Deep convective systems play a crucial role in Earth's climate system, yet tracking their behavior over large spatial and temporal scales remains challenging. This study introduces a new global convection tracking database spanning July 1983 to June 2017, developed using the ISCCP H-Series Pixel-Level Gridded (HXG) dataset and the object-based TOBAC (Tracking and Object-Based Analysis of Clouds) framework. By applying multi-threshold feature detection, segmentation, and linking algorithms to infrared brightness temperature fields, convective systems are systematically identified and tracked through their life cycles. The resulting database provides a rich set of structural, dynamical, and radiative properties for over 67 million convective systems. Statistical analyses reveal key life cycle trends, such as radius expansion and minimum brightness temperature cooling during the mature stage, consistent with past observational studies. Geographical and seasonal variations highlight the dominance of long-lived, intense convection in the tropics and broader system sizes in the midlatitudes. A comparative analysis with higher-resolution datasets (MERGIR and Himawari-8) emphasizes the strong sensitivity of convective system statistics to spatial and temporal resolution. This work provides a valuable resource for investigating convective climatology and offers a foundation for future studies on deep convection.
","abstract_html":"<p>Deep convective systems play a crucial role in Earth's climate system, yet tracking their behavior over large spatial and temporal scales remains challenging. This study introduces a new global convection tracking database spanning July 1983 to June 2017, developed using the ISCCP H-Series Pixel-Level Gridded (HXG) dataset and the object-based TOBAC (Tracking and Object-Based Analysis of Clouds) framework. By applying multi-threshold feature detection, segmentation, and linking algorithms to infrared brightness temperature fields, convective systems are systematically identified and tracked through their life cycles. The resulting database provides a rich set of structural, dynamical, and radiative properties for over 67 million convective systems. Statistical analyses reveal key life cycle trends, such as radius expansion and minimum brightness temperature cooling during the mature stage, consistent with past observational studies. Geographical and seasonal variations highlight the dominance of long-lived, intense convection in the tropics and broader system sizes in the midlatitudes. A comparative analysis with higher-resolution datasets (MERGIR and Himawari-8) emphasizes the strong sensitivity of convective system statistics to spatial and temporal resolution. This work provides a valuable resource for investigating convective climatology and offers a foundation for future studies on deep convection.</p>","abstract_has_math":false,"creators":["Selevich, Yuliya"],"institution":null,"degree_name":"Master of Science (M.S.)","degree_level":"Thesis","degree_discipline":"Earth and Atmospheric Sciences","degree_department":null,"school":null,"contributors":["Zhengzhao Johnny Luo","James Booth","Spencer Hill"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-01-01T08:00:00Z","date_published":"2025-01-01T08:00:00Z","updated_at":"2026-07-24T01:58:07Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://academicworks.cuny.edu/cc_etds_theses/1198","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhengzhao Johnny Luo","James Booth","Spencer Hill"]},{"key":"dc:creator","label":"Author","values":["Selevich, Yuliya"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2025-06-03T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Earth and Atmospheric Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (M.S.)"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://academicworks.cuny.edu/cc_etds_theses/1198"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Deep convective systems play a crucial role in Earth's climate system, yet tracking their behavior over large spatial and temporal scales remains challenging. This study introduces a new global convection tracking database spanning July 1983 to June 2017, developed using the ISCCP H-Series Pixel-Level Gridded (HXG) dataset and the object-based TOBAC (Tracking and Object-Based Analysis of Clouds) framework. By applying multi-threshold feature detection, segmentation, and linking algorithms to infrared brightness temperature fields, convective systems are systematically identified and tracked through their life cycles. The resulting database provides a rich set of structural, dynamical, and radiative properties for over 67 million convective systems. Statistical analyses reveal key life cycle trends, such as radius expansion and minimum brightness temperature cooling during the mature stage, consistent with past observational studies. Geographical and seasonal variations highlight the dominance of long-lived, intense convection in the tropics and broader system sizes in the midlatitudes. A comparative analysis with higher-resolution datasets (MERGIR and Himawari-8) emphasizes the strong sensitivity of convective system statistics to spatial and temporal resolution. This work provides a valuable resource for investigating convective climatology and offers a foundation for future studies on deep convection.
"]},{"key":"dc:title","label":"Title","values":["Developing A Global, Multi-decadal (1983-2017) Convection Tracking Database Utilizing ISCCP HXG Data"]}]}],"canonical_facts":{"dc:contributor":["Zhengzhao Johnny Luo","James Booth","Spencer Hill"],"dc:creator":["Selevich, Yuliya"],"dc:date.available":["2025-06-03T07:00:00Z"],"dc:description.abstract":["Deep convective systems play a crucial role in Earth's climate system, yet tracking their behavior over large spatial and temporal scales remains challenging. This study introduces a new global convection tracking database spanning July 1983 to June 2017, developed using the ISCCP H-Series Pixel-Level Gridded (HXG) dataset and the object-based TOBAC (Tracking and Object-Based Analysis of Clouds) framework. By applying multi-threshold feature detection, segmentation, and linking algorithms to infrared brightness temperature fields, convective systems are systematically identified and tracked through their life cycles. The resulting database provides a rich set of structural, dynamical, and radiative properties for over 67 million convective systems. Statistical analyses reveal key life cycle trends, such as radius expansion and minimum brightness temperature cooling during the mature stage, consistent with past observational studies. Geographical and seasonal variations highlight the dominance of long-lived, intense convection in the tropics and broader system sizes in the midlatitudes. A comparative analysis with higher-resolution datasets (MERGIR and Himawari-8) emphasizes the strong sensitivity of convective system statistics to spatial and temporal resolution. This work provides a valuable resource for investigating convective climatology and offers a foundation for future studies on deep convection.
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