Articles | Volume 13, issue 6
https://doi.org/10.5194/acp-13-3133-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-13-3133-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
15 Mar 2013
Research article |
| 15 Mar 2013
Quantitative comparison of the variability in observed and simulated shortwave reflectance
Y. L. Roberts
Department of Atmospheric and Oceanic Science, University of Colorado – Boulder, Boulder, CO, USA
Laboratory of Atmospheric and Space Science, Boulder, CO, USA
NASA Langley Research Center, Hampton, VA, USA
P. Pilewskie
Department of Atmospheric and Oceanic Science, University of Colorado – Boulder, Boulder, CO, USA
Laboratory of Atmospheric and Space Science, Boulder, CO, USA
B. C. Kindel
Laboratory of Atmospheric and Space Science, Boulder, CO, USA
D. R. Feldman
Lawrence Berkeley National Lab, Berkeley, CA, USA
W. D. Collins
Lawrence Berkeley National Lab, Berkeley, CA, USA
Department of Earth and Planetary Science, University of California – Berkeley, Berkeley, CA, USA
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Ankur Mahesh, William Collins, Boris Bonev, Noah Brenowitz, Yair Cohen, Joshua Elms, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis O'Brien, Michael Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, and Jared Willard
EGUsphere, https://doi.org/10.48550/arXiv.2408.03100, https://doi.org/10.48550/arXiv.2408.03100, 2024
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Simulating extreme weather events in a warming world is a challenging task for current weather and climate models. These models' computational cost poses a challenge in studying low-probability extreme weather. We use machine learning to construct a new probabilistic system. We explain in-depth how we constructed this system. We present a thorough pipeline to validate our method. Our method requires fewer computational resources than existing weather and climate models.
Ankur Mahesh, William Collins, Boris Bonev, Noah Brenowitz, Yair Cohen, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis A. O'Brien, Michael Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, and Jared Willard
EGUsphere, https://doi.org/10.48550/arXiv.2408.01581, https://doi.org/10.48550/arXiv.2408.01581, 2024
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We use machine learning to create a massive database of simulated weather extremes. This database provides a large sample size, which is essential to characterize the statistics of extreme weather events and study their physical mechanisms. Also, such large simulations can be beneficial to accurately forecast the probability of low-likelihood extreme weather.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
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Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Jake J. Gristey, K. Sebastian Schmidt, Hong Chen, Daniel R. Feldman, Bruce C. Kindel, Joshua Mauss, Mathew van den Heever, Maria Z. Hakuba, and Peter Pilewskie
Atmos. Meas. Tech., 16, 3609–3630, https://doi.org/10.5194/amt-16-3609-2023, https://doi.org/10.5194/amt-16-3609-2023, 2023
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The concept of a satellite-based camera is demonstrated for sampling the angular distribution of outgoing radiance from Earth needed to generate data products for new radiation budget spectral channels.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
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The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Michal Segal Rozenhaimer, Meloë Kacenelenbogen, Yohei Shinozuka, Connor Flynn, Rich Ferrare, Sharon Burton, Chris Hostetler, Marc Mallet, and Paquita Zuidema
Atmos. Meas. Tech., 15, 61–77, https://doi.org/10.5194/amt-15-61-2022, https://doi.org/10.5194/amt-15-61-2022, 2022
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This work presents heating rates derived from aircraft observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS). We separate the total heating rates into aerosol and gas (primarily water vapor) absorption and explore some of the co-variability of heating rate profiles and their primary drivers, leading to the development of a new concept: the heating rate efficiency (HRE; the heating rate per unit aerosol extinction).
Hong Chen, Sebastian Schmidt, Michael D. King, Galina Wind, Anthony Bucholtz, Elizabeth A. Reid, Michal Segal-Rozenhaimer, William L. Smith, Patrick C. Taylor, Seiji Kato, and Peter Pilewskie
Atmos. Meas. Tech., 14, 2673–2697, https://doi.org/10.5194/amt-14-2673-2021, https://doi.org/10.5194/amt-14-2673-2021, 2021
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In this paper, we accessed the shortwave irradiance derived from MODIS cloud optical properties by using aircraft measurements. We developed a data aggregation technique to parameterize spectral surface albedo by snow fraction in the Arctic. We found that undetected clouds have the most significant impact on the imagery-derived irradiance. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach that would make it more dependable in the Arctic.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
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Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Meloë Kacenelenbogen, Michal Segal Rozenhaimer, Yohei Shinozuka, Connor Flynn, Amie Dobracki, Paquita Zuidema, Steven Howell, Steffen Freitag, and Sarah Doherty
Atmos. Meas. Tech., 14, 567–593, https://doi.org/10.5194/amt-14-567-2021, https://doi.org/10.5194/amt-14-567-2021, 2021
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Based on observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS), this work establishes an observationally driven link from mid-visible aerosol optical depth (AOD) and other scene parameters to broadband shortwave irradiance (and by extension the direct aerosol radiative effect, DARE). The majority of the case-to-case DARE variability within the ORACLES dataset is attributable to the dependence on AOD and scene albedo.
Prabhat, Karthik Kashinath, Mayur Mudigonda, Sol Kim, Lukas Kapp-Schwoerer, Andre Graubner, Ege Karaismailoglu, Leo von Kleist, Thorsten Kurth, Annette Greiner, Ankur Mahesh, Kevin Yang, Colby Lewis, Jiayi Chen, Andrew Lou, Sathyavat Chandran, Ben Toms, Will Chapman, Katherine Dagon, Christine A. Shields, Travis O'Brien, Michael Wehner, and William Collins
Geosci. Model Dev., 14, 107–124, https://doi.org/10.5194/gmd-14-107-2021, https://doi.org/10.5194/gmd-14-107-2021, 2021
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Detecting extreme weather events is a crucial step in understanding how they change due to climate change. Deep learning (DL) is remarkable at pattern recognition; however, it works best only when labeled datasets are available. We create
ClimateNet– an expert-labeled curated dataset – to train a DL model for detecting weather events and predicting changes in extreme precipitation. This work paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data.
Travis A. O'Brien, Mark D. Risser, Burlen Loring, Abdelrahman A. Elbashandy, Harinarayan Krishnan, Jeffrey Johnson, Christina M. Patricola, John P. O'Brien, Ankur Mahesh, Prabhat, Sarahí Arriaga Ramirez, Alan M. Rhoades, Alexander Charn, Héctor Inda Díaz, and William D. Collins
Geosci. Model Dev., 13, 6131–6148, https://doi.org/10.5194/gmd-13-6131-2020, https://doi.org/10.5194/gmd-13-6131-2020, 2020
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Researchers utilize various algorithms to identify extreme weather features in climate data, and we seek to answer this question: given a
plausibleweather event detector, how does uncertainty in the detector impact scientific results? We generate a suite of statistical models that emulate expert identification of weather features. We find that the connection between El Niño and atmospheric rivers – a specific extreme weather type – depends systematically on the design of the detector.
Wenying Su, Patrick Minnis, Lusheng Liang, David P. Duda, Konstantin Khlopenkov, Mandana M. Thieman, Yinan Yu, Allan Smith, Steven Lorentz, Daniel Feldman, and Francisco P. J. Valero
Atmos. Meas. Tech., 13, 429–443, https://doi.org/10.5194/amt-13-429-2020, https://doi.org/10.5194/amt-13-429-2020, 2020
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The Deep Space Climate Observatory (DSCOVR) provides continuous full-disk global broadband irradiance measurements over most of the sunlit side of the Earth. The three active cavity radiometers measure the total radiant energy from the sunlit side of the Earth in shortwave (SW; 0.2–4 µm), total (0.4–100 µm), and near-infrared (NIR; 0.7–4 µm) channels. In this paper, the algorithm used to derive daytime shortwave and longwave fluxes from NISTAR measurements is presented.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Meloë Kacenelenbogen, Michal Segal Rozenhaimer, Yohei Shinozuka, Connor Flynn, Steven Platnick, Kerry Meyer, Rich Ferrare, Sharon Burton, Chris Hostetler, Steven Howell, Steffen Freitag, Amie Dobracki, and Sarah Doherty
Atmos. Meas. Tech., 12, 6505–6528, https://doi.org/10.5194/amt-12-6505-2019, https://doi.org/10.5194/amt-12-6505-2019, 2019
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For two cases from the NASA ORACLES experiments, we retrieve aerosol and cloud properties and calculate a direct aerosol radiative effect (DARE). We investigate the relationship between DARE and the cloud albedo by specifying the albedo for which DARE transitions from a cooling to warming radiative effect. Our new aerosol retrieval algorithm is successful despite complexities associated with scenes that contain aerosols above clouds and decreases the uncertainty on retrieved aerosol parameters.
Steffen Mauceri, Bruce Kindel, Steven Massie, and Peter Pilewskie
Atmos. Meas. Tech., 12, 6017–6036, https://doi.org/10.5194/amt-12-6017-2019, https://doi.org/10.5194/amt-12-6017-2019, 2019
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Aerosols are fine particles that are suspended in Earth’s atmosphere. A better understanding of aerosols is important to lower uncertainties in climate predictions. We propose measuring aerosols from satellites and airplanes equipped with hyperspectral cameras using an artificial neural network, a form of machine learning. We applied our neural network to hyperspectral observations from a recent airplane flight over India and find general agreement with independent aerosol measurements.
Elizabeth C. Weatherhead, Jerald Harder, Eduardo A. Araujo-Pradere, Greg Bodeker, Jason M. English, Lawrence E. Flynn, Stacey M. Frith, Jeffrey K. Lazo, Peter Pilewskie, Mark Weber, and Thomas N. Woods
Atmos. Chem. Phys., 17, 15069–15093, https://doi.org/10.5194/acp-17-15069-2017, https://doi.org/10.5194/acp-17-15069-2017, 2017
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Satellite overlap is often carried out as a check on the stability of the data collected. We looked at how length of overlap influences how much information can be derived from the overlap period. Several results surprised us: the confidence we could have in the matchup of two records was independent of the offset, and understanding of the relative drift between the two satellite data sets improved significantly with 2–3 years of overlap. Sudden jumps could easily be confused with drift.
Shi Song, K. Sebastian Schmidt, Peter Pilewskie, Michael D. King, Andrew K. Heidinger, Andi Walther, Hironobu Iwabuchi, Gala Wind, and Odele M. Coddington
Atmos. Chem. Phys., 16, 13791–13806, https://doi.org/10.5194/acp-16-13791-2016, https://doi.org/10.5194/acp-16-13791-2016, 2016
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The radiative effects of spatially complex cloud fields are notoriously difficult to estimate and are afflicted with errors up to ±50 % of the incident solar radiation. We find that horizontal photon transport, the leading cause for these three-dimensional effects, manifests itself through a spectral fingerprint – a new observable that holds promise for reducing the errors associated with spatial complexity by moving the problem to the spectral dimension.
S. Jeon, Prabhat, S. Byna, J. Gu, W. D. Collins, and M. F. Wehner
Adv. Stat. Clim. Meteorol. Oceanogr., 1, 45–57, https://doi.org/10.5194/ascmo-1-45-2015, https://doi.org/10.5194/ascmo-1-45-2015, 2015
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This paper investigates the influence of atmospheric rivers on spatial coherence of extreme precipitation under a changing climate. We use our TECA software developed for detecting atmospheric river events and apply statistical techniques based on extreme value theory to characterize the spatial dependence structure between precipitation extremes within the events. The results show that extreme rainfall caused by atmospheric river events is less spatially correlated under the warming scenario.
W. D. Collins, A. P. Craig, J. E. Truesdale, A. V. Di Vittorio, A. D. Jones, B. Bond-Lamberty, K. V. Calvin, J. A. Edmonds, S. H. Kim, A. M. Thomson, P. Patel, Y. Zhou, J. Mao, X. Shi, P. E. Thornton, L. P. Chini, and G. C. Hurtt
Geosci. Model Dev., 8, 2203–2219, https://doi.org/10.5194/gmd-8-2203-2015, https://doi.org/10.5194/gmd-8-2203-2015, 2015
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The integrated Earth system model (iESM) has been developed as a
new tool for projecting the joint human-climate system. The
iESM is based upon coupling an integrated assessment model (IAM)
and an Earth system model (ESM) into a common modeling
infrastructure. By introducing heretofore-omitted
feedbacks between natural and societal drivers in iESM, we can improve
scientific understanding of the human-Earth system
dynamics.
D. R. Feldman, W. D. Collins, and J. L. Paige
Geosci. Model Dev., 8, 1943–1954, https://doi.org/10.5194/gmd-8-1943-2015, https://doi.org/10.5194/gmd-8-1943-2015, 2015
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This work describes a new type of observational simulator for directly comparing measurements and models that takes advantage of all of the information in spectrally resolved top-of-atmosphere data. It describes how to model how the spectrum of the Earth, both in the shortwave and the long wave, changes in response to climate forcings, and provides a path towards inline observational simulation for the upcoming Coupled Model Intercomparison Project – Phase 6.
B. C. Kindel, P. Pilewskie, K. S. Schmidt, T. Thornberry, A. Rollins, and T. Bui
Atmos. Meas. Tech., 8, 1147–1156, https://doi.org/10.5194/amt-8-1147-2015, https://doi.org/10.5194/amt-8-1147-2015, 2015
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Measurements of upper tropospheric-lower stratospheric water vapor amounts in the tropics were made using the 1400 and 1900nm water vapor bands present in airborne solar spectral irradiance data. These were validated with radiative transfer modeling using in situ profiles of water vapor, temperature, and pressure. An approach to extending these types of measurements from aircraft altitudes to the top of the atmosphere to infer stratospheric water vapor amount is outlined.
A. V. Di Vittorio, L. P. Chini, B. Bond-Lamberty, J. Mao, X. Shi, J. Truesdale, A. Craig, K. Calvin, A. Jones, W. D. Collins, J. Edmonds, G. C. Hurtt, P. Thornton, and A. Thomson
Biogeosciences, 11, 6435–6450, https://doi.org/10.5194/bg-11-6435-2014, https://doi.org/10.5194/bg-11-6435-2014, 2014
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Economic models provide scenarios of land use and greenhouse gas emissions to earth system models to project global change. We found, and partially addressed, inconsistencies in land cover between an economic and an earth system model that effectively alter a prescribed scenario, causing significant differences in projected terrestrial carbon and atmospheric CO2 between prescribed and altered scenarios. We outline a solution to this current problem in scenario-based global change projections.
J. A. Holm, J. Q. Chambers, W. D. Collins, and N. Higuchi
Biogeosciences, 11, 5773–5794, https://doi.org/10.5194/bg-11-5773-2014, https://doi.org/10.5194/bg-11-5773-2014, 2014
A. C. Kren, D. R. Marsh, A. K. Smith, and P. Pilewskie
Atmos. Chem. Phys., 14, 4843–4856, https://doi.org/10.5194/acp-14-4843-2014, https://doi.org/10.5194/acp-14-4843-2014, 2014
C. D. Koven, W. J. Riley, Z. M. Subin, J. Y. Tang, M. S. Torn, W. D. Collins, G. B. Bonan, D. M. Lawrence, and S. C. Swenson
Biogeosciences, 10, 7109–7131, https://doi.org/10.5194/bg-10-7109-2013, https://doi.org/10.5194/bg-10-7109-2013, 2013
W.-C. Hsieh, W. D. Collins, Y. Liu, J. C. H. Chiang, C.-L. Shie, K. Caldeira, and L. Cao
Atmos. Chem. Phys., 13, 7489–7510, https://doi.org/10.5194/acp-13-7489-2013, https://doi.org/10.5194/acp-13-7489-2013, 2013
I. Ermolli, K. Matthes, T. Dudok de Wit, N. A. Krivova, K. Tourpali, M. Weber, Y. C. Unruh, L. Gray, U. Langematz, P. Pilewskie, E. Rozanov, W. Schmutz, A. Shapiro, S. K. Solanki, and T. N. Woods
Atmos. Chem. Phys., 13, 3945–3977, https://doi.org/10.5194/acp-13-3945-2013, https://doi.org/10.5194/acp-13-3945-2013, 2013
A. J. Conley, J.-F. Lamarque, F. Vitt, W. D. Collins, and J. Kiehl
Geosci. Model Dev., 6, 469–476, https://doi.org/10.5194/gmd-6-469-2013, https://doi.org/10.5194/gmd-6-469-2013, 2013
Related subject area
Subject: Radiation | Research Activity: Remote Sensing | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
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Ruixue Li, Bida Jian, Jiming Li, Deyu Wen, Lijie Zhang, Yang Wang, and Yuan Wang
Atmos. Chem. Phys., 24, 9777–9803, https://doi.org/10.5194/acp-24-9777-2024, https://doi.org/10.5194/acp-24-9777-2024, 2024
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Hemispheric or interannual averages of reflected solar radiation (RSR) can mask signals from seasonally active or region-specific mechanisms. We examine RSR characteristics from latitude and month perspectives, revealing decreased trends observed by CERES in both hemispheres driven by clear-sky atmospheric and cloud components at 30–50° N and cloud components at 0–50° S. AVHRR achieves symmetry criteria within uncertainty and is suitable for the long-term analysis of hemispheric RSR symmetry.
Johannes Röttenbacher, André Ehrlich, Hanno Müller, Florian Ewald, Anna E. Luebke, Benjamin Kirbus, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 8085–8104, https://doi.org/10.5194/acp-24-8085-2024, https://doi.org/10.5194/acp-24-8085-2024, 2024
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Weather prediction models simplify the physical processes related to light scattering by clouds consisting of complex ice crystals. Whether these simplifications are the cause for uncertainties in their prediction can be evaluated by comparing them with measurement data. Here we do this for Arctic ice clouds over sea ice using airborne measurements from two case studies. The model performs well for thick ice clouds but not so well for thin ones. This work can be used to improve the model.
Donatello Gallucci, Domenico Cimini, Emma Turner, Stuart Fox, Philip W. Rosenkranz, Mikhail Y. Tretyakov, Vinia Mattioli, Salvatore Larosa, and Filomena Romano
Atmos. Chem. Phys., 24, 7283–7308, https://doi.org/10.5194/acp-24-7283-2024, https://doi.org/10.5194/acp-24-7283-2024, 2024
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Nowadays, atmospheric radiative transfer models are widely used to simulate satellite and ground-based observations. A meaningful comparison between observations and simulations requires an estimate of the uncertainty associated with both. This work quantifies the uncertainty in atmospheric radiative transfer models in the microwave range, providing the uncertainty associated with simulations of new-generation satellite microwave sensors.
João Teixeira, R. Chris Wilson, and Heidar Th. Thrastarson
Atmos. Chem. Phys., 24, 6375–6383, https://doi.org/10.5194/acp-24-6375-2024, https://doi.org/10.5194/acp-24-6375-2024, 2024
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This paper presents direct evidence from space (solely based on observations) that CO2 increase leads to the theoretically expected effects on longwave spectral radiances. This is achieved by using a methodology that allows us to isolate the CO2 effects from the temperature and water vapor effects. By searching for ensembles of temperature and water vapor profiles that are similar to each other but have different values of CO2, it is possible to estimate the direct effects of CO2 on the spectra.
Carlos Toledano, Sarah Taylor, África Barreto, Stefan Adriaensen, Alberto Berjón, Agnieszka Bialek, Ramiro González, Emma Woolliams, and Marc Bouvet
Atmos. Chem. Phys., 24, 3649–3671, https://doi.org/10.5194/acp-24-3649-2024, https://doi.org/10.5194/acp-24-3649-2024, 2024
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The calibration of Earth observation sensors is key to ensuring the continuity of long-term and global climate records. Satellite sensors, calibrated prior to launch, are susceptible to degradation in space. The Moon provides a stable calibration reference; however, its illumination depends on the Sun–Earth–Moon geometry and must be modelled. A new lunar irradiance model is presented, built upon observations over 5 years at a high-altitude observatory and a rigorous calibration and validation.
Adeleke S. Ademakinwa, Zahid H. Tushar, Jianyu Zheng, Chenxi Wang, Sanjay Purushotham, Jianwu Wang, Kerry G. Meyer, Tamas Várnai, and Zhibo Zhang
Atmos. Chem. Phys., 24, 3093–3114, https://doi.org/10.5194/acp-24-3093-2024, https://doi.org/10.5194/acp-24-3093-2024, 2024
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Clouds play a critical role in our climate system. At present and in the near future, satellite-based remote sensing is the only means to obtain regional and global observations of cloud properties. The current satellite remote sensing algorithms are mostly based on the so-called 1D radiative transfer. This deviation from the 3D world reality can lead to large errors. In this study we investigate how this error affects our estimation of cloud radiative effects.
Peizhen Li, Lei Zhong, Yaoming Ma, Yunfei Fu, Meilin Cheng, Xian Wang, Yuting Qi, and Zixin Wang
Atmos. Chem. Phys., 23, 9265–9285, https://doi.org/10.5194/acp-23-9265-2023, https://doi.org/10.5194/acp-23-9265-2023, 2023
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In this paper, all-sky downwelling shortwave radiation (DSR) over the entire Tibetan Plateau (TP) at a spatial resolution of 1 km was estimated using an improved parameterization scheme. The influence of topography and different radiative attenuations were comprehensively taken into account. The derived DSR showed good agreement with in situ measurements. The accuracy was better than six other DSR products. The derived DSR also provided more reasonable and detailed spatial patterns.
Elisa T. Sena, Ilan Koren, Orit Altaratz, and Alexander B. Kostinski
Atmos. Chem. Phys., 22, 16111–16122, https://doi.org/10.5194/acp-22-16111-2022, https://doi.org/10.5194/acp-22-16111-2022, 2022
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We used record-breaking statistics together with spatial information to create record-breaking SST maps. The maps reveal warming patterns in the overwhelming majority of the ocean and coherent islands of cooling, where low records occur more frequently than high ones. Some of these cooling spots are well known; however, a surprising elliptical area in the Southern Ocean is observed as well. Similar analyses can be performed on other key climatological variables to explore their trend patterns.
Carola Barrientos-Velasco, Hartwig Deneke, Anja Hünerbein, Hannes J. Griesche, Patric Seifert, and Andreas Macke
Atmos. Chem. Phys., 22, 9313–9348, https://doi.org/10.5194/acp-22-9313-2022, https://doi.org/10.5194/acp-22-9313-2022, 2022
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This article describes an intercomparison of radiative fluxes and cloud properties from satellite, shipborne observations, and 1D radiative transfer simulations. The analysis focuses on research for PS106 expedition aboard the German research vessel, Polarstern. The results are presented in detailed case studies, time series for the PS106 cruise and extended to the central Arctic region. The findings illustrate the main periods of agreement and discrepancies of both points of view.
Yinghui Liu
Atmos. Chem. Phys., 22, 8151–8173, https://doi.org/10.5194/acp-22-8151-2022, https://doi.org/10.5194/acp-22-8151-2022, 2022
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Cloud detection from state-of-art satellite radar and lidar misses low-level clouds. Using in situ observations, this study confirms this cloud detection limitation over the Arctic Ocean. Impacts of this detection limitation from combined satellite radar and lidar on the monthly mean radiation flux estimations at the surface and at the top of the atmosphere in the Arctic are limited but larger from only satellite radar or satellite lidar in monthly mean and instantaneous values.
Babak Jahani, Hendrik Andersen, Josep Calbó, Josep-Abel González, and Jan Cermak
Atmos. Chem. Phys., 22, 1483–1494, https://doi.org/10.5194/acp-22-1483-2022, https://doi.org/10.5194/acp-22-1483-2022, 2022
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The change in the state of sky from cloudy to cloudless (or vice versa) comprises an additional phase called
transition zonewith characteristics laying between those of aerosols and clouds. This study presents an approach for the quantification of the broadband longwave radiative effects of the cloud–aerosol transition zone at the top of the atmosphere during daytime over the ocean based on satellite observations and radiative transfer simulations.
William Cossich, Tiziano Maestri, Davide Magurno, Michele Martinazzo, Gianluca Di Natale, Luca Palchetti, Giovanni Bianchini, and Massimo Del Guasta
Atmos. Chem. Phys., 21, 13811–13833, https://doi.org/10.5194/acp-21-13811-2021, https://doi.org/10.5194/acp-21-13811-2021, 2021
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The presence of clouds over Concordia, in the Antarctic Plateau, is investigated. Results are obtained by applying a machine learning algorithm to measurements of the infrared radiation emitted by the atmosphere toward the surface. The clear-sky, ice cloud, and mixed-phase cloud occurrence at different timescales is studied. A comparison with satellite measurements highlights the ability of the algorithm to identify multiple cloud conditions and study their variability at different timescales.
Ina Neher, Susanne Crewell, Stefanie Meilinger, Uwe Pfeifroth, and Jörg Trentmann
Atmos. Chem. Phys., 20, 12871–12888, https://doi.org/10.5194/acp-20-12871-2020, https://doi.org/10.5194/acp-20-12871-2020, 2020
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Photovoltaic power is one current option to meet the rising energy demand with low environmental impact. Global horizontal irradiance (GHI) is the fuel for photovoltaic power installations and needs to be evaluated to plan and dimension power plants. In this study, 35 years of satellite-based GHI data are analyzed over West Africa to determine their impact on photovoltaic power generation. The major challenges for the development of a solar-based power system in West Africa are then outlined.
Eamon K. Conway, Iouli E. Gordon, Jonathan Tennyson, Oleg L. Polyansky, Sergei N. Yurchenko, and Kelly Chance
Atmos. Chem. Phys., 20, 10015–10027, https://doi.org/10.5194/acp-20-10015-2020, https://doi.org/10.5194/acp-20-10015-2020, 2020
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Water vapour has a complex spectrum and absorbs from the microwave to the near-UV where it dissociates. There is limited knowledge of the absorption features in the near-UV, and there is a large disagreement for the available models and experiments. We created a new ab initio model that is in good agreement with observation at 363 nm. At lower wavelengths, our calculations suggest that the latest experiments overestimate absorption. This has implications for trace gas retrievals in the near-UV.
Jay Herman, Alexander Cede, Liang Huang, Jerald Ziemke, Omar Torres, Nickolay Krotkov, Matthew Kowalewski, and Karin Blank
Atmos. Chem. Phys., 20, 8351–8380, https://doi.org/10.5194/acp-20-8351-2020, https://doi.org/10.5194/acp-20-8351-2020, 2020
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The amount of erythemal irradiance reaching the Earth's surface has been calculated from ozone, aerosol, and reflectivity data obtained from OMI and DSCOVR/EPIC satellite instruments showing areas with high levels of solar UV radiation. Changes in erythemal irradiance, cloud transmission, aerosol transmission, and ozone absorption have been estimated for 14 years 2005–2018 in units of percent per year for 191 locations, mostly large cities, and from EPIC for the entire illuminated Earth.
Rong Tang, Xin Huang, Derong Zhou, and Aijun Ding
Atmos. Chem. Phys., 20, 6177–6191, https://doi.org/10.5194/acp-20-6177-2020, https://doi.org/10.5194/acp-20-6177-2020, 2020
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Biomass-burning-induced large areas of dark char (i.e.
surface darkening) could influence the radiative energy balance. During the harvest season in eastern China, satellite retrieval shows that surface albedo was significantly decreased. Observational evidence of meteorological perturbations from the surface darkening is identified, which is further examined by model simulation. This work highlights the importance of burning-induced albedo change in weather forecast and regional climate.
Aolin Jia, Shunlin Liang, Dongdong Wang, Bo Jiang, and Xiaotong Zhang
Atmos. Chem. Phys., 20, 881–899, https://doi.org/10.5194/acp-20-881-2020, https://doi.org/10.5194/acp-20-881-2020, 2020
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The Tibetan Plateau (TP) plays a vital role in regional and global climate change due to its location and orography. After generating a long-term surface radiation (SR) dataset, we characterized the SR spatiotemporal variation along with temperature. Evidence from multiple data sources indicated that the TP dimming was primarily driven by increased aerosols from human activities, and the cooling effect of aerosol loading offsets TP surface warming, revealing the human impact on regional warming.
Lei Zhong, Yaoming Ma, Zeyong Hu, Yunfei Fu, Yuanyuan Hu, Xian Wang, Meilin Cheng, and Nan Ge
Atmos. Chem. Phys., 19, 5529–5541, https://doi.org/10.5194/acp-19-5529-2019, https://doi.org/10.5194/acp-19-5529-2019, 2019
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Fine-temporal-resolution turbulent heat fluxes at the plateau scale have significant importance for studying diurnal variation characteristics of atmospheric boundary and weather systems in the Tibetan Plateau (TP) and its surroundings. Time series of land surface heat fluxes with high temporal resolution over the entire TP were derived. The derived surface heat fluxes proved to be in good agreement with in situ measurements and were superior to GLDAS flux products.
Meloë S. Kacenelenbogen, Mark A. Vaughan, Jens Redemann, Stuart A. Young, Zhaoyan Liu, Yongxiang Hu, Ali H. Omar, Samuel LeBlanc, Yohei Shinozuka, John Livingston, Qin Zhang, and Kathleen A. Powell
Atmos. Chem. Phys., 19, 4933–4962, https://doi.org/10.5194/acp-19-4933-2019, https://doi.org/10.5194/acp-19-4933-2019, 2019
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Significant efforts are required to estimate the direct radiative effects of aerosols above clouds (DAREcloudy). We have used a combination of passive and active A-Train satellite sensors and derive mainly positive global and regional DAREcloudy values (e.g., global seasonal values between 0.13 and 0.26 W m-2). Despite differences in methods and sensors, the DAREcloudy values in this study are generally higher than previously reported. We discuss the primary reasons for these higher estimates.
Domenico Cimini, Philip W. Rosenkranz, Mikhail Y. Tretyakov, Maksim A. Koshelev, and Filomena Romano
Atmos. Chem. Phys., 18, 15231–15259, https://doi.org/10.5194/acp-18-15231-2018, https://doi.org/10.5194/acp-18-15231-2018, 2018
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The paper presents a general approach to quantify the uncertainty related to atmospheric absorption models. These models describe how the atmosphere interacts with radiation, and they have general implications for atmospheric sciences.
The presented approach contributes to a better understanding of the total uncertainty affecting atmospheric radiative properties, thus reducing the chances of systematic errors when observations are exploited for weather forecast or climate trend derivations.
Michael Schäfer, Katharina Loewe, André Ehrlich, Corinna Hoose, and Manfred Wendisch
Atmos. Chem. Phys., 18, 13115–13133, https://doi.org/10.5194/acp-18-13115-2018, https://doi.org/10.5194/acp-18-13115-2018, 2018
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Airborne observed horizontal fields of cloud optical thickness are compared with semi-idealized large eddy simulations of Arctic stratus. The comparison focuses on horizontal cloud inhomogeneities and directional features of the small-scale cloud structures. Using inhomogeneity parameters and autocorrelation analysis it is investigated, if the observed small-scale cloud inhomogeneities can be represented by the model. Forcings for cloud inhomogeneities are investigated in a sensitivity study.
Qianqian Song, Zhibo Zhang, Hongbin Yu, Seiji Kato, Ping Yang, Peter Colarco, Lorraine A. Remer, and Claire L. Ryder
Atmos. Chem. Phys., 18, 11303–11322, https://doi.org/10.5194/acp-18-11303-2018, https://doi.org/10.5194/acp-18-11303-2018, 2018
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Mineral dust is the most abundant atmospheric aerosol component in terms of dry mass. In this study, we integrate recent aircraft measurements of dust microphysical and optical properties with satellite retrievals of aerosol and radiative fluxes to quantify the dust direct radiative effects on the shortwave and longwave radiation at both the top of the atmosphere and the surface in the tropical North Atlantic during summer months.
Shu-Peng Ho, Liang Peng, Carl Mears, and Richard A. Anthes
Atmos. Chem. Phys., 18, 259–274, https://doi.org/10.5194/acp-18-259-2018, https://doi.org/10.5194/acp-18-259-2018, 2018
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In this study, we compare 7 years of atmospheric total precipitable water (TPW) derived from multiple microwave radiometers to collocated TPW estimates derived from COSMIC radio occultation under various atmospheric conditions over the oceans. Results show that these two TPW trends from independent observations are larger than previous estimates and are a strong indication of the positive water vapor–temperature feedback on a warming planet.
Anna Mackie, Paul I. Palmer, and Helen Brindley
Atmos. Chem. Phys., 17, 15095–15119, https://doi.org/10.5194/acp-17-15095-2017, https://doi.org/10.5194/acp-17-15095-2017, 2017
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We compare the balance of solar and thermal radiation at the surface and the top of the atmosphere from a forecasting model to observations at a site in Niamey, Niger, in the Sahel. To interpret the energy budgets we examine other factors, such as cloud properties, water vapour and aerosols, which we use to understand the differences between the observation and model. We find that some differences are linked to lack of ice in clouds, underestimated aerosol loading and surface temperatures.
Thomas Fauchez, Steven Platnick, Kerry Meyer, Céline Cornet, Frédéric Szczap, and Tamás Várnai
Atmos. Chem. Phys., 17, 8489–8508, https://doi.org/10.5194/acp-17-8489-2017, https://doi.org/10.5194/acp-17-8489-2017, 2017
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This study presents impact of cirrus cloud horizontal heterogeneity on simulated thermal infrared brightness temperatures at the top of the atmosphere for spatial resolutions ranging from 50 m to 10 km. The cirrus is generated by the 3DCLOUD code and the radiative transfer by the 3DMCPOL code. Brightness temperatures are mostly impacted by the horizontal transport effect and plane-parallel bias at high and coarse spatial resolutions, respectively, with a minimum around 100 m–250 m.
Zhao-Cheng Zeng, Qiong Zhang, Vijay Natraj, Jack S. Margolis, Run-Lie Shia, Sally Newman, Dejian Fu, Thomas J. Pongetti, Kam W. Wong, Stanley P. Sander, Paul O. Wennberg, and Yuk L. Yung
Atmos. Chem. Phys., 17, 2495–2508, https://doi.org/10.5194/acp-17-2495-2017, https://doi.org/10.5194/acp-17-2495-2017, 2017
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We propose a novel approach to describing the scattering effects of atmospheric aerosols using H2O retrievals in the near infrared. We found that the aerosol scattering effect is the primary contributor to the variations in the wavelength dependence of the H2O SCD retrievals and the scattering effects can be derived using H2O retrievals from multiple bands. This proposed method could potentially contribute towards reducing biases in greenhouse gas retrievals from space.
Michael Schäfer, Eike Bierwirth, André Ehrlich, Evelyn Jäkel, Frank Werner, and Manfred Wendisch
Atmos. Chem. Phys., 17, 2359–2372, https://doi.org/10.5194/acp-17-2359-2017, https://doi.org/10.5194/acp-17-2359-2017, 2017
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Cloud optical thickness fields, retrieved from solar spectral radiance measurements, are used to investigate the directional structure of horizontal cloud inhomogeneities with scalar one-dimensional inhomogeneity parameters, two-dimensional auto-correlation functions, and two-dimensional Fourier analysis. The investigations reveal that it is not sufficient to quantify horizontal cloud inhomogeneities by one-dimensional inhomogeneity parameters; two-dimensional parameters are necessary.
Quentin Libois, Liviu Ivanescu, Jean-Pierre Blanchet, Hannes Schulz, Heiko Bozem, W. Richard Leaitch, Julia Burkart, Jonathan P. D. Abbatt, Andreas B. Herber, Amir A. Aliabadi, and Éric Girard
Atmos. Chem. Phys., 16, 15689–15707, https://doi.org/10.5194/acp-16-15689-2016, https://doi.org/10.5194/acp-16-15689-2016, 2016
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The first airborne measurements performed with the FIRR are presented. Vertical profiles of upwelling spectral radiance in the far-infrared are measured in the Arctic atmosphere for the first time. They show the impact of the temperature inversion on the radiative budget of the atmosphere, especially in the far-infrared. The presence of ice clouds also significantly alters the far-infrared budget, highlighting the critical interplay between water vapour and clouds in this very dry region.
Jani Huttunen, Harri Kokkola, Tero Mielonen, Mika Esa Juhani Mononen, Antti Lipponen, Juha Reunanen, Anders Vilhelm Lindfors, Santtu Mikkonen, Kari Erkki Juhani Lehtinen, Natalia Kouremeti, Alkiviadis Bais, Harri Niska, and Antti Arola
Atmos. Chem. Phys., 16, 8181–8191, https://doi.org/10.5194/acp-16-8181-2016, https://doi.org/10.5194/acp-16-8181-2016, 2016
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For a good estimate of the current forcing by anthropogenic aerosols, knowledge in past is needed. One option to lengthen time series is to retrieve aerosol optical depth from solar radiation measurements. We have evaluated several methods for this task. Most of the methods produce aerosol optical depth estimates with a good accuracy. However, machine learning methods seem to be the most applicable not to produce any systematic biases, since they do not need constrain the aerosol properties.
Claire Pettersen, Ralf Bennartz, Mark S. Kulie, Aronne J. Merrelli, Matthew D. Shupe, and David D. Turner
Atmos. Chem. Phys., 16, 4743–4756, https://doi.org/10.5194/acp-16-4743-2016, https://doi.org/10.5194/acp-16-4743-2016, 2016
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We examined four summers of data from a ground-based atmospheric science instrument suite at Summit Station, Greenland, to isolate the signature of the ice precipitation. By using a combination of instruments with different specialities, we identified a passive microwave signature of the ice precipitation. This ice signature compares well to models using synthetic data characteristic of the site.
Zhibo Zhang, Kerry Meyer, Hongbin Yu, Steven Platnick, Peter Colarco, Zhaoyan Liu, and Lazaros Oreopoulos
Atmos. Chem. Phys., 16, 2877–2900, https://doi.org/10.5194/acp-16-2877-2016, https://doi.org/10.5194/acp-16-2877-2016, 2016
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The frequency of occurrence and shortwave direct radiative effects (DRE) of above-cloud aerosols (ACAs) over global oceans are investigated using 8 years of collocated CALIOP and MODIS observations. We estimated that ACAs have a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m−2 (range of −0.03 to 0.06 W m−2) at TOA. The DREs at surface and within atmosphere are −0.15 W m−2 (range of −0.09 to −0.21 W m−2), and 0.17 W m−2 (range of 0.11 to 0.24 W m−2), respectively.
Wenjun Tang, Jun Qin, Kun Yang, Shaomin Liu, Ning Lu, and Xiaolei Niu
Atmos. Chem. Phys., 16, 2543–2557, https://doi.org/10.5194/acp-16-2543-2016, https://doi.org/10.5194/acp-16-2543-2016, 2016
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In this paper, we develop a new method to quickly retrieve high-resolution surface solar radiation (SSR) over China by combining MODIS and MTSAT data. The RMSEs of the retrieved SSR at hourly, daily, and monthly scales are about 98.5, 34.2, and 22.1 W m−2. The accuracy is comparable to or even higher than other two satellite radiation products. Finally, we derive an 8-year high-resolution SSR data set (hourly, 5 km) from 2007 to 2014, which would contribute to studies of land surface processes.
S. Doniki, D. Hurtmans, L. Clarisse, C. Clerbaux, H. M. Worden, K. W. Bowman, and P.-F. Coheur
Atmos. Chem. Phys., 15, 12971–12987, https://doi.org/10.5194/acp-15-12971-2015, https://doi.org/10.5194/acp-15-12971-2015, 2015
W. Sun, R. R. Baize, G. Videen, Y. Hu, and Q. Fu
Atmos. Chem. Phys., 15, 11909–11918, https://doi.org/10.5194/acp-15-11909-2015, https://doi.org/10.5194/acp-15-11909-2015, 2015
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A method is reported for retrieving super-thin cloud optical depth with polarized light. It is found that near-backscatter p-polarized light is sensitive to clouds, but not to ocean conditions. Near-backscatter p-polarized intensity linearly relates to super-thin cloud optical depth. Based on these findings, super-thin cloud optical depth can be retrieved with little effect from surface reflection.
M. Schäfer, E. Bierwirth, A. Ehrlich, E. Jäkel, and M. Wendisch
Atmos. Chem. Phys., 15, 8147–8163, https://doi.org/10.5194/acp-15-8147-2015, https://doi.org/10.5194/acp-15-8147-2015, 2015
W. Sun, R. R. Baize, C. Lukashin, and Y. Hu
Atmos. Chem. Phys., 15, 7725–7734, https://doi.org/10.5194/acp-15-7725-2015, https://doi.org/10.5194/acp-15-7725-2015, 2015
E. C. Turner, H.-T. Lee, and S. F. B. Tett
Atmos. Chem. Phys., 15, 6561–6575, https://doi.org/10.5194/acp-15-6561-2015, https://doi.org/10.5194/acp-15-6561-2015, 2015
M. M. Wonsick, R. T. Pinker, and Y. Ma
Atmos. Chem. Phys., 14, 8749–8761, https://doi.org/10.5194/acp-14-8749-2014, https://doi.org/10.5194/acp-14-8749-2014, 2014
X. Ceamanos, D. Carrer, and J.-L. Roujean
Atmos. Chem. Phys., 14, 8209–8232, https://doi.org/10.5194/acp-14-8209-2014, https://doi.org/10.5194/acp-14-8209-2014, 2014
Q. Shi and S. Liang
Atmos. Chem. Phys., 14, 5659–5677, https://doi.org/10.5194/acp-14-5659-2014, https://doi.org/10.5194/acp-14-5659-2014, 2014
C. Fricke, A. Ehrlich, E. Jäkel, B. Bohn, M. Wirth, and M. Wendisch
Atmos. Chem. Phys., 14, 1943–1958, https://doi.org/10.5194/acp-14-1943-2014, https://doi.org/10.5194/acp-14-1943-2014, 2014
Y. Ma, Z. Zhu, L. Zhong, B. Wang, C. Han, Z. Wang, Y. Wang, L. Lu, P. M. Amatya, W. Ma, and Z. Hu
Atmos. Chem. Phys., 14, 1507–1515, https://doi.org/10.5194/acp-14-1507-2014, https://doi.org/10.5194/acp-14-1507-2014, 2014
W. Sun and C. Lukashin
Atmos. Chem. Phys., 13, 10303–10324, https://doi.org/10.5194/acp-13-10303-2013, https://doi.org/10.5194/acp-13-10303-2013, 2013
L. Shi, C. J. Schreck III, and V. O. John
Atmos. Chem. Phys., 13, 6907–6920, https://doi.org/10.5194/acp-13-6907-2013, https://doi.org/10.5194/acp-13-6907-2013, 2013
M. J. Alvarado, V. H. Payne, E. J. Mlawer, G. Uymin, M. W. Shephard, K. E. Cady-Pereira, J. S. Delamere, and J.-L. Moncet
Atmos. Chem. Phys., 13, 6687–6711, https://doi.org/10.5194/acp-13-6687-2013, https://doi.org/10.5194/acp-13-6687-2013, 2013
T. Várnai, A. Marshak, and W. Yang
Atmos. Chem. Phys., 13, 3899–3908, https://doi.org/10.5194/acp-13-3899-2013, https://doi.org/10.5194/acp-13-3899-2013, 2013
A. Riihelä, T. Manninen, V. Laine, K. Andersson, and F. Kaspar
Atmos. Chem. Phys., 13, 3743–3762, https://doi.org/10.5194/acp-13-3743-2013, https://doi.org/10.5194/acp-13-3743-2013, 2013
C. L. Young, I. N. Sokolik, and J. Dufek
Atmos. Chem. Phys., 12, 3699–3715, https://doi.org/10.5194/acp-12-3699-2012, https://doi.org/10.5194/acp-12-3699-2012, 2012
A. Ehrlich, E. Bierwirth, M. Wendisch, A. Herber, and J.-F. Gayet
Atmos. Chem. Phys., 12, 3493–3510, https://doi.org/10.5194/acp-12-3493-2012, https://doi.org/10.5194/acp-12-3493-2012, 2012
E. M. Wilcox
Atmos. Chem. Phys., 12, 139–149, https://doi.org/10.5194/acp-12-139-2012, https://doi.org/10.5194/acp-12-139-2012, 2012
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