dot
Detailansicht
Katalogkarte GBA
Katalogkarte ISBD
Suche präzisieren
Drucken
Download RIS
Hier klicken, um den Treffer aus der Auswahl zu entfernen
Titel Identifying convective transport of carbon monoxide by comparing remotely sensed observations from TES with cloud modeling simulations
VerfasserIn J. J. Halland, H. E. Fuelberg, K. E. Pickering, M. Luo
Medientyp Artikel
Sprache Englisch
ISSN 1680-7316
Digitales Dokument URL
Erschienen In: Atmospheric Chemistry and Physics ; 9, no. 13 ; Nr. 9, no. 13 (2009-07-03), S.4279-4294
Datensatznummer 250007484
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/acp-9-4279-2009.pdf
 
Zusammenfassung
Understanding the mechanisms that transport pollutants from the surface to the free atmosphere is important for determining the atmosphere's chemical composition. This study quantifies the vertical transport of tropospheric carbon monoxide (CO) by deep mesoscale convective systems and assesses the ability of the satellite-borne Tropospheric Emission Spectrometer (TES) to detect the resulting enhanced CO in the upper atmosphere. A squall line that is similar to one occurring during NASA's INTEX-B mission is simulated using a typical environmental wind shear profile and the 2-D Goddard Cumulus Ensemble model. The simulation provides post-convection CO profiles. The structure of the simulated squall line is examined, and its vertical transport of CO is quantified. Then, TES' ability to resolve the convectively modified CO distribution is documented using a "clear-sky" retrieval scheme. Results show that the simulated squall line transports the greatest mass of CO in the upper levels, with a value of 96 t upward and 67 t downward at 300 hPa. Results indicate that TES has sufficient sensitivity to resolve convectively lofted CO, as long as the retrieval scene is cloud-free. TES swaths located immediately downwind of squall lines have the greatest chance of sensing convective transport because the impact of clouds on retrieval quality becomes less. A note of caution is to always analyze TES-derived CO data (or data from any satellite sensor) together with the retrieval averaging kernels that describe the information content of the retrieval.
 
Teil von