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METICE is a machine-learning ensemble transfer function that converts a CW Lidar’s turbulence measurements into an equivalent cup reading. What sets METICE apart is its novel architecture combining multiple site-specific models with a Bayesian weighting scheme, combined with extensive training and validation data sets that represent best-in-class turbulence intensity data from a Lidar.

An Informative Guide for the Wind Energy Industry.

Measuring wind in the 10–50 m layer above ground or sea level is critical for a range of applications within the wind energy industry - from designing wind energy projects to understanding loads on modern wind turbines.

This informative guide explores the unique wind flow behaviour in the 10–50 m layer, the challenges of measuring wind in this regime, and how ZX’s Lidar technology addresses these challenges. We present validation evidence comparing ZX Lidars against traditional sensors (cup and ultrasonic anemometers) at low heights, discuss use cases across wind energy and offshore platforms, and include real-world case studies. All claims are grounded in validated data and aligned with IEC 61400-12-1 standards and industry best practices for wind measurements.

Over the past decade, wind Lidars have transformed resource assessment for the wind energy industry, offering unprecedented flexibility, scalability, and measurement capabilities compared to conventional meteorological masts and cup anemometers.The flexibility and lower cost of standalone lidar use in complex terrain has increased their prevalence.
In complex terrain, where wind flows are influenced by rugged topography, well-proven methods can be used to harmonise Lidar measurements with traditional approaches. This alignment is an opportunity to
unlock the full potential of remote sensing devices like ground-based, vertical wind Lidar ZX 300, ensuring continued progress and innovation in wind energy development.
In doing so, Lidars provide a significant step forward in wind measurement technology.

This best practice guide from ZX Lidars describes how the perceived challenges of using remote sensing devices in complex terrain are overcome to unlock these wider benefits, using well-proven
commercial solutions from leading authorities in the wind energy industry.

This paper highlights the maturity of CFD methods for Lidar to point wind measurement conversion.

It aggregates results from over 140 test cases which included mountainous terrain, coastal areas and forestry, with ruggedness index values of over 10%. Across all campaigns RS-to-mast differences were reduced below 1% in over 90% of the test cases.