Changes in vegetation status generally also represents changes in the ecological health of islands and reefs(IRs).However,studies are limited of drivers and trends of vegetation change of Nansha Islands,China and how ...Changes in vegetation status generally also represents changes in the ecological health of islands and reefs(IRs).However,studies are limited of drivers and trends of vegetation change of Nansha Islands,China and how they relate to climate change and human activities.To resolve this limitation,we studied changes to the Normalized Difference Vegetation Index(NDVI)vegetation-greenness index for 22 IRs of Nansha Islands during normal and extreme conditions.Trends of vegetation greenness were analyzed using Sen's slope and Mann-Kendall test at two spatial scales(pixel and island),and driving factor analyses were performed by time-lagged partial correlation analyses.These were related to impacts from human activities and climatic factors under normal(temperature,precipitation,radiation,and Normalized Difference Built-up Index(NDBI))and extreme conditions(wind speed and latitude of IRs)from 2016 to 2022.Results showed:1)among the 22 IRs,NDVI increased/decreased significantly in 15/4 IRs,respectively.Huayang Reef had the highest NDVI change-rate(0.48%/mon),and Zhongye Island had the lowest(–0.29%/mon).Local spatial patterns were in one of two forms:dotted-form,and degradation in banded-form.2)Under normal conditions,human activities(characterized by NDBI)had higher impacts on vegetation-greenness than other factors.3)Under extreme conditions,wind speed(R^(2)=0.2337,P<0.05)and latitude(R^(2)=0.2769,P<0.05)provided limited explanation for changes from typhoon events.Our results provide scientific support for the sustainable development of Nansha Islands and the United Nations‘Ocean Decade’initiative.展开更多
Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of...Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.展开更多
A comparative study of extreme temperature parameters from different sources is carried out by examining standardized anomalies, trends, correlation, and equivalence of datasets. Maximum temperature （Tmax） and minim...A comparative study of extreme temperature parameters from different sources is carried out by examining standardized anomalies, trends, correlation, and equivalence of datasets. Maximum temperature （Tmax） and minimum temperature （Wmln） for Dehradun, from two different sources such as computed and gridded data from Climatic Research Unit （CRU） and observed data from India Meteorological Department （IMD） are used for 1901-2012. The CRU data are compared initially with IMD, by graphical assessment of standardized anomalies. Subsequently, change points are identified by using Cumulative Sum （CUSUM）-chart technique for trend analysis. The magnitude and significance of trends are determined by applying Sen＇s slope test, and on the basis of these, trends are compared. Further, correlation analysis is carried out and datasets are tested for equivalence by using Wileoxon-Mann Whitney test. The result shows that annual standardized anomalies of CRU data follow the pattern of annual standardized anomalies of IMD data. The CRU data exhibit similar trends and are well correlated with IMD dataset. Moreover, CRU anomaly data are identical with IMD anomaly data in the recent decades. High resolution gridded CRU data have open access and may be more useful due to its spatio-temporal continuity for land areas of the world.展开更多
In the context of climate variability resulting in a decrease in rainfall with a severe drought, a spatio-temporal study of this phenomenon remains imperative for the efficient management of water resources. This pape...In the context of climate variability resulting in a decrease in rainfall with a severe drought, a spatio-temporal study of this phenomenon remains imperative for the efficient management of water resources. This paper aims to assess the long-term rainfall drought trend and breakpoints within the Comoe River watershed. From monthly rainfall data series (1960-2000), Standardized Precipitation Index (SPI) values were calculated for a time scale of 3 months (SPI.3). Statistical tests for breaks (CUSUM, and t-Student) and trends (Man-Kendall and Linear Regression) as well as the Sen’ slope method for estimating the magnitude of trends w<span style="font-family:Verdana;">as</span><span style="font-family:Verdana;"> applied. The breaks dates observed are mostly located after the 1970s. Based on SPI.3 values below the threshold of 0.84 chosen as an indicator of drought, rarely has more than half of the catchment area been affected by drought. The average watershed affected is about 20% over the study period (1960-2000). The most representative years, in terms of spatial expansion of the drought, in decreasing order of importance are: 1983, 1992, 1972 and 1982. The years 1982 and 1983 stand out for their exceptional condition, as the drought-affected 50% to 90% of the total catchment area. SPI.3 series from 1960 to the various break dates recorded slopes between </span><span style="font-family:Verdana;"><span style="white-space:nowrap;">-</span>0.01 and 0.00 with a slight drought trend for most of the catchment. After the break periods, almost the entire northern part of the basin is characterized by slight moisture with Sen’s slopes between 0.000 and 0.005. The southern part will remain slightly subject to normal rainfall conditions.</span>展开更多
Trends in rainy/non-rainy days are investigated using the Mann-Kendall non-parametric test at 249 weather station sites of North Carolina, United States. Sen-Slope method has been applied to predict the trend magnitud...Trends in rainy/non-rainy days are investigated using the Mann-Kendall non-parametric test at 249 weather station sites of North Carolina, United States. Sen-Slope method has been applied to predict the trend magnitude. Inverse distance weighing interpolation technique is adopted to represent the spatial distribution of trend magnitude across the North Carolina. Quality controlled daily precipitation data sets from 1950 to 2009 have been used to analyze. The double-mass curve and autocorrelation were adopted to analyze the precipitation time series of each station to check the consistency and homogeneity. Standard Precipitation Index (SPI) has also been discussed for the study area. It is found in North Carolina that a number of rainy day trends are increasing both spatially and temporally. Eastern part of North Carolina shows the significant increasing rainy day trends. Trend significance has been checked at 1% and 5% significance level. Recent decades show the high SPI in both the extent of wetness and dryness.展开更多
A quantitative study was used in the study of the tendency to change drought indicators in Vietnam through the Ninh Thuan province case study. The research data are temperature and precipitation data of 11 stations fr...A quantitative study was used in the study of the tendency to change drought indicators in Vietnam through the Ninh Thuan province case study. The research data are temperature and precipitation data of 11 stations from 1986 to 2016 inside and outside Ninh Thuan province. To do the research, the author uses a non-parametric analysis method and the drought index calculation method. Specifically, with the non-parametric method, the author uses the analysis, Mann-Kendall (MK) and Theil-Sen (Sen’s slope), and to analyze drought, the author uses the Standardized Precipitation Index (SPI) and the Moisture Index (MI). Two Softwares calculated in this study are ProUCL 5.1 and MAKENSEN 1.0 by the US Environmental Protection Agency and Finnish Meteorological Institute. The calculation results show that meteorological drought will decrease in the future with areas such as Phan Rang, Song Pha, Quan The, Ba Thap tend to increase very clearly, while Tam My and Nhi Ha tend to increase very clearly short. With the agricultural drought, the average MI results increased 0.013 per year, of which Song Pha station tended to increase the highest with 0.03 per year and lower with Nhi Ha with 0.001 per year. The forecast results also show that by the end of the 21st century, the SPI tends to decrease with SPI 1 being <span style="white-space:nowrap;">−</span>0.68, SPI 3 being <span style="white-space:nowrap;">−</span>0.40, SPI 6 being <span style="white-space:nowrap;">−</span>0.25, SPI 12 is 0.42. Along with that is the forecast that the MI index will increase 0.013 per year to 2035, the MI index is 0.93, in 2050 it is 1.13, in 2075 it will be 1.46, and by 2100 it is 1.79. Research results will be used in policymaking, environmental resources management agencies, and researchers to develop and study solutions to adapt and mitigate drought in the context of variable climate change.展开更多
Recently, study in past trends of climate variables gained significant consideration because of its contribution in adaptions and mitigation strategies for potential future changes in climate, primarily in the area of...Recently, study in past trends of climate variables gained significant consideration because of its contribution in adaptions and mitigation strategies for potential future changes in climate, primarily in the area of water resource management. Future interannual and inter-seasonal variations in maximum and minimum temperature may bring significant changes in hydrological systems and affect regional water resources. The present study has been performed to observe past(1970-2010) as well as future(2011-2100)spatial and temporal variability in temperature(maximum and minimum) over selected stations of Sutlej basin located in North-Western Himalayan region in India. The generation of future time series of temperature data at different stations is done using statistical downscaling technique. The nonparametric test methods, modified Mann-Kendall test and Cumulative Sum chart are used for detecting monotonic trend and sequential shift in time series of maximum and minimum temperature. Sen's slope estimator test is used to detect the magnitude of change over a period of time on annual and seasonal basis. The cooling experienced in annual TMax and TMin at Kasol in past(1970-2010) would be replaced by warming in future as increasing trends are detected in TMax during 2020 s and 2050 s and in TMin during 2020 s, 2050 s and 2080 s under A1 B and A2 scenarios. Similar results of warming are also predicted at Sunnifor annual TMin in future under both scenarios which witnessed cooling during 1970-2010. The rise in TMin at Rampur is predicted to be continued in future as increasing trends are obtained under both the scenarios. Seasonal trend analysis reveals large variability in trends of TMax and TMin over these stations for the future periods.展开更多
基金Under the auspices of National Key Research and Development Program of China (No.2022YFC3103103)。
文摘Changes in vegetation status generally also represents changes in the ecological health of islands and reefs(IRs).However,studies are limited of drivers and trends of vegetation change of Nansha Islands,China and how they relate to climate change and human activities.To resolve this limitation,we studied changes to the Normalized Difference Vegetation Index(NDVI)vegetation-greenness index for 22 IRs of Nansha Islands during normal and extreme conditions.Trends of vegetation greenness were analyzed using Sen's slope and Mann-Kendall test at two spatial scales(pixel and island),and driving factor analyses were performed by time-lagged partial correlation analyses.These were related to impacts from human activities and climatic factors under normal(temperature,precipitation,radiation,and Normalized Difference Built-up Index(NDBI))and extreme conditions(wind speed and latitude of IRs)from 2016 to 2022.Results showed:1)among the 22 IRs,NDVI increased/decreased significantly in 15/4 IRs,respectively.Huayang Reef had the highest NDVI change-rate(0.48%/mon),and Zhongye Island had the lowest(–0.29%/mon).Local spatial patterns were in one of two forms:dotted-form,and degradation in banded-form.2)Under normal conditions,human activities(characterized by NDBI)had higher impacts on vegetation-greenness than other factors.3)Under extreme conditions,wind speed(R^(2)=0.2337,P<0.05)and latitude(R^(2)=0.2769,P<0.05)provided limited explanation for changes from typhoon events.Our results provide scientific support for the sustainable development of Nansha Islands and the United Nations‘Ocean Decade’initiative.
基金Under the auspices of National Natural Science Foundation of China(No.52279016,51909106,51879108,42002247,41471160)Natural Science Foundation of Guangdong Province,China(No.2020A1515011038,2020A1515111054)+1 种基金Special Fund for Science and Technology Development in 2016 of Department of Science and Technology of Guangdong Province,China(No.2016A020223007)the Project of Jinan Science and Technology Bureau(No.2021GXRC070)。
文摘Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.
基金Supported by the Ministry of Human Resource Development of India for Doctoral Program
文摘A comparative study of extreme temperature parameters from different sources is carried out by examining standardized anomalies, trends, correlation, and equivalence of datasets. Maximum temperature （Tmax） and minimum temperature （Wmln） for Dehradun, from two different sources such as computed and gridded data from Climatic Research Unit （CRU） and observed data from India Meteorological Department （IMD） are used for 1901-2012. The CRU data are compared initially with IMD, by graphical assessment of standardized anomalies. Subsequently, change points are identified by using Cumulative Sum （CUSUM）-chart technique for trend analysis. The magnitude and significance of trends are determined by applying Sen＇s slope test, and on the basis of these, trends are compared. Further, correlation analysis is carried out and datasets are tested for equivalence by using Wileoxon-Mann Whitney test. The result shows that annual standardized anomalies of CRU data follow the pattern of annual standardized anomalies of IMD data. The CRU data exhibit similar trends and are well correlated with IMD dataset. Moreover, CRU anomaly data are identical with IMD anomaly data in the recent decades. High resolution gridded CRU data have open access and may be more useful due to its spatio-temporal continuity for land areas of the world.
文摘In the context of climate variability resulting in a decrease in rainfall with a severe drought, a spatio-temporal study of this phenomenon remains imperative for the efficient management of water resources. This paper aims to assess the long-term rainfall drought trend and breakpoints within the Comoe River watershed. From monthly rainfall data series (1960-2000), Standardized Precipitation Index (SPI) values were calculated for a time scale of 3 months (SPI.3). Statistical tests for breaks (CUSUM, and t-Student) and trends (Man-Kendall and Linear Regression) as well as the Sen’ slope method for estimating the magnitude of trends w<span style="font-family:Verdana;">as</span><span style="font-family:Verdana;"> applied. The breaks dates observed are mostly located after the 1970s. Based on SPI.3 values below the threshold of 0.84 chosen as an indicator of drought, rarely has more than half of the catchment area been affected by drought. The average watershed affected is about 20% over the study period (1960-2000). The most representative years, in terms of spatial expansion of the drought, in decreasing order of importance are: 1983, 1992, 1972 and 1982. The years 1982 and 1983 stand out for their exceptional condition, as the drought-affected 50% to 90% of the total catchment area. SPI.3 series from 1960 to the various break dates recorded slopes between </span><span style="font-family:Verdana;"><span style="white-space:nowrap;">-</span>0.01 and 0.00 with a slight drought trend for most of the catchment. After the break periods, almost the entire northern part of the basin is characterized by slight moisture with Sen’s slopes between 0.000 and 0.005. The southern part will remain slightly subject to normal rainfall conditions.</span>
文摘Trends in rainy/non-rainy days are investigated using the Mann-Kendall non-parametric test at 249 weather station sites of North Carolina, United States. Sen-Slope method has been applied to predict the trend magnitude. Inverse distance weighing interpolation technique is adopted to represent the spatial distribution of trend magnitude across the North Carolina. Quality controlled daily precipitation data sets from 1950 to 2009 have been used to analyze. The double-mass curve and autocorrelation were adopted to analyze the precipitation time series of each station to check the consistency and homogeneity. Standard Precipitation Index (SPI) has also been discussed for the study area. It is found in North Carolina that a number of rainy day trends are increasing both spatially and temporally. Eastern part of North Carolina shows the significant increasing rainy day trends. Trend significance has been checked at 1% and 5% significance level. Recent decades show the high SPI in both the extent of wetness and dryness.
文摘A quantitative study was used in the study of the tendency to change drought indicators in Vietnam through the Ninh Thuan province case study. The research data are temperature and precipitation data of 11 stations from 1986 to 2016 inside and outside Ninh Thuan province. To do the research, the author uses a non-parametric analysis method and the drought index calculation method. Specifically, with the non-parametric method, the author uses the analysis, Mann-Kendall (MK) and Theil-Sen (Sen’s slope), and to analyze drought, the author uses the Standardized Precipitation Index (SPI) and the Moisture Index (MI). Two Softwares calculated in this study are ProUCL 5.1 and MAKENSEN 1.0 by the US Environmental Protection Agency and Finnish Meteorological Institute. The calculation results show that meteorological drought will decrease in the future with areas such as Phan Rang, Song Pha, Quan The, Ba Thap tend to increase very clearly, while Tam My and Nhi Ha tend to increase very clearly short. With the agricultural drought, the average MI results increased 0.013 per year, of which Song Pha station tended to increase the highest with 0.03 per year and lower with Nhi Ha with 0.001 per year. The forecast results also show that by the end of the 21st century, the SPI tends to decrease with SPI 1 being <span style="white-space:nowrap;">−</span>0.68, SPI 3 being <span style="white-space:nowrap;">−</span>0.40, SPI 6 being <span style="white-space:nowrap;">−</span>0.25, SPI 12 is 0.42. Along with that is the forecast that the MI index will increase 0.013 per year to 2035, the MI index is 0.93, in 2050 it is 1.13, in 2075 it will be 1.46, and by 2100 it is 1.79. Research results will be used in policymaking, environmental resources management agencies, and researchers to develop and study solutions to adapt and mitigate drought in the context of variable climate change.
基金financial support in the form of fellowship provided by University Grant Commission (UGC), Government of India to Mr. Dharmaveer Singh as Research Fellow for carrying out the research
文摘Recently, study in past trends of climate variables gained significant consideration because of its contribution in adaptions and mitigation strategies for potential future changes in climate, primarily in the area of water resource management. Future interannual and inter-seasonal variations in maximum and minimum temperature may bring significant changes in hydrological systems and affect regional water resources. The present study has been performed to observe past(1970-2010) as well as future(2011-2100)spatial and temporal variability in temperature(maximum and minimum) over selected stations of Sutlej basin located in North-Western Himalayan region in India. The generation of future time series of temperature data at different stations is done using statistical downscaling technique. The nonparametric test methods, modified Mann-Kendall test and Cumulative Sum chart are used for detecting monotonic trend and sequential shift in time series of maximum and minimum temperature. Sen's slope estimator test is used to detect the magnitude of change over a period of time on annual and seasonal basis. The cooling experienced in annual TMax and TMin at Kasol in past(1970-2010) would be replaced by warming in future as increasing trends are detected in TMax during 2020 s and 2050 s and in TMin during 2020 s, 2050 s and 2080 s under A1 B and A2 scenarios. Similar results of warming are also predicted at Sunnifor annual TMin in future under both scenarios which witnessed cooling during 1970-2010. The rise in TMin at Rampur is predicted to be continued in future as increasing trends are obtained under both the scenarios. Seasonal trend analysis reveals large variability in trends of TMax and TMin over these stations for the future periods.
