This chapter outlines several methods for obtaining wind data. The traditional approach involves in situ measurement, i.e., deploying instruments directly within the air volume of interest (Sect. 3.1). With the recent advancements in remote sensing technologies, remote sensing instruments, such as lidars and sodars, have emerged as powerful tools for wind observation (Sect. 3.2). However, due to the discrete nature of observations in both space and time, it is impossible to cover every aspect of the Earth’s atmosphere. An alternative approach to reproduce wind fields is to use numerical models, such as numerical weather prediction (NWP) models and computational fluid dynamics (CFD) simulations (Sect. 3.3). They can provide gridded, gap-free wind data in three-dimensional space, Albert such simulated data needs careful validation before use.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Wind Observation and Modeling Techniques

  • Junyi He,
  • Qiu-Sheng Li

摘要

This chapter outlines several methods for obtaining wind data. The traditional approach involves in situ measurement, i.e., deploying instruments directly within the air volume of interest (Sect. 3.1). With the recent advancements in remote sensing technologies, remote sensing instruments, such as lidars and sodars, have emerged as powerful tools for wind observation (Sect. 3.2). However, due to the discrete nature of observations in both space and time, it is impossible to cover every aspect of the Earth’s atmosphere. An alternative approach to reproduce wind fields is to use numerical models, such as numerical weather prediction (NWP) models and computational fluid dynamics (CFD) simulations (Sect. 3.3). They can provide gridded, gap-free wind data in three-dimensional space, Albert such simulated data needs careful validation before use.