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Готові списки джерел за темами / Retrieval Depth / Статті в журналах

Щоб переглянути інші типи публікацій з цієї теми, перейдіть за посиланням: Retrieval Depth.

Статті в журналах з теми "Retrieval Depth"

Автор: Grafiati

Опубліковано: 7 червня 2025

Оновлено: 2 серпня 2025

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1

Evans, K. Franklin, Alexander Marshak, and Tamás Várnai. "The Potential for Improved Boundary Layer Cloud Optical Depth Retrievals from the Multiple Directions of MISR." Journal of the Atmospheric Sciences 65, no. 10 (2008): 3179–96. http://dx.doi.org/10.1175/2008jas2627.1.

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The Multiangle Imaging Spectroradiometer (MISR) views the earth with nine cameras, ranging from a 70° zenith angle viewing forward through nadir to 70° viewing aft. MISR does not have an operational cloud optical depth retrieval algorithm, but previous research has hinted that solar reflection measured in multiple directions might improve cloud optical depth retrievals. This study explores the optical depth information content of MISR’s multiple angles using a retrieval simulation approach. Hundreds of realistic boundary-layer cloud fields are generated with large-eddy simulation (LES) models

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2

Stein, Thorwald H. M., Julien Delanoë, and Robin J. Hogan. "A Comparison among Four Different Retrieval Methods for Ice-Cloud Properties Using Data from CloudSat, CALIPSO, and MODIS." Journal of Applied Meteorology and Climatology 50, no. 9 (2011): 1952–69. http://dx.doi.org/10.1175/2011jamc2646.1.

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AbstractThe A-Train constellation of satellites provides a new capability to measure vertical cloud profiles that leads to more detailed information on ice-cloud microphysical properties than has been possible up to now. A variational radar–lidar ice-cloud retrieval algorithm (VarCloud) takes advantage of the complementary nature of the CloudSat radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to provide a seamless retrieval of ice water content, effective radius, and extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thi

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3

Zhang, H., R. M. Hoff, S. Kondragunta, I. Laszlo, and A. Lyapustin. "Aerosol Optical Depth (AOD) retrieval using simultaneous GOES-East and GOES-West reflected radiances over the Western US." Atmospheric Measurement Techniques Discussions 5, no. 5 (2012): 7945–81. http://dx.doi.org/10.5194/amtd-5-7945-2012.

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Abstract. Aerosol Optical Depth (AOD) in the Western United States is observed independently by both the GOES-East and GOES-West imagers. The GASP (GOES Aerosol/Smoke Product) aerosol optical depth retrieval algorithm treats each satellite as a unique sensor and thus NOAA obtains two separate aerosol optical depth values at the same time for the same location. The TOA radiances and the associated derived optical depths can be quite different due to the different viewing geometries with large difference in solar-scattering angles. In order to fully exploit the simultaneous observations and gene

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4

Tu, Jinsheng, Haohan Wei, Rui Zhang, et al. "GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data." Remote Sensing 13, no. 21 (2021): 4311. http://dx.doi.org/10.3390/rs13214311.

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Global navigation satellite system interferometric reflectometry (GNSS-IR) represents an extra method to detect snow depth for climate research and water cycle managing. However, using a single frequency of GNSS-IR for snow depth retrieval is often found to be challenging when attempting to achieve a high spatial and temporal sensitivity. To evaluate both the capability of the GNSS-IR snow depth retrieved by the multi-GNSS system and multi-frequency from signal-to-noise ratio (SNR) data, the accuracy of snow depth retrieval by different frequency signals from the multi-GNSS system is analyzed,

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5

Holz, Robert E., Steve Ackerman, Paolo Antonelli, et al. "An Improvement to the High-Spectral-Resolution CO2-Slicing Cloud-Top Altitude Retrieval." Journal of Atmospheric and Oceanic Technology 23, no. 5 (2006): 653–70. http://dx.doi.org/10.1175/jtech1877.1.

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Abstract An improvement to high-spectral-resolution infrared cloud-top altitude retrievals is compared to existing retrieval methods and cloud lidar measurements. The new method, CO2 sorting, determines optimal channel pairs to which the CO2 slicing retrieval will be applied. The new retrieval is applied to aircraft Scanning High-Resolution Interferometer Sounder (S-HIS) measurements. The results are compared to existing passive retrieval methods and coincident Cloud Physics Lidar (CPL) measurements. It is demonstrated that when CO2 sorting is used to select channel pairs for CO2 slicing there

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6

Garrett, T. J., and C. Zhao. "Ground-based remote sensing of thin clouds in the Arctic." Atmospheric Measurement Techniques Discussions 5, no. 6 (2012): 8653–99. http://dx.doi.org/10.5194/amtd-5-8653-2012.

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Abstract. This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" where absorption by water vapor is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in two micro-windows, constrained by the transmission through clouds of stratospheric ozone emission. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius, v

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7

Lipponen, Antti, Tero Mielonen, Mikko R. A. Pitkänen, et al. "Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land." Atmospheric Measurement Techniques 11, no. 3 (2018): 1529–47. http://dx.doi.org/10.5194/amt-11-1529-2018.

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Abstract. We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different w

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8

Zheng, Jianyu, Zhibo Zhang, Hongbin Yu, et al. "Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations." Atmospheric Chemistry and Physics 23, no. 14 (2023): 8271–304. http://dx.doi.org/10.5194/acp-23-8271-2023.

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Abstract. In this study, we developed a novel algorithm based on the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR) observations and dust vertical profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) to simultaneously retrieve dust aerosol optical depth at 10 µm (DAOD10 µm) and the coarse-mode dust effective diameter (Deff) over global oceans. The accuracy of the Deff retrieval is assessed by comparing the dust lognormal volume particle size distribution (PSD) corresponding to retrieved Deff with the in situ-measured dust PSDs fro

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9

Zhang, H., R. M. Hoff, S. Kondragunta, I. Laszlo, and A. Lyapustin. "Aerosol optical depth (AOD) retrieval using simultaneous GOES-East and GOES-West reflected radiances over the western United States." Atmospheric Measurement Techniques 6, no. 2 (2013): 471–86. http://dx.doi.org/10.5194/amt-6-471-2013.

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Abstract. Aerosol optical depth (AOD) in the western United States is observed independently by both the (Geostationary Operational Environmental Satellites) GOES-East and GOES-West imagers. The GASP (GOES Aerosol/Smoke Product) aerosol optical depth retrieval algorithm treats each satellite as a unique sensor and thus obtains two separate aerosol optical depth values at the same time for the same location. The TOA (the top of the atmosphere) radiances and the associated derived optical depths can be quite different due to the different viewing geometries with large difference in solar-scatter

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10

Yang, Yuekui, Alexander Marshak, J. Christine Chiu, et al. "Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal." Journal of the Atmospheric Sciences 65, no. 11 (2008): 3513–26. http://dx.doi.org/10.1175/2008jas2744.1.

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Abstract Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other spaceborne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (&lt; about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so one must first calibrate the reflected solar radiation received by the photon-counting detectors of the GLAS

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11

Li, Chong, Jing Li, Oleg Dubovik, Zhao-Cheng Zeng, and Yuk L. Yung. "Impact of Aerosol Vertical Distribution on Aerosol Optical Depth Retrieval from Passive Satellite Sensors." Remote Sensing 12, no. 9 (2020): 1524. http://dx.doi.org/10.3390/rs12091524.

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When retrieving Aerosol Optical Depth (AOD) from passive satellite sensors, the vertical distribution of aerosols usually needs to be assumed, potentially causing uncertainties in the retrievals. In this study, we use the Moderate Resolution Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors as examples to investigate the impact of aerosol vertical distribution on AOD retrievals. A series of sensitivity experiments was conducted using radiative transfer models with different aerosol profiles and surface conditions. Assuming a 0.2 AOD, we found that the AOD

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12

Crook, D. A., B. J. Adair, and L. J. Hetherington. "Low-cost device for retrieval of moorings deployed with underwater remote release systems." Marine and Freshwater Research 69, no. 3 (2018): 473. http://dx.doi.org/10.1071/mf17189.

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Underwater acoustic and timed-release systems are commonly deployed with sensors and other equipment for ecological and oceanographic research in aquatic environments. These systems allow equipment deployed at depth to be remotely released from their moorings for retrieval. However, a current limitation is that most systems do not incorporate mechanisms for retrieval of the mooring anchor and attachments (e.g. shackles, cable). Herein we provide a detailed description and evaluation of a ‘retrieval pod’ that can be attached directly to remotely released underwater devices to facilitate mooring

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13

Barker, H. W., C. F. Pavloski, M. Ovtchinnikov, and E. E. Clothiaux. "Assessing a Cloud Optical Depth Retrieval Algorithm with Model-Generated Data and the Frozen Turbulence Assumption." Journal of the Atmospheric Sciences 61, no. 23 (2004): 2951–56. http://dx.doi.org/10.1175/jas-3310.1.

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Abstract A cloud optical depth retrieval algorithm that utilizes time series of solar irradiance and zenith downwelling radiance data collected at a fixed surface site is assessed using model-generated cloud fields and simulated radiation measurements. To date, the retrieval algorithm has only been assessed using instantaneous cloud fields in which time series were mimicked via the frozen turbulence assumption. In this study, time series of radiation data are generated for use by the algorithm from a series of snapshots of an evolving and advecting cloud field, with values of optical depth ret

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14

Dong, Zhaoqing, Lijian Shi, Mingsen Lin, and Tao Zeng. "A Suitable Retrieval Algorithm of Arctic Snow Depths with AMSR-2 and Its Application to Sea Ice Thicknesses of Cryosat-2 Data." Remote Sensing 14, no. 4 (2022): 1041. http://dx.doi.org/10.3390/rs14041041.

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Arctic sea ice and snow affect the energy balance of the global climate system through the radiation budget. Accurate determination of the snow cover over Arctic sea ice is significant for the retrieval of the sea ice thickness (SIT). In this study, we developed a new snow depth retrieval method over Arctic sea ice with a long short-term memory (LSTM) deep learning algorithm based on Operation IceBridge (OIB) snow depth data and brightness temperature data of AMSR-2 passive microwave radiometers. We compared climatology products (modified W99 and AWI), altimeter products (Kwok) and microwave r

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15

Torres, Benjamin, and David Fuertes. "Characterization of aerosol size properties from measurements of spectral optical depth: a global validation of the GRASP-AOD code using long-term AERONET data." Atmospheric Measurement Techniques 14, no. 6 (2021): 4471–506. http://dx.doi.org/10.5194/amt-14-4471-2021.

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Abstract. A validation study is conducted regarding aerosol optical size property retrievals from measurements of the direct sun beam only (without the aid of diffuse radiation). The study focuses on using real data to test the new GRASP-AOD application, which uses only spectral optical depth measurements to retrieve the total column aerosol size distributions, assumed to be bimodal lognormal. In addition, a set of secondary integral parameters of aerosol size distribution and optical properties are provided: effective radius, total volume concentration and fine-mode fraction of aerosol optica

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16

Liu, Jiping, Yuanyuan Zhang, Xiao Cheng, and Yongyun Hu. "Retrieval of Snow Depth over Arctic Sea Ice Using a Deep Neural Network." Remote Sensing 11, no. 23 (2019): 2864. http://dx.doi.org/10.3390/rs11232864.

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The accurate knowledge of spatial and temporal variations of snow depth over sea ice in the Arctic basin is important for understanding the Arctic energy budget and retrieving sea ice thickness from satellite altimetry. In this study, we develop and validate a new method for retrieving snow depth over Arctic sea ice from brightness temperatures at different frequencies measured by passive microwave radiometers. We construct an ensemble-based deep neural network and use snow depth measured by sea ice mass balance buoys to train the network. First, the accuracy of the retrieved snow depth is val

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17

Feng, Qian, N. Christina Hsu, Ping Yang, and Si-Chee Tsay. "Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations." IEEE Transactions on Geoscience and Remote Sensing 49, no. 6 (2011): 2819–27. http://dx.doi.org/10.1109/tgrs.2011.2118762.

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The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector r

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18

Ventress, Lucy J., Gregory McGarragh, Elisa Carboni, Andrew J. Smith, and Roy G. Grainger. "Retrieval of ash properties from IASI measurements." Atmospheric Measurement Techniques 9, no. 11 (2016): 5407–22. http://dx.doi.org/10.5194/amt-9-5407-2016.

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Abstract. A new optimal estimation algorithm for the retrieval of volcanic ash properties has been developed for use with the Infrared Atmospheric Sounding Interferometer (IASI). The retrieval method uses the wave number range 680–1200 cm−1, which contains window channels, the CO2 ν2 band (used for the height retrieval), and the O3 ν3 band.Assuming a single infinitely (geometrically) thin ash plume and combining this with the output from the radiative transfer model RTTOV, the retrieval algorithm produces the most probable values for the ash optical depth (AOD), particle effective radius, plum

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19

Hoppinen, Zachary, Ross T. Palomaki, George Brencher, et al. "Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites." Cryosphere 18, no. 11 (2024): 5407–30. http://dx.doi.org/10.5194/tc-18-5407-2024.

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Abstract. Snow depth retrievals from spaceborne C-band synthetic aperture radar (SAR) backscatter have the potential to fill an important gap in the remote monitoring of seasonal snow. Sentinel-1 (S1) SAR data have been used previously in an empirical algorithm to generate snow depth products with near-global coverage, subweekly temporal resolution and spatial resolutions on the order of hundreds of meters to 1 km. However, there has been no published independent validation of this algorithm. In this work we develop the first open-source software package that implements this Sentinel-1 snow de

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20

Rutter, Nick, Melody J. Sandells, Chris Derksen, et al. "Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals." Cryosphere 13, no. 11 (2019): 3045–59. http://dx.doi.org/10.5194/tc-13-3045-2019.

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Abstract. Spatial variability in snowpack properties negatively impacts our capacity to make direct measurements of snow water equivalent (SWE) using satellites. A comprehensive data set of snow microstructure (94 profiles at 36 sites) and snow layer thickness (9000 vertical profiles across nine trenches) collected over two winters at Trail Valley Creek, NWT, Canada, was applied in synthetic radiative transfer experiments. This allowed for robust assessment of the impact of estimation accuracy of unknown snow microstructural characteristics on the viability of SWE retrievals. Depth hoar layer

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21

Chen, Lijuan, Ren Wang, Ying Fei, Peng Fang, Yong Zha, and Haishan Chen. "Multi-angle aerosol optical depth retrieval method based on improved surface reflectance." Atmospheric Measurement Techniques 17, no. 14 (2024): 4411–24. http://dx.doi.org/10.5194/amt-17-4411-2024.

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Abstract. Retrieval of atmospheric aerosol optical depth (AOD) has been a challenge for Earth satellite observations, mainly due to the difficulty of estimating surface reflectance with the combined influence of land–atmosphere coupling. Current major satellite AOD retrieval products have low spatial resolution under complex surface processes. In this study, we further improved the surface reflectance by modeling the error correction based on the previous AOD retrieval and obtained more accurate AOD retrieval results. A lookup table was constructed using the Second Simulation of Satellite Sign

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22

Garrett, T. J., and C. Zhao. "Ground-based remote sensing of thin clouds in the Arctic." Atmospheric Measurement Techniques 6, no. 5 (2013): 1227–43. http://dx.doi.org/10.5194/amt-6-1227-2013.

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Abstract. This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" at 862.5 cm−1, 935.8 cm−1, and 988.4 cm−1 where absorption by water vapour is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in the first two of these micro-windows, constrained by the transmission through clouds of primarily stratospheric ozone emission at 1040 cm−1. Assuming a cloud does not approxim

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23

Friedrich, Martina Michaela, Claudia Rivera, Wolfgang Stremme, et al. "NO<sub>2</sub> vertical profiles and column densities from MAX-DOAS measurements in Mexico City." Atmospheric Measurement Techniques 12, no. 4 (2019): 2545–65. http://dx.doi.org/10.5194/amt-12-2545-2019.

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Abstract. We present a new numerical code, Mexican MAX-DOAS Fit (MMF), developed to retrieve profiles of different trace gases from the network of MAX-DOAS instruments operated in Mexico City. MMF uses differential slant column densities (dSCDs) retrieved with the QDOAS (Danckaert et al., 2013) software. The retrieval is comprised of two steps, an aerosol retrieval and a trace gas retrieval that uses the retrieved aerosol profile in the forward model for the trace gas. For forward model simulations, VLIDORT is used (e.g., Spurr et al., 2001; Spurr, 2006, 2013). Both steps use constrained least

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24

Meehan, Tate G., Ahmad Hojatimalekshah, Hans-Peter Marshall, et al. "Spatially distributed snow depth, bulk density, and snow water equivalent from ground-based and airborne sensor integration at Grand Mesa, Colorado, USA." Cryosphere 18, no. 7 (2024): 3253–76. http://dx.doi.org/10.5194/tc-18-3253-2024.

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Abstract. Estimating snow mass in the mountains remains a major challenge for remote-sensing methods. Airborne lidar can retrieve snow depth, and some promising results have recently been obtained from spaceborne platforms, yet density estimates are required to convert snow depth to snow water equivalent (SWE). However, the retrieval of snow bulk density remains unsolved, and limited data are available to evaluate model estimates of density in mountainous terrain. Toward the goal of landscape-scale retrievals of snow density, we estimated bulk density and length-scale variability by combining

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25

Liu, Z., D. Winker, A. Omar, et al. "Evaluation of CALIOP 532 nm aerosol optical depth over opaque water clouds." Atmospheric Chemistry and Physics 15, no. 3 (2015): 1265–88. http://dx.doi.org/10.5194/acp-15-1265-2015.

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Abstract. With its height-resolved measurements and near global coverage, the CALIOP lidar onboard the CALIPSO satellite offers a new capability for aerosol retrievals in cloudy skies. Validation of these retrievals is difficult, however, as independent, collocated and co-temporal data sets are generally not available. In this paper, we evaluate CALIOP aerosol products above opaque water clouds by applying multiple retrieval techniques to CALIOP Level 1 profile data and comparing the results. This approach allows us to both characterize the accuracy of the CALIOP above-cloud aerosol optical de

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26

Zhang, Hang, Peng Lu, Miao Yu, et al. "Comparison of Pond Depth and Ice Thickness Retrieval Algorithms for Summer Arctic Sea Ice." Remote Sensing 14, no. 12 (2022): 2831. http://dx.doi.org/10.3390/rs14122831.

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In order to satisfy the demand of key sea ice parameters, including melt pond depth Hp and underlying ice thickness Hi, in studies of Arctic sea ice change in summer, four algorithms of retrieving Hp and Hi were compared and validated by using optical data of melt ponds from field observations. The Malinka18 algorithm stood out as the most accurate algorithm for the retrieval of Hp. For the retrieval of Hi, Malinka18 and Zhang21 algorithms could also provide reasonable results and both can be applied under clear and overcast sky conditions, while retrievals under clear sky conditions are more

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27

Wu, Yerong, Martin de Graaf, and Massimo Menenti. "Improved MODIS Dark Target aerosol optical depth algorithm over land: angular effect correction." Atmospheric Measurement Techniques 9, no. 11 (2016): 5575–89. http://dx.doi.org/10.5194/amt-9-5575-2016.

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Abstract. Aerosol optical depth (AOD) product retrieved from MODerate Resolution Imaging Spectroradiometer (MODIS) measurements has greatly benefited scientific research in climate change and air quality due to its high quality and large coverage over the globe. However, the current product (e.g., Collection 6) over land needs to be further improved. The is because AOD retrieval still suffers large uncertainty from the surface reflectance (e.g., anisotropic reflection) although the impacts of the surface reflectance have been largely reduced using the Dark Target (DT) algorithm. It has been sh

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28

Karthikeyan, Lanka, Ming Pan, Dasika Nagesh Kumar, and Eric F. Wood. "Effect of Structural Uncertainty in Passive Microwave Soil Moisture Retrieval Algorithm." Sensors 20, no. 4 (2020): 1225. http://dx.doi.org/10.3390/s20041225.

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Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM) using brightness temperatures (TB) at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM using dual-polarized TB measurements to retrieve the VOD and SM concurrently. Algorithms in this regard typically use the τ-ω types of models, which consist of two third-order polynomial equations and, thus, can have multiple solutions. Through this work, we find that uncertainty occurs due to the structural indeterminacy that i

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29

Loveridge, Jesse, Aviad Levis, Larry Di Girolamo, et al. "Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization." Atmospheric Measurement Techniques 16, no. 16 (2023): 3931–57. http://dx.doi.org/10.5194/amt-16-3931-2023.

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Abstract. Our global understanding of clouds and aerosols relies on the remote sensing of their optical, microphysical, and macrophysical properties using, in part, scattered solar radiation. Current retrievals assume clouds and aerosols form plane-parallel, homogeneous layers and utilize 1D radiative transfer (RT) models. These assumptions limit the detail that can be retrieved about the 3D variability in the cloud and aerosol fields and induce biases in the retrieved properties for highly heterogeneous structures such as cumulus clouds and smoke plumes. In Part 1 of this two-part study, we v

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30

Kolmonen, P., A. M. Sundström, L. Sogacheva, E. Rodriguez, T. Virtanen, and G. de Leeuw. "Uncertainty characterization of AOD for the AATSR dual and single view retrieval algorithms." Atmospheric Measurement Techniques Discussions 6, no. 2 (2013): 4039–75. http://dx.doi.org/10.5194/amtd-6-4039-2013.

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Abstract. The uncertainty associated with satellite-retrieved aerosol properties is needed when these data are used to constrain chemical transport or climate models by using data assimilation. Global uncertainty as provided by comparison with independent ground-based observations is usually not adequate for that purpose. Rather the per-pixel uncertainty is needed. In this work we describe how these are determined in the AATSR dual and single view aerosol retrieval algorithms (ADV and ASV) which are used to retrieve aerosol optical properties from reflectance measured at the top of the atmosph

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31

Turner, D. D. "Arctic Mixed-Phase Cloud Properties from AERI Lidar Observations: Algorithm and Results from SHEBA." Journal of Applied Meteorology 44, no. 4 (2005): 427–44. http://dx.doi.org/10.1175/jam2208.1.

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Abstract A new approach to retrieve microphysical properties from mixed-phase Arctic clouds is presented. This mixed-phase cloud property retrieval algorithm (MIXCRA) retrieves cloud optical depth, ice fraction, and the effective radius of the water and ice particles from ground-based, high-resolution infrared radiance and lidar cloud boundary observations. The theoretical basis for this technique is that the absorption coefficient of ice is greater than that of liquid water from 10 to 13 μm, whereas liquid water is more absorbing than ice from 16 to 25 μm. MIXCRA retrievals are only valid for

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Lievens, Hans, Isis Brangers, Hans-Peter Marshall, Tobias Jonas, Marc Olefs, and Gabriëlle De Lannoy. "Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps." Cryosphere 16, no. 1 (2022): 159–77. http://dx.doi.org/10.5194/tc-16-159-2022.

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Abstract. Seasonal snow is an essential water resource in many mountain regions. However, the spatio-temporal variability in mountain snow depth or snow water equivalent (SWE) at regional to global scales is not well understood due to the lack of high-resolution satellite observations and robust retrieval algorithms. We investigate the ability of the Sentinel-1 mission to monitor snow depth at sub-kilometer (100 m, 500 m, and 1 km) resolutions over the European Alps for 2017–2019. The Sentinel-1 backscatter observations, especially in cross-polarization, show a high correlation with regional m

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33

Mei, L. L., Y. Xue, A. A. Kokhanovsky, W. von Hoyningen-Huene, G. de Leeuw, and J. P. Burrows. "Retrieval of aerosol optical depth over land surfaces from AVHRR data." Atmospheric Measurement Techniques 7, no. 8 (2014): 2411–20. http://dx.doi.org/10.5194/amt-7-2411-2014.

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Abstract. The Advanced Very High Resolution Radiometer (AVHRR) provides a global, long-term, consistent time series of radiance data in several wavebands which are used for the retrieval of surface spectral reflectance, albedo and surface temperature. Long-term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. AVHRR radiances have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land is challenging because of the limited

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34

Mei, L., Y. Xue, A. A. Kokhanovsky, W. von Hoyningen-Huene, G. de Leeuw, and J. P. Burrows. "Retrieval of aerosol optical depth over land surfaces from AVHRR data." Atmospheric Measurement Techniques Discussions 6, no. 1 (2013): 2227–51. http://dx.doi.org/10.5194/amtd-6-2227-2013.

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Abstract. The Advanced Very High Resolution Radiometer (AVHRR) radiance data provide a global, long-term, consistent time series having high spectral and spatial resolution and thus being valuable for the retrieval of surface spectral reflectance, albedo and surface temperature. Long term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. These data have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land and land surfac

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35

Li, Dingdong, Yonghua Wu, Barry Gross, and Fred Moshary. "Capabilities of an Automatic Lidar Ceilometer to Retrieve Aerosol Characteristics within the Planetary Boundary Layer." Remote Sensing 13, no. 18 (2021): 3626. http://dx.doi.org/10.3390/rs13183626.

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Continuous observation and quantitative retrieval of aerosol backscatter coefficients are important in the study of air quality and climate in metropolitan areas such as New York City. Ceilometers are ideal for this application, but aerosol backscatter coefficient retrievals from ceilometers are challenging and require proper calibration. In this study, we calibrate the ceilometer (Lufft CHM15k, 1064 nm) system constant with the molecular backscatter coefficient and evaluate the calibrated profiles with other independent methods, including the water-phase cloud method and comparison with the N

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36

Poulsen, C. A., R. Siddans, G. E. Thomas, et al. "Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR." Atmospheric Measurement Techniques 5, no. 8 (2012): 1889–910. http://dx.doi.org/10.5194/amt-5-1889-2012.

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Abstract. Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud) which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of th

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37

Zhang, H., A. Lyapustin, Y. Wang, et al. "A multi-angle aerosol optical depth retrieval algorithm for geostationary satellite data over the United States." Atmospheric Chemistry and Physics Discussions 11, no. 4 (2011): 12519–60. http://dx.doi.org/10.5194/acpd-11-12519-2011.

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Abstract. Aerosol optical depth (AOD) retrieval from geostationary satellites has high temporal resolution compared to the polar orbiting satellites and thus enables us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosol and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day compo

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38

Coakley, James A., Michael A. Friedman, and William R. Tahnk. "Retrieval of Cloud Properties for Partly Cloudy Imager Pixels." Journal of Atmospheric and Oceanic Technology 22, no. 1 (2005): 3–17. http://dx.doi.org/10.1175/jtech-1681.1.

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Abstract Retrievals of cloud properties from satellite imagery often invoke the assumption that the fields of view are overcast when cloud-contaminated, even though a significant fraction are only partially cloud-covered. The overcast assumption leads to biases in the retrieved cloud properties: cloud amounts and droplet effective radii are typically overestimated, while visible optical depths, cloud altitudes, cloud liquid water amounts, and column droplet number concentrations are typically underestimated. In order to estimate these biases, a retrieval scheme was developed to obtain the prop

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39

Gatebe, Charles K., Hiren Jethva, Ritesh Gautam, Rajesh Poudyal, and Tamás Várnai. "A new measurement approach for validating satellite-based above-cloud aerosol optical depth." Atmospheric Measurement Techniques 14, no. 2 (2021): 1405–23. http://dx.doi.org/10.5194/amt-14-1405-2021.

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Abstract. The retrieval of aerosol parameters from passive satellite instruments in cloudy scenes is challenging, partly because clouds and cloud-related processes may significantly modify aerosol optical depth (AOD) and particle size, a problem that is further compounded by 3D radiative processes. Recent advances in retrieval algorithms such as the “color ratio” method, which utilizes the measurements at a shorter (470 nm) and a longer (860 nm) wavelength, have demonstrated the simultaneous derivation of AOD and cloud optical depth (COD) for scenes in which absorbing aerosols are found to ove

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40

Kern, Stefan, and Burcu Ozsoy. "An Attempt to Improve Snow Depth Retrieval Using Satellite Microwave Radiometry for Rough Antarctic Sea Ice." Remote Sensing 11, no. 19 (2019): 2323. http://dx.doi.org/10.3390/rs11192323.

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Snow depth on sea ice is a major constituent of the marine cryosphere. It is a key parameter for the derivation of sea-ice thickness from satellite altimetry. One way to retrieve the basin-scale snow depth on sea ice is by satellite microwave radiometry. There is evidence from measurements and inter-comparison studies that current retrievals likely under-estimate the snow depth over deformed, rough sea ice. We follow up on an earlier study, where satellite passive microwave data were combined with information on the sea-ice topography from the satellite laser altimeter on board the Ice, Cloud

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41

Wu, L., O. Hasekamp, B. van Diedenhoven, and B. Cairns. "Aerosol retrieval from multiangle, multispectral photopolarimetric measurements: importance of spectral range and angular resolution." Atmospheric Measurement Techniques 8, no. 6 (2015): 2625–38. http://dx.doi.org/10.5194/amt-8-2625-2015.

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Abstract. We investigated the importance of spectral range and angular resolution for aerosol retrieval from multiangle photopolarimetric measurements over land. For this purpose, we use an extensive set of simulated measurements for different spectral ranges and angular resolutions and subsets of real measurements of the airborne Research Scanning Polarimeter (RSP) carried out during the PODEX and SEAC4RS campaigns over the continental USA. Aerosol retrievals performed from RSP measurements show good agreement with ground-based AERONET measurements for aerosol optical depth (AOD), single scat

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42

Chen, Yunping, Yue Yang, Lei Hou, Kangzhuo Yang, Jiaxiang Yu, and Yuan Sun. "High-Resolution Aerosol Optical Depth Retrieval in Urban Areas Based on Sentinel-2." Photogrammetric Engineering & Remote Sensing 89, no. 6 (2023): 361–71. http://dx.doi.org/10.14358/pers.22-00122r2.

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In this paper, an improved aerosol optical depth (AOD ) retrieval algorithm is proposed based on Sentinel-2 and AErosol RObotic NETwork (AERONET ) data. The surface reflectance for AOD retrieval was estimated from the image that had minimal aerosol contamination in a temporal window determined by AERONET data. Validation of the Sentinel-2 AOD retrievals was conducted against four Aerosol Robotic Network (AERONET ) sites located in Beijing. The results show that the Sentinel-2 AOD retrievals are highly consistent with the AERONET AOD measurements (R = 0.942), with 85.56% falling within the expe

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43

Yang, Jianwei, Lingmei Jiang, Jinmei Pan, et al. "Comparison of Machine Learning-Based Snow Depth Estimates and Development of a New Operational Retrieval Algorithm over China." Remote Sensing 14, no. 12 (2022): 2800. http://dx.doi.org/10.3390/rs14122800.

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Snow depth estimation with passive microwave (PM) remote sensing is challenged by spatial variations in the Earth’s surface, e.g., snow metamorphism, land cover types, and topography. Thus, traditional static snow depth retrieval algorithms cannot capture snow thickness well. In this study, we present a new operational retrieval algorithm, hereafter referred to as the pixel-based method (0.25° × 0.25° grid-level), to provide more accurate and nearly real-time snow depth estimates. First, the reference snow depth was retrieved using a previously proposed model in which a microwave snow emission

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44

Siu, Leong Wai, Joseph S. Schlosser, David Painemal, et al. "Retrievals of aerosol optical depth over the western North Atlantic Ocean during ACTIVATE." Atmospheric Measurement Techniques 17, no. 9 (2024): 2739–59. http://dx.doi.org/10.5194/amt-17-2739-2024.

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Abstract. Aerosol optical depth was retrieved from two airborne remote sensing instruments, the Research Scanning Polarimeter (RSP) and Second Generation High Spectral Resolution Lidar (HSRL-2), during the National Aeronautics and Space Administration (NASA) Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). The field campaign offers a unique opportunity to evaluate an extensive 3-year dataset under a wide range of meteorological conditions from two instruments on the same platform. However, a long-standing issue in atmospheric field studies is that there i

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45

Rosenburg, Sophie, Charlotte Lange, Evelyn Jäkel, Michael Schäfer, André Ehrlich, and Manfred Wendisch. "Retrieval of snow layer and melt pond properties on Arctic sea ice from airborne imaging spectrometer observations." Atmospheric Measurement Techniques 16, no. 16 (2023): 3915–30. http://dx.doi.org/10.5194/amt-16-3915-2023.

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Abstract. A melting snow layer on Arctic sea ice, as a composition of ice, liquid water, and air, supplies meltwater that may trigger the formation of melt ponds. As a result, surface reflection properties are altered during the melting season and thereby may change the surface energy budget. To study these processes, sea ice surface reflection properties were derived from airborne measurements using imaging spectrometers. The data were collected over the closed and marginal Arctic sea ice zone north of Svalbard in May–June 2017. A retrieval approach based on different absorption indices of pu

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46

Ding, Haonan, Limin Zhao, Shanwei Liu, et al. "FY-4A/AGRI Aerosol Optical Depth Retrieval Capability Test and Validation Based on NNAeroG." Remote Sensing 14, no. 21 (2022): 5591. http://dx.doi.org/10.3390/rs14215591.

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The Advanced Geostationary Radiation Imager (AGRI) is one of the main imaging sensors on the Fengyun-4A (FY-4A) satellite. Due to the combination of high spatial and temporal resolution, the AGRI is suitable for continuously monitoring atmospheric aerosol. Existing studies only perform AOD retrieval on the dark target area of FY-4A/AGRI, and the full disk AOD retrieval is still under exploration. The Neural Network AEROsol Retrieval for Geostationary Satellite (NNAeroG) based on the Fully Connected Neural Network (FCNN) was used to retrieve FY-4A/AGRI full disk aerosol optical depth (AOD). The

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47

Huang, Jingting, William Patrick Arnott, James C. Barnard, and Heather A. Holmes. "Theoretical Uncertainty Analysis of Satellite Retrieved Aerosol Optical Depth Associated with Surface Albedo and Aerosol Optical Properties." Remote Sensing 13, no. 3 (2021): 344. http://dx.doi.org/10.3390/rs13030344.

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Deriving aerosol optical depth (AOD) from space-borne observations is still challenging due to uncertainties associated with sensor calibration drift, cloud screening, aerosol type classification, and surface reflectance characterization. As an initial step to understanding the physical processes impacting these uncertainties in satellite AOD retrievals, this study outlines a theoretical approach to estimate biases in the satellite aerosol retrieval algorithm affected by surface albedo and prescribed aerosol optical properties using a simplified radiative transfer model with a traditional erro

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48

Zhang, H., A. Lyapustin, Y. Wang, et al. "A multi-angle aerosol optical depth retrieval algorithm for geostationary satellite data over the United States." Atmospheric Chemistry and Physics 11, no. 23 (2011): 11977–91. http://dx.doi.org/10.5194/acp-11-11977-2011.

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Анотація:

Abstract. Aerosol optical depth (AOD) retrievals from geostationary satellites have high temporal resolution compared to the polar orbiting satellites and thus enable us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosols and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day com

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49

Smith, William L., Elisabeth Weisz, Stanislav V. Kireev, Daniel K. Zhou, Zhenglong Li, and Eva E. Borbas. "Dual-Regression Retrieval Algorithm for Real-Time Processing of Satellite Ultraspectral Radiances." Journal of Applied Meteorology and Climatology 51, no. 8 (2012): 1455–76. http://dx.doi.org/10.1175/jamc-d-11-0173.1.

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AbstractA fast physically based dual-regression (DR) method is developed to produce, in real time, accurate profile and surface- and cloud-property retrievals from satellite ultraspectral radiances observed for both clear- and cloudy-sky conditions. The DR relies on using empirical orthogonal function (EOF) regression “clear trained” and “cloud trained” retrievals of surface skin temperature, surface-emissivity EOF coefficients, carbon dioxide concentration, cloud-top altitude, effective cloud optical depth, and atmospheric temperature, moisture, and ozone profiles above the cloud and below th

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50

Lai, Wendian, Zhongping Lee, Junwei Wang, Yongchao Wang, Rodrigo Garcia, and Huaguo Zhang. "A Portable Algorithm to Retrieve Bottom Depth of Optically Shallow Waters from Top-Of-Atmosphere Measurements." Journal of Remote Sensing 2022 (February 3, 2022): 1–16. http://dx.doi.org/10.34133/2022/9831947.

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Bottom depth (H) of optically shallow waters can be retrieved from multiband imagery, where remote sensing reflectance (Rrs) are commonly used as the input. Because of the difficulties of removing the atmospheric effects in coastal areas, quite often, there are no valid Rrs from satellites for the retrieval of H. More importantly, the empirical algorithms for H are hardly portable to new measurements. In this study, using data from Landsat-8 and ICESat-2 as examples, we present an approach to retrieve H directly from the top-of-atmosphere (TOA) data. It not only bypasses the requirement to cor

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