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The recent state of the climate: Driving components of cloud-type variability
Earth Observation Research Center, JAXA, 2-1-1 Sengen, Tsukuba.
Earth Observation Research Center, JAXA, 2-1-1 Sengen, Tsukuba.
Earth Observation Research Center, JAXA, 2-1-1 Sengen, Tsukuba.
LuleƄ University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.ORCID iD: 0000-0001-7144-9778
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2011 (English)In: Journal of Geophysical Research, ISSN 0148-0227, E-ISSN 2156-2202, Vol. 116, no 11Article in journal (Refereed) Published
Abstract [en]

To reduce the Earth's radiation budget uncertainty related to cloud types' changes, and better understand the climate constraints resulting from long-term clouds' variability, frequent and finer (than actually existing) observations are necessary. This is one of the aims of future satellite programs such as the Global Change Observation Mission-Climate (GCOM-C) satellite, to be launched by the Japan Aerospace Exploration Agency (JAXA). To facilitate the transition from past to future observations, the actual state of climate variables (e.g., cloud types) needs to be evaluated. This evaluation is attempted in the present work with the analysis of long-term cloud types' distribution and amounts. The data set used for this study is 25 years (1982-2006) of global daytime cloud properties observed by the National Oceanic and Atmospheric Administration- Advanced Very-High-Resolution Radiometer (NOAA-AVHRR) satellites sensors. Though various calibrations have been applied on NOAA-AVHRR data, the effects of the orbit drift experienced by these satellites need to be corrected. A signal processing decomposition method allowing the filtering of the cloud types' amount trend affected by the orbit drift is used to perform the necessary corrections. The results obtained show a quantifiable improvement of the cloud amount estimation and trends of the individual NOAA satellites initial observations, at the global and regional scales. The corrected global cloud amount shows a slight decrease in its linear trend. The driving factors of this trend are the decrease in mid and low clouds overwhelming the increase in high clouds (+0.04% cloud amount/yr). A comparison with other cloud climatology studies such as the International Cloud Satellite Climatology Project (ISCCP) data set shows that the global cloud decrease noticed in NOAA-AVHRR's data is smaller. And, contrary to the NOAA-AVHRR's data, the driving force of the ISCCP linear trend is a sharp decrease in low clouds (-0.20% cloud amount/yr).

Place, publisher, year, edition, pages
2011. Vol. 116, no 11
National Category
Water Engineering
Research subject
Water Resources Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-10424DOI: 10.1029/2010JD014559ISI: 000291820900001Scopus ID: 2-s2.0-79958784184Local ID: 93aa88a6-8089-4836-a18c-404231dd17ceOAI: oai:DiVA.org:ltu-10424DiVA, id: diva2:983369
Note
Validerad; 2011; Bibliografisk uppgift: Article number D11117 ; 20110701 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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