Articles | Volume 11, issue 3
https://doi.org/10.5194/amt-11-1515-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-1515-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Mar 2018
Research article |
| 16 Mar 2018
| 16 Mar 2018
Information content of OCO-2 oxygen A-band channels for retrieving marine liquid cloud properties
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91125, USA
Graeme L. Stephens
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91125, USA
Department of Meteorology, University of Reading, Reading, RG6 6BB, UK
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Mark T. Richardson, Brian H. Kahn, and Peter Kalmus
Atmos. Chem. Phys., 23, 7699–7717, https://doi.org/10.5194/acp-23-7699-2023, https://doi.org/10.5194/acp-23-7699-2023, 2023
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Convection over land often triggers hours after a satellite last passed overhead and measured the state of the atmosphere, and during those hours the atmosphere can change greatly. Here we show that it is possible to reconstruct most of those changes by using weather forecast winds to predict where warm and moist air parcels will travel. The results can be used to better predict where precipitation is likely to happen in the hours after satellite measurements.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
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Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that
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away fromthe Sun, so calculating
across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.
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Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
David R. Thompson, Brian H. Kahn, Philip G. Brodrick, Matthew D. Lebsock, Mark Richardson, and Robert O. Green
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Concentrations of water vapor in the atmosphere vary dramatically over space and time. Mapping this variability can provide insights into atmospheric processes that help us understand atmospheric processes in the Earth system. Here we use a new measurement strategy based on imaging spectroscopy to map atmospheric water vapor concentrations at very small spatial scales. Experiments demonstrate the accuracy of this technique and some initial results from an airborne remote sensing experiment.
Mark Richardson, Matthew D. Lebsock, James McDuffie, and Graeme L. Stephens
Atmos. Meas. Tech., 13, 4947–4961, https://doi.org/10.5194/amt-13-4947-2020, https://doi.org/10.5194/amt-13-4947-2020, 2020
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We previously combined CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar data and reflected-sunlight measurements from OCO-2 (Orbiting Carbon Observatory 2) for information about low clouds over oceans. The satellites are no longer formation-flying, so this work is a step towards getting new information about these clouds using only OCO-2. We can rapidly and accurately identify liquid oceanic clouds and obtain their height better than a widely used passive sensor.
Jui-Lin Frank Li, Mark Richardson, Wei-Liang Lee, Eric Fetzer, Graeme Stephens, Jonathan Jiang, Yulan Hong, Yi-Hui Wang, Jia-Yuh Yu, and Yinghui Liu
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Observed summer Arctic sea ice retreat has been faster than simulated by the average CMIP5 models, most of which exclude falling ice particles from their radiative calculations.
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We retrieve cloud properties, including geometric thickness, by combining hyperspectral Orbiting Carbon Observatory-2 (OCO-2) A-band measurements with CALIPSO lidar. This uses cloudy scene data that are not used in OCO-2's main mission, which is aimed at clear-sky atmospheric CO2 abundance. This is the first retrieval using such hyperspectral information and promises to provide a unique constraint on the properties of low liquid clouds over the ocean.
Mark T. Richardson, Brian H. Kahn, and Peter Kalmus
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Convection over land often triggers hours after a satellite last passed overhead and measured the state of the atmosphere, and during those hours the atmosphere can change greatly. Here we show that it is possible to reconstruct most of those changes by using weather forecast winds to predict where warm and moist air parcels will travel. The results can be used to better predict where precipitation is likely to happen in the hours after satellite measurements.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 15, 117–129, https://doi.org/10.5194/amt-15-117-2022, https://doi.org/10.5194/amt-15-117-2022, 2022
Short summary
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Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that
smears2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is
towardsor
away fromthe Sun, so calculating
across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, https://doi.org/10.5194/amt-14-5555-2021, 2021
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Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
David R. Thompson, Brian H. Kahn, Philip G. Brodrick, Matthew D. Lebsock, Mark Richardson, and Robert O. Green
Atmos. Meas. Tech., 14, 2827–2840, https://doi.org/10.5194/amt-14-2827-2021, https://doi.org/10.5194/amt-14-2827-2021, 2021
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Concentrations of water vapor in the atmosphere vary dramatically over space and time. Mapping this variability can provide insights into atmospheric processes that help us understand atmospheric processes in the Earth system. Here we use a new measurement strategy based on imaging spectroscopy to map atmospheric water vapor concentrations at very small spatial scales. Experiments demonstrate the accuracy of this technique and some initial results from an airborne remote sensing experiment.
Mark Richardson, Matthew D. Lebsock, James McDuffie, and Graeme L. Stephens
Atmos. Meas. Tech., 13, 4947–4961, https://doi.org/10.5194/amt-13-4947-2020, https://doi.org/10.5194/amt-13-4947-2020, 2020
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Short summary
We previously combined CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar data and reflected-sunlight measurements from OCO-2 (Orbiting Carbon Observatory 2) for information about low clouds over oceans. The satellites are no longer formation-flying, so this work is a step towards getting new information about these clouds using only OCO-2. We can rapidly and accurately identify liquid oceanic clouds and obtain their height better than a widely used passive sensor.
Jui-Lin Frank Li, Mark Richardson, Wei-Liang Lee, Eric Fetzer, Graeme Stephens, Jonathan Jiang, Yulan Hong, Yi-Hui Wang, Jia-Yuh Yu, and Yinghui Liu
The Cryosphere, 13, 969–980, https://doi.org/10.5194/tc-13-969-2019, https://doi.org/10.5194/tc-13-969-2019, 2019
Short summary
Short summary
Observed summer Arctic sea ice retreat has been faster than simulated by the average CMIP5 models, most of which exclude falling ice particles from their radiative calculations.
We use controlled CESM1-CAM5 simulations to show for the first time that snowflakes' radiative effects can accelerate sea ice retreat. September retreat rates are doubled above current CO2 levels, highlighting falling ice radiative effects as a high priority for inclusion in future modelling of the Arctic.
Mark Richardson, Jussi Leinonen, Heather Q. Cronk, James McDuffie, Matthew D. Lebsock, and Graeme L. Stephens
Atmos. Meas. Tech., 12, 1717–1737, https://doi.org/10.5194/amt-12-1717-2019, https://doi.org/10.5194/amt-12-1717-2019, 2019
Short summary
Short summary
We retrieve cloud properties, including geometric thickness, by combining hyperspectral Orbiting Carbon Observatory-2 (OCO-2) A-band measurements with CALIPSO lidar. This uses cloudy scene data that are not used in OCO-2's main mission, which is aimed at clear-sky atmospheric CO2 abundance. This is the first retrieval using such hyperspectral information and promises to provide a unique constraint on the properties of low liquid clouds over the ocean.
Brian H. Kahn, Hanii Takahashi, Graeme L. Stephens, Qing Yue, Julien Delanoë, Gerald Manipon, Evan M. Manning, and Andrew J. Heymsfield
Atmos. Chem. Phys., 18, 10715–10739, https://doi.org/10.5194/acp-18-10715-2018, https://doi.org/10.5194/acp-18-10715-2018, 2018
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The Atmospheric Infrared Sounder (AIRS) satellite instrument shows statistically significant global trends in ice cloud properties between September 2002 and August 2016. The trends are not explained by known AIRS instrument limitations. Significant differences in the ice cloud particle size is found between convective clouds and thin ice clouds in the tropics. These results will be a useful benchmark for other studies of global ice cloud properties.
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products
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Climatology of estimated liquid water content and scaling factor for warm clouds using radar–microwave radiometer synergy
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Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
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JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
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Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
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Christian Matar, Céline Cornet, Frédéric Parol, Laurent C.-Labonnote, Frédérique Auriol, and Marc Nicolas
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Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
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The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
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Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
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We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
Anja Hünerbein, Sebastian Bley, Stefan Horn, Hartwig Deneke, and Andi Walther
Atmos. Meas. Tech., 16, 2821–2836, https://doi.org/10.5194/amt-16-2821-2023, https://doi.org/10.5194/amt-16-2821-2023, 2023
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The Multi-Spectral Imager (MSI) on board the EarthCARE satellite will provide the information needed for describing the cloud and aerosol properties in the cross-track direction, complementing the measurements from the Cloud Profiling Radar, Atmospheric Lidar and Broad-Band Radiometer. The accurate discrimination between clear and cloudy pixels is an essential first step. Therefore, the cloud mask algorithm provides a cloud flag, cloud phase and cloud type product for the MSI observations.
Zhipeng Qu, Howard W. Barker, Jason N. S. Cole, and Mark W. Shephard
Atmos. Meas. Tech., 16, 2319–2331, https://doi.org/10.5194/amt-16-2319-2023, https://doi.org/10.5194/amt-16-2319-2023, 2023
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This paper describes EarthCARE’s L2 product ACM-3D. It includes the scene construction algorithm (SCA) used to produce the indexes for reconstructing 3D atmospheric scene based on satellite nadir retrievals. It also provides the information about the buffer zone sizes of 3D assessment domains and the ranking scores for selecting the best 3D assessment domains. These output variables are needed to run 3D radiative transfer models for the radiative closure assessment of EarthCARE’s L2 retrievals.
Steven T. Massie, Heather Cronk, Aronne Merrelli, Sebastian Schmidt, and Steffen Mauceri
Atmos. Meas. Tech., 16, 2145–2166, https://doi.org/10.5194/amt-16-2145-2023, https://doi.org/10.5194/amt-16-2145-2023, 2023
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This paper provides insights into the effects of clouds on Orbiting Carbon Observatory (OCO-2) measurements of CO2. Calculations are carried out that indicate the extent to which this satellite experiment underestimates CO2, due to these cloud effects, as a function of the distance between the surface observation footprint and the nearest cloud. The paper discusses how to lessen the influence of these cloud effects.
Armin Blanke, Andrew J. Heymsfield, Manuel Moser, and Silke Trömel
Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023, https://doi.org/10.5194/amt-16-2089-2023, 2023
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We present an evaluation of current retrieval techniques in the ice phase applied to polarimetric radar measurements with collocated in situ observations of aircraft conducted over the Olympic Mountains, Washington State, during winter 2015. Radar estimates of ice properties agreed most with aircraft observations in regions with pronounced radar signatures, but uncertainties were identified that indicate issues of some retrievals, particularly in warmer temperature regimes.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-44, https://doi.org/10.5194/amt-2023-44, 2023
Revised manuscript accepted for AMT
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We test a new method for measuring the 3D spatial variations of water within clouds using measurements of reflections of the sun's light observed at multiple angles by satellites. This is a great improvement over older methods which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 1803–1847, https://doi.org/10.5194/amt-16-1803-2023, https://doi.org/10.5194/amt-16-1803-2023, 2023
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We describe a new method for measuring the 3D spatial variations in water within clouds using the reflected light of the Sun viewed at multiple different angles by satellites. This is a great improvement over older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Leilei Kou, Zhengjian Lin, Haiyang Gao, Shujun Liao, and Piman Ding
Atmos. Meas. Tech., 16, 1723–1744, https://doi.org/10.5194/amt-16-1723-2023, https://doi.org/10.5194/amt-16-1723-2023, 2023
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Forward modeling of spaceborne millimeter-wave radar composed of eight submodules is presented. We quantify the uncertainties in radar reflectivity that may be caused by the physical model parameters via a sensitivity analysis. The simulations with improved and conventional settings are compared with CloudSat data, and the simulation results are evaluated and analyzed. The results are instructive to the optimization of forward modeling and microphysical parameter retrieval.
Heike Kalesse-Los, Anton Kötsche, Andreas Foth, Johannes Röttenbacher, Teresa Vogl, and Jonas Witthuhn
Atmos. Meas. Tech., 16, 1683–1704, https://doi.org/10.5194/amt-16-1683-2023, https://doi.org/10.5194/amt-16-1683-2023, 2023
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The Virga-Sniffer, a new modular open-source Python package tool to characterize full precipitation evaporation (so-called virga) from ceilometer cloud base height and vertically pointing cloud radar reflectivity time–height fields, is described. Results of its first application to RV Meteor observations during the EUREC4A field experiment in January–February 2020 are shown. About half of all detected clouds with bases below the trade inversion height were found to produce virga.
Yulan Hong, Stephen W. Nesbitt, Robert J. Trapp, and Larry Di Girolamo
Atmos. Meas. Tech., 16, 1391–1406, https://doi.org/10.5194/amt-16-1391-2023, https://doi.org/10.5194/amt-16-1391-2023, 2023
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Deep convective updrafts form overshooting tops (OTs) when they extend into the upper troposphere and lower stratosphere. An OT often indicates hazardous weather conditions. The global distribution of OTs is useful for understanding global severe weather conditions. The Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and Terra satellites provides 2 decades of records on the Earth–atmosphere system with stable orbits, which are used in this study to derive 20-year OT climatology.
Pragya Vishwakarma, Julien Delanoë, Susana Jorquera, Pauline Martinet, Frederic Burnet, Alistair Bell, and Jean-Charles Dupont
Atmos. Meas. Tech., 16, 1211–1237, https://doi.org/10.5194/amt-16-1211-2023, https://doi.org/10.5194/amt-16-1211-2023, 2023
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Cloud observations are necessary to characterize the cloud properties at local and global scales. The observations must be translated to cloud geophysical parameters. This paper presents the estimation of liquid water content (LWC) using radar and microwave radiometer (MWR) measurements. Liquid water path from MWR scales LWC and retrieves the scaling factor (ln a). The retrievals are compared with in situ observations. A climatology of ln a is built to estimate LWC using only radar information.
Bhupendra A. Raut, Paytsar Muradyan, Rajesh Sankaran, Robert C. Jackson, Seongha Park, Sean A. Shahkarami, Dario Dematties, Yongho Kim, Joseph Swantek, Neal Conrad, Wolfgang Gerlach, Sergey Shemyakin, Pete Beckman, Nicola J. Ferrier, and Scott M. Collis
Atmos. Meas. Tech., 16, 1195–1209, https://doi.org/10.5194/amt-16-1195-2023, https://doi.org/10.5194/amt-16-1195-2023, 2023
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We studied the stability of a blockwise phase correlation (PC) method to estimate cloud motion using a total sky imager (TSI). Shorter frame intervals and larger block sizes improve stability, while image resolution and color channels have minor effects. Raindrop contamination can be identified by the rotational motion of the TSI mirror. The correlations of cloud motion vectors (CMVs) from the PC method with wind data vary from 0.38 to 0.59. Optical flow vectors are more stable than PC vectors.
William K. Jones, Matthew W. Christensen, and Philip Stier
Atmos. Meas. Tech., 16, 1043–1059, https://doi.org/10.5194/amt-16-1043-2023, https://doi.org/10.5194/amt-16-1043-2023, 2023
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Geostationary weather satellites have been used to detect storm clouds since their earliest applications. However, this task remains difficult as imaging satellites cannot observe the strong vertical winds that are characteristic of storm clouds. Here we introduce a new method that allows us to detect the early development of storms and continue to track them throughout their lifetime, allowing us to study how their early behaviour affects subsequent weather.
Andrew M. Sayer, Luca Lelli, Brian Cairns, Bastiaan van Diedenhoven, Amir Ibrahim, Kirk D. Knobelspiesse, Sergey Korkin, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 969–996, https://doi.org/10.5194/amt-16-969-2023, https://doi.org/10.5194/amt-16-969-2023, 2023
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This paper presents a method to estimate the height of the top of clouds above Earth's surface using satellite measurements. It is based on light absorption by oxygen in Earth's atmosphere, which darkens the signal that a satellite will see at certain wavelengths of light. Clouds "shield" the satellite from some of this darkening, dependent on cloud height (and other factors), because clouds scatter light at these wavelengths. The method will be applied to the future NASA PACE mission.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
EGUsphere, https://doi.org/10.5194/egusphere-2023-145, https://doi.org/10.5194/egusphere-2023-145, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE L2 processing chain, in which the microphysical retrievals and target classification are performed.
Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 16, 645–667, https://doi.org/10.5194/amt-16-645-2023, https://doi.org/10.5194/amt-16-645-2023, 2023
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In this work, we analyze polarized cloudbow observations by the airborne camera system specMACS to retrieve the cloud droplet size distribution defined by the effective radius (reff) and the effective variance (veff). Two case studies of trade-wind cumulus clouds observed during the EUREC4A field campaign are presented. The results are combined into maps of reff and veff with a very high spatial resolution (100 m × 100 m) that allow new insights into cloud microphysics.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-13, https://doi.org/10.5194/amt-2023-13, 2023
Revised manuscript accepted for AMT
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We show that big liquid droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration of this inertia effect leads to an unrealistic broadening of the simulated radar Doppler spectrum. Based on the physics-based simulation, we propose a new simulator that can generate more consistent radar Doppler spectra compared with observation, providing a valuable tool to decode the cloud microphysics and dynamics properties.
Minrui Wang, Takashi Y. Nakajima, Woosub Roh, Masaki Satoh, Kentaroh Suzuki, Takuji Kubota, and Mayumi Yoshida
Atmos. Meas. Tech., 16, 603–623, https://doi.org/10.5194/amt-16-603-2023, https://doi.org/10.5194/amt-16-603-2023, 2023
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SMILE (a spectral misalignment in which a shift in the center wavelength appears as a distortion in the spectral image) was detected during our recent work. To evaluate how it affects the cloud retrieval products, we did a simulation of EarthCARE-MSI forward radiation, evaluating the error in simulated scenes from a global cloud system-resolving model and a satellite simulator. Our results indicated that the error from SMILE was generally small and negligible for oceanic scenes.
Ming Li, Husi Letu, Hiroshi Ishimoto, Shulei Li, Lei Liu, Takashi Y. Nakajima, Dabin Ji, Huazhe Shang, and Chong Shi
Atmos. Meas. Tech., 16, 331–353, https://doi.org/10.5194/amt-16-331-2023, https://doi.org/10.5194/amt-16-331-2023, 2023
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Influenced by the representativeness of ice crystal scattering models, the existing terahertz ice cloud remote sensing inversion algorithms still have significant uncertainties. We developed an ice cloud remote sensing retrieval algorithm of the ice water path and particle size from aircraft-based terahertz radiation measurements based on the Voronoi model. Validation revealed that the Voronoi model performs better than the sphere and hexagonal column models.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech., 15, 7119–7136, https://doi.org/10.5194/amt-15-7119-2022, https://doi.org/10.5194/amt-15-7119-2022, 2022
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Vertical profiles of latent heating are derived from GOES-16 to be used in convective initialization. They are compared with other latent heating products derived from NEXRAD and GPM satellites, and the results show that their values are very similar to the radar-derived products. Finally, using latent heating derived from GOES-16 for convective initialization shows improvements in precipitation forecasts, which are comparable to the results using latent heating derived from NEXRAD.
Simon Whitburn, Lieven Clarisse, Marc Crapeau, Thomas August, Tim Hultberg, Pierre François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 6653–6668, https://doi.org/10.5194/amt-15-6653-2022, https://doi.org/10.5194/amt-15-6653-2022, 2022
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With more than 15 years of measurements, the IASI radiance dataset is becoming a reference climate data record. Its exploitation for satellite applications requires an accurate and unbiased detection of cloud scenes. Here, we present a new cloud detection algorithm for IASI that is both sensitive and consistent over time. It is based on the use of a neural network, relying on IASI radiance information only and taking as a reference the last version of the operational IASI L2 cloud product.
Wenyu Wang, Zhenzhan Wang, Qiurui He, and Lanjie Zhang
Atmos. Meas. Tech., 15, 6489–6506, https://doi.org/10.5194/amt-15-6489-2022, https://doi.org/10.5194/amt-15-6489-2022, 2022
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This paper uses a neural network approach to retrieve the ice water path from FY-3B/MWHS polarimetric measurements, focusing on its unique 150 GHz quasi-polarized channels. The Level 2 product of CloudSat is used as the reference value for the neural network. The results show that the polarization information is helpful for the retrieval in scenes with thicker cloud ice, and the 150 GHz channels give a significant improvement compared to using only 183 GHz channels.
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
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The article investigates different S5P TROPOMI cloud retrieval algorithms for tropospheric trace gas retrievals. The cloud products show differences primarily over snow and ice and for scenes under sun glint. Some issues regarding across-track dependence are found for the cloud fractions as well as for the cloud heights.
Han Ding, Haoran Li, and Liping Liu
Atmos. Meas. Tech., 15, 6181–6200, https://doi.org/10.5194/amt-15-6181-2022, https://doi.org/10.5194/amt-15-6181-2022, 2022
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In this study, a framework for processing the Doppler spectra observations of a multi-mode pulse compression Ka–Ku cloud radar system is presented. We first proposed an approach to identify and remove the clutter signals in the Doppler spectrum. Then, we developed a new algorithm to remove the range sidelobe at the modes implementing the pulse compression technique. The radar observations from different modes were then merged using the shift-then-average method.
Andrew T. Prata, Roy G. Grainger, Isabelle A. Taylor, Adam C. Povey, Simon R. Proud, and Caroline A. Poulsen
Atmos. Meas. Tech., 15, 5985–6010, https://doi.org/10.5194/amt-15-5985-2022, https://doi.org/10.5194/amt-15-5985-2022, 2022
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Satellite observations are often used to track ash clouds and estimate their height, particle sizes and mass; however, satellite-based techniques are always associated with some uncertainty. We describe advances in a satellite-based technique that is used to estimate ash cloud properties for the June 2019 Raikoke (Russia) eruption. Our results are significant because ash warning centres increasingly require uncertainty information to correctly interpret,
aggregate and utilise the data.
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
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Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger
Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, https://doi.org/10.5194/amt-15-5415-2022, 2022
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Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
Willi Schimmel, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert
Atmos. Meas. Tech., 15, 5343–5366, https://doi.org/10.5194/amt-15-5343-2022, https://doi.org/10.5194/amt-15-5343-2022, 2022
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This study introduces the novel Doppler radar spectra-based machine learning approach VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn). VOODOO is a powerful probability-based extension to the existing Cloudnet hydrometeor target classification, enabling the detection of liquid-bearing cloud layers beyond complete lidar attenuation via user-defined p* threshold. VOODOO performs best for (multi-layer) stratiform and deep mixed-phase clouds with liquid water path > 100 g m−2.
Vikas Nataraja, Sebastian Schmidt, Hong Chen, Takanobu Yamaguchi, Jan Kazil, Graham Feingold, Kevin Wolf, and Hironobu Iwabuchi
Atmos. Meas. Tech., 15, 5181–5205, https://doi.org/10.5194/amt-15-5181-2022, https://doi.org/10.5194/amt-15-5181-2022, 2022
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A convolutional neural network (CNN) is introduced to retrieve cloud optical thickness (COT) from passive cloud imagery. The CNN, trained on large eddy simulations from the Sulu Sea, learns from spatial information at multiple scales to reduce cloud inhomogeneity effects. By considering the spatial context of a pixel, the CNN outperforms the traditional independent pixel approximation (IPA) across several cloud morphology metrics.
Rachel T. Pinker, Yingtao Ma, Wen Chen, Istvan Laszlo, Hongqing Liu, Hye-Yun Kim, and Jaime Daniels
Atmos. Meas. Tech., 15, 5077–5094, https://doi.org/10.5194/amt-15-5077-2022, https://doi.org/10.5194/amt-15-5077-2022, 2022
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Scene-dependent narrow-to-broadband transformations are developed to facilitate the use of observations from the Advanced Baseline Imager (ABI), the primary instrument on GOES-R, to derive surface shortwave radiative fluxes. This is a first NOAA product at the high resolution of about 5 k over the contiguous United States (CONUS) region. The product is archived and can be downloaded from the NOAA Comprehensive Large Array-data Stewardship System (CLASS).
Mariko Oue, Stephen M. Saleeby, Peter J. Marinescu, Pavlos Kollias, and Susan C. van den Heever
Atmos. Meas. Tech., 15, 4931–4950, https://doi.org/10.5194/amt-15-4931-2022, https://doi.org/10.5194/amt-15-4931-2022, 2022
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This study provides an optimization of radar observation strategies to better capture convective cell evolution in clean and polluted environments as well as a technique for the optimization. The suggested optimized radar observation strategy is to better capture updrafts at middle and upper altitudes and precipitation particle evolution of isolated deep convective clouds. This study sheds light on the challenge of designing remote sensing observation strategies in pre-field campaign periods.
Jean-Marie Lalande, Guillaume Bourmaud, Pierre Minvielle, and Jean-François Giovannelli
Atmos. Meas. Tech., 15, 4411–4429, https://doi.org/10.5194/amt-15-4411-2022, https://doi.org/10.5194/amt-15-4411-2022, 2022
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In this paper we describe the implementation of an interpolation–prediction estimator applied to cloud properties derived from CloudSat observations. The objective is to evaluate the uncertainty associated with the estimated quantity. The model developed in this study can be valuable for satellite applications (GPS, telecommunication) as well as for cloud product comparisons. This paper is didactic and beneficial for anyone interested in kriging estimators.
Julia Fuchs, Hendrik Andersen, Jan Cermak, Eva Pauli, and Rob Roebeling
Atmos. Meas. Tech., 15, 4257–4270, https://doi.org/10.5194/amt-15-4257-2022, https://doi.org/10.5194/amt-15-4257-2022, 2022
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Two cloud-masking approaches, a local and a regional approach, using high-resolution satellite data are developed and validated for the region of Paris to improve applicability for analyses of urban effects on low clouds. We found that cloud masks obtained from the regional approach are more appropriate for the high-resolution analysis of locally induced cloud processes. Its applicability is tested for the analysis of typical fog conditions over different surface types.
Eleni Tetoni, Florian Ewald, Martin Hagen, Gregor Köcher, Tobias Zinner, and Silke Groß
Atmos. Meas. Tech., 15, 3969–3999, https://doi.org/10.5194/amt-15-3969-2022, https://doi.org/10.5194/amt-15-3969-2022, 2022
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We use the C-band POLDIRAD and the Ka-band MIRA-35 to perform snowfall dual-wavelength polarimetric radar measurements. We develop an ice microphysics retrieval for mass, apparent shape, and median size of the particle size distribution by comparing observations to T-matrix ice spheroid simulations while varying the mass–size relationship. We furthermore show how the polarimetric measurements from POLDIRAD help to narrow down ambiguities between ice particle shape and size.
Assia Arouf, Hélène Chepfer, Thibault Vaillant de Guélis, Marjolaine Chiriaco, Matthew D. Shupe, Rodrigo Guzman, Artem Feofilov, Patrick Raberanto, Tristan S. L'Ecuyer, Seiji Kato, and Michael R. Gallagher
Atmos. Meas. Tech., 15, 3893–3923, https://doi.org/10.5194/amt-15-3893-2022, https://doi.org/10.5194/amt-15-3893-2022, 2022
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We proposed new estimates of the surface longwave (LW) cloud radiative effect (CRE) derived from observations collected by a space-based lidar on board the CALIPSO satellite and radiative transfer computations. Our estimate appropriately captures the surface LW CRE annual variability over bright polar surfaces, and it provides a dataset more than 13 years long.
Baike Xi, Xiquan Dong, Xiaojian Zheng, and Peng Wu
Atmos. Meas. Tech., 15, 3761–3777, https://doi.org/10.5194/amt-15-3761-2022, https://doi.org/10.5194/amt-15-3761-2022, 2022
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This study develops an innovative method to determine the cloud phases over the Southern Ocean (SO) using the combination of radar and lidar measurements during the ship-based field campaign of MARCUS. Results from our study show that the low-level, deep, and shallow cumuli are dominant, and the mixed-phase clouds occur more than single phases over the SO. The mixed-phase cloud properties are similar to liquid-phase (ice-phase) clouds in the midlatitudes (polar) region of the SO.
Adrien Guyot, Alain Protat, Simon P. Alexander, Andrew R. Klekociuk, Peter Kuma, and Adrian McDonald
Atmos. Meas. Tech., 15, 3663–3681, https://doi.org/10.5194/amt-15-3663-2022, https://doi.org/10.5194/amt-15-3663-2022, 2022
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Ceilometers are instruments that are widely deployed as part of operational networks. They are usually not able to detect cloud phase. Here, we propose an evaluation of various methods to detect supercooled liquid water with ceilometer observations, using an extensive dataset from Davis, Antarctica. Our results highlight the possibility for ceilometers to detect supercooled liquid water in clouds.
Xiaotong Li, Baozhu Wang, Bo Qiu, and Chao Wu
Atmos. Meas. Tech., 15, 3629–3639, https://doi.org/10.5194/amt-15-3629-2022, https://doi.org/10.5194/amt-15-3629-2022, 2022
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The all-sky camera images can reflect the local cloud cover, which is considerable for astronomical observatory site selection. Therefore, the realization of automatic classification of the images is very important. In this paper, three cloud cover features are proposed to classify the images. The proposed method is evaluated on a large dataset, and the method achieves an accuracy of 96.58 % and F1_score of 96.24 %, which greatly improves the efficiency of automatic processing of the images.
Huige Di, Yun Yuan, Qing Yan, Wenhui Xin, Shichun Li, Jun Wang, Yufeng Wang, Lei Zhang, and Dengxin Hua
Atmos. Meas. Tech., 15, 3555–3567, https://doi.org/10.5194/amt-15-3555-2022, https://doi.org/10.5194/amt-15-3555-2022, 2022
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It is necessary to correctly evaluate the amount of cloud water resources in an area. Currently, there is a lack of effective observation methods for atmospheric column condensate evaluation. We propose a method for atmospheric column condensate by combining millimetre cloud radar, lidar and microwave radiometers. The method can realise determination of atmospheric column condensate. The variation of cloud before precipitation is considered, and the atmospheric column is deduced and obtained.
Daniel Robbins, Caroline Poulsen, Steven Siems, and Simon Proud
Atmos. Meas. Tech., 15, 3031–3051, https://doi.org/10.5194/amt-15-3031-2022, https://doi.org/10.5194/amt-15-3031-2022, 2022
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A neural network (NN)-based cloud mask for a geostationary satellite instrument, AHI, is developed using collocated data and is better at not classifying thick aerosols as clouds versus the Japanese Meteorological Association and the Bureau of Meteorology masks, identifying 1.13 and 1.29 times as many non-cloud pixels than each mask, respectively. The improvement during the day likely comes from including the shortest wavelength bands from AHI in the NN mask, which the other masks do not use.
Pascal Marquet, Pauline Martinet, Jean-François Mahfouf, Alina Lavinia Barbu, and Benjamin Ménétrier
Atmos. Meas. Tech., 15, 2021–2035, https://doi.org/10.5194/amt-15-2021-2022, https://doi.org/10.5194/amt-15-2021-2022, 2022
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Two conservative thermodynamic variables (moist-air entropy potential temperature and total water content) are introduced into a one-dimensional EnVar data assimilation system to demonstrate their benefit for future operational assimilation schemes, with the use of microwave brightness temperatures from a ground-based radiometer installed during the field campaign SOFGO3D. Results show that the brightness temperatures analysed with the new variables are improved, including the liquid water.
Valery Shcherbakov, Frédéric Szczap, Alaa Alkasem, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech., 15, 1729–1754, https://doi.org/10.5194/amt-15-1729-2022, https://doi.org/10.5194/amt-15-1729-2022, 2022
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We performed extensive Monte Carlo (MC) simulations of lidar signals and developed an empirical model to account for the multiple scattering in the lidar signals. The simulations have taken into consideration four types of lidar configurations (the ground based, the airborne, the CALIOP, and the ATLID) and four types of particles (coarse aerosol, water cloud, jet-stream cirrus, and cirrus).
The empirical model has very good quality of MC data fitting for all considered cases.
Alexander Myagkov and Davide Ori
Atmos. Meas. Tech., 15, 1333–1354, https://doi.org/10.5194/amt-15-1333-2022, https://doi.org/10.5194/amt-15-1333-2022, 2022
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This study provides equations to characterize random errors of spectral polarimetric observations from cloud radars. The results can be used for a broad spectrum of applications. For instance, accurate error characterization is essential for advanced retrievals of microphysical properties of clouds and precipitation. Moreover, error characterization allows for the use of measurements from polarimetric cloud radars to potentially improve weather forecasts.
Yuli Liu and Gerald G. Mace
Atmos. Meas. Tech., 15, 927–944, https://doi.org/10.5194/amt-15-927-2022, https://doi.org/10.5194/amt-15-927-2022, 2022
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We propose a suite of Bayesian algorithms for synergistic radar and radiometer retrievals to evaluate the next-generation NASA Cloud, Convection and Precipitation (CCP) observing system. The algorithms address pixel-level retrievals using active-only, passive-only, and synergistic active–passive observations. Novel techniques in developing synergistic algorithms are presented. Quantitative assessments of the CCP observing system's capability in retrieving ice cloud microphysics are provided.
Cited articles
Baum, B. A., Menzel, W. P., Frey, R. A., Tobin, D. C., Holz, R. E., Ackerman,
S. A., Heidinger, A. K., and Yang, P.: MODIS Cloud-Top Property Refinements
for Collection 6, J. Appl. Meteorol. Clim., 51, 1145–1163,
https://doi.org/10.1175/JAMC-D-11-0203.1, 2012.
Bennartz, R.: Global assessment of marine boundary layer cloud droplet number
concentration from satellite, J. Geophys. Res., 112, D02201,
https://doi.org/10.1029/2006JD007547, 2007.
Boesch, H., Brown, L., Castano, R., Christi, M., Connor, B., Crisp, D.,
Eldering, A., Fisher, B., Frankenberg, C., Gunson, M., Granat, R., McDuffie,
J., Miller, C., Natraj, V., O'Brien, D., O'Dell, C., Osterman, G., Oyafuso,
F., Payne, V., Polonsky, I., Smyth, M., Spurr, R., Thompson, D., and Toon,
G.: Orbiting Carbon Observatory (OCO)-2 Level 2 Full Physics Algorithm
Theoretical Basis Document, Pasadena, CA, available at:
https://disc.gsfc.nasa.gov/OCO-2/documentation/oco-2-v6/OCO2_L2_ATBD.V6.pdf
(last access: 5 March 2018), 2015.
Bony, S. and Dufresne, J.-L.: Marine boundary layer clouds at the heart of
tropical cloud feedback uncertainties in climate models, Geophys. Res. Lett.,
32, L20806, https://doi.org/10.1029/2005GL023851, 2005.
Borg, L. A. and Bennartz, R.: Vertical structure of stratiform marine
boundary layer clouds and its impact on cloud albedo, Geophys. Res. Lett.,
34, L05807, https://doi.org/10.1029/2006GL028713, 2007.
Brenguier, J.: Parameterization of the Condensation Process: A Theoretical
Approach, J. Atmos. Sci., 48, 264–282,
https://doi.org/10.1175/1520-0469(1991)048<0264:POTCPA>2.0.CO;2, 1991.
Chang, K.-W., L'Ecuyer, T. S., Kahn, B. H., and Natraj, V.: Information
content of visible and midinfrared radiances for retrieving tropical ice
cloud properties, J. Geophys. Res.-Atmos., 122, 4944–4966,
https://doi.org/10.1002/2016JD026357, 2017.
Crisp, D.: NASA Orbiting Carbon Observatory: measuring the column averaged
carbon dioxide mole fraction from space, J. Appl. Remote Sens., 2, 23508,
https://doi.org/10.1117/1.2898457, 2008.
Crisp, D., Pollock, H. R., Rosenberg, R., Chapsky, L., Lee, R. A. M.,
Oyafuso, F. A., Frankenberg, C., O'Dell, C. W., Bruegge, C. J., Doran, G. B.,
Eldering, A., Fisher, B. M., Fu, D., Gunson, M. R., Mandrake, L., Osterman,
G. B., Schwandner, F. M., Sun, K., Taylor, T. E., Wennberg, P. O., and Wunch,
D.: The on-orbit performance of the Orbiting Carbon Observatory-2 (OCO-2)
instrument and its radiometrically calibrated products, Atmos. Meas. Tech.,
10, 59–81, https://doi.org/10.5194/amt-10-59-2017, 2017.
Deschamps, P.-Y., Breon, F.-M., Leroy, M., Podaire, A., Bricaud, A., Buriez,
J.-C., and Seze, G.: The POLDER mission: instrument characteristics and
scientific objectives, IEEE T. Geosci. Remote, 32, 598–615,
https://doi.org/10.1109/36.297978, 1994.
Desmons, M., Ferlay, N., Parol, F., Mcharek, L., and Vanbauce, C.: Improved
information about the vertical location and extent of monolayer clouds from
POLDER3 measurements in the oxygen A-band, Atmos. Meas. Tech., 6, 2221–2238,
https://doi.org/10.5194/amt-6-2221-2013, 2013.
Devasthale, A. and Thomas, M. A.: A global survey of aerosol-liquid water
cloud overlap based on four years of CALIPSO-CALIOP data, Atmos. Chem. Phys.,
11, 1143–1154, https://doi.org/10.5194/acp-11-1143-2011, 2011.
Ding, S., Wang, J., and Xu, X.: Polarimetric remote sensing in oxygen A and B
bands: sensitivity study and information content analysis for vertical
profile of aerosols, Atmos. Meas. Tech., 9, 2077–2092,
https://doi.org/10.5194/amt-9-2077-2016, 2016.
Divakarla, M. G., Barnet, C. D., Goldberg, M. D., McMillin, L. M., Maddy, E.,
Wolf, W., Zhou, L., and Liu, X.: Validation of Atmospheric Infrared Sounder
temperature and water vapor retrievals with matched radiosonde measurements
and forecasts, J. Geophys. Res., 111, D09S15, https://doi.org/10.1029/2005JD006116, 2006.
Eldering, A., O'Dell, C. W., Wennberg, P. O., Crisp, D., Gunson, M. R.,
Viatte, C., Avis, C., Braverman, A., Castano, R., Chang, A., Chapsky, L.,
Cheng, C., Connor, B., Dang, L., Doran, G., Fisher, B., Frankenberg, C., Fu,
D., Granat, R., Hobbs, J., Lee, R. A. M., Mandrake, L., McDuffie, J., Miller,
C. E., Myers, V., Natraj, V., O'Brien, D., Osterman, G. B., Oyafuso, F.,
Payne, V. H., Pollock, H. R., Polonsky, I., Roehl, C. M., Rosenberg, R.,
Schwandner, F., Smyth, M., Tang, V., Taylor, T. E., To, C., Wunch, D., and
Yoshimizu, J.: The Orbiting Carbon Observatory-2: first 18 months of science
data products, Atmos. Meas. Tech., 10, 549–563,
https://doi.org/10.5194/amt-10-549-2017, 2017.
Ferlay, N., Thieuleux, F., Cornet, C., Davis, A. B., Dubuisson, P., Ducos,
F., Parol, F., Riédi, J., and Vanbauce, C.: Toward New Inferences about
Cloud Structures from Multidirectional Measurements in the Oxygen A Band:
Middle-of-Cloud Pressure and Cloud Geometrical Thickness from
POLDER-3/PARASOL, J. Appl. Meteorol. Clim., 49, 2492–2507,
https://doi.org/10.1175/2010JAMC2550.1, 2010.
Fischer, J. and Grassl, H.: Detection of Cloud-Top Height from Backscattered
Radiances within the Oxygen A Band. Part 1: Theoretical Study, J. Appl.
Meteorol., 30, 1245–1259,
https://doi.org/10.1175/1520-0450(1991)030<1245:DOCTHF>2.0.CO;2,
1991.
Flatau, P. J. and Stephens, G. L.: On the fundamental solution of the
radiative transfer equation, J. Geophys. Res., 93, 11037,
https://doi.org/10.1029/JD093iD09p11037, 1988.
Frankenberg, C., O'Dell, C., Berry, J., Guanter, L., Joiner, J., Köhler,
P., Pollock, R., and Taylor, T. E.: Prospects for chlorophyll fluorescence
remote sensing from the Orbiting Carbon Observatory-2, Remote Sens. Environ.,
147, 1–12, https://doi.org/10.1016/j.rse.2014.02.007, 2014.
Hanel, R. A.: Determination of cloud altitude from a satellite, J. Geophys.
Res., 66, 1300–1300, https://doi.org/10.1029/JZ066i004p01300, 1961.
Heidinger, A. K. and Stephens, G. L.: Molecular Line Absorption in a
Scattering Atmosphere. Part II: Application to Remote Sensing in the O2
A band, J. Atmos. Sci., 57, 1615–1634,
https://doi.org/10.1175/1520-0469(2000)057<1615:MLAIAS>2.0.CO;2, 2000.
Herman, B. M.: Infra-red absorption, scattering, and total attenuation
cross-sections for water spheres, Q. J. Roy. Meteor. Soc., 88, 143–150,
https://doi.org/10.1002/qj.49708837604, 1962.
Huang, Y., Siems, S. T., Manton, M. J., Hande, L. B., and Haynes, J. M.: The
Structure of Low-Altitude Clouds over the Southern Ocean as Seen by CloudSat,
J. Climate, 25, 2535–2546, https://doi.org/10.1175/JCLI-D-11-00131.1, 2012.
Koelemeijer, R. B. A., Stammes, P., Hovenier, J. W., and de Haan, J. F.: A
fast method for retrieval of cloud parameters using oxygen A band
measurements from the Global Ozone Monitoring Experiment, J. Geophys.
Res.-Atmos., 106, 3475–3490, https://doi.org/10.1029/2000JD900657, 2001.
L'Ecuyer, T. S. and Jiang, J. H.: Touring the atmosphere aboard the A-Train,
Phys. Today, 63, 36–41, https://doi.org/10.1063/1.3463626, 2010.
Li, J., Huang, J., Stamnes, K., Wang, T., Lv, Q., and Jin, H.: A global
survey of cloud overlap based on CALIPSO and CloudSat measurements, Atmos.
Chem. Phys., 15, 519–536, https://doi.org/10.5194/acp-15-519-2015, 2015.
Mahfouf, J.-F., Birman, C., Aires, F., Prigent, C., Orlandi, E., and Milz,
M.: Information content on temperature and water vapour from a hyper-spectral
microwave sensor, Q. J. Roy. Meteor. Soc., 141, 3268–3284,
https://doi.org/10.1002/qj.2608, 2015.
Martinet, P., Lavanant, L., Fourrié, N., Rabier, F. and Gambacorta, A.:
Evaluation of a revised IASI channel selection for cloudy retrievals with a
focus on the Mediterranean basin, Q. J. Roy. Meteor. Soc., 140, 1563–1577,
https://doi.org/10.1002/qj.2239, 2014.
Merlin, G., Riedi, J., Labonnote, L. C., Cornet, C., Davis, A. B., Dubuisson,
P., Desmons, M., Ferlay, N., and Parol, F.: Cloud information content
analysis of multi-angular measurements in the oxygen A-band: application to
3MI and MSPI, Atmos. Meas. Tech., 9, 4977–4995,
https://doi.org/10.5194/amt-9-4977-2016, 2016.
Miles, N. L., Verlinde, J., and Clothiaux, E. E.: Cloud Droplet Size
Distributions in Low-Level Stratiform Clouds, J. Atmos. Sci., 57, 295–311,
https://doi.org/10.1175/1520-0469(2000)057<0295:CDSDIL>2.0.CO;2, 2000.
Min, Q.-L., Harrison, L. C., Kiedron, P., Berndt, J., and Joseph, E.: A
high-resolution oxygen A-band and water vapor band spectrometer, J. Geophys.
Res., 109, D02202, https://doi.org/10.1029/2003JD003540, 2004.
Munro, R., Lang, R., Klaes, D., Poli, G., Retscher, C., Lindstrot, R.,
Huckle, R., Lacan, A., Grzegorski, M., Holdak, A., Kokhanovsky, A.,
Livschitz, J., and Eisinger, M.: The GOME-2 instrument on the Metop series of
satellites: instrument design, calibration, and level 1 data processing – an
overview, Atmos. Meas. Tech., 9, 1279–1301,
https://doi.org/10.5194/amt-9-1279-2016, 2016.
Nakajima, T. and King, M. D.: Determination of the Optical Thickness and
Effective Particle Radius of Clouds from Reflected Solar Radiation
Measurements. Part I: Theory, J. Atmos. Sci., 47, 1878–1893,
https://doi.org/10.1175/1520-0469(1990)047<1878:DOTOTA>2.0.CO;2, 1990.
Natraj, V. and Spurr, R. J. D.: A fast linearized pseudo-spherical two orders
of scattering model to account for polarization in vertically inhomogeneous
scattering–absorbing media, J. Quant. Spectrosc. Ra., 107, 263–293,
https://doi.org/10.1016/j.jqsrt.2007.02.011, 2007.
O'Brien, D. M. and Mitchell, R. M.: Error Estimates for Retrieval of
Cloud-Top Pressure Using Absorption in the A Band of Oxygen, J. Appl.
Meteorol., 31, 1179–1192,
https://doi.org/10.1175/1520-0450(1992)031<1179:EEFROC>2.0.CO;2, 1992.
OCO-2 Science Team, Gunson, M., and Eldering, A.: OCO-2 Level 1B calibrated,
geolocated science spectra, Retrospective Processing V8r, Greenbelt, MD, USA,
Goddard Earth Sciences Data and Information Services Center (GES DISC),
https://doi.org/10.5067/1RJW1YMLW2F0, 2017.
O'Dell, C. W.: Acceleration of multiple-scattering, hyperspectral radiative
transfer calculations via low-streams interpolation, J. Geophys. Res., 115,
D10206, https://doi.org/10.1029/2009JD012803, 2010.
Osterman, G. B., Eldering, A., Avis, C., Chafin, B., O'Dell, C. W.,
Frankenberg, C., Fisher, B. M., Mandrake, L., Wunch, D., Granat, R., and
Crisp, D.: Orbiting Carbon Observatory-2 (OCO-2) Data Product User's Guide,
Operational L1 and L2 Data Versions 7 and 7R, Jet Propulsion Laboratory,
Pasadena, CA, USA, 2016.
Platnick, S., Ackerman, S. A., King, M. D., Meyer, K., Menzel, W. P., Holz,
R. E., Baum, B. A., and Yang, P.: MODIS atmosphere L2 cloud product (06_L2),
Goddard Space Flight Center, Greenbelt, MA, USA,
https://doi.org/10.5067/MODIS/MYD06_L2.006, 2015.
Rabier, F., Fourrié, N., Chafaï, D., and Prunet, P.: Channel
selection methods for Infrared Atmospheric Sounding Interferometer radiances,
Q. J. Roy. Meteor. Soc., 128, 1011–1027, https://doi.org/10.1256/0035900021643638, 2002.
Richardson, M., McDuffie, J., Stephens, G. L., Cronk, H. Q., and Taylor, T.
E.: The OCO-2 oxygen A-band response to liquid marine cloud properties from
CALIPSO and MODIS, J. Geophys. Res.-Atmos., 122, 8255–8275,
https://doi.org/10.1002/2017JD026561, 2017.
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding Theory and Practice,
World Scientific, Singapore, 2000.
Rozanov, V. V. and Kokhanovsky, A. A.: Semianalytical cloud retrieval
algorithm as applied to the cloud top altitude and the cloud geometrical
thickness determination from top-of-atmosphere reflectance measurements in
the oxygen A band, J. Geophys. Res., 109, D05202, https://doi.org/10.1029/2003JD004104,
2004.
Schuessler, O., Loyola Rodriguez, D. G., Doicu, A., and Spurr, R.:
Information Content in the Oxygen A-Band for the Retrieval of Macrophysical
Cloud Parameters, IEEE T. Geosci. Remote, 52, 3246–3255,
https://doi.org/10.1109/TGRS.2013.2271986, 2014.
Shannon, C. and Weaver, W.: The Mathematical Theory of Communication, Univ.
of Illinois Press, Urbana, IL, USA, 1949.
Spurr, R. J. D.: VLIDORT: A linearized pseudo-spherical vector discrete
ordinate radiative transfer code for forward model and retrieval studies in
multilayer multiple scattering media, J. Quant. Spectrosc. Ra., 102,
316–342, https://doi.org/10.1016/j.jqsrt.2006.05.005, 2006.
Spurr, R. J. D., Kurosu, T. P., and Chance, K. V.: A linearized discrete
ordinate radiative transfer model for atmospheric remote-sensing retrieval,
J. Quant. Spectrosc. Ra., 68, 689–735, https://doi.org/10.1016/S0022-4073(00)00055-8,
2001.
Stephens, G. L.: Radiation Profiles in Extended Water Clouds.
II: Parameterization Schemes, J. Atmos. Sci., 35, 2123–2132,
https://doi.org/10.1175/1520-0469(1978)035<2123:RPIEWC>2.0.CO;2, 1978.
Stephens, G. L. and Heidinger, A.: Molecular Line Absorption in a Scattering
Atmosphere. Part I: Theory, J. Atmos. Sci., 57, 1599–1614,
https://doi.org/10.1175/1520-0469(2000)057<1599:MLAIAS>2.0.CO;2,
2000.
Stephens, G. L., Vane, D. G., Tanelli, S., Im, E., Durden, S., Rokey, M.,
Reinke, D., Partain, P., Mace, G. G., Austin, R., L'Ecuyer, T., Haynes, J.,
Lebsock, M., Suzuki, K., Waliser, D., Wu, D., Kay, J., Gettelman, A., Wang,
Z., and Marchand, R.: CloudSat mission: Performance and early science after
the first year of operation, J. Geophys. Res., 113, D00A18,
https://doi.org/10.1029/2008JD009982, 2008.
Szczodrak, M., Austin, P. H., and Krummel, P. B.: Variability of Optical
Depth and Effective Radius in Marine Stratocumulus Clouds, J. Atmos. Sci.,
58, 2912–2926,
https://doi.org/10.1175/1520-0469(2001)058<2912:VOODAE>2.0.CO;2, 2001.
Taylor, T. E., O'Dell, C. W., Frankenberg, C., Partain, P. T., Cronk, H. Q.,
Savtchenko, A., Nelson, R. R., Rosenthal, E. J., Chang, A. Y., Fisher, B.,
Osterman, G. B., Pollock, R. H., Crisp, D., Eldering, A., and Gunson, M. R.:
Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation
against collocated MODIS and CALIOP data, Atmos. Meas. Tech., 9, 973–989,
https://doi.org/10.5194/amt-9-973-2016, 2016.
Vanbauce, C., Buriez, J. C., Parol, F., Bonnel, B., Sèze, G., and
Couvert, P.: Apparent pressure derived from ADEOS-POLDER observations in the
oxygen A-band over ocean, Geophys. Res. Lett., 25, 3159–3162,
https://doi.org/10.1029/98GL02324, 1998.
Vaughan, M. A., Powell, K. A., Winker, D. M., Hostetler, C. A., Kuehn, R. E.,
Hunt, W. H., Getzewich, B. J., Young, S. A., Liu, Z., and McGill, M. J.:
Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar
Measurements, J. Atmos. Ocean. Tech., 26, 2034–2050,
https://doi.org/10.1175/2009JTECHA1228.1, 2009.
Vidot, J., Bennartz, R., O'Dell, C. W., Preusker, R., Lindstrot, R., and
Heidinger, A. K.: CO2 Retrieval over Clouds from the OCO Mission: Model
Simulations and Error Analysis, J. Atmos. Ocean. Tech., 26, 1090–1104,
https://doi.org/10.1175/2009JTECHA1200.1, 2009.
Winker, D. M., Pelon, J., Coakley, J. A., Ackerman, S. A., Charlson, R. J.,
Colarco, P. R., Flamant, P., Fu, Q., Hoff, R. M., Kittaka, C., Kubar, T. L.,
Le Treut, H., McCormick, M. P., Mégie, G., Poole, L., Powell, K., Trepte,
C., Vaughan, M. A., and Wielicki, B. A.: The CALIPSO Mission: A Global 3D
View of Aerosols and Clouds, B. Am. Meteorol. Soc., 91, 1211–1229,
https://doi.org/10.1175/2010BAMS3009.1, 2010.
Wood, R. and Hartmann, D. L.: Spatial Variability of Liquid Water Path in
Marine Low Cloud: The Importance of Mesoscale Cellular Convection, J.
Climate, 19, 1748–1764, https://doi.org/10.1175/JCLI3702.1, 2006.
Yamamoto, G. and Wark, D. Q.: Discussion of the letter by R. A. Hanel,
“Determination of cloud altitude from a satellite”, J. Geophys. Res., 66,
3596–3596, https://doi.org/10.1029/JZ066i010p03596, 1961.
Yang, Y., Marshak, A., Mao, J., Lyapustin, A., and Herman, J.: A method of
retrieving cloud top height and cloud geometrical thickness with oxygen A and
B bands for the Deep Space Climate Observatory (DSCOVR) mission: Radiative
transfer simulations, J. Quant. Spectrosc. Ra., 122, 141–149,
https://doi.org/10.1016/j.jqsrt.2012.09.017, 2013.
Zelinka, M. D., Klein, S. A., and Hartmann, D. L.: Computing and Partitioning
Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative
Kernels, J. Climate, 25, 3715–3735, https://doi.org/10.1175/JCLI-D-11-00248.1, 2012.
Short summary
This study analyses how much information can be obtained about liquid clouds over oceans using measurements of reflected sunlight by the OCO-2 satellite. We find that using 75 of the 853 functioning oxygen A-band channels is sufficient to retrieve cloud optical depth, and the height and thickness of the cloud in terms of atmospheric pressure coordinates, to better than 3 hPa.
This study analyses how much information can be obtained about liquid clouds over oceans using...
