Daily maximum/minimum temperature and precipitation data from 35 weather stations in Xinjiang during 1961-2010 were examined using kriging spatial analysis, linear tendency estimation, and correlation analysis. Temporal trends and spatial distribution patterns of extreme temperature and precipitation in this area were then analyzed using 12 extreme temperature and 7 extreme precipitation indices. The following results were obtained. 1) Over the past 50 years, extreme cold indices, excepting the monthly maximum temperature minimum value and monthly extreme minimum temperature, showed slight decreasing trends. These indices include the maximum number of consecutive frost days, icy days, cold-nighttime days, and cold-daytime days. 2) Extreme warm events generally showed significant increasing trends (P < 0.01), including the indices of summertime days, warm-nighttime days, warm-daytime days, monthly extreme maximum temperature, and monthly minimum temperature maximum value. 3) The spatial distributions of threshold values of extreme warm and cold events showed notable regional differences. A reducing trend of extreme cold events and an increase in extreme warm events has occurred mainly in northern Xinjiang. 4) For the past 50 years, six extreme precipitation indices, aside from consecutive dry days, showed significant increasing trends in Xinjiang (P < 0.05) and notable differences in spatial distribution. The increase in extreme precipitation events was more rapid at northern than at southern sites. Extreme precipitation intensity was greater in mountainous areas, and precipitation frequency increased in the plain region. 5) Factor analysis revealed good correlations among extreme temperature indices, excepting extreme temperature days.
At present, no doubt exists about global warming. The fourth assessment report of the Intergovernmental Panel on Climate Change [
Many studies have indicated that frequent extreme climatic events cause huge losses for society and the economy, as well as loss of human lives [
Xinjiang, located far from the ocean in the center of Eurasia, in the border region of northwestern China , is impacted by the uplifted Tibetan Plateau, westerly wind circulation effects, and high mountain landforms. This region is thus an important route by which cold air invades China , and has a diverse climate. Northern Xinjiang has a variable continental arid and semi-arid climate, whereas southern Xinjiang has a warm continental arid climate; the ecology of these regions is fragile and has suffered greatly under the influence of climatic change [
Daily precipitation and maximum, minimum, and mean temperature data from China’s Meteorological Administration for the period 1961-2010 in Xinjiang were used for this study. Data from 43 meteorological stations were reviewed to identify problems with missing or misdetected observations. We selected high-quality data from 35 stations (
The standards used to define and calculate the extreme climatic indices used in this study were based on the World Meteorological Organization’s Commission for Climatology World Climate Research and Climatic Variation and Predictability programs’ expert team on climate change detection, monitoring, and indices [
All of the extreme climate indices reflect three aspects of temperature or precipitation events: strength, frequency, and temporal duration of climatic change. In extreme climate research, a certain percentile value is usually adopted as a threshold (with values exceeding it defined as extreme), and calculations are performed according to the nonparametric method of Bonsal et al. [
In this study, percentile values were used to calculate relative and other indices. Specifically, temperature data were sorted in ascending order, and the 90th and 10th percentile values were regarded as thresholds for extreme temperature. When the highest temperature on a given day exceeded the 90th percentile value, an extreme high-temperature event was considered to have occurred on that day; when the highest temperature on a given day was less than the 10th percentile value, an extreme low-temperature event was considered to have occurred. Secondly, we analyzed extreme climatic events using linear tendency estimation, the Mann-Kendall method, and the kriging method of spatial analysis.
No. | Station | Longitude (˚E) | Latitude (˚N) | Elevation (m) | Period of series |
---|---|---|---|---|---|
1 | Habahe | 86.40 | 48.05 | 532.6 | 1961.01.01-2010.12.31 |
2 | Jimunai | 85.87 | 47.43 | 984.1 | 1961.01.01-2010.12.31 |
3 | Fuai | 87.47 | 47.12 | 500.9 | 1961.01.01-2010.12.31 |
4 | Aletai | 88.08 | 47.73 | 735.3 | 1961.01.01-2010.12.31 |
5 | Fuyun | 89.52 | 46.98 | 807.5 | 1961.01.01-2010.12.31 |
6 | Qinghe | 90.38 | 46.67 | 1218.2 | 1961.01.01-2010.12.31 |
7 | Alashankou | 82.57 | 45.18 | 336.1 | 1961.01.01-2010.12.31 |
8 | Tuoli | 83.60 | 45.93 | 1077.8 | 1961.01.01-2010.12.31 |
9 | Beitashan | 90.53 | 45.37 | 1653.7 | 1961.01.01-2010.12.31 |
10 | Caijiahu | 87.53 | 44.20 | 440.5 | 1961.01.01-2010.12.31 |
11 | Qitai | 89.57 | 44.02 | 793.5 | 1961.01.01-2010.12.31 |
12 | Yinning | 81.33 | 43.95 | 662.5 | 1961.01.01-2010.12.31 |
13 | Zhaosu | 81.13 | 43.15 | 1851.0 | 1961.01.01-2010.12.31 |
14 | Baluntai | 86.30 | 42.73 | 1739.0 | 1961.01.01-2010.12.31 |
15 | Kumishi | 88.22 | 42.23 | 922.4 | 1961.01.01-2010.12.31 |
16 | Bayinbuluke | 84.15 | 43.03 | 2458.0 | 1961.01.01-2010.12.31 |
17 | Tulufan | 89.20 | 42.93 | 34.5 | 1961.01.01-2010.12.31 |
18 | Akesu | 80.23 | 41.17 | 1103.8 | 1961.01.01-2010.12.31 |
19 | Baicheng | 81.90 | 41.78 | 1229.2 | 1961.01.01-2010.12.31 |
20 | Luntai | 84.25 | 41.78 | 976.1 | 1961.01.01-2010.12.31 |
21 | Kuerle | 86.13 | 41.75 | 931.5 | 1961.01.01-2010.12.31 |
22 | Tuergate | 75.40 | 40.52 | 3504.4 | 1961.01.01-2010.12.31 |
23 | Wuqia | 75.25 | 39.72 | 2175.7 | 1961.01.01-2010.12.31 |
24 | Kashi | 75.98 | 39.47 | 1289.4 | 1961.01.01-2010.12.31 |
25 | Aheqi | 78.45 | 40.93 | 1984.9 | 1961.01.01-2010.12.31 |
26 | Alaer | 81.27 | 40.55 | 1012.2 | 1961.01.01-2010.12.31 |
27 | Ruoqiang | 88.17 | 39.03 | 887.7 | 1961.01.01-2010.12.31 |
28 | Shache | 77.27 | 38.43 | 1231.2 | 1961.01.01-2010.12.31 |
29 | Pishan | 78.28 | 37.62 | 1375.4 | 1961.01.01-2010.12.31 |
30 | Hetian | 79.93 | 37.13 | 1375.0 | 1961.01.01-2010.12.31 |
31 | Minfeng | 82.72 | 37.07 | 1409.5 | 1961.01.01-2010.12.31 |
32 | Qiemo | 85.55 | 38.15 | 1247.2 | 1961.01.01-2010.12.31 |
33 | Balikun | 93.00 | 43.60 | 1677.2 | 1961.01.01-2010.12.31 |
34 | Yiwu | 94.70 | 43.27 | 1728.6 | 1961.01.01-2010.12.31 |
35 | Hongliuhe | 94.67 | 41.53 | 1573.8 | 1961.01.01-2010.12.31 |
Index | Descriptive name | Definition | Unit | |
---|---|---|---|---|
Temperature | TXx | Warmest day | Annual highest TX | ˚C |
TNx | Warmest night | Annual highest TN | ˚C | |
TXn | Coldest day | Annual lowest TX | ˚C | |
TNn | Coldest night | Annual lowest TN | ˚C | |
TN10p | Cold night frequency | Percentage of days when TN < 10th percentile of 1961-1990 | d | |
TX10p | Cold day frequency | Percentage of days when TX < 10th percentile of 1961-1990 | d | |
TN90p | Warm night frequency | Percentage of days when TN > 90th percentile of 1961-1990 | d | |
TX90p | Warm day frequency | Percentage of days when TX > 90th percentile of 1961-1990 | d | |
FD | Frost days | Annual count when TN < 0˚C | d | |
ID | Ice days | Annual count when TX < 0˚C | d | |
SU25 | Summer days | the highest temperature is over 25˚C day number | d | |
DTR | Diurnal temperature range | Annual mean difference between TX and TN | ˚C | |
Precipitation | SDII | Simple daily intensity index | Average precipitation on wet days | Mm/d |
PRCPTOT | Wet day precipitation | Annual total precipitation from wet days | mm | |
RX1day | Maximum 1-day precipitation | Annual maximum 1-day precipitation | mm | |
RX5day | Maximum 5-day precipitation | Annual maximum consecutive 5-day precipitation | mm | |
CDD | Consecutive dry days | Maximum number of consecutive dry days | d | |
CWD | Consecutive wet days | Maximum number of consecutive wet days | d | |
R95p | Very wet day precipitation | Annual total precipitation when RR > 95th percentile of 1961-1990 daily precipitation | mm |
Notes: aAll the indices are calculated by RCLimDEX. Abbreviations are as follows: TX, daily maximum temperature; TN, daily minimum temperature; TG, daily mean temperature; RR, daily precipitation. A wet day is defined when RR ≥ 0.1 mm, and a dry day is defined when RR < 0.1 mm. Indices are included for completeness but are not analyzed further in this article.
Consistent with global changes, the frequency of extreme low-temperature events in the Xinjiang area was found to have decreased while that of extreme high-temperature events increased [
Index | Standard difference | Change tendency rate | Average value | |||||
---|---|---|---|---|---|---|---|---|
Over the years | The 1960s | The 1970s | The 1980s | The 1990s | From the year of 2000s | |||
FD | 10.05 | 4.8 | 162.64 | 169.88 | 167.47 | 166.69 | 162.18 | 146.78 |
ID | 8.85 | 2.75 | 68.799 | 72.07 | 73.8 | 69.3 | 67.8 | 60.9 |
TXn | 3.29 | 0.16 | −14.917 | −15.8 | −15 | −13.3 | −12.8 | −17.8 |
TNn | 3.01 | 0.505 | −26.504 | −27.8 | −27.4 | −24.7 | −24.2 | −28.4 |
TN10 | 3.88 | 2.237 | 8.44 | 12.7 | 11.1 | 8.1 | 6.4 | 3.9 |
TX10 | 2.81 | 0.879 | 9.54 | 10.4 | 10.9 | 10 | 8.9 | 7.5 |
The monthly maximum temperature minimum value (TXn) and monthly extreme minimum temperature (TNn) showed increasing trends, with interannual variation tendency rates of 0.16˚C/ 10a and 0.505˚C/10a, respectively, although these trends were not significant (α > 0.05). The correlation coefficients of TXn and TNn by year were −0.133 and 0.042, indicating significant warming, especially on low-temperature days, the frequency of which has decreased over time.
Against the background of global warming, the extreme cold indices generally showed decreasing trends over the past 50 years, but changes in these indices were characterized by spatial variation (
Variation tendency rates for TN10p ranged from −3.7 to −0 d/ 10a and were <0 at 88.5% of stations; however, the decreasing trends were not significant. The rates for TX10p ranged from −1.3 to −0.5 d/ 10a and were < 0 at 48.5% of stations; these declining trends were significant. The variation tendency rates for TXn ranged from 0.04 to 2.5˚C/ 10a and exceeded 0 at 48.5% of stations; increasing trends were significant at 37.5% of stations. Variation tendency rates for TNn ranged from 0 to 2.5˚C/ 10a and showed obvious increasing trends at 94.2% of stations.
For the past 50 years, all extreme warm event indices, such as the numbers of summertime days (SU25), warm- nighttime days (TN90p), and warm-daytime days (TX90p), as well as monthly extreme maximum temperature (TXx) and the monthly minimum temperature maximal value (TNx), showed significant increasing trends in the Xinjiang area (
The graph of changes in day-by-day temperature range (DTR;
Against the background of global warming, the extreme warm indices in the Xinjiang area generally showed increasing trends over the past 50 years, but these changes were characterized by spatial variation (
Although the ranges of increase in variation tendency rates for TXn and TNn exceeded those for TXx and TNx, all stations showed decreasing trends for DTR.
Precipitation intensity is one factor used to measure extreme precipitation, with greater intensity associated with greater possibility of disaster. Average precipitation intensity in the Xinjiang area showed a predominant trend of annual increases over the past 50 years, consistent with global data and those for China [
Index | Standard difference | Change tendency rate | Mean value | |||||
---|---|---|---|---|---|---|---|---|
Over the year | The 1960s | The 1970s | The 1980s | The 1990s | From the year of 2000s | |||
PRCPTOT | 23.297 | 8.232 | 144.33 | 129.38 | 134.16 | 143.79 | 159.22 | 155.11 |
SDII | 0.549 | 0.13 | 4.62 | 4.45 | 4.3 | 4.64 | 4.82 | 4.9 |
RX1day | 2.355 | 0.474 | 17.97 | 17.71 | 16.51 | 17.81 | 19 | 18.81 |
RX5day | 5.639 | 0.434 | 25.704 | 26.68 | 23.86 | 23.69 | 28.01 | 26.29 |
R95 | 32.197 | 9.322 | 116.24 | 108.56 | 97.1 | 105.65 | 136.7 | 133.2 |
CDD | 11.795 | −2.867 | 67.2 | 71.23 | 68.53 | 70.59 | 66.59 | 59.04 |
CWD | 0.49 | 0.154 | 4.92 | 4.83 | 4.67 | 4.63 | 5.11 | 5.35 |
The simple precipitation intensity index (SDII) showed small increasing trend at a rate of 0.13 mm / 10a , but this trend was not significant (α > 0.05;
Interannual variation tendencies for most extreme precipitation indices, with the exception of the CDD index, showed significant increasing trends at most stations in the Xinjiang area over the past 50 years (
Increasing trends in the extreme precipitation indices of RX1day, RX5day, R95, and CWDs were found at 25 (71.4%), 28 (80%), 30 (85.7%), and 29 (82.8%) stations, respectively. More than 70% of stations showed increasing trends for PRCPTOT, SDII, RX1day, RX5day, R95, and CWDs, indicating that the frequency of extreme precipitation trends is generally increasing in the Xinjiang area. Analysis of CDD data from 11 (31.4%) stations in southern and northern Xinjiang revealed an increasing trend and demonstrated regional tendencies for increased numbers of disasters involving drought.
In this study, 12 extreme temperature indices and 5 extreme precipitation indices were used to examine temporal and spatial variation in climatic extremes in Xinjiang over the past 50 years. The main conclusions are described below.
1) Analysis of temporal changes revealed decreasing trends in extreme cold indices (i.e., obvious reductions in the number of severely cold days and extreme low-temperature events), consistent with global warming. Linear variation in extreme warm indices showed notable increasing trends. The trends for TX10p, TN10p, IDs, and FDs (−0.88, −2.24, −2.75, −4.8 d/10a, respectively) decreased, whereas those for TX90p, TN90p, and SU25 (1.59, 3.38, and 2.59 d/10a, respectively) increased.
2) Analysis of temporal changes in extreme precipitation indices (except CDDs), such as RX1day, RX5day, R95, and CWD, as well as PRCPTOT, showed consistently increasing trends (rates of 0.474 mm/10a, 0.434 mm/10a, 9.322 d/10a, 0.154 d/10a, and 8.232 mm/10a, respectively).
3) Differences in the spatial distributions of the indices were notable. The frequencies of extreme cold and extreme warm events decreased in southern Xinjiang. The spatial distribution of extreme precipitation also showed obvious regional differences, with the directionality of trends differing between mountainous and desert basin areas. The response to global warming has been more notable in northern than in southern Xinjiang. Global climatic change has altered the ecology of northern Xinjiang and increased the frequency of extreme climatic disasters.
4) Changes in extreme cold and warm indices, as well as those in nighttime and daytime indices, showed notable asymmetry: the warming ranges of the cold and nighttime indices exceeded those of the warm and daytime indices, respectively.
This study is jointly financed by the National Natural Science Fund Project (U1203282) and the National Natural Science Foundation Project of China (41001020), and the Xinjiang Uygur Autonomous Region Key Laboratory of “Xinjiang laboratory of Lake Environoments and Resources in Arid Zone” (XJDX0909-2012- 12), the Shihezi University team innovation project (2014ZRKXJQ08). The authors gratefully acknowledge funding for this research and would like to express their sincere thanks to Zhang Yan Wei for the help with data.
Xiangling Tang,Xin Lv,Yineng Ouyang, (2016) Spatial and Temporal Variations of Extreme Climate Events in Xinjiang, China during 1961-2010. American Journal of Climate Change,05,360-372. doi: 10.4236/ajcc.2016.53027