| 基于FY-2G产品的江西省总云量最小二乘法建模与分析 |
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| 引用本文： | 刘雅楠,邹海波,吴琼.基于FY-2G产品的江西省总云量最小二乘法建模与分析[J].气象与环境学报,2020,36(2):105-111. |
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| 作者姓名： | 刘雅楠 邹海波 吴琼 |
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| 作者单位： | 江西省气象科学研究所, 江西 南昌 330046 |
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| 摘 要： | 使用2016年1月至2018年12月FY-2G卫星逐小时总云量产品和江西省26个测站的地面总云量观测资料,分析了两者在江西地区相关性的时空分布特征。结果表明:江西地区卫星总云量和地面观测总云量在数值和演变趋势上一致性较好,两者的总体相关系数超过0.60,但空间分布不均匀,大型水体(鄱阳湖和柘林湖)附近相关系数较低,低于0.45,江西省南部地区相关系数也不高,低于0.50。两者的相关系数在时间上也分布不均,其中14时的相关系数最高。此外,基于FY-2G卫星总云量产品和最小二乘法采用分段建模的方式,构建了江西省地面观测云的回归模型,且模拟的地面总云量在数值和演变趋势上更加接近观测的地面云量。
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| 关 键 词： | 总云量 最小二乘法 分段建模 |
| 收稿时间： | 2019-02-28 |
Modelling and analysis of the total cloud amount using the least square method based on FY-2G product in Jiangxi province |
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| Ya-nan LIU,Hai-bo ZOU,Qiong WU.Modelling and analysis of the total cloud amount using the least square method based on FY-2G product in Jiangxi province[J].Journal of Meteorology and Environment,2020,36(2):105-111. |
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| Authors: | Ya-nan LIU Hai-bo ZOU Qiong WU |
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| Institution: | Institute of Meteorological Sciences in Jiangxi Province, Nanchang 330046, China |
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| Abstract: | Based on the hourly total cloud amount (TCA) product provided by FY-2G satellite and ground observation data of 26 observation stations in Jiangxi province from January of 2016 to December of 2018, the spatio-temporal distribution characteristics of correlation between two types of data were analyzed.The result shows that the TCAs based on FY-2G satellite and the observation data have good consistency in value and change trend with a population correlation coefficient of above 0.60.However, the spatial correlation is unevenly distributed.Specifically, the correlation coefficient in the vicinity of large water bodies (Poyang Lake and Zhelin Lake), is relatively small and less than 0.45, and that in southern Jiangxi province is less than 0.50.In addition, the correction coefficient of two TCA data in time is unevenly distributed and is the largest at 14 o'clock.Besides, based on the FY-2G satellite TCA product, the regression model of TCA with surface observation is established by using the least square method with segment modelling.As a result, the TCA and its change trend simulated by the model are closer to those of the ground-based observations. |
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| Keywords: | Total cloud amount The least square method Segment modelling |
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