以2007年数据为例，利用MODIS产品和地面观测数据对NOAA/AVHRR计算得到的总云量进行数据质量评估。评估结果表明，利用NOAA/AVHRR计算的总云量能较好地反映中国总云量的变化特征，总体上在统计意义上要比站点观测总云量略偏低。当以地面观测云为真值，与MODIS云检测产品相比，利用NOAA/AVHRR检测的云像元准确性较高，误判率较低。利用EOF和SVD分解分析NOAA/AVHRR计算总云量与地面观测和MODIS产品的相似度，得到NOAA/AVHRR计算总云量在空间分布上更接近站点观测值，NOAA/AVHRR计算总云量与地面观测总云量SVD分解第一模态时间系数的相关系数（0.96）高于MODIS产品和地面观测总云量间的相关系数（0.76），特别在冬季，NOAA/AVHRR计算总云量明显好于MODIS总云量产品。
Based on recalibration and accurate re-location of NOAA/AVHRR data, long term total cloud amount were calculated by improved cloud detection and radiation calculation method. The study satellite data came from National Satellite meteorological Center. The long term total cloud amount is daily data and has 0.01°×0.01° spatial resolution. Based on 2007 data, NOAA/AVHRR calculated total cloud amount were validated using MODIS cloud products and synoptic observations. Compared with synoptic observations, NOAA/AVHRR derived total cloud amount shows the same cloud distribution character in China. The value of total cloud amounts estimated from NOAA/AVHRR is smaller than synoptic observations. These results are the same as Europe research conclusions. There are a lot of reasons to cause biases. One of reasons may come from the observation ability of NOAA/AVHRR. Compared with surface observation, accurate rate of AVHRR's cloud detection get 77.12%. It is higher than MODIS's 74.34%. At the same time, NOAA/AVHRR has lower false rate and higher loss rate than MODIS. NOAA/AVHRR used added snow detection to improve the accuracy of cloud detection so that NOAA AVHRR has lower false rate, especially in winter time over high latitude area. Because MODIS has more channels to detect cloud than NOAA/AVHRR, especially for cirrus, MODIS has lower loss rate than NOAA/AVHRR. EOF method was used to analyze the cloud amount distribution properties of AVHRR calculated, MODIS product and surface observations. The results show that the first EOF eigenvector can represent the distribution of three kinds of cloud amount. Compared with MODIS, either the time coefficient or spatial distribution of AVHRR calculated cloud amount is closer to surface observation, especially in winter time. In order to analyze the spatial relationship between satellite observation and surface observation, SVD method was used. AVHRR or MODIS data was set as left vector field. Surface observation was set as right vector. The SVD analysis results show that both AVHRR and MODIS have good relationship with surface observation. The first five correlation coefficients of AVHRR are 0.95, 0.95, 0.94, 0.92 and 0.88. They are all higher than corresponding MODIS's (0.89, 0.91, 0.90, 0.88 and 0.74). At the same time, the first SVD mode time correlation coefficient of AVHRR is 0.96, which is higher than MODIS's 0.76. AVHRR has lower discrete degree of curve fitting than MODIS. Two suit data show that AVHRR derived cloud amount has better match degree with surface observation than MODIS cloud amount.
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