Chrome Extension
WeChat Mini Program
Use on ChatGLM

Water Vapor Line Profile at 183-Ghz: Temperature Dependence of Broadening, Shifting, and Speed-Dependent Shape Parameters

Journal of Quantitative Spectroscopy and Radiative Transfer(2021)SCI 3区

RAS | Univ Massachusetts Lowell | Inst Methodol Environm Anal | MIT

Cited 10|Views14
Abstract
The water vapor line at 183 GHz was studied over the temperature range of 219-358 K using a spectrometer with radioacoustic detection of absorption, providing a signal-to-noise ratio of up to 8000. The study includes the first measurement of speed-dependent collisional broadening and shifting of this line for both self- and air-broadening, and their temperature dependences. The sign of self-shifting changes at about 280 K. Line-shape parameters are obtained for Voigt and quadratic speed-dependent Voigt shape factors. Temperature dependences of the line parameters are analyzed using empirical models from the literature. Theoretical Modified Complex Robert-Bonamy calculations of the line shape parameters, their temperature and speed-dependence are made over the temperature range of 20 0-30 00 K. The measurements and calculations show very good agreement, although with some discrepancies for line shift parameters. The impact of the newly-measured line parameters on atmospheric water-vapor estimation from ground-based and satellite instruments is evaluated by simulation of downwelling and upwelling brightness temperatures and retrieved water-vapor mixing ratio, for atmospheric conditions typical of six climate zones. For the case of ground-based or limb-scanning radiometry with a background of cold space, the impact of speed-dependence is comparable to or exceeds that of measurement error and will introduce systematic errors if neglected. Therefore, consideration of speed-dependence is necessary for accurate estimation of water vapor with this line. The impact on upwelling brightness temperature is smaller. (C) 2020 Elsevier Ltd. All rights reserved.
More
Translated text
Key words
Microwave laboratory spectroscopy,Modified complex Robert-Bonamy calculations,Radiative transfer modeling,Speed-dependent profile,Water vapor,Line shape parameters
PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers

Russian Investigations in the Field of Atmospheric Radiation in 2019–2022

Известия Российской академии наук Физика атмосферы и океана 2023

被引用0

Temperature Dependence of Line Shape Parameters for N2- and O2-broadened Methane Lines by Quantum Cascade Laser Spectroscopy

B. Vispoel, T. Roland, O. Browet,M. Lepere
Journal of Quantitative Spectroscopy and Radiative Transfer 2024

被引用1

Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest