Raman lidar in operational meteorology

B. Valentin Simeonov; Todor Dinoev; Ilya Serikov; Sergei Bobrovnikov; Alexander Hafele; Giovanni Martucci; Daniel Leuenbergerd; Bertrand Calpini

doi:10.1117/12.2501987

24 October 2018 Raman lidar in operational meteorology

B. Valentin Simeonov, Todor Dinoev, Ilya Serikov, Sergei Bobrovnikov, Alexander Hafele, Giovanni Martucci, Daniel Leuenbergerd, Bertrand Calpini

Author Affiliations +

Proceedings Volume 10779, Lidar Remote Sensing for Environmental Monitoring XVI; 107790I (2018) https://doi.org/10.1117/12.2501987
Event: SPIE Asia-Pacific Remote Sensing, 2018, Honolulu, Hawaii, United States

Abstract

Water vapor and temperature spatial distribution and their temporal evolution are among the most important parameters in numerical weather forecasting and climate models. The operational relative humidity/temperature profiling in meteorology is carried out mostly by radio sondes. Sondes provide profiles with high vertical resolution but suffer from systematic errors and low temporal resolution. The temporal resolution is also a limitation for the now-casting, which has become more and more important for meteorological alerts and for the aviation. Recently, some of national meteorological services have introduced Raman lidars for additional operational humidity/temperature profiling. The lidars allow monitoring of water vapor mixing ratio and temperature with high vertical and temporal resolutions. Here the design and measurement results from the Raman Lidar for Meteorological Observation (RALMO) developed by the Ecole Polytechnique Féderal de Lausanne (EPFL) and operated by MeteoSwiss is presented as an illustration of the potential of Raman lidars in operational meteorology. The first applications of lidar data in numerical weather forecasting is also discussed.

Citation Download Citation

B. Valentin Simeonov, Todor Dinoev, Ilya Serikov, Sergei Bobrovnikov, Alexander Hafele, Giovanni Martucci, Daniel Leuenbergerd, and Bertrand Calpini "Raman lidar in operational meteorology", Proc. SPIE 10779, Lidar Remote Sensing for Environmental Monitoring XVI, 107790I (24 October 2018); https://doi.org/10.1117/12.2501987

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