Surface Observed Global Land Precipitation Variations ... · Annual and monthly mean values of continental freshwater discharge into the oceans are estimated at 18 ... based on observed

NOVEMBER 1997 J. Climate 2943 D A I E T A L .

q 1997 American Meteorological Society

Surface Observed Global Land Precipitation Variations during 1900–88

AIGUO DAI*Department of Applied Physics, Columbia University, New York, New York

INEZ Y. FUNG

School of Earth and Ocean Sciences, University of Victoria, Victoria, Canada, andNASA/Goddard Institute for Space Studies, New York, New York

ANTHONY D. DEL GENIO

NASA/Goddard Institute for Space Studies, New York, New York

(Manuscript received 9 July 1996, in fina form 11 October 1996)

ABSTRACT

The authors have analyzed global station data and created a gridded dataset of monthly precipitation for theperiod of 1900–88. Statistical analyses suggest that discontinuities associated with instrumental errors are largefor many high-latitude station records, although they are unlikely to be significan for the majority of the stations.The firs leading EOF in global precipitation field is an ENSO-related pattern, concentrating mostly in the lowlatitudes. The second leading EOF depicts a linear increasing trend (;2.4 mm decade21) in global precipitationfield during the period of 1900–88. Consistent with the zonal precipitation trends identifie in previous analyses,the EOF trend is seen as a long-term increase mostly in North America, mid- to high-latitude Eurasia, Argentina,and Australia. The spatial patterns of the trend EOF and the rate of increase are generally consistent with thoseof the precipitation changes in increasing CO2 GCM experiments.

The North Atlantic oscillation (NAO) accounts for ;10% of December–February precipitation variance overNorth Atlantic surrounding regions. The mode suggests that during high-NAO-index winters, precipitation isabove normal in northern (.508N) Europe, the eastern United States, northern Africa, and the Mediterranean,while below-normal precipitation occurs in southern Europe, eastern Canada, and western Greenland.

Wet and dry months of one standard deviation occur at probabilities close to those of a normal distributionin midlatitudes. In the subtropics, the mean interval between two extreme events is longer. The monthly wetand dry events seldom (probability , 5%) last longer than 2 months. ENSO is the single largest cause of globalextreme precipitation events. Consistent with the upward trend in global precipitation, globally, the averagedmean interval between two dry months increased by ;28% from 1900–44 to 1945–88. The percentage of wetareas over the United States has more than doubled (from ;12% to .24%) since the 1970s, while the percentageof dry areas has decreased by a similar amount since the 1940s. Severe droughts and flood comparable to the1988 drought and 1993 floo in the Midwest have occurred 2–9 times in each of several other regions of theworld during this century.

1. Introduction

Station rain gauge records have been used to estimatethe monthly climatology (e.g., Jaeger 1983; Shea 1986;Legates and Willmott 1990) and large-scale variationsof precipitation during this century (Bradley et al. 1987;Diaz et al. 1989; Vinnikov et al. 1990). These large-scale analyses of precipitation changes have revealed

* Current affiliation National Center for Atmospheric Research,Boulder, Colorado.

Corresponding author address: Dr. Aiguo Dai, NCAR, P.O. Box3000, Boulder, CO 80307.E-mail: [email protected]

that during the last 4–5 decades precipitation has in-creased over northern midlatitudes and most SouthernHemisphere land areas, but has decreased in northernlow-latitude land areas. However, these long-term pre-cipitation trends have been interpreted cautiously dueto the possible inhomogeneity and the limited spatialcoverage of the precipitation station data (Følland et al.1990, 1992).

It is well known that terrestrial rain gauge recordscontain various instrumental errors (Sevruk 1982; Leg-ates and Willmott 1990; Groisman et al. 1991; Groismanand Legates 1994). The errors may be grouped into twotypes: undercatch and inhomogeneity. The undercatcherror, which results from wind blowing, wall wetting,evaporation, and splashing, varies from less than 5% inthe Tropics to more than 50% near the poles in winter

adai

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VOLUME 12 AUGUST 1999J O U R N A L O F C L I M A T E

q 1999 American Meteorological Society 2451

Effects of Clouds, Soil Moisture, Precipitation, and Water Vapor on DiurnalTemperature Range

AIGUO DAI AND KEVIN E. TRENBERTH

National Center for Atmospheric Research,* Boulder, Colorado

THOMAS R. KARL

NOAA/National Climatic Data Center, Asheville, North Carolina

(Manuscript received 9 July 1998, in fina form 9 September 1998)

ABSTRACT

The diurnal range of surface air temperature (DTR) has decreased worldwide during the last 4–5 decades andchanges in cloud cover are often cited as one of the likely causes. To determine how clouds and moisture affectDTR physically on daily bases, the authors analyze the 30-min averaged data of surface meteorological variablesand energy fluxe from the the First International Satellite Land Surface Climatology Project Field Experimentand the synoptic weather reports of 1980–1991 from about 6500 stations worldwide. The statistical relationshipsare also examined more thoroughly in the historical monthly records of DTR, cloud cover, precipitation, andstreamflo of this century.

It is found that clouds, combined with secondary damping effects from soil moisture and precipitation, canreduce DTR by 25%–50% compared with clear-sky days over most land areas; while atmospheric water vaporincreases both nighttime and daytime temperatures and has small effects on DTR. Clouds, which largely determinethe geographic patterns of DTR, greatly reduce DTR by sharply decreasing surface solar radiation while soilmoisture decreases DTR by increasing daytime surface evaporative cooling. Clouds with low bases are mostefficien in reducing the daytime maximum temperature and DTR mainly because they are very effective inreflectin the sunlight, while middle and high clouds have only moderate damping effects on DTR. The DTRreduction by clouds is largest in warm and dry seasons such as autumn over northern midlatitudes when latentheat release is limited by the soil moisture content. The net effects of clouds on the nighttime minimumtemperature is small except in the winter high latitudes where the greenhouse warming effect of clouds exceedstheir solar cooling effect.

The historical records of DTR of the twentieth century covary inversely with cloud cover and precipitationon interannual to multidecadal timescales over the United States, Australia, midlatitude Canada, and formerU.S.S.R., and up to 80% of the DTR variance can be explained by the cloud and precipitation records. Giventhe strong damping effect of clouds on the daytime maximum temperature and DTR, the well-establishedworldwide asymmetric trends of the daytime and nighttime temperatures and the DTR decreases during the last4–5 decades are consistent with the reported increasing trends in cloud cover and precipitation over many landareas and support the notion that the hydrologic cycle has intensified

1. Introduction

The diurnal range of surface air temperature (DTR)has decreased since the 1950s worldwide (especiallyover the Northern Hemisphere land areas) mainly butnot always due to an increase in nighttime minimumtemperature (Tmin) that exceeds the increase in daytimemaximum temperature (Tmax) (Karl et al. 1993; Horton

* The National Center for Atmospheric Research is sponsored bythe National Science Foundation.

Corresponding author address: Dr. A. Dai, NCAR, P.O. Box 3000,Boulder, CO 80307.E-mail: [email protected]

1995; Houghton et al. 1996; Easterling et al. 1997).Coincident increases in total cloud cover have beenfound in a number of locations (Henderson-Sellers1992; Dessens and Bucher 1995; Kaas and Frich 1995;Jones 1995) and are often cited as a likely cause for theobserved DTR decrease (Kukla and Karl 1993; Karl etal. 1993; Karl et al. 1996; Dai et al. 1997a). Annualand seasonal DTR are strongly correlated with cloudcover over the contiguous United States with the highestcorrelation in autumn (Plantico and Karl 1990; Karl etal. 1993). A jump in cloud cover was found to concurwith a large decrease in DTR over the former U.S.S.R.(Karl et al. 1996). Strong correlation between annualDTR and cloud cover/precipitation also exists over othercontinents where data are available (Dai et al. 1997a).

Clouds can reduce Tmax by reflectin the sunlight and

15 FEBRUARY 2001 J. Climate 485D A I E T A L .


Climates of the Twentieth and Twenty-First Centuries Simulated by theNCAR Climate System Model

AIGUO DAI, T. M. L. WIGLEY, B. A. BOVILLE, J. T. KIEHL, AND L. E. BUJA


(Manuscript received 3 November 1999, in fina form 24 March 2000)

ABSTRACT

The Climate System Model, a coupled global climate model without ‘‘flu adjustments’’ recently developedat the National Center for Atmospheric Research, was used to simulate the twentieth-century climate usinghistorical greenhouse gas and sulfate aerosol forcing. This simulation was extended through the twenty-firscentury under two newly developed scenarios, a business-as-usual case (ACACIA-BAU, CO2 ø 710 ppmv in2100) and a CO2 stabilization case (STA550, CO2 ø 540 ppmv in 2100). Here we compare the simulated andobserved twentieth-century climate, and then describe the simulated climates for the twenty-firs century. Themodel simulates the spatial and temporal variations of the twentieth-century climate reasonably well. Theseinclude the rapid rise in global and zonal mean surface temperatures since the late 1970s, the precipitationincreases over northern mid- and high-latitude land areas, ENSO-induced precipitation anomalies, and Pole–midlatitude oscillations (such as the North Atlantic oscillation) in sea level pressure fields The model has acold bias (28–68C) in surface air temperature over land, overestimates of cloudiness (by 10%–30%) over land,and underestimates of marine stratus clouds to the west of North and South America and Africa.

The projected global surface warming from the 1990s to the 2090s is ;1.98C under the BAU scenario and;1.58C under the STA550 scenario. In both cases, the midstratosphere cools due to the increase in CO 2, whereasthe lower stratosphere warms in response to recovery of the ozone layer. As in other coupled models, the surfacewarming is largest at winter high latitudes ($5.08C from the 1990s to the 2090s) and smallest (;1.08C) overthe southern oceans, and is larger over land areas than ocean areas. Globally averaged precipitation increasesby ;3.5% (3.0%) from the 1990s to the 2090s in the BAU (STA550) case. In the BAU case, large precipitationincreases (up to 50%) occur over northern mid- and high latitudes and over India and the Arabian Peninsula.Marked differences occur between the BAU and STA550 regional precipitation changes resulting from inter-decadal variability. Surface evaporation increases at all latitudes except for 608–908S. Water vapor from increasedtropical evaporation is transported into mid- and high latitudes and returned to the surface through increasedprecipitation there. Changes in soil moisture content are small (within 63%). Total cloud cover changes little,although there is an upward shift of midlevel clouds. Surface diurnal temperature range decreases by about 0.28–0.58C over most land areas. The 2–8-day synoptic storm activity decreases (by up to 10%) at low latitudes andover midlatitude oceans, but increases over Eurasia and Canada. The cores of subtropical jets move slightly up-and equatorward. Associated with reduced latitudinal temperature gradients over mid- and high latitudes, thewintertime Ferrel cell weakens (by 10%–15%). The Hadley circulation also weakens (by ;10%), partly due tothe upward shift of cloudiness that produces enhanced warming in the upper troposphere.

1. Introduction

The earth’s climate system (the atmosphere, ocean,biosphere, etc.) has been altered by human activities(e.g., fossil fuel combustion and deforestation) in manyways. One of the consequences is a sharp rise in at-mospheric concentrations of greenhouse gases (CO2,CH4, etc.) and aerosols since the late-nineteenth century


Corresponding author address: Aiguo Dai, National Center forAtmospheric Research, P.O. Box 3000, Boulder, CO 80307-3000.E-mail: [email protected]

(Watson et al. 1990; Schimel et al. 1996). A large num-ber of climate model experiments predict substantialclimate changes (including surface warming) in re-sponse to increased concentrations of CO2 and othergreenhouse gases (e.g., Mitchell et al. 1990; Kattenberget al. 1996). Because the atmospheric loading of green-house gases is likely to rise in the twenty-firs centuryas a result of the expected growth in the world economyand population, meaningful predictions of climatechanges in the next century have many practical appli-cations (e.g., for impact assessments and to guide futureemission controls).

Reliable predictions of future climates are, however,still a big challenge for climate researchers. They requirea) comprehensive models of the earth’s climate systemthat include all of its major components and the inter-

1112 VOLUME 14J O U R N A L O F C L I M A T E 2 0 0 1

Global Precipitation and Thunderstorm Frequencies.Part II: Diurnal Variations

AIGUO DAI


(Manuscript received 24 January 2000, in fina form 8 May 2000)

ABSTRACT

Three-hourly present weather reports from ;15 000 stations around the globe and from the ComprehensiveOcean–Atmosphere Data Set from 1975 to 1997 were analyzed for diurnal variations in the frequency ofoccurrence for various types of precipitation (drizzle, nondrizzle, showery, nonshowery, and snow) and thun-derstorms. Significan diurnal variations with amplitudes exceeding 20% of the daily mean are found over muchof the globe, especially over land areas and during summer. Drizzle and nonshowery precipitation occur mostfrequently in the morning around 0600 local solar time (LST) over most land areas and from midnight to 0400LST over many oceanic areas. Showery precipitation and thunderstorms occur much more frequently in the lateafternoon than other times over most land areas in all seasons, with a diurnal amplitude exceeding 50% of thedaily mean frequencies. Over the North Pacific the North Atlantic, and many other oceanic areas adjacent tocontinents, showery precipitation is most frequent in the morning around 0600 LST, which is out of phase withland areas. Over the tropical and southern oceans, showery precipitation tends to peak from midnight to 0400LST. Maritime thunderstorms occur most frequently around midnight. It is suggested that the diurnal variationsin atmospheric relative humidity contribute to the morning maximum in the frequency of occurrence for drizzleand nonshowery precipitation, especially over land areas. Solar heating on the ground produces a late-afternoonmaximum of convective available potential energy in the atmosphere that favors late-afternoon moist convectionand showery precipitation over land areas during summer. This strong continental diurnal cycle induces a diurnalcycle of opposite phase in low-level convergence over large nearby oceanic areas that favors a morning maximumof maritime showery precipitation. Larger low-level convergence induced by pressure tides and higher relativehumidity at night than at other times may contribute to the nighttime maximum of maritime showery andnonshowery precipitation over remote oceans far away from continents.

1. Introduction

Documentation of the diurnal variability of precipi-tation over various regions has been a topic of hundredsof published articles. Studies before 1975 have beensummarized by Wallace (1975). Dai et al. (1999a) sum-marized more recent analyses for the United States (e.g.,Schwartz and Bosart 1979; Balling 1985; Easterling andRobinson 1985; Englehart and Douglas 1985; Riley etal. 1987; Landin and Bosart 1989; Tucker 1993; Higginset al. 1996). There are also more recent studies for thecoastal and island regions in eastern Asia (Hu and Hong1989; Oki and Musiake 1994; Lim and Kwon 1998),tropical America (Kousky 1980), East Africa (Majugu1986), and the Sahel (Shinoda et al. 1999). The resultsof these studies, which are based on station records, canbe summarized as follows: 1) summer precipitation and


Corresponding author address: A. Dai, National Center for At-mospheric Research, P.O. Box 3000, Boulder, CO 80307-3000.E-mail: [email protected]

thunderstorms over inland regions tend to be more fre-quent during the afternoons while the maximum rainfallis at night or during early morning over the coastal andsmall-island areas. 2) There are, however, exceptions tothis general tendency. For example, summer precipita-tion is most frequent from middle night to early morningover the central United States and around 1400–1600local solar time (LST) over the entire Florida Peninsula(Wallace 1975; Dai et al. 1999a). 3) During the otherseasons, precipitation has a much weaker diurnal cyclethan in summer, with a morning maximum in winterover many land areas (Dai et al. 1999a). 4) Precipitationintensity generally has much smaller diurnal variationsthan precipitation frequency (Oki and Musiake 1994;Dai et al. 1999a). 5) Although a single large peak is adominant feature in most station rain gauge records,there is a secondary peak or a weak semidiurnal (12-h)cycle of rainfall at many tropical (peak around 0300LST) and midlatitude (peak around 0600 LST) stations(Hamilton 1981a,b; Oki and Musiake 1994).

Over the open oceans, in situ observations of precip-itation are sparse. Kraus (1963) analyzed weather re-ports from nine fixe weather-ships in the northern (308–

660 VOLUME 3J O U R N A L O F H Y D R O M E T E O R O L O G Y 2 0 0 2


Estimates of Freshwater Discharge from Continents: Latitudinal andSeasonal Variations



(Manuscript received 22 March 2002, in fina form 12 July 2002)

ABSTRACT

Annual and monthly mean values of continental freshwater discharge into the oceans are estimated at 18resolution using several methods. The most accurate estimate is based on streamflo data from the world’slargest 921 rivers, supplemented with estimates of discharge from unmonitored areas based on the ratios ofrunoff and drainage area between the unmonitored and monitored regions. Simulations using a river transportmodel (RTM) forced by a runoff fiel were used to derive the river mouth outflo from the farthest downstreamgauge records. Separate estimates are also made using RTM simulations forced by three different runoff fields1) based on observed streamflo and a water balance model, and from estimates of precipitation P minusevaporation E computed as residuals from the atmospheric moisture budget using atmospheric reanalyses from2) the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR)and 3) the European Centre for Medium-Range Weather Forecasts (ECMWF). Compared with previous estimates,improvements are made in extending observed discharge downstream to the river mouth, in accounting for theunmonitored streamflo , in discharging runoff at correct locations, and in providing an annual cycle of continentaldischarge. The use of river mouth outflo increases the global continental discharge by ;19% compared withunadjusted streamflo from the farthest downstream stations. The river-based estimate of global continentaldischarge presented here is 37 288 6 662 km3 yr21, which is ;7.6% of global P or 35% of terrestrial P. Whilethis number is comparable to earlier estimates, its partitioning into individual oceans and its latitudinal distributiondiffer from earlier studies. The peak discharges into the Arctic, the Pacific and global oceans occur in June,versus May for the Atlantic and August for the Indian Oceans. Snow accumulation and melt are shown to havelarge effects on the annual cycle of discharge into all ocean basins except for the Indian Ocean and the Med-iterranean and Black Seas. The discharge and its latitudinal distribution implied by the observation-based runoffand the ECMWF reanalysis-based P–E agree well with the river-based estimates, whereas the discharge impliedby the NCEP–NCAR reanalysis-based P–E has a negative bias.

1. Introduction

In a steady state, precipitation P exceeds evaporationE (or evapotranspiration) over land and the residual wa-ter runs off and results in a continental freshwater dis-charge into the oceans. Within the oceans, surface netfreshwater fluxe into the atmosphere are balanced bythis discharge from land along with transports withinthe oceans. The excess of E over P over the oceansresults in atmospheric moisture that is transported ontoland and precipitated out, thereby completing the land–ocean water cycle. While E and P vary spatially, thereturn of terrestrial runoff into the oceans is mostly con-centrated at the mouths of the world’s major rivers, thusproviding significan freshwater inflo locally and


Corresponding author address: A. Dai, National Center for At-mospheric Research, P.O. Box 3000, Boulder, CO 80307.E-mail: [email protected]

thereby forcing the oceans regionally through changesin density (Carton 1991; Nakamura 1996).

To study the freshwater budgets within the oceans,therefore, estimates of continental freshwater dischargeinto the ocean basins at each latitude are needed. Baum-gartner and Reichel (1975, BR75 hereafter) derivedglobal maps of annual runoff and made estimates ofannual freshwater discharge largely based on streamflodata from the early 1960s analyzed by Marcinek (1964).Despite various limitations of the BR75 discharge data(e.g., rather limited station coverage, areal integrationover 58 latitude zones, no seasonal values), these esti-mates are still widely used in evaluations of ocean andclimate models (Pardaens et al. 2002) and in estimatingoceanic freshwater transport (Wijffels et al. 1992; Wijff-els 2001), mainly because there have been few updatedglobal estimates of continental discharge. The primarypurpose of this study is to remedy this situation.

Correct simulations of the world river system and itsrouting of terrestrial runoff into the oceans has alsobecome increasingly important in global climate system

DECEMBER 2004 J. Hydrometeorology 1117D A I E T A L .


A Global Dataset of Palmer Drought Severity Index for 1870–2002: Relationship withSoil Moisture and Effects of Surface Warming

AIGUO DAI, KEVIN E. TRENBERTH, AND TAOTAO QIAN


(Manuscript received 24 February 2004, in fina form 26 May 2004)

ABSTRACT

A monthly dataset of Palmer Drought Severity Index (PDSI) from 1870 to 2002 is derived using historicalprecipitation and temperature data for global land areas on a 2.58 grid. Over Illinois, Mongolia, and parts ofChina and the former Soviet Union, where soil moisture data are available, the PDSI is significantl correlated(r 5 0.5 to 0.7) with observed soil moisture content within the top 1-m depth during warm-season months. Thestrongest correlation is in late summer and autumn, and the weakest correlation is in spring, when snowmeltplays an important role. Basin-averaged annual PDSI covary closely (r 5 0.6 to 0.8) with streamflo for sevenof world’s largest rivers and several smaller rivers examined. The results suggest that the PDSI is a good proxyof both surface moisture conditions and streamflo . An empirical orthogonal function (EOF) analysis of thePDSI reveals a fairly linear trend resulting from trends in precipitation and surface temperature and an El Nino–Southern Oscillation (ENSO)-induced mode of mostly interannual variations as the two leading patterns. Theglobal very dry areas, define as PDSI , 23.0, have more than doubled since the 1970s, with a large jump inthe early 1980s due to an ENSO-induced precipitation decrease and a subsequent expansion primarily due tosurface warming, while global very wet areas (PDSI . 13.0) declined slightly during the 1980s. Together, theglobal land areas in either very dry or very wet conditions have increased from ;20% to 38% since 1972, withsurface warming as the primary cause after the mid-1980s. These results provide observational evidence for theincreasing risk of droughts as anthropogenic global warming progresses and produces both increased temperaturesand increased drying.

1. Introduction

Droughts and flood are extreme climate events thatpercentage-wise are likely to change more rapidly thanthe mean climate (Trenberth et al. 2003). Because theyare among the world’s costliest natural disasters andaffect a very large number of people each year (Wilhite2000), it is important to monitor them and understandand perhaps predict their variability. The potential forlarge increases in these extreme climate events underglobal warming is of particular concern (Trenberth etal. 2004). However, the precise quantificatio ofdroughts and wet spells is difficul because there aremany different definition for these extreme events (e.g.,meteorological, hydrological, and agricultural droughts;see Wilhite 2000 and Keyantash and Dracup 2002) andthe criteria for determining the start and end of a droughtor wet spell also vary. Furthermore, historical recordsof direct measurements of the dryness and wetness of



the ground, such as soil moisture content (Robock et al.2000), are sparse. In order to monitor droughts and wetspells and to study their variability, numerous special-ized indices have been devised using readily availabledata such as precipitation and temperature (Heim 2000;Keyantash and Dracup 2002).

The Palmer Drought Severity Index (PDSI) is themost prominent index of meteorological drought usedin the United States (Heim 2002). The PDSI was createdby Palmer (1965) with the intent to measure the cu-mulative departure (relative to local mean conditions)in atmospheric moisture supply and demand at the sur-face. It incorporates antecedent precipitation, moisturesupply, and moisture demand [based on the classic workof Thornthwaite (1948)] into a hydrological accountingsystem. Palmer used a two-layer bucket-type model forsoil moisture computations and made certain assump-tions relating to fiel water-holding capacity and transferof moisture to and from the layers based on limited datafrom the central United States (Palmer 1965; Heim2002). The Palmer model also computes, as an inter-mediate term in the computation of the PDSI, the Palmermoisture anomaly index (Z index), which is a measureof surface moisture anomaly for the current month with-out the consideration of the antecedent conditions that

930 VOLUME 17J O U R N A L O F C L I M A T E


The Diurnal Cycle and Its Depiction in the Community Climate System Model



(Manuscript received 29 May 2003, in fina form 26 August 2003)

ABSTRACT

To evaluate the performance of version 2 of the Community Climate System Model (CCSM2) in simulatingthe diurnal cycle and to diagnose the deficiencie in underlying model physics, 10 years of 3-hourly data froma CCSM2 control run are analyzed for global and large-scale features of diurnal variations in surface airtemperature, surface pressure, upper-air winds, cloud amount, and precipitation. The model-simulated diurnalvariations are compared with available observations, most of which were derived from 3-hourly synoptic reportsand some new results are reported for surface air temperatures. The CCSM2 reproduces most of the large-scaletidal variations in surface pressure and upper-air winds, although it overestimates the diurnal pressure tide by20%–50% over low-latitude land and underestimates it over most oceans, the Rockies, and other midlatitudeland areas. The CCSM2 captures the diurnal amplitude (18–68C) and phase [peak at 1400–1600 local solar time(LST)] of surface air temperature over land, but over ocean the amplitude is too small (#0.28C). The CCSM2overestimates the mean total cloud amount by 10%–20% of the sky from ;158S to 158N during both December–January–February (DJF) and June–July–August (JJA) and over northern mid- and high-latitude land areas inDJF, whereas it underestimates the cloud amount by 10%–30% in the subtropics and parts of the midlatitudes.Over the marine stratocumulus regions west to the continents, the diagnostic cloud scheme in the CCSM2underestimates the mean stratocumulus amount by 10%–30% and does not simulate the observed large diurnalvariations (;3%–10%) in the marine stratocumulus clouds even when driven by observational data. In theCCSM2, warm-season daytime moist convection over land starts prematurely around 0800 LST, about 4 hourstoo early compared with observations, and plateaus from 1100 to 1800 LST, in contrast to a sharp peak around1600–1700 LST in observations. The premature initiation of convection prevents convective available potentialenergy (CAPE) from accumulating in the morning and early afternoon and intense convection from occurringin the mid to late afternoon. As a result of the extended duration of daytime convection over land, the CCSM2rains too frequently at reduced intensity despite the fairly realistic patterns of rainy days with precipitation .1mm day21. Furthermore, the convective versus nonconvective precipitation ratio is too high in the model asdeep convection removes atmospheric moisture prematurely. The simulated diurnal cycle of precipitation is tooweak over the oceans, especially for convective precipitation. These results suggest that substantial improvementsare desirable in the CCSM2 in simulating cloud amount, initiation of warm-season deep convection over land,and in the diurnal cycle in sea surface temperatures.

1. Introduction

Solar heating near the surface and in the atmospheregenerates strong diurnal (i.e., 24 h) and subdiurnal (e.g.,12-h semidiurnal) oscillations in surface and atmospher-ic temperature, pressure, and wind fields These regularoscillations, which are often referred to as atmospherictides (Chapman and Lindzen 1970; Dai and Wang 1999),are among the most pronounced signals of earth’s cli-mate and weather. Considerable diurnal variations, mod-ulated by synoptic weather events, are also found inmoist convection and cloudiness (e.g., Hendon and


Corresponding author address: Aiguo Dai, NCAR, P.O. Box 3000,Boulder, CO 80307.E-mail: [email protected]

Woodberry 1993; Rosendaal et al. 1995; Bergman andSalby 1996; Sui et al. 1997; Garreaud and Wallace 1997;Yang and Slingo 2001), precipitation (e.g., Wallace1975; Oki and Musiake 1994; Janowiak et al. 1994;Chang et al. 1995; Dai et al. 1999a; Dai 2001b; So-rooshian et al. 2002; Nesbitt and Zipser 2003), and at-mospheric water vapor (Dai et al. 2002). These diurnalvariations affect surface and atmospheric fluxe of en-ergy (Bergman and Salby 1997), water (Trenberth et al.2003), and momentum (Dai and Deser 1999). For ex-ample, because surface solar heating typically has asharp midday peak, precipitation that occurs during theday evaporates from the surface more rapidly than thatat night. This changes the fraction of rainfall involvedin runoff versus evaporation and the partitioning of sur-face energy into latent and sensible heat fluxes Climatemodels without a diurnal cycle cannot simulate thesenonlinear processes, resulting in degraded model sim-ulations (Wilson and Mitchell 1986).

Atlantic Thermohaline Circulation in a Coupled General Circulation Model: UnforcedVariations versus Forced Changes

AIGUO DAI, A. HU, G. A. MEEHL, W. M. WASHINGTON, AND W. G. STRAND


(Manuscript received 30 September 2004, in final form 10 March 2005)

ABSTRACT

A 1200-yr unforced control run and future climate change simulations using the Parallel Climate Model(PCM), a coupled atmosphere–ocean–land–sea ice global model with no flux adjustments and relativelyhigh resolution (�2.8° for the atmosphere and 2/3° for the oceans) are analyzed for changes in AtlanticOcean circulations. For the forced simulations, historical greenhouse gas and sulfate forcing of the twentiethcentury and projected forcing for the next two centuries are used. The Atlantic thermohaline circulation(THC) shows large multidecadal (15–40 yr) variations with mean-peak amplitudes of 1.5–3.0 Sv (1 Sv � 106

m3 s�1) and a sharp peak of power around a 24-yr period in the control run. Associated with the THCoscillations, there are large variations in North Atlantic Ocean heat transport, sea surface temperature(SST) and salinity (SSS), sea ice fraction, and net surface water and energy fluxes, which all lag thevariations in THC strength by 2–3 yr. However, the net effect of the SST and SSS variations on upper-oceandensity in the midlatitude North Atlantic leads the THC variations by about 6 yr, which results in the 24-yrperiod. The simulated SST and sea ice spatial patterns associated with the THC oscillations resemble thosein observed SST and sea ice concentrations that are associated with the North Atlantic Oscillation (NAO).The results suggest a dominant role of the advective mechanism and strong coupling between the THC andthe NAO, whose index also shows a sharp peak around the 24-yr time scale in the control run. In the forcedsimulations, the THC weakens by �12% in the twenty-first century and continues to weaken by anadditional �10% in the twenty-second century if CO2 keeps rising, but the THC stabilizes if CO2 levels off.The THC weakening results from stabilizing temperature increases that are larger in the upper and northernAtlantic Ocean than in the deep and southern parts of the basin. In both the control and forced simulations,as the THC gains (loses) strength and depth, the separated Gulf Stream (GS) moves southward (northward)while the subpolar gyre centered at the Labrador Sea contracts from (expands to) the east with the NorthAtlantic Current (NAC) being shifted westward (eastward). These horizontal circulation changes, which aredynamically linked to the THC changes, induce large temperature and salinity variations around the GS andNAC paths.

1. Introduction

Atlantic Ocean circulations, in particular the thermo-haline circulation (THC), have large impacts on re-gional and global climate (Rahmstorf 2002). Because ofthis, the natural variability of the THC and its potentialresponse to anthropogenic forcing have attracted con-siderable attention (e.g., Broecker 1987, 1997; Rahm-

storf 1999). Paleoceanographic records suggest that theTHC exhibited different modes during the last glacialcycle and its mode changes have been linked to abruptclimate changes over the North Atlantic region (Clarket al. 2002). Early ocean model studies suggest that theTHC may have multiple equilibrium states (Stommel1961; Bryan 1986). More recent studies show that theTHC may exhibit a hysteresis behavior in which it canhave two distinct states for a given value of the controlvariable (e.g., heat or freshwater flux; Stocker andWright 1991; Mikolajewicz and Maier-Reimer 1994;Rahmstorf 1995), which is a common feature of non-linear physical systems. A number of model studies onlow-frequency THC variability have focused on therelative role of thermal and haline forcing in driving thevariation (e.g., Marotzke and Willebrand 1991; Weaver

* The National Center for Atmospheric Research is sponsoredby the National Science Foundation.

Corresponding author address: Aiguo Dai, NCAR, P.O. Box3000, Boulder, CO 80307.E-mail: [email protected]

3270 J O U R N A L O F C L I M A T E VOLUME 18

© 2005 American Meteorological Society

JCLI3481

Recent Climatology, Variability, and Trends in Global Surface Humidity

AIGUO DAI


(Manuscript received 20 July 2005, in final form 22 November 2005)

ABSTRACT

In situ observations of surface air and dewpoint temperatures and air pressure from over 15 000 weatherstations and from ships are used to calculate surface specific (q) and relative (RH) humidity over the globe(60°S–75°N) from December 1975 to spring 2005. Seasonal and interannual variations and linear trends areanalyzed in relation to observed surface temperature (T) changes and simulated changes by a coupledclimate model [namely the Parallel Climate Model (PCM)] with realistic forcing. It is found that spatialpatterns of long-term mean q are largely controlled by climatological surface temperature, with the largestq of 17–19 g kg�1 in the Tropics and large seasonal variations over northern mid- and high-latitude land.Surface RH has relatively small spatial and interannual variations, with a mean value of 75%–80% overmost oceans in all seasons and 70%–80% over most land areas except for deserts and high terrain, whereRH is 30%–60%. Nighttime mean RH is 2%–15% higher than daytime RH over most land areas becauseof large diurnal temperature variations. The leading EOFs in both q and RH depict long-term trends,while the second EOF of q is related to the El Niño–Southern Oscillation (ENSO). During 1976–2004,global changes in surface RH are small (within 0.6% for absolute values), although decreasing trends of�0.11% � �0.22% decade�1 for global oceans are statistically significant. Large RH increases (0.5%–2.0%decade�1) occurred over the central and eastern United States, India, and western China, resulting fromlarge q increases coupled with moderate warming and increases in low clouds over these regions during1976–2004. Statistically very significant increasing trends are found in global and Northern Hemispheric qand T. From 1976 to 2004, annual q (T ) increased by 0.06 g kg�1 (0.16°C) decade�1 globally and 0.08 g kg�1

(0.20°C) decade�1 in the Northern Hemisphere, while the Southern Hemispheric q trend is positive butstatistically insignificant. Over land, the q and T trends are larger at night than during the day. The largestpercentage increases in surface q (�1.5% to 6.0% decade�1) occurred over Eurasia where large warming(�0.2° to 0.7°C decade�1) was observed. The q and T trends are found in all seasons over much of Eurasia(largest in boreal winter) and the Atlantic Ocean. Significant correlation between annual q and T is foundover most oceans (r � 0.6–0.9) and most of Eurasia (r � 0.4–0.8), whereas it is insignificant over subtropicalland areas. RH–T correlation is weak over most of the globe but is negative over many arid areas. The q–Tanomaly relationship is approximately linear so that surface q over the globe, global land, and oceanincreases by �4.9%, 4.3%, and 5.7% per 1°C warming, respectively, values that are close to those suggestedby the Clausius–Clapeyron equation with a constant RH. The recent q and T trends and the q–T relation-ship are broadly captured by the PCM; however, the model overestimates volcanic cooling and the trendsin the Southern Hemisphere.

1. Introduction

Atmospheric water vapor provides the single largestgreenhouse effect on the earth’s climate. All climate

models predict increased atmospheric content of watervapor with small changes in relative humidity as theglobal-mean surface temperature rises in response toincreased CO2 and other greenhouse gases (Cubasch etal. 2001; Dai et al. 2001). The increased water vaporprovides the single largest positive feedback on surfacetemperature (Hansen et al. 1984) and is the main causeof increased precipitation at mid- and high latitudes inthe model simulations. It is therefore vital to monitorchanges in atmospheric water vapor content not onlyfor detecting global warming but also for validating thelarge water vapor feedback seen in climate models.



1 AUGUST 2006 D A I 3589


JCLI3816

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J. Climate

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Precipitation Characteristics in Eighteen Coupled Climate Models

AIGUO DAI


(Manuscript received 9 June 2005, in final form 21 December 2005)

ABSTRACT

Monthly and 3-hourly precipitation data from twentieth-century climate simulations by the newest gen-eration of 18 coupled climate system models are analyzed and compared with available observations. Thecharacteristics examined include the mean spatial patterns, intraseasonal-to-interannual and ENSO-relatedvariability, convective versus stratiform precipitation ratio, precipitation frequency and intensity for differ-ent precipitation categories, and diurnal cycle. Although most models reproduce the observed broad pat-terns of precipitation amount and year-to-year variability, models without flux corrections still show anunrealistic double-ITCZ pattern over the tropical Pacific, whereas the flux-corrected models, especially theMeteorological Research Institute (MRI) Coupled Global Climate Model (CGCM; version 2.3.2a), producerealistic rainfall patterns at low latitudes. As in previous generations of coupled models, the rainfall doubleITCZs are related to westward expansion of the cold tongue of sea surface temperature (SST) that isobserved only over the equatorial eastern Pacific but extends to the central Pacific in the models. Thepartitioning of the total variance of precipitation among intraseasonal, seasonal, and longer time scales isgenerally reproduced by the models, except over the western Pacific where the models fail to capture thelarge intraseasonal variations. Most models produce too much convective (over 95% of total precipitation)and too little stratiform precipitation over most of the low latitudes, in contrast to 45%–65% in convectiveform in the Tropical Rainfall Measuring Mission (TRMM) satellite observations. The biases in the con-vective versus stratiform precipitation ratio are linked to the unrealistically strong coupling of tropicalconvection to local SST, which results in a positive correlation between the standard deviation of Niño-3.4SST and the local convective-to-total precipitation ratio among the models. The models reproduce thepercentage of the contribution (to total precipitation) and frequency for moderate precipitation (10–20 mmday�1), but underestimate the contribution and frequency for heavy (�20 mm day�1) and overestimatethem for light (�10 mm day�1) precipitation. The newest generation of coupled models still rains toofrequently, mostly within the 1–10 mm day�1 category. Precipitation intensity over the storm tracks aroundthe eastern coasts of Asia and North America is comparable to that in the ITCZ (10–12 mm day�1) in theTRMM data, but it is much weaker in the models. The diurnal analysis suggests that warm-season convec-tion still starts too early in these new models and occurs too frequently at reduced intensity in some of themodels. The results show that considerable improvements in precipitation simulations are still desirable forthe latest generation of the world’s coupled climate models.

1. Introduction

Precipitation is one of the most important climatevariables. The largest impact of future climate changeson the society will likely come from changes in precipi-tation patterns and variability. However, it is still a big

challenge for coupled global climate models (CGCMs)to realistically simulate the regional patterns, temporalvariations, and correct combination of frequency andintensity of precipitation (McAvaney et al. 2001; Coveyet al. 2003; Trenberth et al. 2003; Meehl et al. 2005).The difficulty arises from the complexity of precipita-tion processes in the atmosphere that include cloud mi-crophysics, cumulus convection, planetary boundarylayer processes, large-scale circulations, and many oth-ers. Errors in simulated precipitation fields often indi-cate deficiencies in the representation of these physicalprocesses in the model. It is therefore important to ana-lyze precipitation for model evaluation and develop-ment.



15 SEPTEMBER 2006 D A I 4605


JCLI3884

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J. Climate

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Changes in Continental Freshwater Discharge from 1948 to 2004

AIGUO DAI, TAOTAO QIAN, AND KEVIN E. TRENBERTH


JOHN D. MILLIMAN

School of Marine Science, College of William and Mary, Gloucester Point, Virginia

(Manuscript received 16 April 2008, in final form 17 November 2008)

ABSTRACT

A new dataset of historical monthly streamflow at the farthest downstream stations for the world’s 925 largest

ocean-reaching rivers has been created for community use. Available new gauge records are added to a network

of gauges that covers ;80 3 106 km2 or ;80% of global ocean-draining land areas and accounts for about 73%

of global total runoff. For most of the large rivers, the record for 1948–2004 is fairly complete. Data gaps in the

records are filled through linear regression using streamflow simulated by a land surface model [Community

Land Model, version 3 (CLM3)] forced with observed precipitation and other atmospheric forcings that are

significantly (and often strongly) correlated with the observed streamflow for most rivers. Compared with

previous studies, the new dataset has improved homogeneity and enables more reliable assessments of decadal

and long-term changes in continental freshwater discharge into the oceans. The model-simulated runoff ratio

over drainage areas with and without gauge records is used to estimate the contribution from the areas not

monitored by the gauges in deriving the total discharge into the global oceans.

Results reveal large variations in yearly streamflow for most of the world’s large rivers and for continental

discharge, but only about one-third of the top 200 rivers (including the Congo, Mississippi, Yenisey, Parana,

Ganges, Columbia, Uruguay, and Niger) show statistically significant trends during 1948–2004, with the rivers

having downward trends (45) outnumbering those with upward trends (19). The interannual variations are

correlated with the El Nino–Southern Oscillation (ENSO) events for discharge into the Atlantic, Pacific, Indian,

and global ocean as a whole. For ocean basins other than the Arctic, and for the global ocean as a whole, the

discharge data show small or downward trends, which are statistically significant for the Pacific (29.4 km3 yr21).

Precipitation is a major driver for the discharge trends and large interannual-to-decadal variations. Compari-

sons with the CLM3 simulation suggest that direct human influence on annual streamflow is likely small

compared with climatic forcing during 1948–2004 for most of the world’s major rivers. For the Arctic drainage

areas, upward trends in streamflow are not accompanied by increasing precipitation, especially over Siberia,

based on available data, although recent surface warming and associated downward trends in snow cover and

soil ice content over the northern high latitudes contribute to increased runoff in these regions. The results are

qualitatively consistent with climate model projections but contradict an earlier report of increasing continental

runoff during the recent decades based on limited records.

1. Introduction

Continental freshwater runoff or discharge is an im-

portant part of the global water cycle (Trenberth et al.

2007). Precipitation over continents partly comes from

water evaporated from the oceans, and streamflow re-

turns this water back to the seas, thereby maintaining a

long-term balance of freshwater in the oceans. The

discharge from rivers also brings large amounts of par-

ticulate and dissolved minerals and nutrients to the

oceans (e.g., Boyer et al. 2006); thus it also plays a key

role in the global biogeochemical cycles. Unlike oceanic

evaporation, continental discharge occurs mainly at the

mouths of the world’s major rivers. Therefore, it pro-

vides significant freshwater inflow locally and forces

ocean circulations regionally through changes in density

* The National Center for Atmospheric Research is sponsored

by the National Science Foundation.

Corresponding author address: Dr. Aiguo Dai, National Center

for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-

3000.

E-mail: [email protected]

15 MAY 2009 D A I E T A L . 2773

DOI: 10.1175/2008JCLI2592.1

� 2009 American Meteorological Society

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J. Climate

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Advanced Review

Drought under global warming:a reviewAiguo Dai∗

This article reviews recent literature on drought of the last millennium, followedby an update on global aridity changes from 1950 to 2008. Projected future aridityis presented based on recent studies and our analysis of model simulations.Dry periods lasting for years to decades have occurred many times duringthe last millennium over, for example, North America, West Africa, and EastAsia. These droughts were likely triggered by anomalous tropical sea surfacetemperatures (SSTs), with La Nina-like SST anomalies leading to drought inNorth America, and El-Nino-like SSTs causing drought in East China. Over Africa,the southward shift of the warmest SSTs in the Atlantic and warming in theIndian Ocean are responsible for the recent Sahel droughts. Local feedbacks mayenhance and prolong drought. Global aridity has increased substantially since the1970s due to recent drying over Africa, southern Europe, East and South Asia,and eastern Australia. Although El Nino-Southern Oscillation (ENSO), tropicalAtlantic SSTs, and Asian monsoons have played a large role in the recent drying,recent warming has increased atmospheric moisture demand and likely alteredatmospheric circulation patterns, both contributing to the drying. Climate modelsproject increased aridity in the 21st century over most of Africa, southern Europeand the Middle East, most of the Americas, Australia, and Southeast Asia. Regionslike the United States have avoided prolonged droughts during the last 50 yearsdue to natural climate variations, but might see persistent droughts in the next20–50 years. Future efforts to predict drought will depend on models’ ability topredict tropical SSTs. 2010 John Wiley & Sons, Ltd. WIREs Clim Change 2011 2 45–65 DOI:10.1002/wcc.81

WHAT IS DROUGHT?

Drought is a recurring extreme climate eventover land characterized by below-normal

precipitation over a period of months to years.Drought is a temporary dry period, in contrast tothe permanent aridity in arid areas. Drought occursover most parts of the world, even in wet and humidregions. This is because drought is defined as a dryspell relative to its local normal condition. On theother hand, arid areas are prone to drought becausetheir rainfall amount critically depends on a fewrainfall events.1

Drought is often classified into three types2,3:(1) Meteorological drought is a period of months toyears with below-normal precipitation. It is oftenaccompanied with above-normal temperatures, and

∗Correspondence to: [email protected]

National Center for Atmospheric Research, Boulder,CO, USA

DOI: 10.1002/wcc.81

precedes and causes other types of droughts. Mete-orological drought is caused by persistent anomalies(e.g., high pressure) in large-scale atmospheric circula-tion patterns, which are often triggered by anomaloustropical sea surface temperatures (SSTs) or otherremote conditions.4–6 Local feedbacks such as reducedevaporation and humidity associated with dry soilsand high temperatures often enhance the atmosphericanomalies.7 (2) Agricultural drought is a period withdry soils that results from below-average precipitation,intense but less frequent rain events, or above-normalevaporation, all of which lead to reduced crop pro-duction and plant growth. (3) Hydrological droughtoccurs when river streamflow and water storages inaquifers, lakes, or reservoirs fall below long-termmean levels. Hydrological drought develops moreslowly because it involves stored water that is depletedbut not replenished. A lack of precipitation often trig-gers agricultural and hydrological droughts, but otherfactors, including more intense but less frequent pre-cipitation, poor water management, and erosion, can

Volume 2, January/February 2011 2010 John Wi ley & Sons, L td. 45

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WIREs Climate Change

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Characteristics and trends in various forms of the Palmer DroughtSeverity Index during 1900–2008

Aiguo Dai1

Received 21 December 2010; revised 17 March 2011; accepted 29 March 2011; published 29 June 2011.

[1] The Palmer Drought Severity Index (PDSI) has been widely used to study ariditychanges in modern and past climates. Efforts to address its major problems have led to newvariants of the PDSI, such as the self‐calibrating PDSI (sc_PDSI) and PDSI usingimproved formulations for potential evapotranspiration (PE), such as the Penman‐Monteithequation (PE_pm) instead of the Thornthwaite equation (PE_th). Here I compare andevaluate four forms of the PDSI, namely, the PDSI with PE_th (PDSI_th) and PE_pm(PDSI_pm) and the sc_PDSI with PE_th (sc_PDSI_th) and PE_pm (sc_PDSI_pm)calculated using available climate data from 1850 to 2008. Our results confirm previousfindings that the choice of the PE only has small effects on both the PDSI and sc_PDSI forthe 20th century climate, and the self‐calibration reduces the value range slightly andmakes the sc_PDSI more comparable spatially than the original PDSI. However, thehistograms of the sc_PDSI are still non‐Gaussian at many locations, and all four forms ofthe PDSI show similar correlations with observed monthly soil moisture (r = 0.4–0.8)in North America and Eurasia, with historical yearly streamflow data (r = 0.4–0.9) overmost of the world’s largest river basins, and with GRACE (Gravity Recovery and ClimateExperiment) satellite‐observed water storage changes (r = 0.4–0.8) over most landareas. All the four forms of the PDSI show widespread drying over Africa, East andSouth Asia, and other areas from 1950 to 2008, and most of this drying is due to recentwarming. The global percentage of dry areas has increased by about 1.74% (of globalland area) per decade from 1950 to 2008. The use of the Penman‐Monteith PE andself‐calibrating PDSI only slightly reduces the drying trend seen in the original PDSI.The percentages of dry and wet areas over the global land area and six select regions areanticorrelated (r = −0.5 to −0.7), but their long‐term trends during the 20th century donot cancel each other, with the trend for the dry area often predominating over that for thewet area, resulting in upward trends during the 20th century for the areas under extreme(i.e., dry or wet) conditions for the global land as a whole (∼1.27% per decade) andthe United States, western Europe, Australia, Sahel, East Asia, and southern Africa.The recent drying trends are qualitatively consistent with other analyses and modelpredictions, which suggest more severe drying in the coming decades.

Citation: Dai, A. (2011), Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900–2008,J. Geophys. Res., 116, D12115, doi:10.1029/2010JD015541.

1. Introduction

[2] Drought is a recurring extreme climate event over landcharacterized by below‐normal precipitation over a period ofseveral months to several years or even a few decades. It isamong the most damaging natural disasters, causing tens ofbillions of dollars in damage and affecting millions of peoplein the world each year [Wilhite, 2000]. To quantify droughtand monitor its development, many drought indices havebeen developed and applied [Heim, 2000, 2002; Keyantash

and Dracup, 2002; Vicente‐Serrano et al., 2010a; Dai,2011]. Among them, the Palmer Drought Severity Index(PDSI) is the most prominent index of meteorologicaldrought used in the United States for drought monitoring andresearch [Heim, 2002]. The PDSI and its variants have beenused to quantify long‐term changes in aridity over land in the20th [Dai et al., 1998, 2004; van der Schrier et al., 2006a,2006b, 2007; Dai, 2011] and 21st [Burke et al., 2006; Burkeand Brown, 2008; Dai, 2011] century. The PDSI has alsobeen widely used in tree ring‐based reconstructions of pastdroughts in North America and other regions [e.g., Cook et al.,2004, 2007].[3] The PDSI was originally developed by Palmer [1965]

with the intent to measure the cumulative departure in sur-

1National Center for Atmospheric Research, Boulder, Colorado, USA.

Copyright 2011 by the American Geophysical Union.0148‐0227/11/2010JD015541

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Surface Observed Global Land Precipitation Variations ... · Annual and monthly mean values of continental freshwater discharge into the oceans are estimated at 18 ... based on observed