and Long 2004; Weissman et al. 2002) or proximity to coastal areas (~15 km for
QuikSCAT and 30 km for ASCAT). The data typically have in-swath spatial
resolution of 25 km, and some product for hurricane studies has ultrahigh resolution
of 2.5 km (Williams and Long 2008). Because of the narrow satellite swath and
orbit, temporal sampling is rather limited. Synthetic Aperture Radars (SARs) are
able to provide wave spectrum from kilometer to capillary wave scales, hence wind
field monitoring capability (Beal et al. 2005). Use of multiple scatterometers can
greatly improve the temporal sampling and directional measurements and help fill
in the data gaps in rainy conditions.
Passive microwave radiometers measure electromagnetic radiation from the ocean
surface at several frequencies and routinely provide global near-surface wind speed
estimates over rain-free ocean at a spatial resolution of roughly 25 km. Wind measuring microwave sensors include the Scanning Multichannel Microwave Radiometer
(SMMR) onboard the NIMBUS-7 satellite, the Special Sensor Microwave Imager
(SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS) onboard the
Defense Meteorological Satellite Program (DMSP), the Tropical Rainfall Measuring
Mission (TRMM) Microwave Imager (TMI), and the Advanced Microwave Scanning
Radiometer – Earth Observing System (AMSR-E). Retrieval algorithms of wind speed
include the traditional D-matrix (Lo 1983), regression (Goodberlet et al. 1989;
Goodberlet and Swift 1992), neural network (Krasnopolsky et al. 1995), and physical
approaches (Wentz et al. 1986). Resolution of the ambiguity in wind direction (Wentz
1992) requires polarization measurements at Æ45
in addition to the horizontal and
vertical polarizations (Dzura et al. 1992; Gasiewski and Kunkee 1993), or the use of
variational analysis methods (Atlas et al. 1991). These wind retrievals are quite
accurate under typical ocean conditions (Mears et al. 2001; Meissner et al. 2001),
and there are good agreements between passive radiometer winds and scatterometer
winds (Wentz et al. 2007).
11.3.2 Sea Surface Temperature
Skin sea surface temperature (SST), which is the temperature at the interface between
the ocean and the atmosphere, should be used to compute LHF and SHF (Curry et al.
2004). Skin (~10–20 μm) or subskin (~1–2 mm) SSTs determined from satellites
include estimates from infrared and passive microwave radiometry. Both types of
observations have their own strengths and weaknesses. Infrared SST measurements
have good spatial resolution (1–10 km), radiometric accuracy (0.2–0.8 K) (Donlon
et al. 2007), and long heritage (~30 years). However, they require atmospheric
correction and fail over cloudy situations, under which a lot of interesting meteorological phenomena occur, such as over a hurricane. Infrared instruments for deriving
SST include the Advanced Very High-Resolution Radiometer (AVHRR), the
Advanced Along-Track Scanning Radiometer (AATSR), the Geostationary Operational Environmental Satellite (GOES) Imager, and the Moderate Resolution Imaging
Spectroradiometer (MODIS) (see Sun 2011). Passive microwave sensors can
measure SST through clouds with lower accuracy (0.5–1 K) and resolution
11 Satellite-Based Ocean Surface Turbulent Fluxes
169
QuikSCAT and 30 km for ASCAT). The data typically have in-swath spatial
resolution of 25 km, and some product for hurricane studies has ultrahigh resolution
of 2.5 km (Williams and Long 2008). Because of the narrow satellite swath and
orbit, temporal sampling is rather limited. Synthetic Aperture Radars (SARs) are
able to provide wave spectrum from kilometer to capillary wave scales, hence wind
field monitoring capability (Beal et al. 2005). Use of multiple scatterometers can
greatly improve the temporal sampling and directional measurements and help fill
in the data gaps in rainy conditions.
Passive microwave radiometers measure electromagnetic radiation from the ocean
surface at several frequencies and routinely provide global near-surface wind speed
estimates over rain-free ocean at a spatial resolution of roughly 25 km. Wind measuring microwave sensors include the Scanning Multichannel Microwave Radiometer
(SMMR) onboard the NIMBUS-7 satellite, the Special Sensor Microwave Imager
(SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS) onboard the
Defense Meteorological Satellite Program (DMSP), the Tropical Rainfall Measuring
Mission (TRMM) Microwave Imager (TMI), and the Advanced Microwave Scanning
Radiometer – Earth Observing System (AMSR-E). Retrieval algorithms of wind speed
include the traditional D-matrix (Lo 1983), regression (Goodberlet et al. 1989;
Goodberlet and Swift 1992), neural network (Krasnopolsky et al. 1995), and physical
approaches (Wentz et al. 1986). Resolution of the ambiguity in wind direction (Wentz
1992) requires polarization measurements at Æ45
in addition to the horizontal and
vertical polarizations (Dzura et al. 1992; Gasiewski and Kunkee 1993), or the use of
variational analysis methods (Atlas et al. 1991). These wind retrievals are quite
accurate under typical ocean conditions (Mears et al. 2001; Meissner et al. 2001),
and there are good agreements between passive radiometer winds and scatterometer
winds (Wentz et al. 2007).
11.3.2 Sea Surface Temperature
Skin sea surface temperature (SST), which is the temperature at the interface between
the ocean and the atmosphere, should be used to compute LHF and SHF (Curry et al.
2004). Skin (~10–20 μm) or subskin (~1–2 mm) SSTs determined from satellites
include estimates from infrared and passive microwave radiometry. Both types of
observations have their own strengths and weaknesses. Infrared SST measurements
have good spatial resolution (1–10 km), radiometric accuracy (0.2–0.8 K) (Donlon
et al. 2007), and long heritage (~30 years). However, they require atmospheric
correction and fail over cloudy situations, under which a lot of interesting meteorological phenomena occur, such as over a hurricane. Infrared instruments for deriving
SST include the Advanced Very High-Resolution Radiometer (AVHRR), the
Advanced Along-Track Scanning Radiometer (AATSR), the Geostationary Operational Environmental Satellite (GOES) Imager, and the Moderate Resolution Imaging
Spectroradiometer (MODIS) (see Sun 2011). Passive microwave sensors can
measure SST through clouds with lower accuracy (0.5–1 K) and resolution
11 Satellite-Based Ocean Surface Turbulent Fluxes
169