Ground-based Temperature and Humidity Profile Retrieval Using Infrared Hyperspectrum Based on Adaptive Fast Iterative Algorithm
Abstract. Due to the complex radiative transfer process, the retrieval time of the physical retrieval algorithm is significantly increased compared with that of the statistical retrieval algorithm. The calculation of the Jacobian matrix is the most computationally intensive part of the physical retrieval algorithm. Further analysis showed that the changes in Jacobians had little effect on the performance of the physical retrieval algorithm. On the basis of the above findings, a fast physical-iterative retrieval algorithm was proposed by adaptively updating the Jacobian in keeping with the changes of the atmospheric state. The performance of the algorithm is evaluated using synthetic ground-based infrared spectra observations. The retrieval speed is significantly improved compared with the traditional physical retrieval algorithm under the condition that the parameters of the computing platform remain unchanged, with the average retrieval time reduced from 8.96 min to 3.69 min. The retrieval accuracy of the fast retrieval model is equivalent to that of the traditional algorithm, with maximum root-mean-square errors of less than 1.2 K and 1.0 g/kg for heights below 3 km for the temperature and water vapor mixing ratio (WVMR), respectively. The Jacobian updating strategy has a certain impact on the convergence of the retrieval algorithm, whose convergence rate is 98.7 %, which is lower than that of the traditional algorithm to some extent. However, reliable retrieval results can still be obtained by adjusting the convergence criteria.
Wei Huang et al.
Status: open (until 16 Jun 2023)
- RC1: 'Comment on egusphere-2023-637', Anonymous Referee #1, 31 May 2023 reply
Wei Huang et al.
Wei Huang et al.
Viewed (geographical distribution)
It has been well recognized that a significant drawback of the optimal estimation method is that a high retrieval time is required, especially for the high-resolution spectrometers. The manuscript “Ground-based Temperature and Humidity Profile Retrieval Using Infrared Hyperspectrum Based on Adaptive Fast Iterative Algorithm” proposes a new method to improve the retrieval speed of the optimal estimation algorithm for retrieving temperature and water vapor profiles from AERI data. I would like to remark the good experimental design to fully evaluate the fast retrieval algorithm, which is important to justify the superiority of the proposed method. The manuscript is well organized and figures are presented in a concise manner and easy to follow. It is interesting and well suited to the audience of the journal and worth being published after a minor revision. The specific comments are as follows:
For the title, may be “Ground-based infrared hyperspectral retrievals of temperature and humidity profile based on Adaptive Fast Iterative Algorithm” is better.
Line10: “due to” is usually not placed at the beginning of a sentence
Line12: “part” -> “step”
Line15: “is” -> “was”
Line17: suggest revising to “resulting in an average retrieval time reduction from 8.96 min to 3.69 min” instead of “with the average retrieval time reduced from 8.96 min to 3.69 min”
Line41: “FTIR” -> “The FTIR instrument”
Line45: “which is more advantageous” can be revised to “which makes it more advantageous”
Line57: this sentence should be reworked