Use of lidar water vapor retrieval for assessment of model capability to simulate water vapor profiles

Lev Labzovskii; I. Binietoglou; A. Papayannis; R. F. Banks; J. M. Baldasano

doi:10.1117/12.2195638

20 October 2015 Use of lidar water vapor retrieval for assessment of model capability to simulate water vapor profiles

Lev Labzovskii, I. Binietoglou, A. Papayannis, R. F. Banks, J. M. Baldasano

Proceedings Volume 9645, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing XI; 96450G (2015) https://doi.org/10.1117/12.2195638
Event: SPIE Remote Sensing, 2015, Toulouse, France

Abstract

This work focuses on the evaluation of the abilities of a numerical weather prediction model to simulate water vapor profiles retrieved by multiwavelength Raman lidar measurements. In this work water vapor mixing ratio profiles are retrieved based on lidar measurements at 387 and 407 nm Raman channels. Relative humidity profiles are calculated based on the combination of humidity measurements from lidar and temperature measurements from a microwave radiometer. Simulated water vapor mixing ratio and relative humidity are diagnosed using the Weather Research and Forecasting (WRF) model with 1 × 1 km grid and 1-h temporal resolutions. The accuracy of the WRF model in means of water vapor simulation is assessed by addressing to the experimental datasets based on lidar measurements. All the data used in this work were collected during an international field campaign From Hygrosopic Aerosols to Cloud Droplets (the HygrA-CD campaign) organized from May to June 2014 in Athens, Greece.

Citation Download Citation

Lev Labzovskii, I. Binietoglou, A. Papayannis, R. F. Banks, and J. M. Baldasano "Use of lidar water vapor retrieval for assessment of model capability to simulate water vapor profiles", Proc. SPIE 9645, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing XI, 96450G (20 October 2015); https://doi.org/10.1117/12.2195638

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KEYWORDS

LIDAR

Radiometry

Humidity

Atmospheric modeling

Microwave radiation

Calibration

Data modeling

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