Robust algorithm for precise X<sub>CO2</sub> retrieval using single observation of IPDA LIDAR
Hongyuan Zhang, Ge Han, Xin Ma, Weibiao Chen, Xingying Zhang, Jiqiao Liu, Wei Gong
Abstract
CO 2 column-weighted dry-air mixing ratio ( X CO 2 ) products with high precision and spatial resolution are essential for inverting CO 2 fluxes and promoting our understanding of global climate change. Compared with passive remote sensing methods, IPDA LIDAR, as an active remote sensing technique, offers many advantages in measuring X CO 2 . However, a significant random error in IPDA LIDAR measurements causes X CO 2 values calculated directly from LIDAR signals to be unqualified as the final X CO 2 products. Hence, we propose an efficient particle filter-based inversion of CO 2 for single observation (EPICSO) algorithm to precisely retrieve the X CO 2 of every LIDAR observation while preserving the high spatial resolution of LIDAR measurements. The EPICSO algorithm adopts the sliding average results as the first estimate of the local X CO 2 ; subsequently, it estimates the difference between two adjacent X CO 2 points and calculates the posterior probability of X CO 2 based on particle filter theory. To evaluate the performance of the EPICSO algorithm numerically, we perform an EPICSO to process pseudo-observation data. The simulation results show that the results retrieved by the EPICSO algorithm satisfy the required high precision and that the algorithm is robust to a significant amount of random errors. In addition, we utilize LIDAR observation data from actual experiments in Hebei, China, to validate the performance of the EPICSO algorithm. The results retrieved by the EPICSO algorithm are more consistent with the actual local X CO 2 than those of the conventional method, indicating that the EPICSO algorithm is efficient and practical for retrieving X CO 2 with high precision and spatial resolution.