Although the SSA （singular spectral analysis） is a potential tool for analysing time series of different physical processes, the processing of large geophysical data set requires more time and is found to be computa...Although the SSA （singular spectral analysis） is a potential tool for analysing time series of different physical processes, the processing of large geophysical data set requires more time and is found to be computationally expansive. In particular for the SVD （singular value decomposition） of large trajectory matrix, the processing units require huge memory and high performance computing system. In the present work, we propose an alternative scheme based on WSSA （windowed singular spectral analysis）, which is robust for analysing long data sets without losing any valuable low-frequency information contained in the data. The underlying scheme reduces the floating point operations in SVD computations as the size of the trajectory matrix is small in windowed processing. In order to test the efficiency, the authors applied the proposed method on two geophysical data sets i.e., the climatic record with 30,000 data points and seismic reflection trace with 8,000 data points. The authors have shown that without distorting any physical information, the low-frequency contents of the data are well preserved after the windowed processing in both the cases.展开更多
Monitoring glacier mass balance is crucial to managing water resources and also to understanding climate change for the arid and semi-arid regions of Central Asia. This study extracted the inter-annual oscillations of...Monitoring glacier mass balance is crucial to managing water resources and also to understanding climate change for the arid and semi-arid regions of Central Asia. This study extracted the inter-annual oscillations of glacier mass over Central Asia from the first ten principal components（S-PCs） of filtered variability via multichannel singular spectral analysis（MSSA）, based on gridded data of glacier mass inferred from Gravity Recovery and Climate Experiment（GRACE） data obtained from July 2002 to March 2015. Two significant cycles of glacier mass balance oscillations were identified. The first cycle with a period of 6.1-year accounted for 54.5% of the total variance and the second with a period of 2.3-year accounted for 4.3%. The 6.1-year oscillation exhibited a stronger variability compared with the 2.3-year oscillation. For the 6.1-year oscillation, the results from lagged cross-correlation function suggested that there were significant correlations between glacier mass balances and precipitation variations with the precipitation variations leading the response of glacier mass balances by 9–16 months.展开更多
In the context of 1965- 2000 monthly rainfall data from 73 stations distributed over 3 province level districts and 2 metropolises (Beijing and Tianjin) of North China with some stations in the neighboring provinces,d...In the context of 1965- 2000 monthly rainfall data from 73 stations distributed over 3 province level districts and 2 metropolises (Beijing and Tianjin) of North China with some stations in the neighboring provinces,diagnostic study is undertaken of the features of spatially anomalous patterns and dominant periods of the annual precipitation in terms of EOF,REOF and SSA.Also, a scheme consisting of SSA combined with autoregression (AR) as a prediction model is employed to make forecasts of monthly rainfall sequences of the anomalous patterns in terms of an adaptive filter.Results show that the scheme,if further improved,would be of operational utility in preparing county-level prediction.展开更多
文摘Although the SSA （singular spectral analysis） is a potential tool for analysing time series of different physical processes, the processing of large geophysical data set requires more time and is found to be computationally expansive. In particular for the SVD （singular value decomposition） of large trajectory matrix, the processing units require huge memory and high performance computing system. In the present work, we propose an alternative scheme based on WSSA （windowed singular spectral analysis）, which is robust for analysing long data sets without losing any valuable low-frequency information contained in the data. The underlying scheme reduces the floating point operations in SVD computations as the size of the trajectory matrix is small in windowed processing. In order to test the efficiency, the authors applied the proposed method on two geophysical data sets i.e., the climatic record with 30,000 data points and seismic reflection trace with 8,000 data points. The authors have shown that without distorting any physical information, the low-frequency contents of the data are well preserved after the windowed processing in both the cases.
基金funded by the National Basic Research Program of China (2012CB957703, 2013CB733301)the National Natural Science Foundation of China (41274025, 41174064)
文摘Monitoring glacier mass balance is crucial to managing water resources and also to understanding climate change for the arid and semi-arid regions of Central Asia. This study extracted the inter-annual oscillations of glacier mass over Central Asia from the first ten principal components（S-PCs） of filtered variability via multichannel singular spectral analysis（MSSA）, based on gridded data of glacier mass inferred from Gravity Recovery and Climate Experiment（GRACE） data obtained from July 2002 to March 2015. Two significant cycles of glacier mass balance oscillations were identified. The first cycle with a period of 6.1-year accounted for 54.5% of the total variance and the second with a period of 2.3-year accounted for 4.3%. The 6.1-year oscillation exhibited a stronger variability compared with the 2.3-year oscillation. For the 6.1-year oscillation, the results from lagged cross-correlation function suggested that there were significant correlations between glacier mass balances and precipitation variations with the precipitation variations leading the response of glacier mass balances by 9–16 months.
文摘In the context of 1965- 2000 monthly rainfall data from 73 stations distributed over 3 province level districts and 2 metropolises (Beijing and Tianjin) of North China with some stations in the neighboring provinces,diagnostic study is undertaken of the features of spatially anomalous patterns and dominant periods of the annual precipitation in terms of EOF,REOF and SSA.Also, a scheme consisting of SSA combined with autoregression (AR) as a prediction model is employed to make forecasts of monthly rainfall sequences of the anomalous patterns in terms of an adaptive filter.Results show that the scheme,if further improved,would be of operational utility in preparing county-level prediction.
