Presentation Description: Remote Sensing Devices (RSDs) such as lidars and sodars are widely used in wind farm development and operations. Studies of commercially available RSDs show excellent agreement with cup anemometry in flat terrain. RSDs use retrieval algorithms that assume horizontal homogeneity of the wind above the sensor. In complex terrain, however, this is not a safe assumption due to upward and downward flow inclinations caused by the terrain. Inhomogeneous flow creates a bias in the RSD wind speeds compared to anemometry. To solve this problem, several products have been developed that use computational fluid dynamics (CFD) to estimate and correct the RSD errors. This survey compares the commercially available techniques for RSD correction, including data from WindCubes, ZX lidars, and Triton sodars. There are similarities across the different models: they solve either the mass conservation equation or the mass and momentum conservation equations; they all use global terrain and land cover databases. They also show similarities in performance: uncorrected RSD wind speeds show biases between 2%-5% compared to anemometry; model-corrected RSD data are within ±1%; site-to-site variation is reduced from 2.5%-3.2% to 1.0%-2.5%. This study also shows that when including flow inclination in anemometer bias and uncertainty estimates, the agreement between CFD-corrected RSD wind speeds and anemometer wind speeds in complex terrain is equivalent to that in flat terrain. Improvements to this correction framework are ongoing: the models add new detail, and the RSDs’ hardware and software are improved. The similarities between models and performance demonstrate a mature technology that can be used with confidence for wind energy applications.