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Observational analysis and retrieval of snowfall using satellite data at high microwave frequencies.

机译:使用高微波频率的卫星数据进行观测分析和降雪检索。

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摘要

In the high latitudes during cold seasons, a substantial portion of precipitation falls in the form of snow. Measuring snow precipitation has many applications such as forecasting hazardous weather, understanding hydrological water budget, and evaluating the cooling and freshening effects of snow onto ocean surface. However, unlike rainfall, snowfall measurement is extremely limited due to technical difficulties, especially over ocean and in the Polar Regions. The goal of this study is to assess the feasibility of measuring snowfall from satellite observations. From the temporal analysis of surface radar data, a diurnal variation of snowfall in the Wakasa Bay area is detected, which is not identified by satellite infrared data. Snowfall signatures are analyzed using satellite and airborne microwave radiometer measurements at frequencies ranging from 37 to 340 GHz. Data used in the analysis include satellite data from the Advanced Microwave Scanning Radiometer---EOS and the Advanced Microwave Sounding Unit - B, and airborne data from a millimeter-wave radiometer and a dual-frequency precipitation radar during January 2003 near Japan. An investigation of the sensitivity of microwave channels to snowfall associated with shallow convective clouds shows that microwave radiation at higher frequencies (≥150 GHz) is sensitive to scattering by snow/ice. Through data analysis and radiative transfer modeling, a snowfall retrieval algorithm based on Bayes' theorem is developed using high frequency satellite microwave data. In the Bayesian snowfall retrieval algorithm, observational data from airborne and surface-based radars are used to construct the a-priori database that is the most important component in the algorithm. Two size distributions for snowflakes and ten observed atmospheric sounding profiles are used to diversify the results and reduce the errors in the radiative transfer model. The scattering properties of the snowflakes are calculated based on realistic nonspherical shapes using discrete dipole approximation for the radiative transfer modeling. The algorithm is validated by independent surface radar/gauge data, subsequently applied to satellite AMSU-B data for winter snowstorms near Japan. The retrieved results show reasonable agreement with surface radar observations, which shows the possibility of applying this algorithm globally by expanding the database.
机译:在寒冷季节的高纬度地区,大部分降水以雪的形式降落。测量积雪的降水量有许多应用,例如预测危险天气,了解水文水量预算以及评估积雪对海洋表面的冷却和新鲜效果。但是,与降雨不同,降雪测量由于技术困难而受到极大限制,尤其是在海洋和极地地区。这项研究的目的是评估通过卫星观测测量降雪的可行性。通过对地面雷达数据的时间分析,发现了Wakasa湾地区降雪的日变化,但卫星红外数据无法识别。使用卫星和机载微波辐射计在37至340 GHz频率范围内对降雪特征进行分析。分析中使用的数据包括2003年1月在日本附近的高级微波扫描辐射仪EOS和高级微波探测仪B的卫星数据以及毫米波辐射仪和双频降水雷达的机载数据。对微波信道对与浅层对流云相关的降雪的敏感性的调查表明,较高频率(≥150GHz)的微波辐射对雪/冰的散射敏感。通过数据分析和辐射传递建模,利用高频卫星微波数据开发了基于贝叶斯定理的降雪检索算法。在贝叶斯降雪检索算法中,来自机载雷达和基于地面的雷达的观测数据用于构建先验数据库,该数据库是算法中最重要的组成部分。雪花的两个尺寸分布和十个观测到的大气探测轮廓被用于使结果多样化,并减少辐射传输模型中的误差。雪花的散射特性是基于实际的非球形形状,使用离散偶极子近似值进行辐射传递建模计算的。该算法已通过独立的地面雷达/仪表数据验证,随后应用于日本附近冬季暴风雪的AMSU-B卫星数据。检索到的结果与地面雷达观测结果显示出合理的一致性,这表明通过扩展数据库在全球范围内应用该算法的可能性。

著录项

  • 作者

    Noh, Yoo-Jeong.;

  • 作者单位

    The Florida State University.;

  • 授予单位 The Florida State University.;
  • 学科 Physics Atmospheric Science.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 96 p.
  • 总页数 96
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 大气科学(气象学);
  • 关键词

  • 入库时间 2022-08-17 11:39:33

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