Sea surface salinity of ocean waters has been obtained from L-band microwave radiometer on satellite, such SMOS, Aquarius and SMAP. It provides a new technology and way to observe the salinity over large region from space. However, it is still difficult to get the sea surface salinity of the coastal waters due to that the effect on satellite-observed microwave radiance of radio frequency interference over near-shore regions. Fortunately, the colored dissolved organic matter (CDOM) has conservative or semi-conservative property in the freshwater areas of coastal rivers and it has a good linear correlation between the absorption coefficient of CDOM and salinity. Based on those, a conservative mixing relationship between the fresh water from the Pearl River and the sea water from the South China Sea are established and the distribution of sea surface salinity from MODIS-retrieved absorption coefficient of CDOM (aCDOM) at 355nm wavelength in this study. The linear relationship between salinity and aCDOM at 355 nm under conservative mixing conditions can be established from the in-situ observed salinity and MODIS-retrieved aCDOM at 355 nm at the central water mass in the Pearl River Estuary and the northern basin region of South China Sea. By comparing daily observed MODIS-retrieved sea surface salinity with the in-site observed salinity, it shows that the salinity retrieved from satellite-based aCDOM has good agreement with observations, and it can better capture the location of low salinity fresh water in the Pearl River. For the summer averaged satellite-based salinity from 2002 to 2018, sea surface salinity are gradually increases from the vertical coastline to the sea in the Pearl River Estuary region. The salinity in coastal region is low by the effect of the Pearl River diluted water, and the salinity in offshore region is high. On average, the distribution of salinity shows that the diffusion of fresh water from the Pearl River generally spread along the coastline to the east and west in summer, while the runoff on the westward is larger and on the eastward it is affected by some flushing water of other rivers. In the future, MODIS-retrieved salinity can be as a supplement to salinity inversion of Microwave radiometer in the coastal region.
Asian dust storms, which can long-range transport to ocean, often occur on spring. The present of Asian dust aerosols over ocean makes some difficult for other studies, such as cloud detection, and also take some advantage for ocean, such as take nutrition into the ocean by dry or wet deposition. Therefore, it is important to study the dust aerosol and retrieve the properties of dust from satellite observations that is mainly from the thermal infrared radiance. In this paper, the thermal infrared radiance properties of dust aerosol over ocean are analyzed from MODIS and MTSAT2 observations and Streamer model simulations. By analyzing some line samples and a series of dust aerosol region, it shows that the dust aerosol brightness temperature at 12μm (BT12) is always greater than BT11 and BT8.5, and BT8.5 is general greater than BT11. The brightness temperature different between 11μm and 12μm (BTD11-12) increases with the dust intensity. And the BTD11-12 will become positive when the atmospheric relative humidity is greater than 70%. The BTD11-12 increases gradually with the surface temperature while the effect on BTD11-12 of dust layer temperature is not evident. Those are caused by the transmission of the dust aerosol is different at the two thermal infrared channels. During daytime, dust infrared brightness temperature at mid-infrared bands should reduce the visual radiance, which takes about 25K or less. In general, BT3.7 is greater than BT11 for dust aerosol. Those results are helpful to monitor or retrieve dust aerosol physical properties over ocean from satellite.
In this study, a 3-hourly time resolution gap free sea surface temperature (SST) analysis is generated to resolve the diurnal cycle in the South China Sea (SCS, 0°–25°N, 100°–125°E).It takes advantage of hourly geostationary satellite MTSAT observations and combines three infrared and two microwave polar satellite observations at different local times. First, all the data are classified into eight SST datasets at 3 hour intervals and then remapped to 0.05°resolution grids. A series of critical quality control is done to remove the outliers.Then bias adjustment is applied to the polar satellite observations with reference to the MTSAT data. Finally, the six satellites SST data are blended by using the optimal interpolated algorithm. The 3-hourly blended SST is compared against buoy measurements. It shows a good agreement that the biases do not exceed 0.2 °C and root mean square errors range from 0.5 to 0.65 °C. A typical diurnal cycle similar to sine wave is observed. The minimum SST occurs at around 0600h and warming peak occurring between 1300h and 1500h local solar time and then decrease in the late afternoon, tapering off at night on March 13, 2008 for example. The frequency of diurnal warming events derived from four years of the blended SST provides solid statistics to investigate the seasonal and spatial distributions of the diurnal warming in the SCS. The sea surface diurnal warming tends to appear more easily in spring, especially in the coastal regions than other seasons and the central regions.
The blended sea surface temperature (SST), which generated from satellites-retrieved SST, is widely used in the fields of oceanic and atmospheric researches. Due to the quality of satellites-retrieved SST will affect the blended SST, the quality control (QC) is necessary and important. In general, the quality of data is controlled by the in situ observations. However, the in situ SST observations are sparse and not available in near real time over the globally ocean, especially for the China Seas and their adjacent seas. In this paper, a complementary quality control procedure, which use the Optimal Interpolation SST as a reference standard (TR) to identify outliers in infrared SST (TS) is proposed. The TR is validated against in situ SST first. Then a time evolution check for TS is employed. The TS lies between the limit checks, which are defined relative to TR of the previous 10 days. Spatial-coherence analyses of the differences (ΔSST) between the TS and the TR is taken into account later on. Then, robust statistics is applied to flag the extreme residual outliers. After those QC procedures for MODIS-retrieved SST, most of the outliers are removed. The histogram of ΔSST is strong asymmetry and the minimum value reach ~-35°C mainly due to the cloud contamination before QC. The corresponding histogram after QC shows that the ΔSST are close to Gaussian and the min and max ΔSST reach~ ±4°C. The further validation for this method is performed using a total number of 506 matchups of buoy and MODIS. The bias is -0.458 and the standard deviation is 1.341. This QC procedure can effectively remove the outliers and the remaining observation errors are mainly due to diurnal variability, which should be focused on in the future study.
Asian dust storms, which often occur on spring, can long range transport and pass through the China Seas. During this
process, it makes some impact on marine ecology and region climate. In this paper, the optical and thermal properties of
Asian dust aerosols are firstly presented from the satellite MODIS observations. By comparing strong dust, weak dust,
clear water and clouds, the reflectances of dust aerosols over ocean at the visible 0.47μm 0.86μm, and the near-infrared
1.64μm have some significant features, it satisfies R0.47<R1.64<R0.86 for strong dust aerosol over ocean, the weak dust
aerosol meets R1.64<R0.47<R0.86, even R1.64<R0.86<R0.47, and the dust reflectance may be from 0.1 to 0.3. At the
thermal atmospheric windows bands 8.5, 11 and 12μm, for cloud and clear water region, the brightness temperature at
12μm is highest and the temperature at 11μm is close to 12μm. However, for dust aerosols, the brightness temperature at
12μm is much greater than those at 8.5μm and 11μm. The brightness temperature difference between 8.5μm and 11μm is
small and the lower is the difference, the stronger is the dust aerosol. Based on those visible and thermal characteristics,
a detection algorithm for dust aerosols over ocean is designed and is conducted for some cases. It can identify the strong
and the weak dust regions well and it is nice to study the dust properties deeply.
Knowledge of tropical cyclone intensity is good for pre-analysis on its development and its possible damage. It is the
lack of observations in situ and the drawback of numerical model that make the remotely sensing from space be a useful
method for tropical cyclone study. In this paper, a preliminary study on estimating tropical cyclone intensity by using
MODIS (Moderate Resolution Imaging Spectroradiometer) data is present. The typhoon 0922 Nida is as a case for this
study and the maximum wind speed in the cyclone is used to an index of cyclone intensity. By detecting the typhoon
body from MODIS observation, the eyewall and edge of Nida is identified. The cloud-top height and cloud-top
temperature in tropical cyclone region, which are two key parameters for estimating tropical cyclone intensity, is also
obtained from MODIS observations. The retrieved cloud-top height is compared and validated with the CloudSat radar
observations, which just cross the neighborhood of the 0922 storm center. According to a physically based framework,
the maximum wind speed is estimated approximately from the background sea surface temperature, cloud-top
temperature and cloud-top height. A simple result indicates that the technique for estimating cyclone intensity from
MODIS observation is feasible. On the other hand, the future applications and some potential uncertainties on means are
needed to be on second thoughts and discussed.
Asian dust often occurring in the spring can be transported to the China Sea, even far to the North Pacific region. In this
process, the dust deposition brings some nutrients and microelements into ocean and can affect the marine ecosystem
significantly, such as the phytoplankton populations. In this study, we firstly analyze the monthly variations of
chlorophyll a (Chla) concentrations and aerosol optical thickness (AOT), and then consider three major dust storm events
during April 2006 to study their impact on the chlorophyll concentrations along the track of the dust storm using satellite
observations over the Yellow Sea, including AOT and the Chla from Modis, composited sea surface temperature (SST)
from TRMM / TMI and AMSR-E, and sea surface winds (SSW) from Quikscat. The central of North Yellow Sea (38-
39°N,123-124°E) and South Yellow Sea (35-37°N, 123-125°E) are regions where Chla blooming frequently during
dust events. The Chla usually up to 5-12mg/m3 and the max value even greater than 30 mg/m3. Without high wind speed
and suitable temperature, dust deposition could also cause chlorophyll concentrations increased, but its impact region is
limited and intensity is small in the Yellow Sea. Due to the AOT usually overflow or failure over dust regions, the high
AOT can denote dust event. In the future, the dust aerosol optical thickness and other properties need to be estimated for
further study on the ocean biogeochemical response to Asian dust events.