Dropsonde-Derived Moist Static Energy Variability in North Atlantic Tropical Cyclones
Tropical cyclones (TCs) are among the most impactful weather phenomena around the world. Each year, there are around 85 TCs that form around the globe, yet there is still a great deal to be understood about them (Emanuel, 2003). While idealized computer models can serve as a great “laboratory” to pr...
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ftfloridasu:oai:diginole.lib.fsu.edu:fsu_911278 2024-05-19T07:44:58+00:00 Dropsonde-Derived Moist Static Energy Variability in North Atlantic Tropical Cyclones Kopelman, Michael (author) 2024-04-23 computer online resource 1 online resource application/pdf https://diginole.lib.fsu.edu/islandora/object/fsu%3A911278/datastream/TN/view/Dropsonde-Derived%20Moist%20Static%20Energy%20Variability%20in%20North%20Atlantic%20Tropical%20Cyclones.jpg English eng fsu:911278 iid: honors_thesis_submission-4a70e14a-e30f-4c9a-9ddd-03734e15df00 https://diginole.lib.fsu.edu/islandora/object/fsu%3A911278/datastream/TN/view/Dropsonde-Derived%20Moist%20Static%20Energy%20Variability%20in%20North%20Atlantic%20Tropical%20Cyclones.jpg Creative Commons Attribution (CC BY 4.0) Text bachelor thesis 2024 ftfloridasu 2024-04-30T23:30:52Z Tropical cyclones (TCs) are among the most impactful weather phenomena around the world. Each year, there are around 85 TCs that form around the globe, yet there is still a great deal to be understood about them (Emanuel, 2003). While idealized computer models can serve as a great “laboratory” to probe physical properties of TCs that would be difficult to acquire in reality, observational data is vital to complement these models and add tangible data to study from the real environment. Our understanding of processes that control TC structure and intensity would greatly benefit from using observational data to validate results from modeling studies. Among these processes relevant to TC development are interactions between clouds, water vapor, radiation, and mesoscale circulations, such as cloud longwave radiative effects. Quantifying these feedbacks requires knowing how moist static energy (MSE) and its column-integral (CMSE) vary spatially around the TC. Dropsondes from aircraft reconnaissance can directly sample MSE, providing a useful observational tool to address this question. Though dropsondes are limited in number and spatial coverage around a given storm, recent modeling work suggests that they can faithfully resolve a TC’s radial MSE and CMSE variability when deployed strategically. Therefore, this study uses upper-level reconnaissance dropsonde data from North Atlantic TCs spanning 1996-2021 to evaluate the spatial variability of MSE and CMSE around TCs. MSE and CMSEdecrease with distance from the TC center. The spatial variability of MSE and CMSE is larger in Category 1 and 2 hurricanes compared to Tropical Storms. While differences in MSE spatial variability are insignificant between weakening and intensifying TCs, raw MSE is generally larger in intensifying TCs. As TCs approach and persist beyond their Lifetime Maximum Intensity (LMI), the variance of CMSE generally increases. Lastly, some dependence of the MSE structure on the wind field structure is observed, as characterized by a storm’s radius of ... Bachelor Thesis North Atlantic Florida State University: DigiNole Commons |
institution |
Open Polar |
collection |
Florida State University: DigiNole Commons |
op_collection_id |
ftfloridasu |
language |
English |
description |
Tropical cyclones (TCs) are among the most impactful weather phenomena around the world. Each year, there are around 85 TCs that form around the globe, yet there is still a great deal to be understood about them (Emanuel, 2003). While idealized computer models can serve as a great “laboratory” to probe physical properties of TCs that would be difficult to acquire in reality, observational data is vital to complement these models and add tangible data to study from the real environment. Our understanding of processes that control TC structure and intensity would greatly benefit from using observational data to validate results from modeling studies. Among these processes relevant to TC development are interactions between clouds, water vapor, radiation, and mesoscale circulations, such as cloud longwave radiative effects. Quantifying these feedbacks requires knowing how moist static energy (MSE) and its column-integral (CMSE) vary spatially around the TC. Dropsondes from aircraft reconnaissance can directly sample MSE, providing a useful observational tool to address this question. Though dropsondes are limited in number and spatial coverage around a given storm, recent modeling work suggests that they can faithfully resolve a TC’s radial MSE and CMSE variability when deployed strategically. Therefore, this study uses upper-level reconnaissance dropsonde data from North Atlantic TCs spanning 1996-2021 to evaluate the spatial variability of MSE and CMSE around TCs. MSE and CMSEdecrease with distance from the TC center. The spatial variability of MSE and CMSE is larger in Category 1 and 2 hurricanes compared to Tropical Storms. While differences in MSE spatial variability are insignificant between weakening and intensifying TCs, raw MSE is generally larger in intensifying TCs. As TCs approach and persist beyond their Lifetime Maximum Intensity (LMI), the variance of CMSE generally increases. Lastly, some dependence of the MSE structure on the wind field structure is observed, as characterized by a storm’s radius of ... |
author2 |
Kopelman, Michael (author) |
format |
Bachelor Thesis |
title |
Dropsonde-Derived Moist Static Energy Variability in North Atlantic Tropical Cyclones |
spellingShingle |
Dropsonde-Derived Moist Static Energy Variability in North Atlantic Tropical Cyclones |
title_short |
Dropsonde-Derived Moist Static Energy Variability in North Atlantic Tropical Cyclones |
title_full |
Dropsonde-Derived Moist Static Energy Variability in North Atlantic Tropical Cyclones |
title_fullStr |
Dropsonde-Derived Moist Static Energy Variability in North Atlantic Tropical Cyclones |
title_full_unstemmed |
Dropsonde-Derived Moist Static Energy Variability in North Atlantic Tropical Cyclones |
title_sort |
dropsonde-derived moist static energy variability in north atlantic tropical cyclones |
publishDate |
2024 |
url |
https://diginole.lib.fsu.edu/islandora/object/fsu%3A911278/datastream/TN/view/Dropsonde-Derived%20Moist%20Static%20Energy%20Variability%20in%20North%20Atlantic%20Tropical%20Cyclones.jpg |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
fsu:911278 iid: honors_thesis_submission-4a70e14a-e30f-4c9a-9ddd-03734e15df00 https://diginole.lib.fsu.edu/islandora/object/fsu%3A911278/datastream/TN/view/Dropsonde-Derived%20Moist%20Static%20Energy%20Variability%20in%20North%20Atlantic%20Tropical%20Cyclones.jpg |
op_rights |
Creative Commons Attribution (CC BY 4.0) |
_version_ |
1799484870600163328 |