642

JOURNAL OF HYDROMETEOROLOGYVOLUME 7

Relative Roles of Large-Scale Orography and Land Surface Processes in the Global
Hydroclimate. Part II: Impacts on Hydroclimate over Eurasia
KAZUYUKI SAITO
Frontier Research Center for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama, Kanagawa, JapanTETSUZO YASUNARI
Frontier Research Center for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama, Kanagawa, andNagoya University, Nagoya, Aichi, JapanKUMIKO TAKATA
Frontier Research Center for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama, Kanagawa, Japan(Manuscript received 12 May 2005, in final form 5 January 2006)
ABSTRACTA series of simplistic simulations from an AGCM coupled to a simple land surface scheme and water
vapor tracers was performed to explore the relative roles of basic factors in land surface conditions, withregard to the seasonal evolution of the hydroclimate over Eurasia. Large-scale orography in Asia andvegetation (further decomposed to soil and vegetation skin) were evaluated, with orography represented in
the model by surface altitude, soil represented by water-holding capacity, and vegetation skin represented
by surface albedo and roughness.
The percentage of global annual precipitation over land (occupying 25.6% of the total surface) was
14.8%, 15.0%, and 21.7% for the mountainless “bare rock” (i.e., vegetationless) surface, and the bare-rockand vegetated surface, respectively. The result for evaporation was 8.9%, 9.0%, and 16.2%, respectively,
showing higher sensitivity to the land surface changes than precipitation. The orography and vegetation(i.e., soil and vegetation skin) showed different impacts on Eurasian hydroclimate on the seasonal andregional scales. Thermodynamical forcings to the atmosphere increased over the continent with the inclusion of both. Large-scale orography in Asia exerted east–west contrast in the surface energy exchange insummer in eastern Eurasia. An increase in extratropical winter precipitation with mountains was also
noticed because of the atmospheric vapor transport changes. Impact of soil and vegetation skin was clearlyfound in the warm season in the extratropics; soil impacts extratropical summer precipitation due toenhanced recycling of water and the resultant increased water supply.

1. Introduction
Water is fundamental to the planetary ecoclimate
system. Understanding the variability and availabilityof water over land is a significant issue for human societies. Variability in the hydroclimate over land isclosely and directly linked to land surface conditions
and processes. Although the role of the ocean, the largest reservoir of water on earth, cannot be exaggerated,

Corresponding author address: Kazuyuki Saito, FRCGC/
JAMSTEC, 3173-25 Showa-Machi, Kanazawa-Ku, Yokohama
City, Kanagawa 236-0001, Japan.
E-mail: ksaito@jamstec.go.jp© 2006 American Meteorological Society

JHM516the land surface conditions determine an important aspect of water and energy exchanges with the atmosphere and affect the amount and variability of waterflow and storage, especially over land. Monsoon activity is a prominent example of a land role in the globalhydroclimate. Recent analyses of the temporal variability of remotely sensed oceanic water vapor show large
annual variations only near continental coastal areasthat coincide with the major monsoon regions (Chen
2004); variability is smaller over the open ocean. Suchenhanced variability near land implies how the presence and conditions of land may be important in thecontinental hydroclimate. The present-day land surface conditions comprise of several individual pro-

AUGUST 2006

SAITO ET AL.

cesses or conditions that have been developed throughtime. Our fundamental question is which of the individual conditions that comprises the present land surface may be relatively more important to the current
continental hydroclimate.
Beginning in the late nineteenth century, pedologists,or soil scientists, recognized that topography, vegetation (organism), soil, and climate mutually interact toconstitute a system near the earth’s surface (Jenny
1941; Buol et al. 1997). Soil has formed through physical and chemical processes such as weathering, andthrough biological processes for which vegetation has
played an important role. In other words, soil layer is a
product of vegetation activity in collaboration with climate, and must be treated explicitly when the basic
effect of vegetation is concerned. In turn, soil has provided a vital base for vegetation and other organisms.
In Asia, the uplift of the Tibetan Plateau must haveplayed a decisive role in shaping the continental tohemispheric atmospheric circulation patterns and thehydroclimate of the continent. Grounded on the above
speculations, we choose large-scale orography and vegetation as key conditions. The latter may be conceptually decomposed further into soil and surface vegetation. “Bare rock”—that is, a soilless, vegetationless surface—is termed a nonvegetated land surface. Our
attempt reflects some important stages or components,of relatively long time scale, in the evolution of theearth’s surface from the paleoclimatic past (bare rockwithout the Tibetan Plateau) to the present continental
surface.
There have been a number of model studies on land
surface effects on climate. They, however, tend to havefocused on one or a few specific processes or conditions, separately. Examples include studies on the effects of orography or land–sea geometry (Hahn andManabe 1975; Broccoli and Manabe 1992; Kutzbach etal. 1993; Dirmeyer 1998), albedo (Charney et al. 1975,
1977; Dirmeyer and Shukla 1996), vegetation (Sato etal. 1989; Xue et al. 2004), and soil wetness (Delworthand Manabe 1988, 1989; Milly and Dunne 1994; Douville et al. 2001). An investigation, attempting to evaluate the relative importance of these land surface conditions on the hydroclimate in one outline, has not been
completed.
To this purpose, an atmospheric general circulation
model (AGCM) coupled to a simple land surface
scheme was used under an idealistic experiment design.
In this study, we aimed at delineating a simplistic picture of the basic mechanism evolved over millions ofyears, with the same configuration. Our simple scheme,
however, includes the basic vegetation processes ofrelatively long time scale, such as surface albedo and643

roughness length, and indirectly considers the effect oftranspiration. The conditions of large-scale topography,
soil, and surface vegetation are parameterized in themodel by surface altitude, by water-holding capacity or
field capacity; and by vegetation skin (surface albedo
and roughness), respectively. Note that “surface vegetation” in this study, therefore, refers only to the vegetation skin since the model does not include subgridscale, biospheric parameterizations. Similarly, (total)
vegetation or vegetated surface is a reference only to
the “soil layer with vegetation skin” in this study. Relevant details of the important land surface processes inthe simple scheme are described in the next section. A
thorough description of the scheme is found in the firstpart of this study (Yasunari et al. 2006, hereafter PartI). We set the horizontal resolution at T42 (almost
equivalent to 2.8° gridding in latitude and longitude)
for computational efficiency, so that we can derive
monthly climatology from 50-yr realization, and pentad
climatology from 25-yr simulation.
Part I of this study evaluated the relative roles of land
surface processes on monsoon activity and the related
large-scale atmospheric circulation in the Tropics.
Here, in Part II, the climatology and seasonality of thecontinental hydroclimate is discussed, with a special focus on extratropical eastern Eurasia. Section 2 briefly
describes the model and the experiment design. Sections 3 through 6 show the results of the analysis. Discussions and concluding remarks are given in section 7.

2. Model and experiment designPart I contains detailed descriptions of the model andexperiment design. Only a brief outline therefore ispresented here. The model, the Center for Climate System Research/National Institute for Environmental
Studies/Frontier Research Center for Global Change(CCSR/NIES/FRCGC) AGCM, is a three-dimensionalhydrostatic primitive equation model with sphericaland sigma coordinates. The model is run at T42 horizontal resolution with 20 vertical levels up to about 10
hPa in the lower stratosphere. Ocean surface conditions(sea surface temperatures and sea ice concentration)
are prescribed using a monthly climatology derived
from 1979–89 observations that were prepared andused for the Atmospheric Model Intercomparison Project (Gates 1992).
Soil moisture amount is an important factor in controlling the amount of water and energy fluxes from theland to the atmosphere. Soil water content is prognostically determined in the scheme in one layer throughthe balance of precipitation, evapotranspiration, snowmelt, and runoff in the simple hydrology scheme (Num-644

JOURNAL OF HYDROMETEOROLOGY

aguti 1999). The water-holding capacity (saturation soil
water storage) of the 1-m soil layer is defined by field
capacity (FC). Default value of the FC is 20 cm, considering soil porosity, gravity drainage, and available
depth for vegetation.
Surface albedo affects the rate of incoming solar radiation absorbed at the surface and thus the amount ofavailable energy at the surface. Roughness is used indiagnostic estimation of the aerodynamic resistance. In
the simple land scheme we used, surface albedo androughness length (Z0) are specified in accordance withthe prescribed vegetation type, although change inamount of leaf or canopy is not explicitly accounted forsince no vegetation physiology is included in thescheme.
Vertical turbulent fluxes at the surface are estimatedby bulk formulas. Aerodynamic resistance is diagnostically determined, and stomatal resistance is set to thedaytime or nighttime value according to the local solar
angle if vegetation is present, and thus the transpiration
is included in a simple way. The evaporation efficiency
is then estimated from soil wetness, aerodynamic resistance, and stomatal resistance.
Four simulations with different land surface conditions comprised the study: a bare-rock surface with noorography in Asia (NMR), the bare-rock surface (MR),a desert condition (MS), and a vegetated condition(MVS). The bare-rock surface mimics nonvegetatedstate. The vegetation type was specified to desert wherealbedo and roughness length (Z0) were 0.30 and 0.02 m,
respectively, and field capacity was set to 1 cm. The
default topography was used except for the NMR run,in which it is set to zero east of 30°E in the Asian region
including the Arabian Peninsula to simulate the absence of the large-scale orography (cf. Fig. 2 in Part I).
In the MS run, FC was set to the default value of 20 cm
to represent the soil layer. The MS condition is a virtualcomplementary setting to bridge the bare-rock and vegetated conditions. The MVS run used the default vegetation type, FC, and surface altitude. Thus, albedo and
Z0 were specified according to the vegetation type ateach grid point. Table 1 in Part I summarizes the experiment design.
For each of the four simulations, the model was run
for 50 yr after a 5-yr spinup. Monthly climatology for
simulated variables was calculated for the last 40 simulation years; pentad climatology was derived from thefinal 25 yr.

3. Near-surface energy balance
Figure 1 shows the summer [June–August (JJA)] climatology for near-surface air temperatures for the (a)–VOLUME 7

FIG. 1. (a) Surface air temperature at 2 m (T2m) in summer(JJA) for (a) NMR, (b) MR, (c) MVS, and (d) observation. Contour interval is 5°C.

AUGUST 2006

645

SAITO ET AL.

(c) simulations and (d) observations. Boreal seasons
are used in this paper unless otherwise stated. The observed climatology was calculated from the Climatic
Research Unit (CRU) time series (TS) 2.0 dataset provided at the University of East Anglia, United Kingdom (Mitchell and James 2005), for the same periodused to derive the SST climatology. Comparison of regional precipitation with observed values is discussed inPart I (cf. Fig. 4 in Part I).
Figure 2 shows the impact of the land surface conditions on summer near-surface air temperature. Positive
values are contoured with thick lines and filled withdark shades, while negative values are contoured thin
and are shaded lightly. We discuss in this section only
summer climatology for it is the season in which theimpact of vegetation is acknowledged in the broadest
regions. Seasonal change will be discussed in the next
section. Presence of the orography (i.e., MR minus
NMR) decreases local surface temperatures following
the atmospheric lapse rate (Fig. 2a). Figures 2b and 2cshow apparently offsetting impacts of soil and vegetation skin on temperature, being emphasized in the extratropics. Sensible heat decreases (and consequently
surface air temperature decreases) due to an increase ofsoil moisture and resultant latent heat flux in the MS
run, while net radiation increases (leading to increased
surface air temperature) due to vegetation albedo in
the MVS run. The model’s climatology of near-surface
air temperature is simulated reasonably well in the
Tropics and subtropics, but tends to overestimate northof 40°N by several degrees in both seasons (Fig. 1d).
The reason for the warm bias is not clear. Lack of subgrid biospherical parameterization (e.g., canopy layer
and root-to-leaf transpiration mechanism) may accountfor the bias to some degree (Sato et al. 1989). Anotherpossible factor is the insufficient implementation ofprocesses related to soil freezing and permafrost (Luoet al. 2003; Viterbo et al. 1999), for the used land surface scheme is not enough to resolve the soil-freezing
processes. For other meteorological variables, spatial
patterns and magnitudes in the MVS climatology werereasonably in agreement with the observation to similar
extent (not shown), and we considered them sufficientfor our purpose.
The land surface conditions give a large impact on
surface energy balance, and consequently the thermodynamical forcing at the land surface to the atmosphere. Figure 3 illustrates the changes in the total
amount of surface available energy, defined here as asum of surface sensible and latent heat flux to the atmosphere. The surface energy balance in the model isexpressed by the following equation at the infinitely
thin skin of the surface:

FIG. 2. Difference of JJA T2m between (a) MR and NMR runs,(b) MS and MR runs, and (c) MVS and MR runs. Contour interval is 4°C. Positive values are shaded lightly and negative values
heavily.

S↓ ⫹ S↑ ⫹ L↓ ⫹ L↑ ⫽ H ⫹ ␭E ⫹ G,
where S↓(S↑) denotes downward (upward) shortwave
radiation, L↓(L↑) denotes downward (upward) longwave radiation, and H and ␭E denote sensible and latent heat flux to/from the atmosphere, respectively.
Here G is ground heat conduction and latent heat usedin snowmelt. The left-hand side (lhs) of the equation is
the net radiation absorbed at the surface and equals thetotal available energy at surface for heat fluxes. The
amount of ground heat conduction and snowmelt latent

646

JOURNAL OF HYDROMETEOROLOGYVOLUME 7

heat is usually small, especially in summer, compared to
the first two terms on the right-hand side (rhs) of theequation, and therefore we refer to the sum of sensible
and latent heat flux as the “surface available energy” inthe following analysis. The distribution of the surface
available energy over land was substantially similar tothat of the sum of two column-integrated atmosphericheating terms, apparent heat source Q1, and apparent
moisture source ⫺Q2 since the column-integrated atmospheric radiative heating was minor compared to thesum of the two terms. Surface available energy in the
MVS run was in good agreement with the observed ineastern Eurasia (Yanai and Li 1994).
The fraction of sensible heat flux FH in the partitionof the surface available energy is defined by the following equation:
FH ⫽ HⲐ共H ⫹ ␭E兲,FIG. 3. Surface available energy for (a) NMR, (b) MR, (c) MS,
and (d) MVS run. Contour interval is 20 W m⫺2.

and is shown in Fig. 4. The surface available energy
decreases in general monotonically from the equator to
the pole, reflecting the hemispheric difference in thesolar radiation. The sensible seat fraction also has ameridional distribution in Eurasia, but modified by aneast–west contrast regarding the distance from theocean (Figs. 3a, 4a). The continental area of the subtropical high, from North Africa through the Arabian
Peninsula to the southern central Asia, shows a relatively small amount of surface available energy for its
latitude, and high fraction of sensible heat. In contrast,
the eastern areas close to the ocean have relatively
large surface available energy and lower fraction of sensible heat, likely resulting from moisture advection
from the oceans associated with monsoon activity.
Mountains and vegetation affect the total amount andpartition of the surface available energy at different
places with different magnitudes.
The large-scale orography increased the amount of
the local surface available energy by about 20 W m⫺2(Fig. 3b) and decreased the sensible heat fraction to thearea (Fig. 4b), thereby creating an east–west contrast.
This increase in heating of the lower atmosphere fromsurface is consistent with the argument on the Tibetan
Plateau’s role on the Asian summer monsoon from theobservational side (e.g., He et al. 1987; Yanai et al.
1992) and from the numerical side (e.g., Hahn andManabe 1975; Dirmeyer 1998). Increased moistureavailability due to changes in the atmospheric moisturetransport may also account for the change (cf. Fig. 5 inPart I). In contrast, surface available energy is smaller
and the sensible heat fraction is larger in the westernpart of central Asia where the surface is drier due toprecipitation decrease (cf. Figs. 3a,b in Part I). Broccoli

AUGUST 2006

SAITO ET AL.

FIG. 4. As in Fig. 3, but for sensible heat fraction.

647

and Manabe (1992) examined effects of orography withand without soil moisture feedback in the midlatitudecontinent. Our result for the MR–NMR (Figs. 3a,b) is
consistent with their results (their Figs. 15, 16) in thatthe presence of orography leads to an arid condition incentral Asia. However, the result of the difference to
MS or MVS is compared: it shows less arid conditions in
the region (Fig. 4 in Part I), as also seen in surface
available balance in Fig. 3. This may result from different soil moisture capacity; their NM run (no mountains
with interactive soil moisture) has the FC value of 15
cm compared to 1 cm for our NMR run, and may indicate the amount of moisture capacity is more relevant
than interactivity of soil moisture. Asian topography
had small but discernible impact on the amount of surface available energy in remote regions too, for example, near the Rocky Mountains (topography outside
Asia remains unchanged between the NMR and MR
simulations), and central to West Africa. For the latter,the influence of the Tibetan Plateau on atmosphericcirculation and African climate has been discussed inseveral studies (e.g., Rodwell and Hoskins 1996) and inPart I.
When vegetation is present (in MS and MVS), thesurface available energy increases and sensible heat
fraction decreases in large areas in the continent (Figs.
3c,d and 4c,d). Zonally uniform distribution of surface
available energy is emphasized by the soil layer, withlarger meridional gradient than for the NMR case (Fig.
3c). The sensible heat fraction decreases to one-third or
smaller except the subtropical high regions, likely due
to increased availability of soil moisture to evaporationin the MS run (Fig. 4c), and surface air temperature
decreases (Fig. 2b). The vegetation skin (albedo androughness), specified according to the vegetation typeat each grid point, changes the local-scale distributionof the available energy at the surface, although it adds
only a minor impact on the sensible heat fraction (Fig.
4d). Patchiness of the available energy reflects the distribution of vegetation types and their albedo (cf. Fig.
2a in Part I). This additional decrease in albedo byvegetation skin works to increase the net radiation, andsurface available energy increases, leading to surface
air temperature increase. Thereby, both sensible andlatent heat increase, keeping the ratio of partition almost the same, since the soil layer is present to provide
moisture (Figs. 3c,d and 4c,d). The results and argument by Charney et al. (1977) of positive feedback between albedo, atmosphere (convection), and precipitation, especially in the midlatitude semiarid areas, is inline with the difference shown between MVS and MS
runs as far as surface temperature and energetics areconcerned (their Tables 4.3–4).

648

JOURNAL OF HYDROMETEOROLOGYVOLUME 7

FIG. 5. (a) Time–latitude cross section of air temperature near surface averaged over the area between 70° and
100°E for the (a) NMR, (b) MR, (c) MS, and (d) MVS runs. Contour interval is 8°C. Two horizontal black solidlines denote the region of high orography, including the Tibetan Plateau.

4. Seasonal transitions over Asian land regions
Changes in land surface conditions led not only todifferent seasonal climatology, as demonstrated in Part
I and in the previous section, but also to different seasonal evolution of the continental hydroclimate. Latitude–time characteristics of continental hydroclimate
under different land surface conditions are compared ina meridional strip between 70° and 100°E, using pentad
climatology. This geographical area includes, fromsouth to north, India, western Indochina, Tibet, the Tarim Basin, and the Siberian Plain and Plateau. Various
climate sections of Eurasia are included, from moist
Tropics to arid arctic areas and from coastal regions tothe continental interior.

a. Near-surface air temperature
Figure 5 shows latitude–time sections of near-surface
air temperature (Ts) averaged over the strip defined
above. The area between the two horizontal solid blacklines denotes the latitude band of high orography that
includes the Tibetan Plateau. Mean altitude in this region exceeds 2000 m.
For all the seasons, local surface air temperature decreases following the atmospheric lapse rate if the

Tibetan Plateau is absent (Fig. 5a; cf. Fig. 2a). The latitudinal distribution of Ts is either monomodal (summer) or monotonic (other seasons) without the orography. The highest temperature would exceed 40°C insummer around 30°N; a descending motion would prevail and no topographically forced convective clouds
appear to give a shade. The northern continent is lesschanged with or without the orography, but its amplitude of the seasonal change is suppressed with vegetation. In the tropical region, the seasonal amplitudechanges with orography, but less impact is found withsoil and vegetation skin.

b. Precipitation
Figure 6 shows the similar plots for precipitation. A
northward jump in the precipitation center, associatedwith the onset of the south Asian monsoon, is found in
the all the simulations, although the duration, intensity,and geographical extent of the jump are different. For
the NMR run, it is rather a mild migration rather thana jump. It reiterates the results of the previous studies(e.g., Hahn and Manabe 1975; Dirmeyer 1998; Abe etal. 2003) that the Tibetan Plateau is attributable to theprogress of the Asian monsoon precipitation as it isAUGUST 2006

SAITO ET AL.

649

FIG. 6. (a)–(d) As in Fig. 5, but for precipitation (mm month⫺1). Contours are drawn at 5, 10, 50, and 90 mm
month⫺1. (e) As in (a) but from CMAP.

observed in the present days. Vegetation adds a small
modification to make the onset of the summer monsoon earlier, the timing of the precipitation shift, andthe rainy season long.
In the extratropics, rainfall will be very small if thesurface has no soil layer to store moisture and has asmall seasonal cycle (Figs. 6a,b), for the Eurasian continent is a global moisture source in summer and a sinkin winter (Fig. 2 in Numaguti 1999). With large-scale
orography, a zonal band between 40° and 60°N will bewetter except for midsummer, resulting in even smaller
seasonal change due to changed atmospheric circulation (Fig. 6b). This contrast of drying north and moist-

ening south is consistent with the previous studies
noted above. The summer monsoon season is the mostextensive period, but other seasons shows a similar tendency with smaller amplitude. With vegetation, the extratropical continent has more precipitation during thewarm season, leading to a longer seasonal cycle with alarger amplitude. The presence of soil is largely responsible for the change in summer precipitation (almost
doubled in the simulation). It has long been acknowledged that water-storage capacity of the surface (i.e.,soil layer) and consequent evaporation have a large
influence on continental precipitation. It is more evident in semiarid areas and the extratropics than in the

650

JOURNAL OF HYDROMETEOROLOGYVOLUME 7

FIG. 7. As in Fig. 5 but for evaporation (mm month⫺1). Contour interval is 15 mm month⫺1, beginning from 10
mm month⫺1.

Tropics (Fig. 1 in Shukla and Mintz 1982; Fig. 2 in Milly
and Dunne 1994). The vegetation skin further accelerates the start of rainy season by up to two months.
The simulated amount of precipitation in the extratropical continents for the MS and MVS run is higher
than the observed present-day values taken from the
Climate Prediction Center (CPC) Merged Analysis ofPrecipitation (CMAP; Xie and Arkin 1997) (Fig. 6e; cf.
Figs. 4 and 11 in Part I). The reasons of this overestimation are not fully clear yet, but at least two factors
appear to be attributable, to some extent: one is thewarm bias of air temperatures from the surface to theupper troposphere, and the other is the overestimation
tendency of evaporation in the simple surface scheme,
as will be discussed later. With a warm bias and an
excess of evaporation, the air column tends to havemore precipitable water, possibly bringing more precipitation to the column. Parameterization related tocloud formation and precipitation processes may also
be responsible for the bias. However, it is out of ourscope.

c. Evaporation
The amount of moisture flux (evaporation), or latent
heat flux, is directly related to the water-holding capac-

ity of the land surface. Changes in latent heat havepartly been discussed in section 3. Seasonal change inevaporation in the extratropical continent is synchronous with the annual solar cycle regardless of the surface conditions, as shown in Fig. 7. In the extratropicalcontinent, uplift of mountains exerts only a small decrease, corresponding to a drier condition as noted before (Figs. 6a,b). With vegetation, the evaporation rateincreases drastically. Despite the increase in the amplitude, the phase does not change with the surface conditions. This is a characteristic of continental evaporation cycle at high latitudes that it is largely phase lockedwith the available energy cycle. Evaporation enhancement occurs during the warm rainy season in high latitudes, likely due to the short time scale of water vapor
residence in the atmosphere and to a positive feedback
between evaporation and precipitation. Increased
evaporation enhances additional vapor for precipitation, and more precipitation further increases local
evaporation. Reduced albedo and the resultant increase in the surface available energy, and the increased storage of soil moisture, augment the highlatitude evaporation by about 100 mm month⫺1 in the
MVS simulation. Additional analysis on precipitationand evaporation changes by vapor tracking will be

AUGUST 2006

SAITO ET AL.

given in section 6. The result of increased evaporation
with the soil layer appears to be reasonable, in comparison with previous studies (e.g., Milly and Dunne
1994). In fact, the difference between the MR and MS(or MVS) runs for evaporation and precipitation are
consistent with the result of Milly and Dunne (1994; cf.
their Figs. 4 and 6). The absolute value, however, may
be overestimated because of the overestimation tendency in the simple hydrology scheme employed in thisstudy, when compared with advanced biosphere–hydrology schemes, such as Simple Biosphere Model(SiB; Sato et al. 1989) variants or other recent schemes(Henderson-Sellers et al. 2003). Sato et al. (1989) demonstrated the difference may exceed 25 W m⫺2 in thelarge areas of the continents during summer, except for
the arid regions.
To the contrary, the evaporation rate in the Tropics
is more closely related to the precipitation cycle, or
water availability, because the surface available energy
is usually abundant in the region. Uplift of the Tibetan
surface increases the monsoon-related precipitation,
which consequently increases evaporation from spring
to autumn over the Tibetan Plateau and in the Tropics(Figs. 7a,b). With vegetation, evaporation further increases during the dry season (November to next
March), likely because of the prolonged rainy season
and stored water for simultaneous or delayed evaporation.

5. Hydrometeorology north of 40°N overcontinental Eurasia
a. Low-level cloud (stratocumulus)
Low-level clouds (defined in the model as the percentage of cloud cover below 680 hPa) can trace synoptic-scale disturbances and frontal activities at midand high latitudes (Fig. 8). Continental low-levelcloudiness in MVS in Fig. 8d was overestimated at midlatitude winter and underestimated from mid- to highlatitudes in other seasons when compared to a climatology derived from International Satellite Cloud Climatology (ISCCP) (Fig. 8e). Nonetheless, the seasonalchange is qualitatively reproduced, sufficient to discuss
the relative impacts of land surface processes on theseasonal cycle of synoptic-scale disturbances in the region.
Asian orography exerts a small impact on low-levelcloud cover. It delays the northern migration in summer, by a month or shorter, at 70°N or higher. The
cloud cover decreases in the band between 50° and
70°N for the other seasons in the mountain case (Fig.
8b).
In MS run, the low-level cloud cover is more exten-

651

sive at high latitudes in the warm season, compared to
MVS run. Charney et al. (1977) showed that a decreasein net radiation at the surface and a resulting decreasein transfer of surface energy, due to increased albedo,
lead to a decrease in total cloud cover in semiarid area
(their Tables 4.2–4). In our MS and MVS runs, summer
cloud cover decreases with increased surface albedo in
the subtropical semiarid regions in good agreementwith Charney’s results (not shown), but it increases inthe extratropics, showing a different result from theirs(Figs. 8c,d). The lower-tropospheric air from 50° to
70°N in MS run is found to contain less specific humidity and the dry-bulb temperature is noticed to be muchcolder compared to the MVS run, resulting in higher
relative humidity but lower equivalent potential temperature. The meridional equivalent potential temperature gradient is larger in the lower troposphere and,speculatively, more favorable for baroclinic instability
in the MS run, and organized upward motion is evident
at the latitudes (not shown). The large cloud cover inthe MS run, however, does not bring precipitation to
the surface, only keeping temperatures cooler at thesurface and in the lower troposphere by reducing thesolar radiation. Cloud cover is smaller in MVS (Fig.
8d), except only at midsummer in the higher latitude
north of 75°N. It may be argued that at latitudes 50°–
70°N, baroclinic instability is less favored and upward
motion is weak, likely attributed to smaller meridionaltemperature gradients for the most areas. The low-levelcloud distribution reproduced in each simulation wasconsistent with the ambient conditions regarding thebaroclinic instability and upward motions. However,the cloud representation of the AGCM has a systematic
bias as noted before, which implies some insufficiencies
in the cloud parameterization or large-scale condensation. The warm bias of surface air temperatures, discussed in section 3, may also be related to the cloudparameterization, to some extent. Further investigation
will be needed to examine the robustness of the above
results and discussion. In early spring (March to April),the northward shift of the synoptic activities starts earlier and at higher latitude in the MVS run, in accordance with earlier snowmelt in the region as discussed
shortly.

b. Snow hydrology in Siberia
In this section we look at impacts on the seasonal
cycle of the snow hydrology in a region between 50°
and 80°N and 80° and 140°E, defined as Siberia. Figure
9 shows the monthly change, starting in August, of total
precipitation, solid precipitation (snowfall), snowmelt,
and accumulated snow-water equivalent (snow depth).

652

JOURNAL OF HYDROMETEOROLOGYVOLUME 7

FIG. 8. (a)–(d) As in Fig. 5, but for percentage of low-level cloud cover (surface to 680 hPa) between 40° and
80°N. Contour interval is 5, beginning at 10%. (e) As in (a) but for monthly low cloud cover from ISCCP.

The presence of large-scale Asian orography significantly altered the total and seasonal distribution of precipitation over extratropical Eurasia. Without mountains the seasonal cycle of precipitation has only a small
amplitude, with higher winter precipitation (all in solidform). The maximum snow accumulation is deeper by aquarter than with the mountains (MR). In spring, snowfall ends early and snowmelt is faster, leading to ashorter snow accumulation season in the NMR case.
The impact of vegetation is apparent on snow hydrology in the extratropical continent, and the influence ofvegetation skin is dominating especially from late winter to spring. Snow accumulation is lower in the MVS

run than in the MS or MR runs because temperatures
are warmer in late summer/early autumn, resulting inlater snow accumulation (Fig. 9d). Snowmelt starts earlier in MVS, reflecting warmer lower-tropospheric air
temperatures with vegetation (cf. Figs. 5b–d). This isparallel to the early peak both in snow-water equivalentand in snowmelt by two pentads (Figs. 9c,d). After
snowmelt starts, precipitation (liquid or solid) in the
MVS run becomes higher than in the other two (MSand MR) runs. This enhanced precipitation is consistent with the faster northward displacement of synoptic-scale disturbances shown in Fig. 8d. The impact ofsoil is largely seen in summer, as precipitation amountAUGUST 2006

653

SAITO ET AL.

FIG. 9. (a) Monthly total precipitation (mm month⫺1) for NMR (thin solid), MR (dotted),
MS (dashed), and MVS (solid). (b) As in (a) but for snowfall (mm month⫺1). (c) As in (a) but
for snowmelt (mm month⫺1). (d) As in (a) but for snow-water equivalent (mm).

almost doubles with soil layer (Fig. 9a). This is further
examined in the next section.

6. Sources of water vapor in precipitation
Land surface conditions altered the amount of total
precipitation on the global scale. The global mean of
annual total precipitation is 996, 986, 1031, and 1024
mm for NMR, MR, MS, and MVS runs, respectively(Table 1). This includes the changes over ocean andland. Percentage of total precipitation that falls overland (open surface without permanent ice or snow
cover occupies 25.6% of the total area) is 14.8%,
15.0%, 17.4%, and 21.7%, respectively, showing small
increase with the presence of large-scale orography andlarge increase with vegetation. The total amount of annual evaporation from the land surface shows a similar
result; respective percentages are 8.9%, 9.0%, 13.1%,
and 16.2%. Comparison between MR, MS, and MVS
shows a good agreement with the results of Milly andDunne (1994) that annual land evaporation has ahigher sensitivity to the water-holding capacity (theirFig. 12). This result illustrates an impact of land surface
condition changes on global redistribution of water.
This section examines the impacts on water vapor

transport at different land areas in Eurasia and othercontinents.
Tracking of “tagged” water vapor was used to quantify the relative contributions of water vapor comingfrom different sources that precipitates in an arbitrarytarget region. The methodology that had been used in aprevious version of the AGCM was used in this study(Numaguti 1999), which followed the similar tagging
methods used in other previous studies (Koster et al.
TABLE 1. Area-averaged precipitation and evaporation for the
globe, land (open-surface land, 25.6% in area), and ocean (71.4%
in area). The percentage value to the global total is given inparentheses.
Total precipitation (mm)
NMR

MR

MS

MVS

Globe
996.
986.
1031.
1023.
Land 574. (14.8%) 578. (15.0%) 698. (17.4%) 867. (21.7%)
Ocean 1181. (84.6%) 1165. (84.4%) 1184. (82.0%) 1114. (77.7%)
Total evaporation (mm)
NMR

MR

MS

MVS

Globe
996.
986.
1031.
1023.
Land
346. (8.9%)345. (9.0%) 527. (13.1%) 645. (16.2%)
Ocean 1268. (90.9%) 1255. (90.9%) 1252. (86.7%) 1200. (83.7%)

654

JOURNAL OF HYDROMETEOROLOGY

FIG. 10. Schematic presentation of water vapor tracing andwater recycling.

1986, 1993; Bosilovich and Schubert 2002; Bosilovich etal. 2003). Figure 10 illustrates the motion of tagged vapor that ultimately precipitates in a target region in
Eurasia. The evaporating water molecules are taggedwith the “source” region, either from the land or ocean
surface, and are subsequently advected following the
calculated flow. Large-scale condensation and cumulus
convection both form liquid water in an air parcel at
each vertical level according to condensation conditions. It is assumed that the air is well mixed in theparcel so that the parcel contains water masses fromdifferent sources in proportion to the amount of vapor
tagged with the “source” regions. Reevaporation issimilarly considered. Water vapor that most recently
evaporated from ocean surface (oceanic source) isshown in gray in the figure and vapor from land surface(land source) is shown in black. The globe is divided
into five oceanic (Arctic, Pacific, Indian, Atlantic, andSouthern) and seven continental (Greenland, Northand South America, Africa, Oceania, Antarctica, andEurasia) source regions as illustrated in Fig. 11. Relative contributions of the above 12 source regions inprecipitation in a target region are computed by relative amounts of water vapor tagged with the sources(thick arrows in Fig. 11).
The primary impetus for tracing water vapor in continental precipitation was to investigate the relative impact of land surface conditions on the importance ofground surface to bring water inside continents. Recycling is a term used to refer to precipitation in which thevapor was evapotranspired at the same region (Brubaker et al. 1993; Eltahir and Bras 1996). Our interest iswhether the precipitating water came directly fromocean surfaces or from land surfaces, and it is of little
interest if it came from the same area. The term “recycling,” or “continental recycling,” in this study is therefore defined as precipitated water vapor that evaporated from a continental source region, regardless ofdefinitions of geographical extent of target regions.
Model data spanning 10 yr after a 2-yr spinup period

VOLUME 7

FIG. 11. Source regions for surface evaporation. There are fiveoceanic regions (1: Arctic, 2: Pacific, 3: Indian, 4: Atlantic, and 5:
Southern) and seven land regions (6: Greenland, 7: North
America, 8: South America, 9: Africa, 10: Oceania, 11: Antarctica,and 12: Eurasia).

during which the model comes into equilibrium wereused from all four simulations. The result of this versionof the AGCM was substantially the same with the results of the previous version (Numaguti 1999). We also
compared precipitation pattern and recycling ratio of
our model’s result with that of Brubaker et al. (1993)
for their four regions, that is, western Eurasia, Mississippi, Amazon, and Sahel. The model reproduced themonthly precipitation in each region reasonably well, as
compared with the result of Brubaker et al. and CMAP
observation, except for known biases in Eurasia andAmazon (cf. Fig. 10 in Part I). Note that our respective
source regions for the above four regions are Eurasia,
North America, South America, and Africa, having
much wider geographical extent than in Brubaker et al.
Therefore, direct comparison of recycling ratio is difficult. The simulated annual mean recycling ratio is 12%,44%, 44%, and 47% for western Eurasia, Mississippi,
Amazon, and Sahel, respectively, while the corresponding values obtained by Brubaker et al. were 11%, 24%,
25%, and 35%. The reproduced seasonal cycle of recycling ratio is reasonable, although our estimate tends tobe higher for the above reason (not shown).

a. Changes in sources of vapor in rainy season
Figure 12 shows the changes in the averaged relative
contribution of major vapor sources in precipitation at
the five target regions of our interest in or near Eurasia
for the rainy season. The five regions are Maritime
Continent (10°S–8°N, 90°–160°E), south and Southeast
Asia (8°–25°N, 65°–110°E), east Asia (25°–45°N, 110°–145°E), Siberia (50°–80°N, 80°–140°E), and West Africa (0°–20°N, 20°W–10°E). The rainy season at theseregions is defined in Table 2 in Part I.
In the Maritime Continent and the Tropics (Figs.
12a,b), the oceans remain the primary source of water

AUGUST 2006

SAITO ET AL.

655

FIG. 12. (a) Averaged precipitation over the Maritime Continent (Indonesia) for March–May (closed circle), andthe percentage of water vapor coming from different source regions. Lines with square (diamond, cross) symbols
denote a source from Oceania (Indian, Pacific). Scale of the precipitation (percentage) is shown at top (bottom).
(b) As in (a), but for south/Southeast Asia for June, July, and August. (c) As in (b), but for east Asia. Line withsquare symbols denotes Eurasian source. (d) As in (c), but for Siberia for June–September. Line with triangle
symbols denotes the Atlantic source. (e) As in (d), but for West Africa for July, August, and September. Line withsquare symbols denotes African source.

vapor for precipitation, despite change in the amount of
total precipitation. Contribution ratios are insensitive
to land surface boundary changes because oceansourced convective rain dominates. In the extratropicalcontinent, to the contrary, vegetation almost doubles
total precipitation, with local (continental) source increasing more than twice (red line with square symbols
in Fig. 12d) whereas the oceanic sources (Atlantic andPacific) decrease by one-third. Large-scale topography
has little influence on summer precipitation in Siberia.

The results for the temperate eastern coastal area (Fig.
12c) are intermediate to the responses in tropical andhigh-latitude areas. The Pacific contribution is insensitive to the land surface changes. The contribution fromthe land (Eurasia) increases and that from the Indian
Ocean decreases in east Asia as the mountains and vegetation are added.
The West Africa area shows a similar response tothat of Siberia regarding precipitation amount and vapor source composition to vegetation in that the conti-

656

JOURNAL OF HYDROMETEOROLOGYVOLUME 7

FIG. 13. Annual change of composition of water vapor from different source regions in precipitation over east
Asia for (a) NMS, (b) MR, (c) MS, and (d) MVS. Solid (dashed, thin solid) line denotes percentage of water vapor
coming from the Pacific (Indian, Eurasian) region.

nental contribution increases while the oceanic sources
decrease. However, the Tibetan Plateau shows a different impact. Presence of the large-scale orographystrengthens descent through changes in the Rossby
wave pattern generated by the Tibetan orography andthe increased diabetic heating (Rodwell and Hoskins
1996), to decrease total rainy-season precipitation by 60
mm in JJA, and the local vapor source by one-third.

b. East Asia
Figure 13 shows the impact of land surface conditions
on the major sources of water vapor precipitates out ineast Asia. The Pacific Ocean is the primary source
throughout the year regardless of the surface conditions. The comparable contribution from other source
regions is the Indian Ocean for the summer monsoon
period. It increases as the mountains and vegetation areadded. Continental contribution is not large for all thecases, although it increases in spring as the land surface
conditions approach the present-day state.

c. Siberia
Summer is the season when recycled water vapor isthe major vapor source for precipitation in Siberia(Brubaker et al. 1993; Numaguti 1999). Our result in
Fig. 14 and in previous sections indicates vegetation isimportant in enhancing the continental recycling, withthe vegetation skin and the soil layer having comparable impacts in our model. In winter, when biosphericactivities are inactive, little impact is found from vegetation. Topography, in turn, shows a discernible impact during winter. The major vapor source remains the
Atlantic Ocean, accounting for about 80% of the total
water molecules in all the cases. The Indian source becomes comparable to the Pacific for the NMR run, although it becomes negligible when blocking mountains
are present.
All the simulations with mountains (MR, MS, and
MVS runs) show a large interannual variation in thewinter transport. A circulation anomaly is associatedwith this interannual variation, showing a positive zonal
wind anomaly between 30° and 50°N and a negative
anomaly between 50° and 70°N when the Atlantic contribution is anomalously small. The interannual variability is not found for the NMR run, which implies adynamical mechanism possibly involving orographicallygenerated eddies and position or strength of the tropospheric jet stream. This issue is left to future investigations.

7. Discussions and summary
A series of simplistic simulations using an AGCM
coupled to a simple land surface scheme quantitatively

AUGUST 2006

SAITO ET AL.

657

FIG. 14. As in Fig. 14, but over Siberia. Solid (dashed, dotted, thin solid) line denotes percentage of water
vapor coming from the Pacific (Indian, Atlantic, Eurasian) region.

and qualitatively evaluated the relative impacts of basic
factors in land surface conditions (i.e., large-scale orography, soil, and vegetation) on the hydroclimate of Eurasia. This study provides useful information regarding
the basic land surface properties and their potential
impacts that comprise basic parts of the present-day
continental hydroclimate. It was decided to use a
simple land surface scheme setting for this study because we attempted to draw a picture of the basic hydroclimate mechanisms related to the land surface conditions evaluated by the same configuration. A sophisticated scheme may obscure our intention by its
complexity, which may interfere with the drastic setting, and the spread of the parameter space. However,it must be acknowledged that the result of the study
may suffer from the insufficiency in the land hydrology
scheme. Although our land surface scheme is improved
from the original bucket-type hydrology scheme(Manabe et al. 1965) to include or consider some vital
components of physiological–hydrological processes,
simplistic treatment may still distort the water balanceat surface as demonstrated in the Program for Intercomparison of Land Surface Parameterization Schemes(PILPS; Shao and Henderson-Sellers 1996) or otherstudies (e.g., Sato et al. 1989) for the standard bucket
model. Therefore, the results of this study need be examined with caution in mind, and too-minute interpretation of absolute value comparisons may be inappropriate.

The model ocean in this study was prescribed frommonthly climatological sea surface temperatures (SSTs)
and sea ice concentrations. Recent studies have shownthat changes in land surface conditions, such as orography, change the SST distribution through radiative
and thermodynamic feedbacks between atmosphereand ocean (e.g., Kitoh 2002; Abe et al. 2004). For example, Abe et al. (2004) used a coupled atmosphere–
ocean GCM to show that summer SST distributions in
the Tropics are sensitive to a gradual decrease in surface elevation over the globe. As mountain heights decrease, SSTs in the west-to-central equatorial Pacificwarm to 31°C. Several factors influence the increase,including suppressed upwelling due to weaker surface
winds, an increase in solar radiation due to decreased
cloud cover, and suppressed convection associated withthe removal of orography. Other studies have suggested that the intensity of atmospheric response is
weaker when it is forced by prescribed rather than interactive SSTs (e.g., Waliser et al. 1999; Fu and Wang
2004).
By using identical ocean boundary conditions in allmodel experiments, the fluctuations induced by oceanic
variability are suppressed and the more subtle effects ofland surface conditions can be evaluated. In addition,
Abe et al. (2004) suggested that the influence of aninteractive ocean is highest over the ocean and near thecoasts. Continental interiors are more isolated. However, including an interactive ocean is an important fu-

658

JOURNAL OF HYDROMETEOROLOGY

ture research topic in this type of investigation as wellas upgrading the biosphere–hydrology scheme in a continuous way. Another issue on improvement is subgridscale land hydrology (e.g., Gedney and Cox 2003). Inclusion of realistic runoff, and river and subsurface water discharge into the oceans is desired to close ahydrological cycle. More elaborate evaluations using
output from a fully coupled atmosphere–ocean–landmodels will be necessary to evaluate more thoroughly
the quantitative impacts of land surface changes.
Major results of Part II include the following. Landsurface conditions had impacts on land precipitation on
global scale; the global mean of annual total precipitation was 996, 986, and 1024 mm for NMR, MR, and
MVS runs, respectively. A stronger impact was noticed
on the percentage of precipitation that falls on landarea (occupying 25.6% of the total surface). It was
14.8%, 15.0%, and 21.7%, and similarly, the percentageof land evaporation was 8.9%, 9.0%, and 16.2%, respectively. On the global and annual scale, vegetation
showed a greater effect on the hydrological balance
than the Asian mountains in our simulation. At regional and seasonal scales, however, large-scale orography and vegetation gave different impacts on themagnitude and distribution of energy and water cycle indifferent regions in different seasons. The summer hydroclimate in the Eurasian extratropical continent wassensitive to vegetation. In winter, mountains’ impact
overrode any atmospheric circulation changes.
Combined results from both parts of this study
showed that the current hydroclimate of the earth haslargely been shaped by an integrated system of land
surface processes, within a range of properties of relatively long time scale, such as large-scale orography andvegetation. The presence of large-scale topography increased the atmospheric heating by the turbulent heat
fluxes from the surface and strongly altered atmospheric circulation to transport more water and energy
into the continental interior. Vegetation (soil and vegetation skin), although examined by a simple scheme,
further increased the surface available energy andadded small-scale features to the continental hydroclimate according to the vegetation type. It has recently
been demonstrated that improved biosphere–land surface schemes, resolving subgrid-scale biophysical processes of shorter time scale, reproduce more realistichydroclimatology (e.g., Xue et al. 2004). A fully
coupled atmosphere–ocean–land–biosphere model of afiner horizontal resolution with a sophisticated physiology–hydrology scheme will enable further examinations of more minute impacts of vegetation and subsequently its changes on continental hydroclimate, for example, water availability and its change, following theVOLUME 7

large-scale land-use changes such as deforestation orforest fires. This will be an ingenuous extension of ourinvestigation. In addition, an elaborate tracking of vapor transport has a potential to provide accurate information on the characteristics and sensitivity of vapor
transport to those changes. Coupling of the vapor
tracking with such a full model will derive information
useful for water resource management in the future.
These are the potential directions for future research.
Acknowledgments. The authors thank ISCCP andNASA Goddard Institute for Space Studies for providing climatology cloud data. The authors are grateful tothree anonymous reviewers for their constructive comments that improved the original manuscript.
REFERENCES
Abe, M., A. Kitoh, and T. Yasunari, 2003: An evolution of the
Asian summer monsoon associated with mountain uplift—
Simulation with the MRI Atmosphere–Ocean Coupled
GCM. J. Meteor. Soc. Japan, 81, 909–933.
——, T. Yasunari, and A. Kitoh, 2004: Effects of large-scale orography on the coupled atmosphere–ocean system in the tropical Indian and Pacific Oceans in boreal summer. J. Meteor.
Soc. Japan, 82, 745–759.
Bosilovich, M. G., and S. D. Schubert, 2002: Water vapor tracers
as diagnostics of the regional hydrologic cycle. J. Hydrometeor., 3, 149–165.
——, Y. C. Sud, S. D. Schubert, and G. K. Walker, 2003: Numerical simulation of the large-scale North American monsoon
water sources. J. Geophys. Res., 108, 8614, doi:10.1029/
2002JD003095.
Broccoli, A. J., and S. Manabe, 1992: The effects of orography on
midlatitude Northern Hemisphere dry climates. J. Climate, 5,1181–1201.
Brubaker, K. L., D. Entekhabi, and P. S. Eagleson, 1993: Estimation of continental precipitation recycling. J. Climate, 6, 1077–
1089.
Buol, S. W., F. D. Hole, and R. J. McCracken, 1997: Soil Genesis
and Classification. 4th ed. Iowa State University Press, 527
pp.
Charney, J. G., P. H. Stone, and W. J. Quirk, 1975: Drought in
Sahara: A biogeophysical feedback mechanism. Science, 187,
434–435.
——, W. J. Quirk, S. Chow, and J. Kornfield, 1977: A comparative
study of the effects of albedo change on drought in semi-arid
regions. J. Atmos. Sci., 34, 1366–1385.
Chen, G., 2004: A 10-yr climatology of oceanic water vapor derived from the TOPEX Microwave Radiometer. J. Climate,17, 2541–2557.
Delworth, T., and S. Manabe, 1988: The influence of potential
evaporation on the variabilities of simulated soil wetness andclimate. J. Climate, 1, 523–547.
——, and ——, 1989: The influence of soil wetness on nearsurface atmospheric variability. J. Climate, 2, 1447–1462.
Dirmeyer, P. A., 1998: Land–sea geometry and its effect on monsoon circulation. J. Geophys. Res., 103 (D10), 11 555–11 572.
——, and J. Shukla, 1996: The effect on regional and global cli-

AUGUST 2006

SAITO ET AL.

mate of expansion of the world’s deserts. Quart. J. Roy. Meteor. Soc., 122, 451–482.
Douville, H., F. Chauvin, and H. Broqua, 2001: Influence of soil
moisture on the Asian and African monsoons. Part I: Meanmonsoon and daily precipitation. J. Climate, 14, 2381–2403.
Eltahir, E. A. B., and R. L. Bras, 1996: Precipitation recycling.
Rev. Geophys., 34, 367–378.
Fu, X., and B. Wang, 2004: Differences of boreal summer intraseasonal oscillations simulated in an atmosphere–ocean
coupled model and an atmosphere-only model. J. Climate, 17,
1263–1271.
Gates, W. L., 1992: AMIP: The Atmospheric Model Intercomparison Project. Bull. Amer. Meteor. Soc., 73, 1962–1970.
Gedney, N., and P. M. Cox, 2003: The sensitivity of global climate
model simulations to the representation of soil moisture heterogeneity. J. Hydrometeor., 4, 1265–1275.
Hahn, D. G., and S. Manabe, 1975: The role of mountains in thesouthern Asian monsoon circulation. J. Atmos. Sci., 32, 1515–
1541.
He, H., J. W. McGinnis, Z. Song, and M. Yanai, 1987: Onset of the
Asian summer monsoon in 1979 and the effect of the Tibetan
Plateau. Mon. Wea. Rev., 115, 1966–1995.
Henderson-Sellers, A., P. Irannejad, K. McGuffie, and A. J. Pitman, 2003: Predicting land-surface climates—Better skill or
moving targets? Geophys. Res. Lett., 30, 1777, doi:10.1029/
2003GL017387.
Jenny, H., 1941: Factors of Soil Formation; A System of Quantitative Pedology. Dover Publications, 281 pp.
Kitoh, A., 2002: Effect of large-scale mountains on surface climate—A coupled ocean–atmosphere general circulation. J.
Meteor. Soc. Japan, 80, 1165–1181.
Koster, R., J. Jouzel, R. Suozzo, G. Russell, W. Broecker, D.
Rind, and P. Eagleson, 1986: Global sources of local precipitation as determined by the NASA/GISS GCM. Geophys.
Res. Lett., 13, 121–124.
——, D. Perry de Valpine, and J. Jouzel, 1993: Continental water
recycling and H218O concentrations. Geophys. Res. Lett., 20,
2215–2218.
Kutzbach, J. E., W. L. Prell, and W. F. Ruddiman, 1993: Sensitivity of Eurasian climate to surface uplift of the Tibetan Plateau. J. Geol., 101, 177–190.
Luo, L., and Coauthors, 2003: Effects of frozen soil on soil temperature, spring infiltration, and runoff: Results from PILPS
2(d) Experiment at Valdai, Russia. J. Hydrometeor., 4, 334–
351.
Manabe, S., J. Smagorinsky, and R. F. Strickler, 1965: Simulated
climatology of a general circulation model with a hydrologic
cycle. Mon. Wea. Rev., 93, 769–798.

659

Milly, P. C. D., and K. A. Dunne, 1994: Sensitivity of the global
water cycle to the water-holding capacity of land. J. Climate,
7, 506–526.
Mitchell, T. D., and P. D. Jones, 2005: An improved method of
constructing a database of monthly climate observations andassociated high-resolution grids. Int. J. Climatol., 25, 693–712
Numaguti, A., 1999: Origin and recycling processes of precipitating water over the Eurasian continent: Experiments using an
atmospheric general circulation model. J. Geophys. Res., 104(D2), 1957–1972.
Rodwell, M., and B. Hoskins, 1996: Monsoons and the dynamics
of deserts. Quart. J. Roy. Meteor. Soc., 122, 1385–1404.
Sato, N., P. J. Sellers, D. A. Randall, E. K. Schneider, J. Shukla,
J. L. Kinter III, Y.-T. Hou, and E. Albertazzi, 1989: Implementing the Simple Biosphere model in a general circulation
model. J. Atmos. Sci., 46, 2757–2782.
Shao, Y., and A. Henderson-Sellers, 1996: Modeling soil moisture:
A project for intercomparison of land surface parameterization schemes phase 2(b). J. Geophys. Res., 101 (D3), 7227–
7250.
Shukla, J., and Y. Mintz, 1982: Influence of land-surface evapotranspiration on the Earth’s climate. Science, 215, 1498–1501.
Viterbo, P., A. Beljaars, J.-F. Mahfouf, and J. Teixeira, 1999: The
representation of soil moisture freezing and its impact on thestable boundary layer. Quart. J. Roy. Meteor. Soc., 125, 2401–
2426.
Waliser, D. E., K. M. Lau, and J. H. Kim, 1999: The influence of
coupled sea surface temperatures on the Madden–Julian oscillation: A model perturbation experiment. J. Atmos. Sci.,
56, 333–358.
Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year
monthly analysis based on gauge observation, satellite estimates, and numerical model outputs. Bull. Amer. Meteor.
Soc., 78, 2539–2558.
Xue, Y., H.-M. H. Juang, W.-P. Li, S. Prince, R. DeFries, Y. Jiao,
and R. Vasic, 2004: Role of land surface processes in monsoon development: East Asia and West Africa. J. Geophys.
Res., 109, D03105, doi:10.1029/2003JD003556.
Yanai, M., and C. Li, 1994: Mechanism of heating and the boundary layer over the Tibetan Plateau. Mon. Wea. Rev., 122,
305–323.
——, ——, and Z. Song, 1992: Seasonal heating of the Tibetan
Plateau and its effects on the evolution of the Asian summer
monsoon. J. Meteor. Soc. Japan, 70, 319–351.
Yasunari, T., K. Saito, and K. Takata, 2006: Relative roles oflarge-scale orography and land surface processes in the globalhydroclimate. Part I: Impacts on monsoon systems and theTropics. J. Hydrometeor., 7, 626–641.