Articles | Volume 5, issue 12
12 Dec 2012
Research article | 12 Dec 2012
Effect of spectrally varying albedo of vegetation surfaces on shortwave radiation fluxes and aerosol direct radiative forcing
L. Zhu et al.
No articles found.
Qianqian Song, Zhibo Zhang, Hongbin Yu, Jasper F. Kok, Claudia Di Biagio, Samuel Albani, Jianyu Zheng, and Jiachen Ding
Atmos. Chem. Phys., 22, 13115–13135,Short summary
This study developed a dataset that enables us to efficiently calculate dust direct radiative effect (DRE, i.e., cooling or warming our planet) for any given dust size distribution in addition to three sets of dust mineral components and two dust shapes. We demonstrate and validate the method of using this dataset to calculate dust DRE. Moreover, using this dataset we found that dust mineral composition is a more important factor in determining dust DRE than dust size and shape.
Qianqian Song, Zhibo Zhang, Hongbin Yu, Paul Ginoux, and Jerry Shen
Atmos. Chem. Phys., 21, 13369–13395,Short summary
We present a satellite-derived global dust climatological record over the last two decades, including the monthly mean visible dust optical depth (DAOD) and vertical distribution of dust extinction coefficient at a 2º × 5º spatial resolution derived from CALIOP and MODIS. In addition, the CALIOP climatological dataset also includes dust vertical extinction profiles. Based on these two datasets, we carried out a comprehensive comparative study of the spatial and temporal climatology of dust.
Z. Zhang, K. Meyer, S. Platnick, L. Oreopoulos, D. Lee, and H. Yu
Atmos. Meas. Tech., 7, 1777–1789,
A. Arola, T. F. Eck, J. Huttunen, K. E. J. Lehtinen, A. V. Lindfors, G. Myhre, A. Smirnov, S. N. Tripathi, and H. Yu
Atmos. Chem. Phys., 13, 7895–7901,
P. Stier, N. A. J. Schutgens, N. Bellouin, H. Bian, O. Boucher, M. Chin, S. Ghan, N. Huneeus, S. Kinne, G. Lin, X. Ma, G. Myhre, J. E. Penner, C. A. Randles, B. Samset, M. Schulz, T. Takemura, F. Yu, H. Yu, and C. Zhou
Atmos. Chem. Phys., 13, 3245–3270,
W. J. Collins, M. M. Fry, H. Yu, J. S. Fuglestvedt, D. T. Shindell, and J. J. West
Atmos. Chem. Phys., 13, 2471–2485,
C. A. Randles, S. Kinne, G. Myhre, M. Schulz, P. Stier, J. Fischer, L. Doppler, E. Highwood, C. Ryder, B. Harris, J. Huttunen, Y. Ma, R. T. Pinker, B. Mayer, D. Neubauer, R. Hitzenberger, L. Oreopoulos, D. Lee, G. Pitari, G. Di Genova, J. Quaas, F. G. Rose, S. Kato, S. T. Rumbold, I. Vardavas, N. Hatzianastassiou, C. Matsoukas, H. Yu, F. Zhang, H. Zhang, and P. Lu
Atmos. Chem. Phys., 13, 2347–2379,
Related subject area
Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information RetrievalAtmospheric visibility inferred from continuous-wave Doppler wind lidarIdentification of smoke and sulfuric acid aerosol in SAGE III/ISS extinction spectraCombining Mie–Raman and fluorescence observations: a step forward in aerosol classification with lidar technologyEffective uncertainty quantification for multi-angle polarimetric aerosol remote sensing over oceanEmploying relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithmAlgorithm for vertical distribution of boundary layer aerosol components in remote sensing dataObservation of bioaerosol transport using wideband integrated bioaerosol sensor and coherent Doppler lidarRetrieval of UVB aerosol extinction profiles from the ground-based Langley Mobile Ozone Lidar (LMOL) systemEnhancing MAX-DOAS atmospheric state retrievals by multispectral polarimetry – studies using synthetic dataAssessing the benefits of Imaging Infrared Radiometer observations for the CALIOP version 4 cloud and aerosol discrimination algorithmThe New MISR Research Aerosol Retrieval Algorithm: A Multi-Angle, Multi-Spectral, Bounded-Variable Least Squares Retrieval of Aerosol Particle Properties over Both Land and WaterA semi-automated procedure for the emitter–receiver geometry characterization of motor-controlled lidarsAerosol optical characteristics in the urban area of Rome, Italy, and their impact on the UV indexAerosol models from the AERONET database: application to surface reflectance validationContinuous mapping of fine particulate matter (PM2.5) air quality in East Asia at daily 6 × 6 km2 resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite dataDeep-learning-based post-process correction of the aerosol parameters in the high-resolution Sentinel-3 Level-2 Synergy productRetrieval of UV–visible aerosol absorption using AERONET and OMI–MODIS synergy: spatial and temporal variability across major aerosol environmentsEstimating cloud condensation nuclei concentrations from CALIPSO lidar measurementsAsh particle refractive index model for simulating the brightness temperature spectrum of volcanic ash clouds from satellite infrared sounder measurementsRetrieval of aerosol properties using relative radiance measurements from an all-sky cameraOptimization of Aeolus' aerosol optical properties by maximum-likelihood estimationA Bayesian parametric approach to the retrieval of the atmospheric number size distribution from lidar dataBiomass burning aerosol heating rates from the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) 2016 and 2017 experimentsAeolus L2A aerosol optical properties product: standard correct algorithm and Mie correct algorithmMethodology to obtain highly resolved SO2 vertical profiles for representation of volcanic emissions in climate modelsInferring the absorption properties of organic aerosol in Siberian biomass burning plumes from remote optical observationsMass concentration estimates of long-range-transported Canadian biomass burning aerosols from a multi-wavelength Raman polarization lidar and a ceilometer in FinlandRetrievals of dust-related particle mass and ice-nucleating particle concentration profiles with ground-based polarization lidar and sun photometer over a megacity in central ChinaIntroducing the MISR level 2 near real-time aerosol productEstimation of PM2.5 concentration in China using linear hybrid machine learning modelSpecies correlation measurements in turbulent flare plumes: considerations for field measurementsRetrieval of aerosol microphysical properties from atmospheric lidar sounding: an investigation using synthetic measurements and data from the ACEPOL campaignIntegration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaignsDeriving boundary layer height from aerosol lidar using machine learning: KABL and ADABL algorithmsEfficient multi-angle polarimetric inversion of aerosols and ocean color powered by a deep neural network forward modelQuantitative comparison of measured and simulated O4 absorptions for one day with extremely low aerosol load over the tropical AtlanticA Dark Target research aerosol algorithm for MODIS observations over eastern China: increasing coverage while maintaining accuracy at high aerosol loadingOptimal use of the Prede POM sky radiometer for aerosol, water vapor, and ozone retrievalsAnalysis of simultaneous aerosol and ocean glint retrieval using multi-angle observationsModel-enforced post-process correction of satellite aerosol retrievalsExplicit and consistent aerosol correction for visible wavelength satellite cloud and nitrogen dioxide retrievals based on optical properties from a global aerosol analysisReducing cloud contamination in aerosol optical depth (AOD) measurementsSynergy processing of diverse ground-based remote sensing and in situ data using the GRASP algorithm: applications to radiometer, lidar and radiosonde observationsRetrieval of stratospheric aerosol size distribution parameters using satellite solar occultation measurements at three wavelengthsRelative sky radiance from multi-exposure all-sky camera imagesAn uncertainty-based protocol for the setup and measurement of soot–black carbon emissions from gas flares using sky-LOSAA new measurement approach for validating satellite-based above-cloud aerosol optical depthOMPS LP Version 2.0 multi-wavelength aerosol extinction coefficient retrieval algorithmSimulated reflectance above snow constrained by airborne measurements of solar radiation: implications for the snow grain morphology in the ArcticModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set
Manuel Queißer, Michael Harris, and Steven Knoop
Atmos. Meas. Tech., 15, 5527–5544,Short summary
Visibility is how well we can see something. Visibility sensors, such as employed in meteorological observatories and airports, measure at a point at the instrument location, which may not be representative of visibilities further away, e.g. near the sea surface during sea spray. Light detecting and ranging (lidar) can measure visibility further away. We find wind lidar to be a viable tool to measure visibility with low accuracy, which could suffice for safety-uncritical applications.
Travis N. Knepp, Larry Thomason, Mahesh Kovilakam, Jason Tackett, Jayanta Kar, Robert Damadeo, and David Flittner
Atmos. Meas. Tech., 15, 5235–5260,Short summary
We used aerosol profiles from the SAGE III/ISS instrument to develop an aerosol classification method that was tested on four case-study events (two volcanic, two fire) and supported with CALIOP aerosol products. The method worked well in identifying smoke and volcanic aerosol in the stratosphere for these events. Raikoke is presented as a demonstration of the limitations of this method.
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Boris Barchunov, and Mikhail Korenskii
Atmos. Meas. Tech., 15, 4881–4900,Short summary
An approach to reveal variability in aerosol type at a high spatiotemporal resolution, by combining fluorescence and Mie–Raman lidar data, is presented. We applied this new classification scheme to lidar data obtained by LOA, University of Lille, in 2020–2021. It is demonstrated that the separation of the main particle types, such as smoke, dust, pollen, and urban, can be performed with a height resolution of 60 m and temporal resolution better than 10 min for the current lidar configuration.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879,Short summary
In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Oleg Dubovik, Joel S. Schafer, Alexander Smirnov, and Mikhail Sorokin
Atmos. Meas. Tech., 15, 4135–4151,Short summary
This paper describes modification of smoothness constraints on the imaginary part of the refractive index employed in the AERONET aerosol retrieval algorithm. This modification is termed relaxed due to the weaker strength of this new smoothness constraint. Applying the modified version of the smoothness constraint results in a significant reduction of retrieved light absorption by brown-carbon-containing aerosols.
Futing Wang, Ting Yang, Zifa Wang, Haibo Wang, and Xi Chen
Atmos. Meas. Tech. Discuss.,
Revised manuscript accepted for AMTShort summary
We develop a new algorithm to get the vertical mass concentration profiles of fine aerosol components based on the synergy of ground-based remote sensing for the first time. The comparisons with in situ observations and chemistry transport model validate the performance of algorithm. Uncertainties caused by input parameters are also assessed in this paper. We expected that the algorithm can provide a new idea for lidar inversion and promote the development of aerosol components profiles.
Dawei Tang, Tianwen Wei, Jinlong Yuan, Haiyun Xia, and Xiankang Dou
Atmos. Meas. Tech., 15, 2819–2838,Short summary
During 11–20 March 2020, three aerosol transport events were investigated by a lidar system and an online bioaerosol detection system in Hefei, China. Observation results reveal that the events not only contributed to high particulate matter pollution but also to the transport of external bioaerosols, resulting in changes in the fraction of fluorescent biological aerosol particles. This detection method improved the time resolution and provided more parameters for aerosol detection.
Liqiao Lei, Timothy A. Berkoff, Guillaume Gronoff, Jia Su, Amin R. Nehrir, Yonghua Wu, Fred Moshary, and Shi Kuang
Atmos. Meas. Tech., 15, 2465–2478,Short summary
Aerosol extinction in the UVB (280–315 nm) is difficult to retrieve using simple lidar techniques due to the lack of lidar ratios at those wavelengths. The 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City region provided the opportunity to characterize the lidar ratio for UVB aerosol retrieval for the Langley Mobile Ozone Lidar (LMOL). A 292 nm aerosol product comparison between the NASA Langley High Altitude Lidar Observatory (HALO) and LMOL was also carried out.
Jan-Lukas Tirpitz, Udo Frieß, Robert Spurr, and Ulrich Platt
Atmos. Meas. Tech., 15, 2077–2098,Short summary
MAX-DOAS is a widely used measurement technique for the remote detection of atmospheric aerosol and trace gases. It relies on the analysis of ultra-violet and visible radiation spectra of skylight. To date, information contained in the skylight's polarisation state has not been utilised. On the basis of synthetic data, we carried out sensitivity analyses to assess the potential of polarimetry for MAX-DOAS applications.
Thibault Vaillant de Guélis, Gérard Ancellet, Anne Garnier, Laurent C.-Labonnote, Jacques Pelon, Mark A. Vaughan, Zhaoyan Liu, and David M. Winker
Atmos. Meas. Tech., 15, 1931–1956,Short summary
A new IIR-based cloud and aerosol discrimination (CAD) algorithm is developed using the IIR brightness temperature differences for cloud and aerosol features confidently identified by the CALIOP version 4 CAD algorithm. IIR classifications agree with the majority of V4 cloud identifications, reduce the ambiguity in a notable fraction of
not confidentV4 cloud classifications, and correct a few V4 misclassifications of cloud layers identified as dense dust or elevated smoke layers by CALIOP.
James A. Limbacher, Ralph A. Kahn, and Jaehwa Lee
Atmos. Meas. Tech. Discuss.,
Revised manuscript accepted for AMTShort summary
Launched in December 1999, NASA’s Multi-angle Imaging SpectroRadiometer (MISR) has given researchers qualitative constraints on aerosol particle properties for the past 22 years. Here, we present a new MISR research aerosol retrieval algorithm (RA) that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address limitations of the MISR operational aerosol retrieval algorithm and improve retrievals of aerosol particle properties.
Marco Di Paolantonio, Davide Dionisi, and Gian Luigi Liberti
Atmos. Meas. Tech., 15, 1217–1231,Short summary
A procedure for the characterization of the lidar transmitter–receiver geometry was developed. This characterization is currently implemented in the Rome RMR lidar to optimize the telescope/beam alignment, retrieve the overlap function, and estimate the absolute and relative tilt of the laser beam. This procedure can be potentially used to complement the standard EARLINET quality assurance tests.
Monica Campanelli, Henri Diémoz, Anna Maria Siani, Alcide di Sarra, Anna Maria Iannarelli, Rei Kudo, Gabriele Fasano, Giampietro Casasanta, Luca Tofful, Marco Cacciani, Paolo Sanò, and Stefano Dietrich
Atmos. Meas. Tech., 15, 1171–1183,Short summary
The aerosol optical depth (AOD) characteristics in an urban area of Rome were retrieved over a period of 11 years (2010–2020) to determine, for the first time, their effect on the incoming ultraviolet (UV) solar radiation. The surface forcing efficiency shows that the AOD is the primary parameter affecting the surface irradiance in Rome, and it is found to be greater for smaller zenith angles and for larger and more absorbing particles in the UV range (such as, e.g., mineral dust).
Jean-Claude Roger, Eric Vermote, Sergii Skakun, Emilie Murphy, Oleg Dubovik, Natacha Kalecinski, Bruno Korgo, and Brent Holben
Atmos. Meas. Tech., 15, 1123–1144,Short summary
From measurements of the sky performed by AERONET, we determined the microphysical properties of the atmospheric particles (aerosols) for each AERONET site. We used the aerosol optical thickness and its variation over the visible spectrum. This allows us to determine an aerosol model useful for (but not only) the validation of the surface reflectance satellite-derived product. The impact of the aerosol model uncertainties on the surface reflectance validation has been found to be 1 % to 3 %.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091,Short summary
This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
Antti Lipponen, Jaakko Reinvall, Arttu Väisänen, Henri Taskinen, Timo Lähivaara, Larisa Sogacheva, Pekka Kolmonen, Kari Lehtinen, Antti Arola, and Ville Kolehmainen
Atmos. Meas. Tech., 15, 895–914,Short summary
We have developed a machine-learning-based model that can be used to correct the Sentinel-3 satellite-based aerosol parameter data of the Synergy data product. The strength of the model is that the original satellite data processing does not have to be carried out again but the correction can be carried out with the data already available. We show that the correction significantly improves the accuracy of the satellite aerosol parameters.
Vinay Kayetha, Omar Torres, and Hiren Jethva
Atmos. Meas. Tech., 15, 845–877,Short summary
Existing measurements of spectral aerosol absorption are limited, particularly in the UV region. We use the synergy of satellite and ground measurements to derive spectral single scattering albedo of aerosols from the UV–visible spectrum. The resulting spectral SSAs are used to investigate seasonality in absorption for carbonaceous, dust, and urban aerosols. Regional aerosol absorption models that could be used to make reliable assumptions in satellite remote sensing of aerosols are derived.
Goutam Choudhury and Matthias Tesche
Atmos. Meas. Tech., 15, 639–654,Short summary
Aerosols are tiny particles suspended in the atmosphere. A fraction of these particles can form clouds and are called cloud condensation nuclei (CCN). Measurements of such aerosol particles are necessary to study the aerosol–cloud interactions and reduce the uncertainty in our future climate predictions. We present a novel methodology to estimate global 3D CCN concentrations from the CALIPSO satellite measurements. The final data set will be used to study the aerosol–cloud interactions.
Hiroshi Ishimoto, Masahiro Hayashi, and Yuzo Mano
Atmos. Meas. Tech., 15, 435–458,Short summary
Using data from the Infrared Atmospheric Sounding Interferometer (IASI) measurements of volcanic ash clouds (VACs) and radiative transfer calculations, we attempt to simulate the measured brightness temperature spectra (BTS) of volcanic ash aerosols in the infrared region. In particular, the dependence on the ash refractive index (RI) model is investigated.
Roberto Román, Juan C. Antuña-Sánchez, Victoria E. Cachorro, Carlos Toledano, Benjamín Torres, David Mateos, David Fuertes, César López, Ramiro González, Tatyana Lapionok, Marcos Herreras-Giralda, Oleg Dubovik, and Ángel M. de Frutos
Atmos. Meas. Tech., 15, 407–433,Short summary
An all-sky camera is used to obtain the relative sky radiance, and this radiance is used as input in an inversion code to obtain aerosol properties. This paper is really interesting because it pushes forward the use and capability of sky cameras for more advanced science purposes. Enhanced aerosol properties can be retrieved with accuracy using only an all-sky camera, but synergy with other instruments providing aerosol optical depth could even increase the power of these low-cost instruments.
Frithjof Ehlers, Thomas Flament, Alain Dabas, Dimitri Trapon, Adrien Lacour, Holger Baars, and Anne Grete Straume-Lindner
Atmos. Meas. Tech., 15, 185–203,Short summary
The Aeolus satellite observes the Earth and can vertically detect any kind of particles (aerosols or clouds) in the atmosphere below it. These observations are typically very noisy, which needs to be accounted for. This work dampens the noise in Aeolus' aerosol and cloud data, which are provided publicly by the ESA, so that the scientific community can make better use of it. This makes the data potentially more useful for weather prediction and climate research.
Alberto Sorrentino, Alessia Sannino, Nicola Spinelli, Michele Piana, Antonella Boselli, Valentino Tontodonato, Pasquale Castellano, and Xuan Wang
Atmos. Meas. Tech., 15, 149–164,Short summary
We present a novel approach that can be used to obtain microphysical properties of atmospheric aerosol, up to several kilometers in the atmosphere, from lidar measurements taken from the ground. Our approach provides accurate reconstructions under many different experimental conditions. Our results can contribute to the expansion of the use of remote sensing techniques for air quality monitoring and atmospheric science in general.
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,Short summary
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).
Thomas Flament, Dimitri Trapon, Adrien Lacour, Alain Dabas, Frithjof Ehlers, and Dorit Huber
Atmos. Meas. Tech., 14, 7851–7871,Short summary
This paper presents the main algorithms of the Aeolus Level 2 aerosol optical properties product. The processing chain was developed under contract with ESA. We show that the ALADIN instrument, although primarily designed to retrieve atmospheric winds, is also able to provide valuable information about aerosol and cloud optical properties. The algorithms are detailed, and validation on simulated and real examples is shown.
Oscar S. Sandvik, Johan Friberg, Moa K. Sporre, and Bengt G. Martinsson
Atmos. Meas. Tech., 14, 7153–7165,Short summary
A method to form SO2 profiles in the stratosphere with high vertical resolution following volcanic eruptions is introduced. The method combines space-based high-resolution vertical aerosol profiles and SO2 measurements the first 2 weeks after an eruption with air mass trajectory analyses. The SO2 is located at higher altitude than in most previous studies. The detailed resolution of the SO2 profile is unprecedented compared to other methods.
Igor B. Konovalov, Nikolai A. Golovushkin, Matthias Beekmann, Mikhail V. Panchenko, and Meinrat O. Andreae
Atmos. Meas. Tech., 14, 6647–6673,Short summary
The absorption of solar light by organic matter, known as brown carbon (BrC), contributes significantly to the radiative budget of the Earth’s atmosphere, but its representation in atmospheric models is uncertain. This paper advances a methodology to constrain model parameters characterizing BrC absorption of atmospheric aerosol originating from biomass burning with the available remote ground-based observations of atmospheric aerosol.
Xiaoxia Shang, Tero Mielonen, Antti Lipponen, Elina Giannakaki, Ari Leskinen, Virginie Buchard, Anton S. Darmenov, Antti Kukkurainen, Antti Arola, Ewan O'Connor, Anne Hirsikko, and Mika Komppula
Atmos. Meas. Tech., 14, 6159–6179,Short summary
The long-range-transported smoke particles from a Canadian wildfire event were observed with a multi-wavelength Raman polarization lidar and a ceilometer over Kuopio, Finland, in June 2019. The optical properties and the mass concentration estimations were reported for such aged smoke aerosols over northern Europe.
Yun He, Yunfei Zhang, Fuchao Liu, Zhenping Yin, Yang Yi, Yifan Zhan, and Fan Yi
Atmos. Meas. Tech., 14, 5939–5954,Short summary
The POLIPHON method can retrieve the height profiles of dust-related particle mass and ice-nucleating particle (INP) concentrations. Applying a dust case data set screening scheme based on the lidar-derived depolarization ratio (rather than Ångström exponent for 440–870 nm and AOD at 532 nm), the mixed-dust-related conversion factors are retrieved from sun photometer observations over Wuhan, China. This method may potentially be extended to regions influenced by mixed dust.
Marcin L. Witek, Michael J. Garay, David J. Diner, Michael A. Bull, Felix C. Seidel, Abigail M. Nastan, and Earl G. Hansen
Atmos. Meas. Tech., 14, 5577–5591,Short summary
This article documents the development and testing of a new near real-time (NRT) aerosol product from the MISR instrument on NASA’s Terra platform. The NRT product capitalizes on the unique attributes of the MISR retrieval approach, which leads to a high-quality and reliable aerosol data product. Several modifications are described that allow for rapid product generation within a 3 h window following acquisition. Implications for the product quality and consistency are discussed.
Zhihao Song, Bin Chen, Yue Huang, Li Dong, and Tingting Yang
Atmos. Meas. Tech., 14, 5333–5347,Short summary
The linear hybrid machine learning model achieves the expected target well. The overall inversion accuracy (R2) of the model is 0.84, and the RMSE is 12.92 µg m−3. R2 was above 0.7 in more than 70 % of the sites, whereas RMSE and mean absolute error were below 20 and 15 µg m−3, respectively. There was severe pollution in winter with an average PM2.5 concentration of 62.10 µg m−3. However, there was only slight pollution in summer with an average PM2.5 concentration of 47.39 µg m−3.
Scott P. Seymour and Matthew R. Johnson
Atmos. Meas. Tech., 14, 5179–5197,Short summary
Field measurements of gas flare emissions often assume that combustion species are spatially and temporally correlated in the plume. By measuring black carbon (BC) and water vapour in turbulent lab-scale flare plumes, this study shows that the well-correlated species assumption is not universally valid and that field measurements may be subject to large added uncertainty. Further analysis suggests that this uncertainty is easily avoided, and initial guidance is provided on sampling protocols.
William G. K. McLean, Guangliang Fu, Sharon P. Burton, and Otto P. Hasekamp
Atmos. Meas. Tech., 14, 4755–4771,Short summary
In this study, we present results from aerosol retrievals using both synthetic and real lidar datasets, including measurements from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined initiative between NASA and SRON (the Netherlands Institute for Space Research). Aerosol microphysical retrievals were performed using the High Spectral Resolution Lidar-2 (HSRL-2) setup, alongside several others, with the ACEPOL retrievals also compared to polarimeter retrievals.
Hyunkwang Lim, Sujung Go, Jhoon Kim, Myungje Choi, Seoyoung Lee, Chang-Keun Song, and Yasuko Kasai
Atmos. Meas. Tech., 14, 4575–4592,Short summary
Aerosol property observations by satellites from geostationary Earth orbit (GEO) in particular have advantages of frequent sampling better than 1 h in addition to broader spatial coverage. This study provides data fusion products of aerosol optical properties from four different algorithms for two different GEO satellites: GOCI and AHI. The fused aerosol products adopted ensemble-mean and maximum-likelihood estimation methods. The data fusion provides improved results with better accuracy.
Thomas Rieutord, Sylvain Aubert, and Tiago Machado
Atmos. Meas. Tech., 14, 4335–4353,Short summary
This article describes two methods to estimate the height of the very first layer of the atmosphere. It is measured with aerosol lidars, and the two new methods are based on machine learning. Both are open source and available under free licenses. A sensitivity analysis and a 2-year evaluation against meteorological balloons were carried out. One method has a good agreement with balloons but is limited by training, and the other has less good agreement with balloons but is more flexible.
Meng Gao, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, Richard Ferrare, Joel Gales, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Brent McBride, Anin Puthukkudy, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 14, 4083–4110,Short summary
Multi-angle polarimetric measurements can retrieve accurate aerosol properties over complex atmosphere and ocean systems; however, most retrieval algorithms require high computational costs. We propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems and then conduct simultaneous aerosol and ocean color retrievals on AirHARP measurements. The computational acceleration is 103 times with CPU or 104 times with GPU.
Thomas Wagner, Steffen Dörner, Steffen Beirle, Sebastian Donner, and Stefan Kinne
Atmos. Meas. Tech., 14, 3871–3893,Short summary
We compare measured and simulated O4 absorptions for conditions of extremely low aerosol optical depth, for which the uncertainties related to imperfect knowledge of aerosol properties do not significantly affect the comparison results. The simulations underestimate the measurements by 15 % to 20 %. Even if no aerosols are considered, the simulated O4 absorptions are systematically lower than the measurements. Our results indicate a fundamental inconsistency between simulations and measurements.
Yingxi R. Shi, Robert C. Levy, Leiku Yang, Lorraine A. Remer, Shana Mattoo, and Oleg Dubovik
Atmos. Meas. Tech., 14, 3449–3468,Short summary
Due to fast industrialization and development, China has been experiencing haze pollution episodes with both high frequencies and severity over the last 3 decades. This study improves the accuracy and data coverage of measured aerosol from satellites, which help quantify, characterize, and understand the impact of the haze phenomena over the entire East Asia region.
Rei Kudo, Henri Diémoz, Victor Estellés, Monica Campanelli, Masahiro Momoi, Franco Marenco, Claire L. Ryder, Osamu Ijima, Akihiro Uchiyama, Kouichi Nakashima, Akihiro Yamazaki, Ryoji Nagasawa, Nozomu Ohkawara, and Haruma Ishida
Atmos. Meas. Tech., 14, 3395–3426,Short summary
A new method, Skyrad pack MRI version 2, was developed to retrieve aerosol physical and optical properties, water vapor, and ozone column concentrations from the sky radiometer, a filter radiometer deployed in the SKYNET international network. Our method showed good performance in a radiative closure study using surface solar irradiances from the Baseline Surface Radiation Network and a comparison using aircraft in situ measurements of Saharan dust events during the SAVEX-D 2015 campaign.
Kirk Knobelspiesse, Amir Ibrahim, Bryan Franz, Sean Bailey, Robert Levy, Ziauddin Ahmad, Joel Gales, Meng Gao, Michael Garay, Samuel Anderson, and Olga Kalashnikova
Atmos. Meas. Tech., 14, 3233–3252,Short summary
We assessed atmospheric aerosol and ocean surface wind speed remote sensing capability with NASA's Multi-angle Imaging SpectroRadiometer (MISR), using synthetic data and a Bayesian inference technique called generalized nonlinear retrieval analysis (GENRA). We found success using three aerosol parameters plus wind speed. This shows that MISR can perform an atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same spacecraft (Terra).
Antti Lipponen, Ville Kolehmainen, Pekka Kolmonen, Antti Kukkurainen, Tero Mielonen, Neus Sabater, Larisa Sogacheva, Timo H. Virtanen, and Antti Arola
Atmos. Meas. Tech., 14, 2981–2992,Short summary
We have developed a new computational method to post-process-correct the satellite aerosol retrievals. The proposed method combines the conventional satellite aerosol retrievals relying on physics-based models and machine learning. The results show significantly improved accuracy in the aerosol data over the operational satellite data products. The correction can be applied to the existing satellite aerosol datasets with no need to fully reprocess the much larger original radiance data.
Alexander Vasilkov, Nickolay Krotkov, Eun-Su Yang, Lok Lamsal, Joanna Joiner, Patricia Castellanos, Zachary Fasnacht, and Robert Spurr
Atmos. Meas. Tech., 14, 2857–2871,Short summary
To explicitly account for aerosol effects in the OMI cloud and nitrogen dioxide algorithms, we use a model of aerosol optical properties from a global aerosol assimilation system and radiative transfer computations. Accounting for anisotropic reflection of Earth's surface is an important feature of the approach. Comparisons of the cloud and tropospheric nitrogen dioxide retrievals with implicit and explicit aerosol corrections are carried out for a selected area with high pollution.
Verena Schenzinger and Axel Kreuter
Atmos. Meas. Tech., 14, 2787–2798,Short summary
When measuring the aerosol optical depth of the atmosphere, clouds in front of the sun lead to erroneously high values. Therefore, measurements that are potentially affected by clouds need to be removed from the dataset by an automatic process. As the currently used algorithm cannot reliably identify thin clouds, we developed a new one based on a method borrowed from machine learning. Tests with 10 years of data show improved performance of the new routine and therefore higher data quality.
Anton Lopatin, Oleg Dubovik, David Fuertes, Georgiy Stenchikov, Tatyana Lapyonok, Igor Veselovskii, Frank G. Wienhold, Illia Shevchenko, Qiaoyun Hu, and Sagar Parajuli
Atmos. Meas. Tech., 14, 2575–2614,Short summary
The article presents novelties in characterizing fine particles suspended in the air by means of combining various measurements that observe light propagation in atmosphere. Several non-coincident observations (some of which require sunlight, while others work only at night) could be united under the assumption that aerosol properties do not change drastically at nighttime. It also proposes how to describe particles' composition in a simplified manner that uses new types of observations.
Felix Wrana, Christian von Savigny, Jacob Zalach, and Larry W. Thomason
Atmos. Meas. Tech., 14, 2345–2357,Short summary
In this paper, we describe a new method for calculating the size of naturally occurring droplets (aerosols) made mostly of sulfuric acid and water that can be found roughly at 20 km altitude in the atmosphere. We use data from the instrument SAGE III/ISS that is mounted on the International Space Station. We show that our method works well, and that the size parameters we calculate are reasonable and can be a valuable addition for a better understanding of aerosols and their effect on climate.
Juan C. Antuña-Sánchez, Roberto Román, Victoria E. Cachorro, Carlos Toledano, César López, Ramiro González, David Mateos, Abel Calle, and Ángel M. de Frutos
Atmos. Meas. Tech., 14, 2201–2217,Short summary
This paper presents a new technique to exploit the potential of all-sky cameras. The sky radiance at three effective wavelengths is calculated and compared with alternative measurements and simulated data. The proposed method will be useful for the retrieval of aerosol and cloud properties.
Bradley M. Conrad and Matthew R. Johnson
Atmos. Meas. Tech., 14, 1573–1591,Short summary
A general uncertainty analysis (GUA) is performed for the sky-LOSA technique used to remotely measure soot emissions from gas flares. GUA data are compiled in an open-source software tool to help sky-LOSA users select critical setup and acquisition parameters while giving quantitative visual feedback on anticipated uncertainties for a specific measurement. The software tool enables easy acquisition of optimal measurement data, significantly increasing the accessibility of the sky-LOSA technique.
Charles K. Gatebe, Hiren Jethva, Ritesh Gautam, Rajesh Poudyal, and Tamás Várnai
Atmos. Meas. Tech., 14, 1405–1423,Short summary
The retrieval of aerosol parameters from passive satellite instruments in cloudy scenes is very challenging, partly because clouds and cloud-related processes significantly modify the aerosol properties and the 3D radiative effects. This study shows simultaneous retrieval of above-cloud aerosol optical depth and aerosol-corrected cloud optical depth from airborne measurements, thereby demonstrating a novel approach for assessing satellite retrievals of aerosols above clouds.
Ghassan Taha, Robert Loughman, Tong Zhu, Larry Thomason, Jayanta Kar, Landon Rieger, and Adam Bourassa
Atmos. Meas. Tech., 14, 1015–1036,Short summary
This work describes the newly released OMPS LP aerosol extinction profile multi-wavelength Version 2.0 algorithm and dataset. It is shown that the V2.0 aerosols exhibit significant improvements in OMPS LP retrieval performance in the Southern Hemisphere and at lower altitudes. The new product is compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies.
Soheila Jafariserajehlou, Vladimir V. Rozanov, Marco Vountas, Charles K. Gatebe, and John P. Burrows
Atmos. Meas. Tech., 14, 369–389,Short summary
In this work, we study retrieval of snow grain morphologies and their impact on the reflectance in a coupled snow–atmosphere system. We present a sensitivity study to highlight the importance of having adequate information about snow and atmosphere. A novel two-stage algorithm for retrieving the size and shape of snow grains is presented. The reflectance simulation results are compared to that of airborne measurements; high correlations of 0.98 at IR and 0.88–0.98 at VIS are achieved.
Antonis Gkikas, Emmanouil Proestakis, Vassilis Amiridis, Stelios Kazadzis, Enza Di Tomaso, Alexandra Tsekeri, Eleni Marinou, Nikos Hatzianastassiou, and Carlos Pérez García-Pando
Atmos. Meas. Tech., 14, 309–334,Short summary
We present the development of the MIDAS (ModIs Dust AeroSol) data set, providing daily dust optical depth (DOD; 550 nm) at a global scale and fine spatial resolution (0.1° x 0.1°) over a 15-year period (2003–2017). It has been developed via the synergy of MODIS-Aqua and MERRA-2 data, while CALIOP and AERONET retrievals are used for its assessment. MIDAS upgrades existing dust observational capabilities, and it is suitable for dust climatological studies, model evaluation, and data assimilation.
Arai, E., Pereira, G., Coura, S. M. C., Cardozo, F. S., Silva, F. B., Shimabukuro, Y. E., Moraes, E. C., Freitsa, R. M., and Espirito-Santo, F. D. B.: Spectral signature of leaves of Amazon rainforest tree species, IGARSS, 2011 IEEE International, 4788–4791, 2010.
Asner, G. P., Wessman, C. A., Bateson, C. A., and Privette, J. L.: Impact of tissue, canopy, and landscape factors on the hyperspectral reflectance variability of arid ecosystems, Remote Sens. Environ., 74, 69–84, 2000.
Betts, R. A.: Offset of the potential carbon sink from boreal forestation by decreases in surface albedo, Nature, 408, 187–190, 2000.
Ceccato, P., Flasse, S., Tarantola, S., Jacquemoud, S., and Gregoire, J. M.: Detecting vegetation leaf water content using reflectance in the optical domain, Remote Sens. Environ., 77, 22–33, 2001.
Cess, R. D.: Biosphere-albedo feedback and climate modeling, J. Atmos. Sci., 35, 1765–1767, 1978.
Clark, R. N., Swayze, G. A., Wise, R., Livo, E., Hoefen, T., Kokaly, R., and Sutley, S. J.: USGS digital spectral library splib06a: US Geological Survey, Digital Data Series 231, http://speclab.cr.usgs.gov/spectral.lib06 (last access: November 2012), 2007.
Collins, W.: Remote sensing of crop type and maturity, Engineering, 44, 43–55, 1978.
Dickinson, R. E.: Land surface processes and climate-Surface albedos and energy balance. Advances in Geophysics, 25, 305–353, Theory of Climate, Academic Press Inc. Published by Elsevier Ltd, 1983.
Dickinson, R. E.: Land processes in climate models, Remote Sens. Environ., 51, 27–38, 1995.
Diner, D.: Level 2 surface retrieval algorithm theoretical basis, JPL 11401, Revision E, 2008.
Dirmeyer, P. A. and Shukla, J.: The response of the general circulation to deforestation in the tropics, American Meteorology Society, Proc., 5th Symposium on Global Change, 131–134, 1994.
Dubovik, O., Holben, B. N., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D., Tanré, D., and Slutsker, I.: Variability of absorption and optical properties of key aerosol types observed in worldwide locations, J. Atmos. Sci., 59, 590–608, 2002.
Eck, T. F., Holben, B. N., Ward, D. E., Mukelabai, M. M., Dubovik, O., Smirnov, A., Schafer, J. S., Hsu, N. C., Piketh, S. J., Queface, A., Le Roux, J., Swap, R. J., and Slutsker, I.: Variability of biomass burning aerosol optical characteristics in southern Africa during the SAFARI 2000 dry season campaign and a comparison of single scattering albedo estimates from radiometric measurements, J. Geophys. Res., 108, 8477, https://doi.org/10.1029/2002JD002321, 2003.
Gilgen, H., Whitlock, C., Koch, F., Müller, G., Ohmura, A., Steiger, D., and Wheeler, R.: Technical Plan for BSRN (Baseline Surface Radiation Network) Data Management, Version 2.1 (final), MO/TD-No. 443, WCRP/WMO, 1995.
Gitelson, A. A., Merzlyak, M. N., and Lichtenthaler, H. K.: Detection of red edge position and Chlorophyll content by reflectance measurements near 700 nm, J. Plant Physiol., 148, 501–508, 1996.
Guyot, G., Baret, F., and Jacquemoud, S.: Imaging spectroscopy for vegetation studies, Imaging Spectroscopy: Fundamentals and Prospective Applications, in: Remote Sensing, Volume 2, edited by: Toselli, F. and Bodechtel, J., Kluwer Academic Publishers, 145–165, 1992.
Hall, F. G. and Sellers, P. J.: First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) in 1995, J. Geophys. Res., 100, 25383–25395, https://doi.org/10.1029/95JD03300, 1995.
Hoffer, R. M.: Biological and physical considerations in applying computer-aided analysis techniques to remote sensing data, in: Remote Sensing: The Quantitative Approach, edited by: Swain, P. H. and Davis, S. M., McGraw-Hill, 227–289, 1978.
Horler, D. N. H., Dockray, M., and Barber, J.: The red edge of plant leaf reflectance, Int. J. Remote Sens., 1, 121–136, 1983.
Hosgood, B., Jacquemoud, S., Andreoli, G., Verdebout, J., Pedrini, A., and Schmuck, G.: Leaf Optical Properties EXperiment 93 (LOPEX93), Report EUR 16095 EN, 1994.
Kim, M. S., Daughtry, C. S., Chappelle, E. W., Mcmurtrey, J. E., and Walthall, C. L.: The use of high spectral resolution bands for estimating absorbed photonsynthetically active radiation (A PAR), in: Proceedings of the 6th Symposium on Physical Measurements and Signatures in Remote Sensing, Val D'Isere, France, 17–21 January, 299–306, 1994.
Koelemeijer, R. B. A., de Haan, J. F., and Stammes, P.: A database of spectral surface reflectivity in the range 335–772 nm derived from 5.5 years of GOME observations, J. Geophys. Res., 108, 4070, https://doi.org/10.1029/2002JD002429, 2003.
Leroy, M., Deuze, J. L., Breon, F. M., Hautecoeur, O., Herman, M., Buriez, J. C., Tanre, D., Bouffies, S., Chazette, P., and Roujean, J. L.: Retrieval of atmospheric properties and surface bidirectional reflectances over land from POLDER/ADEOS, J. Geophys. Res., 102, 17023–17037, 1997.
Liang, S., Strahler, A. H., and Walthall, C.: Retrieval of land surface albedo from satellite observations: a simulation study, J. Appl. Meteorol., 38, 712–725, 1999.
Lofgren, B. M.: Surface albedo-climate feedback simulated using two-way coupling, J. Climate, 8, 2543–2562, 1995.
Lucht, W., Schaaf, C. B., and Strahler, A. H.: An algorithm for the retrieval of albedo from space using semiempirical BRDF models, IEEE Geosci. Remote S., 38, 977–998, 2000.
Lucht, W., Prentice, I. C., Myneni, R. B., Sitch, S., Friedlingstein, P., Cramer, W., Bousquet, P., Buermann, W., and Smith, B.: Climatic control of the high-latitude vegetation greening trend and pinatubo effect, Science, 296, 1687–1689, https://doi.org/10.1126/science.1071828, 2002.
Lyapustin, A. I.: Atmospheric and geometrical effects on land surface albedo, J. Geophys. Res., 104, 4127–4143, https://doi.org/10.1029/1998JD200064, 1999.
McComiskey, A., Schwartz, S. E., Schmid, B., Guan, H., Lewis, E. R., Ricchiazzi, P., and Ogren, J. A.: Direct aerosol forcing: Calculation from observables and sensitivities to inputs, J. Geophys. Res., 113, D09202, https://doi.org/10.1029/2007JD009170, 2008.
Moody, E. G., King, M. D., Platnick, S., Schaaf, C. B., and Gao, F.: Spatially complete global spectral surface albedos: value-added datasets derived from Terra MODIS land products, IEEE Geosci. Remote S., 43, 144–158, 2005.
Muller, J.-P.: MERIS GLOBAL LAND SURFACE ALBEDO MAPS: Algorithm Theoretical Basis Document ATBD 1.4 BRDF/ALBEDO RETRIEVAL, available at: http://www.brockmann-consult.de/albedomap/pdf/MERIS-AlbedoMap-ATBD_BRDF_Albedo-1.0.pdf (last access: May 2012), 2006.
Myhre, G., Kvalevåg, M. M., and Schaaf, C. B.: Radiative frocing due to anthropogenic vegetation change based on MODIS surface albedo data, Geophys. Res. Lett., 32, L21410, https://doi.org/10.1029/2005GL024004, 2005.
Nobre, C. A., Sellers, P. S., and Shukla, J.: Amazonian deforestation and regional climate change, J. Climate, 4, 957–988, 1991.
Patadi, F., Yang, E.-S., and Christopher, S. A.: Does dust change the clear sky top of atmosphere shortwave flux over high surface reflectance regions? Geophys. Res. Lett., 36, L15825, https://doi.org/10.1029/2009GL039092, 2009.
Popp, C., Wang, P., Brunner, D., Stammes, P., Zhou, Y., and Grzegorski, M.: MERIS albedo climatology for FRESCO + O2 A-band cloud retrieval, Atmos. Meas. Tech., 4, 463–483, https://doi.org/10.5194/amt-4-463-2011, 2011.
Procopio, A. S., Remer, L. A., Artaxo, P., Kaufman, Y. J., and Holben, B. N.: Modeled spectral optical properties for smoke aerosols in Amazonia, Geophys. Res. Lett., 30, 2265, https://doi.org/10.1029/2003GL018063, 2003.
Ricchiazzi, P., Yang, S., Gautier, C., and Sowle, D.: SBDART: A research and teaching software tool for plane-parallel radiative transfer in the Earth's atmosphere, B. Am. Meteorol. Soc., 79, 2101–2114, 1998.
Roberts, D. A., Nelson, B. W., Adams, J. B., and Palmer, F.: Spectral changes with leaf aging in Amazon caatinga, Trees – Structure and Function, 12, 315–325, https://doi.org/10.1007/s004680050157, 1990.
Saunders, R. W.: The determination of broad band surface albedo from AVHRR visible and near-infrared radiances, Int. J. Remote Sens., 11, 49–67, 1990.
Schaaf, C. B., Gao, F., Strahler, A. H., Lucht, W., Li, X., and Tsnag, T.: First operational BRDF, albedo nadir reflectance products from MODIS, Remote Sens. Environ., 83, 135–148, 2002.
Sei, A: Joint Polar Satellite System (JPSS) VIIRS surface albedo algorithm theoretical basis document (ATBD), GSFC JPSS CMO 474-00040, available at: http://npp.gsfc.nasa.gov/science/sciencedocuments/ATBD_122011/474-00040_VIIRS_Surface_Albedo_ATBD_Rev-_20110422.pdf (last access: November 2012), 2011.
Sellers, P. J., Hall, F. G., Asrar, G., Strebel, D. E., and Murphy, R. E.: An overview of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), J. Geophys. Res., 97, 18355–18371, 1992.
Shukla, J., Nobre, C., and Sellers, P.: Amazon Deforestation and climate change, Science, 247, 1322–1325, https://doi.org/10.1126/science.247.4948.1322, 1990.
Sims, D. A. and Gamon, J. A.: Relationship between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages, Remote Sens. Environ., 81, 337–354, 2002.
Staenz, K., Williams, D. J., and Walker, B.: Surface reflectance retrieval from AVIRIS data using a six dimensional look up table, in: Summaries of the Sixth Annual JPL Earth Science Workshop, Jet Propulsion Laboratory, Pasadena, CA, 223–230, 1996.
Stimson, H. C., Breshears, D. D., Ustin, S. L., and Kefauver, S. C.: Spectral sensing of folier water conditions in two co-occuring conifer species: Pinus edulis and Juniperus monosperma, Remote Sens. Environ., 96, 108–118, 2005.
Vermote, E. F, Saleous, N. E., Justice, C. O., Kaufman, Y. J., Privette, J. L., and Remer, L.: Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation, J. Geophys. Res., 102, 17131–17141, https://doi.org/10.1029/97JD00201, 1997.
Wang, P., Knap, W. H., and Stammes, P.: Cloudy sky shortwave radiative closure for a Baseline Surface Radiation Network site, J. Geophys. Res., 116, D08202, https://doi.org/10.1029/2010JD015141, 2011.
Wiscombe, W. J.: Improved Mie scattering algorithm, Appl. Optics, 19, 1505–1509, 1980.
Yu, H., Dickinson, R. E., Chin, M., Kaufman, Y. J., Zhou, M., Zhou, L., Tian, Y., Dubovik, O., and Holben, B. N.: The direct radiative effect of aerosols as determined from a combination of MODIS retrievals and GOCART simulations, J. Geophys. Res., 109, D03206, https://doi.org/10.1029/2003JD003914, 2004.
Yu, H., Kaufman, Y. J., Chin, M., Feingold, G., Remer, L. A., Anderson, T. L., Balkanski, Y., Bellouin, N., Boucher, O., Christopher, S., DeCola, P., Kahn, R., Koch, D., Loeb, N., Reddy, M. S., Schulz, M., Takemura, T., and Zhou, M.: A review of measurement-based assessments of the aerosol direct radiative effect and forcing, Atmos. Chem. Phys., 6, 613–666, https://doi.org/10.5194/acp-6-613-2006, 2006.
Zhou, M., Yu, H., Dickinson, R. E., Dubovik, O., and Holben, B. N.: A normalized description of the direct effect of key aerosol types on solar radiation as estimated from aerosol robotic network aerosols and Moderate Resolution Imaging Spectroradiometer albedos, J. Geophys. Res., 110, D19202, https://doi.org/10.1029/2005JD005909, 2005.
Zhu, L., Martins, J. V., and Remer, L. A.: Biomass burning aerosol absorption measurements with MODIS using the critical reflectance method, J. Geophys. Res., 116, D07202, https://doi.org/10.1029/2010JD015187, 2011.