The extreme high temperature anomaly (EHTA) events in a region are one of the most important climatic parameters to make climate assessment of the trend of regional climate change. The diagnosis and analysis of the EH...The extreme high temperature anomaly (EHTA) events in a region are one of the most important climatic parameters to make climate assessment of the trend of regional climate change. The diagnosis and analysis of the EHTA event in Zhejiang Province in East China in 2022 show that the event has set the rarest record in this region in the past 71 years from both time and space perspectives. The results of Mann-Kendall trend analysis showed that the mean annual high temperature days in Zhejiang Province had a sudden change. The sudden change occurred around 2004, and the trend was rising after the sudden change.展开更多
In the last decade,North Africa has witnessed significant population growth,particularly those bordering the Mediterranean Sea.This led to increased demand for groundwater,which is an essential source for various wate...In the last decade,North Africa has witnessed significant population growth,particularly those bordering the Mediterranean Sea.This led to increased demand for groundwater,which is an essential source for various water uses such as drinking water supplies and irrigation.Generally,human activities play a crucial role in the different quantitative and qualitative changes in groundwater.Now,climate changes such as a decrease in precipitation have also led to a shortage of water resources and a decline in the groundwater table.This paper presents the impact of climate changes on groundwater resources in the Ain Azel region,Setif,northeastern Algeria.The analysis of longterm spatiotemporal variability in rainfall over 63 years(1958–2021)revealed a significant decline in groundwater recharge,especially after 2013.In contrast,the Pettitt and Mann–Kendall tests show increased temperatures with breaks between 1984 and 1986.A piezometric analysis of the alluvial aquifer demonstrated a significant decline in groundwater levels in the last 20 years.Hydrochemical analysis showed that groundwater in the region is dominated by Ca–Mg–Cl water type,which indicates the presence of water salinity phenomenon.Water Quality Index(WQI)analysis showed the deterioration of groundwater in the area,which may be caused by several factors:brine intrusion from the Salt Lake(Sebkha)in the north;the dissolution of evaporites(Triassic)and/or anthropogenic sources of agricultural and industrial origin.Our findings provide an overview summarizing the state of groundwater,which will help improve groundwater resource management in the region in the coming years.展开更多
This study presents the work commenced in northern Thailand on spatial and temporal variability of rainfall. Thirty years (1988-2017) rainfall data of eight meteorological stations were used for assessing temporal var...This study presents the work commenced in northern Thailand on spatial and temporal variability of rainfall. Thirty years (1988-2017) rainfall data of eight meteorological stations were used for assessing temporal variability and trend analysis. The results showed decreasing trend in rainfall from its first half of the observed study period (1988-2002) to last half of the time period (2003-2017) in total average annual as well as monsoonal average rainfall by 14.92% and 15.50% respectively. It was predicted from linear regression results that by 2030 the average annual and monsoonal rainfall will drop by 35% and 34.10% respectively. All stations showed negative trend except Fakara met-station in annual rainfall. In the seasonal trend analysis, the results showed decreasing trend almost in all met-stations. Mann-Kendall trend test was applied to assess the trend. All met-stations show significant negative trend. To assess drought in the study area, Standardized Precipitation Index (SPI) was applied to 12-month temporal time period. The results predicted meteorological drought in the near future. The spatial distribution of rainfall presented changing phenomena in average annual, monsoonal, winter, and summer seasons in both analyzed periods.展开更多
To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index(NDVI) time series data from 2000 to 20...To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index(NDVI) time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive: regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.展开更多
Wind speed variations are influenced by both natural climate and human activities.It is important to understand the spatial and temporal distributions of wind speed and to analyze the cause of its changes.In this stud...Wind speed variations are influenced by both natural climate and human activities.It is important to understand the spatial and temporal distributions of wind speed and to analyze the cause of its changes.In this study,data from 26 meteorological stations in the Jing-Jin-Ji region of North China from 1961 to 2017 are analyzed by using the Mann-Kendall(MK)test.Over the study period,wind speed first decreased by−0.028 m s^-1 yr^-1(p<0.01)in 1961^-1991,and then increased by 0.002 m s^-1 yr^-1(p<0.05)in 1992-2017.Wind speed was the highest in spring(2.98 m s^-1),followed by winter,summer,and autumn.The largest wind speed changes for 1961-1991 and 1992-2017 occurred in winter(−0.0392 and 0.0065 m s^-1 yr^-1,respectively);these values represented 36%and 58%of the annual wind speed changes.More than 90.4%of the wind speed was concentrated in the range of 1-5 m s^-1,according to the variation in the number of days with wind speed of different grades.Specifically,the decrease in wind speed in 1961^-1991 was due to the decrease in days with wind speed of 3-5 m s^-1,while the increase in wind speed in 1992-2017 was mainly due to the increase in days with wind speed of 2-4 m s^-1.In terms of driving factors,variations in wind speed were closely correlated with temperature and atmospheric pressure,whereas elevation and underlying surface also influenced these changes.展开更多
文摘The extreme high temperature anomaly (EHTA) events in a region are one of the most important climatic parameters to make climate assessment of the trend of regional climate change. The diagnosis and analysis of the EHTA event in Zhejiang Province in East China in 2022 show that the event has set the rarest record in this region in the past 71 years from both time and space perspectives. The results of Mann-Kendall trend analysis showed that the mean annual high temperature days in Zhejiang Province had a sudden change. The sudden change occurred around 2004, and the trend was rising after the sudden change.
文摘In the last decade,North Africa has witnessed significant population growth,particularly those bordering the Mediterranean Sea.This led to increased demand for groundwater,which is an essential source for various water uses such as drinking water supplies and irrigation.Generally,human activities play a crucial role in the different quantitative and qualitative changes in groundwater.Now,climate changes such as a decrease in precipitation have also led to a shortage of water resources and a decline in the groundwater table.This paper presents the impact of climate changes on groundwater resources in the Ain Azel region,Setif,northeastern Algeria.The analysis of longterm spatiotemporal variability in rainfall over 63 years(1958–2021)revealed a significant decline in groundwater recharge,especially after 2013.In contrast,the Pettitt and Mann–Kendall tests show increased temperatures with breaks between 1984 and 1986.A piezometric analysis of the alluvial aquifer demonstrated a significant decline in groundwater levels in the last 20 years.Hydrochemical analysis showed that groundwater in the region is dominated by Ca–Mg–Cl water type,which indicates the presence of water salinity phenomenon.Water Quality Index(WQI)analysis showed the deterioration of groundwater in the area,which may be caused by several factors:brine intrusion from the Salt Lake(Sebkha)in the north;the dissolution of evaporites(Triassic)and/or anthropogenic sources of agricultural and industrial origin.Our findings provide an overview summarizing the state of groundwater,which will help improve groundwater resource management in the region in the coming years.
文摘This study presents the work commenced in northern Thailand on spatial and temporal variability of rainfall. Thirty years (1988-2017) rainfall data of eight meteorological stations were used for assessing temporal variability and trend analysis. The results showed decreasing trend in rainfall from its first half of the observed study period (1988-2002) to last half of the time period (2003-2017) in total average annual as well as monsoonal average rainfall by 14.92% and 15.50% respectively. It was predicted from linear regression results that by 2030 the average annual and monsoonal rainfall will drop by 35% and 34.10% respectively. All stations showed negative trend except Fakara met-station in annual rainfall. In the seasonal trend analysis, the results showed decreasing trend almost in all met-stations. Mann-Kendall trend test was applied to assess the trend. All met-stations show significant negative trend. To assess drought in the study area, Standardized Precipitation Index (SPI) was applied to 12-month temporal time period. The results predicted meteorological drought in the near future. The spatial distribution of rainfall presented changing phenomena in average annual, monsoonal, winter, and summer seasons in both analyzed periods.
基金National Natural Science Foundation of China,No.41171318 National Key Technology Support Program,No.2012BAH32B03+1 种基金No.2012BAH33B05 The Remote Sensing Investigation and Assessment Project for Decade-Change of the National Ecological Environment(2000–2010)
文摘To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index(NDVI) time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive: regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.
基金Supported by the National Key Research and Development Program of China(2016YFC0401407)National Science Fund for Distinguished Young Scholars(51625904).
文摘Wind speed variations are influenced by both natural climate and human activities.It is important to understand the spatial and temporal distributions of wind speed and to analyze the cause of its changes.In this study,data from 26 meteorological stations in the Jing-Jin-Ji region of North China from 1961 to 2017 are analyzed by using the Mann-Kendall(MK)test.Over the study period,wind speed first decreased by−0.028 m s^-1 yr^-1(p<0.01)in 1961^-1991,and then increased by 0.002 m s^-1 yr^-1(p<0.05)in 1992-2017.Wind speed was the highest in spring(2.98 m s^-1),followed by winter,summer,and autumn.The largest wind speed changes for 1961-1991 and 1992-2017 occurred in winter(−0.0392 and 0.0065 m s^-1 yr^-1,respectively);these values represented 36%and 58%of the annual wind speed changes.More than 90.4%of the wind speed was concentrated in the range of 1-5 m s^-1,according to the variation in the number of days with wind speed of different grades.Specifically,the decrease in wind speed in 1961^-1991 was due to the decrease in days with wind speed of 3-5 m s^-1,while the increase in wind speed in 1992-2017 was mainly due to the increase in days with wind speed of 2-4 m s^-1.In terms of driving factors,variations in wind speed were closely correlated with temperature and atmospheric pressure,whereas elevation and underlying surface also influenced these changes.