A new algorithm for sea-surface wind-speed retrieval based on the L-band radiometer onboard Aquarius -- Journal of Oceanology and Limnology,2015,33(5):1115-1123

	Cite this paper:
	WANG Jin, ZHANG Jie, FAN Chenqing, WANG Jing. A new algorithm for sea-surface wind-speed retrieval based on the L-band radiometer onboard Aquarius[J]. Journal of Oceanology and Limnology, 2015, 33(5): 1115-1123

A new algorithm for sea-surface wind-speed retrieval based on the L-band radiometer onboard Aquarius

WANG Jin^1,3, ZHANG Jie², FAN Chenqing², WANG Jing¹

1 College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China;
2 First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;
3 College of Physics, Qingdao University, Qingdao 266071, China

Abstract:

Aquarius is the second satellite mission to focus on the remote sensing of sea-surface salinity from space and it has mapped global sea-surface salinity for nearly 3 years since its launch in 2011.However, benefiting from the high atmospheric transparency and moderate sensitivity to wind speed of the L-band brightness temperature (TB), the Aquarius L-band radiometer can actually provide a new technique for the remote sensing of wind speed.In this article, the sea-surface wind speeds derived from TBs measured by Aquarius' L-band radiometer are presented, the algorithm for which is developed and validated using multisource wind speed data, including WindSat microwave radiometer and National Data Buoy Center buoy data, and the Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory wind field product.The error analysis indicates that the performance of retrieval algorithm is good.The RMSE of the Aquarius wind-speed algorithm is about 1 and 1.5 m/s for global oceans and areas of tropical hurricanes, respectively.Consequently, the applicability of using the Aquarius L-band radiometer as a near all-weather wind-speed measuring method is verified.

Key words: microwave radiometer|Aquarius|wind speed|L-band

Received: 2014-05-09 Revised: 2014-06-23

Tools

PDF ( KB) Free

Print this page

Add to favorites

Email this article to others

Authors

Articles by WANG Jin

Articles by ZHANG Jie

Articles by FAN Chenqing

Articles by WANG Jing

References:
Amarin R A, Jones W L, El-Nimri S F et al.2012.Hurricane wind speed measurements in rainy conditions using the airborne hurricane imaging radiometer (HIRAD).IEEE Trans.Geosci.Remote Sens., 50 (1): 180-192.
Blume H J C, Kendall B M, Fedors J C.1978.Measurement of ocean temperature and salinity via microwave radiometry.Boundary-Layer Meteorology, 13 (1): 295-308.
Boutin J, Martin N, Reverdin G et al.2013.Sea surface freshening inferred from SMOS and ARGO salinity: impact of rain.Ocean Sci., 9 (1): 183-192.
Boutin J, Martin N, Yin X et al.2012.First assessment of SMOS data over open ocean: Part II—sea surface salinity.IEEE Trans.Geosci.Remote Sens., 50 (5): 1 662-1 675.
Droppleman J D, Mennelin R A.1970.An airborne measurement of salinity variations of the Mississippi river overflow.J.Geophys.Res., 78 (30): 5 909-5 013.
Gabarro C, Font J, Camps A et al.2004.A new empirical model of sea surface microwave emissivity for salinity remote sensing.Geophysical Research Letters, 31 (1): 1-5.
Guimbard S, Gourrion J, Portabella M et al.2012.SMOS semi-empirical ocean forward model adjustment.IEEE Trans.Geosci.Remote Sens., 50 (5): 1 676-1 687.
Hwang P A.2012.Foam and roughness effects on passive microwave remote sensing of the ocean.IEEE Trans.Geosci.Remote Sens., 50 (8): 2 978-2 985.
Johnson J T.2006.An efficient two-scale model for the computation of thermal emission and atmospheric reflection from the sea surface.IEEE Trans.Geosci.Remote Sens., 44 (3): 560-568.
Klein L, Swift C T.1977.An improved model for the dielectric constant of sea water at microwave.IEEE Transactions On Frequencies, Antennas and Propagation, 25 (1): 104-111.
Le Vine D M, Lagerloef G S E, Colomb F R et al.2007.Aquarius: an instrument to monitor sea surface salinity from space.IEEE Trans.Geosci.Remote Sens., 45 (7): 2 040-2 050.
Le Vine D M, Lagerloef G S E, Torrusio S E.2010.Aquarius and remote sensing of sea surface salinity from space.Proceedings of the IEEE, 98 (5): 688-703.
Lerner R M, Hollinger J P.1977.Analysis of 1.4 GHz radiometric measurements from Skylab.Remote Sensing of Environment, 6 (4): 251-269.
Mecklenburg S, Drusch M, Kerr Y H et al.2012.ESA's soil moisture and ocean salinity mission: mission performance and operations.IEEE Trans.Geosci.Remote Sens., 50 (5): 1 354-1 366.
Meissner T, Ricciardulli L, Wentz F J.2011.All-weather wind vector measurements from intercalibrated active and passive microwave satellite sensors.IEEE IGRSS, 1 509-1 511.
Meissner T, Wentz F J.2009.Wind-vector retrievals under rain with passive satellite microwave radiometers, IEEE Trans.Geosci.Remote Sens., 47 (9): 3 065-3 083.
Powell M D, Murillo S, Dodge P et al.2010.Reconstruction of hurricane Katrina's wind fields for storm surge and wave hind casting.Ocean Engineering, 37 (1): 26-36.
Qi Z, Wei E.2012.Analysis of cost functions for retrieving sea surface salinity.Journal of Ocean University of China, 11 (2): 147-152.
Reul N, Tenerelli J, Boutin J et al.2012a.Overview of the first SMOS sea surface salinity products.Part I: quality assessment for the second half of 2010.IEEE Trans.Geosci.Remote Sens., 50 (5): 1 636-1 647.
Reul N, Tenerelli J, Chapron B et al.2012b.SMOS satellite L-band radiometer: A new capability for ocean surface remote sensing in hurricanes.J.Geophys.Res., 117 (C2): 1-24.
Tang W, Yueh S H, Fore A et al.2013.The rain effect on Aquarius' L-band sea surface brightness temperature and radar backscatter.Remote Sensing of Environment, 137 (10): 147-157.
Wentz F, Le Vine D, Meissner T et al.2012.Aquarius salinity retrieval algorithm, Algorithm Theoretical Basis Document, Version 2, Addendum I (2012), Addendum II (2013), Addendum III (2014), RSS Technical Report 082912, Remote Sensing Systems, Santa Rosa, California, http://podaac.jpl.nasa.gov/SeaSurfaceSalinity/Aquarius,Accessed on 2014-04-28.
Yin X, Boutin J, Spurgeon P.2012.First assessment of SMOS data over open ocean: Part I—Pacific Ocean.IEEE Trans.Geosci.Remote Sens., 50 (5): 1 648-1 661.
Yueh S, Dinardo S J, Fore A et al.2010.Passive and active L-band microwave observations and modeling of ocean surface winds.IEEE Trans.Geosci.Remote Sens., 48 (8): 3 087-3 100.
Yueh S, Fore A, Freedman A et al.2012.Aquarius Scatterometer Algorithm Theoretical Basis Document, Version 1, Jet Propulsion Laboratory, http://podaac.jpl.nasa.gov/SeaSurfaceSalinity/Aquarius, Accessed on 2014-04-28.