16 - 19 September 2024
Edinburgh, United Kingdom

This conference focuses on methods, underlying technologies, and applications of remote sensing of clouds and Earth and planetary atmospheres, including the following topics:

Remote sensing, including profiling, of clouds, atmospheric aerosols, trace gases and meteorological parameters: Radiative Transfer: Lidar, Radar, and Other Active and Passive (Microwave, Infrared, Visible and Ultraviolet) Atmospheric Measurement Techniques and Technologies: Applications and Sustainability ;
In progress – view active session
Conference 13193

Remote Sensing of Clouds and the Atmosphere XXIX

17 September 2024
View Session ∨
  • 1: Remote Sensing of Clouds, Aerosols, Trace Gases and Meteorological Parameters I
  • 2: Remote Sensing of Clouds, Aerosols, Trace Gases and Meteorological Parameters II
  • 3: Technologies, Techniques and Algorithms for Active and Passive Remote Sensing I
  • 4: Technologies, Techniques and Algorithms for Active and Passive Remote Sensing II
  • Posters-Tuesday
Session 1: Remote Sensing of Clouds, Aerosols, Trace Gases and Meteorological Parameters I
17 September 2024 • 08:40 - 10:20 BST
Session Chair: Simone Lolli, Istituto di Metodologie per l'Analisi Ambientale (Italy)
13193-1
Author(s): Tiziano Maestri, Michele Martinazzo, Fabrizio Masin, Giorgia Proietti Pelliccia, Univ. degli Studi di Bologna (Italy); Federico Donat, Univ. degli Studi della Basilicata (Italy); Lorenzo Cassini, Univ. degli Studi della Basilicata (Italy), Sapienza Univ. di Roma (Italy); Guido Masiello, Giuliano Liuzzi, Carmine Serio, Univ. degli Studi della Basilicata (Italy)
17 September 2024 • 08:40 - 09:00 BST
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The Cloud Identification and Classification (CIC) algorithm for the analysis of far and mid infrared spectral radiance is described. CIC has been recently improved to enhance the sensitivity to thin clouds (and aerosols) and to increase the cloud hit rates in very challenging conditions such those characterizing the polar regions. The new metric is here introduced. The presentation will show some examples of CIC application to scene classification of real data and the algorithm potentialities when applied to both satellite and ground-based observations. Finally, it is discusssed a strategy describing a possible operational exploitation of CIC for the analysis of the future Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) measurements. The presentation delves into the issues related to the definition of the reference training sets, the characterization of the classification error and the foreseen CIC-FORUM performances in detecting thin cirrus clouds at different latitudes and seasons.
13193-2
Author(s): Guido Masiello, Carmine Serio, Giuliano Liuzzi, Pamela Pasquariello, Rocco Giosa, Univ. degli Studi della Basilicata (Italy); Tiziano Maestri, Michele Martinazzo, Fabrizio Masin, Univ. degli Studi di Bologna (Italy); Lorenzo Cassini, Sapienza Univ. di Roma (Italy), Univ. degli Studi della Basilicata (Italy); Federico Donat, Univ. degli Studi della Basilicata (Italy), Univ. degli Studi di Bologna (Italy); Giorgia Proietti Pelliccia, Univ. degli Studi di Bologna (Italy); Sara Venafra, Agenzia Spaziale Italiana (Italy); Luca Sgheri, Francesco De Cosmo, Istituto per le Applicazioni del Calcolo "Mauro Picone", CNR (Italy)
17 September 2024 • 09:00 - 09:20 BST
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The new σ-IASI/F2N radiative transfer model is an advancement of the σ-IASI model, introduced in 2002. It enables rapid simulations of Earth-emitted radiance and Jacobians under various sky conditions and geometries, covering the spectral range of 3-100 μm. Successfully utilized in δ-IASI, the advanced Optimal Estimation tool tailored for the IASI MetOp interferometer, its extension to the Far Infrared (FIR) holds significance for the ESA Earth Explorer FORUM mission, necessitating precise cloud radiative effect treatment, crucial in regions with dense clouds and temperature gradients. The model's update, incorporating the "linear-in-T" correction, addresses these challenges, complementing the "linear-in-tau" approach. Demonstrations highlight its effectiveness in simulating cloud complexities, with the integration of the "linear-in-T" and Tang correction for the computation of cloud radiative effects. The results presented will show that the updated σ-IASI/F2N can treat the overall complexity of clouds effectively and completely, at the same time minimizing biases.
13193-3
Author(s): Michele Martinazzo, Tiziano Maestri, Univ. degli Studi di Bologna (Italy)
17 September 2024 • 09:20 - 09:40 BST
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A methodology (named MAMA) for the fast computation of spectrally resolved upwelling radiances in the presence of atmospheric diffusive layers is presented. The algorithm is developed as a new analysis tool for application to interferometric data for the study of the atmospheric components. MAMA offers fast and accurate radiance simulations of the Earth's entire longwave emission spectrum, particularly excelling in scenarios involving optically thin scattering layers like cirrus clouds or aerosols. The solution is obtained through a simplification of the multiple scattering term in the general equation of the radiative transfer in plane parallel assumption. To assess the algorithm performances, results obtained with the MAMA code are compared with those derived with a discrete-ordinate based radiative transfer model (DISORT) for a large range of physical and optical properties of ice and liquid water clouds and for multiple atmospheric conditions. Additionally, we discuss the algorithm's effectiveness in simulating a set of ECMWF analyses on a global scale, comparing the MAMA forward solutions to Infrared Atmospheric Sounding Interferometer (IASI) observations.
13193-4
Author(s): Andreu Salcedo-Bosch, Simone Lolli, Istituto di Metodologie per l'Analisi Ambientale (Italy); Zong Lian, Shiyu Chen, Yuanjing Yang, Nanjing Univ. of Information Science & Technology (China)
17 September 2024 • 09:40 - 10:00 BST
13193-5
Author(s): Xu Liu, NASA Langley Research Ctr. (United States)
17 September 2024 • 10:00 - 10:20 BST
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Efficient radiative Transfer Models (forward models) and Retrieval algorithms (inverse model)s for hyperspectral satellite remote sensors are needed due to large number of spectral channels and millions of observations each day. In this presentation, we describe how to use Principal Component Analysis (PCA) to speed up radiative transfer forward model calculations and to numerically stabilize the inversion algorithms. We have developed a Principal Component-based radiative transfer model (PCRTM) which can simulate top of atmosphere (TOA) radiance or reflectance spectra from 50 to 40,000 wavenumber (200 to 0.25 micrometer) quickly and accurately. It has demonstrated very good accuracy relative to reference line-by-line radiative transfer models and saves orders of magnitude in computational time. We will show examples of the PCRTM model and retrieval alglrithms developed for and applied to hyperspectral sensors such as AIRS, CrIS, IASI,CPF, TEMPO, EMIS, SBG, OMI, and SCIAMACHY.
Break
Coffee Break 10:20 AM - 10:50 AM
Session 2: Remote Sensing of Clouds, Aerosols, Trace Gases and Meteorological Parameters II
17 September 2024 • 10:50 - 12:10 BST
Session Chair: Simone Lolli, Istituto di Metodologie per l'Analisi Ambientale (Italy)
13193-6
Author(s): Pamela Pasquariello, Guido Masiello, Carmine Serio, Vito Telesca, Giuliano Liuzzi, Marco D'Emilio, Rocco Giosa, Univ. degli Studi della Basilicata (Italy); Sara Venafra, Agenzia Spaziale Italiana (Italy); Italia De Feis, Istituto per le Applicazioni del Calcolo "Mauro Picone" (Italy); Fabio Della Rocca, Univ. degli Studi di Napoli Federico II (Italy)
17 September 2024 • 10:50 - 11:10 BST
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The Mediterranean basin faces severe consequences of climate change, with regions experiencing droughts and water deficits due to intense summer heatwaves. Monitoring these phenomena is crucial for understanding their evolution and mitigation strategies. Parameters like emissivity, surface and dew point temperature help identify water presence and loss. This study, conducted in Southern Italy (2014-2023), utilized satellite data to estimate Water Deficit and Emissivity Contrast Indices, providing monthly averages. Validation with in situ measurements was conducted to better understand heatwave-induced drought impacts on various land covers.
13193-7
Author(s): Fabio Della Rocca, Univ. degli Studi di Napoli Federico II (Italy); Italia De Feis, Istituto per le Applicazioni del Calcolo "Mauro Picone" (Italy); Guido Masiello, Carmine Serio, Pamela Pasquariello, Univ. degli Studi della Basilicata (Italy)
17 September 2024 • 11:10 - 11:30 BST
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Climate change has increased the frequency of droughts, impacting countries that never experienced them. Assessing drought events is crucial, and satellite data can provide significant assistance due to its large spatial coverage and continuous data supply. A new Water Deficit Index (wdi) was developed based on the Infrared Atmospheric Sounder Interferometer (IASI), demonstrating effectiveness in detecting droughts. However, infrared sensors like IASI cannot penetrate thick cloud cover, leading to sparse and uneven data distribution across regions. To address this, we tested two machine learning algorithms (gradient boosting and random forest) to convert scattered IASI L2 data into a regular L3 grid. Specifically, we trained a model that can predict the wdi index over a 0.05° regular grid, using data from other sensors together with vegetational products, soil indexes, and territorial and geographic information as covariates. We applied the methodology over the Po Valley region, which experienced intense droughts in the last three years. Overall, we found that these methods can yield good results and allow simultaneous regular grid conversion and downscaling.
13193-8
Author(s): Carmine Serio, Guido Masiello, Giuliano Liuzzi, Pamela Pasquariello, Univ. degli Studi della Basilicata (Italy)
17 September 2024 • 11:30 - 11:50 BST
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Nitric acid is a key gas for understanding the processes leading to ozone depletion in Antarctica. The Antarctica ozone hole is a cyclic phenomenon that begins in early September when the region exits the polar night and fully develops in October-November. Nitric acid is the primary constituent of stratospheric aerosol. In the Antarctic region, when the temperature gets below 195 K, it condenses from the gas phase to NAT or nitric acid thryidate (HNO3·3H2O) in the form of ice crystals. Recently, we have developed a new forward/inverse model capable of computing the top-of-atmosphere infrared spectral radiance in all-sky conditions (clear/cloudy, day/night) and surface type (land or ocean). The new forward/inverse system has been applied to IASI (infrared Atmospheric Sounder interferometer) to retrieve O3 and HNO3 simultaneously. We have analyzed data for the years 2021 and 2023, and HNO3 total column retrievals have been compared to those observed with the MLS (Microwave Limb Sounder) instrument to check the capability of IASI to estimate HNO3 and its yearly cycle. The paper also addresses the relationship between HNO3 and O3, especially at the onset of the ozone hole in the early
13193-9
Author(s): Shen-En Qian, Stephane Routhier, Tongxi Wu, Canadian Space Agency (Canada); Ray Nassar, Chris Sioris, Joseph Mendonca, Environment and Climate Change Canada (Canada)
17 September 2024 • 11:50 - 12:10 BST
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Canadian Space Agency (CSA) is studying the concept of its Arctic Observing Mission that would use two satellites in a Highly Elliptical Orbit to make geostationary-like observations of greenhouse gases (GHGs), air quality species of interest, meteorology, and space weather over northern regions. An imaging Fourier transform spectrometer (iFTS) will be used for the GHGs observation. Funded by CSA, Canadian industry and academia have built an iFTS instrument suitable for sub-orbit demonstration and flew it on a stratospheric balloon and processed the acquired FTS image data to demonstrate its ability to measure CO2 & CH4 over the boreal forest from an altitude of 37 km.
Break
Lunch/Exhibition Break 12:10 PM - 1:20 PM
Session 3: Technologies, Techniques and Algorithms for Active and Passive Remote Sensing I
17 September 2024 • 13:20 - 15:00 BST
Session Chair: Evgueni I. Kassianov, Pacific Northwest National Lab. (United States)
13193-10
Author(s): Sonoyo Mukai, The Kyoto College of Graduate Studies for Informatics (Japan); Makiko Nakata, Kindai Univ. (Japan); Souichiro Hioki, Univ. de Lille (France), CNRS (France); Takuya Funatomi, Nara Institute of Scienece and Technology (Japan); Masatugu Kidode, Advanced Telecommunications Research Institute International (Japan)
17 September 2024 • 13:20 - 13:40 BST
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This work intends to demonstrate the simultaneous polarized and un-polarized multi-spectral observations of the SGLI is useful to estimate the vertical information of biomass-burning aerosols (BBAs). The vertical profiles of black carbon (BC) concentration simulated by the chemical transport model (CTM) are also useful for altitude information of BBAs. Comparing the satellite image from SGLI observation with BC distribution from CTM simulations, the radiance and the polarized radiance images are similar to the BC distributions from the entire atmosphere and the upper part atmosphere, respectively. The similarity of these image patterns can be quantitatively demonstrated from pattern matching method. Furthermore, radiative transfer simulations in the atmosphere model show that polarization information strongly reflects the upper atmospheric conditions.
13193-11
Author(s): Souichiro Hioki, Univ. de Lille (France); Takuya Funatomi, Nara Institute of Science and Technology (Japan); Makiko Nakata, Kindai Univ. (Japan); Sonoyo Mukai, The Kyoto College of Graduate Studies for Informatics (Japan); Masatsugu Kidode, Nara Institute of Science and Technology (Japan)
17 September 2024 • 13:40 - 14:00 BST
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This presentation showcases case studies of biomass burning aerosol and volcanic ash plume height estimation from the measurements by the Second-generation global imager (SGLI) instrument. The stereoscopic method is well suited to the height estimation of explosive aerosol emission events as it does not depend on the prior knowledge of atmospheric vertical structure. To adapt the conventional approach with a particular focus on the plume height estimation from the SGLI data, we applied the plume screening and explicit handling of 3-D coordinates.
13193-12
Author(s): Manuela Hoyos Restrepo, Romain Ceolato, ONERA (France); Yoshitaka Jin, National Institute for Environmental Studies (Japan)
17 September 2024 • 14:00 - 14:20 BST
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Atmospheric High Spectral Resolution Lidars (HSRLs) are unable to perform measurements close to emission source because, apart from being blind in the first hundredths of meters (overlap problem), their spatiotemporal resolution is insufficient since they use ultranarrow band (and thus long-pulse) lasers. In this work, we present the proof-of-concept of a compact short-range HSRL (SR-HSRL), closing the gap of aerosol characterization in the short-range. Through a numerical model-based design, the system was optimized, finding the right balance between spectral performance and range resolution. Then, the SR-HSRL concept was tested measuring calibrated particles under controlled conditions. We demonstrate that is it feasible to measure calibrated aerosol backscatter and extinction profiles near to the source without doing assumptions.
13193-13
Author(s): Tatsuo Shiina, Chiba Univ. (Japan); Yasuyuki Kawakami, Takumi Ikeda, Kunihiko Katano, Yuta Yamaguchi, Stanley Electric Co., Ltd. (Japan)
17 September 2024 • 14:20 - 14:40 BST
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Surface atmosphere has the small and steep spatiotemporal dynamics. It is influenced by the ground / sea-surface conditions, their up and down, air current, and so on. It greatly affects to the human living space. 265nm LED mini-lidar is developed to observe the surface atmosphere. As the transmitting light is in solar blind region, it can monitor near-range atmosphere up to 100m in daytime with the same signal-to-noise ratio in nighttime. The lidar echo detection was evaluated under the solar illumination. It is confirmed that the enough signal-to-noise ratio is obtained in daytime, which is matched with the theoretical estimation. The surface atmosphere observation is simulated with the artificial fog / rain facility “Light Tunnel”. Fog flow and rainfall were visualized and analyzed with time series lidar echoes. We will propose the easy-to-use method for dynamics monitoring of surface atmosphere.
13193-14
Author(s): Chao Wang, Shun Yao, DFH Satellite Co. Ltd. (China); Cheng Fan, Ying Zhang, Aerospace Information Research Institute (China); Jun Zhu, DFH Satellite Co. Ltd. (China)
17 September 2024 • 14:40 - 15:00 BST
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The High Dynamic Point Source Carbon Emitting Monitoring Satellite will be China's first 100-meter greenhouse gas emission monitoring satellite. The satellite will be launched in piggyback mode and is suitable for low inclination or polar orbits. It weighs less than 300kg and is equipped with a hyperspectral imager with a spatial resolution of 100m and a width of 30 km. This allows high precision inversion of XCO2 and XCH4 for point source targets, as well as the provision of emission plume and emission flux products.
Break
Coffee Break 3:00 PM - 3:30 PM
Session 4: Technologies, Techniques and Algorithms for Active and Passive Remote Sensing II
17 September 2024 • 15:30 - 17:30 BST
Session Chair: Evgueni I. Kassianov, Pacific Northwest National Lab. (United States)
13193-15
Author(s): Cameron Martus, Brian Johnson, Patrick D. Johnson, David I. Moyer, Joel Thomas, The Aerospace Corp. (United States)
17 September 2024 • 15:30 - 15:50 BST
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Sensor performance plays a central role in the quality of weather data products produced by weather satellite observing systems. Next generation sensors harness commercial technologies and small satellite architectures that may include fewer spectral bands. The Weather Remote Sensing Systems Office (WRSSO) at The Aerospace Corporation is developing an end-to-end modeling and simulation testbed for performance analysis using CLAVR-x, a cloud detection algorithm made available by the Cooperative Institute of Meteorological Satellite Studies (CIMSS) at the University of Wisconsin. The current version of the testbed is being developed specifically for the U.S. Space Force’s EO/IR Weather System (EWS) mission to fill two top priority observational needs: cloud characterization and theater weather imagery. Orion Space Solutions’ Rapid Revisit Optical Cloud Imager (RROCI) is a next generation CubeSat approach to weather monitoring using 8 spectral bands corresponding to equivalent MODIS bands. We present simulations of RROCI sensor performance based on MODIS data, including the sensitivity of cloud products to sensor errors.
13193-16
Author(s): Cameron Martus, Brian Johnson, Andrew Z. Brethorst, Cliff Chan, Eric Wendoloski, The Aerospace Corp. (United States)
17 September 2024 • 15:50 - 16:10 BST
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Traditional cloud detection algorithms for weather monitoring require radiometrically calibrated multispectral visible and infrared (IR) sensors such as those on dedicated weather satellites. In contrast, deep learning methods facilitate the use of proliferated earth observing constellations with uncalibrated sensors and fewer spectral bands for weather applications. This capability detects clouds and classifies types by recognizing spatial and spectral features using a deep neural network. In this study, we leverage existing U-Net architectures and train on several different satellite datasets. Following model development, we compare several ways to segment clouds in remote sensing images, including the number of spectral bands and separation of thin and thick clouds. The separation of thin and thick clouds is a first step in segmenting clouds by type. The capability developed in this work will facilitate the exploitation of rapidly growing data sources from the expanding market of proliferated commercial remote sensing systems.
13193-17
Author(s): Evgueni I. Kassianov, Pacific Northwest National Lab. (United States); Connor Flynn, The Univ. of Oklahoma (United States); James Barnard, Brian Ermold, Erol Cromwell, John E. Shilling, Jennifer M. Comstock, Pacific Northwest National Lab. (United States)
17 September 2024 • 16:10 - 16:30 BST
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Airborne and satellite observations have successfully extracted a wealth of information about clouds, aerosols, and the Earth’s surface. These observations can be significantly complemented by the long-term ground-based radiation data provided by the Multi-Filter Rotating Shadowband Radiometers (MFRSRs) supported by the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) Program. Until recently, ARM-supported MFRSRs measured total irradiance and its direct and diffuse components at six wavelengths (415, 500, 615, 675, 870, and 940 nm). The limited number of wavelengths and the narrow spectral range of these MFRSRs prevent improved retrievals of aerosol, cloud, and surface characteristics. For example, spectrally resolved aerosol optical depth derived from the direct irradiance measured across a wide spectral range offer a valuable avenue for improved estimations of aerosol size distributions, especially for large particles. To address these limitations, ARM has supported the development of two successors to the MFRSR. The first, the MFRSR-7nch, includes a seventh narrowband channel at a 1625 nm wavelength, while the second, the Shortwave Array Spectroradiometer-Hemispheric (SAS-He), features increased spectral coverage (350-1700 nm) and hyperspectral capabilities. The performance of these successors is thoroughly evaluated under a wide range of atmospheric conditions, including different aerosol and cloud types and significant variability in aerosol loading. Our presentation will highlight the design, evaluation, and anticipated applications of these advanced radiometers.
13193-18
Author(s): Rajasri Sen Jaiswal, Sona College of Technology (India)
17 September 2024 • 16:30 - 16:50 BST
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In this paper, the authors attempt in particular, to find functional relations between surface rainfall and CLW, PW, and LH at the TRMM vertical profiling levels. The investigation shows strong correlations between rainfall and each of these parameters and as a combination of all these. The study indicates that the functional relation at the closest TRMM profiling level to the Earth at 0-0.5 km (and at all levels), is able to estimate rainfall with a very good accuracy. So, the authors suggest designing and installing an instrument at say, 0.5 km, to measure the PW/CLW/ LH or all of the three parameters. This will estimate rainfall with an excellent accuracy. Alternatively, the authors feel the need of establishing functional relations between the surface parameters say, surface pressure (SP), surface temperature (ST), and relative humidity (RH) and the upper-air parameters, viz. CLW, PW, and LH. Such relations will help estimating rainfall at any location, in two steps- first estimating the upper- air parameters from the surface parameters and then surface rainfall from the latter.
13193-19
Author(s): Xiaoyu He, Beihang Univ. (China); Ouning Zhu, The System Design Institute of Mechanical (China); Mengfan Zou, Shaoping Shuai, Xiaojian Xu, Beihang Univ. (China)
17 September 2024 • 16:50 - 17:10 BST
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A cloud detection scheme based on the similarity analysis of the measured and the simulated radiant images was proposed in this paper. A set of data measured by the FY-4B satellite was used as the example to demonstrate the usefulness of the scheme. The geometry of the observational scene and the performance of the FY-4B sensor were analyzed to characterize the necessary parameters for the physically-based simulation model. The simulated radiant images were generated using the typical atmospheric parameters for the spectral bands NO. 5 and NO. 7 of the FY-4B. The SSIM images of the measured and simulated images are calculated to separate the cloudy and the clear sky pixels.
13193-20
Author(s): Mengfan Zou, Beihang Univ. (China); Jianhua Li, National Key Lab. of Science and Technology on Space Microwave Technology (China); Xiaojian Xu, Xiaoyu He, Beihang Univ. (China)
17 September 2024 • 17:10 - 17:30 BST
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Solar radiation will be scattered by atmospheric molecules and aerosol particles when it transfers through the earth atmosphere. Based on the BHU-ATM presented in our previous work, an atmospheric radiative transfer model considering the polarization effects is developed, in which the parameter discretization method is used. To this end, the radiative transfer equation is adapted into the Stokes vector form, while the impacts of atmospheric molecules and aerosols on the polarization state of the scattered radiance are represented by means of the scattering phase matrix. The Curtis-Godson approximation and the two-stream approximation are used to obtain the analytical solution of the adapted radiative transfer equation. The scattering phase matrix in the developed model is calculated via the interpolation of a two-dimensional discrete table achieved with a set of preset angles and wavelengths. The simulation results of the atmospheric transmittance, the spectral radiance and the degree of polarization (DOP) for an arbitrarily selected transfer path are given.
Posters-Tuesday
17 September 2024 • 17:30 - 19:00 BST
Conference attendees are invited to attend the Sensors + Imaging poster session on Tuesday evening. Come view the posters, enjoy light refreshments, ask questions, and network with colleagues in your field.

Poster Setup: Tuesday 10:00 – 16:00 hrs
View poster presentation guidelines and set-up instructions at
https://spie.org/ESI/poster-presentation-guidelines
13193-21
Author(s): Simone Lolli, Istituto di Metodologie per l'Analisi Ambientale (Italy); Luciano Alparone, Univ. degli Studi di Firenze (Italy); Alberto Arienzo, Univ. degli studi di Firenze (Italy); Andrea Garzelli, Univ. degli Studi di Siena (Italy)
17 September 2024 • 17:30 - 19:00 BST
13193-22
Author(s): Ilaria Gandolfi, Fabrizio Marra, Istituto di Metodologie per l'Analisi Ambientale (Italy); Fabio Madonna, Univ. degli studi di Salerno (Italy); Marco Rosoldi, Simone Lolli, Istituto di Metodologie per l'Analisi Ambientale (Italy)
17 September 2024 • 17:30 - 19:00 BST
13193-23
Author(s): Makiko Nakata, Kindai Univ. (Japan); Sonoyo Mukai, The Kyoto College of Graduate Studies for Informatics (Japan)
17 September 2024 • 17:30 - 19:00 BST
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A number of reports indicate that fire plumes reach the free troposphere due to large forest fires. Aerosols injected at high altitudes significantly impact atmospheric chemistry and climate. However, the impact of explosive convection on the transport of atmospheric aerosol is not well quantified. Chemical transport models is an effective tool to reproduce the behavior of aerosol transportation in the atmosphere. This study examines how this process can be handled in a chemical transport model for more reproducible simulations.
13193-24
Author(s): Jeffrey Mast, NASA Postdoctoral Program (United States); Yolanda Shea, Xu Liu, NASA Langley Research Ctr. (United States)
17 September 2024 • 17:30 - 19:00 BST
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Cirrus (ice) cloud remote sensing retrieval products are important inputs for weather and climate models. Uncertainties in the retrieval products impact the downstream model results. Hyperspectral instruments contain hundreds to thousands of channels, producing information-dense radiance spectra and thus offerring the opportunity to reduce uncertainties in retrieval products. A cirrus cloud optical and microphysical product retrieval is under development for the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Earth Surface Mineral Dust Source Investigation (EMIT) instruments, and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder). The spectral coverage of all three instruments includes the ultraviolet, visible, and near-infrared (UV-VIS-NIR). In this study a very fast radiative transfer model, the Principal Component-based Radiative Transfer Model in the solar spectral region (PCRTM-Solar), is used for the retrieval’s radiance computations. This enables the entire AVIRIS, EMIT, and CLARREO-Pathfinder spectra to be used in the retrieval. Preliminary results will be shown.
13193-25
Author(s): Xinya Gong, Jun Li, National Satellite Meteorological Ctr. (China); Zhenglong Li, Univ. of Wisconsin-Madison (United States); Ruoying Yin, Wei Han, China Meteorological Administration (China)
17 September 2024 • 17:30 - 19:00 BST
13193-26
Author(s): Andrew Matheson, Anna Michalska, Frances McGinley, Jerome Woodwark, Paul Palmer, The Univ. of Edinburgh (United Kingdom)
17 September 2024 • 17:30 - 19:00 BST
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Health officials, policymakers and the public are becoming increasingly aware of the dangers of long-term exposure to air pollution. One gas of key importance is nitrogen dioxide (NO2), which is strongly linked with respiratory diseases and plays a key role in the production of other air pollutants such as surface ozone and particulate matter. Current NO2 monitoring networks depend largely on stationary systems that sample local air and to a lesser extent on satellite observations that typically collect data with comparatively low (km2) spatial resolution, which make emission source attribution difficult. Additionally, the short atmospheric lifetime of NO2, combined with low ambient levels, means that atmospheric plumes of NO2 from combustion sources are more easily detected than CO2 plumes. To exploit this fully, high spatial and temporal resolution monitoring systems are needed. In this work we introduce SNEEZI (Sensing NO2 Emissions to Evaluate net-Zero Initiatives) , a proposed lightweight NO2 spectral imaging system capable of being launched on a constellation of small satellites to allow NO2 monitoring with high spatial and temporal resolution.
13193-27
Author(s): Frances McGinley, Anna Michalska, A. Jerome P. Woodwark, Andrew B. Matheson, Paul I. Palmer, The Univ. of Edinburgh (United Kingdom)
17 September 2024 • 17:30 - 19:00 BST
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Methane is a potent greenhouse gas with a comparatively short atmospheric lifetime, and identifying and addressing methane emissions now is an effective strategy to mitigate the effects of climate change in the near-term. The Near Infrared Multispectral Camera for Atmospheric Methane, NIMCAM, is a new satellite instrument under development at the University of Edinburgh, designed to deliver high spatial resolution mapping of atmospheric methane. With a spatial resolution of 50m, NIMCAM will be the highest resolution instrument capable of continuous global monitoring among those currently available. The multispectral imaging system operates in the short-wave infrared and will be deployed on a constellation of small satellites, detecting methane emissions continuously without the need to pre-select target sites. We will present results from ground-based field trials, showing NIMCAM's ability to detect atmospheric methane. We will also describe the design of an aircraft demonstrator instrument, which will be used for future air-borne trials, and present concepts for the satellite instrument and mission.
Conference Chair
Pacific Northwest National Lab. (United States)
Conference Chair
CNR-IMAA (Italy)
Program Committee
Univ. de Granada (Spain)
Program Committee
ONERA (France)
Program Committee
Univ. Politècnica de Catalunya (Spain)
Program Committee
Erica Dolinar
U.S. Naval Research Lab. (United States)
Program Committee
The Univ. of Oklahoma (United States)
Program Committee
Univ. degli Studi della Basilicata (Italy)
Program Committee
Atmospheric Physics Consulting (Germany)
Program Committee
Univ. degli Studi della Basilicata (Italy)
Program Committee
SRON Netherlands Institute for Space Research (Netherlands)
Program Committee
CNR-NBFC (Italy)
Program Committee
Fachhochschule Düsseldorf (Germany)
Additional Information

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