Journal of Basic & Applied Sciences, 2015, 11, 637-644
637
A Study of Anomalous Wet and Dry Years in the Winter
Precipitation of Pakistan and Potential Crop Yields Vulnerability
S. Sarfaraz1,* and Tariq Masood Ali Khan2
1
Pakistan Meteorological Department, Karachi, Pakistan
2
Institute of Environmental Studies, University of Karachi, Karachi, Pakistan
Abstract: Pakistan experiences distinctively large rainfall variability on spatial as well as temporal scales. On spatial
scale the rainfall variability is mainly caused by its peculiar topographic features encompassing from south to north of the
country. On the other hand the temporal rainfall variability sometimes exceptionally large, does affect the climate of the
country that in turn impacts the climate-dependent sectors like agriculture, hydroelectric power generation and ecology.
In this study the 30-year winter season (December-March, DJFM) rainfall data of 35 meteorological sites of Pakistan
have been analysed to identify the anomalous wet and dry years, their potential impact on crop yields across Pakistan
and vulnerability of climate. The National Centre for Environmental Prediction (NCEP), US reanalysis data are used to
investigate the association of the surface and upper air atmospheric circulation features responsible for anomalous
wetness and dryness. This study may prove of some help for an improved winter rainfall prediction tool and better
management of available water resources viz-a-viz optimal crop yields production.
Keywords: Winter rains, Anomalous wetness/ dryness, NCEP reanalysis, Agriculture yields.
1. INTRODUCTION
Precipitation and temperatures are the two best
manifestation of climate of an area with rainfall
variability being a crucial feature of climate. The
changes in global rate and precipitation distribution
may have a greater effect on human well-being and
ecosystem dynamics than changes in temperature
itself [1]. Climatic signal is said to originate mainly from
winter precipitation and is robust over ecologically
different sites. The rainfall variability occurs over a wide
range of temporal and spatial scales and an
understanding of such variability can be of
considerable
importance
for
improved
risk
management practices in agricultural and other
industries [2]. Precipitation variability over a particular
period across any area gives an insight to the climate
and climatic change of that area.
Pakistan, exhibiting a markedly diversified climate,
has mostly hot and dry climate in the south, temperate
in northwest and arctic in the north. Summer
temperature in the south rise over 50°C and winter
temperature in the north fall below -20°C [3]. It
experiences mainly two rainy seasons summer
monsoon (July - September, JAS) and winter season
(December - March, DJFM) [4-5]. Annual area weighted rainfall of Pakistan is 238 mm. Of which
summer contributes 140.9 mm (about 57%), winter
share is 74.9 mm (about 30%) and 25.6 mm (13%) is
*Address correspondence to this author at the Pakistan Meteorological
Department, U/Road, Karachi-75270, Pakistan; Tel: +92 21 99261408;
Fax: +92 21 99261405; E-mail: s.abuammar26@gmail.com
ISSN: 1814-8085 / E-ISSN: 1927-5129/15
contributed by the rest, like convective thunderstorms
[3]. The crop yields in the rain-dependent areas have
been typically less than half of those in areas with riverfed irrigation during deficient years [6]. The years 1987
and 1994 saw a drastic reduction of wheat crops
principally due to a failed winter rainfall season [7]. The
Thal (Punjab province) region’s main winter crop grams
is being adversely affected by shortening of winter and
expansion of summer seasons [8]. During 1998-2002
the country faced a shortage of 26%-30% in wheat
production due to a severe drought [9]. Similarly the
rivers’ discharge was noted to have been reduced by
25% due to 20%-30% less rainfall over the period
1998-2004 [10]. Another study revealed that the overall
extent of negative impact of temperature was greater
than the positive effect of rainfall on agriculture in the
Potohar region of Pakistan [11]. Pakistan’s two main
crops wheat and maize are largely dependent on the
winter (DJFM) and summer (monsoon, JAS) rainfall
respectively. In rain-fed areas like Potohar Plateau it is
the amount and frequency of rainfall coupled with its
distribution on temporal and spatial scales which
dictates the terms for maize crop. Excess or deficit rain
badly affects the grain yield especially at early and
reproductive stage of corn maize [12]. Erratic rains at
the time of harvesting and threshing adversely affected
the grain quality and to some extent lower the yield.
Generally, wheat crop is vulnerable to many threats like
diseases (rusts), aphid, fluctuation in temperature,
drought spell and canal water non-availability [13]. BBC
report “Climate-Asia” [14] too describes that erratic
rainfall is damaging crops and reducing access to
water for drinking and irrigation, while increases in
© 2015 Lifescience Global
638
Journal of Basic & Applied Sciences, 2015 Volume 11
pests and mosquitoes have an effect on both
agriculture and the health of people and livestock.
Rezaie et al., [15] confirmed that rainfall variability is
critical for agricultural yields in Iran. If the pattern of
precipitation from the time of planting onward is
unknown, farmers are unable to tune their cropping
systems to optimize resources. A study on Indian
agriculture and climate change impacts demonstrated
that changes in the temperature, solar radiation, and
precipitation will have an effect on crop productivity and
livestock agriculture [16]. Climate change will also have
an economic impact on agriculture, including changes
in farm profitability, prices, supply, demand, trade and
regional comparative advantages [16].
The winter season (DJFM) precipitation in
southwest Asia is brought about by eastwardpropagating
mid-latitude
cyclones
from
the
Mediterranean region [17]. These weather systems
named western disturbances (WDs) are often observed
as closed lows on mean-sea level chart or upper-level
troughs over Iran, Afghanistan and Pakistan moving
east/ northeast-wards. Developing basically over the
Mediterranean and Atlantic seas the WDs pass
between Latitude 30 °N and 60 °N so as to cause
formation of the secondary lows over southeast Iran
and south/ southwest Pakistan which by dragging in a
warm moist air from the Gulf of Oman and north
Arabian Sea cause precipitation across Pakistan.
Over the past few years an uneven and erratic
rainfall occurrence is seen most common over Pakistan
i.e. some years bringing largely excessive rains like last
five consecutive flood years due to above normal JAS
rainfall, and some years with largely deficient rains
leading to drought episodes, e.g. 1998 – 2002 famous
drought which had adversely affected whole southwest
Asia with Pakistan suffered a shortage of 26%-30% in
wheat production [9]. It is now well documented that
the prolonged persistent drought of 1998-2002 was
primly caused by the forcing in the Pacific and Indian
Oceans, related to a combination of
1.
anomalously cold SSTs in the eastern equatorial
Pacific ocean leading to prolonged and
protracted La Niña (temperatures below than
normal),
2.
an unusual above-normal warming in the eastern
Indian / western Pacific oceans and
3.
Indian Ocean precipitation extension, said to be
inversely linked to south west Asia winter rainfall,
Sarfaraz and Khan
inhabiting the main centre of cyclonic activity [1820].
The anomalous wet and dry episodes are not
actually the stand-alone events rather resulted by some
remote atmospheric and oceanic forcing. Various
researches have been carried out to investigate the
wet/dry episodes’ occurrence and their association with
NCEP/NCAR (National Centre of Environmental
Prediction/National Centre for Atmospheric Research)
re-analysis data [21-23 and many others not quoted
here]. Hence the present study too used the NCEP/
NCAR re-analysis data [24] to investigate about the
atmospheric features association with anomalous wet
and dry episodes.
With this backdrop it seems imperative to discern
the anomalously wet and dry years in Pakistan winter
rains, diagnose about the forcing behind them and
potential linkage to crops vulnerability. We use 30-year
seasonal rainfall data of 35 data sites obtained from the
PMD, identify the wet and dry years, investigate about
the atmospheric forcing responsible and see whether
and how much crops yield is affected with anomalous
wetness and dryness. Figure 1 shows the location of
data sites used in the study. The detail of data sites
climate is given in the Annexure. This paper is
structured into 5 sections with data and methodology
covered in section 2, results in section 3, discussion in
section 4 and conclusion in section 5.
2. DATA AND METHODOLOGY
The monthly rainfall datasets of 35 data sites for 30year period (1976-2005) have been obtained from the
climate data processing centre (CDPC) of Pakistan
Meteorological Department (PMD). The 35 stations well
spread over Pakistan represent the whole country
reasonably well. The data used are a quality-controlled
data by the PMD’s climate data processing section
which regularly publishes and broadcasts it. The 30year time span is selected because it conforms to the
World Meteorological Organization (WMO) criteria that
a 30-year time characterizes the climate of a particular
region. The monthly total rainfall is aggregated over
four months, December through March, to obtain the
seasonal total rainfall for each station and then
averaged for whole Pakistan. The wettest and driest
th
years are characterised by the two thresholds, 90 and
th
10 percentiles respectively. The wet (surplus) and dry
(deficient) years are identified by finding out the
positively and negatively anomalous years [16]. The
±1.0 anomalies have been chosen as these values
A Study of Anomalous Wet and Dry Years in the Winter
Journal of Basic & Applied Sciences, 2015 Volume 11
639
Figure 1: The data sites location across Pakistan.
account for 50% above (+1.0) or below normal (-1.0)
rainfall. The surplus (with +1.0 and greater anomaly)
and deficient years (-1.0 and less anomaly) are shown
in Table 1.
We extracted the composite anomalies of mean
sea-level pressure and meridional and zonal winds at
middle and upper atmospheric levels (Figures 3 and 4)
from the NOAA- ESRL (National Oceanic and
Atmospheric Administration- Earth System Research
Laboratory) website using the link http://www.esrl.
noaa.gov/psd/cgi-bin/data/composites/printpage.pl to
identify the prevalence of weather patterns to find out
the linkage among wet and dry spells and the
associated circulation patterns over Pakistan and
surrounding region. Given that a seasonal aggregate
precipitation is actually resulted by combining effects of
the atmospheric circulations at mean-sea-level, mid
(500 mb) and upper-tropospheric (200 mb) levels;
hence these levels of fields are selected for the present
study.
3. RESULTS
th
th
By applying the 90 and 10 percentiles technique
and standardised anomaly calculation to all 30-year
seasonal total rainfall data we have identified the five
wettest and driest years. The years with large anomaly
of +1.0 (or greater) and -1.0 (or lesser) are given in
Table 1. The worth noting point is that there are three
consecutive years in each category i.e. 1990-92, the
wet (surplus) years and 1999-2002, the deficient (dry)
years.
The graphical depiction given in Figure 2, evidently
shows that there were 16 positive anomalies, four
consecutive years of 0.5 to 1.0 anomalies around early
80s, two of same magnitude in mid-80s, three of even
greater magnitude 1.5 to 2 around early 90s followed
by another large positive anomaly in the year 2005.
While ten negative anomalous (indices of -1 to -1.7)
years can be spotted with 1984-85 and 2000-02 being
largely deficient years.
Table 1: Five Surplus (+1.0 and Greater Anomaly) and Deficient (-1.0 and Less Anomaly) Years
Surplus years
Anomaly standardised
Deficient years
Anomaly standardised
2004/05
2.2
2000/01
-1.7
1990/91
2.0
1984/85
-1.4
1991/92
1.4
1999/00
-1.2
1989/90
1.3
1976/77
-1.2
1980/81
1.0
2001/02
-1.1
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Journal of Basic & Applied Sciences, 2015 Volume 11
Sarfaraz and Khan
From a meteorological point of view the abnormally
wet and dry period across a region is actually a
manifestation of prevalence of some particular
atmospheric circulation features over there.
3.1. Wet Years’ Anomalous Features
Figure 2: Pakistan winter
standardised rainfall indices.
season
(DJFM)
30-year
Figure 3(a-e) exhibits the composite anomalies of
sea level pressure (SLP), zonal and meridional wind
(m/s) at 500 mb and 200 mb levels for identified wettest
years. Figure 3a depicts a significant negative anomaly
of -0.5 to -1 mb spreading from east of the Caspian
Sea down to southwest Afghanistan and then
Figure 3: a: SLP (hPa) composite anomaly-wet. b: U(m/s) 500 mb composite anomaly-wet. c: U(m/s) 200 mb composite
anomaly-wet. d: V(m/s) 500 mb composite anomaly-wet. e: V(m/s) 200 mb composite anomaly-wet.
A Study of Anomalous Wet and Dry Years in the Winter
northeast-wards to the Central Asian States. This
feature is indicative of frequent passing of anomalously
low-pressure systems over the area during wet years
resulting in unusual wetness. Figure 3b depicts a
positive anomaly of 0.6-1.4 m/s in zonal winds flow at
mid-tropospheric level (500 hPa) spreading over the
North Arabian Sea, Arabian Gulf, most of Saudi Arabia
and south Iran, which strongly suggests that a steep
wind gradient was prevalent which caused a
pronounced moisture transport from ocean in to
southeast Iran and southwest Pakistan. Figure 3c
Journal of Basic & Applied Sciences, 2015 Volume 11
641
depicting the 200 mb zonal wind anomaly shows the
persistence of positive anomaly of 1-2 m/s over north of
Saudi Arabia extending up to Iran and to southwest
Afghanistan, means that there existed an anomalous
jet stream flowing from southwest carrying the moisture
into Iran and south Afghanistan.
Considering the meridional (vertical) wind structure
at 500 mb (Figure 3d) we observe a marked positive
anomalies of 0.5-1.0 m/s over most of Pakistan, the
Persian Gulf and further down over south Red Sea and
Figure 4: a: SLP (hPa) composite anomaly-dry. b: U(m/s) 500 mb composite anomaly-dry. c: U(m/s) 200 mb composite
anomaly-dry. d: V(m/s) 500 mb composite anomaly-dry. e: V(m/s) 200 mb composite anomaly-dry.
642
Journal of Basic & Applied Sciences, 2015 Volume 11
east Africa implying that there was a strong southerly
flow causing the moisture inflow from Gulf and
formation of deep trough in mid-troposphere over
Pakistan. At 200 mb the meridional wind with a positive
anomaly of 0.5 to 1.0 m/s (Figure 3e) over
north/northwest Pakistan, Afghanistan and central Asia,
which would have given rise to the jet stream.
These features at surface, mid and upper
atmosphere indicate that during wet years there was
more passage of low-pressure systems across
Pakistan supported by strong horizontal and vertical
wind gradients at mid and upper tropospheric levels
which ultimately would have caused an enhanced
moisture incursion from the North Arabian Sea and
Gulf and hence resulting in abnormal wetness.
3.2. Dry Years’ Anomalous Features
The anomalies' plots of the atmospheric fields for
dry (or deficient) years are shown in Figure 4(a-e).
Figure 4a shows a positive anomaly of 0.5 to 1 mb in
SLP prevailing over northeast Afghanistan and
northwest Pakistan with eastward extension which is a
feature quite contrary to that observed in wet years’
case (Figure 3a). This means at mean-sea level there
was no favourable condition for the formation of lowpressure systems. The zonal wind anomalies of -0.5 to
-1.5 m/s at 500 mb and 200 mb (Figure 4b, c) are
observed spreading over a planetary scale from lat.
10°N to 26°N and long. 30 - 125°E, meaning there was
absolutely no horizontal wind gradient which ultimately
led to an abnormally stable atmosphere. The
meridional wind anomalies at 500 mb (Figure 4d) are
observed with strong and significant negative
anomalies of -0.6 to -1.2 m/s spreading over the entire
Arabian Sea, most of Iran, Pakistan, Afghanistan, India
and central Asian states. This is suggestive for
prevalence of northerly flow and unusually high
subsidence of the air, entirely opposite to what we
observed in case of wet years. At 200 mb (Figure 4e)
the situation is materially no different with a strong
negative anomaly of -1 to -2.5m/s over most Pakistan
and extending northwards to Central Asia, while two
positive anomalies of 2-2.5 m/s far too east over south
China and in west over northeast Saudi Arabia to
cause any effect over the study-area, Pakistan. These
features contributed to the situation where at mean-sea
level there was no passage of low-pressure systems
across Pakistan and Afghanistan and upper-air flow
was directed from the north instead of west/ southwest
which led to unusual subsidence and hence the
dryness.
Sarfaraz and Khan
4. DISCUSSION
The analysis of Pakistan 30-year winter rainfall data
shows the 10 largely abnormal or anomalous years, i.e.
five surplus (wet) years and five deficient (dry) years
(Table 1). This is an indication that Pakistan
experiences a considerable inter-annual rainfall
variability and the winter rainfall is greatly influenced by
regional and global atmospheric parameters (Figures 3
and 4). Various studies documented that the failed
winter rainfall has resulted in a reduced wheat (a cash
crop) and other winter crops production coupled with a
reduced rivers discharge across Pakistan which
ultimately affected the water supply for irrigation down
the stream [7-10]. Likewise a study conducted on the
climate change impact on agriculture has documented
that 95 percent farmers in the arid region of northern
Pakistan are of the view that temperature increase and
rainfall decrease is the main cause in changing climate
with rains have been dried up causing dramatic
changes in the agriculture productions [11-13]. The
results vindicate wheat crop high sensitivity to the
changing climatic conditions and that a decreasing
rainfall coupled with increasing temperature has
alarming effects on wheat production.
For some areas in the west and southwest Pakistan
the winter rain is more important as they receive their
40% to 80% rains during the DJFM season with no
considerable monsoon rain, evident from the long term
climatic average rainfall of individual data stations
(Annexure), so its failure means an enhanced risk of
drought-like
situation
there.
Wintertime
solid
precipitation contributes to snow accumulation over
Pakistan mountainous region in the north which feed
the rivers Indus and Shyok basins contributing more
than 25% of the inflow to Tarbela Dam [25] which is the
main controlling structure for the Indus basin irrigation
system and country’s major power production unit. The
inflow to another big reservoir and power generating
unit ‘Mangla Dam’ comes through a river Jhelum
whose basin located in the same terrain is also fed by
winter snow and perennial ice during the summer
season; vital for irrigation and hydropower production in
the region [26].
The NCEP/NCAR reanalysis suggests that a
persistence prevalence of the anomalous tropospheric
pressure pattern at 200 hPa (4-year-averaged) spread
over entire mid-latitudinal belt from west to east
suppressed the cyclonic activity over the area.
Resultantly the oceanic forcing which caused the
change in temperatures, wind and atmospheric
circulations led to unusual protracted drying.
A Study of Anomalous Wet and Dry Years in the Winter
Journal of Basic & Applied Sciences, 2015 Volume 11
5. CONCLUSION AND FUTURE PLAN
We can therefore conclude that a careful analysis of
the past uneven episodes of anomalous wetness
(dryness) with exploration of responsible atmospheric
forcing can lead to a better climate elements’ prediction
and hence an improved assessment of potential impact
on agriculture yields. Such attempt may prove helpful in
better management of available water resources in the
wake of excess (deficit) rainfall episodes. Future plan is
to enhance this study by analysing such data over
longer periods, say 60/ 90-year, and with considering
more atmospheric circulation features like outgoing
643
longwave radiation, OLR, surface air temperatures,
moisture influx and sea surface temperatures (SSTs)
etc. and also for the anomalous monsoon (summer,
July-September, JAS) season over Pakistan.
ACKNOWLEDGEMENT
The authors are grateful to the PMD for providing
the 30-year winter rainfall data and the NCEP/NCAR
reanalysis project for using their data to investigate
about the atmospheric forcing responsible for
anomalous dryness and wetness.
ANNEXURE
Information on WMO Index Number, elevation, location (Lat and Long), Mean winter rain, Mean minimum temperature
and mean maximum temperature of the Meteorological stations used in study
No
WMO Index
Number
Elevation
Lat.
a.s.l (m)
(° N)
Long. (°E)
Mean winter
rain (mm)
Mean Temp.
(Tmin°C)
Mean
Temp.(Tmax°C)
Chitral
Gilgit
Astore
Skardu
Dir
Balakot
Peshawar
Parachinar
Islamabad
Murree
Muzaffarabad
Jehlum
Sialkot
41506
43516
43520
43517
41508
41536
41530
41560
41571
41573
43532
41598
41600
1499
1459
2167
2209
1369
980
359
1725
507
2167
701
232
251
35° 51'
35° 55'
35° 22'
35° 18'
35° 12'
34° 23'
34° 01'
33° 52'
33° 37'
33° 55'
34° 22'
32° 56'
32° 30'
71° 50'
74° 20'
74° 54'
75° 41'
71° 51'
73° 21'
71° 35'
70° 05'
73° 06'
73° 23'
73° 29'
73° 43'
74° 32'
248.3
26.7
193.0
99.3
616.9
518.2
170.4
270.6
256.7
518.6
361.8
174.7
170.2
1.0
0.1
-4.6
-4.2
-0.4
4.1
6.6
0.7
5.2
1.8
5.5
7.7
7.5
34.1
34.3
25.4
29.5
30.7
32.5
37.0
26.5
35.2
22.5
35.0
36.8
36.0
14
Lahore
41640
15
Sargodha
41594
213
31° 33'
74° 20'
105.7
8.9
36.9
187
32° 00'
72° 07'
21.0
6.9
16
Mianwali
41598
----
209
32° 35'
71° 32'
27.7
---
---
17
D.I.Khan
18
Zhob
41624
173
31° 49'
70° 55'
62.7
5.9
38.6
41620
1405
31° 21'
69° 28'
105.6
2.3
19
35.2
Quetta
41660
1600
30° 15'
66° 53'
191.2
-1.0
34.3
20
Barkhan
41685
1097
29° 53'
69° 43'
73.4
4.7
35.3
21
Sibbi
41697
133
29° 33'
67° 53'
44.8
9.0
42.6
22
Kalat
41696
2015
29° 02'
66° 35'
83.2
-1.8
-----
23
Dalbandin
41712
848
28° 53'
64° 24'
60.7
4.5
40.3
24
Khuzdar
41744
1231
27° 50'
66° 38'
88.5
5.9
36.0
25
Panjgur
41739
980
26° 58'
64° 06'
57.6
6.3
38.1
26
Faisalabad
41630
183
31° 26'
73° 06'
65.9
7.2
37.5
27
Multan
41675
122
30° 12'
71° 26'
43.1
7.8
39.4
28
Bhawalpur
41700
116
29° 24'
71° 47'
29.9
8.6
39.6
29
Khanpur
41718
87
28° 39'
70° 41'
18.7
7.4
39.8
30
Sukkur
41724
66
27° 42'
68° 54'
21.0
11.3
40.7
1
2
3
4
5
6
7
8
9
10
11
12
13
Name of Station
31
Jacobabad
41715
55
28° 18'
68° 28'
24.2
10.8
40.6
32
Nawabshah
41749
37
26° 15'
68° 22'
9.3
9.0
40.8
33
Hyderabad
41764
40
25° 23'
68° 25'
12.2
13.9
38.5
34
Karachi
41780
21
24° 54'
67° 08'
31.9
13.1
33.5
35
Jiwani
41756
56
25° 04'
61° 48'
90.9
15.8
32.6
644
Journal of Basic & Applied Sciences, 2015 Volume 11
Sarfaraz and Khan
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Received on 29-09-2015
Accepted on 02-12-2015
Published on 31-12-2015
http://dx.doi.org/10.6000/1927-5129.2015.11.85
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