Temporal and Spatial Variations of Extreme Precipitation in the Main River Basins of China in the Past 60 Years
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摘要: 在全球增暖背景下,中国极端降水事件及洪涝、干旱等次生灾害近年来频发,严重影响生态系统、人民的生产生活和社会经济发展。本文基于气候变化检测和指数专家组(ETCCDI)定义的10个降水指数,利用中国台站日降水资料,系统分析了1961~2017年中国及九大流域片降水变化情况,并利用空间场显著性检验考察不同降水指数的显著变化是否与外强迫作用有关。结果表明,各降水指数的变化具有区域性特征。整体而言,全国范围内平均降水、降水强度、极端强降水和连续性强降水呈增强趋势的台站数多于呈减弱趋势的台站数,呈显著增强趋势的台站占比不可能仅由气候系统内部变率引起,还受到外强迫的影响。此外,中国大部分站点连续干旱日数(CDD)减少,观测中CDD呈显著减弱趋势的台站占比也与外强迫作用有关。九大流域片中,内陆河片能够观测到平均降水、降水强度、极端强降水和连续性强降水的增多以及连续干旱日数的减少,有洪涝灾害增多的风险,且上述变化可归因为外强迫的作用。长江流域片、东南诸河片和珠海流域片平均降水、极端强降水和连续性强降水均增强,其中强降水的变化与外强迫作用有关。西南诸河片极端强降水增强,但大部分站点CDD呈增加趋势,有干旱增加的风险。黄河流域片、海河流域片、淮河流域片及松辽河流域片的大部分站点及区域平均结果中,降水指数多无显著变化趋势。增暖背景下,不同流域片呈现出不同的降水变化特征,将面临不同的气候灾害风险。Abstract: As a consequence of global warming, China has experienced increasing extreme precipitation events and secondary disasters such as floods and droughts, which have had significant effects on the ecosystem, production, life, and society. This study uses daily station precipitation records to systematically analyze the long-term trends in precipitation over China and nine river basins from 1961 to 2017. It uses ten precipitation indices specified by the Expert Team on Climate Change Detection and Indices (ETCCDI). In addition, the detectability of the trends in several precipitation characteristics is also examined based on the field significance test. The findings indicate that the extreme precipitation over China shows obvious regional features. The number of stations showing increasing trends in mean precipitation, precipitation intensity, extreme heavy precipitation, and continuous heavy precipitation exceeds the decreasing trends. However, the observed percentage of stations with significant increasing trends differs statistically from the internal climate variability but is influenced by the external forcings. Furthermore, for the majority of the station, the consecutive dry days (CDD) decreases, and the observed percentage of stations with significant decreasing trends is also related to the external forcing. Across the continental river basins, strengthened mean precipitation, precipitation intensity, extreme heavy precipitation, continuous heavy precipitation, and reduced CDD can be observed, which can be attributed to the influence of external forcings. Flood are becoming frequent in the continental. Strengthened mean precipitation and external force-related increase in heavy precipitation can be found across the Yangtze River, Pearl River, and southeastern river basin. The southwestern river basin has experienced an increase of extremely heavy precipitation, but there is a risk of increasing drought as the CDD lengthens for the majority of stations. Several precipitation indices and the area-averaged mean for the Yellow River, Haihe River, Huaihe River, and Songliao River basin. The various responses of precipitation characteristics to global warming suggest that the different river basins will experience a variety of climate disasters.
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Key words:
- Extreme precipitation /
- River basin /
- Drought and flood /
- Trend
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图 2 1961~2017年(a、c)降水量(PRCPTOT)和(b、d)降水强度(SDII)指数(a、b)气候平均态和(c、d)变化趋势空间分布。(c、d)中蓝色(红色)圆点代表降水指数呈增加(减少)趋势,实心圆点代表趋势通过0.05显著性水平检验,左下角数字代表呈某一趋势的台站数占总台站数百分比
Figure 2. Spatial pattern of (a, b) climatology and (c, d) trend in (a, c) PRCPTOT (total wet-day precipitation) and (b, d) SDII (simple daily precipitation intensity) during 1961–2017. (c–d) The blue (red) dots indicate the increasing (decreasing) trends in precipitation indices; the solid dots indicate the trends are significant at the 95% level; the percentage of stations with different conditions are shown in the bottom left
图 8 1961~2017年极端降水指数呈现显著增加(蓝色)和减少(红色)趋势的台站百分比。其中横坐标表示呈现显著增加或减少趋势的台站百分比,直方图代表1000个bootstrap样本中不同台站百分比对应的发生频率,红色和蓝色直线分别代表对应零假设分布尾部5%的范围,红色和蓝色圆点分别代表对应的台站观测结果。左边两列是内陆河片结果,右边两列是长江流域片、珠江流域片和东南诸河片结果
Figure 8. Percentage of stations with significant increasing (blue) and decreasing (red) trends in extreme precipitation indices. The x-axis represents the percentage of stations with significant increasing or decreasing trends, the histograms denote the distributions of results from 1000 bootstrap samples, the lines mark the upper 5% probability distribution, the dots denote the observed values. The left two columns are the results for continental rivers; the right two columns are the results for the Yangtze River basin, Pearl River basin, and southeastern rivers
图 3 (a)1961~2017年(a、c)PRCPTOT、(b、d)SDII指数呈现(a、b)显著增加、(c、d)显著减少趋势的台站百分比,其中横坐标表示呈现显著增加/减少趋势的台站百分比,直方图代表1000个bootstrap样本中不同台站百分比对应的发生频率,灰色直线代表零假设分布尾部5%的范围,圆点代表台站观测结果
Figure 3. Percentage of stations with (a, b) significant increasing and (c, d) decreasing trends in (a, c) PRCPTOT and (b, d) SDII. The x-axis represents the percentage of stations with significant increasing/decreasing trends, the histograms denote the distributions of results from 1000 bootstrap samples, the gray line marks the upper 5% probability distribution, the dot denotes the observed value
图 4 1961~2017年九大流域片极端降水指数(a、b)Rx5day、(c、d)Rx1day、(e、f)R95p和(g、h)R99p气候态(左列,单位:mm)和变化趋势[右列,单位:(10 a)−1]空间分布。右列中蓝色(红色)圆点代表降水指数呈增加(减少)趋势,实心圆点代表趋势通过95%显著性检验,左下角数字代表呈某一趋势的台站数占总台站数百分比
Figure 4. Spatial pattern of climatology (left column, units: mm) and trend [right column, units: (10 a)−1] in extreme precipitation indices over nine river basins during 1961–2017: (a, b) Rx5day; (c, d) Rx1day; (e, f) R95p; (g, h) R99p. The blue (red) dots in the right columns indicate the increasing (decreasing) trends in precipitation indices; the solid dots indicate the trends are significant at the 95% level, the percentage of stations with different conditions are shown in the bottom left
图 5 1961~2017年极端降水指数(a)Rx5day、(b)Rx1day、(c)R95p、(d)R99p、(e)R10mm、(f)R20mm、(g)CWD和(h)CDD呈现显著增加(蓝色)和减少(红色)趋势的台站百分比。其中横坐标表示呈现显著增加或减少趋势的台站百分比,直方图代表1000个bootstrap样本中不同台站百分比对应的发生频率,红色和蓝色直线分别代表对应零假设分布尾部5%的范围,红色和蓝色圆点分别代表对应的台站观测结果
Figure 5. Percentage of stations with significant increasing (blue) and decreasing (red) trends in extreme precipitation indices: (a) Rx5day, (b) Rx1day, (c) R95p, (d) R99p, (e) R10mm, (f) R20mm, (g) CWD, and (h) CDD. The x-axis represents the percentage of stations with significant increasing or decreasing trends, the histograms denote the distributions of results from 1000 bootstrap samples, the lines mark the upper 5% probability distribution, the dots denote the observed values.
图 6 1961~2017年九大流域片极端降水指数(a、b)R10mm、(c、d)R20mm、(e、f)CWD和(g、h)CDD气候态(左列,单位:d)和变化趋势[右列,单位:(10 a)−1]空间分布。右列中蓝色(红色)圆点代表降水指数呈增加(减少)趋势,其中实心圆点代表趋势通过0.05显著性水平检验,黑色圆点则代表无变化趋势,左下角数字代表呈某一趋势的台站数占总台站数百分比。
Figure 6. Spatial pattern of climatology (left column, units: mm) and trend [right column, units: (10 a)−1] in extreme precipitation indices over nine river basins during 1961–2017: (a, b) R10 mm, (c, d) R20mm, (e, f) CWD, and (g, h) CDD. The blue (red) dots in the right columns indicate the increasing (decreasing) trends in precipitation indices, with solid dots denoting the trends are significant at the 95% level; the black dots indicate no trends in precipitation indices, the percentage of stations with different conditions are shown in the bottom left
图 9 九大流域片降水指数(a)PRCPTOT、(b)SDII、(c)Rx5day、(d)Rx1day、(e)R95p、(f)R99p、(g)R10mm、(h)R20mm、(i)CWD和(j)CDD区域平均变化趋势。绿色(黄色)代表该流域区域平均结果增加(减少),深绿色(棕色)代表该流域区域平均结果显著增加(显著减少);数值为区域平均结果相对于该流域气候态变化趋势,单位:% (10 a)−1
Figure 9. Trends in area-averaged extreme precipitation indices in nine river basins: (a) PRCPTOT, (b) SDII, (c) Rx5day, (d) Rx1day, (e) R95p, (f) R99p, (g) R10mm, (h) R20mm, (i) CWD, and (j) CDD. Green (yellow) shadings indicate increasing (decreasing) trends, dark green (brown) indicate significant increasing (significant decreasing) trends. The numbers denote the area‐averaged trends relative to related climatology, units: % (10 a)−1
图 10 九大流域片降水指数变化概况。平均降水/降水强度为基于PRCPTOT和SDII的综合评估结果,极端强降水为基于Rx1day、R95p和R99p的综合评估结果,连续性强降水基于Rx5day得到,气象干旱基于CDD得到;图中结果为对应的降水指数区域平均变化趋势在0.05的水平下显著,若结果基于多个指数则不同指数变化趋势一致,至少有一个指数变化趋势在0.05的水平下显著。西南诸河片区域平均CDD在0.05的水平下不显著,但其大部分站点呈增加趋势,故标为气象干旱增加。图标来源:https://www.flaticon.com/authors/freepik [2021-01-26]
Figure 10. Changes in precipitation across nine river basins. The results of mean precipitation/precipitation intensity are based on PRCPTOP and SDII, the results of extremely heavy precipitation are based on Rx1day, R95p, and R99p, the results of continuous heavy precipitation are based on Rx5day, results of meteorological drought are based on CDD. The results shown in the figure are for the trends in area-averaged precipitation indices significant at the 95% level. If the results are based on more than one index, all indices increase or decrease, and the trends for at least one index are significant at the 95% level. The trend of area-averaged CDD for southwestern rivers is insignificant at the 95% level, but the CDD increases for most stations, which is marked as an increase of meteorological drought. Icon sources: https://www.flaticon.com/authors/freepik [2021-01-26]
表 1 气候变化检测和指数专家组(ETCCDI)定义的10个降水指数
Table 1. Information for 10 precipitation indices defined by ETCCDI (Expert Team on Climate Change Detection and Indices)
指数 名称 定义 单位 PRCPTOT 年降水量 一年内降水日(日降水量≥1mm)总降水量 mm SDII 降水强度 年降水量与降水日数(日降水量≥1mm)之比 mm d−1 Rx1day 最大日降水量 一年内最大日降水量 mm Rx5day 最大连续5日累计降水量 一年内连续5天最大累计降水量 mm R95p 强降水量 一年内日降水量>研究时段所有日降水95%分位值的累计降水量 mm R99p 极端强降水量 一年内日降水量>研究时段所有日降水99%分位值的累计降水量 mm R10mm 大雨日数 一年内日降水量≥10mm的日数 d R20mm 极端大雨日数 一年内日降水量≥20mm的日数 d CWD 最大连续湿润日数 一年内日降水量≥1mm的最长连续日数 d CDD 最大连续干旱日数 一年内日降水量<1mm的最长连续日数 d 注:详细信息见http://etccdi.pacificclimate.org/list_27_indices.shtml [2021-01-26]。 -
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