Remote sensing research on the influence on the ocean color environment of the East and South China Sea from snowstorm in cold winter this year
2008
At the beginning of 2008, the south area of China suffered a rare heavy snow and low temperature weather, which
brought enormous economic lose and broke the environment. The abnormal weather also influenced the ocean color
environment. Through analysis of MODIS remote sensing 3A data during 2 months before and after the snowstorm and
low temperature weather, the author finds that, on the one hand,compared with same period of last year, the sea surface
temperature (SST) from the East China Sea to the South China Sea (18°N-32°N 108°E-126°E descended 2.57°C; the
average chlorophyll-a concentration(CHL-a)rose from 1.198 mg. m -3 to 1.75 mg. m -3 in the snowstorm and low
temperature weather period from January 11 to 31 of 2008 which was 1.46 times more than that of the same period of
last year. On the other hand, compared with the period before snowstorm,the SST decreased from 22.42°C to 18.34°C but the CHL-a rose from 1.32 mg. m -3 to 1.60 mg. m -3 after the snowstorm. In addition,the sea water transparency(SDD)
had a certain increase in the open sea of South China Sea, but the suspended sediment concentration(SSC) increased
significantly near the seashore, the Yangtse River Estuary and the Pearl River Estuary, which increased 200% compared
with the period before the snowstorm 2008. Through researching and indicating, the main reason of increase of the
CHL-a in the near seashore area(the I water) was more probably due to the increase of the SSC, and the CHL-a by
remote sensing has greater error, which rising from the high SSC led to the increase of CHL-a; but in the open sea the
increase of CHL-a is that the SDD improved and then the euphotic increased. As a result,this could promote the growth
of primary productivity. Therefore, it faces the better applied foreground to monitor the influence on the ocean
ecosystem environment caused by the snowstorm and low temperature weather through remote sensing.
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