首页|地基MAX-DOAS系统获取大气水汽垂直柱浓度方法研究

地基MAX-DOAS系统获取大气水汽垂直柱浓度方法研究

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水汽在大气水循环中起着重要的作用,决定全球的云分布,其浓度的变化影响降水发生频率.降水是影响气候和环境的重要因子,开展准确获取大气水汽浓度是环境气候研究中一个极其重要的课题.多轴差分吸收光谱技术(MAX-DOAS)是一种快速、准确获取大气痕量气体浓度的遥测方法.由于其稳定、实时在线、多组分同时监测和非接触测量等优势,该技术逐步成为反演大气水汽垂直柱浓度的新方法.针对水汽的吸收峰波段范围窄,浓度较高时会出现饱和吸收效应,构建了地基MAX-DOAS水汽垂直分布探测系统,开展了精确获取水汽垂直柱浓度的反演算法研究,并以淮北为研究地点获取了水汽垂直柱浓度.反演过程中,选取天顶方向采集的当圈太阳光谱作为参考谱,根据DOAS算法反演得到其他仰角水汽差分斜柱浓度(dSCD),最终解析出水汽的垂直柱浓度(VCD),其中大气质量因子(AMF)通过几何近似法获得.为了降低其他气体的干扰影响,实验前对比分析了不同波段反演水汽差分斜柱浓度的反演误差,确定最优反演波段433~452 nm.于2023年2月24日至2023年4月2日在淮北地区开展连续观测.实验结果表明:监测期间淮北地区水汽浓度具有早晚高中午低的V型日分布特征.将观测的水汽垂直柱浓度结果和欧洲中期天气预报中心(ECMWF)的ERA5再分析日值数据进行相关性分析,二者具有较好的一致性(R=0.95).分析监测期间风速、风向与H2O VCD分布关系,发现当风向在60.附近且风速小于5 m·s-1时,H2O VCD呈现升高的趋势.在污染阶段,小风速和较高水汽浓度是普遍存在的特征.研究表明,搭建的地基MAX-DOAS系统在蓝光波段可对水汽垂直柱浓度进行有效监测,为反演大气水汽垂直柱浓度提供了一种有效的技术手段.
Investigation of a Ground-Based MAX-DOAS System for Retrieving Vertical Column Density of Atmospheric Water Vapor
Water vapor is a key component of the atmospheric water cycle,influencing global cloud distribution and precipitation frequency.As precipitation significantly impacts climate and the environment,rapidly acquiring atmospheric water vapor concentration is critical in environmental climate research.The multi-axis differential optical absorption spectroscopy(MAX-DOAS)technique is a remote sensing method that enables fast and accurate measurement of trace gas concentrations in the atmosphere.Due to its stability,real-time online measurement,and multi-component and non-contact measurement advantages,this technique has become a promising new method for measuring atmospheric water vapor column concentration.Considering the narrow absorption band range of water vapor and the saturation absorption effect at high concentrations,this paper develops a MAX-DOAS water vapor vertical distribution detection system.It conducts an inversion algorithm study to retrieve the vertical column water vapor concentration accurately.The water vapor vertical column concentration was obtained at the study site in Huaibei.During the inversion process,the solar spectra collected in the zenith direction are chosen as the reference spectra.Using the Differential Optical Absorption Spectroscopy(DOAS)algorithm,the differential slant column densities(dSCD)of water vapor at different elevation angles are obtained.Finally,water vapor's vertical column density(VCD)is extracted.The air mass factor(AMF)was obtained through geometric approximation.To minimize the interference from other gases,we analyzed the inversion errors for different spectral bands before the experiment and determined the optimal inversion band to be 433~452 nm.Continuous observations were conducted in the Huaibei region from February 24,2023,to April 2,2023.The experimental results indicate that during the monitoring period,the water vapor concentration in the Huabei region exhibited a V-shaped diurnal distribution pattern,with higher concentrations in the morning and evening and lower concentrations around noon.A correlation analysis was performed between water vapor's observed vertical column density(VCD)and the daily reanalysis data from the European Centre for Medium-Range Weather Forecasts(ECMWF)ERA5.The results showed a good consistency between the two datasets(R=0.95).Furthermore,an analysis of the relationship between wind speed,wind direction,and H2O VCD distribution during the monitoring period revealed that when the wind direction was around 60° and the wind speed was less than 5 m·s-1,there was an increasing trend in H2O VCD.During the pollution stage,low wind speeds and higher water vapor concentrations were commonly observed features.The study demonstrated that the ground-based MAX-DOAS system effectively monitored water vapor vertical column concentration in the blue light band,providing an effective technical means for inverting atmospheric water vapor vertical column concentration.

MAX-DOASWater vaporVertical column concentrationOptimal retrieval wavelengthHuaibei region

周闯、张琦锦、李素文、雒静、牟福生

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污染物敏感材料与环境修复安徽省重点实验室,淮北师范大学,安徽淮北 235000

多轴差分吸收光谱技术 水汽 垂直柱浓度 最优反演波段 淮北地区

国家自然科学基金项目国家自然科学基金项目安徽省高等学校创新团队项目安徽省自然科学研究基金项目安徽省高校自然科学研究项目

41875040417050122023AH0100432208085QF2152023AH050338

2024

光谱学与光谱分析
中国光学学会

光谱学与光谱分析

CSTPCD北大核心
影响因子:0.897
ISSN:1000-0593
年,卷(期):2024.44(8)
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