A possible interrelation between Earth rotation and climatic variability at decadal time-scale

Zotov, Leonid; Bizouard, Christian; Shum, C. K.

doi:10.1016/j.geog.2016.05.005

Cited by 33 publications

(21 citation statements)

References 21 publications

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“…However, Lambeck (1980) did not provided any explanation of the observation. A correlation between climate records and LOD has been recently discussed also in Zotov et al (2016). Here, we investigate a possible physical linkage.…”

Section: Introductionmentioning

confidence: 80%

The Little Ice Age was 1.0–1.5 °C cooler than current warm period according to LOD and NAO

Mazzarella

Scafetta

2018

Clim Dyn

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We study the yearly values of the length of day (LOD, 1623(LOD, -2016 and its link to the zonal index (ZI, 1873(ZI, -2003, the Northern Atlantic oscillation index (NAO, 1659(NAO, -2000 and the global sea surface temperature (SST, 1850(SST, -2016. LOD is herein assumed to be mostly the result of the overall circulations occurring within the ocean-atmospheric system. We find that LOD is negatively correlated with the global SST and with both the integral function of ZI and NAO, which are labeled as IZI and INAO. A first result is that LOD must be driven by a climatic change induced by an external (e.g. solar/astronomical) forcing since internal variability alone would have likely induced a positive correlation among the same variables because of the conservation of the Earth's angular momentum. A second result is that the high correlation among the variables implies that the LOD and INAO records can be adopted as global proxies to reconstruct past climate change. Tentative global SST reconstructions since the 17 th century suggest that around 1700, that is during the coolest period of the Little Ice Age (LIA), SST could have been about 1.0-1.5°C cooler than the 1950-1980 period. This estimated LIA cooling is greater than what some multiproxy global climate reconstructions suggested, but it is in good agreement with other more recent climate reconstructions including those based on borehole temperature data.

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Section: Introductionmentioning

confidence: 80%

The Little Ice Age was 1.0–1.5 °C cooler than current warm period according to LOD and NAO

Mazzarella

Scafetta

2018

Clim Dyn

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“…Although the two methods are mathematically equivalent, there is a difference in their application. MSSA aims to identify known or unknown periodic signals in the presence of noise [e.g., Ghil et al , ; Rangelova et al , , ; Zotov et al , , ]. To do this, MSSA incorporates a large number of lags M , which leads to increased repetition of signals of interest and improved statistical confidence in estimated signals [ Ghil et al , ].…”

Section: Methodsmentioning

confidence: 99%

Section: 1002/2017jb014379mentioning

confidence: 99%

Correlated error reduction in GRACE data over Greenland using extended empirical orthogonal functions

et al. 2017

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Surface mass change estimates from Gravity Recovery and Climate Experiment (GRACE) spherical harmonic solutions are contaminated by north‐south stripe noise due largely to aliasing of high‐frequency variations into monthly samples. These meridional stripes are especially troubling for ice mass balance studies of the Greenland Ice Sheet (GrIS) where large ice mass variations are known to occur along north‐south trending coastlines. By assuming that mass variations and noise have different patterns in both space and time over Greenland, we use extended empirical orthogonal functions (EEOFs) to filter out this noise. The method is compared with a conventional approach, by examining both continent‐wide estimates and regional changes. GRACE results are compared with independent regional estimates derived from a climate model. The EEOF filter is effective at separating ice mass change signals from meridional stripe noise, with better rejection of high temporal frequency noise and less signal attenuation and spatial smoothing compared to a conventional method. We use EEOF‐filtered GRACE data to examine regional seasonal variations. Consistent with surface and other data, results show ice mass loss along the west, southwest, and east coasts during summer and gain in these regions during winter. In addition, there is summer ice mass gain in the central region of the GrIS.

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“…However, when analyzing the GCM, these methods cannot take into account the correlation of GCM in all directions. Multi-channel singular spectrum analysis (MSSA), as the extended form of SSA, is one of the effective statistical data analysis methods in oceanography, geoscience, meteorology, and other fields [ 25 , 26 , 27 , 28 ]. The MSSA is a method for analyzing non-linear time series.…”

Section: Introductionmentioning

confidence: 99%

Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction

Jin

Liu

Guo

et al. 2021

Sensors

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Geocenter is the center of the mass of the Earth system including the solid Earth, ocean, and atmosphere. The time-varying characteristics of geocenter motion (GCM) reflect the redistribution of the Earth’s mass and the interaction between solid Earth and mass loading. Multi-channel singular spectrum analysis (MSSA) was introduced to analyze the GCM products determined from satellite laser ranging data released by the Center for Space Research through January 1993 to February 2017 for extracting the periods and the long-term trend of GCM. The results show that the GCM has obvious seasonal characteristics of the annual, semiannual, quasi-0.6-year, and quasi-1.5-year in the X, Y, and Z directions, the annual characteristics make great domination, and its amplitudes are 1.7, 2.8, and 4.4 mm, respectively. It also shows long-period terms of 6.09 years as well as the non-linear trends of 0.05, 0.04, and –0.10 mm/yr in the three directions, respectively. To obtain real-time GCM parameters, the MSSA method combining a linear model (LM) and autoregressive moving average model (ARMA) was applied to predict GCM for 2 years into the future. The precision of predictions made using the proposed model was evaluated by the root mean squared error (RMSE). The results show that the proposed method can effectively predict GCM parameters, and the prediction precision in the three directions is 1.53, 1.08, and 3.46 mm, respectively.

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A possible interrelation between Earth rotation and climatic variability at decadal time-scale

Cited by 33 publications

References 21 publications

The Little Ice Age was 1.0–1.5 °C cooler than current warm period according to LOD and NAO

The Little Ice Age was 1.0–1.5 °C cooler than current warm period according to LOD and NAO

Correlated error reduction in GRACE data over Greenland using extended empirical orthogonal functions

Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction

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