Title
Parameterization of oceanic whitecap fraction based on satellite observations
Author
Albert, M.F.M.A.
Anguelova, M.D.
Manders, A.M.M.
Schaap, M.
de Leeuw, G.
Publication year
2017
Abstract
Satellite-based whitecap fraction (W) data have been used to predict sea spray aerosol (SSA) emission rates. This allows to evaluate how an account for natural variability of whitecaps in the W parameterization would affect SSA mass flux predictions when using a sea spray source function (SSSF) based on the whitecap method. Data set containing W data for 2006 together with matching wind speed U10 and sea surface temperature (SST) T has been used. Whitecap fraction W was estimated from observations of the ocean surface brightness temperature TB by satellite-borne radiometers at two frequencies (10 and 37 GHz). A global scale assessment of the data set yielded approximately quadratic correlation between W and U10. A regional scale analysis yielded a new W(U10, T) parameterization which explicitly accounted for the effect of SST on W. The analysis of W values obtained with the new W(U10) and W(U10, T) parameterizations indicates that the influence of secondary factors on W is for the largest part embedded in the exponent of the wind speed dependence. In addition, the W(U10, T) parameterization is capable to model the spread (or variability) of the satellite-based W data. The satellite-based parameterization W(U10, T) was applied in an SSSF to estimate the global SSA emission rate. The thus obtained SSA production rate is within previously reported estimates, however with distinctly different spatial distribution. © 2017 IEEE. IEEE Geoscience and Remote Sensing Society (GRSS)
Subject
2015 Urban Mobility & Environment
CAS - Climate, Air and Sustainability
ELSS - Earth, Life and Social Sciences
Environment & Sustainability
Environment
Urbanisation
Breaking waves
Brightness temperature
Passive remote sensing
Sea spray
Whitecap fraction
To reference this document use:
http://resolver.tudelft.nl/uuid:f4e17590-0437-41bb-80da-08867f20ec99
DOI
https://doi.org/10.1109/igarss.2017.8127056
TNO identifier
787746
Publisher
Institute of Electrical and Electronics Engineers Inc.
ISBN
9781509049516
Source
37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017. 23 July 2017 through 28 July 2017, 732-734
Article number
8127056
Document type
conference paper