京 都 大 学 防 災 研 究 所 年 報 第48号 C 平成17年3月
Annuals of Disas. Prev. Res. Inst., Kyoto Univ., No. 48C, 2005

Numerical Estimation for Greening Effect over the Desert in Saudi Arabia

Yu HOZUMI* and Hiromasa UEDA
*COE Researcher, DPRI, Kyoto University
Synopsis
Greening effect over the desert in Saudi Arabia was estimated by a meteorological numericalmodel (MM5) with sophisticated land surface model (LSM). It is pointed out that the regional
climate after greening by grassland vegetation changes rainfall amount increased by +65%.
However, latent heat flux, LHF, largely increases in arid season, and increases a little in wet season.
Evergreen needle tree was found to suppress LHF by 50% ~74% compared with grassland
greening. As a result with estimation for the net rainfall, greening only around a mountainous areawith needle tree can keep positive net rainfall even in arid season.
Keywords: greening desert, land surface model, net rainfall

1.

Introduction

Desertification over the world is one of the mostproblems in the global climate, and especially in water
resource, because population explosion predicted in the
future may cause water shortage. Greening desert is achallenging way to improve the water shortage. This
technique of greening desert, arid, or semiarid region has
been applied to several regions, but the improvement by
this technique seems to be difficult not only due totechnical measure for greening, but also the complex
feedback among a regional climate, surface condition,and underground aspect. The project of greening coastal
desert over the western coast of Saudi Arabia
commenced, that was supported by MEXT. This area isdivided to the hot desert climate by the Köppen
classification, and covered by large scale anticyclone orlarge scale subsidence mainly in summer (Taha et al.,
1981; Subyani, 2004). Rainfall over southwest Saudi
Arabia in summer is maintained mainly by thesouthwesterly wet flow, well known as the Indian
monsoon, and rainfall over northwest is almost only
identified in winter due to northwest flow or disturbance.

Fig. 1 shows the mean profile of temperature and relative
humidity, RH, for 22 years at Jeddah, and shows
seasonal characteristics in summer (Fig.1 (a)) and winter(Fig. 1(b)). The thick layer that consists of large scale
subsidence and dry westerly flow from North Africa arerepresented as dry warm region above 500hPa. On theother hand, the south-eastern wet flow from the Indian
Ocean reaches Jeddah in the limit below 850hPa.
Distributions of moisture and wind are represented by
Fig. 2. In winter season, however, cold and moistureflow from the Mediterranean prevails over the Red Seathat is touch with Jeddah, and bring about an extent ofmoisture to inland. the target area of greening was set to
the north region of Asir that is mountainous region along
the west coast includes Jeddah (coastal city), Mecca(sacred city), and Taif (mountainous city). Climate ofthis region is categorized as arid or semiarid, and rainfall
pattern varies with space and time. North Asir seems to
be classified to have wet season in winter same as otherarid or semiarid region in western Asia except for south
region in Arabian Peninsula that is affected by the Indian
monsoon. Additionally, mountainous area in Asir secures
an extent of rainfall because wet flows producecondensation due to lifting up along the slope of themountain. So rainfall in north Asir including
mountainous area seems to be occurred by the wet flow
mainly in winter.
Since long ago, response by modification of landuse
with extensive scale with mainly as deforestation has
been reported, namely cutting forests cause cloudformation and rainfall decrease, and also erosion andrunoff increase, such as the destruction of nature. As forgreening with regional scale less than about several
hundred kilometers square, effects of landuse
modification on rainfall are discussed in several studies
and areas (Anthes, 1984; Perlin and Alpert, 2001).
Anthes (1984) summarized the changes in physicalproperties and processes by greening soil land greaterthan about 100km2 with vegetation, and many properties
or processes receive various change, such as
evapotranspiration increasing, moisture retention
increasing, roughness increasing, and also infraredemission decreasing, maximum temperature decreasing,and Bowen ratio decreasing. However, greening effecton rainfall and cloud is identified as uncertainty response
because of the including complicated process andinteraction among large scale phenomena, micro scale
phenomena and processes around the ground. Numericalsimulation not only with considering large scaleatmospheric processes but also with solving surface
processes is one of the appropriate tool to describe thephysical processes that is changed by greening landuse.
Perlin and Alpert (2001) discussed the effects of landuse
modification with plantation and irrigating nearly
10,000km2 area from the shrubs and non-irrigatedagriculture on the dynamic processes of regional scaleconvection with planetary boundary layer (PBL) height,
and convective available potential energy (CAPE) overthe coastal region along the Mediterranean with using
numerical model, MM5, and they showed that rainfall
increased the PBL height when the disturbance movingfrom the Mediterranean because the maximum height of
PBL kept longer than the control run, PBL contained
more moisture, and finally CAPE keeps higher value
before rainfall event. So greening seems to change
directly the moisture amount and the radiation balance on
the surface.
One of the most difficult problems of greening desert
is that greening should be kept with wet canopy layer
including soil layer. This maintenance condition seems
to be greatly strict because of large amount of

evapotranspiration from the vegetation of greening, so
greening technique must be considered not only with
rainfall increase but also with evapotranspiration increase,and namely with the net rainfall, rainfall subtracted by
the evapotranspiration.
The purpose of this study is to estimate the net
rainfall for a long time to maintain the desert greening
with numerical experiment.
2.

Model Description and Methodology

3-D meteorological model, MM5, was introduced inorder to predict and estimate the greening effect overregional scale targeted area around north Asir.
2.1 Model description
MM5 had been developed by the Penn State
University and National Center for AtmosphericResearch (Dudhia, 1993, Dudhia, 1989), withnonhydrostatic primitive equations and sophisticatedphysical schemes for cumulus, radiation, boundary layer,
and explicit moisture. As for the initial condition andboundary condition, NCEP final analysis data with 1
degree as horizontal and 24 layers from surface to 50hPa
height as vertical resolutions and RTG SST data applied
from satellite data with 0.5 degree resolution wereadopted and landuse information by USGS was used.
Horizontal climate aspects were extracted from
NCEP data for 6 years, monthly horizontal distributionsof rainfall owed to satellite TRMM data, and surface andupper air observation data for about 20 years at someobservation points were used to discuss regional climate
around the target region.
2.2 Methodology
Fig.1 means map around the target area, and thetarget area that includes Jeddah, Mecca, and Taif ischosen as Fig. 1(b). Model domain is located at Middle
Western coast of Saudi Arabia, with the grid as 85 x 130
points of 5km interval. Vertical grid is consists of 40pressure sigma coordinate from surface to 50hPa, withlowest layer sigma as 0.001, nearly equivalent to 10m,on the other hand time step is fixed to 5s. Taif city isbedded on a mountain chain belonged to north Asir, andthe height of mountain reaches more than 2000m, andthis high mountain chain forms a steep slope from Mecca
to Taif. The distance between Taif and Jeddah is about
150km. Mainly physical schemes are selected as follow,

(a)

(b)

(a)

(b)

Fig. 2 Mean profile of temperature, RH, and wind in (a)summer and (b) winter at Jeddah.

(c)

(a)

(b)

Fig.1 (a) Global map around Asir, and shading meanswater bodies. Thick square means (b) model domain
including Jeddah, Mecca, Taif and Al-Baha, and squaresurrounded by dashed line means (c) greening area
indicated by darker shading along the mountain slope.
Table 1 Parameters in the vegetation type
Parameter
Albedo (%)
Moisture
Availability (%)
Emissivity (%)
Roughness (cm)Surface heat
capacity(106cal/m3K)

Barren orsparselyvegetation

GrasslandEvergreen
needle tree

25

23

12

5

30

60

85
10

92
10

95
50

1.20

2.08

2.92

CCM2 for radiation (Hack et al., 1993; Dudhia, 1989),
MRF scheme for boundary layer (Hong and Pan, 1996),
and Reisner graupel for explicit moisture, which issimilar to the mixed phase scheme but with a little
developed at the point of graupel and ice number
concentration prediction (Reisner et al., 1998), andcumulus scheme is not used for this study. Boundary
layer process includes the Noah land surface model,
Noah-LSM, with 1 canopy layer, 4 soil layer, andinteracting processes such as evapotranspiration,
infiltration, and runoff (Chen and Dudhia, 2001).
Numerical experiments were executed for present
situation (CTL Run) and greening situation that is shownin Fig.1(c) with greening area that is located above 800m
height by 100km x 10km, and vegetation types were set
to grassland with vegetation coverage of 60% (GRS
Run) and evergreen needle tree with vegetation coverageFig. 3 Seasonal distribution of RH and wind in (a)summer and (b) winter on 900hPa.
of 20% (NDL Run), on the other hand present type isalmost barren or sparsely vegetation in all the model
domain except for the sea surface. Main parameters areshown in Table 1.
The period of model experiments is from 1st
January to 1st March 2004, but 7 days period isprepared before the start time for analysis due to anumerical adjustment.
3.

Seasonal Aspects

There is little rainfall over Arabian Peninsula due tolarge scale subsidence laying the subtropical zone,
except for storm event coming from the Mediterranean(Taha et al., 1981), but seasonal variation in theatmosphere changes the arrangement of moisture under
the subsidence layer. Fig. 2 shows the seasonal profiles
for temperature and relative humidity at Jeddah. In
summer, it is confirmed that a strong stability layer (orsometimes a capping inversion layer) lays nearly from
500hPa to 400hPa and the lower troposphere keeps dry(Fig. 2(a)), which means the convection continued froma lower height that can converge moistures has
difficulty to go through this strong stability layer, so it is

(a)

(b)

Fig.6 Rainfall distribution in January 2004 by (a)TRMM and (b) model result.
(a)

(b)

(c)

(d)

Fig.4 Yearly accumulated rainfall distribution detectedby TRMM around north Asir. Characters of “J”, “M”,
“T”, and “A” mean Jeddah, Mecca, Taif, and Al-Baha,
respectively.

Fig.5 Rainfall characteristics summarized by (upper)
each year, (middle) each month, and (lower) year-monthat Al-Baha, which is shown in Fig.1(b).
usual situation that rainfall due to convective seems
hardly to occur. In winter (Fig.2(b)), however, wet layer
covers over the surface without the strong stability layer.
Fig.3 depicts moisture and wind distributions in(a)summer and (b)winter. Northwesterly wind, which is
not so wet, blows over the western coast of the Arabian
Peninsula in summer. However in winter, large scale
southeasterly wet flow comes into the Red Sea and theMediterranean wet flow also blows on this ocean, andthese flows converge around north Asir. These climate
aspects show convective rainfalls in winter havepossibility to occur easier than in summer. YearlyFig.7 Model comparison with observation data in
February 2004 at Jeddah. Upper panels mean timeseries for (a) temperature and (b) specific humidity at
2m height on the ground; solid lines mean model
results and circles show observation data, and lower
panels represent correlations for (c) temperature and (d)specific humidity, with regression lines.
accumulated rainfall distribution detected by TRMM isrepresented by Fig.4. Western coast including Jeddah
and Mecca shows little rainfall of nearly 100mm/year,
on the other hand, area near the top of mountain
including Taif has an extent of rainfall of nearly
600mm/year, and other region over mountainous chain
including Al-Baha shows nearly 300mm/year.
Fig.5 shows one example of climate aspects ofrainfall at Al-Baha, which is shown in Fig.1(b) and isaway from Taif by 150km and located on themountainous region. Yearly series rainfall variation
indicates that rainfall amount varies with age; theminimum peak is less than 100mm/yr and the
maximum peak is near 300mm/yr. Seasonal aspectoccurs by intermittently disturbances in additional toseasonal situation. Since next chapter effect of greening
desert in typical rainy month and dry month and discuss
the alternation of the net rainfall amount.
4.

Fig.8 Rainfall time series in the period of some events,
for CTL, GRS, and NDL Run over the greening area.
Table 2 Rainfall, Latent heat flux, and net rainfall
value over the greening area in January and February
2004.
LatentRainfall
Net Rainfall
Heat Flux(mm/mon) (mm/mon)(mm/mon)Jan CTL

61.4

11.6

+55.6

Jan GRS

89.6

29.5

+60.1

Jan NDL

87.2

21.8

+65.4

Feb CTL

0.46

6.6

-6.1

Feb GRS

0.80

65.2

-64.4

Feb NDL

0.72

33.0

-32.2

Fig.9 LHF daily series for a sunny day in 16th Feb, for
CTL, GRS, and NDL Run.
shows more rainfall not only in winter but also in springthat is transition season, and it is difficult to categorize
rainfall aspects with season, mainly because rainfall

Model Validation

Fig.6 displays monthly rainfall in January 2004 as
rainy season. TRMM data (Fig.6(a)) shows some spotty
events near mountain chain, but model result represents
these spots with hazy. This reason seems to owe to thedifference of the way to detect rainfall between TRMM
that catch only along a thin line and numericalcalculation that follows rain generations at each grid
points. It is confirmed, however, that the amount andcoarse distribution of rainfall from the model calculation
are similar to that from TRMM, so this simulation still is
worthy of analyzing to discuss physical processes
concerned with moisture distribution. In February 2004,
there was hardly rainfall, so other parameters werecompared to the observation data substitute for rainfall.
5.

Greening Effect

5.1 Effect on rainfall
In order to estimate the greening effect over thedesert in wet season and dry season, the period tosimulate was fixed as 2 month, January and February
2004. It is not satisfied to understand completely the
aspect of greening effect for the long ages as somedecades, including the variation of ENSO, or IOD, but it
is satisfied to estimate the local scale, or mesoscale
dynamical effect on the region for some months that
includes rainy season and dry season. As for this view,Jan 2004 is categorized as rainy season and Feb 2004 is
as dry season. Especially the period from 7th to 24th
January has some rain events, as shown by Fig.8. This
figure shows the change of rainfall intensities among thelanduse modification for each rainy event, but the change
seems to be small.
5.2 Effect on LHF and net rainfall
Table 2 represents total value of rainfall, latent heat
flux, and the net rainfall over the greening areal mean in
Jan 2004. Rainfall intensity enhances due to greening, by+28.2mm/mon with grassland, and by +25.8mm/monwith evergreen needle tree, compared to the natural valueof 61.4mm/mon, so enhancement ratios become +46%,

and +42%, respectively. The values of accumulated LHF
are converted to the values that are easier to comparewith rainfall value (mm/mon). LHF also increases after
greening, by the ratio of +154%, and +88%, respectively,
and the LHF after grassland greening has greater value
than the LHF after needle tree greening by 7.7mm/mon.
As a result, the net rainfall values both increase
compared to CTL Run by +8%, and +18%, respectively.
However in February, greening causes a little terrible andnegative effect, to become drier by –58.3mm/moncompared to CTL Run. This is due to the huge increaseof LHF after greening, especially grassland greening,
mainly because of dryness climate and large value of
evapotranspiration.
5.3 Landuse effect on LHF
Fig.9 shows an example of the variation of LHF insunny day in 16th February, 2 days after short rain event.
The each maximum value of LHF show drastic change
by landuse type, from 18W/m2 as CTL Run to 146W/m2
as GRS Run, on the other hand, LHF of NDL Run issuppressed compared with GRS Run as 72W/m2. The
net rainfall value after needle tree greening surpasses thatafter grassland greening by 5.3mm/mon, and this iscaused by the suppression of LHF as transpiration releasewith sparsely needle tree that has larger roughness lengththan grassland in Table 1.
6.

Estimate the Net Rainfall for A Year

Table 2 shows the net rainfall in January as rainyseason and February as dry season, and rainfall value inJanuary is not so much compared to other rainy season
with considering Fig.4 and Fig.5. Rainfall aspects of
Fig.5 is at the location that has nearly 300mm/year, andTaif that is near the top of mountain keeps nearly
600mm/year, so it seems to be the twice values of Fig.5
at Taif, namely monthly rainfall as 60mm/month isexpected usually. Under this consideration, and theconsideration that Al-Baha has totally 4 rainy months
and 8 dry months in a year, Taif seems to receive suchclimate as 4 rainy and 8 dry months. With thisassumption it is estimated that how is the change of
rainfall value after greening at Taif, with the net rainfall
value of 65.4mm/mon and –32.2mm/mon. The result of
this estimate becomes +4mm/year after needle greening.
This value means the climate around north Asir canaccept a kind of landuse change as greening without

dryness due to evapotranspiration, and also the surface
over the greening area keeps getting amount of moistureor water in every years. The net rainfall value of+4mm/year on the greening area with 1,000km2 means+4x106ton/year.
7.

Conclusions

Greening effect over the desert in Saudi Arabia that
contains dry climate especially in summer was estimatedby a meteorological numerical model (MM5) withsophisticated land surface model (LSM). Rainfall
variance is difficult to be fixed with categorized asseasonal characteristics, so it is decided to estimate intypical rainy and dry season, namely in January 2004 andFebruary 2004 in order to estimate the greening effect on
the net rainfall through a year. Greening area wasselected on the slope of the mountainous chain over thenorth Asir, with 100km x 10km above 800m height, andvegetation types for greening was set to grassland andevergreen needle tree with the vegetation coverage as60%, and 20%, respectively.
It is pointed out that the regional climate after
greening by grassland vegetation changes rainfall
amount increased by +65%. However, latent heat flux,
LHF, largely increases in arid season, and increases alittle in wet season. Evergreen needle tree was found to
suppress LHF by 50% ~74% compared to grassland
greening. As a result, estimated net rainfall values inselected months are 65.4mm/mon in rainy season and–32.2mm/mon in dry season. Roughly estimate for the
net rainfall through a year showed a little positive value
with the assumption for the rainfall climatology at Taifby +4mm/year that equals to 4x106ton/year over thegreening area, and this means that greening only arounda mountainous area with sparsely needle tree can keep
neutral or positive net rainfall even in arid area.
Acknowledgements
This work was supported by the DPRI’s 21st Century
COE Program of MEXT, Japan, and was a part of
RR2002 “Sustainable Coexistence of Human Nature andthe Earth” conducted by MEXT. We would like to thankDr. Ryoji Ohba with fruitful discussion, suggestion, andrainfall data at some points such as Al-Baha.

Perlin, N. and Alpert, P. (2001): Effects of land-use
modification on potential increase of convection: A
numerical mesoscale study over south Israel, Journal ofGeophysical Research, Vol.106D, pp.22621-22634.
Reisner, J., Rasmussen, R.J. and Bruintjes, R.T. (1998):
Explicit forecasting of supercooled liquid water inwinter storms using the MM5 mesoscale model,
Quarterly Journal of the Royal Meteorological Society,Vol.124B, 1071-1107.
Subyani, A.M. (1981): Geostatistical study of annual andseasonal mean rainfall patterns in southwest Saudi
Arabia, Hydrological Sciences Journal –Journal desSciences Hydrologiques, Vol.49, pp. 803-817.
Taha, M.F., Harb, S.A., Nagib, M.K. and Tantawy, A.H.
(1981): The climate of the near east. In: The Climate ofSouthern and Western Asia (Edited by K. Takahashi
and H. Arakawa), World Survey of Climatology, Vol.9,
pp.183-255, Elsevier Scientific, New York, USA.

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State-NCAR MM5 modeling system. Part I: Model
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Raach, P.J. and Williamson, D.L. (1993): Descriptionof the NCAR community climate model (CCM2),
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数値シミュレーションによる海洋性砂漠緑化の影響評価
穂積 祐＊・植田 洋匡＊

京都大学防災研究所COE研究員
要旨

サウジアラビア西海岸における海洋性砂漠緑化が水収支に与える影響を，気象モデルおよび洗練された陸面モデルを用いて評価した．山岳地域に施した緑化による気候場変化により，降水量は約65%増加した．しかしながら特に乾燥期には蒸発散量も大幅に増加することが判明したため，常緑針葉樹を緑化に適用した結果，蒸発散量を50%〜74%抑え，正味降水量を見積もったところ，年間を通した正味降水量が正になる可能性があることが判明した．

キーワード:砂漠緑化，陸面モデル，正味降水量

C-32

数値シミュレーションによる海洋性砂漠緑地化の影響評価〇穂積 祐・植田 洋匡

１．はじめに地球温暖化と砂漠拡大との関連が指摘される中，砂漠緑化の試みは生活空間や飲料水，農業水の確保のみならず，地球温暖化に対する一つの対策となる．これら砂漠緑化の必要性があるにもかかわらず，緑化対策はあまり進んでいないのが現状である．文部科学省 RR2002 の「人・自然・地
球共生プロジェクト」にて砂漠緑化対策への取り組みが行なわれており，本研究では海洋性砂漠の緑地化が環境場に及ぼす影響を，特に水収支に着目し，緑化維持について議論をする．
この緑化対象地域であるサウジアラビア西海

２．領域気象モデル
数値モデルは 3 次元非静力学領域モデル MM5
ver.3.6 であり，降水過程の再現が可能である．
水平格子はランベルト，間隔は 5km，鉛直は静水圧を基にした地形準拠座標で地表直上では約 10mの間隔である．インプットデータは NCEPfnl，
RTG-SST データであり，植生，土壌データはこれ
らのデータおよび AVHRR，USGS（米国地質調査院）
等のデータを用い，緑化時にはこれらを編集して用いた．環境場の再現期間は 2004 年の 1 ヶ月間
である．なお，海岸都市ジェッダにおける気象観
測と計算結果との比較では，再現された温度場の相関係数は 0.92，水蒸気場の相関係数は 0.74 であった．

岸は，年間降水量が 100mm〜200mm，被植率はほぼ 0%の領域が広がり海洋性砂漠を形成している．
緑化研究では緑化の維持がひとつの大きな課題となっているため，まずは緑化維持にはどのような環境である必要か，環境場は緑化によってどのように変わるのか，を評価する必要がある．

３．緑化による正味降水量の変化
2004 年 2 月におけるコントロール計算および
図１(a)の領域に緑化を施した後の計算における緑化領域での積算降水量を表 1 に示す．降水量は緑化により約 0.3mm/month 増加しているが，地表からの蒸発散による潜熱フラックスが急激に増大し正味の降水量は負値になっている．次に，
2 月および 1 月におけるコントロール計算および
図１の緑化領域における値（表１）から，針葉樹を緑化することで蒸発散量が抑えられること，および 1 月は典型的な雨季であり，正味降水量は緑化により増大することがわかる．
なお本研究は文部科学省 RR2002「人・自然・
地球共生プロジェクト」の援助を受けています．

図 1：数値モデル中での緑化領域（灰色）．(a)はジェッダ，メッカ，タイフを含む 100km×150km，(b)は山岳地域の 100km×10km．

降水量 R(mm/mon)

蒸発散量
LHF(mm/mon)R−LHF(mm/mon)2 月 Ctl

0.46

6.6

-6.1

2 月草地 a

0.76

67.6

-66.8

2 月草地 b

0.80

65.2

-64.4

2 月針葉樹 b

0.72

33.0

-32.2

１月 Ctl

61.4

11.6

+55.6

１月草地 a

67.3

47.6

+19.7

１月草地 b

89.6

29.5

+60.1

１月針葉樹 b

87.2

21.8

+65.4

表 1：コントロール計算および図１の緑化領域における積算降水量，蒸発散量，およびそれらの差．