dc.contributor.author | Luo, Jiesi | |
dc.contributor.author | Chan, Wei | |
dc.contributor.author | Ray, Jim | |
dc.contributor.author | Li, Jiancheng | |
dc.date.accessioned | 2023-06-12T22:56:13Z | |
dc.date.available | 2023-06-12T22:56:13Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Luo, J., Chen, W., Ray, J. and Li, J. (2022) Short-Term Polar Motion Forecast Based on the Holt-Winters Algorithm and Angular Momenta of Global Surficial Geophysical Fluids. Surveys in Geophysics, 43:09733, pp.1929-1945. DOI: https://doi.org/10.1007/s10712-022-09733-0 | en_US |
dc.identifier.uri | https://repository.oceanbestpractices.org/handle/11329/2285 | |
dc.description.abstract | By taking into account the variable free polar motion (PM) known as the Chandler wobble (CW) and irregular forced PM excited by quasi-periodic changes in atmosphere, oceans and land water (described by the data of effective angular momenta EAM), we propose a short-term PM forecast method based on the Holt-Winters (HW) additive algorithm (termed as the HW-VCW method, with VCW denoting variable CW). In this method, the variable CW period is determined by minimizing the differences between PM observations and EAM-derived PM for every 8-year sliding timespan. Compared to the X- and Y-pole forecast errors (Delta PMX and Delta PMY) of the International Earth Rotation and Reference Systems Service (IERS) Bulletin A, our results derived from operational EAM can reduce Delta PMX by up to 38.4% and Delta PMY by up to 34.3% for forecasts ranging from 1 to 30 days. Further, we prove that using EAM forecast instead of operational EAM in the HW-VCW method can achieve similar accuracies. | en_US |
dc.language.iso | en | en_US |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject.other | Holt-Winters algorithm | en_US |
dc.subject.other | Earth orientation | en_US |
dc.subject.other | Polar motion forecast | en_US |
dc.title | Short-Term Polar Motion Forecast Based on the Holt-Winters Algorithm and Angular Momenta of Global Surficial Geophysical Fluids. | en_US |
dc.type | Journal Contribution | en_US |
dc.description.refereed | Refereed | en_US |
dc.format.pagerange | pp.1929-1945 | en_US |
dc.identifier.doi | http://dx.doi.org/10.1007/s10712-022-09733-0 | |
dc.subject.parameterDiscipline | Field geophysics | en_US |
dc.subject.dmProcesses | Data analysis | en_US |
dc.subject.dmProcesses | Data aggregation | en_US |
dc.bibliographicCitation.title | Surveys in Geophysics | en_US |
dc.bibliographicCitation.volume | 43 | en_US |
dc.bibliographicCitation.issue | Article 09733 | en_US |
dc.description.sdg | 14.a | en_US |
dc.description.maturitylevel | Pilot or Demonstrated | en_US |
dc.description.adoption | Novel (no adoption outside originators) | en_US |
dc.description.methodologyType | Method | en_US |
obps.contact.contactname | Wei Chen | |
obps.contact.contactemail | wchen@sgg.whu.edu.cn | |
obps.resourceurl.publisher | https://link.springer.com/article/10.1007/s10712-022-09733-0 | |