Atmospheric Measurement Techniques最新文献

{"title":"Simulation and detection efficiency analysis for measurements of polar mesospheric clouds using a spaceborne wide-field-of-view ultraviolet imager","authors":"Ke Ren, Haiyang Gao, Shuqi Niu, Shaoyang Sun, Leilei Kou, Yanqing Xie, Liguo Zhang, Lingbing Bu","doi":"10.5194/amt-17-4825-2024","DOIUrl":"https://doi.org/10.5194/amt-17-4825-2024","url":null,"abstract":"Abstract. The variation trends and characteristics of polar mesospheric clouds (PMCs) are important for studying the evolution of atmospheric systems and understanding various atmospheric dynamic processes. Through observation and analysis of PMCs, we can gain a comprehensive understanding of the mechanisms driving atmospheric processes, providing a scientific basis and support for addressing climate change. Ultraviolet (UV) imaging technology, adopted by the Cloud Imaging and Particle Size (CIPS) instrument on board the Aeronomy of Ice in the Mesosphere (AIM) satellite, has significantly advanced the research on PMCs. Due to the retirement of the AIM satellite, there is currently no concrete plan for next-generation instruments based on the CIPS model, resulting in a discontinuity in the observation data sequence. In this study, we propose a compact and cost-effective wide-field-of-view ultraviolet imager (WFUI) that can be integrated into various satellite platforms for future PMC observation missions. A forward model was built to evaluate the detection capability and efficiency of the WFUI. CIPS and Solar Occultation for Ice Experiment (SOFIE) data were fused to reconstruct a three-dimensional PMC scene as the input background. Based on the scattering and extinction characteristics of ice particles and atmospheric molecules, the radiative transfer was calculated using the solar radiation path through the atmosphere and PMCs. The optical system and satellite platform parameters of the WFUI were selected according to CIPS, enabling the calculation of the number of photons received by the WFUI. The actual detection signal is then simulated by photoelectric conversion, and the PMC information can be obtained by removing detector noise. Subsequently, a comparison with the input background field was conducted to compute and analyze the detection efficiency. Additionally, a sensitivity analysis of the instrument and platform parameters was conducted. Simulations were performed for both individual orbits and for the entire PMC seasons. The research results demonstrate that the WFUI performs well in PMC detection and has high detection efficiency. Statistical analysis of the detection efficiency using data from 2008 to 2012 revealed an exponential relationship between the ice water content (IWC) of PMCs and detection efficiency. During the initial and final durations of the PMC season, when the IWC was relatively low, the detection efficiency remained limited. However, as the season progressed and the IWC increased, the detection efficiency significantly improved. We note that regions at lower latitudes exhibited a lower IWC and, consequently, lower detection efficiency. In contrast, regions at higher latitudes, with a greater IWC, demonstrated better detection efficiency. Additionally, the sensitivity analysis results suggest that increasing the satellite orbit altitude and expanding the field of view (FOV) of the WFUI both contribute to improving the","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"24 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gridded surface O3, NOx, and CO abundances for model metrics from the South Korean ground station network","authors":"Calum Patrick Wilson, Michael John Prather","doi":"10.5194/egusphere-2024-1173","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1173","url":null,"abstract":"<strong>Abstract.</strong> We present gridded surface air quality datasets over South Korea for three key species – ozone (O₃), carbon monoxide (CO), and nitrogen oxides (NO_x) during the timeframe of the Korea–US Air Quality (KORUS–AQ) mission (May–June 2016). The tenth degree hourly averaged abundances are constructed from the 300+ air quality network sites using inverse distance weighting with simple declustering. Cross–comparing the interpolated fields against the site data that was used to create them reveals high prediction skill for O₃ (80 %) throughout South Korea, and moderate skill (60 %) for CO and NO_x on average in densely observed regions after individual mean bias corrections. The gridded O₃ and CO interpolations predict the NASA DC–8 observations in the planetary boundary layer (PBL) with high skill (80 %) in the Seoul Metropolitan Area (SMA) after subtracting the mean bias. DC–8 NO_x observations were much less predictable on account of consistently negative vertical gradients within the PBL. Our gridded products capture the mean and variability of O₃ throughout South Korea, and of CO and surface NO_x in most site–dense urban centres (SMA, Cheongju, Gwangju, Daegu, Changwon, and Busan).","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"13 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitigating Radome Induced Bias in X-Band Weather Radar Polarimetric moments using Adaptive DFT Algorithm","authors":"Thiruvengadam Padmanabhan, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, Joël Van Baelen","doi":"10.5194/amt-2024-117","DOIUrl":"https://doi.org/10.5194/amt-2024-117","url":null,"abstract":"<strong>Abstract.</strong> In recent years, the application of compact and cost-effective deployable X-band polarimetric radars has gained in popularity, particularly in regions with complex terrain. The deployable radars generally use a radome constructed by joining multiple panels using metallic threads to facilitate easy transportation. As a part of the ESPOIRS project, Laboratoire de l’Atmosphère et des Cyclones has acquired an X-band meteorological radar with four panel radome configuration. In this study, we investigated the effect of the radome on the measured polarimetric variables, particularly differential reflectivity and differential phase. Our observations reveal that the metallic threads connecting the radome panels introduce power loss at vertical polarization, leading to a positive bias in the differential reflectivity values. To address the spatial variability bias observed in differential reflectivity and differential phase, we have developed a novel algorithm based on the Discrete Fourier Transform. The algorithm's performance was tested during an intense heavy rainfall event caused by the Batsirai cyclone on Reunion Island. The comparative and joint histogram analysis demonstrates the algorithm's effectiveness in correcting the spatial bias in the polarimetric variables.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"101 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vertical profiles and surface distributions of trace gases (CO, O3, NO, NO2) in the Arctic wintertime boundary layer using low-cost sensors during ALPACA-2022","authors":"Brice Barret, Patrice Medina, Natalie Brett, Roman Pohorsky, Kathy Law, Slimane Bekki, Gilberto J. Fochesatto, Julia Schmale, Steve Arnold, Andrea Baccarini, Mauricio Busetto, Meeta Cesler-Maloney, Barbara D'Anna, Stefano Decesari, Jingqiu Maoe, Gianluca Pappaccogli, Joel Savarino, Federico Scoto, William R. Simpson","doi":"10.5194/egusphere-2024-2421","DOIUrl":"https://doi.org/10.5194/egusphere-2024-2421","url":null,"abstract":"<strong>Abstract.</strong> Electrochemical gas sensors (EGSs) have been used to measure the surface distributions and vertical profiles of trace gases in the wintertime Arctic Boundary Layer during the Alaskan Layered Pollution and Chemical Analysis (ALPACA) field experiment in Fairbanks, Alaska in January–February 2022. The MICRO sensors for MEasurements of GASes (MICROMEGAS) instrument set up with CO, NO, NO₂ and O₃EGSs was operated on the ground at an outdoor reference site downtown Fairbanks for calibration, onboard a vehicle moving through the city and its surroundings and onboard a tethered balloon, the Helikite, at a site at the edge of the city. To calibrate the measurements, a set of machine learning (ML) calibration methods were tested. For each method, learning and prediction were performed with coincident MICROMEGAS and reference analyser measurements at the downtown site. For CO, the calibration parameters provided by the manufacturer led to the best agreement between the EGS and the reference analyser and no ML method was needed for calibration. The correlation coefficient R is 0.82 and the slope of the linear regression between MICROMEGAS and reference data is 1.12. The mean bias is not significant but the Root Mean Square Error (290 ppbv) is rather large because of CO concentrations reaching several ppmv downtown Fairbanks. For NO, NO₂ and O₃, the best agreements for the prediction datasets were obtained with an artificial neural network, the Multi-Layer Perceptron. For these 3 gases, the correlation coefficients are higher than 0.95 and the slopes of linear regressions with the reference data are in the range 0.93–1.04. The mean biases which are 1±3 ppbv, 0±4 ppbv and 3±12 ppbv for NO₂, O₃ and NO respectively are not significant. Measurements from the car round of January 21 are presented to highlight the ability of MICROMEGAS to quantify the surface variability of the target trace gases in Fairbanks and the surrounding hills. MICROMEGAS flew 11 times from the ground up to a maximum of 350 m a.g.l. onboard the Helikite at the site at the edge of the city. The statistics performed over the Helikite MICROMEGAS dataset show that the median vertical gas profiles are characterised by almost constant mixing ratios. The median values over the vertical are 140, 8, 4 and 32 ppbv for CO, NO, NO₂ and O₃. Extreme values are detected with low O₃ and high NO₂ and NO concentrations between 100 and 150 m a.g.l. O₃ minimum levels (5^<em>th</em> percentile) of 5 ppbv coincident with NO₂ maximum levels (95^<em>th</em> percentile) of 40 ppbv occur around 200 m a.g.l. The peaks aloft are linked to pollution plumes originating from Fairbanks power plants such as documented with the flight of February 20.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"12 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Transfer Learning Method for Seasonal TROPOMI XCH4 Albedo Correction","authors":"Alexander C. Bradley, Barbara Dix, Fergus Mackenzie, J. Pepijn Veefkind, Joost A. de Gouw","doi":"10.5194/egusphere-2024-2352","DOIUrl":"https://doi.org/10.5194/egusphere-2024-2352","url":null,"abstract":"<strong>Abstract.</strong> The retrieval of methane from satellite measurements is sensitive to the reflectance of the surface. In many regions, especially those with agriculture, surface reflectance depends on season, but this is not accounted for in many satellite products. It is an important issue to consider, as agricultural emissions of methane are significant and other sources, like oil and gas production, are also often located in agricultural lands. In this work, we use a set of 12 monthly machine learning models to generate a seasonally resolved surface albedo correction for TROPOMI methane data across the Denver-Julesburg basin. We found that land cover is important in the correction, specifically the type of crops grown in an area, with drought-resistant crop covered areas requiring a correction of 5–6 ppb larger than areas covered in water-intensive crops. Additionally, the correction over different land covers changes significantly over the seasonally resolved timescale, with corrections over drought-resistant crops being up to 10 ppb larger in the summer than in the winter. This correction will allow for more accurate determination of methane emissions by removing the effect of agricultural and other seasonal effects on the albedo correction. The correction may also allow for the deconvolution of agricultural methane emissions, which are seasonally dependent, from oil and gas emissions, which are more constant in time.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"10 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developments on a 22GHz Microwave Radiometer and Reprocessing of 13-Year Time Series for Water Vapour Studies","authors":"Alistair Bell, Eric Sauvageat, Gunter Stober, Klemens Hocke, Axel Murk","doi":"10.5194/egusphere-2024-2474","DOIUrl":"https://doi.org/10.5194/egusphere-2024-2474","url":null,"abstract":"<strong>Abstract.</strong> Long-term observations of water vapour in the middle atmosphere are important for climate studies and predictions, chemical and dynamical process studies, as well as modelling certain weather events with implications for surface conditions. Measurements from an instrument making middle atmosphere water vapour observations near Bern, Switzerland- named MIAWARA- have been completely reprocessed since 2010. This has comprised of a new calibration which has been integrated into the framework for the calibration of other University of Bern radiometers, and a new retrieval algorithm. The installation of a new spectrometer on the instrument has also allowed the comparison and correction of past observations. We present these corrected measurements and their subsequent analysis against data from Aura MLS. The comparison shows that the corrected spectra yield more consistent values of water vapour mixing ratio between MIAWARA and Aura MLS, with a lower standard deviation of differences at all heights, and a reduced bias between the two instruments at pressure (height) levels below (above) 0.3 hPa.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"44 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new portable sampler of atmospheric methane for radiocarbon measurements","authors":"Giulia Zazzeri, Lukas Wacker, Negar Haghipour, Philip Gautchi, Thomas Laemmel, Sönke Szidat, Heather Graven","doi":"10.5194/amt-2024-123","DOIUrl":"https://doi.org/10.5194/amt-2024-123","url":null,"abstract":"<strong>Abstract.</strong> Radiocarbon (¹⁴C) is an optimal tracer of methane emissions, as ¹⁴C measurements enable distinguishing fossil from biogenic methane (CH₄). However, ¹⁴C measurements in atmospheric methane are still rare, mainly because of the technical challenge of collecting enough carbon for ¹⁴C analysis from ambient air samples. In this study we address this challenge by advancing the system in Zazzeri et al. (2021) into a much more compact and portable sampler, and by coupling the sampler with the MICADAS AMS system at ETH, Zurich, using a gas interface. Here we present the new sampler setup, the assessment of the system contamination and a first inter-laboratory comparison with the LARA AMS laboratory at the University of Bern. With our sampling line we achieved a very low blank, 0.7 µgC compared to 5.5 µgC in Zazzeri et al. (2021), and a sample precision of 0.9 %, comparable with other measurements techniques for ¹⁴CH₄, while reducing the sample size to 60 liters of air. We show that this technique, with further improvements, will enable routine ¹⁴CH₄ measurements in the field for an improved understanding of CH₄ sources.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"14 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Number- and size-controlled rainfall regimes in the Netherlands: physical reality or statistical mirage?","authors":"Marc Schleiss","doi":"10.5194/amt-17-4789-2024","DOIUrl":"https://doi.org/10.5194/amt-17-4789-2024","url":null,"abstract":"Abstract. An experimental study aimed at identifying special rainfall regimes with the help of co-located disdrometers is performed. Eight potentially special events (i.e., four number-controlled events and four size-controlled events) are identified and examined. However, a detailed cross-check with additional, independent radar measurements reveals no clear evidence of special rainfall dynamics. The research underscores the difficulty of experimentally confirming seemingly straightforward questions about rainfall patterns and dynamics that have been theorized in the literature for several decades but never formally validated experimentally. The study also questions the reliability of previous claims and serves as a reminder to approach such problems with more caution, emphasizing the need for rigorous uncertainty analysis and multiple cross-checks between sensors to avoid misinterpretation.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"18 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) – Part 1: Instrument description and level 1 radiances","authors":"Jonathan E. Murray, Laura Warwick, Helen Brindley, Alan Last, Patrick Quigley, Andy Rochester, Alexander Dewar, Daniel Cummins","doi":"10.5194/amt-17-4757-2024","DOIUrl":"https://doi.org/10.5194/amt-17-4757-2024","url":null,"abstract":"Abstract. The Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) instrument combines a commercial Bruker EM27 spectrometer with a front-end viewing and calibration rig developed at Imperial College London. FINESSE is specifically designed to enable accurate measurements of surface emissivity, covering the range 400–1600 cm−1, and, as part of this remit, can obtain views over the full 360° angular range. In this part, Part 1, we describe the system configuration, outlining the instrument spectral characteristics, our data acquisition methodology, and the calibration strategy. As part of the process, we evaluate the stability of the system, including the impact of knowledge of blackbody (BB) target emissivity and temperature. We also establish a numerical description of the instrument line shape (ILS), which shows strong frequency-dependent asymmetry. We demonstrate why it is important to account for these effects by assessing their impact on the overall uncertainty budget on the level 1 radiance products from FINESSE. Initial comparisons of observed spectra with simulations show encouraging performance given the uncertainty budget.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"73 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) – Part 2: First measurements of the emissivity of water in the far-infrared","authors":"Laura Warwick, Jonathan E. Murray, Helen Brindley","doi":"10.5194/amt-17-4777-2024","DOIUrl":"https://doi.org/10.5194/amt-17-4777-2024","url":null,"abstract":"Abstract. In this paper, we describe a method for retrieving the surface emissivity of specular surfaces across the wavenumber range of 400–1600 cm−1 using novel radiance measurements of the Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) instrument. FINESSE is described in detail in Part 1 (Murray et al., 2024) of this paper. We apply the method to two sets of measurements of distilled water. The first set of emissivity retrievals is of distilled water heated above ambient temperature to enhance the signal-to-noise ratio. The second set of emissivity retrievals is of ambient temperate water at a range of viewing angles. In both cases, the observations agree well with calculations based on compiled refractive indices across the mid- and far-infrared. It is found that the reduced contrast between the up- and downwelling radiation in the ambient temperature case degrades the performance of the retrieval. Therefore, a filter is developed to target regions of high contrast, which improves the agreement between the ambient temperature emissivity retrieval and the predicted emissivity. These retrievals are, to the best of our knowledge, the first published simultaneous retrievals of the surface temperature and emissivity of water that extend into the far-infrared and demonstrate a method that can be used and further developed for the in situ retrieval of the emissivity of other surfaces in the field.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"32 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}