Atmospheric excitation of polar motion

Date

1996

Authors

Kuehne, John William, 1960-

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Analysis of nonseasonal polar motion excitation and atmospheric mass equatorial angular momentum (EAM) over land for the period 1980-1993 reveals a clear pattern of high power and correlation during the northern hemisphere (NH) winter followed by low power and correlation during the NH summer. During the southern hemisphere winter there is significant correlation between the atmospheric EAM over midlatitude southern oceans and polar motion excitation indicating the existence of a dynamic atmosphere-ocean excitation. The atmospheric excitation power is too small to explain the large correlation during the NH winter. The momentum of wind probably accounts for the deficit in power. The implication of these results is that there are two main excitation sources each dominant at different seasons. Atmospheric mass redistribution over land forces polar motion during the NH winter, and a dynamic atmosphere-ocean response is important during the SH winter. The Chandler wobble frequency F and quality factor Q are estimated by least squares using polar motion data in combination with proxy excitations derived from atmospheric data. Monte Carlo tests show that this approach can provide useful improvements over traditional maximum likelihood methods, which use only observed polar motion. With less than a decade of good simultaneous polar motion and atmospheric data there is no new information about Q, but 90% confidence intervals for F are near ±0.004 cycles per year (cpy), making them comparable to maximum likelihood results based on nearly a century of historical polar motion data. Using a proxy excitation constructed from a linear combination of atmospheric EAM over land and SH ocean, the estimate of F is near 0.831 cpy (a period of 439.5 days), which is significantly different from the maximum likelihood value near 0.843 cpy (433 days). This difference can be understood in light of the assumptions underlying the two methods.

Description

Keywords

Citation