气候变化领域集成服务门户(CCPortal): Linear correction method for improved atmospheric vertical profile retrieval based on ground-based microwave radiometer

CCPortal

DOI	10.1016/j.atmosres.2019.104678
	Linear correction method for improved atmospheric vertical profile retrieval based on ground-based microwave radiometer
	Zhao Y.; Yan H.; Wu P.; Zhou D.
发表日期	2020
ISSN	0169-8095
卷号	232
英文摘要	The back-propagation neural network (BPNN) is the most commonly used retrieval algorithm for microwave radiometers. Few researchers have attempted specifically to enhance training set quality, which markedly affects retrieval results and can minimize error and uncertainty in simulated brightness temperatures (BTs) in the BPNN. A local BPNN retrieval and correction method were established in this study using radiosonde data, BTs calculated from the radiosonde data, and a monochromatic radiative transfer model (February 2012 to August 2017) in Harbin. The correlation between simulated and observed BTs was improved after correction. The results were analyzed using three sets of comparisons before and after correction: (i) total root mean square errors and total mean absolute errors; (ii) root mean square errors and mean absolute errors in three layers; and (iii) root mean square errors and mean absolute errors under clear days and cloudy days. The results of this study contribute to the theoretical development of microwave remote sensing of atmospheric temperature and humidity. © 2019 Elsevier B.V.
英文关键词	Atmospheric profile retrieval; Brightness temperature correction; Linear regression; Vertical temperature; Water vapor profiles
学科领域	Atmospheric humidity; Backpropagation algorithms; Electromagnetic wave attenuation; Errors; Linear regression; Luminance; Mean square error; Microwave devices; Microwave measurement; Neural networks; Radiative transfer; Radiometers; Radiosondes; Remote sensing; Atmospheric profile retrieval; Back-propagation neural networks; Brightness temperatures; Microwave remote sensing; Temperature and humidities; Vertical profile retrieval; Vertical temperature; Water vapor profile; Atmospheric temperature; back propagation; brightness temperature; ground-based measurement; microwave radiometer; regression analysis; remote sensing; water vapor
语种	英语
scopus关键词	Atmospheric humidity; Backpropagation algorithms; Electromagnetic wave attenuation; Errors; Linear regression; Luminance; Mean square error; Microwave devices; Microwave measurement; Neural networks; Radiative transfer; Radiometers; Radiosondes; Remote sensing; Atmospheric profile retrieval; Back-propagation neural networks; Brightness temperatures; Microwave remote sensing; Temperature and humidities; Vertical profile retrieval; Vertical temperature; Water vapor profile; Atmospheric temperature; back propagation; brightness temperature; ground-based measurement; microwave radiometer; regression analysis; remote sensing; water vapor
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/120591
作者单位	College of Automation, Harbin Engineering University, Harbin, 150001, China; China Ship Development and Design Center, WuHan, 430064, China
推荐引用方式 GB/T 7714	Zhao Y.,Yan H.,Wu P.,et al. Linear correction method for improved atmospheric vertical profile retrieval based on ground-based microwave radiometer[J],2020,232.
APA	Zhao Y.,Yan H.,Wu P.,&Zhou D..(2020).Linear correction method for improved atmospheric vertical profile retrieval based on ground-based microwave radiometer.Atmospheric Research,232.
MLA	Zhao Y.,et al."Linear correction method for improved atmospheric vertical profile retrieval based on ground-based microwave radiometer".Atmospheric Research 232(2020).