%0 Book Section %1 Sica-2017-ilrc %A Sica, R J %A Haefele, A %A Jalali, A %A Mahagammulla Gamage, S %A Farhani, G %D 2017 %E Nicolae, D. %I EDP Sciences %K ilrc, lidar, pcl sica water-vapour, %T How to Apply the Optimal Estimation Method to your Lidar Measurements for Improved Retrievals of Temperature and Composition %X The optimal estimation method (OEM) has a long history of use in passive remote sensing, but has only recently been applied to active instruments like lidar. OEMs advantage over traditional techniques includes obtaining a full systematic and random uncertainty budget plus the ability to work with the raw measurement without first applying instrument corrections. We will show you how to use the OEM for temperature and composition retrievals for Rayleigh-scatter, Raman-scatter and DIAL lidars.

@incollection{Sica-2017-ilrc, abstract = {The optimal estimation method (OEM) has a long history of use in passive remote sensing, but has only recently been applied to active instruments like lidar. OEMs advantage over traditional techniques includes obtaining a full systematic and random uncertainty budget plus the ability to work with the raw measurement without first applying instrument corrections. We will show you how to use the OEM for temperature and composition retrievals for Rayleigh-scatter, Raman-scatter and DIAL lidars.}, added-at = {2019-04-05T21:27:46.000+0200}, author = {Sica, R J and Haefele, A and Jalali, A and Mahagammulla Gamage, S and Farhani, G}, biburl = {https://www.bibsonomy.org/bibtex/22f0e9949e328d0d56e7e2b4d13c24f2a/bobsica}, editor = {Nicolae, D.}, interhash = {db547bc8139d7e6fe78735be7fa4f7dd}, intrahash = {2f0e9949e328d0d56e7e2b4d13c24f2a}, keywords = {ilrc, lidar, pcl sica water-vapour,}, publisher = {EDP Sciences}, timestamp = {2019-04-05T21:27:46.000+0200}, title = {How to Apply the Optimal Estimation Method to your Lidar Measurements for Improved Retrievals of Temperature and Composition}, year = 2017 }