoscillations) forcing mechanisms to understand what isdriving changes and variability in soil moisture anddrought occurrence.

2. Datasets and methods

To represent drought globally, we use soil moisturefields from a land surface hydrological model simula-tion driven by observation-based meteorological forc-ings (Sheffield and Wood 2007). Soil moisture balancesthe fluxes of precipitation, evapotranspiration and run-off and thus provides an aggregate measure of wateravailability and drought. In drought terminology, soilmoisture falls somewhere in between meteorologicaland hydrological drought and may be representative ofagricultural drought through its control on transpira-tion and thus vegetative vigor. We calculate an index ofdrought as the deficit of soil moisture relative to itsseasonal climatology (Sheffield et al. 2004a). Wet spellscan be calculated similarly but as the surplus of soilmoisture. The simulation and the derivation of thedrought index and related statistics are briefly de-scribed next. Further details can be found in Sheffieldet al. (2004a).

a. Land surface hydrological simulation

The Variable Infiltration Capacity (VIC) land sur-face model (Liang et al. 1994; Cherkauer et al. 2002)was used to generate spatially and temporally consis-tent fields of soil moisture and other water budget fluxand state variables. The VIC model simulates the ter-

1 FEBRUARY 2008 S H E F F I E L D A N D W O O D 433

restrial water and energy balances and distinguishes it-self from other land surface schemes through the rep-resentation of subgrid variability in soil storage capacityas a spatial probability distribution, to which surfacerunoff is related, and by modeling base flow from alower soil moisture zone as a nonlinear recession. TheVIC model has been applied extensively at regional(e.g., Maurer et al. 2002) and global scales (Nijssen etal. 2001; Sheffield et al. 2004b).

For this study, the VIC model was run globally at 1.0°spatial resolution and 3-hourly time step for the period1950–2000. This simulation was forced by a hybriddataset of precipitation, near-surface meteorologicaland radiation data derived from the National Centersfor Environmental Prediction–National Center for At-mospheric Research (NCEP–NCAR) reanalysis (Kal-nay et al. 1996) and a suite of global observation-basedproducts. In effect, the subdaily variations in the re-analysis are used to downscale the monthly observa-tions. These observations, which are generally availableat higher spatial resolution, are concurrently used todownscale the reanalysis in space. Known biases in thereanalysis precipitation and near-surface meteorologywere corrected at the monthly scale using observation-based datasets of precipitation, air temperature, andradiation. Corrections were also made to the rain daystatistics of the reanalysis precipitation, which havebeen found to exhibit a spurious wavelike pattern inhigh-latitude wintertime. Other meteorological vari-ables (downward short- and longwave, specific humid-ity, surface air pressure, and wind speed) were down-scaled in space with account for changes in elevation.The forcing dataset is described in detail by Sheffield etal. (2006). The simulation has been validated againstavailable observations of terrestrial hydrology (J. Shef-field and E. F. Wood 2007, unpublished manuscript),including in situ measurements of soil moisture, largebasin streamflow, and remote sensing–based snowdatasets.

Given recent and future potential increases in airtemperature, we also carried out a second simulation toinvestigate the impact of trends in temperature on thedrought trends. Higher temperatures will increase po-tential evapotranspiration and possibly result in in-creased drought occurrence, although actual changeswill be controlled by available moisture from precipi-tation and be modified by temperature impacts onsnow. Following Hamlet et al. (2007) and Dai et al.(2004), we forced the VIC model with climatologicalsurface air temperature instead of annually varying val-ues. In this way, any differences in the trends in soilmoisture and drought characteristics between the twosimulations would be attributable to trends in tempera-

ture. In the discussion in section 5b, the original simu-lation with annually varying air temperature forcing isreferred to as TANN and the simulation with climato-logical air temperature as TCLIM.

b. Relationship with previous studies of droughtusing the VIC model

Previously, soil moisture fields from a retrospectivesimulation of the VIC model for the United States(Maurer et al. 2002) have been analyzed in terms ofdrought occurrence by Sheffield et al. (2004a), whofound that the simulated soil moisture values were ableto represent historic drought events, display coherencyand sufficient detail at small space scales, and comparewell with standard drought indices such as the PDSI.The PDSI is one of the most widely used drought indi-ces both operationally and in climate research (Dai etal. 2004; Burke et al. 2006) and uses a generic two-layersoil model to describe the cumulative departure ofmoisture supply (Palmer 1965). In snow-dominated re-gions, Sheffield et al. (2004a) found that the VIC-baseddataset and the PDSI dataset diverged, likely becauseof inadequate representation of cold season processesin the calculation of the PDSI.

The simulations analyzed in Sheffield et al. (2004a)and in this paper were both generated by the VICmodel (albeit slightly different versions) but differ sub-stantially in terms of their domain (United States versusglobal), the meteorological forcings (gauge based ver-sus a hybrid reanalysis–observation dataset), spatialresolution (0.125° versus 1.0°), and parameter data (dif-ferent underlying datasets for the soil and vegetationdistributions). Despite this, comparison of their repre-sentation of drought over the United States shows goodagreement with respect to major drought events (notshown). Furthermore, the trends described in section 3are consistent with Andreadis and Lettenmaier (2006)who used an extended version of the Maurer et al.(2002) U.S. dataset at 0.5° resolution. Work in progresshas compared the 0.5° extended dataset with this globaldataset in the framework of severity–area–durationcurves (Andreadis et al. 2005) and shows close agree-ment that is encouraging given the differences in thesimulations.

c. Soil moisture–based drought index

The drought index is calculated using the method ofSheffield et al. (2004a) and is briefly described here.Simulated soil moisture data at multiple model soil lay-ers are aggregated over the total soil column, convertedto volumetric values, and averaged to monthly values.For each model grid cell and month, a beta distribution


is fitted to the 51 monthly values (1 value for each yearin 1950–2000) using the method of moments. The cur-rent level of drought or wetness for a particular monthand point in space can then be gauged relative to thisfitted distribution or climatology. A drought is definedas a period of duration D months with a soil moisturequantile value, q(�), less than an arbitrary thresholdlevel, q0(�), preceded and followed by a value abovethis level. The departure below this level at any par-ticular time is the drought magnitude:

M � q0�� q��,

and the mean magnitude over the drought duration isthe intensity:

I �1D �

t�t1

t1 � D�1

q0�� q��t.

The product of duration and intensity gives the droughtseverity:

S � I � D, or

S � �t�t1

t�D�1

q0�� q��t,

acknowledging that the impacts of drought are a bal-ance between the length and the intensity of deficits.We also define classes of drought event based on theirduration as follows:

D4�6, short term: 4 � D � 6, q�� q0��,

D7�12, medium term: D7 � D � 12, q�� q0��,

D12�, long term: D � 12, q�� q0��,

where the subscript to D indicates the range of droughtduration in months. A climatological analysis of thisdataset is given in Sheffield and Wood (2007).

3. Trends in soil moisture and drought

a. Trends in soil moisture

Trends are calculated using the nonparametricMann–Kendall trend test (Mann 1945; Kendall 1975;Hirsch and Slack 1984), which is robust and distributionindependent. We tested for serial correlation in themonthly data, which would invalidate the assumptionof independent data. The areal extent of statisticallysignificant serial correlation (0.01 level) is between12% and 17% depending on the month, with about50% of this area in drier regions and the majority of theremainder in very high latitudes. Therefore, the areathat potentially invalidates the independence assump-tion is small and generally restricted to drier regions,

such as the Sahara, which we ignore in the analysis.Figure 1 shows a map of the trends in annual volumetricsoil moisture on a grid by grid basis. Results for theSahara and other desert regions have been maskedout based on a threshold of mean annual precipitation0.5 mm day�1 to screen out serially correlated dataand trend values that are essentially zero but are pickedup by the ranked-based test. Table 1 summarizes trendsof regional averaged time series. The regions are de-fined by Giorgi and Francisco (2000) and are shown inFig. 2. For brevity, these regions may be referred to byacronyms that are defined in Table 1. The GRL regionwas originally defined as Greenland and northeasternCanada, but as the VIC model is not designed to simu-late permanent ice sheets and glaciers we exclude theinterior of Greenland from the definition of the GRLregion and rename it northeastern Canada (NEC). Wediscuss the trend results in relation to precipitation andtemperature trends in the forcing dataset (Fig. 3), whichare calculated in the same manner as for the soil mois-ture quantiles.

At global scales, the trend in soil moisture is positive(wetting). Generally speaking, wetting trends occur inthe Americas, Australia, Europe, and western Asia,and negative trends (drying) occur in Africa and partsof eastern Asia. The trends are generally collocatedwith equivalent trends in precipitation (Fig. 3). Statis-tically significant trends in soil moisture at the 0.05 levelare, however, restricted to relatively small subareas ofthese continents. Regions of wetting trends are evidentin the central Northern Territories of Canada (up to0.2% vol yr�1), central USA (0.05%–0.2% vol yr�1)and northern Mexico (0.1% vol yr�1). These are co-incident with statistically significant increasing trends inprecipitation (Fig. 3). For northern Canada, increasedprecipitation has also been noted by Zhang et al. (2000)and McBean et al. (2005). Nevertheless, the simulatedincrease in soil moisture (and increase in precipitation)appears contradictory to decreasing river discharge intothe Arctic and North Atlantic from Canadian riverssince the mid-1960s (Déry and Wood 2005a). Thiscould be explained by increasing evapotranspirationdriven by higher temperatures (Zhang et al. 2000) thatresults in increased precipitation and decreased stream-flow, although changes to snow will complicate this.However, calculation of soil moisture trends over a simi-lar period (1964–2000) as used by Déry and Wood(2005a) shows widespread decreasing (but not alwayssignificant) trends over much of northern Canada that isconsistent with decreasing streamflow. This indicatesthe large influence of increasing moisture during 1950–63on the overall trend, which is further discussed in gen-eral in section 4b. The trends over the United States are


FIG. 1. Global distribution of linear trends in annual mean volumetric soil moisture, 1950–2000, calculated using the Mann–Kendallnonparametric trend test. Regions with mean annual precipitation less than 0.5 mm day�1 have been masked out because the VICmodel simulates small drying trends in desert regions that, despite being essentially zero are identified by the nonparametric test. Thetrends in the bottom panel have been filtered for significance at the 0.05 level.


Fig 1 live 4/C

also consistent, with increases in precipitation and soilwetness during the twentieth century reported byGroisman et al. (2004) and Andreadis and Lettenmaier(2006). Scattered regions in Brazil and Columbia and alarge part of central Argentina show increasing trendsup to 0.1% vol yr�1. These are generally collocatedwith increasing precipitation trends, and the trends areconsistent with increased streamflow in large SouthAmerican basins (Garcia and Mechoso 2005) and in-creased precipitation and streamflow in the La Platabasin (Berbery and Barros 2002). In the Western Hemi-sphere, parts of Scandinavia, eastern Europe, and west-ern Russia show increasing trends (up to 0.2% volyr�1). A few small regions of significant increasingtrend of up to 0.4% vol yr�1 occur in western China inthe northern Tibetan Plateau. In western Australiathere are significant increasing trends up to 0.25% volyr�1. These trends are generally consistent with increas-ing precipitation in these regions, also noted over thetwentieth century by Dai et al. (1997).

Drying trends are most prominent in the Sahel (up to�0.6% vol yr�1 for individual grid cells), which hasbeen well documented in terms of precipitation deficitsduring the 1970s and 1980s (Hulme 1992; L’Hôte et al.

2002). Also, significant decreasing trends occur in partsof central Africa and in southern Africa (up to �0.15%vol yr�1 through Angola and Zambia) that coincidewith the southern extent of the ITCZ and are againcollocated with decreasing trends in precipitation. Al-though the Arctic as a whole has likely experiencedincreased precipitation over the latter half of the twen-tieth century (McBean et al. 2005), several regionsshow significant drying trends, such as northern andsoutheastern Alaska. The majority of northeasternAsia shows drying trends (up to �0.2% vol yr�1) thatare coincident with decreasing precipitation as shown inFig. 3 and reported by McBean et al. (2005), althoughthe area of statistically significant values is relativelysmall, being restricted to the central Yenesei and east-ern Amur basins and far northeastern Siberia. The con-sistency of these trends with observed changes in re-lated variables is unclear, as there is lack of consistencybetween increasing Arctic discharge from Siberian riv-ers (Peterson et al. 2002; Shiklomanov et al. 2006) andprecipitation (Berezovskaya et al. 2004) and much de-bate over the impact of other processes such as changesin permafrost and fires (McClelland et al. 2006). Sig-nificant drying trends are also apparent in northern

TABLE 1. Nonparametric trends in regional average soil moisture quantile, precipitation, and surface air temperature. Trends valuesin bold are significant at the 0.05 level. Statistical test values are given in parentheses.

RegionSoil moisture

quantile (% yr�1)Precipitation

(mm day�1 yr�1)Surface air

temperature (K yr�1)

World 0.017 (1.137) �0.001 (�0.999) 0.015 (5.166)Europe

Northern Europe (NEU) 0.096 (1.592) 0.003 (1.811) 0.018 (2.307)Mediterranean (MED) �0.048 (�0.780) �0.002 (�1.430) 0.009 (2.201)

AfricaWest Africa (WAF) �0.299 (�4.207) �0.009 (�3.964) 0.008 (3.647)East Africa (EAF) �0.144 (�2.713) �0.004 (�2.355) 0.016 (5.556)Southern Africa (SAF) �0.149 (�1.901) �0.003 (�1.446) 0.012 (4.524)

North AsiaNorthern Asia (NAS) �0.073 (�1.868) �0.001 (�0.650) 0.023 (3.233)Central Asia (CAS) �0.016 (�0.227) �0.001 (�1.056) 0.018 (3.411)Tibetan Plateau (TIB) 0.133 (1.689) �0.000 (�0.032) 0.021 (4.768)Eastern Asia (EAS) �0.083 (�1.982) �0.001 (�1.413) 0.016 (3.891)

South Asia and OceaniaSoutheast Asia (SEA) 0.020 (0.211) �0.006 (�1.040) 0.009 (4.776)South Asia (SAS) �0.055 (�1.251) �0.007 (�2.534) 0.007 (2.843)Australia (AUS) 0.214 (2.079) 0.003 (1.218) 0.014 (4.427)

North AmericaAlaska (ALA) 0.169 (1.527) 0.002 (2.339) 0.032 (3.947)Western North America (WNA) 0.212 (2.713) 0.002 (1.933) 0.020 (3.281)Central North America (CNA) 0.253 (2.892) 0.006 (1.998) 0.007 (1.162)Eastern North America (ENA) 0.108 (1.836) 0.001 (0.569) 0.002 (0.528)Northeastern Canada (NEC) 0.252 (2.437) 0.003 (2.485) 0.007 (1.007)

South AmericaCentral America (CAM) 0.091 (1.429) �0.002 (�0.877) 0.007 (2.063)Amazon (AMZ) 0.152 (2.331) 0.004 (1.348) 0.009 (3.225)Southern South America (SSA) 0.184 (2.827) 0.005 (2.290) 0.004 (1.998)


China and parts of Southeast Asia, up to �0.2% volyr�1. This is consistent with Zou et al. (2005), who ana-lyzed trends in PDSI data in China during 1951–2003and found no significant changes except for northernregions.

To investigate whether the trends vary by season,which is more likely in monsoonal regions and conti-nental interiors where interseasonal climate variabilityis relatively high, we also calculated trend values foreach season separately (Fig. 4). Over the United States,the overall increasing trend is most prominent in wintermonths. In South America, the tendency is for highertrends in Argentina during the Austral summer [De-cember–February (DJF)] and autumn [March–May(MAM)] whereas trends in Brazil and elsewhere in thenorth are greater in the drier seasons [June–July (JJA),September–November (SON)]. Over Africa, the largesttrends tend to coincide with the peak or retreat of theITCZ (JJA and SON over the Sahel; DJF and MAM incentral and southern Africa). The few scattered regionsof significant trends in Europe are mainly restricted tothe winter months. Decreasing trends in far northeast-ern Siberia are dominant in the summer, whereas in-creasing trends east of the Urals are dominant in thespring. Decreasing trends in China are highest in the

DJF–MAM, and decreasing trends in northern Indiaand Southeast Asia are highest in the Monsoon season(JJA–SON). In Australia, increasing trends in the westare highest in the Austral summer (DJF).

b. Global trends in drought characteristics

Next we investigate trends in droughts characteristics(duration, magnitude, and severity) over the 50-yr pe-riod. Trends are again calculated using the Mann–Kendall nonparametric test. Individual drought eventsare assumed to be independent and the period betweenevents is calculated from the beginning of an event tothe beginning of the next. We tested for serial correla-tion in the characteristics of events and found thatabout 5% or less of grid cells had significant values(0.05 level) and, similar to the results for soil moisture,that most of these were located in the Sahara regionwhich we ignore in the analysis. The geographic distri-bution of trends in drought duration, intensity, and se-verity is shown in Fig. 5 for statistically significanttrends only, at the 0.05 level for soil moisture quantilethreshold q0(�) � (10.0, 50.0), corresponding to severeand mild drought, respectively. Table 2 shows the per-cent area of each continent that has statistically signifi-

FIG. 2. Map of regions used in the analysis as defined by Giorgi and Francisco (2000). The GRL region has been modified from itsoriginal definition that covered Greenland and eastern Canada to exclude the interior of Greenland. This is because the VIC modelis not designed to simulate permanent ice caps and glaciers. The region is renamed NEC.


Fig 2 live 4/C

cant trends in drought characteristics. In general, hy-drological and meteorological variables exhibit spatialcorrelation, which reduces the number of independentdata points over a region. To determine the field sig-nificance of the area of significant trends, we estimatedthe distribution of trend areas using a bootstrap ap-proach in which we generate 1000 time series of soilmoisture fields by resampling from the original dataset.Tests over a single region showed that 1000 sampleswere sufficient to give stable results. The area of sig-nificant trends was then calculated for each resampledseries and the 95th percentile calculated from the totalsample. If the original trend area is greater than thispercentile value it is field significant.

Overall, the area that has undergone statisticallysignificant changes in drought characteristics is small(Table 2). In general, the area of negative trends isgreater than that of positive trends, a result of theglobal wetting trend in soil moisture. Significant trendsare more spatially extensive for q0(�) � 50%, a resultinfluenced by the greater number of droughts at this

threshold value. Also, the area of significant trends indrought severity is generally greater than that fordrought intensity, which is in turn greater than that forduration. Globally, only 0.6%–4.1% of the land has ex-perienced increasing trends in duration, intensity andseverity, and 1.8%–6.8% has experienced decreas-ing trends. At continental scales, Africa is dominatedby significant increasing trends in drought severity[area � 10.4% for q0(�) � 50%]. Over Asia, the areasof significant decreasing trends at q0(�) � 50% arehighest for duration (4.5%), intensity (4.0%), and se-verity (4.0%). Negative trends tend to dominate overEurope, especially for drought duration [area � 9.6%for q0(�) � 50%]. Elsewhere, decreasing trends aremore prevalent in North America (e.g., area of decreas-ing trends in duration � 8.3%) and Oceania especiallyfor drought intensity [area � 10.3% for q0(�) � 50%].In South America, the area of decreasing trends isdominant, especially for q0(�) � 50% (8.1%, 8.1%,and 9.7% for duration, intensity, and severity, respec-tively).

FIG. 3. Global distribution of linear trends, 1950–2000, in surface air temperature and precipitation as used to force the VIC model.The data are taken from the dataset of Sheffield et al. (2006), which are based on the CRU TS2.0 dataset of Mitchell and Jones (2005).The trends in the right-hand panels have been filtered for significance at the 0.05 level.


Fig 3 live 4/C

c. Regional trends in drought spatial extent

Table 3 gives trends in the spatial extent of droughtfor the world and regionally, for various threshold val-ues. Globally, there is an overall decreasing trend indrought extent of �0.021 to �0.035% yr�1, althoughonly for a threshold q0(�) � 20% are the trends statis-tically significant at the 0.05 level. Regionally there aredistinct differences in the sign of the trends as well asthe magnitude and statistical significance that are con-sistent with the trends in soil moisture. Over northernEurope the tendency is for a decrease in spatial extent,although only trends for q0(�) � 20.0 are significant,and in the Mediterranean region all trends are positivebut essentially statistically zero. Lloyd-Hughes andSaunders (2002) analyzed PDSI and SPI over Europe,and similarly found generally insignificant change in theproportion of land experiencing medium to extremedrought during the twentieth century. West Africa isdominated by events in the Sahel, which result in large

increases in spatial extent that are approximately pro-portional to the threshold. For example, for q0(�) �50% the trend is 0.527% yr�1, which translates intoabout 28% increase over the full period. Although east-ern Africa shows consistently increasing trends also (upto 0.15% yr�1), they are only significant for q0(�) �

40%. In southern Africa (SAF), positive trends of0.038%–0.234% yr�1 are only significant at the 0.1level.

Over the northern part of Asia (regions NAS, CAS,TIB, and EAS) the picture is mixed, with positive andsignificant trends over northern Asia, positive but in-significant trends over eastern Asia and negative trendsover central Asia and the Tibetan Plateau, althoughonly over TIB are the majority of the trends significant.All trends in southern Asia are insignificant with nega-tive trends for SEA and positive for SAS. The Austra-lian region trends are negative and all significant rang-ing from �0.08% to �0.32% yr�1. For North America,the trends in spatial extent are uniformly negative and

FIG. 4. Global distribution of linear trends in seasonal meanvolumetric soil moisture, 1950–2000, calculated using the Mann–Kendall nonparametric trend test. Regions with mean annual pre-cipitation less than 0.5 mm day�1 have been masked out in thesame way as for Fig. 1. The bottom panel shows the seasonalrange in trends calculated as the maximum minus the minimumtrend of the four seasonal values at each grid cell.


Fig 4 live 4/C

almost always significant [the exceptions are in WNAfor q0(�) � (10, 20), ENA for q0(�) � (10, 20, 30)threshold, and ALA for q0(�) � (40, 50) threshold].The largest trends are in CNA for q0(�) � 50% (ap-proximately �0.4% yr�1 or 19% decrease in spatialextent over the full period) and NEC for q0(�) � 50%(approximately �0.5% yr�1 or 26% decrease). Oversouth America, all trends are negative, with all AMZtrends significant, but only trends for q0(�) � 30% sig-nificant in CAM and for q0(�) � 30% in SSA.

d. Epochal changes in drought frequency

We next calculated the change in drought statisticsbetween the first (1950–75) and second (1976–99)halves of the simulation period (Fig. 6), which showsthat the number of droughts has tended to decrease

over most parts of the world. For short-term droughts,D3–6, midlatitudes are dominated by decreases, mostnotably in central and eastern Europe, Australia, south-ern South America, and central North America. In-creases are evident across southern Canada, southwestEurope, and across northern Russia and most of Sibe-ria, although these are localized. The pattern for me-dium-term (D6–12) droughts is more organized, withlarge and spatially coherent decreases across most ofAlaska and northern Canada, eastern Europe and west-ern Russia, subtropical Asia, and central Australia.Conversely, a large expanse of increased frequencytraverses Siberia. The number of long-term droughts(D12) in both epochs is limited to a few regions (north-ern Canada, Tibetan Plateau) and the changes are alldecreasing. Mean drought duration has decreased innorthern midlatitudes and northern Canada, but has

FIG. 5. Nonparametric trend in drought duration D, intensity I, and severity S for q0(�) � {10.0%, 50.0%} threshold values for1950–2000. Note that the units have been scaled by 10 000, 1000, and 100, respectively. Regions with average precipitation 0.5 mmday�1 have been masked out.


Fig 5 live 4/C

increased over the northwest United States and largeregions of Siberia. In Africa, mean drought durationincreased in the Sahel and southern Africa. For droughtintensity the changes are generally small and localized,and where they are more prominent they tend to col-locate with regions of large changes in mean droughtlength. For drought severity, the distribution of changesis similar to that for mean drought duration, and giventhat changes in mean drought intensity are relativelysmall, the indication is that changes in drought severityare driven mainly by changes in drought duration.

4. Temporal variability of soil moisture anddrought

a. Regional temporal variability

Within the long-term linear trends identified there isconsiderable variability at interannual to decadal timescales. Figure 7 shows the temporal variation of severaldrought characteristics {mean drought duration, D for[q0(�) � 50.0%]; number of short, high-intensitydroughts [q0(�) � 10.0%, D � D1–3]; number of long,low-intensity droughts [q0(�) � 50.0%, D � D12�]; spa-tial extent of drought [q0(�) � 50.0%, D � D1] calcu-lated for an 11-yr moving window. The drought char-acteristics are averaged over each region. The time se-ries for long, low-intensity droughts is multiplied by afactor of 3 to aid visualization. At global scales, there islittle variation over the time period in drought durationand frequency, although the spatial extent of drought

TABLE 2. Percent area with statistically significant positive or negative trends in drought duration (D), intensity (I), and severity (S)for q0(�) � (10.0, 50.0%). The values in parentheses are field significance calculated using a bootstrap resampling approach.

D I S

�ve �ve �ve �ve �ve �ve

q0(�) � 10%World 0.6 (19) 1.8 (80) 1.8 (74) 3.1 (91) 1.9 (69) 2.6 (60)Africa 0.8 (95) 1.7 (97) 1.7 (70) 2.3 (71) 2.4 (89) 2.1 (48)Asia 0.9 (74) 1.3 (19) 2.1 (92) 2.8 (64) 2.4 (95) 1.7 (5)Europe 0.4 (25) 3.3 (90) 1.6 (47) 3.9 (75) 1.0 (23) 4.0 (75)North America 0.3 (2) 2.7 (95) 1.3 (13) 4.2 (98) 1.3 (19) 4.1 (94)Oceania 0.3 (15) 0.8 (7) 2.1 (77) 2.8 (57) 1.4 (37) 3.1 (71)South America 0.2 (19) 1.7 (45) 2.1 (80) 2.8 (72) 1.8 (33) 2.1 (36)

q0(�) � 50%World 1.9 (98) 6.8 (100) 3.0 (97) 6.0 (99) 4.1 (100) 6.6 (99)Africa 4.1 (99) 7.4 (98) 6.8 (100) 4.5 (81) 10.4 (100) 4.6 (80)Asia 2.2 (96) 4.5 (85) 3.2 (85) 4.0 (69) 4.5 (99) 4.0 (69)Europe 1.0 (63) 9.6 (100) 0.9 (31) 6.4 (98) 1.1 (43) 8.2 (97)North America 1.1 (43) 8.3 (99) 1.9 (38) 7.6 (99) 2.0 (35) 9.4 (99)Oceania 0.7 (29) 5.2 (83) 0.7 (15) 10.3 (96) 1.0 (20) 7.8 (91)South America 0.5 (36) 8.1 (98) 2.0 (43) 8.1 (96) 1.8 (40) 9.7 (96)

TABLE 3. Trends in the spatial extent of drought for variousq0(�) values. The trends are calculated using the Mann–Kendallnonparametric test. Trend values in bold are significant at the0.05 level.

Region

Trend in drought spatial extent (% yr�1)

q0(�)

10.0 20.0 30.0 40.0 50.0

World �0.021 �0.032 �0.035 �0.027 �0.021Europe

NEU �0.102 �0.143 �0.139 �0.139 �0.140MED 0.014 0.022 0.022 0.026 0.022

AfricaWAF 0.068 0.179 0.319 0.435 0.527EAF 0.029 0.064 0.088 0.117 0.154SAF 0.038 0.090 0.150 0.203 0.234

North AsiaNAS 0.055 0.102 0.129 0.139 0.140CAS �0.049 �0.098 �0.151 �0.176 �0.203TIB �0.063 �0.130 �0.166 �0.208 �0.206EAS 0.011 0.023 0.053 0.083 0.093

South Asia and OceaniaSEA �0.011 �0.016 �0.026 �0.031 �0.009SAS 0.022 0.031 0.037 0.032 0.032AUS �0.082 �0.191 �0.258 �0.319 �0.318

North AmericaALA �0.115 �0.206 �0.238 �0.241 �0.207WNA �0.052 �0.113 �0.195 �0.248 �0.279CAN �0.108 �0.199 �0.264 �0.325 �0.376ENA �0.050 �0.108 �0.152 �0.177 �0.185NEC �0.181 �0.315 �0.407 �0.481 �0.509

South AmericaCAM �0.060 �0.118 �0.139 �0.130 �0.111AMZ �0.069 �0.125 �0.172 �0.216 �0.238SSA �0.034 �0.090 �0.155 �0.214 �0.258


has swung from the high of the 1950s through a low inthe 1960–70s and back up again in recent years.

Figure 8 shows the spatial loadings of the first threeprincipal components of monthly soil moisture quan-tiles and represents the major modes of variability inglobal drought and wet spells. Figure 9 shows smoothedtime series of these principal components. Althoughthe variance explained by the first three components issmall, the value decreases rapidly for higher order com-ponents, and so we show only the first three compo-nents for brevity. PC1 explains 8.1% of the global vari-ability in soil moisture and is negative in the Amazon,the Sahel, southern Africa, northeastern Siberia, South-east Asia, and Australia among other places. It is posi-tive in southern South America, central and southernUnited States, northern Canada, and central and east-ern Asia. The distribution of loadings for PC1 remi-nisce ESNO impacts. In fact the time series in Fig. 9 is

correlated with Niño-3.4 SST variability (r � 0.50) andso, notwithstanding the variability associated with theoverall trend, tropical Pacific temperatures appear tobe the primary driver of global variability in soil mois-ture, a result also shown by Dai et al. (2004) for PDSIdata. PC2 explains 6.4% of the variance and showsstrong positive loadings over northern Canada, theAmazon, southern Africa, and central Australia. Nega-tive loadings are highest in Alaska, northern Europe,and far eastern Asia. The time series of PC2 shows alow-frequency multidecadal oscillation that covarieswell with the AMO index (r � 0.67) and is consistentwith the PDSI analysis of McCabe and Palecki (2006).The third component, PC3, explains 6.0% of the vari-ance and shows strong positive loadings over centralEurope through Russia, Australia, South America andAlaska, and strong negative loadings over northern Si-beria, east Africa, and northeast Canada. The decadal

FIG. 6. Percent change in frequency of short- (D3–6), medium- (D6–12), and long-term (D12�) duration droughts and mean droughtduration (D), intensity (I), and severity (S ) for q0(�) � 10.0%, between 1950–75 and 1976–99.


Fig 6 live 4/C

FIG. 7. Regional average time series of various drought statistics: mean duration of drought [q0(�) � 50.0%],number of droughts [q0(�) � 10.0%, D � D1–3], number of droughts [q0(�) � 50.0%, D � D12�], and spatial extentof drought [% area, q0(�) � 50.0%, D � D1]. The statistics are calculated over an 11-yr moving window and areplotted at the center of the window. The data series for the number of long-term droughts [q0(�) � 50.0%, D �D12�] are multiplied by 3 for ease of comparison.


Fig 7 live 4/C

FIG. 8. Spatial loadings of the first three principal components of annual soil moisture quantile for1950–2000. The amount of variance explained by each component is also given.


Fig 8 live 4/C

variability follows the NAO somewhat (Fig. 9), how-ever the correlation is insignificant (r � 0.21) and es-pecially weak during the mid-1980s–mid-1990s.

Regionally, considerable variation in drought char-acteristics is evident (Fig. 7), and we can also relate thevariations in soil moisture to large-scale climate oscil-lations that act at interannual to decadal time scales.Table 4 shows the correlation between regional princi-pal components of smoothed monthly soil moisturequantiles and various climate indices. The soil moisturedata are detrended to avoid spurious correlations atmultidecadal time scales and the PCs are smoothed us-ing a 13-month moving window. It should be noted thatthe large extent of some regions may hide any strongconnectivity at smaller scales.

In northern Europe, a decadal oscillation, most evi-dent in the spatial extent, underlies the small decreas-ing trend in drought (section 3c), with peaks in the1950s, 1970s, and 1990s (Fig. 7). Lloyd-Hughes andSaunders (2002) and van der Schrier et al. (2006) also

found the 1950s and 1990s to be the most drought-prone periods in terms of PDSI and 3- and 12-monthSPI. For the Mediterranean, although overall trends areinsignificant, there is a slight decreasing trend until theearly 1980s when there is a sharp increase in frequen-cies, especially for drought spatial extent. The underly-ing soil moisture variability in the Mediterranean ap-pears to be weakly correlated with the NAO (r � 0.56),as documented previously (e.g., Rodo et al. 1997). Therelationship in northern Europe is insignificant (r ��0.19, Table 4), which may be a result of the variabilityin strength of connectivity across the region and sea-sonally (Uvo 2003).

FIG. 9. Smoothed time series of the first three principal com-ponents of monthly soil moisture quantile for 1950–2000 com-pared to climate indices. Niño-3.4 SSTs are defined as over 5.0°S–5.0°N, 120.0°–170.0°W. AMO: Atlantic multidecadal oscillationdefined as detrended area weighted average SSTs over the NorthAtlantic, 0°–70°N. NAO: DJFM wintertime North Atlantic Oscil-lation defined as the difference of normalized sea level pressurebetween stations in Portugal and Iceland.

TABLE 4. Correlation between regional principal components ofdetrended annual soil moisture quantile and various climate indi-ces. The climate indices are also annual values and are comparedyear for year (51 values) with no lag relative to the soil moisturedata. The correlations are the maximum values for the first threePCs and those in bold are statistically significant at the 0.01 level.Niño-3.4: SST anomalies in the Niño-3.4 region, 5.0°S–5.0°N,120.0°–170.0°W. PDO: Pacific decadal oscillation defined as theleading PC of monthly SST anomalies in the North Pacific Ocean,poleward of 20°N. AMO: Atlantic multidecadal oscillation de-fined as detrended area weighted average SSTs over the NorthAtlantic, 0°–70°N. NAO: DJFM wintertime North Atlantic Oscil-lation defined as the difference of normalized sea level pressurebetween Portugal and Iceland.

Region

Climate index

Niño-3.4 PDO AMO NAO

World �0.50 �0.22 �0.67 �0.21Europe

NEU �0.20 0.23 0.24 �0.19MED 0.21 0.19 �0.20 0.56

AfricaWAF �0.16 �0.17 �0.46 �0.43EAF �0.48 �0.16 0.43 �0.32SAF �0.39 0.16 �0.36 0.18

North AsiaNAS �0.17 �0.08 0.16 �0.16CAS �0.46 �0.22 �0.49 �0.13TIB 0.08 �0.23 0.42 �0.24EAS 0.42 0.17 �0.28 0.22

Southern Asia and OceaniaSEA �0.87 �0.17 �0.12 0.04SAS 0.39 0.12 �0.20 �0.14AUS �0.49 �0.13 0.20 �0.04

North AmericaALA �0.12 0.12 0.46 0.33NEC �0.34 �0.19 0.49 �0.18WNA 0.38 0.22 0.45 0.23CNA 0.39 �0.12 0.26 �0.15ENA 0.24 �0.09 0.32 �0.12

South AmericaCAM 0.36 0.22 0.42 �0.22AMZ 0.72 0.11 �0.37 �0.23SSA 0.33 �0.1 �0.18 �0.21


The change in the number of droughts over WestAfrica is dominated by the increasing trend up to themid-1980s but there is a large reversal in trend in thefollowing years. Correlations between the detrendedsoil moisture time series and the AMO are modest (r ��0.46 for PC1) but are consistent with observationaland model-based studies (Zhang and Delworth 2006).Previous studies have shown that NAO has some influ-ence over the climate in this region (Oba et al. 2001),although there is contradictory evidence (Wang 2003)and the correlation here is weakly significant (r ��0.43 for PC2), which reflects this uncertainty. A simi-lar, but less pronounced, picture is apparent in EastAfrica, with a noticeable decrease in drought frequencyin the 1950–60s. The AMO and Niño-3.4 SSTs providethe highest, but weak, correlations (r � 0.43 and 0.48,respectively). In southern Africa, peaks occur in thelate 1960s and early 1990s, which overlays the positivetrend in drought characteristics and decreasing soilmoisture trend. Rouault and Richard (2005) analyzedSouth African SPI and found a substantial increase in2-yr droughts since the 1970s. They surmised that thechange was likely driven by stronger connections withENSO, although correlations here with the Niño-3.4index are low, likely due to the large size of the SAFregion.

A decadal oscillation in north Asia (NAS) overlaysthe general increasing trend for all characteristics that isconsistent with decreasing soil moisture. Of note is theincrease in the number of long, low-intensity droughtsduring the 1980s and 1990s, which may be related to theswitch to a positive NAO phase (Visbeck et al. 2001),although correlations of soil moisture with climate in-dices are insignificant. Central Asian droughts also fol-low a decadal cycle, peaking in the 1970s and endingwith an upward trend in the 1990s. Correlations withclimate indices are weak but greatest with the Niño-3.4and AMO indices. Over the Tibetan Plateau, the seriesare dominated by a peak in all variables around 1960,and a decreasing trend thereafter until the early 1990s,when there are slight increases again, which has con-tinued into recent years (Barlow et al. 2002). The AMOprovides the only significant, although weak, correla-tion (r � 0.42). Drought in East Asia shows little varia-tion over the 50 yr as seen before and is most closelytied to Niño-3.4 variability.

For Southeast and South Asia, there are small butincreasing trends over much of the period with a slightdecreasing trend in the 1990s. Note the high and ex-pected correlation (r � �0.87, PC1) with the Niño-3.4index. The decreasing trends over Australia are domi-nated by a large amplitude decadal variation that peaks

in the 1960s and late 1980s. The correlation with Niño-3.4 is expected (r � �0.49, PC1) but is weak, likelyowing to the size of the AUS region.

Over North America, the overall wetting trend is re-flected in decreasing trends in all drought variables, yetthere is large variability within this. Alaska and North-eastern Canada show large decreases since the 1950sbut an upturn in the 1990s with weak correlation be-tween soil moisture and the AMO (r � 0.46 and 0.49,respectively, PC1). The number and spatial extent ofdroughts in western North America decreases until theearly 1970s, at which time they increase to the end ofthe record. In central North America there is an overalldecreasing trend, although both the western and centralregions exhibit an upward jump in longer durationdrought frequencies during the 1970s. In eastern NorthAmerica the series are dominated by decadal variabilityoverlaid by a decreasing trend. Low values occur duringthe 1970s and for a brief period around the early 1990s.The changes across these three latter regions are gen-erally consistent with the overall decreasing droughttrends found by Andreadis and Lettenmaier (2006) forthe United States.

A decreasing trend is apparent in Central America,most prominently at the beginning of the period. TheAmazon is dominated by a decadal cycle, peakingin the early 1960s and mid-1980s that relates to Niño-3.4 SSTs (r � �0.72). In southern South America thereare similar oscillations with peaks in frequenciesand extent in the mid-1960s followed by a drop untilthe early 1980s and then increasing conditions there-after.

b. Variation and robustness of trends

The regional time series of soil moisture and droughtstatistics show large variability within the long-termtrends identified in section 3. Of interest is how thesevariations affect the robustness of the global wettingtrend, especially as we move into the twenty-first cen-tury and the potential impacts of global warming. Re-cent increases in global temperatures (e.g., Jones et al.1999; Jones and Moberg 2003; Hansen et al. 1999; Bro-han et al. 2006) may have already caused an accelera-tion of the water cycle (Huntington 2006) and intensi-fication of drought. For example, many regions showdecadal variations that switch during the 1970s, whichhas been reported previously (Dai et al. 2004; Rouaultand Richard 2005) and may be indicative of tem-perature impacts on drought, either directly or indi-rectly through intensification of climate drivers such asENSO (Hunt 1999; Herbert and Dixon 2003). Never-theless, evidence of increasing summertime soil mois-


ture across Asia despite increasing temperatures (Ro-bock et al. 2000) and forcing of increased drought bylarge-scale climate anomalies [e.g., decreased late-spring precipitation in China driven by a shift to posi-tive phase of the NAO (Xin et al. 2006)] add to theuncertainty of current and future drought response tochanging temperatures.

Figure 10 shows a time series of trends in regionalmean soil moisture quantile calculated over an 11-yrmoving window. The trends are color coded accordingto the sign of the trend and the statistical significance atthe 0.05 level. At the global scale the trends oscillatefrom wetting to drying around the mid-1970s with peakdrying trends in the mid-1980s and subsequent reduc-tion in magnitude toward the end of the century. Overnorthern Europe, mostly insignificant wetting trendsare separated by drying trends at the beginning and endof the series. In the Mediterranean, initially increasingsoil moisture is overwhelmed by decreasing trends fromthe mid-1960s onward. For Africa, generally decreasingtrends dominate (with a spate of increasing trends cen-tered on 1970 in southern Africa), although all regionsbegin to experience increasing trends at the end of thetime period. Over northern Asian regions, mostly in-creasing trends are juxtaposed with decreasing trends inthe last 20 yr, although the north Asia region showsdrying trends since the mid-1960s. The decadal oscilla-tion in trends over Southeast and southern Asia, Aus-tralia, and the Amazon indicates a consistency overmost of the tropics, which mirrors the variation at theglobal scale as well. Over the Americas, all regions (ex-cept the Amazon) end the period with decreasingtrends, although there is considerable variability previ-ously in some regions (e.g., central North America). Ofparticular note are the large trends in Alaska andnorthern Canada in the last 10–20 yr that are concur-rent with increasing temperatures (not shown).

These results indicate a switch to drying trends insoil moisture in many regions and more generally atglobal scales, despite a long-term wetting trend. Al-though there is considerable variability over the wholeperiod, we hypothesize that this is caused in part bywarming temperatures that act to increase evapotrans-piration and/or early snowmelt and therefore the oc-currence of drought. This is despite the possibility ofconcurrent increases in precipitation, although this isunlikely in some regions because of the anticorrelationof precipitation and temperature (Déry and Wood2005b). We explore the relationship between soil mois-ture/drought and precipitation and temperature vari-ability next and then address the impact of warmingtrends.

5. Relationships with meteorological forcings

a. Relationship with precipitation and temperaturevariability

Drought is driven primarily by lack of precipitation,but this is accentuated or diminished by associatedchanges in temperature and other meteorological pro-cesses. Anomalously high temperatures will tend to in-crease evapotranspiration, while low precipitation willobviously reduce recharge of the soil column. Theseprocesses may interact in complex and nonlinear wayssuch that drought can, for example, be induced by manymonths of below-normal rainfall, be prolonged by hightemperatures, and then be alleviated by a single storm.These relationships may also have implications for theoccurrence of drought under future climates that arelikely to be warmer but with associated changes in pre-cipitation that are regionally dependent and may showincrease or decreases. Drought development may alsolag anomalies in precipitation and other meteorologicalforcings, but this relationship is not well understood.For example, months of anomalously low precipitationmay not result in drought conditions until some timelater. A subsequent return to normal conditions maysimilarly be delayed as moisture takes time to filterthrough the hydrologic system and replenish depletedstores. These processes are complicated by seasonalvariations where precipitation may dominate in coolseasons and be modified in warm seasons by tempera-ture effects.

Figure 11 shows scatterplots of the trends in precipi-tation and temperature stratified by trends in soil mois-ture quantile for several regions chosen to represent adiversity of climates. Wetting (drying) trends that aresignificant at the 0.05 level in soil moisture are associ-ated with positive (negative) trends in precipitation inall regions. Of note is the small spread in the distribu-tion of precipitation trends and clear delineation be-tween wetting and drying soil moisture trends in high-latitude regions (ALA and NAS). Tropical and South-ern Hemisphere regions (e.g., AMZ, SAF, SAS) showlarger spread in precipitation trends and some overlapin the range of positive soil moisture trends with nega-tive precipitation trends. The relationship between soilmoisture and temperature is somewhat unclear, how-ever (in part, because decreasing temperature trendsare uncommon). As significant trends in soil moisture(wetting and drying) are generally associated with posi-tive temperature trends, indicating that increasing tem-peratures do not necessarily hinder increasing soilmoisture, and, conversely, that they may enhance de-creasing soil moisture.


FIG. 10. Trends in regional average soil moisture for a 21-yr moving window. The x axis indicates the middle dateover which the trend is calculated. Trends that are significant at the 0.05 level are shaded in darker colors. Positive(negative) trend values are shaded in warm (cool) colors. The values for “world” have been multiplied by 3 for easeof visualization.


Fig 10 live 4/C

At seasonal scales, the relationship between soilmoisture, precipitation, and temperature is more com-plex, especially for cooler regions where snowpackstorage and seasonally frozen soil water play an im-portant role. As an example, the results for the NASregion (Fig. 12) show very different relationships be-tween trends in soil moisture and those in the forcingvariables. During summer (JJA) and autumn (SON),drying (wetting) soil moisture trends are generallyassociated with decreasing (increasing) precipita-tion. However, in the cooler months (DJF and MAM)this distinction is not apparent and the sign of trendsin soil moisture is independent of the sign of the pre-cipitation trend. Springtime soil moisture is domi-nated by snowmelt, which, although driven in part byspringtime temperatures and precipitation, is a functionof the snowpack accumulated over the precedingwinter. As a comparison, humid regions such as theAmazon (not shown) show little seasonal variability inthe precipitation–temperature–soil moisture relation-ships.

b. Sensitivity of drought to temperature trends

To further investigate the impact of temperatureon soil moisture and drought trends we compare theresults of the TANN and the TCLIM simulations. Fig-ure 13 shows the difference between the two simula-tions in terms of mean soil moisture and trends in soilmoisture, and indicates where changes are attributableto trends in temperature. Regions of maximum differ-ences in mean soil moisture tend to occur in the North-ern Hemisphere, in mid–high latitudes, with TANNdriving increases in soil moisture in eastern Europe,northern Eurasia, southern Alaska, and southeasternCanada, and decreases in the eastern United States,Pacific Northwest, eastern Canada, and small parts ofcentral Europe, central Asia, and eastern Siberia. Glob-ally, the tendency is for equal areas of increases anddecreases in the Northern Hemisphere and a ratio of3:2 in favor of increases in the Southern Hemisphere.The differences in trends between the two simulationsare small (of the order of 0.002% yr�1 or less), although

FIG. 11. Scatterplot of trends in precipitation and surface air temperature, stratified by trends in soil moisturefor selected regions. Blue (red) symbols represent positive (negative), significant trends in soil moisture at the0.05 level.


Fig 11 live 4/C

this is the trend over the full 50 yr (0.1% 50 yr�1). Thelargest differences are found in high northern latitudes,with increased trend magnitude for TCLIM over north-ern Canada and northern Europe and decreased trendmagnitude for the area from eastern Europe throughcentral Siberia. Eastern Siberia also shows decreasedmagnitudes. Elsewhere, the northern half of the Andesshows lower magnitudes in Peru and higher magnitudesin Columbia.

In Fig. 14, the differences between the two simula-tions are shown for 11-yr moving averages in trends inregional mean soil moisture quantile. For the majorityof regions the differences are generally less than 1%yr�1. However, outstanding are a few regions with dif-ferences up to 6% yr�1 (ALA, NEC) and 2%–3% yr�1

(NEU, NAS). Note that these are differences in trendsover 11-yr windows and will generally be much higherthan the 50-yr trends. Of particular interest are thelarge differences in regions ALA and NEC during thelast 20 yr of the record that indicate that decreasing soilmoisture is exaggerated by the increasing trend in air

temperature. The temperature trend is particularly pro-nounced during 1990–2000 (not shown). Similar behav-ior in the latter years of the record exists for otherregions, such as EAS, WNA, ENA, and SSA, but themagnitude of the differences are considerably smaller.Even at the global scale a difference is noticeable in thelast 20 yr. Despite some long term variability over thefull period in most regions, the evidence points towarda temperature effect in recent years that tends to exag-gerate or force decreasing trends in soil moisture.

6. Discussion and conclusions

a. Uncertainties in the meteorological forcings andhydrologic modeling

The trends discussed are only as robust as the me-teorological data that forces the simulation and the landsurface model that is used to derive the soil moisturedata. It has been shown that modeled land surface hy-drology is sensitive to the forcing dataset that drives it,and especially precipitation (Ngo-Duc et al. 2005;

FIG. 12. Scatterplot of seasonal trends in precipitation and surface air temperature, stratified by trends in soilmoisture for the NAS region. Blue (red) symbols represent positive (negative), significant trends in soil moistureat the 0.05 level.


Fig 12 live 4/C

FIG. 13. Comparison of soil moisture between the original simulation with annually varying air temperature forcing (TANN) and thatwith time invariant or climatological air temperature (TCLIM). (top) Difference in mean soil moisture, 1950–2000. (bottom) Differencein soil moisture trend, 1950–2000.


Fig 13 live 4/C

FIG. 14. Difference in 11-yr moving window trends in soil moisture quantile between the TANN and TCLIM simulations. The TANNsimulation was forced with annually varying surface air temperature. The TCLIM simulation was forced with climatological surface airtemperature.


Fekete et al. 2004; Berg et al. 2003; Sheffield et al.2004b; Guo et al. 2006). Fekete et al. (2004) showedthat the uncertainty in precipitation datasets was of theorder of interannual variability, and that the impact ofprecipitation uncertainties on the terrestrial water bud-get was of at least the same magnitude, especially insemiarid regions where the hydrologic response ishighly nonlinear. In the second Global Soil WetnessProject (GSWP-2) multimodel comparison, Guo et al.(2006) found that uncertainties in the forcings were aslarge as differences between land surface models. Thefirst-order drivers of drought, monthly precipitation,and temperature are derived in this study from the Cli-matic Research Unit (CRU) TS2.0 gauge-based dataset(Mitchell and Jones 2005). For time periods when sta-tion observations are limited or nonexistent the CRUdataset relies on climatological values, or so-called re-laxation to climatology (Mitchell and Jones 2005). Ad-ditionally, the gauge density that contributes to a gridcell may force errors in the simulated hydrology fordensities of the order of less than 30 gauges per 106 km2

(Oki et al. 1999).It is therefore likely that errors in the forcing dataset

used here will result in errors in the representation ofdrought, and that the reliability of the time series at thegrid scale (1.0°) may be reduced (Patz et al. 2002), al-though this can be alleviated through spatial and tem-poral averaging (Giorgi 2002). Nevertheless, at largerscales, and especially in data-poor regions, we arguethat this is our best estimate. In data-rich regions, suchas the United States and Europe, our estimates maycompare less favorably against that obtained when us-ing data from dense station networks. For example, De-charme and Douville (2006) showed that the GSWP-2forcing dataset drastically overestimated precipitationcompared to data from a dense network in France withresulting impacts on modeled river discharge, and thatthis overestimation was systematic globally. However,comparisons of drought characteristics derived fromthe dataset in this paper and datasets based on higherspatial resolution modeling forced with gauge-basedobservations (Sheffield et al. 2004a; Andreadis et al.2005; Andreadis and Lettenmaier 2006) are encourag-ing (section 2b). Furthermore, biases in the modeling ofthe land surface budgets, through simplifications in themodeling and uncertainties in the parameter data, mayresult in errors in the trends (Sheffield et al. 2004a).These biases are generally unquantifiable but most im-portantly are systematic and therefore uniform overtime. Therefore it is likely they will not impact the signor strength of the calculated trends appreciably. Wesimilarly argue that comparable results would be ob-

tained if we used a different model. Intercomparison ofland surface models driven by the same forcings hasbeen carried out regionally (Wood et al. 1998; Mitchellet al. 2004) and globally (Guo and Dirmeyer 2006) andhave concluded that although the models do poorly atreproducing the absolute values of observed soil mois-ture they do reasonably well at mimicking the anoma-lies and interannual variability. They may, therefore,provide useful information on drought occurrence andtrends when viewed with respect to their own clima-tologies.

The PDSI can be considered as another type ofmodel but designed specifically to monitor drought (al-though much simpler in its treatment of physical pro-cesses when compared to hydrologic land surface mod-els) and has been used to assess trends in globaldrought previously (Dai et al. 2004; Burke et al. 2006).Burke et al. (2006) looked at trends in PDSI over thesecond half of the twentieth century as calculated fromi) the observation-driven PDSI dataset of Dai et al.(2004) and ii) a PDSI dataset driven by precipitationand temperature from coupled and uncoupled runs ofthe Hadley climate model. They found that the twodatasets show a global drying trend of between �0.2and �0.3 decade�1 in PDSI units. This is at odds withthe results of this paper, which show a small wettingtrend globally, although the pattern of regional trendsis similar (cf. Fig. 1 with their Fig. 3). The difference ismainly because of the larger drying trend in the PDSIdatasets for the last 20 yr as shown by Burke et al.(2006) and Sheffield and Wood (2007) and is systematicof the PDSI, whether driven by the Burke et al. (2006),the Dai et al. (2004), or the VIC forcings (Sheffield andWood 2007). This may be due to a number of differ-ences in the PDSI and VIC modeling approaches, suchas the model time step (PDSI is monthly; VIC is 3hourly), the sensitivity of the model to precipitationand temperature changes [e.g., the PDSI uses theThornthwaite method to calculate PE that may be bi-ased for higher temperatures (Burke et al. 2006)], andthe fundamental physical processes that are modeled(e.g., the PDSI does not include snow processes) andrequires further investigation.

There are also a number of nonmeteorologicalboundary conditions, such as land cover, that are as-sumed time invariant (although vegetation parameterssuch as leaf area index do vary seasonally) but mayactually have an appreciable impact on the trends. Forexample, anthropogenic factors—including irrigation,water withdrawals, and land use change—and naturalprocesses—such as vegetation dynamics and wildfire—are not modeled explicitly, and the impact of these may


vary in time also, thus affecting the trends. Estimates ofcurrent day irrigation are that 16.3% of cultivated re-gions are equipped for irrigation (Siebert et al. 2005),which can have a significant impact on the water cycle(Haddeland et al. 2007), although historically this mayhave been offset by changes in land use. Land cover haschanged dramatically over the past 300 yr (Ramankuttyand Foley 1999) and more so in tropical/developing re-gions over the twentieth century (Klein Goldewijk2001). The impact that this has had on the water cyclemay be substantial (Zhang and Schilling 2006; Scanlonet al. 2007), likely reducing evapotranspiration and in-creasing runoff with possible implications for the resultspresented here. Furthermore, elevated levels of CO2

and increased growing season length may be respon-sible for recent increases in net primary productivity(NPP) and thus transpiration (Friend et al. 2007), al-though stomatal closure response to elevated CO2 lev-els may have had the opposite effect (Gedney et al.2006).

b. Summary and conclusions

Global and regional trends in drought over the past50 yr are analyzed using a soil moisture–based droughtindex over global terrestrial areas, excluding Greenlandand Antarctica. Drought is described in terms of vari-ous statistics that summarize drought duration, inten-sity, and severity. Trends in soil moisture and droughtcharacteristics were calculated using a nonparametrictrend test on a grid cell basis and for regional averages.Despite some uncertainties in the forcings and the mod-eling process, we have confidence in the results as de-rived from a validated dataset, especially at largerscales and when put in context of other studies.

An overall increasing trend in global soil moisture,driven by increasing precipitation, underlies the wholeanalysis, which is reflected most obviously over thewestern hemisphere and especially in North America.Regional variation is nevertheless apparent and signifi-cant drying over West Africa, as driven by decreasingSahel precipitation, stands out. Elsewhere, Europe ap-pears to have not experienced significant changes in soilmoisture, a trait shared by Southeast and southernAsia. Trends in drought characteristics are predomi-nantly decreasing, but statistically significant changesare limited in areal extent, of the order of 1.0%–7.0%globally, depending on the drought threshold and vari-able and being generally less than 10% of continentalareas. Concurrent changes in drought spatial extent areevident, with a global decreasing trend of �0.021% to�0.035% yr�1. Regionally, drought extent over Africahas increased and is dominated by large increases over

West Africa. Northern and East Asia show positivetrends and central Asia and the Tibetan Plateau showdecreasing trends. In South Asia all trends are insignifi-cant. Drought extent over Australia has decreased.Over the Americas, trends are uniformly negative andmostly significant.

Within the long-term trends there are interannualand decadal variations in soil moisture and droughtcharacteristics that are apparent in many regions. Glob-ally, variations are driven mainly by ENSO variability,although the AMO appears to play an important roleglobally and in many regions, such as West and EastAfrica, central Asia, and the high latitudes of NorthAmerica. However, the short length of record relativeto the scale of the AMO precludes any definite conclu-sions. High correlation values are found between theMediterranean and the NAO, and Southeast Asia andthe Amazon basin and Niño-3.4 SSTs. Stronger connec-tion are likely at scales smaller than the regions exam-ined here and by using seasonal and lagged correla-tions. The decadal variations in soil moisture anddrought characteristics impact the robustness of thelong-term trends. In general, they are responsible fordiminishing the long-term trends. In fact, despite theoverall wetting trend, there is a switch in later years toa drying trend, globally and in many regions, which isconcurrent with increasing temperatures. Althoughdrought is driven primarily by variability in precipita-tion, temperature has an effect that appears to be ex-aggerated in the last decade or so especially in highnorthern latitudes. This is most pertinent within thecontext of potential continued temperature increasesduring the twenty-first century.

Future climate projections from coupled models pre-dict increases in global temperatures and generally in-creasing temperatures over land regions for most emis-sion scenarios (e.g., Giorgi and Bi 2005). The range inpredictions varies among scenarios but is generally in-creasing. If temperature is a secondary forcing ofdrought (precipitation being the primary forcing) inmost regions, then the implication is that droughts willincrease in the future, especially given the magnitude ofpredicted temperature increases. On the other hand,predicted changes in precipitation are highly variable inspace and are scenario dependent to the extent thatprecipitation is predicted to increase in some regionsand decrease in others (Giorgi and Bi 2005). Tempera-ture-driven changes in drought will be modified by thechanges to precipitation, although the fact that precipi-tation and temperature are anticorrelated in many re-gions (Trenberth and Shea 2005; Déry and Wood2005b) may lead to enhanced drought occurrence.


Acknowledgments. This work has been supported byNOAA Grants NA86GP0248 and NA0303AR4310001and NASA Grant NAG5-9486. We thank three anony-mous reviewers for their useful comments and sugges-tions.

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