FN Archimer Export Format
PT J
TI GNSS-R nonlocal sea state dependencies: Model and empirical verification
BT 
AF CHEN-ZHANG, David D.
   RUF, Christopher S.
   ARDHUIN, Fabrice
   PARK, Jeonghwan
AS 1:1;2:2;3:3;4:4;
FF 1:;2:;3:;4:;
C1 Univ Michigan, Dept Elect & Comp Engn, Ann Arbor, MI 48109 USA.
   Univ Michigan, Climate & Space Dept, Ann Arbor, MI 48109 USA.
   Univ Brest, IFREMER, Lab Ocean Phys & Satellite Oceanog, CNRS,IRD, Plouzane, France.
   Ohio State Univ, Electrosci Lab, Columbus, OH 43212 USA.
C2 UNIV MICHIGAN, USA
   UNIV MICHIGAN, USA
   CNRS, FRANCE
   UNIV OHIO STATE, USA
UM LOPS
IF 2.939
TC 14
UR https://archimer.ifremer.fr/doc/00358/46909/46809.pdf
LA English
DT Article
DE ;waves;wind;remote sensing
AB Global Navigation Satellite System Reflectometry (GNSS-R) is an active, bistatic remote sensing technique operating at L-band frequencies. GNSS-R signals scattered from a rough ocean surface are known to interact with longer surface waves than traditional scatterometery and altimetry signals. A revised forward model for GNSS-R measurements is presented which assumes an ocean surface wave spectrum that is forced by other sources than just the local near-surface winds. The model is motivated by recent spaceborne GNSS-R observations that indicate a strong scattering dependence on significant wave height, even after controlling for local wind speed. This behavior is not well represented by the most commonly used GNSS-R scattering model, which features a one-to-one relationship between wind speed and the mean-square-slope of the ocean surface. The revised forward model incorporates a third generation wave model that is skillful at representing long waves, an anchored spectral tail model, and a GNSS-R electromagnetic scattering model. In comparisons with the spaceborne measurements, the new model is much better able to reproduce the empirical behavior.
PY 2016
PD NOV
SO Journal Of Geophysical Research-oceans
SN 2169-9275
PU Amer Geophysical Union
VL 121
IS 11
UT 000392841000024
BP 8379
EP 8394
DI 10.1002/2016JC012308
ID 46909
ER

EF