Alps are an important geographical area of the European continent and,in this area,temperature increase is most evident.However,the 1991-2020 climate normal in the Alps has still not been thoroughly investigated.Aimin...Alps are an important geographical area of the European continent and,in this area,temperature increase is most evident.However,the 1991-2020 climate normal in the Alps has still not been thoroughly investigated.Aiming to fill this gap with a focus on high-elevation environments,minimum and maximum daily air temperature acquired by 23 automatic weather station were used.The results show that the mean annual values of minimum and maximum temperature for the 1991-2020 climate normal in the Alps are-2.4℃ and 4.4℃,respectively,with a warming rate of 0.5℃/10 years.The mean annual temperature comparison between 1961-1990 and 1971-2000,1961-1990 and 1981-2010,1961-1990 and 1991-2020 climate normal show an increase of 0.3℃,0.5℃ and 0.9℃,respectively.The results also confirm that seasonal and annual temperatures are rising through the whole Alpine arc,mainly in summer and autumn.This work highlights that annual minimum and maximum temperature do not seem to be affected by a positive elevation-dependent warming.Instead,a positive elevation-dependent warming in the maximum values of the annual minimum temperature was found.If anthropogenic emissions maintain the trend of the last decades,the expected mean annual temperature of the 2001-2030 climate normal is-0.2℃,with an increase of 0.5℃ if compared to the 1991-2020 climate normal and with an increase of 1.5℃ if compared to the 1961-1990 climate normal.This study highlights the warming rate that is now present in the European Alps,provides indications on the warming rate that will occur in the coming years and highlights the importance of carrying out investigations that consider not only the last 30-year climate normal,but also the most recent 30-year climate normal by comparing them with each other.展开更多
Climate normal calculation over Oman is a key challenge due to scattered and inconsistent ground observations.Based on the available observations record to calculate the normal,the study derives the Provisional Climat...Climate normal calculation over Oman is a key challenge due to scattered and inconsistent ground observations.Based on the available observations record to calculate the normal,the study derives the Provisional Climate Normal.The data from selected stations in this project have been tested and investigated by using the quality check and missing data evaluation.It is found that ERA-5 is the best reanalysis data in temperature as the correlation coefficient is higher compared to ERA-5 land and MERRA-2 which explains the reason for choosing ERA-5 data to calculate the regression model to fulfil the missing data.By using MODIS data,the Urban Heat Island Index(UHI)shows that Sohar and Muscat stations have the greatest UHI effect and Rustaq has the negative UHI trend.Regarding the interpolation,the project used different interpolation methods to calculate the provisional climate normal for Oman,showing that different variogram fitting models must be used for different months for Kriging interpolation.The final results show that all the interpolation methods struggle to predict the air temperature during summertime due to a complex spatial contrast and distribution,except GWR which shows a well-predicted dataset by which it can be said that the GWR is the best performing method for the temperature over Oman.展开更多
The traditional anomaly （TA） reference frame and its corresponding anomaly for a given data span changes with the extension of data length. In this study, the modulated annual cycle （MAC）, instead of the widely us...The traditional anomaly （TA） reference frame and its corresponding anomaly for a given data span changes with the extension of data length. In this study, the modulated annual cycle （MAC）, instead of the widely used climatological mean annual cycle, is used as an alternative reference frame for computing climate anomalies to study the multi-timescale variability of surface air temperature （SAT） in China based on homogenized daily data from 1952 to 2004. The Ensemble Empirical Mode Decomposition （EEMD） method is used to separate daily SAT into a high frequency component, a MAC component, an interannual component, and a decadal-to-trend component. The results show that the EEMD method can reflect historical events reasonably well, indicating its adaptive and temporally local characteristics. It is shown that MAC is a temporally local reference frame and will not be altered over a particular time span by an exten-sion of data length, thereby making it easier for physical interpretation. In the MAC reference frame, the low frequency component is found more suitable for studying the interannual to longer timescale variability （ILV） than a 13-month window running mean, which does not exclude the annual cycle. It is also better than other traditional versions （annual or summer or winter mean） of ILV, which contains a portion of the annual cycle. The analysis reveals that the variability of the annual cycle could be as large as the magnitude of interannual variability. The possible physical causes of different timescale variability of SAT in China are further discussed.展开更多
The Chinese government adopted six ecological restoration programs to improve its natural environments. Although these programs have proven successful in improving local environments, some studies have questioned thei...The Chinese government adopted six ecological restoration programs to improve its natural environments. Although these programs have proven successful in improving local environments, some studies have questioned their performance when regions suffer from drought. Whether we should consider the effects of drought on vegetation change in assessments of the benefits of ecological restoration programs is unclear. Therefore, taking the Grain for Green Program(GGP) region as a study area, we estimated vegetation growth in the region from 2000–2010 to clarify the trends in vegetation and their driving forces. Results showed that: 1) vegetation growth increased in the GGP region during 2000–2010, with 59.4% of the area showing an increase in the Normalized Difference Vegetation Index(NDVI). This confirmed the benefits of the ecological restoration program. 2) Drought can affect the vegetation change trend, but human activity plays a significant role in altering vegetation growth, and the slight downward trend in the NDVI was not consistent with the severity of the drought. Positive human activity led to increased NDVI in 89.13% of areas. Of these, 22.52% suffered drought, but positive human activity offset the damage in part. 3) Results of this research suggest that appropriate human activity can maximize the benefits of ecological restoration programs and minimize the effects of extreme weather. We therefore recommend incorporating eco-risk assessment and scientific management mechanisms in the design and management of ecosystem restoration programs.展开更多
Twenty-six sequences of grades of dryness/wetness and a combined sequence of indexes of winter temperature since A.D. 1471 in China were adopted as our data. The fluctuations of variability of precipitation and mean t...Twenty-six sequences of grades of dryness/wetness and a combined sequence of indexes of winter temperature since A.D. 1471 in China were adopted as our data. The fluctuations of variability of precipitation and mean temperature are statistically significant from analyses. It has been found that in middle latitudes of eastern China the distribution of the relation between mean temperature and interannual variability of precipitation in historical time forms a rather complex regional pattern, and the correlation coefficients are not unique in signs. But the negative correlations are dominant either in extent or in magnitude. The authors provide evidence that Little Ice Age was a time of more frequent extremes and support the idea that the climatic instability is above normal in cool periods.展开更多
基金the framework of the Gio Mon Project,co-financed by“Fondazione Cassa di Risparmio di Torino”。
文摘Alps are an important geographical area of the European continent and,in this area,temperature increase is most evident.However,the 1991-2020 climate normal in the Alps has still not been thoroughly investigated.Aiming to fill this gap with a focus on high-elevation environments,minimum and maximum daily air temperature acquired by 23 automatic weather station were used.The results show that the mean annual values of minimum and maximum temperature for the 1991-2020 climate normal in the Alps are-2.4℃ and 4.4℃,respectively,with a warming rate of 0.5℃/10 years.The mean annual temperature comparison between 1961-1990 and 1971-2000,1961-1990 and 1981-2010,1961-1990 and 1991-2020 climate normal show an increase of 0.3℃,0.5℃ and 0.9℃,respectively.The results also confirm that seasonal and annual temperatures are rising through the whole Alpine arc,mainly in summer and autumn.This work highlights that annual minimum and maximum temperature do not seem to be affected by a positive elevation-dependent warming.Instead,a positive elevation-dependent warming in the maximum values of the annual minimum temperature was found.If anthropogenic emissions maintain the trend of the last decades,the expected mean annual temperature of the 2001-2030 climate normal is-0.2℃,with an increase of 0.5℃ if compared to the 1991-2020 climate normal and with an increase of 1.5℃ if compared to the 1961-1990 climate normal.This study highlights the warming rate that is now present in the European Alps,provides indications on the warming rate that will occur in the coming years and highlights the importance of carrying out investigations that consider not only the last 30-year climate normal,but also the most recent 30-year climate normal by comparing them with each other.
文摘Climate normal calculation over Oman is a key challenge due to scattered and inconsistent ground observations.Based on the available observations record to calculate the normal,the study derives the Provisional Climate Normal.The data from selected stations in this project have been tested and investigated by using the quality check and missing data evaluation.It is found that ERA-5 is the best reanalysis data in temperature as the correlation coefficient is higher compared to ERA-5 land and MERRA-2 which explains the reason for choosing ERA-5 data to calculate the regression model to fulfil the missing data.By using MODIS data,the Urban Heat Island Index(UHI)shows that Sohar and Muscat stations have the greatest UHI effect and Rustaq has the negative UHI trend.Regarding the interpolation,the project used different interpolation methods to calculate the provisional climate normal for Oman,showing that different variogram fitting models must be used for different months for Kriging interpolation.The final results show that all the interpolation methods struggle to predict the air temperature during summertime due to a complex spatial contrast and distribution,except GWR which shows a well-predicted dataset by which it can be said that the GWR is the best performing method for the temperature over Oman.
基金supported by Grant 2006CB400504 from the National Basic Research Program of ChinaGrant LCS-2006-03 fromthe Laboratory for Climate Studies, China MeteorologicalAdministration+1 种基金sponsored by the National Science Foundation of USA (ATM-0653136, ATM-0917743)sponsored by National Key Technologies R&D Pro-gram under Grant No. 2007BAC29B03
文摘The traditional anomaly （TA） reference frame and its corresponding anomaly for a given data span changes with the extension of data length. In this study, the modulated annual cycle （MAC）, instead of the widely used climatological mean annual cycle, is used as an alternative reference frame for computing climate anomalies to study the multi-timescale variability of surface air temperature （SAT） in China based on homogenized daily data from 1952 to 2004. The Ensemble Empirical Mode Decomposition （EEMD） method is used to separate daily SAT into a high frequency component, a MAC component, an interannual component, and a decadal-to-trend component. The results show that the EEMD method can reflect historical events reasonably well, indicating its adaptive and temporally local characteristics. It is shown that MAC is a temporally local reference frame and will not be altered over a particular time span by an exten-sion of data length, thereby making it easier for physical interpretation. In the MAC reference frame, the low frequency component is found more suitable for studying the interannual to longer timescale variability （ILV） than a 13-month window running mean, which does not exclude the annual cycle. It is also better than other traditional versions （annual or summer or winter mean） of ILV, which contains a portion of the annual cycle. The analysis reveals that the variability of the annual cycle could be as large as the magnitude of interannual variability. The possible physical causes of different timescale variability of SAT in China are further discussed.
基金Under the auspices of the National Key R&D Program of China(No.2017YFC0504701)Science and Technology Service Network Initiative Project of Chinese Academy of Sciences(No.KFJ-STS-ZDTP-036)+1 种基金Fundamental Research Funds for the Central Universities(No.GK201703053)China Postdoctoral Science Foundation(No.2017M623114)
文摘The Chinese government adopted six ecological restoration programs to improve its natural environments. Although these programs have proven successful in improving local environments, some studies have questioned their performance when regions suffer from drought. Whether we should consider the effects of drought on vegetation change in assessments of the benefits of ecological restoration programs is unclear. Therefore, taking the Grain for Green Program(GGP) region as a study area, we estimated vegetation growth in the region from 2000–2010 to clarify the trends in vegetation and their driving forces. Results showed that: 1) vegetation growth increased in the GGP region during 2000–2010, with 59.4% of the area showing an increase in the Normalized Difference Vegetation Index(NDVI). This confirmed the benefits of the ecological restoration program. 2) Drought can affect the vegetation change trend, but human activity plays a significant role in altering vegetation growth, and the slight downward trend in the NDVI was not consistent with the severity of the drought. Positive human activity led to increased NDVI in 89.13% of areas. Of these, 22.52% suffered drought, but positive human activity offset the damage in part. 3) Results of this research suggest that appropriate human activity can maximize the benefits of ecological restoration programs and minimize the effects of extreme weather. We therefore recommend incorporating eco-risk assessment and scientific management mechanisms in the design and management of ecosystem restoration programs.
文摘Twenty-six sequences of grades of dryness/wetness and a combined sequence of indexes of winter temperature since A.D. 1471 in China were adopted as our data. The fluctuations of variability of precipitation and mean temperature are statistically significant from analyses. It has been found that in middle latitudes of eastern China the distribution of the relation between mean temperature and interannual variability of precipitation in historical time forms a rather complex regional pattern, and the correlation coefficients are not unique in signs. But the negative correlations are dominant either in extent or in magnitude. The authors provide evidence that Little Ice Age was a time of more frequent extremes and support the idea that the climatic instability is above normal in cool periods.
