The Retrieval, Assimilation, Pentadly Averaged Time Series Building And Analysis Of Sea Ice In The Bohai Sea Using The Visible Remote Sensing Data

The MODIS (Moderate Resolution Imaging Spectroradiometer) on the EOS(Earth Observing Satellites, including EOS-AM and EOS-PM) of NASA (NationalAeronautics and Space Administration) has high-resolution visual spectral data. Toretrieval the sea ice in Bohai, we use the data of band2and band7to distinguish thesnow and cloud, which has a better result than the previous algorithm. MODIS datais missed when coverd by cloud, however, the missing data can be interpolated byassimilation technology. Based on the MODIS remote sensing satellite data, thetime series of pentadly averaged distance between sea ice edge and the coast ofBohai Sea from2001to2011is built. The analysis of the interannual andintraseasonal variability of the series shows that the largest distance usually appearsin January and early February, and the appearing time of the largest distance inLiaodong Bay is later than that of the rest two Bays. What’s more, a later appearinglargest distance corresponds to heavier sea ice. The key factors are analyzed as wellbased on the pentadly time series. The results show that sea ice in small area, suchas Bohai Bay and Laizhou Bay, has a quicker response to air temperature, and thepentadly negative accumulated temperature is a better predictor for sea ice than thepentadly averaged temperature for these two bays; while sea ice in larger sea area,such as Liaodong Bay, has a better correlation with the prophase temperature. Seaice of the whole Bohai Sea is negatively correlated with the prophase area, intensityand ridge line of the subtropical high, among these subtropical high indexes, area isthe factor having quickest and most intense effect on the sea ice distance. Wepresent two key factors from the500hPa geopotential height near the westerlycirculation zone. The averaged geopotential height of East-Asia and West-Pacificareas can act as new predictors for the sea ice of Bohai Sea. We also analyse and interpret the influencing mechanism of the two new factors. We structure a linearregress equation of Bohai sea ice extentwith pentadly averaged temperature,pentadly negative accumulated temperature, averaged geopotential height ofEast-Asia and West-Pacific areas as the predictors. The result of this equationapproximates the MODIS series well, especially in the seasonal variation. In theregress equation, the temperature has the biggest variance contribution, but theanalysis indicates that the averaged geopotential height of East-Asia is moreimportant in the years when the sea ice is heavy.