Evaluation of cloud seeding project in Yazd Province of Iran using historical regression method (case study: Yazd 1 cloud seeding project, 1999)

doi:10.4236/ns.2013.59124

Paper Menu >>

Journal Menu >>

Vol.5, No.9, 1006-1011 (2013) Natural Science

http://dx.doi.org/10.4236/ns.2013.59124

Evaluation of cloud seeding project in Yazd Province

of Iran using historical regression method

(case study: Yazd 1 cloud seeding project, 1999)

Mojtaba Zoljoodi*, Ali Didevarasl#,†

Atmospheric Sciences and Meteorological Research Center (ASMERC), Tehran, Iran;

†Corresponding Author: [email protected]

Received 9 June 2013; revised 9 July 2013; accepted 16 July 2013

tion License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly

cited.

ABSTRACT

In this research, the result of the cloud seeding

over Yazd province during three months of Feb-

ruary, March and April in 1999 has been evalu-

ated using the historical regression method.

Hereupon, the rain-gages in Yazd province as

the target stations and the rain-gages of the

neighboring provinces as the control stations

have been selected. The rainfall averages for the

three aforementioned months through 25 years

(1973-1997) in all control and target stations have

been calculated. In the next step, the correla-

tions between the rainfalls of control and target

stations have been estimated about 75%, which

indicates a good consistency in order to use the

historical regression . Then, through the obtai ne d

liner correlation equation between the control

and target stations the precipitation amount for

February, March and April in 1999, over the tar-

get region (Yazd province) was estimated about

27.57 mm, whiles the observed amount was 34.23

mm. In fact the precipitation increasing around

19.5% over Yazd province confirmed the suc-

cess of this cloud seeding project.

Keywords: Cloud Seeding Project; Target and

Control Stations; Histo rical Regression Method;

Yazd Province

1. INTRODUCTION

Water is one of the most basic commodities on earth

sustaining human life. In many regions of the world, how-

ever, traditional sources and supplies of ground water,

rivers and reservoirs, are either inadequate or under threat

from ever-increasing demands on water from changes in

land use and growing populations. In many countries,

water supplies frequently come under stress from droughts

and increase pollution in rivers, resulting in shortages and

an increase in the cost of potable water. Ground water

tables have been steadily decreasing in many areas around

the world where ground water is one of the primary

sources of freshwater [1]. This is particularly evident in

most parts of Iran. To help alleviate some of these stresses,

cloud seeding for precipitation enhancement has been

used as a tool to help mitigate dwindling water resources.

The first usually considered question after a cloud

seeding operation is that “how much was the effect of

this operation in rainfall increasing?” impact assessments

of the cloud seeding were regarded from the initial seed-

ing operations all around the world. The results derived

through seeding of the stratus clouds that usually don’t

result in rainfall, are controllable by in situ observations

or by using the radar based watch [2]. Whiles the impacts

of convective cloud seeding, especially in the case of

natural rainfall, often are hidden. Only a small part of the

available moisture in clouds is transformed into precipi-

tation that reaches the surface [3-6]. This fact has prompted

scientists and engineers to explore the possibility of aug-

menting water supplies by means of cloud seeding.

The ability to influence and modify cloud microstruc-

ture in certain simple cloud systems such as fog, thin

layer clouds, simple orographic clouds, and small cumu-

lus clouds, has been demonstrated and verified in labo-

ratory, modeling, and observational studies [7].

Australia has a long history of cloud seeding research

and operations, with initial investigations occurring about

60 years ago. Between 1955 and 1959, the Snowy Moun-

tains were the focus of an aircraft-based cloud seeding

*Associate professor and chairman of ASMERC.

#Senior expert of ASMERC.

M. Zoljoodi, A. Didev arasl / Natural Science 5 (2013) 10 06-1011 1007

experiment run jointly by the Commonwealth Scientific

and Industrial Research Organization (CSIRO) and the

Snowy Mountains Hydro-Electricity Authority (SMHEA).

From this experiment, Smith et al. (1963) reported a 19%

precipitation increase in seeded events; however, despite

these encouraging results cloud seeding over the Snowy

Mountains was not pursued [8].

A feasibility study by Shaw and King (1986) assessed

the potential for cloud seeding over the Snowy Moun-

tains as positive [9]. This study considered meteorology-

cal and cloud physics data over the region as well as the

ecological, community and wider-area effects of cloud

seeding. Further evaluation of the physical and chemical

characteristics of the clouds and snowfall over the region

during the winters of 1988-1989 [10] supported the find-

ings of Shaw and King (1986) [9].

In 1993, SMHEA drafted an Environmental Impact

Statement (EIS) proposing a six-year cloud seeding ex-

periment over a 2000 km2 area of the Snowy Mountains

[11]. This experiment did not proceed because of object-

tions from key stakeholders. An independent expert panel

report, addressing the principal objections that had been

raised in 1993, was submitted to the New South Wales

(NSW) government in 2003. The Snowy Mountains Cloud

Seeding Trial Act (NSW) was passed in 2004 allowing

Snowy Hydro Limited (SHL) to undertake a six year

winter cloud seeding trial—the Snowy Precipitation En-

hancement Research Project (SPERP). The objectives of

SPERP are to determine the technical, economic and

environmental feasibility of precipitation enhancement

over the main range of the Snowy Mountains. In the sci-

entific community weather modification is still viewed as

a somewhat controversial topic. Changnon and Lambright

(1990) identified several problems and difficulties that

have arisen during the conduct of weather modification

experiments [12]. According to Changnon and Lambright,

based on their analyses of the National Hail Research

Experiment and the Sierra Cooperative Pilot Program

(SCPP), the major scientific controversies were a result

of six factors. These factors were 1) proceeding with an

inadequate scientific knowledge base; 2) a flawed pro-

ject-planning process; 3) differing views between fund-

ing agencies and project scientists; 4) lack of continuing

commitment by the principal agency conducting the ex-

periment; 5) changes in project directors; and 6) poor

performance by project scientists. Because of the com-

plex nature of precipitation enhancement experiments, it

is extremely important to funding agencies, water man-

agers, and scientists that current experiments are criti-

cally reviewed in terms of these six factors in order to

avoid repeating the mistakes listed above.

The results derived from two cloud seeding experiences

over Israel have been presented by Nirel and Rosenfeld,

1996 and 1995 [13,14]. They evaluated the results of cloud

seeding operation by using logarithmic models during

these two periods 1961-1967 and 1970-1975, and then

confirmed a precipitation increase around 13% to 15% in

the target region.

In Iran, some studies have already been developed on

evaluation of cloud seeding operations. Regarding the

reports of the “Iran National Research Centre of Cloud

Seeding Studies” in Yazd province, the cloud seeding

project in 2008-2009 over Zagros mountain chain resulted

in an increase of precipitation about 18.9%. Meantime

the results of cloud seeding over 2008-2009 in central

plain of Iran indicated 19.5% of precipitation increase.

Through an impact assessment study on cloud seeding

operation over Gavekhoni Watershed (in central Iran) in

Feb 2010, using historical regression method, an increase

of precipitation about 46.4% has been estimated [15].

Khalili et al. (2009) took under consideration the results

derived through cloud seeding operations in Iran during

1999-2007 [16]. Based on their analyzes, the cloud seed-

ing operations over central parts of Iran caused increase

of seasonal precipitation around 22% - 40%.

2. MATERIALS AND METHODS

To estimate the effect of seeding it is necessary to es-

timate the long-range average of seeded precipitation in

the contracted target, a sample of which is directly

available, and also the similar long-range average of

what would have fallen without seeding, for which no

direct data exist. Thus, this latter estimation must be in-

direct and involves two arbitrary choices. One is the

choice of the so-called “historical period” when there

was no seeding. The other is the arbitrary choice of the

so-called “control” area. The reader will notice that the

precise meaning of “target” and “control area” is two sets

of rain gauges functioning in the two localities. When

these two choices are made, the observed historical pre-

cipitation amounts, averaged over gauges in the target

and in the control areas, are used to estimate the linear

regression equation of the historical target precipitation

on that in the control. Next, this historical regression line

and the operational period’s precipitation in the control

are used to estimate the mean precipitation in target to be

expected without seeding.

In this work we have applied the historical regression

method to find the success or un-success of the cloud

seeding over Yazd province in 1999. The historical re-

gression, is recounted the most usual applicable method

to assess the cloud seeding results. This method is based

on principal factors which would be affected by cloud

seeding (such as: precipitation or snow). Data series of

the principal factors through a long term (for example 25

years) should be analyzed.

For data gathering in this regard we chose two groups

of rain gages as target and control stations. The control

M. Zoljoodi, A. Didev arasl / Natural Science 5 (2013) 10 06-1011

1008

stations should be selected from the regions as fare as

possible out of cloud seeding operation region/target

region, but whiles should be representative of the same

climate of the target region.

Historical data series of precipitation in both target and

control regions are over a period before seeding opera-

tion. These two data series (which of target and control

regions) have been analyzed to obtain a regression rela-

tionship between them to estimate the precipitation amount

in the target region over the period of seeding operation

without taking in account the seeding affect. Then the

estimated precipitation, observed and the long term av-

erage are compared to find the amount of precipitation

increase in target region. The equation below shows the

regression relationship:

Yt = aYc + b

Yt: estimated precipitation of target region

Yc: actual precipitation of control region

The coefficients of (a) and (b) are determined using

historical precipitation data series before seeding opera-

tion through quantification of square error method.

Using of this method is recommended as there is a

well correlation between the long term data series of the

target and control regions. Climate similarity of target

and control regions will result in a high correlation. For

evaluating of precipitation, correlation coefficient (r) equal

to >0.9 is appropriate. This research aims to study the

derived results from cloud seeding project at 30 Jan to 29

Apr 1999 over Yazd province.

3. POSITION OF THE STUDY AREA, AND

SELECTION OF TARGET AND

CONTROL STATIONS

In this research, we used the data series of meteoro-

logical stations and rain gages over Yazd province through

1973-1997. Table 1 shows the position and founding

time of these stations. We selected in total 19 stations and

rain gages over our target region (Yazd province).

Among these selected 19 stations, Dihook and Saghand

stations are ignored because of the limitation in statistical

period that is less than 15 years. Thus 17 stations over

Yazd province (an area about 125,000 km2) as the target

stations for this project are taken in account. Yazd prov-

ince placed in the central Iran is widely rough, as the

elevations vary between 1000 m to 4000 m throughout

this region. Spatial variation of precipitation over Yazd

province is very high, as in the central regions the annual

rainfall amount ranges 50 mm to 60 mm, whiles, the

western and southwestern regions of this province re-

ceive annual rainfall between 300 mm to 400 mm. Rain-

fall period in this region usually lasts 8 months, from Oct

to May, however 90% and 67% of it’s total precipitation

respectively events during Dec to May, and Jan to Apr

(Figure 1).

The control stations selected should have maximum

climate similarity with the target region, as having a high

correlation between their precipitations is necessary (Fig-

ure 2). In the Tabl e 2 you can see the information of the

13 selected control stations. The geographic position of

all selected target and control stations on the study area

are illustrated through Figure 3.

Table 1. Selected target stations in Yazd Province.

Stations LatLon Elevation Founding time

Mohamad abad 31.4754.25 1250 1971

Yazd 31.5454.17 1236 1952

tabass 33.354.55 791 1960

Dihook 33.1757.31 1100 1962

Abarkooh 31.0053.17 1500 1964

Ardekan 32.1954.01 1400 1966

Baigan 31.3755.5 1400 1966

Ghatroom 31.2355.4 1500 1966

Hajiabad zarrin 33.0954.51 1100 1966

Kharanegh 32.2054.40 1000 1966

Khoidak 31.354.3 1300 1966

Robat posht badam 33.0255.10 1200 1966

Saghand 32.3355.11 1350 1966

Taft 31.4554.14 1590 1966

Hajiabad kariz 31.2054.00 2000 1967

Dehshir 31.2053.44 1900 1967

Hosseinabad rastagh32.1454.12 1050 1967

Mazraeh noo 32.2453.29 1350 1967

Nasrabad pishkooh 31.4753.52 2050 1967

Table 2. Selected control stations in the neighboring provinces.

Stations Lat Lon Elevation Founding time

Varzaneh 32.26 52.39 1470 1968

Esfahan 32.39 51.39 1585 1968

Neistan 32.58 52.47 1870 1971

Varzaneh2 32.26 52.39 1250 1956

Mobarakeh 31.04 52.49 2050 1965

Peykan 32.13 52.10 1300 1965

Yazd abad 32.43 52.44 2200 1965

Garmeh 33.32 54.59 950 1966

Bayazeh 33.20 55.20 1450 1968

Shahre babak 30.07 55.09 1890 1961

Raver 31.15 56.33 1290 1961

Boshroyeh 33.52 57.25 885 1970

bovanat 30.28 53.4 1990 1971

Figure 1. Monthly precipitation averages in Yazd province

(1973-1997).

M. Zoljoodi, A. Didev arasl / Natural Science 5 (2013) 10 06-1011 1009

Figure 2. Monthly precipitation averages in the control region

(1973-1997).

Figure 3. Position of the selected target and control stations in

the study area.

4. RESULTS

As mentioned before, the period of implementing this

could seeding project is during 30 Jan to 29 Apr 1999

over Yazd province. Thus in order to obtain a regression

relation between long term average of precipitation of

control and target stations, the long term precipitation

averages for Feb, Mar and Apr in two target and control

regions before seeding operation (1973-1997) have been

calculated and used.

The Figure 4 compares the long term precipitation

variations of two control and target regions in 3 afore-

mentioned months over 1973-1997. As it is evident by

the graph below we can expect to find a high correlation

between these two regions regarding precipitation varia-

tions.

By using the long term average of precipitation in two

target and control regions the below regression equation

has been obtained:

Y = 0.722x − 0.389

Figure 5 illustrates the linear correlation of precipita-

tion for two study regions during 25 years. The correla-

Figure 4. Yearly variations of the average precipitation of 3

months (Feb, Mar and Apr) during 1973-1997, in the target and

control regions (respectively blue and red curves).

Figure 5. Linear correlation of average precipitation of 3

months (Feb, Mar and Apr) between control and target regions

during 1973-1997.

tion rank is estimated about 75%, which indicates the

fact that the control stations appropriately have been se-

lected.

Figure 6 shows the observed, estimated and long term

average precipitations in our target region, comparing

them gives interesting information about the result of

seeding operation.

Through the obtained regression equation, the rainfall

amount in target region over Feb-Apr 1999, has been

estimated about 27.57 mm, whiles comparing to the ob-

served rainfall amount that was 34.23 mm, we found an

increase of rainfall around 19.46% through cloud seeding

in Yazd province.

5. CONCLUSIONS

Cloud seeding is recounted one of operational and

emergency ways to coup with drought as well as water

shortage over a specific period and a given region. Im-

plementation of cloud seeding project and increasing of

rainfall amount considerably depend on cloud sort (for

example the conductive clouds are suitable to be seeded)

and atmospheric conditions. Yazd 1 project was a cloud

seeding operation in Yazd province over February, March

and April of 1999, that was operated by Iran National

Center of Cloud Seeding Researches and Studies. We used

M. Zoljoodi, A. Didev arasl / Natural Science 5 (2013) 10 06-1011

1010

Figure 6. Long term average precipitation (1973-1997), esti-

mated precipitation (for Feb, Mar and Apr of 1999), and ob-

served precipitation (over Feb, Mar and Apr of 1999) in Yazd

province.

the regression method for evaluating the results of this

project. For this purpose the meteorology stations and the

rain gages were selected from Yazd province as target

region, and neighboring provinces as control regions.

Through linear correlation analysis between precipita-

tions of two target and control regions over a 25-year

period (1973-1997), we found a high compatibility for

them (with a correlation rank around 75%) that indicates

a good linear relation to estimate the rainfall amount for

target region over Feb, Mar and Apr of 1999, so we es-

timated the rainfall around 27.57 mm. whiles, the long

term rainfall average was 16.57 mm and observed amount

was 34.23 mm.

This evaluation implies the success of the Yazd 1 pro-

ject. As comparing to the estimated rainfall, we had a

considerable increase of precipitation around 19.46%.

Usually cloud seeding operation is developing for dif-

ferent objectives regarding the target region conditions,

any way in a dry-semi dry country such as Iran cloud

seeding operation basically aims to water resources man-

agement in drought period and irrigating of dry farming.

Thus we suggest developing such projects for other parts

of the country along with pro-feasibility studies of could

seeding, in order to coup with water shortage.

Although the main objections are raised against the

use of the historical regression method for the evaluation

of the influence efficiency. First of all, the problem of the

stability of Eq.2 under conditions of microclimatic changes

arises. The period of cloud seeding activities may differ,

in principle, from the preceding period, in particular, due

to the change in frequency of various types of synoptic

situations, which can be characterized by various regres-

sion coefficients between target and control area precipi-

tation [17]. Another probability of the origin of differ-

ences, connected with time is possibly, the difference in

microclimatic trends of target and control area precipita-

tion, however the origin of the differential trend is unlikely

in the case of the near location of the target and control

area [2].

REFERENCES

[1] Bruintjes, R.T. (1999) A review of cloud seeding experi-

ments to enhance precipitation and some new prospects.

Bulletin of the American Meteorological Society, 80, 805-

820.

doi:10.1175/1520-0477(1999)080<0805:AROCSE>2.0.C

O;2

[2] Kloskove, B.P. (2010) Statistical evaluation of results of

operative precipitation enhancement activities over large

areas using historical regression method. Russian Mete-

orology and Hydrology, 35, 265-271.

doi:10.3103/S1068373910040047

[3] Weather Modification Advisory Board (1978) The man-

agement of weather resources. Report to the Secretary of

Commerce, 2 Volumes.

[4] National Academy of Science (1966) Weather and climate

modification, problems and prospects. Vol. I. NASA/

NRC Publ.1350, Washington DC, 39 p.

[5] National Academy of Science (1966) Weather and climate

modification, problems and prospects. Vol. 2. NASA/

NRC Publ. 1350, Washington DC, 210 p.

[6] (1973) Weather and climate modification, problems and

prospects. NASA/NRC, Washington DC, 258 p.

[7] American Meteorological Society (1992) Planned and

inadvertent weather modification. Bulletin of the Ameri-

can Meteorological Society, 73, 331-337.

[8] Smith, E.J., Adderly, E.E. and Walsh, D.T. (1963) Cloud-

seeding experiment in the snowy mountains, Australia.

Journal of Applied Meteorology, 2, 324-332.

doi:10.1175/1520-0450(1963)002<0324:ACSEIT>2.0.C

O;2

[9] Shaw, D.E. and King, W.D. (1986) Feasibility study to

assess the potential of a cloud seeding experiment over

the catchment of the Snowy Mountains Scheme. SIRO-

MATH Pty Ltd., Report.

[10] Warburton, W.J.A. and Wetzel, M.A. (1992) Field study

of the potential for winter precipitation enhancement in

the Australian Snowy Mountains. Atmospheric Research,

28, 327-363. doi:10.1016/0169-8095(92)90016-4

[11] Snowy Mountains Hydro Electric Authority (SMHEA)

(1993) Snowy precipitation enhancement project. Draft

Environmental Impact Statement.

[12] Changnon, S.A. and Lambright, W.H. (1990) Experimenta-

tion involving controversial scientific and technological

issues: Weather modification as a case illustration. Bulle-

tin of the American Meteorological Society, 71, 334-344.

doi:10.1175/1520-0477(1990)071<0334:EICSAT>2.0.CO

[13] Rosenfeld, D. and Nirel, R. (1996) Seeding effective-

ness—The interaction of the desert dust and the southern

margins of rain cloud systems in Israel. Journal of Ap-

plied Meteorology, 35, 1502-1510.

doi:10.1175/1520-0450(1996)035<1502:SEIODD>2.0.C

O;2

[14] Nirel, R. and Rosenfeld, D. (1995) Estimation of the ef-

fect of operational seeding on rain amounts in Israel.

Journal of Applied Meteorology, 34, 2220-2229.

M. Zoljoodi, A. Didev arasl / Natural Science 5 (2013) 10 06-1011

1011

doi:10.1175/1520-0450(1995)034<2220:EOTEOO>2.0.C

O;2

[15] Iran National Research Centre of Cloud Seeding Studies

(2010) Enhancement of water extraction over Gavekhoni

watershed through cloud seeding operation.

[16] Khalili Sr., M., Seidhassani, M., Golkar, F. and Khatibi, V.

(2009) Results of cloud seeding operations for precipita-

tion enhancement in Iran during 1999-2007. National

Cloud Seeding Research Center, Yazd.

[17] Neyman, J. (1967) Experimentation with weather control.

Journals of the Royal Statistical Society, Series A, 130,

285-326.