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Regional forecast of the UV index with optimized total ozone prediction using satellite observations over East Asia

机译:使用东亚地区的卫星观测数据,通过优化总臭氧预测值对紫外线指数进行区域预测

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摘要

A regional forecast model of the ultraviolet (UV) index has been developed by using a radiative transfer model and a multiple linear regression model to forecast total ozone over East Asia. This is a difficult and challenging task because of frequent cloud cover and atmospheric aerosols. The new, improved total ozone forecast model was constructed over each grid point in East Asia based on extensive investigation of the correlation between the total ozone and predictors related to the variation in total ozone. Root mean square errors (RMSEs) in the UV index between the forecast and satellite observations from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) for clear sky conditions range from 0.27 to 1.50 with an average of 0.79 in monthly statistics. Although the patterns of the corrected UV index when applying the cloud modification factor (CMF) and the aerosol modification factor (AMF) compare reasonably well with those of the UV index measured with the Ozone Monitoring Instrument (OMI), the performance depends on the accuracy of forecast for cloud and aerosol optical depth (AOD). Additional consideration of surface albedo and cloud optical depth are required to further refine and improve the accuracy of the prediction.
机译:通过使用辐射转移模型和多元线性回归模型,开发了紫外线(UV)指数的区域预报模型,以预测东亚的总臭氧量。由于频繁的云层覆盖和大气气溶胶,这是一项艰巨而具有挑战性的任务。在广泛研究总臭氧和与总臭氧变化有关的预测因子之间的相关性的基础上,在东亚的每个网格点上构建了新的,改进的总臭氧预测模型。晴空条件下,来自大气图表的扫描成像吸收光谱仪(SCIAMACHY)的预报和卫星观测值之间的UV指数的均方根误差(RMSEs)在0.27至1.50之间,每月统计平均值为0.79。尽管应用云量修正因子(CMF)和气溶胶修正因子(AMF)时校正后的紫外线指数的模式与用臭氧监测仪(OMI)测得的紫外线指数的模式相比相当合理,但性能取决于精度云和气溶胶光学深度(AOD)的预测。需要进一步考虑表面反照率和云的光学深度,以进一步完善和提高预测的准确性。

著录项

  • 来源
    《International journal of remote sensing》 |2009年第22期|6035-6051|共17页
  • 作者单位

    IEAA BK21 Programme, Global Environment Laboratory, Department of Atmospheric Sciences, Yonsei University, Seoul, Korea;

    IEAA BK21 Programme, Global Environment Laboratory, Department of Atmospheric Sciences, Yonsei University, Seoul, Korea;

    IEAA BK21 Programme, Global Environment Laboratory, Department of Atmospheric Sciences, Yonsei University, Seoul, Korea;

    Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju, Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

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