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Abstract. The use of branched glycerol dialkyl glycerol tetraethers (bGDGTs) in loess–palaeosol sequences (LPSs) has shown promises in continental palaeotemperature reconstructions. Thus far, however, little is known about the effect of soil moisture on their distributions in the water-limited Chinese Loess Plateau (CLP). In this study, the relationships between environmental variables and the cyclization of branched tetraethers (CBT) were investigated in arid–subhumid China using 97 surface soils in the CLP and its vicinity, as well as 78 soils with pH > 7 which have been previously published. We find that CBT correlates best with soil water content (SWC) or mean annual precipitation (MAP) for the overall data set. This indicates that CBT is mainly controlled by soil moisture instead of soil pH in alkaline soils from arid–subhumid regions, where water availability is a limiting factor for the producers of bGDGTs. Therefore, we suggest that CBT can potentially be used as a palaeorainfall proxy on the alkaline CLP. According to the preliminary CBT–MAP relationship for modern CLP soils (CBT = −0.0021 × MAP + 1.7, n = 37, r = −0.93), palaeorainfall history was reconstructed from three LPSs (Yuanbao, Lantian, and Mangshan) with published bGDGT data spanning the past 70 ka. The CBT-derived MAP records of the three sites consistently show precession-driven variation resembling the monsoon record based on speleothem δ18O, supporting CBT as a reasonable proxy for palaeorainfall reconstruction in LPS. The direct application of CBT as a palaeorainfall proxy in corroboration with the bGDGT-based temperature proxy may enable us to further assess the temperature/hydrological association for palaeoclimate studies on the CLP.

A new methodology for the calculation of critical eigenvalues in the small signal stability analysis of large power systems is presented in this paper. The Jacobi-Davidson method, which is a very recent subspace iteration method, is suggested to compute the rightmost eigenvalues. The method is attractive as a new powerful technique for solving a variety of large sparse eigenproblems. The method combined Davidson's idea of taking a different subspace with Jacobi's idea of restricting the search of an update to the subspace orthogonal to current eigenvector approximation. An exact solution of the correction equation leads to quadratic convergence for the selected Ritz values. Based on the iterative construction of a partial Schur form and the effective restart, the algorithms are suitable for the efficient computation of a large number of eigenvalues and clustering eigenvalues. The proposed method is applied to a practical 46-machine system, and the results of the experiment are described.Index Terms-Jacobi-Davidson (JD) method, large power systems, rightmost eigenvalues, small signal stability.

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