|Title||Paleomagnetism and paleosecular variations from the Plio-Pleistocene Golan Heights volcanic plateau, Israel|
|Publication Type||Journal Article|
|Year of Publication||2019|
|Authors||Behar N., Shaar R, Tauxe L, Asefaw H., Ebert Y., Heimann A., Koppers A.AP, Ron H.G|
|Type of Article||Article|
|Keywords||Ar; Ar ages; averaged field; cretaceous normal superchron; Geochemistry & Geophysics; geomagnetic secular variation; golan heights; inclination anomaly; magnetic-field; palaeosecular variation; paleomagnetism; paleosecular variations; time|
Statistical analysis of geomagnetic paleosecular variation (PSV) and time-averaged field has been largely based on global compilations of paleomagnetic data from lava flows. These show different trends in the averaged inclination anomaly (Delta I) between the two hemispheres, with small positive (<2 degrees) anomalies in midsouthern latitudes and large negative (> -5 degrees) anomalies in midnorthern latitudes. To inspect the large Delta I between 20 degrees N and 40 degrees N we augment the global data with a new paleomagnetic data set from the Golan-Heights (GH), a Plio-Pleistocene volcanic plateau in northeast Israel, located at 32-33 degrees N. The GH data set consists of 91 lava flows sites: 40 sites obtained in the 1990s and 51 obtained in this study. The chronology of the flows is constrained by 57 Ar-40/Ar-39 ages: 39 from previous studies and 18 from this study, which together cover most of the GH plateau. We show that the 1990s data set might be affected by block rotations and does not fully sample PSV. The Plio-Pleistocene pole (86.3 degrees N, 120.8 degrees E, N = 44, k = 25, alpha(95) = 4.4 degrees), calculated after applying selection criteria with Fisher precision parameter (k) >= 100 and number of specimens per site (n) >= 5 is consistent with a geocentric axial dipole field and shows smaller inclination anomaly (Delta I = -0.4 degrees) than predicted by global compilations and PSV models. Reexamination of the inclination anomaly in the global compilation using different calculation methods and selection criteria suggests that inclination anomaly values are affected by (1) inclusion of poor quality data, (2) averaging data by latitude bins, and (3) the way the inclination anomaly is calculated.