{"id":{"repo_id":"embry-riddle","oai_identifier":"oai:commons.erau.edu:db-theses-1035"},"canonical_url":"https://search.dev.ndltd.org/etd/embry-riddle/oai:commons.erau.edu:db-theses-1035","repository":{"repo_id":"embry-riddle","name":"Embry Riddle Aeronautical University","base_url":"https://commons.erau.edu/do/oai/"},"display":{"title":"A Measure of the Hurst Exponent Variability on Ground Based Magnetometer Data for Quiet and Active Magnetospheric Periods","abstract":"<p>Ground-based magnetometer data were analyzed for the period of 1991-2001. The data were classified into periods of quiet and active magnetospheric activity. Those periods classified as quiet required that Kp < 1 for not less than 48 consecutive hours and active periods required a Kp > 4 for not less than 24 consecutive hours. Detrended fluctuation analysis was employed to analyze 40 events. A monofractal approach was used to identify differences in the Hurst exponent of quiet and active events. No statistical differences were found using this approach since both types of events displayed quasirandom walk behavior. A second approach determined the temporal variations in the Hurst exponent for each event. The Hurst exponent is temporally dynamic — active events are more correlated than quiet events - suggesting a multifractional rather than monofractal behavior. The results are useful to suggest an appropriate model of magnetic field fluctuations.</p>","abstract_html":"&lt;p&gt;Ground-based magnetometer data were analyzed for the period of 1991-2001. The data were classified into periods of quiet and active magnetospheric activity. Those periods classified as quiet required that Kp &lt; 1 for not less than 48 consecutive hours and active periods required a Kp &gt; 4 for not less than 24 consecutive hours. Detrended fluctuation analysis was employed to analyze 40 events. A monofractal approach was used to identify differences in the Hurst exponent of quiet and active events. No statistical differences were found using this approach since both types of events displayed quasirandom walk behavior. A second approach determined the temporal variations in the Hurst exponent for each event. The Hurst exponent is temporally dynamic — active events are more correlated than quiet events - suggesting a multifractional rather than monofractal behavior. The results are useful to suggest an appropriate model of magnetic field fluctuations.&lt;/p&gt;","abstract_has_math":false,"creators":["Cersosimo, Dario O."],"institution":null,"degree_name":"Master of Science in Space Science","degree_level":"Thesis - Open Access","degree_discipline":"Physical Sciences","degree_department":null,"school":null,"contributors":["James Wanliss","Mahmut Reyhanoglu","Hong Liu"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2005,"date_issued":"2005-04-01T08:00:00Z","date_published":"2005-04-01T08:00:00Z","updated_at":"2026-07-27T19:25:37Z","subjects":["Hurst exponent","variability","magnetometer","magnetosphere","Astrophysics and Astronomy","Atmospheric Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/db-theses/27","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["James Wanliss","Mahmut Reyhanoglu","Hong Liu"]},{"key":"dc:creator","label":"Author","values":["Cersosimo, Dario O."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Physical Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Space Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Hurst exponent","variability","magnetometer","magnetosphere","Astrophysics and Astronomy","Atmospheric Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/db-theses/27"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>Ground-based magnetometer data were analyzed for the period of 1991-2001. The data were classified into periods of quiet and active magnetospheric activity. Those periods classified as quiet required that Kp < 1 for not less than 48 consecutive hours and active periods required a Kp > 4 for not less than 24 consecutive hours. Detrended fluctuation analysis was employed to analyze 40 events. A monofractal approach was used to identify differences in the Hurst exponent of quiet and active events. No statistical differences were found using this approach since both types of events displayed quasirandom walk behavior. A second approach determined the temporal variations in the Hurst exponent for each event. The Hurst exponent is temporally dynamic — active events are more correlated than quiet events - suggesting a multifractional rather than monofractal behavior. The results are useful to suggest an appropriate model of magnetic field fluctuations.</p>"]},{"key":"dc:title","label":"Title","values":["A Measure of the Hurst Exponent Variability on Ground Based Magnetometer Data for Quiet and Active Magnetospheric Periods"]}]}],"canonical_facts":{"dc:contributor":["James Wanliss","Mahmut Reyhanoglu","Hong Liu"],"dc:creator":["Cersosimo, Dario O."],"dc:description.abstract":["<p>Ground-based magnetometer data were analyzed for the period of 1991-2001. The data were classified into periods of quiet and active magnetospheric activity. Those periods classified as quiet required that Kp < 1 for not less than 48 consecutive hours and active periods required a Kp > 4 for not less than 24 consecutive hours. Detrended fluctuation analysis was employed to analyze 40 events. A monofractal approach was used to identify differences in the Hurst exponent of quiet and active events. No statistical differences were found using this approach since both types of events displayed quasirandom walk behavior. A second approach determined the temporal variations in the Hurst exponent for each event. The Hurst exponent is temporally dynamic — active events are more correlated than quiet events - suggesting a multifractional rather than monofractal behavior. The results are useful to suggest an appropriate model of magnetic field fluctuations.</p>"],"dc:identifier":["https://commons.erau.edu/db-theses/27"],"dc:subject":["Hurst exponent","variability","magnetometer","magnetosphere","Astrophysics and Astronomy","Atmospheric Sciences"],"dc:title":["A Measure of the Hurst Exponent Variability on Ground Based Magnetometer Data for Quiet and Active Magnetospheric Periods"],"thesis:degree_discipline":["Physical Sciences"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Space Science"]},"updated_at":"2026-07-27T19:25:37Z"}