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Free keywords:
Humidity, Meteorology, Numerical weather forecasting, Precipitation, Raman lidar, Temperature, Water vapor, Atmospheric humidity, Climate models, Environmental engineering, Meteorology, Optical radar, Precipitation (chemical), Precipitation (meteorology), Remote sensing, Systematic errors, Temperature, Water vapor, High vertical resolution, Meteorological observation, Numerical weather forecasting, Polytechnique, Raman LIDAR, Temporal evolution, Temporal resolution, Water vapor mixing ratio, Weather forecasting
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. © 2018 SPIE.
