Collaborative development of the Lidar Processing Pipeline (LPP)

Abstract

Lidars can simultaneously measure clouds and aerosols with high temporal and spatial resolution and, therefore, help improve the understanding of their interactions, which are among the largest sources of uncertainty in current climate projections. However, lidars are typically custom-built, resulting in significant differences between systems. In this context, lidar networks play a crucial role by coordinating the efforts of different groups and providing guidelines for quality-assured routine measurements aimed at harmonizing physical retrievals. With this objective, this work describes an ongoing collaborative effort to develop a Lidar Processing Pipeline (LPP). The LPP is a collection of tools developed in C/C++, Python, and Linux scripts that handle all stages of a typical lidar analysis. The first publicly released version of the LPP produces data files at Level 0 (raw data and metadata), Level 1 (signal averaging and layer masking), and Level 2 (aerosol optical properties). We discuss the application of the LPP in two case studies, conducted in São Paulo and the Amazon, which demonstrate the capabilities of the current release while also highlighting the need for additional features. Based on these applications, we developed and present a roadmap to guide future development and accommodate the evolving needs of the lidar research community.