Fluvial magnetic susceptibility as a proxy for long‐term variations of mountain permafrost development in the Alp‐Carpathian region

Boreas ◽  
2021 ◽  
Author(s):  
Zoltán Püspöki ◽  
Philip Leonard Gibbard ◽  
Annamária Nádor ◽  
Edit Thamó‐Bozsó ◽  
Pál Sümegi ◽  
...  
Keyword(s):  
Magnetic Susceptibility ◽  
Carpathian Region ◽  
Mountain Permafrost ◽  
Long Term Variations

Long-term variations of surface solar radiation in China from routine meteorological observations

2021 ◽  
pp. 105715
Author(s):  
Xuefang Yang ◽  
Wenmin Qin ◽  
Lunche Wang ◽  
Ming Zhang ◽  
Zigeng Niu
Keyword(s):  
Solar Radiation ◽  
Surface Solar Radiation ◽  
Meteorological Observations ◽  
Long Term Variations

Long-term variations of C1–C5 alkyl nitrates and their sources in Hong Kong

2021 ◽  
Vol 270 ◽  
pp. 116285
Author(s):  
Lewei Zeng ◽  
Hai Guo ◽  
Xiaopu Lyu ◽  
Beining Zhou ◽  
Zhenhao Ling ◽  
...  
Keyword(s):  
Hong Kong ◽  
Alkyl Nitrates ◽  
Long Term Variations

Application of singular spectrum analysis in reconstruction of the annual signal from GRACE

2020 ◽  
Vol 14 (3) ◽  
pp. 295-302
Author(s):  
Chuandong Zhu ◽  
Wei Zhan ◽  
Jinzhao Liu ◽  
Ming Chen
Keyword(s):  
Time Series ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Mixture Effect ◽  
Singular Spectrum ◽  
Grace Data ◽  
Terrestrial Water ◽  
Annual Signal ◽  
Long Term Variations

AbstractThe mixture effect of the long-term variations is a main challenge in single channel singular spectrum analysis (SSA) for the reconstruction of the annual signal from GRACE data. In this paper, a nonlinear long-term variations deduction method is used to improve the accuracy of annual signal reconstructed from GRACE data using SSA. Our method can identify and eliminate the nonlinear long-term variations of the equivalent water height time series recovered from GRACE. Therefore the mixture effect of the long-term variations can be avoided in the annual modes of SSA. For the global terrestrial water recovered from GRACE, the peak to peak value of the annual signal is between 1.4 cm and 126.9 cm, with an average of 11.7 cm. After the long-term and the annual term have been deducted, the standard deviation of residual time series is between 0.9 cm and 9.9 cm, with an average of 2.1 cm. Compared with the traditional least squares fitting method, our method can reflect the dynamic change of the annual signal in global terrestrial water, more accurately with an uncertainty of between 0.3 cm and 2.9 cm.

scholarly journals Long term variations measurement of electromagnetic field exposures in Alcalá de Henares (Spain)

2017 ◽  
Vol 598 ◽  
pp. 657-668 ◽  
Author(s):  
R. Sánchez-Montero ◽  
C. Alén-Cordero ◽  
P.L. López-Espí ◽  
J.M. Rigelsford ◽  
F. Aguilera-Benavente ◽  
...  
Keyword(s):  
Electromagnetic Field ◽  
Long Term Variations

Long-term variations in total solar irradiance

Solar Physics ◽  
1994 ◽  
Vol 152 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Judit M. Pap ◽  
Richard C. Willson ◽  
Claus Fr�hlich ◽  
Richard F. Donnelly ◽  
Larry Puga
Keyword(s):  
Solar Irradiance ◽  
Total Solar Irradiance ◽  
Long Term Variations

Long-term variations of TN and TP in four lakes fed by Yangtze River at various timescales

2015 ◽  
Vol 74 (5) ◽  
pp. 3993-4009 ◽  
Author(s):  
Jian Huang ◽  
Xixi Wang ◽  
Beidou Xi ◽  
Qiujin Xu ◽  
Yan Tang ◽  
...  
Keyword(s):  
Yangtze River ◽  
Long Term Variations
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