The observed intensity, frequency, and duration（IFD） of summer wet spells, defined here as extreme events with one or more consecutive days in which daily precipitation exceeds a given threshold（the 95th percentile...The observed intensity, frequency, and duration（IFD） of summer wet spells, defined here as extreme events with one or more consecutive days in which daily precipitation exceeds a given threshold（the 95th percentile）, and their future changes in RCP4.5 and RCP8.5 in the late 21st century over China, are investigated by using the wet spell model（WSM） and by extending the point process approach to extreme value analysis. Wet spell intensity is modeled by a conditional generalized Pareto distribution, frequency by a Poisson distribution, and duration by a geometric distribution, respectively. The WSM is able to realistically model summer extreme rainfall spells during 1961–2005, as verified with observations at 553 stations throughout China. To minimize the impact of systematic biases over China in the global climate models（GCMs） of the Coupled Model Intercomparison Project Phase 5（CMIP5）, five best GCMs are selected based on their performance to reproduce observed wet spell IFD and average precipitation during the historical period. Furthermore, a quantile–quantile scaling correction procedure is proposed and applied to produce ensemble projections of wet spell IFD and corresponding probability distributions. The results show that in the late 21st century, most of China will experience more extreme rainfall and less low-intensity rainfall. The intensity and frequency of wet spells are projected to increase considerably, while the duration of wet spells will increase but to a much less extent. The IFD changes in RCP8.5 are in general much larger than those in RCP4.5.展开更多
For the purpose of crop planning and to carry out the agricultural practices,it is important to know the sequence of dry and wet periods.The present study was undertaken with the objectives to forecast dry and wet spe...For the purpose of crop planning and to carry out the agricultural practices,it is important to know the sequence of dry and wet periods.The present study was undertaken with the objectives to forecast dry and wet spell analysis using Markov chain model and also to find out the exact time of onset and termination of monsoon at study area for North Lakhimpur(Assam),India using weekly rainfall data for a period of 24 years.The results indicated that probability of occurrence of dry week is higher from week 1st to 14^(th) and also from week 41^(st) to 52^(nd).The range of probability of occurrence of dry week in these weeks varies from 41.67% to 100%.Probability of occurrence of wet week is higher from week 17^(th) to 40^(th).The range of probability of wet week in these weeks varies from 66.67% to 100%.Week 1^(st) to 4^(th) and 43^(rd) to 52^(nd) of the year remains under stress on an average,as there are 50% to 95.83% chances of occurrence of two consecutive dry weeks.The analysis showed that monsoon starts effectively from week 23^(rd)(4^(th) June to 10^(th) June)in North Lakhimpur.The week 25^(th)(18^(th) June to 24^(th) June)is ideal time for initiation of wet land preparation for growing short duration rice variety.Pre-monsoon effectively starts from week 14^(th)(2^(nd) April to 8^(th) April).On week 14^(th) sowing of summer maize(rain fed)may be done.Week 15^(th)(9^(th) April to 15^(th) April)is ideal time for initiation of wet land preparation for growing long duration rice variety.展开更多
Monthly data of Self-Calibrated Palmer Drought Severity Index (PDSI) from 1951 to 2000 are calculated using historical precipitation and temperature data for Chinese 160 stations. Temporal and spatial pat-terns of the...Monthly data of Self-Calibrated Palmer Drought Severity Index (PDSI) from 1951 to 2000 are calculated using historical precipitation and temperature data for Chinese 160 stations. Temporal and spatial pat-terns of the first empirical orthogonal function (EOF) of the PDSI reveals a fairly linear trend resulting from trends in precipitation and surface temperature, which is similar to the linear PDSI trend during 1951―2000 calculated using all monthly data. The EOF analysis also reveals that the leading mode correlates significantly with ENSO events in time and space. The ENSO EOF shows that during the typical warm phase of ENSO, surface conditions are drier in most regions of China, especially North China, but wetter than normal in the southern regions of Changjiang River, and Northwest China. During the typical cold phase of ENSO, these anomalies reverse sign. From 1951 to 2000, there are large multi-year to decadal variations in droughts and wet spells over China, which are all closely related to strong El Nio events. In other words, when one strong El Nio event happens, there is a possible big variability in droughts and wet spells over China on the multi-year or decadal scale. Studies also sug-gest that during the last 2―3 decades climate changes over China, especially North China's drying and northwest China's wetting, are closely related to the shift in ENSO towards warmer events and global warming since the late 1970s. The instability of the relationship is also studied. It is revealed that there is a good correlation between ENSO and Chinese variations in droughts and wet spells in the 3―8-year band, but the correlation between ENSO and Chinese variations in droughts and wet spells is instable. Studies suggest that there are decadal changes in the correlation: the wavelet coherency between ENSO and Chinese variations in droughts and wet spells is high during 1951―1962 and 1976―1991, but low during 1963―1975 and 1992―2000.展开更多
Rainfall is a key climate parameter that affects most operations that affect human life, especially in the tropics. Therefore, understanding the various factors that affect the distribution and intensity of this rainf...Rainfall is a key climate parameter that affects most operations that affect human life, especially in the tropics. Therefore, understanding the various factors that affect the distribution and intensity of this rainfall is important for effective planning among the different stakeholders in the weather and climate sectors. This study aimed at understanding how intra seasonal rainfall characteristics, especially Consecutive Dry Days (CDD) and Consecutive Wet Days (CWD), in the two major rainfall seasons will change under two future climate scenarios of RCP4.5 and RCP8.5 in Uganda, covering two future periods of 2021-2050 and 2051-2080. The results indicate a high likelihood of reduced consecutive rainfall days, especially over the Northeastern regions of the country, for both 2021-2050 and 2051-2080. However, the trends in the entire country for the two major rainfall seasons, March to May and September to November, are not significant. Nonetheless, the distribution of these days is important for most agricultural activities during different stages of crop growth. The consecutive dry days show a fairly increasing trend in the eastern part of the country, particularly in the second season of September to November. An increase in consecutive dry days implies more frequent dry spells in the midst of the growing season, potentially affecting some crops during critical growth stages.展开更多
为了按不同的应用需求生成可信的任意长序列逐日天气数据,为作物天气系统研究提供数据支持,该文描述了一个以干湿期随机模型为基础,组合了日降水量、温度和辐射变量随机模型的逐日天气发生器WGDWS(Weather Generator based on Dry and W...为了按不同的应用需求生成可信的任意长序列逐日天气数据,为作物天气系统研究提供数据支持,该文描述了一个以干湿期随机模型为基础,组合了日降水量、温度和辐射变量随机模型的逐日天气发生器WGDWS(Weather Generator based on Dry and Wet Spells)。它分为两部分:以干湿期为独立随机变量的干湿期模型部分,和依赖第一种模型生成其余天气变量的模型部分;其天气要素的生成主要分2个步骤,即首先根据月经验分布值产生一个干期或湿期长度,然后生成干期或湿期的逐日值。利用代表中国不同地理区域的9个站点1973-2003年的逐日气象资料对天气发生器WGDWS进行了检验,并与基于干湿日开发的DWSS天气发生器进行了比较。结果表明两者性能基本相近,并且WGDWS模拟干湿期的效果更好。因此,WGDWS天气发生器用于生成逐日天气序列是可靠的,同时作为一个JAVA组件,还可以方便地嵌入作物模型系统。展开更多
为了检验基于干湿期的天气发生器(Weather Generator based on Dry and Wet Spells,WGDWS)在中国不同气候区的应用效果,该研究利用中国五大主要气候区16个站点57a的逐日天气数据,通过对比生成与实测气象要素统计值,及比较WGDWS与随机天...为了检验基于干湿期的天气发生器(Weather Generator based on Dry and Wet Spells,WGDWS)在中国不同气候区的应用效果,该研究利用中国五大主要气候区16个站点57a的逐日天气数据,通过对比生成与实测气象要素统计值,及比较WGDWS与随机天气模拟器(Daily Weather Stochastic Simulator,DWSS)生成的气象要素统计值,测试WGDWS的可用性和准确性。显著性检验表明,WGDWS产生的每个气象要素的月值和干湿期长度与实测值相比没有显著差异。月最高、最低气温绝对误差≤0.5℃的站点比例分别达93.8%和96.4%,月降水日数绝对误差≤1d的站点比例达95.8%,月降水量绝对误差有91.7%的站点在10mm之内,月太阳总辐射绝对误差2MJ/m^(2)以内的站点比例达90.1%;月最长干期、最长湿期、平均干期、平均湿期的平均绝对误差分别为4.16、0.76、1.00、0.15d。WGDWS在温带季风和亚热带季风气候下的干湿期模拟效果优于温带大陆气候和热带季风气候。比较WGDWS和DWSS生成的逐日模拟序列的误差分布,月最高气温、月最低气温和月总太阳辐射的误差分布高度一致。WGDWS对月降水日数的模拟效果优于DWSS,即等概率条件下,WGDWS相对误差更小,而DWSS对月降水量的模拟效果优于WGDWS。因此,WGDWS能够准确反映长期干旱或长期阴雨天气的实际情况,可用于生成长序列逐日天气数据,以满足气候模型、水分模型和作物生理模型的需求。展开更多
基金National Key Research and Development Program of China(2017YFA0603804)China Meteorological Administration Special Public Welfare Research Fund(GYHY201306024)National Natural Science Foundation of China(41230528)
文摘The observed intensity, frequency, and duration（IFD） of summer wet spells, defined here as extreme events with one or more consecutive days in which daily precipitation exceeds a given threshold（the 95th percentile）, and their future changes in RCP4.5 and RCP8.5 in the late 21st century over China, are investigated by using the wet spell model（WSM） and by extending the point process approach to extreme value analysis. Wet spell intensity is modeled by a conditional generalized Pareto distribution, frequency by a Poisson distribution, and duration by a geometric distribution, respectively. The WSM is able to realistically model summer extreme rainfall spells during 1961–2005, as verified with observations at 553 stations throughout China. To minimize the impact of systematic biases over China in the global climate models（GCMs） of the Coupled Model Intercomparison Project Phase 5（CMIP5）, five best GCMs are selected based on their performance to reproduce observed wet spell IFD and average precipitation during the historical period. Furthermore, a quantile–quantile scaling correction procedure is proposed and applied to produce ensemble projections of wet spell IFD and corresponding probability distributions. The results show that in the late 21st century, most of China will experience more extreme rainfall and less low-intensity rainfall. The intensity and frequency of wet spells are projected to increase considerably, while the duration of wet spells will increase but to a much less extent. The IFD changes in RCP8.5 are in general much larger than those in RCP4.5.
文摘For the purpose of crop planning and to carry out the agricultural practices,it is important to know the sequence of dry and wet periods.The present study was undertaken with the objectives to forecast dry and wet spell analysis using Markov chain model and also to find out the exact time of onset and termination of monsoon at study area for North Lakhimpur(Assam),India using weekly rainfall data for a period of 24 years.The results indicated that probability of occurrence of dry week is higher from week 1st to 14^(th) and also from week 41^(st) to 52^(nd).The range of probability of occurrence of dry week in these weeks varies from 41.67% to 100%.Probability of occurrence of wet week is higher from week 17^(th) to 40^(th).The range of probability of wet week in these weeks varies from 66.67% to 100%.Week 1^(st) to 4^(th) and 43^(rd) to 52^(nd) of the year remains under stress on an average,as there are 50% to 95.83% chances of occurrence of two consecutive dry weeks.The analysis showed that monsoon starts effectively from week 23^(rd)(4^(th) June to 10^(th) June)in North Lakhimpur.The week 25^(th)(18^(th) June to 24^(th) June)is ideal time for initiation of wet land preparation for growing short duration rice variety.Pre-monsoon effectively starts from week 14^(th)(2^(nd) April to 8^(th) April).On week 14^(th) sowing of summer maize(rain fed)may be done.Week 15^(th)(9^(th) April to 15^(th) April)is ideal time for initiation of wet land preparation for growing long duration rice variety.
基金Supported by the Key Program of the Chinese Academy of Sciences (Grant No. KZCX3-SW-221)the National Natural Science Foundation of China (Grant No. 40475037)
文摘Monthly data of Self-Calibrated Palmer Drought Severity Index (PDSI) from 1951 to 2000 are calculated using historical precipitation and temperature data for Chinese 160 stations. Temporal and spatial pat-terns of the first empirical orthogonal function (EOF) of the PDSI reveals a fairly linear trend resulting from trends in precipitation and surface temperature, which is similar to the linear PDSI trend during 1951―2000 calculated using all monthly data. The EOF analysis also reveals that the leading mode correlates significantly with ENSO events in time and space. The ENSO EOF shows that during the typical warm phase of ENSO, surface conditions are drier in most regions of China, especially North China, but wetter than normal in the southern regions of Changjiang River, and Northwest China. During the typical cold phase of ENSO, these anomalies reverse sign. From 1951 to 2000, there are large multi-year to decadal variations in droughts and wet spells over China, which are all closely related to strong El Nio events. In other words, when one strong El Nio event happens, there is a possible big variability in droughts and wet spells over China on the multi-year or decadal scale. Studies also sug-gest that during the last 2―3 decades climate changes over China, especially North China's drying and northwest China's wetting, are closely related to the shift in ENSO towards warmer events and global warming since the late 1970s. The instability of the relationship is also studied. It is revealed that there is a good correlation between ENSO and Chinese variations in droughts and wet spells in the 3―8-year band, but the correlation between ENSO and Chinese variations in droughts and wet spells is instable. Studies suggest that there are decadal changes in the correlation: the wavelet coherency between ENSO and Chinese variations in droughts and wet spells is high during 1951―1962 and 1976―1991, but low during 1963―1975 and 1992―2000.
文摘Rainfall is a key climate parameter that affects most operations that affect human life, especially in the tropics. Therefore, understanding the various factors that affect the distribution and intensity of this rainfall is important for effective planning among the different stakeholders in the weather and climate sectors. This study aimed at understanding how intra seasonal rainfall characteristics, especially Consecutive Dry Days (CDD) and Consecutive Wet Days (CWD), in the two major rainfall seasons will change under two future climate scenarios of RCP4.5 and RCP8.5 in Uganda, covering two future periods of 2021-2050 and 2051-2080. The results indicate a high likelihood of reduced consecutive rainfall days, especially over the Northeastern regions of the country, for both 2021-2050 and 2051-2080. However, the trends in the entire country for the two major rainfall seasons, March to May and September to November, are not significant. Nonetheless, the distribution of these days is important for most agricultural activities during different stages of crop growth. The consecutive dry days show a fairly increasing trend in the eastern part of the country, particularly in the second season of September to November. An increase in consecutive dry days implies more frequent dry spells in the midst of the growing season, potentially affecting some crops during critical growth stages.
文摘为了按不同的应用需求生成可信的任意长序列逐日天气数据,为作物天气系统研究提供数据支持,该文描述了一个以干湿期随机模型为基础,组合了日降水量、温度和辐射变量随机模型的逐日天气发生器WGDWS(Weather Generator based on Dry and Wet Spells)。它分为两部分:以干湿期为独立随机变量的干湿期模型部分,和依赖第一种模型生成其余天气变量的模型部分;其天气要素的生成主要分2个步骤,即首先根据月经验分布值产生一个干期或湿期长度,然后生成干期或湿期的逐日值。利用代表中国不同地理区域的9个站点1973-2003年的逐日气象资料对天气发生器WGDWS进行了检验,并与基于干湿日开发的DWSS天气发生器进行了比较。结果表明两者性能基本相近,并且WGDWS模拟干湿期的效果更好。因此,WGDWS天气发生器用于生成逐日天气序列是可靠的,同时作为一个JAVA组件,还可以方便地嵌入作物模型系统。
文摘为了检验基于干湿期的天气发生器(Weather Generator based on Dry and Wet Spells,WGDWS)在中国不同气候区的应用效果,该研究利用中国五大主要气候区16个站点57a的逐日天气数据,通过对比生成与实测气象要素统计值,及比较WGDWS与随机天气模拟器(Daily Weather Stochastic Simulator,DWSS)生成的气象要素统计值,测试WGDWS的可用性和准确性。显著性检验表明,WGDWS产生的每个气象要素的月值和干湿期长度与实测值相比没有显著差异。月最高、最低气温绝对误差≤0.5℃的站点比例分别达93.8%和96.4%,月降水日数绝对误差≤1d的站点比例达95.8%,月降水量绝对误差有91.7%的站点在10mm之内,月太阳总辐射绝对误差2MJ/m^(2)以内的站点比例达90.1%;月最长干期、最长湿期、平均干期、平均湿期的平均绝对误差分别为4.16、0.76、1.00、0.15d。WGDWS在温带季风和亚热带季风气候下的干湿期模拟效果优于温带大陆气候和热带季风气候。比较WGDWS和DWSS生成的逐日模拟序列的误差分布,月最高气温、月最低气温和月总太阳辐射的误差分布高度一致。WGDWS对月降水日数的模拟效果优于DWSS,即等概率条件下,WGDWS相对误差更小,而DWSS对月降水量的模拟效果优于WGDWS。因此,WGDWS能够准确反映长期干旱或长期阴雨天气的实际情况,可用于生成长序列逐日天气数据,以满足气候模型、水分模型和作物生理模型的需求。
