Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basinReport as inadecuate




Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin - Download this document for free, or read online. Document in PDF available to download.

* Corresponding author 1 CEREA - Centre d-Enseignement et de Recherche en Environnement Atmosphérique 2 LSCE - Laboratoire des Sciences du Climat et de l-Environnement Gif-sur-Yvette 3 Clime - Coupling environmental data and simulation models for software integration Inria Paris-Rocquencourt 4 RSLab - Remote Sensing Laboratory Barcelona 5 Centre de Recerca de l-Aeronàutica i de l-Espai 6 IMAA-CNR - Istituto di Metodologie per l-Analisi Ambientale 7 LA - Laboratoire d-aérologie - LA 8 IISTA 9 Dpt. Applied Physics 10 LPCA - Laboratoire de Physico-Chimie de l-Atmosphère 11 National Institute of R&D for Optoelectronics 12 LaMP - Laboratoire de météorologie physique 13 CETEMPS 14 NTUA - Physics Department 15 Department of Environment, CIEMAT 16 University of Evora Departement of Geosciences and Geophysics Center of Evora

Abstract : This paper presents a new application of assim-ilating lidar signals to aerosol forecasting. It aims at in-vestigating the impact of a ground-based lidar network on the analysis and short-term forecasts of aerosols through a case study in the Mediterranean basin. To do so, we em-ploy a data assimilation DA algorithm based on the opti-mal interpolation method developed in the POLAIR3D chem-istry transport model CTM of the POLYPHEMUS air qual-ity modelling platform. We assimilate hourly averaged nor-malised range-corrected lidar signals PR 2 retrieved from a 72 h period of intensive and continuous measurements performed in July 2012 by ground-based lidar systems of the European Aerosol Research Lidar Network EAR-LINET integrated into the Aerosols, Clouds, and Trace Published by Copernicus Publications on behalf of the European Geosciences Union. 12032 Y. Wang et al.: Assimilation of lidar signals gases Research InfraStructure ACTRIS network and an ad-ditional system in Corsica deployed in the framework of the pre-ChArMEx Chemistry-Aerosol Mediterranean Ex-periment-TRAQA TRAnsport à longue distance et Qualité de l-Air campaign. This lidar campaign was dedicated to demonstrating the potential operationality of a research net-work like EARLINET and the potential usefulness of assim-ilation of lidar signals to aerosol forecasts. Particles with an aerodynamic diameter lower than 2.5 µm PM 2.5 and those with an aerodynamic diameter higher than 2.5 µm but lower than 10 µm PM 10−2.5 are analysed separately using the li-dar observations at each DA step. First, we study the spatial and temporal influences of the assimilation of lidar signals on aerosol forecasting. We conduct sensitivity studies on al-gorithmic parameters, e.g. the horizontal correlation length L h used in the background error covariance matrix 50 km, 100 km or 200 km, the altitudes at which DA is performed 0.75–3.5 km, 1.0–3.5 km or 1.5–3.5 km a.g.l. and the assim-ilation period length 12 h or 24 h. We find that DA with L h = 100 km and assimilation from 1.0 to 3.5 km a.g.l. dur-ing a 12 h assimilation period length leads to the best scores for PM 10 and PM 2.5 during the forecast period with refer-ence to available measurements from surface networks. Sec-ondly, the aerosol simulation results without and with lidar DA using the optimal parameters L h = 100 km, an assim-ilation altitude range from 1.0 to 3.5 km a.g.l. and a 12 h DA period are evaluated using the level 2.0 cloud-screened and quality-assured aerosol optical depth AOD data from AERONET, and mass concentration measurements PM 10 or PM 2.5 from the French air quality BDQA network and the EMEP-Spain-Portugal network. The results show that the simulation with DA leads to better scores than the one with-out DA for PM 2.5 , PM 10 and AOD. Additionally, the com-parison of model results to evaluation data indicates that the temporal impact of assimilating lidar signals is longer than 36 h after the assimilation period.





Author: Yiguo Wang - Karine Sartelet - Marc Bocquet - Patrick Chazette - Michaël Sicard - Giuseppe D-Amico - Jean-François Léon - Luca

Source: https://hal.archives-ouvertes.fr/



DOWNLOAD PDF




Related documents