Annual freezing and thawing index of 7 meteorological stations along the Qing- hai-Xizang Railway were calculated based on daily maximum and minimum temperature records for 1966-2004. Trends of annual freezing and tha...Annual freezing and thawing index of 7 meteorological stations along the Qing- hai-Xizang Railway were calculated based on daily maximum and minimum temperature records for 1966-2004. Trends of annual freezing and thawing index were analyzed using the Mann-Kendall test and a simple linear regression method. The results show that： 1） The mean annual freezing indices range from 95 to 2300℃·d and the mean annual thawing indices range from 630 to 3250℃·d. The mean annual freezing index of the 7 stations exhibited decreasing trends with decreasing rate of -16.6- -59.1 ℃·d/10a. The mean annual thawing index of these 7 stations showed increasing trends with the related decreasing rate is 19.83-45.6℃·d/10a. 2） The MK trend test indicated the significant decreasing trends （significant at 〈 0.05 significant level） in the annual freezing index for most stations except for Golmud. The significant increasing trends can be observed in the annual thawing index for 4 stations except Golmud and Tuotuohe. Golmud was the only station with no trends in both annual freezing and annual thawing index.展开更多
Utilizing the 45 a European Centre for Medium-Range Weather Forecasts （ECMWF） reanalysis wave da- ta （ERA-40）, the long-term trend of the sea surface wind speed and （wind wave, swell, mixed wave） wave height in ...Utilizing the 45 a European Centre for Medium-Range Weather Forecasts （ECMWF） reanalysis wave da- ta （ERA-40）, the long-term trend of the sea surface wind speed and （wind wave, swell, mixed wave） wave height in the global ocean at grid point 1.5°× 1.5° during the last 44 a is analyzed. It is discovered that a ma- jority of global ocean swell wave height exhibits a significant linear increasing trend （2-8 cm/decade）, the distribution of annual linear trend of the significant wave height （SWH） has good consistency with that of the swell wave height. The sea surface wind speed shows an annually linear increasing trend mainly con- centrated in the most waters of Southern Hemisphere westerlies, high latitude of the North Pacific, Indian Ocean north of 30°S, the waters near the western equatorial Pacific and low latitudes of the Atlantic waters, and the annually linear decreasing mainly in central and eastern equator of the Pacific, Juan. Fernandez Archipelago, the waters near South Georgia Island in the Atlantic waters. The linear variational distribution characteristic of the wind wave height is similar to that of the sea surface wind speed. Another find is that the swell is dominant in the mixed wave, the swell index in the central ocean is generally greater than that in the offshore, and the swell index in the eastern ocean coast is greater than that in the western ocean inshore, and in year-round hemisphere westerlies the swell index is relatively low.展开更多
Vegetation indices(VIs) from satellite remote sensing have been extensively applied to analyze the trends of vegetation phenology. In this paper, the NDVI(normalized difference vegetation index) and SR(simple ration),...Vegetation indices(VIs) from satellite remote sensing have been extensively applied to analyze the trends of vegetation phenology. In this paper, the NDVI(normalized difference vegetation index) and SR(simple ration), which are calculated from the same spectral bands of MODIS data with different mathematical expressions, were used to extract the start date(SOS) and end date(EOS) of the growing season in northern China and Mongolia from 2000 to 2015. The results show that different vegetation indices would lead to differences in vegetation phenology especially in their trends. The mean SOS from NDVI is 15.5 d earlier than that from SR, and the mean EOS from NDVI is 13.4 d later than that from SR. It should be noted that 16.3% of SOS and 17.2% of EOS derived from NDVI and SR exhibit opposite trends. The phenology dates and trends from NDVI are also inconsistent with those of SR among various vegetation types. These differences based on different mathematical expressions in NDVI and SR result from different resistances to noise and sensitivities to spectral signal at different stage of growing season. NDVI is prone to be effected more by low noise and is less sensitive to dense vegetation. While SR is affected more by high noise and is less sensitive to sparse vegetation. Therefore, vegetation indices are one of the uncertainty sources of remote sensing-based phenology, and appropriate indices should be used to detect vegetation phenology for different growth stages and estimate phenology trends.展开更多
With the background of China's fast growing economy, Internet has become a key factor to keep the economy go steadily. It is important to quantitatively analyze the whole Internet industry and hence master its dev...With the background of China's fast growing economy, Internet has become a key factor to keep the economy go steadily. It is important to quantitatively analyze the whole Internet industry and hence master its development direction clearly, which will provide regulators with reference for industry analysis, policy formulation, and policy evaluation. This article re-constructs the calculation method of traditional Prosperity Indexes, and builds up a new indicators portfolio for Internet Industry Prosperity Indexes. By calculation, the Internet Industry Coincidence Index value is 105.9. And the Leading Index and Coincidence Index are all within the up-going range, which suggests that China's Internet Industry is likely to remain in its usual fast growing state.展开更多
Predicting tourism traffic demand accurately plays an important role in making effective policies for tourist administration. It helps to distribute the resources reasonably and avoid the tourism congestions. This pap...Predicting tourism traffic demand accurately plays an important role in making effective policies for tourist administration. It helps to distribute the resources reasonably and avoid the tourism congestions. This paper considered the noise interference and proposed a hybrid model, combining ensemble empirical mode decomposition (EEMD), deep belief network (DBN) and Google trends, for tourism traffic demand prediction. This model firstly applied dislocation weighted synthesis method to combine Google trends into a search composite index, and then it denoised the series with EEMD. EEMD extracted the high frequency noise from the original series. The low frequency series of search composite index would be used to forecast the low frequency tourism traffic series. Taking the inbound tourism in Shanghai as an example, this paper trained the model and predicted the next 12 months tourism arrivals. The conclusion demonstrated that the forecast error of EEMD-DBN model is lower remarkably than the baselines of ARIMA, GM(1,1), FTS, SVM, CES and DBN model. This revealed that nosing processing is necessary and EEMD-DBN forecast model can improve the prediction accuracy.展开更多
Industrialization and urbanization are the most dominant causal factors for long-term changes in surface air temperatures. To examine this fact, the long term changes in the surface-air temperatures have been evaluate...Industrialization and urbanization are the most dominant causal factors for long-term changes in surface air temperatures. To examine this fact, the long term changes in the surface-air temperatures have been evaluated by the linear trend for the different periods, i.e. 1901-2013, 1901-1970 and recent period 1971-2013 as rapid industrialization was observed during the recent four decades. In the present study, seasonal and annual mean, maximum and minimum temperature data of 36 stations for the period 1901-2013 have been used. These stations are classified into 4 groups, namely major, medium, small cities and hill stations. During the period 1901-1970, less than 50% stations from each group showed a significant increasing trend in annual mean temperature, whereas in the recent period 1971-2013, more than 80% stations from all the groups except small city group showed a significant increasing trend. The minimum temperature increased faster than that of the maximum temperature over major and medium cities, while maximum temperature increased faster than the minimum temperature over the small cities and hill stations. The annual mean temperature of all the coastal stations showed a significant increasing trend and positive correlation with Precipitable Water Vapour (PWV). The effect of PWV is more pronounced on minimum temperature than that of the maximum.展开更多
基金Knowledge Innovation Program of Xinjiang Institute of Ecology and Geography, CAS, No.0571041
文摘Annual freezing and thawing index of 7 meteorological stations along the Qing- hai-Xizang Railway were calculated based on daily maximum and minimum temperature records for 1966-2004. Trends of annual freezing and thawing index were analyzed using the Mann-Kendall test and a simple linear regression method. The results show that： 1） The mean annual freezing indices range from 95 to 2300℃·d and the mean annual thawing indices range from 630 to 3250℃·d. The mean annual freezing index of the 7 stations exhibited decreasing trends with decreasing rate of -16.6- -59.1 ℃·d/10a. The mean annual thawing index of these 7 stations showed increasing trends with the related decreasing rate is 19.83-45.6℃·d/10a. 2） The MK trend test indicated the significant decreasing trends （significant at 〈 0.05 significant level） in the annual freezing index for most stations except for Golmud. The significant increasing trends can be observed in the annual thawing index for 4 stations except Golmud and Tuotuohe. Golmud was the only station with no trends in both annual freezing and annual thawing index.
基金The National Basic Research Program of China under contract No.2012CB957803
文摘Utilizing the 45 a European Centre for Medium-Range Weather Forecasts （ECMWF） reanalysis wave da- ta （ERA-40）, the long-term trend of the sea surface wind speed and （wind wave, swell, mixed wave） wave height in the global ocean at grid point 1.5°× 1.5° during the last 44 a is analyzed. It is discovered that a ma- jority of global ocean swell wave height exhibits a significant linear increasing trend （2-8 cm/decade）, the distribution of annual linear trend of the significant wave height （SWH） has good consistency with that of the swell wave height. The sea surface wind speed shows an annually linear increasing trend mainly con- centrated in the most waters of Southern Hemisphere westerlies, high latitude of the North Pacific, Indian Ocean north of 30°S, the waters near the western equatorial Pacific and low latitudes of the Atlantic waters, and the annually linear decreasing mainly in central and eastern equator of the Pacific, Juan. Fernandez Archipelago, the waters near South Georgia Island in the Atlantic waters. The linear variational distribution characteristic of the wind wave height is similar to that of the sea surface wind speed. Another find is that the swell is dominant in the mixed wave, the swell index in the central ocean is generally greater than that in the offshore, and the swell index in the eastern ocean coast is greater than that in the western ocean inshore, and in year-round hemisphere westerlies the swell index is relatively low.
基金Under the auspices of the Strategic Priority Research Program of the Chinese Academy Sciences(No.XDA19080303)the National Key Research and Development Program for Global Change and Adaptation(No.2016YFA0600201)+1 种基金the Distinctive Institutes Development Program,Chinese Academy of Sciences(No.TSYJS04)the National Natural Sciences Foudation of China(No.41171285)
文摘Vegetation indices(VIs) from satellite remote sensing have been extensively applied to analyze the trends of vegetation phenology. In this paper, the NDVI(normalized difference vegetation index) and SR(simple ration), which are calculated from the same spectral bands of MODIS data with different mathematical expressions, were used to extract the start date(SOS) and end date(EOS) of the growing season in northern China and Mongolia from 2000 to 2015. The results show that different vegetation indices would lead to differences in vegetation phenology especially in their trends. The mean SOS from NDVI is 15.5 d earlier than that from SR, and the mean EOS from NDVI is 13.4 d later than that from SR. It should be noted that 16.3% of SOS and 17.2% of EOS derived from NDVI and SR exhibit opposite trends. The phenology dates and trends from NDVI are also inconsistent with those of SR among various vegetation types. These differences based on different mathematical expressions in NDVI and SR result from different resistances to noise and sensitivities to spectral signal at different stage of growing season. NDVI is prone to be effected more by low noise and is less sensitive to dense vegetation. While SR is affected more by high noise and is less sensitive to sparse vegetation. Therefore, vegetation indices are one of the uncertainty sources of remote sensing-based phenology, and appropriate indices should be used to detect vegetation phenology for different growth stages and estimate phenology trends.
文摘With the background of China's fast growing economy, Internet has become a key factor to keep the economy go steadily. It is important to quantitatively analyze the whole Internet industry and hence master its development direction clearly, which will provide regulators with reference for industry analysis, policy formulation, and policy evaluation. This article re-constructs the calculation method of traditional Prosperity Indexes, and builds up a new indicators portfolio for Internet Industry Prosperity Indexes. By calculation, the Internet Industry Coincidence Index value is 105.9. And the Leading Index and Coincidence Index are all within the up-going range, which suggests that China's Internet Industry is likely to remain in its usual fast growing state.
文摘Predicting tourism traffic demand accurately plays an important role in making effective policies for tourist administration. It helps to distribute the resources reasonably and avoid the tourism congestions. This paper considered the noise interference and proposed a hybrid model, combining ensemble empirical mode decomposition (EEMD), deep belief network (DBN) and Google trends, for tourism traffic demand prediction. This model firstly applied dislocation weighted synthesis method to combine Google trends into a search composite index, and then it denoised the series with EEMD. EEMD extracted the high frequency noise from the original series. The low frequency series of search composite index would be used to forecast the low frequency tourism traffic series. Taking the inbound tourism in Shanghai as an example, this paper trained the model and predicted the next 12 months tourism arrivals. The conclusion demonstrated that the forecast error of EEMD-DBN model is lower remarkably than the baselines of ARIMA, GM(1,1), FTS, SVM, CES and DBN model. This revealed that nosing processing is necessary and EEMD-DBN forecast model can improve the prediction accuracy.
文摘Industrialization and urbanization are the most dominant causal factors for long-term changes in surface air temperatures. To examine this fact, the long term changes in the surface-air temperatures have been evaluated by the linear trend for the different periods, i.e. 1901-2013, 1901-1970 and recent period 1971-2013 as rapid industrialization was observed during the recent four decades. In the present study, seasonal and annual mean, maximum and minimum temperature data of 36 stations for the period 1901-2013 have been used. These stations are classified into 4 groups, namely major, medium, small cities and hill stations. During the period 1901-1970, less than 50% stations from each group showed a significant increasing trend in annual mean temperature, whereas in the recent period 1971-2013, more than 80% stations from all the groups except small city group showed a significant increasing trend. The minimum temperature increased faster than that of the maximum temperature over major and medium cities, while maximum temperature increased faster than the minimum temperature over the small cities and hill stations. The annual mean temperature of all the coastal stations showed a significant increasing trend and positive correlation with Precipitable Water Vapour (PWV). The effect of PWV is more pronounced on minimum temperature than that of the maximum.
