The East China Sea (ECS) is often obscured from space in the visible and near-visible bands by cloud cover, which prevents remote sensing retrieval of optical properties. However, clouds are transparent to microwaves, and satellites with L-band radiometers have recently been put into orbit to monitor sea surface salinity (SSS). Previous studies have used the mixing of fluvial colored dissolved organic matter (CDOM) near coasts, where the mixing is approximately conservative over short time scales, to estimate SSS. In this study, the usual relationship between CDOM and salinity in the ECS has been used in reverse to estimate CDOM from remotely sensed SSS in the ECS and compare that CDOM with MODIS data. The SSS data used are 7 day composites from NASA’s Aquarius/SAC-D satellite which has an L-band radiometer. The challenges in using this approach are that 1) Aquarius SSS has coarse spatial resolution (150 km), and 2) the ECS has numerous anthropogenic sources of radiofrequency interference which adds noise to the L-band signal for the SSS retrievals. Despite the limits in the method, CDOM distribution in the ECS can be estimated under cloudy conditions. In addition to all-weather retrievals, an additional advantage of the approach is that the algorithm provides an estimate of CDOM absorption that is unaffected by the spectrally similar detritus absorption that can confound optical remote sensing estimates of CDOM.
Measuring the sea surface during tropical cyclones (TC) is challenging due to severe weather conditions that prevent shipboard measurements and clouds which mask the sea surface for visible satellite sensors. However, sea surface emission in the microwave L-band can penetrate rain and clouds and be measured from space. The European Space Agency (ESA) MIRAS L-band radiometer on the Soil Moisture and Ocean Salinity (SMOS) satellite enables a view of the sea surface from which the effects of tropical cyclones on sea surface emissivity can be measured. The emissivity at these frequencies is a function of sea surface salinity (SSS), sea surface temperature (SST), sea surface roughness, polarization, and angle of emission. If the latter four variables can be estimated, then models of the sea surface emissivity can be used to invert SSS from measured brightness temperature (T<sub>B</sub>). Actual measured T<sub>B</sub> from space also has affects due to the ionosphere and troposphere, which have to be compensated for, and components due to the galactic and cosmic background radiation those have to be removed. In this research, we study the relationships between retrieved SSS from MIRAS, and SST and precipitation collected by the NASA TMI sensor from the Tropical Rainfall Measuring Mission (TRMM) satellite during Hurricane Isaac, in August 2012. During the slower movement of the storm, just before landfall on the vicinity of the Louisiana Shelf, higher precipitation amounts were associated with lower SSS and slightly increased SST. This increased trend of SST and lower SSS under regions of high precipitation are indicative of inhibited vertical mixing. The SMOS Level 2 SSS were filtered by a stepwise process with removal of high uncertainty in T<sub>B</sub> under conditions of strong surface roughness which are known to create noise. The signature of increased SST associated with increasing precipitation was associated with decreased SSS during the storm. Although further research is required, this study shows that there is a T<sub>B</sub> signal from the sea surface beneath a tropical cyclone that provides information on roughness and salinity.