Theor Appl Climatol (2012) 110:229–244
DOI 10.1007/s00704-012-0611-4
ORIGINAL PAPER
Changing structure of the precipitation process
during 1960–2005 in Xinjiang, China
Qiang Zhang & Jianfeng Li & Vijay P. Singh &
Chong-Yu Xu & Yungang Bai
Received: 2 September 2011 / Accepted: 13 February 2012 / Published online: 20 March 2012
# Springer-Verlag 2012
Abstract Using daily precipitation data spanning 1960–
2005 from 51 meteorological stations in Xinjiang province,
China, spatial and temporal changes in consecutive maximum wet days in the year, summer, and winter were investigated. Fifteen precipitation extreme indices, which reflect
the attributes of consecutive maximum wet days, were defined, and the modified Mann–Kendall test was applied to
detect the tendencies, and changes in the indices were
Q. Zhang (*) : J. Li
Department of Water Resources and Environment,
Sun Yat-sen University,
Guangzhou 510275, China
e-mail: zhangq68@mail.sysu.edu.cn
Q. Zhang : J. Li
Key Laboratory of Water Cycle and Water Security in Southern
China of Guangdong High Education Institute,
Sun Yat-sen University,
Guangzhou 510275, China
Q. Zhang : J. Li
School of Geography and Planning, and Guangdong Key
Laboratory for Urbanization and Geo-simulation,
Sun Yat-sen University,
Guangzhou 510275, China
V. P. Singh
Department of Biological and Agricultural Engineering and
Department of Civil and Environmental Engineering,
Texas A&M University,
College Station, TX 77843-2117, USA
C.-Y. Xu
Department of Geosciences and Hydrology, University of Oslo,
PO Box 1047, Blindern,
0316, Oslo, Norway
Y. Bai
Xinjiang Research Institute of Water Resources and Hydropower,
Xinjiang 830049, China
evaluated through linear regression with the F test. Results
showed that: (1) two consecutive wet days occurred most
frequently in the year and summer, and the fractional contributions and precipitation intensities decreased as the duration increased; in winter, one wet day had the maximum
possibility, fractional contributions decreased and intensities
increased as the duration increased. (2) The possibility of
consecutive wet days which had short durations reduced,
while those of long durations increased; annual fractional
contributions of short durations decreased, while those of
long durations increased; summer and winter fractional contribution of all durations decreased first and then increased;
the intensities of all durations increased. (3) The wet tendency was identified in Xinjiang; the wet trend in Southern
Xinjiang was more significant than Northern Xinjiang in
summer, while in winter the wet tendency in Northern
Xinjiang was more pronounced.
1 Introduction
Extreme hydroclimatic events, such as precipitation and
temperature extremes, floods, and droughts, can have significant environmental, societal, and even political consequences. It is therefore important to investigate changes in
the properties of these extreme events on regional and global
scales in the context of changing climate(Osborn et al. 2000;
Milly et al. 2002; Ramos and Martínez-Casasnovas 2006;
Mladjic et al. 2011; Min et al. 2011; Gemmer et al. 2011;
Zhang et al. 2009a, 2011a, b). It is believed that the projected global climate changes have the potential to accelerate the global hydrological cycle, triggering changes in
precipitation, runoff, and soil moisture (e.g., Alan et al.
2003). The accelerated hydrological cycle may further enhance uneven spatial and temporal distribution of water
230
resources and also the changing patterns of extreme weather
events in both time and space (e.g., Zhang et al. 2010a).
There are numerous studies addressing the changing features and underlying causes of precipitation extremes.
Groisman et al. (1999) indicated that the probability of daily
precipitation exceeding 50.8 mm in midlatitude countries
(USA, Mexico, China, and Australia) increased by about
20% in the later part of the twentieth century. Suppiah and
Hennessy (1998) pointed out that heavy precipitation events
in most parts of Australia have increased. Zhai et al. (1999)
found that the intensive precipitation events have increased
in western China since 1950. Wang and Zhou (2005) studied
the spatial distribution of extreme precipitation during
1961–2001 and showed that the annual mean precipitation
increased significantly in southwest, northwest, and east
China, and decreased significantly in central, north, and
northeast China. Endo et al. (2005) detected long-term
trends in summer precipitation totals, number of rainy days,
and precipitation intensity in daily rainfall records spanning
from 1961 to 2000 in China. Significant positive trends
were found for summer totals, and the number of rainy days
in the Yangtze River basin and northwestern China and
negative trends were detected for most other regions. Becker
et al. (2004) related rainfall variability in the Yangtze basin
to v-wind variability at the 700 hPa level over southern
China. It is evident that precipitation in the region not only
depends on the monsoon intensity but also on the amount of
water vapor that is transported by the atmospheric system.
Many investigations have indicated that increasing temperature can cause alterations in the spatial and temporal distribution of precipitation regimes by influencing the atmospheric
circulation, which will exert tremendous impacts on water
resource management at the river basin scale and on agricultural activities in China (e.g., Chavas et al. 2009). In addition,
the societal infrastructure is becoming more sensitive to
Fig. 1 Meteorological stations
in Xinjiang
Q. Zhang et al.
weather and climate extremes, which would be exacerbated
by climate change (e.g., Easterling et al. 2000).
The foregoing studies mainly focused on extreme precipitation events defined by precipitation indices (e.g., Peterson
et al. 2002; Brown et al. 2010; Gemmer et al. 2011; Zhang et
al. 2011a, b). In a recent study, the duration of consecutive
wet days or the wet period and related precipitation intensity
have aroused much attention (e.g., Zolina et al. 2010). Wet
periods (WPs) are defined as consecutive wet days with
daily precipitation larger than 1 mm day−1 and are adopted
to investigate the changing structure of precipitation process. Analyzing wet periods and the associated precipitation
intensity over Europe, Zolina et al. (2010) indicated that
longer wet periods and higher intensities should have a
significant impact on the terrestrial hydrologic cycle, including subsurface hydrodynamics, surface runoff and European
flooding. Further, dry spells defined as a period of consecutive days of exactly, say x, dry days immediately preceded
and followed by a wet day have also aroused a great deal of
interest as an important component of the precipitation
process (Zin and Jemain 2010). Extreme precipitation
events can reflect changes in certain precipitation components and can be helpful in understanding the impact of
climate change on the hydrological cycle. However, shifts
in the changing properties of extreme precipitation are essentially alterations of the precipitation structure in both
space and time. The length and distribution of wet periods
and related waiting time (the duration between two consecutive wet periods) are of significant theoretical and practical
implications for understanding the occurrences of meteorhydrological extremes, such as floods and droughts.
Xinjiang, located in the inland of China (Fig. 1), is
characterized by arid climate with serious water shortages.
It has a semi-arid and arid climate with long-term average
annual precipitation of 130 mm and long-term average rainy
Changing structure of the precipitation process during 1960–2005
231
days of 55. The variability and availability of water resources is a crucial factor influencing the development and
conservation of the environment and also the sustainability
of socio-economy of the region, particularly agriculture
whose development in Xinjiang is heavily dependent on
irrigation (Zhang et al. 2010b). Shi et al. (2003) showed
that the regional climate in Xinjiang exhibited a shift from a
warm–dry climate to a warm–wet one over the last two
decades as the globe is becoming warmer, with the result
that hydrometeorological extremes have higher probabilities
of occurrence. Xue (2003) investigated precipitation data in
70 stations and concluded that annual precipitation in Xinjiang was increasing, and the annual precipitation changing
rate in South Xinjiang was more homogeneous than that in
North Xinjiang. Qian and Lin (2005) reported an increasing
trend in precipitation intensity in Xinjiang, and higher precipitation as a result of persistent wet days significantly
contributed to the increasing frequency of floods during
1980–2000. Jiang et al. (2003) indicated an agreement between the flood-damaged area and precipitation changes in
Xinjiang since the 1960s, illustrating intensifying flood
hazards and increasing disaster-induced damages. Also
Ren (2000) indicated that the precipitation in southwest
China was increasing since 1960s. Climate warming is
suggested to be linked to the recent increases in extreme
precipitation events due to increased atmospheric water
vapor and warmer air (IPCC 2007). While it is now widely
recognized that regional temperature is increasing (e.g.,
Zhang et al. 2009b), changes in extreme precipitation are
not yet well understood, particularly no reports are available
so far concerning changes in the precipitation structure from
the viewpoint of wet durations and related precipitation
Fig. 2 Occurrences of missing
days per season
intensity and precipitation amount. This is what motivated
this current study.
The objective of this study therefore is to investigate the
changing properties of precipitation in Xinjiang, a typical
arid region in China, in both space and time. This study will
shed new light on the regional responses to global climate
change in terms of the hydrological cycle in the arid regions
of the world. Besides, results of this study may also be of
practical merit for water resources management in arid and
semi-arid regions under the influence of changing climate,
particularly under the influence of altered hydrological cycle
due to increasing temperature on regional and global scales.
2 Data
Daily precipitation data for the period 1960–2005 from 51
rain gauging stations were obtained from the National Metrological Information Center of the China Meteorological
Administration. Locations of the rain gauging stations are
shown in Fig. 1. There are missing values in the daily
precipitation series at 12 rain gauging stations. Missing
values account for >1% of the total precipitation data at
two stations and <1% at other stations. Figure 2 illustrates
the frequency of days with missing data per season. The
frequency of missing data for 1 day is about 47%. Figure 3
shows the frequency of missing data for consecutive days
without considering monthly gaps. The missing values of 1–
2 days were replaced by the average values of precipitation
of neighboring days. Adequate consecutive days with missing data were filled by the long-term average of the same
days of other years. In view of the objectives of this study,
50
45
40
Occurrence (%)
35
30
25
20
15
10
5
0
0
10
20
30
40
50
60
70
Number of missing days (days)
80
90
100
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Q. Zhang et al.
80
precipitation amount is considered; (3) total precipitation
amount of AD (AP), SD (SP), and WD (WP); (4) fractional
contribution of AP to ATP (AF), SP to STP (SF), and WP to
WTP (WF); (5) the average precipitation intensity of AD,
SD, and WD, i.e., AI for AD, SI for SD, and WI for WD.
Definitions of these precipitation indices are given in
Table 1.
70
Occurrence (%)
60
50
40
30
20
3 Methodology
10
0
1
2
3
4
5
6
7
8
Duration of continuous gaps (days)
Fig. 3 Occurrences of continuous missing days (without considering
monthly gaps)
this gap-fill method did not significantly affect the final
results. A similar gap-fill method has been used by Zhang
et al. (2011a, b).
Fifteen precipitation indices were defined in this study:
(1) total precipitation amount in a year (ATP), in summer
(STP), and in winter (WTP); (2) the duration of maximum
consecutive wet days, in other words, the duration of the
continuous wet days that last for the longest time in a year
(AD), in summer (SD), and in winter (WD). Wet day is
defined as the rainy day with daily precipitation larger than
1 mm. If the events of maximum consecutive wet days occur
several times in a specific period (annual, summer, or winter), then only the one which has the largest total
The modified Mann–Kendall test (MMK test hereafter;
Hamed and Rao 1998) and linear regressive technique were
adopted to detect possible trends within the precipitation
series. Hamed and Rao (1998) modified the MK test by
considering the lag-i autocorrelation in the hydrometeorological series. The modified MK test has been shown to be
robust and used in the study of trends in hydrometeorological series (e.g., Daufresne et al. 2009). Besides, estimation
of the significance of linear trends by F test was done after
the removal of autocorrelation effects by prewhitening
(Matalas and Sankarasubramanian 2003; von Storch
1999). The significance of trends was evaluated at a 5%
significance level.
Field significance (Livesey and Chen 1983; Zolina et al.
2008) of all linear trends was analyzed to evaluate the
significance of trends in Xinjiang. Let N denote the number
of significant linear trends. The index of each station in
Xinjiang, China was shuffled randomly and the number of
significant linear trends of each new series was computed.
This computation procedure was repeated more than 1,000
Table 1 Precipitation indices
Seasons
Indices
Definitions
Annual
ATP
Annual total precipitation amount
mm
AD
day
AF
AI
The duration of maximum consecutive wet days in a year. A wet day is defined as the rainy day with daily
precipitation exceeding 1 mm
Total precipitation amount of AD. There may be several maximum consecutive wet days with the same
duration in a year. Then, only the one that has the maximum total precipitation amount is considered
Fractional contribution of AP to ATP (AF 0 AP/ATP)
Precipitation intensity of AD (AI 0 AP/AD)
%
mm/day
STP
SD
SP
SF
SI
WTP
WD
WP
WF
WI
Total precipitation amount in summer
The duration of maximum consecutive wet days in summer
Total precipitation amount of SD
Fractional contribution of SP to STP (SF 0 SP/STP)
Precipitation intensity of SD (SI 0 SP/SD)
Total precipitation amount in winter
The duration of maximum consecutive wet days in winter
Total precipitation amount of WD
Fractional contribution of WP to WTP (WF 0 WP/WTP)
Precipitation intensity of WD (WI 0 WP/WD)
mm
day
mm
%
mm/day
mm
day
mm
%
mm/day
AP
Summer
Winter
Unit
mm
Changing structure of the precipitation process during 1960–2005
times. The significance of field trend was the percentage p
of which the number of significant trends was smaller than
N. Results of field significance across Xinjiang are given in
Table 2.
We also discussed the temporal alterations of different
indices. Specifically, the arithmetical averages of index of
individual durations in individual year were calculated.
Then for a particular duration, the series of average of index
in all available years was standardized. The standardized
procedure is as follows:
Z¼
X X
SDðX Þ
where X is the mean value of X series and SD(X) is the
standard deviation of X series. Then, the 5-year moving
average was computed and plotted. It should be noted that
when temporal alterations of normalized series of AF, SF,
WF, AI, SI, and WI were discussed, we referred to the
indices themselves; when temporal alterations of normalized
occurrences of AD, SD, and WD were discussed, we referred to the frequencies of these indices.
4 Results and discussions
4.1 Changes in ATP, STP, and WTP
Figure 4a illustrates the MMK trends of ATP across Xinjiang. It can be seen from Fig. 4a that ATP is increasing in
most parts of Xinjiang. There are 49 precipitation stations
showing increasing ATP, accounting for 96% of the total
precipitation stations considered in the study. Besides,
Table 2 Result of field significance
Indices
Significant
increasing trends
Significant
decreasing trends
Field
significance (%)
ATP
STP
WTP
AD
SD
25
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8
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WD
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WP
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10
23
1
233
significant increasing trends of ATP can be found in Xinjiang, except for the southwest parts. There are 33 rain
stations characterized by significant increasing ATP, accounting for 65% of the total rain stations. The increasing
rate of ATP at most rain stations is ranging between 0 and
10 mm per decade and different changing rate of ATP can be
identified (Fig. 4d). Specifically, increasing rate of ATP in
the west Xinjiang is larger than that in the middle and
eastern parts of Xinjiang. The increasing rate of ATP at
some rain stations can reach 30–40 mm per decade and the
largest increasing rate of ATP was detected in the east parts
of the Tianshan Mountains, being about 30–40 mm per
decade (Fig. 4d). Therefore, ATP changes tend to show a
wetting tendency across the Xinjiang region. However, the
wetting tendency is also different in different regions of
Xinjiang; specifically, the increasing magnitude of ATP in
western Xinjiang is larger than that in the middle and eastern
Xinjiang.
Similarly, STP is also subjected to increase (Fig. 4b).
Significant increasing STP can be observed mainly in western Xinjiang and eastern parts of the Tianshan Mountains.
Figure 4e shows the spatial patterns of the changing rate of
STP. Most regions of Xinjiang are dominated by changing
rates ranging between 0 and 5 mm per decade. A larger
changing rate of 10–15 mm per decade can be detected in
western Xinjiang and in the western and eastern Tianshan
Mountains. However, the largest changing rate of STP,
about 15–20 mm per decade, can be identified in the eastern
parts of the Tianshan Mountains. Nevertheless, there are
small regions being characterized by decreasing STP with
changing rate of −5 to 0 mm per decade. In this case,
Xinjiang is dominated by increasing summer precipitation,
particularly in the west parts of south Xinjiang and the
eastern parts of Tianshan Mountains.
Different changing properties of WTP can be observed
from Fig. 4c when compared to those of ATP and STP.
Significant increasing WTP can be found only in northern
Xinjiang with changing rates ranging between 4 and 8 mm
per decade. However, the changing rate of WTP at most of
the precipitation stations ranges between 0 and 2 mm per
decade. Decreasing WTP can be observed mainly in southern Xinjiang with changing rates of −2 to 0 mm per decade
(Fig. 4f). In this case, WTP in northern Xinjiang and the
Tianshan Mountains is increasing. No significant changes in
WTP can be detected in southern Xinjiang. In summary,
increasing precipitation is found in winter in mainly northern Xinjiang and the Tianshan Mountains. Precipitation
changes in southern Xinjiang are not evident and a slight
decrease of precipitation is detected in southern Xinjiang.
Increasing total precipitation at annual and seasonal time
scales imply a wetting tendency in the Xinjiang region (Shi
et al. 2003), and it is particularly the case for northern
Xinjiang.
234
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Fig. 4 MMK test trends of a ATP, b STP, and c WTP (blue dots
insignificant increasing trend, red dots insignificant decreasing trend,
upward blue triangles significant increasing trends, and downward red
triangles significant decreasing trends). Changing rates (millimeter per
decade) of d ATP, e STP, f WTP
4.2 Changes in the number of maximum consecutive
wet days
2 days have the largest occurrence frequency, being about
35% (see Fig. 5). The next largest frequency is found for the
annual 3-day maximum consecutive wet days, being about
30%. The annual maximum consecutive wet days exceeding
9 days are scarce events. Similarly, in summer, the 2-day
Frequency of different maximum consecutive wet days
shows that the annual maximum consecutive wet days of
Changing structure of the precipitation process during 1960–2005
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9
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Duration (days)
Fig. 5 Frequencies of AD (black), SD (gray), and WD (white) in
Xinjiang
maximum consecutive wet days are also subjected to the
largest occurrence frequency, being nearly 40%. The next
highest occurrence frequency is detected in the 1-day maximum consecutive days, being about 25%. Also, the maximum consecutive wet days exceeding 9 days in summer are
also scarce events. In winter, however, the highest frequency
can be found in the 1-day maximum consecutive wet days,
being over 35%. Besides, 0-day maximum consecutive wet
days are also very common in winter, which means there is
no rainy day in winter. Figure 5 demonstrates that 0 days in
WD are also in high frequency, being over 25%. No 8-day
maximum consecutive wet days are observed. These results
indicate that precipitation events of short durations are
predominant.
We also investigated temporal variations of the standardized occurrences of AD, SD, and WD series and results are
shown in Fig. 6. Figure 6a indicates that the frequency of the
0- to 3-day AD is decreasing after 1987; however, the
frequency of 3- to 8-day AD is increasing. These results
imply the lengthening of the maximum consecutive wet
days. Similar changing properties can also be found in the
SD changes (Fig. 6b), i.e., the frequency of 0- to 2-day SD is
decreasing after 1987; and the frequency of 3- to 8-day SD
is increasing. The maximum WD ranges between 0 and
7 days. After 1987, the frequency of 0- to 1-day WD is
decreasing and the frequency of >2-day WD is increasing
(Fig. 6c). These results show that the frequency of maximum consecutive wet days of shorter durations is decreasing, and of the maximum consecutive wet days of longer
durations is increasing. That is, the lengthening of maximum consecutive wet days and precipitation changes are
tending to shift to the extreme sides with evident clustering.
Figure 7 shows the spatial distribution of MMK trends of
AD, SD, and WD and related changing magnitudes. Results
Fig. 6 Temporal alteration of normalized occurrences of a AD, b SD,
and c WD in Xinjiang
of MMK trends show significant increasing AD in northern
Xinjiang, western parts of south Xinjiang and eastern parts
of the Tianshan Mountains and no significant decreasing
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Fig. 7 MMK test trends of a AD, b SD, and c WD (blue dots
insignificant increasing trend, and red dots insignificant decreasing
trend, upward blue triangles significant increasing trends, and
downward red triangles significant decreasing trends). Changing rates
(days per decade) of d AD, e SD, f WD
AD can be detected across the entire Xinjiang region
(Fig. 7a). Nevertheless, more regions of Xinjiang are characterized by nonsignificant increasing AD. With respect to
the changing rate, larger changing magnitude of AD is
identified in northern parts of north Xinjiang, western parts
of south Xinjiang and eastern parts of the Tianshan Mountains (Fig. 7d), ranging between 0.2 and 0.4 day per decade
and most of the regions are characterized by 0- to 0.2-day
Changing structure of the precipitation process during 1960–2005
per decade. Besides, decreasing magnitude of –0.2 to 0 day
per decade can be found in parts of the Xinjiang region.
As for spatial distribution of SD, only three stations are
characterized by significant increasing SD and these three
stations are located in the eastern parts of Tianshan Mountains and southern parts of south Xinjiang (Fig. 7b). The
changing rate of SD is between 0 and 0.4 day per decade
and that at some stations is nearly −0.2 to 0 day per decade
(Fig. 7e). Spatial features of WD show distinctly different
patterns. Stations located in northern Xinjiang and southern
parts of the Tianshan Mountains are dominated by significant increasing WD with changing magnitude of 0.2–
0.4 day per decade (Fig. 7f). No significant decreasing
WD can be found across the entire Xinjiang (Fig. 7c).
Decreasing magnitude of −0.2 to 0 day per decade of WD
is found in the eastern parts of south Xinjiang (Fig. 7f). In
this case, the lengthening of consecutive maximum wet
periods is not evident and is different within different
regions. This phenomenon is different from that observed
by Zolina et al. (2010), showing different regional responses
in terms of precipitation structure changes to global climate
change.
4.3 Changes in the precipitation amount of maximum
consecutive wet days
Figure 8a shows that AP in Xinjiang is increasing and
significant increasing AP is found in northern Xinjiang,
southern parts of the Tianshan Mountains, southern parts
of Xinjiang and southwestern parts of south Xinjiang with
changing magnitude of about 2–3 mm per decade. Decreasing AP is observed in the eastern parts of Tianshan Mountains and southern Xinjiang with changing magnitude of −2
to 0 mm per decade (Fig. 8d). As for changes of SP, a
majority of parts of Xijiang are characterized by increasing
SP. Significant increasing SP is observed mainly in southern
Xinjiang and eastern parts of the Tianshan Mountains
(Fig. 8b). Figure 8e shows increasing SP in most parts of
Xinjiang, which is in agreement with the results shown in
Fig. 8b. Significant increasing SP is observed mainly in
southern Xinjiang with a smaller increasing magnitude
when compared to that in northern Xinjiang. Increasing
magnitude of SP in northern Xinjiang is 4–6 mm per decade
and the decreasing magnitude is −2 to 0 mm per decade in
the southern parts of Tianshan Mountains. Similarly, increasing WP is detected generally across the entire Xinjiang
with significant increasing WP mainly in northern Xinjiang
and the Tianshan Mountains (Fig. 8c). As for the increasing
magnitude of WP, the largest increasing magnitude is found
in northern Xinjiang, being about 1–3 mm per decade
(Fig. 8f). Increasing magnitude of WP in most regions of
Xinjiang is 0–1 mm per decade and decreasing magnitude of
WP in southern Xinjiang is −1 to 0 mm per decade.
237
4.4 Fractional contribution of maximum consecutive wet
days to annual and seasonal total precipitation amounts
The percentage of precipitation amount of maximum consecutive wet days to the annual and seasonal total precipitation amounts is defined as the fractional contribution of
the maximum consecutive wet days in terms of the precipitation amount. The lengths of maximum consecutive wet
days are different, thus the average fractional contribution of
the maximum consecutive wet days is analyzed (Fig. 9). It
can be seen from Fig. 9 that 1-day AF is subjected to the
largest fractional contribution, being more than 40%; and
the fractional contribution of the 2-day AF is the second
largest. The increase in the length of maximum consecutive
wet days causes a decrease in the fractional contribution
(AF). However, 8-day AF is in a sudden increase in the
fractional contribution, being more than 15%. The fractional
contribution of 9- and 10-day AF is increasing. The fractional contribution of 1-day SF is the largest, about 50% and
that of the 1-day WF is about 70%. In general, longer
maximum consecutive wet days have smaller fractional
contributions to the total precipitation amount. In this sense,
higher probability of extreme weather extremes such as
floods and droughts can be expected.
Figure 10 illustrates the temporal changes of AF, SF, and
WF. It can be seen from Fig. 10a that AF of maximum
consecutive wet days with lengths of 1–6 days is higher
than that with lengths of >6 days before 1980. After 1980,
AF of shorter maximum consecutive wet days is small,
while AF of maximum consecutive wet days with longer
lengths, e.g., 6–9 days, is larger. Similar properties can be
found in the changes of SF. Higher SF of maximum consecutive wet days with lengths of 1–6 days can be observed
initially. SF of longer and shorter maximum consecutive wet
days is increasing after roughly 1980 (Fig. 10b). As for WF,
it is increasing after 1995 (Fig. 10c). In summary, AF of
longer maximum consecutive wet days is increasing and
those of shorter maximum consecutive wet days are decreasing. However, SF and WF of maximum consecutive wet
days with different lengths is increasing.
Figure 11 shows the spatial distribution of MMK trends
and related changing magnitudes of AF, SF, and WF. It can
be observed from Fig. 11a that most precipitation stations in
Xinjiang are characterized by decreasing AF. Significant
decreasing AF can be detected in the northern Xinjiang,
parts of the Tianshan Mountains and southwest parts of
south Xinjiang. The changing magnitude of AF at majority
of precipitation stations is between −4% to 2% per decade
and even −6% to 4% per decade (Fig. 11d). SF changes,
however, are dominated by decreasing trends and significant
decreasing trends of SF are identified mainly in southern
Xinjiang and northern parts of the Tianshan Mountains.
Nevertheless, precipitation stations in northern Xinjiang
238
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f
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c
75°
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50°
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a
Q. Zhang et al.
-4 - -2
-2 - 0
0-2
2-4
4-6
35°
75°
80°
85°
90°
95°
-1 - 0
0-1
1-2
2-3
Fig. 8 MMK test trends of a AP, b SP, and c WP (blue dots insignificant increasing trend, and red dots insignificant decreasing trend,
upward blue triangles significant increasing trends, and downward
red triangles denotes significant decreasing trends). Changing rates
(millimeter per decade) of d AP, e SP, f WP
are characterized by increasing trends but are not statistically significant (Fig. 11b). Figure 11e shows that the changing
rate of SF in southern Xinjiang is about −6% to 3% per
decade; and increasing rate of SF in northern Xinjiang is
approximately 0–3% per decade. The WF changes show
different changing properties when compared to those of
AF and SF (Fig. 11c). Decreasing WF is found mainly in
northern Xinjiang. Nearly half of the total precipitation
stations are characterized by increasing WF trends, though
most of the trends are not statistically significant. The
Changing structure of the precipitation process during 1960–2005
239
80
Fractional contribution (%)
70
60
50
40
30
20
10
0
0
1
2
3
4
5
6
7
8
9
10
Duration (days)
Fig. 9 Averages of AF (black), SF (gray), WF (white) in Xinjiang (the
x-axis is the duration of maximum consecutive wet days; the y-axis is
the average of fractional contribution with corresponding duration. The
fractional contribution is calculated as the precipitation amount of
maximum consecutive wet days to the annual and seasonal total
precipitation amounts)
increasing rate of WF is about 0–5% and even 5–10% per
decade (Fig. 11f). Comparison between Fig. 11a, b, and c
shows that increasing tendency is predominant in the WF
changes and decreasing tendency is predominant in the AF
and SF changes.
4.5 Changes in precipitation intensity of maximum
consecutive wet days
The distribution of average precipitation intensity of maximum consecutive wet days over Xinjiang is illustrated in
Fig. 12. AI of 1-day maximum consecutive wet days is the
largest, about 9 mm/day and AI of 2-day maximum consecutive wet days is the second largest. In general, the longer is
the length of the maximum consecutive wet days, the less
the AI is. The SI changes show similar changing properties.
WI, however, demonstrates different changing features. The
7-day maximum consecutive wet days have the largest WI,
being over 4 mm/day. The longer the length of the maximum consecutive wet days, the larger the WI is.
Temporal changes of AI, SI, and WI are illustrated in
Fig. 13. The largest AI is identified for the 1–2, 4–6, and 8–
10 maximum consecutive wet days. After 1975, AI of
longer maximum consecutive wet days is increasing. After
1995, however, higher AI can be found in the maximum
consecutive wet days of various durations. SI changes show
similar changing properties when compared to those of AI.
However, distinctly different changing features can be observed in the WI changes. The duration of maximum consecutive wet days with high WI is decreasing during 1960–
Fig. 10 Temporal alteration of normalized series of a AF, b SF, and c
WF in Xinjiang
1980, and is increasing suddenly after 1980. Particularly,
during 1992–2005, high WI of the maximum consecutive
240
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90°
95°
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90°
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-6% - -4%
-4% - -2%
-2% - 0%
0% - 2%
2% - 4%
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50°
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85°
90°
95°
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50°
(e)
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40°
40°
35°
90°
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50°
85°
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e
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50°
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a
Q. Zhang et al.
-9% - -6%
-6% - -3%
-3% - 0%
0% - 3%
3% - 6%
35°
75°
80°
85°
90°
95°
(f)
-10% - -5%
-5% - 0%
0% - 5%
5% - 10%
10% - 15%
Fig. 11 MMK test trends of a AF, b SF, and c WF (blue dots
insignificant increasing trend, and red dots insignificant decreasing
trend, upward blue triangles significant increasing trends, and
downward red triangles significant decreasing trends). Changing rates
(percent per decade) of d AF, e SF, and f WF
wet days is observed for various durations. Therefore, enhanced precipitation intensity of maximum consecutive wet
days with different durations can be observed in Xinjiang.
With respect to spatial and temporal variations of AI, SI,
and WI (Fig. 14), no fixed spatial patterns can be identified
for AI and SI. The stations with increasing or decreasing AI
and SI (Figs. 14a, b) are distributed interchangeably across
Xinjiang. About 57% the total stations are characterized by
increasing AI, though most of the increasing trends are not
significant statistically (Fig. 14a). About 75% of the total
Changing structure of the precipitation process during 1960–2005
241
10
Precipitation intensity (mm/day)
9
8
7
6
5
4
3
2
1
0
0
1
2
3
4
5
6
7
8
9
10
Duration (days)
Fig. 12 Averages of AI (black), SI (gray), WI (white) in Xinjiang (the
x-axis is the duration of maximum consecutive wet days; the y-axis is
the average of precipitation intensity with corresponding duration. The
precipitation intensity is calculated as the precipitation amount of
maximum consecutive wet days to the duration)
stations are characterized by increasing SI (Fig. 14b). In
this sense, the increase is predominant in the AI and SI
changes. Besides, the changing magnitude of AI is relatively small, about −1 mm/day (Fig. 14d). The changing
magnitude of SI at most of the precipitation stations is
about 0–1 mm/day. The largest changing magnitude can
be found in eastern Xinjiang, about 2–3 mm/day
(Fig. 14e). Relatively confirmative spatial patterns of
WI can be observed (Fig. 14c). Most regions of Xinjiang
are characterized by increasing WI with an increasing
rate of 0–0.5 mm/day (Fig. 14f). The precipitation stations with increasing WI account for about 78% of the
total precipitation stations. Decreasing WI can be observed mainly in northeastern Xinjiang and the southwestern corner of Xinjiang (Fig. 14c) with an increasing
rate of −0.5 to 0 mm/day (Fig. 14f).
5 Field significance test
Field significance test procedure was performed to evaluate
the validity of the field trends of precipitation variables
defined in the study, and results are displayed in Table 2.
It can be clearly seen from the table that field significance of
most of the precipitation variables is significant at a confidence level of <10%, implying that trends of precipitation
variables across Xinjiang is statistically meaningful. The
field significance of SD and SF is 13% and 12%, being
larger than 10%. However, these values are approaching
10%. The field significance of SI is only 23%. However, it
still makes sense to study the spatial patterns of SI. In this
Fig. 13 Temporal alteration of normalized series of a AI, b SI, and c
WI in Xinjiang
sense, the trends detected in this study are meaningful and
reliable statistically.
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-2 - -1
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1-2
2 -3
35°
75°
80°
85°
90°
95°
(f)
-0.5 - 0
0 - 0.5
0.5 - 1
Fig. 14 MMK test trends of a AI, b SI, and c WI (blue dots insignificant increasing trend, and red dots insignificant decreasing trend,
upward blue triangles significant increasing trends, and downward
red triangles significant decreasing trends). Changing rates (percent
per day per decade) of d AI, e SI, and f WI
6 Discussions
studies (Shi et al. 2003; Xue 2003; Qian and Lin 2005; Jiang
et al. 2003; Ren 2000; Zhang et al. 2011a, b).
Figure 11 shows that AF and SF have decreasing trends,
However, Fig. 10 indicates that AF and SF of long duration
increased after 1980, while AF and SF of short duration
The changes of extreme precipitation indicate a wet tendency and the precipitation pattern shifted to more extreme site
in Xinjiang, these results are strongly supported by previous
Changing structure of the precipitation process during 1960–2005
decreased after 1980. Meanwhile, maximum consecutive wet
days with long duration occurred more frequently after 1980,
while those with short duration occurred less. But this does not
mean the tendency of AF without considering duration
(Fig. 11) was positive. The reason is that the maximum
consecutive wet days with short durations still occurred much
more frequently than those with long durations (Fig. 5). The
MMK test just detects whether there is a trend in a series, and
cannot find out whether the precipitation pattern changes.
Thus, decreasing AF and SF are detected while their patterns
have changed. On the other hand, it should be noted that the
fractional contribution is the precipitation amount of maximum consecutive wet days to the annual and seasonal total
precipitation amounts. Figures 4 and 7 illustrate that both
precipitation amount of maximum consecutive wet days and
the annual and seasonal total precipitation amount increased,
but the changing magnitudes of the precipitation amount of
maximum consecutive wet days are smaller than those of the
annual and seasonal total precipitation amounts. This also can
explain why AF and SF decreased.
7 Conclusions and closing remarks
From analysis of duration, precipitation amount, fractional
contribution, and precipitation intensity of the maximum
consecutive wet days across Xinjiang, the following conclusions are drawn:
1. In year and summer, 2-day maximum consecutive wet
days are relatively frequent. However, the fractional
contribution of 1-day maximum consecutive wet days
is the largest. Longer maximum consecutive wet days
may have less fractional contribution to the total precipitation amount. In winter, however, the occurrence of 1day maximum consecutive wet days is subjected to a
higher occurrence frequency. Besides, it can also frequently happen that there are no rainy days for an entire
winter season. In this case, precipitation is highly scarce
in the Xinjiang region.
2. In general, the maximum consecutive wet days and
related total precipitation amount are increasing.
Thus, the wetting tendency is relatively evident in
Xinjiang. Besides, the lengthening of maximum consecutive wet days is evident in Xinjiang from the
viewpoint of frequencies of maximum consecutive
wet days. However, different changing properties are
also observed for the durations of maximum consecutive wet days in different regions of Xinjiang,
implying uneven spatial distribution of changes in
maximum consecutive wet days. Therefore, at least
in Xinjiang, the lengthening of maximum consecutive wet days is evident.
243
3. Wetting tendency is evident in Xinjiang, however, different wetting degrees can be found in northern and
southern Xinjiang. Relatively, the wetting tendency in
summer is more evident in southern Xinjiang than in
northern Xinjiang; in winter, however, the wetting tendency in northern Xinjiang is more evident that in
southern Xinjiang. This result is practically important
for regional water resources management. The annual
total precipitation is increasing with the lengthening of
maximum consecutive wet days. However, precipitation
intensity is increasing, particularly after 1990s. Specifically, increasing precipitation intensity is observed in
winter. Spatial patterns of precipitation intensity
changes in summer are ambiguous and no confirmative
patterns can be identified.
Acknowledgments This work is financially supported by Xinjiang
Technology Program (grant no.: 201001066; 200931105), the National
Natural Science Foundation of China (grant no.: 41071020;
50839005), the Project from Guangdong Science and Technology
Department (grant no.: 2010B050800001; 2010B050300010), Program for New Century Excellent Talents in University (the Fundamental Research Funds for the Central Universities), and by a grant from
the Research Grants Council of the Hong Kong Special Administrative
Region, China (project no. CUHK405308). Last but not the least, our
cordial gratitude should also goes to the editor, Prof. Dr. Hartmut
Graßl, and two anonymous reviewers for their pertinent and professional comments and suggestions which are greatly helpful for further
improvement of the quality of this manuscript.
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