SMOS sea surface salinity prototype processor:: Algorithm validation

被引:0
作者
Zine, S. [1 ,4 ]
Boutin, J. [1 ]
Font, J. [2 ]
Talone, M. [2 ]
Gabarro, C. [2 ]
Reul, N. [3 ]
Tenerelli, J. [3 ]
Waldteufel, P. [4 ]
Petitcolin, F. [5 ]
Vergely, J. -L. [5 ]
机构
[1] Inst Pierre Simon Laplace, Lab Oceanog & Climat Experimentat & Approches Num, Paris, France
[2] CMIMA CSIC, Inst Ciencias Mar, Barcelona, Spain
[3] IFREME, Lab Oceanog Spatiale, Plouzane, France
[4] Service Aeronom Inst Pierre Simon, Verrieres Le Buisson, France
[5] ACRI ST, Sophia Antipolis, France
来源
IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET | 2007年
关键词
radiometry; oceanography; salinity; SMOS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A The Soil Moisture and Ocean Salinity (SMOS) mission (launch scheduled for 2008) aims at obtaining global maps of soil moisture and sea surface salinity (SSS). It uses an L-band (1.4 GHz) microwave interferometric radiometer to obtain brightness temperatures (Tb) at the Earth surface at horizontal and vertical polarizations. They will be used to retrieve both geophysical variables, following specifically designed algorithms that will be applied when the satellite field-of-view, is covering land or ocean surfaces respectively. The retrieval of salinity is a complex process that requires the knowledge of environmental information and an accurate processing of the radiometer measurements, because of the narrow range of ocean Tb and the strong impact on the measures of geophysical parameters (such as sea state). Here we present the baseline approach chosen to retrieve sea surface salinity from SMOS data, as developed and implemented by the joint team of scientists and engineers responsible for the SMOS Salinity Level 2 Prototype Processor. We present academic tests conducted over homogeneous scenes with the prototype. In these configurations, external perturbation sources (sky radiation, sun glint,...) are not taken into account. Roughness is the main sea surface signal disturbing SSS retrieval.
引用
收藏
页码:3955 / +
页数:2
相关论文
共 24 条
[1]  
Boutin J, 2004, J ATMOS OCEAN TECH, V21, P1432, DOI 10.1175/1520-0426(2004)021<1432:SSRFSM>2.0.CO
[2]  
2
[3]   Retrieving sea surface salinity with multiangular L-band brightness temperatures: Improvement by spatiotemporal averaging [J].
Camps, A ;
Vall-llossera, M ;
Batres, L ;
Torres, F ;
Duffo, N ;
Corbella, I .
RADIO SCIENCE, 2005, 40 (02) :RS2003-RS2013
[4]  
Camps A, 2003, INT GEOSCI REMOTE SE, P13
[5]   Influence of sea surface emissivity model parameters at L-band for the estimation of salinity [J].
Dinnat, EP ;
Boutin, J ;
Caudal, G ;
Etcheto, J ;
Waldteufel, P .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2002, 23 (23) :5117-5122
[6]  
Freilich MH, 1997, J ATMOS OCEAN TECH, V14, P695, DOI 10.1175/1520-0426(1997)014<0695:VOVMDE>2.0.CO
[7]  
2
[8]   A new empirical model of sea surface microwave emissivity for salinity remote sensing -: art. no. L01309 [J].
Gabarró, C ;
Font, J ;
Camps, A ;
Vall-Ilossera, M ;
Julià, A .
GEOPHYSICAL RESEARCH LETTERS, 2004, 31 (01) :L013091-5
[9]  
HASSELMANN S, 1988, J PHYS OCEANOGR, V18, P1775
[10]   Theoretical study of the small slope approximation for ocean polarimetric thermal emission [J].
Johnson, JT ;
Zhang, M .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1999, 37 (05) :2305-2316