In order to understand the seasonal variation of aerosol optical properties in the Yangtze River Delta,5 years of measurements were conducted during September 2005 to December 2009 at Taihu,China.The monthly averages of aerosol optical depth were commonly 0.6;the maximum seasonal average（0.93） occurred in summer.The magnitude of the Angstr¨om exponent was found to be high throughout the year;the highest values occurred in autumn（1.33） and were the lowest in spring（1.08）.The fine modes of volume size distribution showed the maxima（peaks） at a radius of ～0.15 μm in spring,autumn,and winter;at a radius of ～0.22 μm in summer.The coarse modes showed the maxima（peaks） at a radius of 2.9 μm in spring,summer,and autumn and at a radius of 3.8 μm in winter.The averages of single-scattering albedo were 0.92（spring）,0.92（summer）,0.91（autumn）,and 0.88（winter）.The averages of asymmetry factor were found to be larger in summer than during other seasons;they were taken as 0.66 at 440-1020 nm over Taihu.The real part of the refractive index showed a weak seasonal variation,with averages of 1.48（spring）,1.43（summer）,1.45（autumn）,and 1.48（winter）.The imaginary parts of the refractive index were higher in winter（0.013） than in spring（0.0076）,summer（0.0092）,and autumn（0.0091）,indicating that the atmosphere in the winter had higher absorbtivity.
Radio-frequency interference （RFI） affects greatly the quality of the data and retrieval products from space-borne microwave radiometry. Analysis of the Advanced Microwave Scanning Radiometer on the Earth Observing System （AMSR-E） Aqua satellite observations reveals very strong and widespread RFI contam- inations on the C- and X-band data. Fortunately, the strong and moderate RFI signals can be easily identified using an index on observed brightness temperature spectrum. It is the weak RFI that is diffi- cult to be separated from the nature surface emission. In this study, a new algorithm is proposed for RFI detection and correction. The simulated brightness temperature is used as a background signal （B） and a departure of the observation from the background （O–B） is utilized for detection of RFI. It is found that the O–B departure can result from either a natural event （e.g., precipitation or flooding） or an RFI signal. A separation between the nature event and RFI is further realized based on the scattering index （SI）. A positive SI index and low brightness temperatures at high frequencies indicate precipitation. In the RFI correction, a relationship between AMSR-E measurements at 10.65 GHz and those at 18.7 or 6.925 GHz is first developed using the AMSR-E training data sets under RFI-free conditions. Contamination of AMSR-E measurements at 10.65 GHz is then predicted from the RFI-free measurements at 18.7 or 6.925 GHz using this relationship. It is shown that AMSR-E measurements with the RFI-correction algorithm have better agreement with simulations in a variety of surface conditions.
应用2002—2004年青藏高原CAMP/Tibet试验期间4个地面站点的反照率观测结果定量分析Terra MODIS 1km分辨率短波SW波段(0.3～5.0μm)反照率全反演结果和当量反演结果的精度。对于全反演结果,黑空反照率、白空反照率与地面观测结果的均方根差分别为0.0187和0.0168;对于当量反演结果,黑空反照率、白空反照率与地面观测结果的均方根差分别为0.0766和0.0761。综合全反演结果和当量反演结果,则黑空反照率、白空反照率与地面观测结果的均方根差分别为0.0679和0.0675。当地面观测结果与MODIS反照率当量反演结果均为"无雪"状态时,黑空反照率、白空反照率与地面观测结果的均方根差分别为0.0352和0.0364;当地面观测结果为"积雪"状态,MODIS反照率当量反演结果为"无雪"状态时,黑空反照率、白空反照率与地面观测结果的均方根差分别高达0.1556和0.1541。
