Articles | Volume 11, issue 7
https://doi.org/10.5194/amt-11-4093-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-4093-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jul 2018
Research article |
| 16 Jul 2018
| 16 Jul 2018
A cloud algorithm based on the O2-O2 477 nm absorption band featuring an advanced spectral fitting method and the use of surface geometry-dependent Lambertian-equivalent reflectivity
Alexander Vasilkov
CORRESPONDING AUTHOR
Science Systems and Applications Inc., Lanham, MD, USA
Eun-Su Yang
Science Systems and Applications Inc., Lanham, MD, USA
Sergey Marchenko
Science Systems and Applications Inc., Lanham, MD, USA
Wenhan Qin
Science Systems and Applications Inc., Lanham, MD, USA
Lok Lamsal
Universities Space Research Association, Columbia, MD, USA
Joanna Joiner
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Nickolay Krotkov
NASA Goddard Space Flight Center, Greenbelt, MD, USA
David Haffner
Science Systems and Applications Inc., Lanham, MD, USA
Pawan K. Bhartia
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Robert Spurr
RT Solutions Inc., Cambridge, MA, USA
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Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-66, https://doi.org/10.5194/amt-2023-66, 2023
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A pipeline for retrieving Total Column Water Vapor from satellite blue spectra is developed. New constraints are considered. Water-leaving radiance is important over the oceans. Results agree with reference datasets well under clear conditions. Due to high sensitivity to clouds, strict data filtering criteria are required. All-sky retrievals can be corrected using machine learning. GPS stations’ representation errors follow a power law relationship with grid resolutions.
Jianglong Zhang, Jeffrey S. Reid, Steven D. Miller, Miguel Román, Zhuosen Wang, Robert J. D. Spurr, and Shawn Jaker
Atmos. Meas. Tech., 16, 2531–2546, https://doi.org/10.5194/amt-16-2531-2023, https://doi.org/10.5194/amt-16-2531-2023, 2023
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We adapted the spherical harmonics discrete ordinate method 3-dimentional radiative transfer model (3-D RTM) and developed a nighttime 3-D RTM capability for simulating top-of-atmosphere radiances from artificial light sources for aerosol retrievals. Our study suggests that both aerosol optical depth and aerosol plume height can be effectively retrieved using nighttime observations over artificial light sources, through the newly developed radiative transfer modeling capability.
Nick Gorkavyi, Nickolay Krotkov, and Alexander Marshak
Atmos. Meas. Tech., 16, 1527–1537, https://doi.org/10.5194/amt-16-1527-2023, https://doi.org/10.5194/amt-16-1527-2023, 2023
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The article discusses topical issues of the visible (libration) motion of the Earth in the sky of the Moon in a rectangle measuring 13.4° × 15.8°. On the one hand, the librations of the Moon make these observations difficult. On the other hand, they can be used as a natural scanning mechanism for cameras and spectroscopes mounted on a fixed platform on the surface of the Moon.
Joanna Joiner, Sergey Marchenko, Zachary Fasnacht, Lok Lamsal, Can Li, Alexander Vasilkov, and Nickolay Krotkov
Atmos. Meas. Tech., 16, 481–500, https://doi.org/10.5194/amt-16-481-2023, https://doi.org/10.5194/amt-16-481-2023, 2023
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Nitrogen dioxide (NO2) is an important trace gas for both air quality and climate. NO2 affects satellite ocean color products. A new ocean color instrument – OCI (Ocean Color Instrument) – will be launched in 2024 on a NASA satellite. We show that it will be possible to measure NO2 from OCI even though it was not designed for this. The techniques developed here, based on machine learning, can also be applied to instruments already in space to speed up algorithms and reduce the effects of noise.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Ihab Abboud, Nickolay Krotkov, Peter J. T. Leonard, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Earth Syst. Sci. Data, 15, 75–93, https://doi.org/10.5194/essd-15-75-2023, https://doi.org/10.5194/essd-15-75-2023, 2023
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Sulfur dioxide (SO2) measurements from three satellite instruments were used to update and extend the previously developed global catalogue of large SO2 emission sources. This version 2 of the global catalogue covers the period of 2005–2021 and includes a total of 759 continuously emitting point sources. The catalogue data show an approximate 50 % decline in global SO2 emissions between 2005 and 2021, although emissions were relatively stable during the last 3 years.
Can Li, Joanna Joiner, Fei Liu, Nickolay A. Krotkov, Vitali Fioletov, and Chris McLinden
Atmos. Meas. Tech., 15, 5497–5514, https://doi.org/10.5194/amt-15-5497-2022, https://doi.org/10.5194/amt-15-5497-2022, 2022
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Satellite observations provide information on the sources of SO2, an important pollutant that affects both air quality and climate. However, these observations suffer from relatively poor data quality due to weak signals of SO2. Here, we use a machine learning technique to analyze satellite SO2 observations in order to reduce the noise and artifacts over relatively clean areas while keeping the signals near pollution sources. This leads to significant improvement in satellite SO2 data.
Jay Herman, Liang Huang, David Hafner, and Adam Szabo
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-481, https://doi.org/10.5194/acp-2022-481, 2022
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The research object is to see if reflections from clouds by the DSCOVR satellite at the Earth-Sun Lagrange point are enhanced as the backscattering angle nears 180 degrees. The 388 nm wavelength channel sees almost nothing from the Earth's surface. The result is that the Southern Hemisphere radiance increase in December 2020 and 2021 is likely caused by cloud amount increase and not by enhanced reflectivity at a 178-degree backscatter angle.
Aaron Pearlman, Monica Cook, Boryana Efremova, Francis Padula, Lok Lamsal, Joel McCorkel, and Joanna Joiner
Atmos. Meas. Tech., 15, 4489–4501, https://doi.org/10.5194/amt-15-4489-2022, https://doi.org/10.5194/amt-15-4489-2022, 2022
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NOAA’s Geostationary Extended Observations (GeoXO) constellation is planned to consist of an atmospheric composition instrument (ACX) to support air quality forecasting and monitoring. As design trade-offs are being studied, we investigated one parameter, the polarization sensitivity, which has yet to be fully documented for NO2 retrievals. Our simulation study explores these impacts to inform the ACX’s development and better understand polarization’s role in trace gas retrievals.
Jan-Lukas Tirpitz, Udo Frieß, Robert Spurr, and Ulrich Platt
Atmos. Meas. Tech., 15, 2077–2098, https://doi.org/10.5194/amt-15-2077-2022, https://doi.org/10.5194/amt-15-2077-2022, 2022
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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.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Nickolay Krotkov, Fei Liu, and Henk Eskes
Atmos. Chem. Phys., 22, 4201–4236, https://doi.org/10.5194/acp-22-4201-2022, https://doi.org/10.5194/acp-22-4201-2022, 2022
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The COVID-19 lockdown had a large impact on anthropogenic emissions and particularly on nitrogen dioxide (NO2). A new method of isolation of background, urban, and industrial components in NO2 is applied to estimate the lockdown impact on each of them. From 16 March to 15 June 2020, urban NO2 declined by −18 % to −28 % in most regions of the world, while background NO2 typically declined by less than −10 %.
Fei Liu, Zhining Tao, Steffen Beirle, Joanna Joiner, Yasuko Yoshida, Steven J. Smith, K. Emma Knowland, and Thomas Wagner
Atmos. Chem. Phys., 22, 1333–1349, https://doi.org/10.5194/acp-22-1333-2022, https://doi.org/10.5194/acp-22-1333-2022, 2022
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In this work, we present a novel method to infer NOx emissions and lifetimes based on tropospheric NO2 observations together with reanalysis wind fields for cities located in polluted backgrounds. We evaluate the accuracy of the method using synthetic NO2 observations derived from a high-resolution model simulation. Our work provides an estimate for uncertainties in satellite-derived emissions inferred from chemical transport model (CTM)-independent approaches.
Nick Gorkavyi, Nickolay Krotkov, Can Li, Leslie Lait, Peter Colarco, Simon Carn, Matthew DeLand, Paul Newman, Mark Schoeberl, Ghassan Taha, Omar Torres, Alexander Vasilkov, and Joanna Joiner
Atmos. Meas. Tech., 14, 7545–7563, https://doi.org/10.5194/amt-14-7545-2021, https://doi.org/10.5194/amt-14-7545-2021, 2021
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The 21 June 2019 eruption of the Raikoke volcano produced significant amounts of volcanic aerosols (sulfate and ash) and sulfur dioxide (SO2) gas that penetrated into the lower stratosphere. We showed that the amount of SO2 decreases with a characteristic period of 8–18 d and the peak of sulfate aerosol lags the initial peak of SO2 by 1.5 months. We also examined the dynamics of an unusual stratospheric coherent circular cloud of SO2 and aerosol observed from 18 July to 22 September 2019.
Luis Guanter, Cédric Bacour, Andreas Schneider, Ilse Aben, Tim A. van Kempen, Fabienne Maignan, Christian Retscher, Philipp Köhler, Christian Frankenberg, Joanna Joiner, and Yongguang Zhang
Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021, https://doi.org/10.5194/essd-13-5423-2021, 2021
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Sun-induced chlorophyll fluorescence (SIF) is an electromagnetic signal emitted by plants in the red and far-red parts of the spectrum. It has a functional link to photosynthesis and can be measured by satellite instruments, which makes it an important variable for the remote monitoring of the photosynthetic activity of vegetation ecosystems around the world. In this contribution we present a SIF dataset derived from the new Sentinel-5P TROPOMI missions.
Nicolas Theys, Vitali Fioletov, Can Li, Isabelle De Smedt, Christophe Lerot, Chris McLinden, Nickolay Krotkov, Debora Griffin, Lieven Clarisse, Pascal Hedelt, Diego Loyola, Thomas Wagner, Vinod Kumar, Antje Innes, Roberto Ribas, François Hendrick, Jonas Vlietinck, Hugues Brenot, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 16727–16744, https://doi.org/10.5194/acp-21-16727-2021, https://doi.org/10.5194/acp-21-16727-2021, 2021
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We present a new algorithm to retrieve sulfur dioxide from space UV measurements. We apply the technique to high-resolution TROPOMI measurements and demonstrate the high sensitivity of the approach to weak SO2 emissions worldwide with an unprecedented limit of detection of 8 kt yr−1. This result has broad implications for atmospheric science studies dealing with improving emission inventories and identifying and quantifying missing sources, in the context of air quality and climate.
Jerald R. Ziemke, Gordon J. Labow, Natalya A. Kramarova, Richard D. McPeters, Pawan K. Bhartia, Luke D. Oman, Stacey M. Frith, and David P. Haffner
Atmos. Meas. Tech., 14, 6407–6418, https://doi.org/10.5194/amt-14-6407-2021, https://doi.org/10.5194/amt-14-6407-2021, 2021
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Seasonal and interannual ozone profile climatologies are produced from combined MLS and MERRA-2 GMI ozone for the general public. Both climatologies extend from pole to pole at altitudes of 0–80 km (1 km spacing) for the time record from 1970 to 2018. These climatologies are important for use as a priori information in satellite ozone retrieval algorithms, as validation of other measured and model-simulated ozone, and in radiative transfer studies of the atmosphere.
Antti Arola, William Wandji Nyamsi, Antti Lipponen, Stelios Kazadzis, Nickolay A. Krotkov, and Johanna Tamminen
Atmos. Meas. Tech., 14, 4947–4957, https://doi.org/10.5194/amt-14-4947-2021, https://doi.org/10.5194/amt-14-4947-2021, 2021
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Methods to estimate surface UV radiation from satellite measurements offer the only means to obtain global coverage, and the development of satellite-based UV algorithms has been ongoing since the early 1990s. One of the main challenges in this development has been how to account for the overall effect of absorption by atmospheric aerosols. One such method was suggested roughly a decade ago, and in this study we propose further improvements for this kind of approach.
Lily N. Zhang, Susan Solomon, Kane A. Stone, Jonathan D. Shanklin, Joshua D. Eveson, Steve Colwell, John P. Burrows, Mark Weber, Pieternel F. Levelt, Natalya A. Kramarova, and David P. Haffner
Atmos. Chem. Phys., 21, 9829–9838, https://doi.org/10.5194/acp-21-9829-2021, https://doi.org/10.5194/acp-21-9829-2021, 2021
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In the 1980s, measurements at the British Antarctic Survey station in Halley, Antarctica, led to the discovery of the ozone hole. The Halley total ozone record continues to be uniquely valuable for studies of long-term changes in Antarctic ozone. Environmental conditions in 2017 forced a temporary cessation of operations, leading to a gap in the historic record. We develop and test a method for filling in the Halley record using satellite data and find evidence to further support ozone recovery.
Nikita M. Fedkin, Can Li, Nickolay A. Krotkov, Pascal Hedelt, Diego G. Loyola, Russell R. Dickerson, and Robert Spurr
Atmos. Meas. Tech., 14, 3673–3691, https://doi.org/10.5194/amt-14-3673-2021, https://doi.org/10.5194/amt-14-3673-2021, 2021
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This study presents a new volcanic sulfur dioxide (SO2) layer height retrieval algorithm for the Ozone Monitoring Instrument (OMI). We generated a large spectral dataset with a radiative transfer model and used it to train neural networks to predict SO2 height from OMI radiance data. The algorithm is fast and takes less than 10 min for a single orbit. Retrievals were tested on four eruption cases, and results had reasonable agreement (within 2 km) with other retrievals and previous studies.
Alexander Vasilkov, Nickolay Krotkov, Eun-Su Yang, Lok Lamsal, Joanna Joiner, Patricia Castellanos, Zachary Fasnacht, and Robert Spurr
Atmos. Meas. Tech., 14, 2857–2871, https://doi.org/10.5194/amt-14-2857-2021, https://doi.org/10.5194/amt-14-2857-2021, 2021
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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.
Juseon Bak, Xiong Liu, Robert Spurr, Kai Yang, Caroline R. Nowlan, Christopher Chan Miller, Gonzalo Gonzalez Abad, and Kelly Chance
Atmos. Meas. Tech., 14, 2659–2672, https://doi.org/10.5194/amt-14-2659-2021, https://doi.org/10.5194/amt-14-2659-2021, 2021
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We apply a principal component analysis (PCA)-based approach combined with lookup tables (LUTs) of corrections to accelerate the VLIDORT radiative transfer (RT) model used in the retrieval of ozone profiles from backscattered ultraviolet (UV) measurements by the Ozone Monitoring Instrument (OMI).
Eloise A. Marais, John F. Roberts, Robert G. Ryan, Henk Eskes, K. Folkert Boersma, Sungyeon Choi, Joanna Joiner, Nader Abuhassan, Alberto Redondas, Michel Grutter, Alexander Cede, Laura Gomez, and Monica Navarro-Comas
Atmos. Meas. Tech., 14, 2389–2408, https://doi.org/10.5194/amt-14-2389-2021, https://doi.org/10.5194/amt-14-2389-2021, 2021
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Nitrogen oxides in the upper troposphere have a profound influence on the global troposphere, but routine reliable observations there are exceedingly rare. We apply cloud-slicing to TROPOMI total columns of nitrogen dioxide (NO2) at high spatial resolution to derive near-global observations of NO2 in the upper troposphere and show consistency with existing datasets. These data offer tremendous potential to address knowledge gaps in this oft underappreciated portion of the atmosphere.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
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On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Nick Gorkavyi, Zachary Fasnacht, David Haffner, Sergey Marchenko, Joanna Joiner, and Alexander Vasilkov
Atmos. Meas. Tech., 14, 961–974, https://doi.org/10.5194/amt-14-961-2021, https://doi.org/10.5194/amt-14-961-2021, 2021
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Various instrumental or geophysical artifacts, such as saturation, stray light or obstruction of light, negatively impact satellite measured ultraviolet and visible Earthshine radiance spectra. Here, we introduce a straightforward detection method that is based on the correlation, r, between the observed Earthshine radiance and solar irradiance spectra over a 10 nm spectral range; our decorrelation index (DI for brevity) is simply defined as DI of 1–r.
Lok N. Lamsal, Nickolay A. Krotkov, Alexander Vasilkov, Sergey Marchenko, Wenhan Qin, Eun-Su Yang, Zachary Fasnacht, Joanna Joiner, Sungyeon Choi, David Haffner, William H. Swartz, Bradford Fisher, and Eric Bucsela
Atmos. Meas. Tech., 14, 455–479, https://doi.org/10.5194/amt-14-455-2021, https://doi.org/10.5194/amt-14-455-2021, 2021
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The NASA standard nitrogen dioxide (NO2) version 4.0 product for OMI Aura incorporates the most salient improvements. It represents the first global satellite trace gas retrieval with OMI–MODIS synergy accounting for surface reflectance anisotropy in cloud and NO2 retrievals. Improved spectral fitting procedures for NO2 and oxygen dimer (for cloud) retrievals and reliance on high-resolution field-of-view-specific input information for NO2 and cloud retrievals help enhance the NO2 data quality.
Jianglong Zhang, Robert J. D. Spurr, Jeffrey S. Reid, Peng Xian, Peter R. Colarco, James R. Campbell, Edward J. Hyer, and Nancy L. Baker
Geosci. Model Dev., 14, 27–42, https://doi.org/10.5194/gmd-14-27-2021, https://doi.org/10.5194/gmd-14-27-2021, 2021
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A first-of-its-kind scheme has been developed for assimilating Ozone Monitoring Instrument (OMI) aerosol index (AI) measurements into the Naval Aerosol Analysis and Predictive System. Improvements in model simulations demonstrate the utility of OMI AI data assimilation for improving the accuracy of aerosol model analysis over cloudy regions and bright surfaces. This study can be considered one of the first attempts at direct radiance assimilation in the UV spectrum for aerosol analyses.
Can Li, Nickolay A. Krotkov, Peter J. T. Leonard, Simon Carn, Joanna Joiner, Robert J. D. Spurr, and Alexander Vasilkov
Atmos. Meas. Tech., 13, 6175–6191, https://doi.org/10.5194/amt-13-6175-2020, https://doi.org/10.5194/amt-13-6175-2020, 2020
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Sulfur dioxide (SO2) is an important pollutant that causes haze and acid rain. The Ozone Monitoring Instrument (OMI) has been providing global observation of SO2 from space for over 15 years. In this paper, we introduce a new OMI SO2 dataset for global pollution monitoring. The dataset better accounts for the influences of different factors such as location and sun and satellite angles, leading to improved data quality. The new OMI SO2 dataset is publicly available through NASA's data center.
Clark J. Weaver, Pawan K. Bhartia, Dong L. Wu, Gordon J. Labow, and David E. Haffner
Atmos. Meas. Tech., 13, 5715–5723, https://doi.org/10.5194/amt-13-5715-2020, https://doi.org/10.5194/amt-13-5715-2020, 2020
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Currently, we do not know whether clouds will accelerate or moderate climate. We look to the past and ask whether cloudiness has changed over the last 4 decades. Using a suite of nine satellite instruments, we need to ensure that the first satellite, which was launched in 1980 and died in 1991, observed the same measurement as the eight other satellite instruments used in the record. If the instruments were measuring length and observing a 1.00 m long stick, they would all see 0.99 to 1.01 m.
Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. E. Tuinder, Abram F. J. Sanders, Willem W. Verstraeten, Rüdiger Lang, Alessandra Cacciari, Joanna Joiner, Wouter Peters, and K. Folkert Boersma
Atmos. Meas. Tech., 13, 4295–4315, https://doi.org/10.5194/amt-13-4295-2020, https://doi.org/10.5194/amt-13-4295-2020, 2020
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With our improved algorithm we have generated a stable, long-term dataset of fluorescence measurements from the GOME-2A satellite instrument. In this study we determined a correction for the degradation of GOME-2A in orbit and applied this correction along with other improvements to our SIFTER v2 retrieval algorithm. The result is a coherent dataset of daily and monthly averaged fluorescence values for the period 2007–2018 to track worldwide changes in photosynthetic activity by vegetation.
Mengyao Liu, Jintai Lin, Hao Kong, K. Folkert Boersma, Henk Eskes, Yugo Kanaya, Qin He, Xin Tian, Kai Qin, Pinhua Xie, Robert Spurr, Ruijing Ni, Yingying Yan, Hongjian Weng, and Jingxu Wang
Atmos. Meas. Tech., 13, 4247–4259, https://doi.org/10.5194/amt-13-4247-2020, https://doi.org/10.5194/amt-13-4247-2020, 2020
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Nitrogen oxides (NOx = NO + NO2) are important air pollutants in the troposphere and play crucial roles in the formation of ozone and particulate matter. The recently launched TROPOspheric Monitoring Instrument (TROPOMI) provides an opportunity to retrieve tropospheric concentrations of nitrogen dioxide (NO2) at an unprecedented high horizontal resolution. This work presents a new NO2 retrieval product over East Asia and further quantifies key factors affecting the retrieval, including aerosol.
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.
Zhong Chen, Pawan K. Bhartia, Omar Torres, Glen Jaross, Robert Loughman, Matthew DeLand, Peter Colarco, Robert Damadeo, and Ghassan Taha
Atmos. Meas. Tech., 13, 3471–3485, https://doi.org/10.5194/amt-13-3471-2020, https://doi.org/10.5194/amt-13-3471-2020, 2020
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The scope of the paper is the evaluation of stratospheric aerosols derived from the OMPS/LP instrument via comparison with independent datasets from the SAGE III/ISS instrument. Results show very good agreement for extinction profiles between an altitude of 19 and 27 km, to within ±25 %, and show systematic differences (LP-SAGE III/ISS) above 28 km and below 19 km (greater than ±25 %).
Stacey M. Frith, Pawan K. Bhartia, Luke D. Oman, Natalya A. Kramarova, Richard D. McPeters, and Gordon J. Labow
Atmos. Meas. Tech., 13, 2733–2749, https://doi.org/10.5194/amt-13-2733-2020, https://doi.org/10.5194/amt-13-2733-2020, 2020
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We use the NASA GEOS-GMI chemistry climate model to construct a climatology of stratospheric ozone diurnal variations as a function of latitude, pressure and month, which can be used in a variety of data analysis tasks involving ozone observations made at different times of the day. The climatology compares well with previous modeling simulations and available observations, and to the authors' knowledge is the first characterization of the diurnal cycle available for general ozone data analyses.
Sungyeon Choi, Lok N. Lamsal, Melanie Follette-Cook, Joanna Joiner, Nickolay A. Krotkov, William H. Swartz, Kenneth E. Pickering, Christopher P. Loughner, Wyat Appel, Gabriele Pfister, Pablo E. Saide, Ronald C. Cohen, Andrew J. Weinheimer, and Jay R. Herman
Atmos. Meas. Tech., 13, 2523–2546, https://doi.org/10.5194/amt-13-2523-2020, https://doi.org/10.5194/amt-13-2523-2020, 2020
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Nicolas Theys, Diego G. Loyola, Pascal Hedelt, Nickolay A. Krotkov, and Can Li
Atmos. Chem. Phys., 20, 5591–5607, https://doi.org/10.5194/acp-20-5591-2020, https://doi.org/10.5194/acp-20-5591-2020, 2020
Ernest Nyaku, Robert Loughman, Pawan K. Bhartia, Terry Deshler, Zhong Chen, and Peter R. Colarco
Atmos. Meas. Tech., 13, 1071–1087, https://doi.org/10.5194/amt-13-1071-2020, https://doi.org/10.5194/amt-13-1071-2020, 2020
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This paper shows the importance of the nature of the aerosol phase function used in the retrieval of the stratospheric aerosol extinction from limb scattering measurements. The aerosol phase function is derived from the parameters using either a unimodal lognormal or gamma aerosol size distribution. These two distributions were fitted to the same aerosol concentration measurements at two altitudes, and depending on the nature of the measurements, each distribution shows its strengths.
Fei Liu, Bryan N. Duncan, Nickolay A. Krotkov, Lok N. Lamsal, Steffen Beirle, Debora Griffin, Chris A. McLinden, Daniel L. Goldberg, and Zifeng Lu
Atmos. Chem. Phys., 20, 99–116, https://doi.org/10.5194/acp-20-99-2020, https://doi.org/10.5194/acp-20-99-2020, 2020
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We present a novel method to infer CO2 emissions from individual power plants, based on satellite observations of co-emitted NO2. We find that the CO2 emissions estimated by our satellite-based method during 2005–2017 are in reasonable agreement with the CEMS measurements for US power plants. The broader implication of our methodology is that it has the potential to provide an additional constraint on CO2 emissions from power plants in regions of the world without reliable emissions accounting.
Zachary Fasnacht, Alexander Vasilkov, David Haffner, Wenhan Qin, Joanna Joiner, Nickolay Krotkov, Andrew M. Sayer, and Robert Spurr
Atmos. Meas. Tech., 12, 6749–6769, https://doi.org/10.5194/amt-12-6749-2019, https://doi.org/10.5194/amt-12-6749-2019, 2019
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The anisotropy of Earth's surface reflection plays an important role in satellite-based retrievals of cloud, aerosol, and trace gases. Most current ultraviolet and visible satellite retrievals utilize climatological surface reflectivity databases that do not account for surface anisotropy. The GLER concept was introduced to account for such features. Here we evaluate GLER for water surfaces by comparing with OMI measurements and show that it captures these surface anisotropy features.
Pascal Hedelt, Dmitry S. Efremenko, Diego G. Loyola, Robert Spurr, and Lieven Clarisse
Atmos. Meas. Tech., 12, 5503–5517, https://doi.org/10.5194/amt-12-5503-2019, https://doi.org/10.5194/amt-12-5503-2019, 2019
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Sulfur dioxide (SO2) emitted during volcanic eruptions poses not only a major threat to local populations, air quality, and aviation but also has an impact on the climate. The satellite-based detection of the SO2 plume is easy; however, it requires exact knowledge of the SO2 layer height. This paper presents a new method for the extremely fast and accurate determination of the layer height, which is essential in volcanic plume forecasts and the exact determination of the SO2 density.
Bradford L. Fisher, Nickolay A. Krotkov, Pawan K. Bhartia, Can Li, Simon A. Carn, Eric Hughes, and Peter J. T. Leonard
Atmos. Meas. Tech., 12, 5137–5153, https://doi.org/10.5194/amt-12-5137-2019, https://doi.org/10.5194/amt-12-5137-2019, 2019
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This article describes a new discrete wavelength algorithm, MS_SO2, which has been used operationally to retrieve global daily volcanic SO2 vertical column densities and the UV volcanic ash index from the Total Ozone Mapping Spectrometer (TOMS) data collected by NASA’s Nimbus-7 satellite from 1978 to 1991. We examine the sensitivity of the algorithm to the detection of SO2, evaluate potential sources of error and compare results from MS_SO2 with the Principal Component Analysis (PCA) algorithm.
Wenhan Qin, Zachary Fasnacht, David Haffner, Alexander Vasilkov, Joanna Joiner, Nickolay Krotkov, Bradford Fisher, and Robert Spurr
Atmos. Meas. Tech., 12, 3997–4017, https://doi.org/10.5194/amt-12-3997-2019, https://doi.org/10.5194/amt-12-3997-2019, 2019
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Satellite observations depend on Sun and view angles due to anisotropy of the Earth's atmosphere and surface reflection. But most of the ultraviolet and visible cloud, aerosol, and trace-gas algorithms utilize surface reflectivity databases that do not account for surface anisotropy. We create a surface database using the GLER concept which adequately accounts for surface anisotropy, validate it with independent satellite data, and provide a simple implementation to the current algorithms.
Rachel F. Silvern, Daniel J. Jacob, Loretta J. Mickley, Melissa P. Sulprizio, Katherine R. Travis, Eloise A. Marais, Ronald C. Cohen, Joshua L. Laughner, Sungyeon Choi, Joanna Joiner, and Lok N. Lamsal
Atmos. Chem. Phys., 19, 8863–8878, https://doi.org/10.5194/acp-19-8863-2019, https://doi.org/10.5194/acp-19-8863-2019, 2019
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The US EPA reports a steady decrease in nitrogen oxide (NOx) emissions from fuel combustion over the 2005–2017 period, while satellite observations show a leveling off after 2009, suggesting emission reductions and related air quality gains have halted. We show the sustained decrease in NOx emissions is in fact consistent with observed trends in surface NO2 and ozone concentrations and that the flattening of the satellite trend reflects a growing influence from the non-anthropogenic background.
Yuekui Yang, Kerry Meyer, Galina Wind, Yaping Zhou, Alexander Marshak, Steven Platnick, Qilong Min, Anthony B. Davis, Joanna Joiner, Alexander Vasilkov, David Duda, and Wenying Su
Atmos. Meas. Tech., 12, 2019–2031, https://doi.org/10.5194/amt-12-2019-2019, https://doi.org/10.5194/amt-12-2019-2019, 2019
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The physical basis of the EPIC cloud product algorithms and an initial evaluation of their performance are presented. EPIC cloud products include cloud mask, effective height, and optical depth. Comparison with co-located retrievals from geosynchronous earth orbit (GEO) and low earth orbit (LEO) satellites shows that the algorithms are performing well and are consistent with theoretical expectations. These products are publicly available at the NASA Langley Atmospheric Sciences Data Center.
Jerry R. Ziemke, Luke D. Oman, Sarah A. Strode, Anne R. Douglass, Mark A. Olsen, Richard D. McPeters, Pawan K. Bhartia, Lucien Froidevaux, Gordon J. Labow, Jacquie C. Witte, Anne M. Thompson, David P. Haffner, Natalya A. Kramarova, Stacey M. Frith, Liang-Kang Huang, Glen R. Jaross, Colin J. Seftor, Mathew T. Deland, and Steven L. Taylor
Atmos. Chem. Phys., 19, 3257–3269, https://doi.org/10.5194/acp-19-3257-2019, https://doi.org/10.5194/acp-19-3257-2019, 2019
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Both a 38-year merged satellite record of tropospheric ozone from TOMS/OMI/MLS/OMPS and a MERRA-2 GMI model simulation show large increases of 6–7 Dobson units from the Near East to India–East Asia and eastward over the Pacific. These increases in tropospheric ozone are attributed to increases in pollution over the region over the last several decades. Secondary 38-year increases of 4–5 Dobson units with both GMI model and satellite measurements occur over central African–tropical Atlantic.
Cristen Adams, Chris A. McLinden, Mark W. Shephard, Nolan Dickson, Enrico Dammers, Jack Chen, Paul Makar, Karen E. Cady-Pereira, Naomi Tam, Shailesh K. Kharol, Lok N. Lamsal, and Nickolay A. Krotkov
Atmos. Chem. Phys., 19, 2577–2599, https://doi.org/10.5194/acp-19-2577-2019, https://doi.org/10.5194/acp-19-2577-2019, 2019
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We estimated how much carbon monoxide, ammonia, and nitrogen oxides were emitted in the smoke from the Fort McMurray Horse River wildfire using satellite data and air quality models. The fire emitted amounts of carbon monoxide that were similar to anthropogenic (human-caused) emissions for all of Alberta over a full year. We also estimated large amounts of ammonia and nitrogen oxides emitted from the fire. These results can be used to evaluate the performance of air quality forecasting models.
Huanxin Zhang, Jun Wang, Lorena Castro García, Jing Zeng, Connor Dennhardt, Yang Liu, and Nickolay A. Krotkov
Atmos. Chem. Phys., 19, 2165–2181, https://doi.org/10.5194/acp-19-2165-2019, https://doi.org/10.5194/acp-19-2165-2019, 2019
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OMU-based surface erythemal UV irradiance is compared with ground observations in the United States from 2005 to 2017. We reveal that the assumption of constant atmospheric conditions between OMI overpass time and local solar noon time may not fully represent the real atmosphere and the peaks of surface UV are not always at local solar noon because of cloud effects. Future geostationary satellites (e.g., TEMPO) would reduce sampling bias and improve trend analysis of surface UV estimate.
Zhong Chen, Pawan K. Bhartia, Robert Loughman, Peter Colarco, and Matthew DeLand
Atmos. Meas. Tech., 11, 6495–6509, https://doi.org/10.5194/amt-11-6495-2018, https://doi.org/10.5194/amt-11-6495-2018, 2018
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We describe the derivation of an improved aerosol size distribution (ASD) for the OMPS/LP retrieval algorithm. The new ASD uses a gamma function distribution that is derived from CARMA-calculated results. The new ASD also explains the spectral dependence of LP-measured radiances well. Initial comparisons with collocated extinction profiles retrieved at 676 nm from the SAGE III/ISS instrument show a significant improvement in agreement for the LP retrievals.
Eloise A. Marais, Daniel J. Jacob, Sungyeon Choi, Joanna Joiner, Maria Belmonte-Rivas, Ronald C. Cohen, Steffen Beirle, Lee T. Murray, Luke D. Schiferl, Viral Shah, and Lyatt Jaeglé
Atmos. Chem. Phys., 18, 17017–17027, https://doi.org/10.5194/acp-18-17017-2018, https://doi.org/10.5194/acp-18-17017-2018, 2018
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We intercompare two new products of global upper tropospheric nitrogen dioxide (NO2) retrieved from the Ozone Monitoring Instrument (OMI). We evaluate these products with aircraft observations from NASA DC8 aircraft campaigns and interpret the useful information these products can provide about nitrogen oxides (NOx) in the global upper troposphere using the GEOS-Chem chemical transport model.
Fei Liu, Sungyeon Choi, Can Li, Vitali E. Fioletov, Chris A. McLinden, Joanna Joiner, Nickolay A. Krotkov, Huisheng Bian, Greet Janssens-Maenhout, Anton S. Darmenov, and Arlindo M. da Silva
Atmos. Chem. Phys., 18, 16571–16586, https://doi.org/10.5194/acp-18-16571-2018, https://doi.org/10.5194/acp-18-16571-2018, 2018
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Sulfur dioxide measurements from space have been used to detect emissions from large sources. We developed a new emission inventory by combining the satellite-based emission estimates and the conventional bottom-up inventory for smaller sources. The new inventory improves the model agreement with in situ observations and offers the possibility of rapid updates to emissions.
Yao Zhang, Joanna Joiner, Seyed Hamed Alemohammad, Sha Zhou, and Pierre Gentine
Biogeosciences, 15, 5779–5800, https://doi.org/10.5194/bg-15-5779-2018, https://doi.org/10.5194/bg-15-5779-2018, 2018
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Using satellite reflectance measurements and a machine learning algorithm, we generated a new solar-induced chlorophyll fluorescence (SIF) dataset that is closely linked to plant photosynthesis. This new dataset has higher spatial and temporal resolutions, and lower uncertainty compared to the existing satellite retrievals. We also demonstrated its application in monitoring drought and improving the understanding of the SIF–photosynthesis relationship.
Natalya A. Kramarova, Pawan K. Bhartia, Glen Jaross, Leslie Moy, Philippe Xu, Zhong Chen, Matthew DeLand, Lucien Froidevaux, Nathaniel Livesey, Douglas Degenstein, Adam Bourassa, Kaley A. Walker, and Patrick Sheese
Atmos. Meas. Tech., 11, 2837–2861, https://doi.org/10.5194/amt-11-2837-2018, https://doi.org/10.5194/amt-11-2837-2018, 2018
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The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) is a newly designed research sensor aiming to continue high vertical resolution ozone records from space-borne sensors. In summer 2017 all LP measurements were processed with the new version 2.5 algorithm. In this paper we provide a description of the key changes implemented in the new algorithm and evaluate the quality of ozone retrievals by comparing with independent satellite profile measurements (MLS, ACE-FTS and OSIRIS).
Omar Torres, Pawan K. Bhartia, Hiren Jethva, and Changwoo Ahn
Atmos. Meas. Tech., 11, 2701–2715, https://doi.org/10.5194/amt-11-2701-2018, https://doi.org/10.5194/amt-11-2701-2018, 2018
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Since about three years after the launch the Ozone Monitoring Instrument (OMI) on the EOS-Aura satellite, the sensor’s viewing capability has been affected by what is believed to be an internal obstruction that has reduced OMI’s spatial coverage. It currently affects about half of the instrument’s 60 viewing positions. In this work we carry out an analysis to assess the effect of the reduced spatial coverage on the monthly average values of retrieved parameters.
Robert Loughman, Pawan K. Bhartia, Zhong Chen, Philippe Xu, Ernest Nyaku, and Ghassan Taha
Atmos. Meas. Tech., 11, 2633–2651, https://doi.org/10.5194/amt-11-2633-2018, https://doi.org/10.5194/amt-11-2633-2018, 2018
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The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 algorithm retrieves aerosol extinction profiles at 675 nm by iteration, based on comparisons between the measured and calculated radiance profiles (assuming an aerosol size distribution). The most significant error source is uncertainty about the aerosol phase function. Horizontal variations in aerosol extinction may also limit the quality of the retrieved aerosol extinction profiles.
J. Li, S. Chen, W. Qin, M. Murefu, Y. Wang, Y. Yu, and Z. Zhen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 819–823, https://doi.org/10.5194/isprs-archives-XLII-3-819-2018, https://doi.org/10.5194/isprs-archives-XLII-3-819-2018, 2018
Pieternel F. Levelt, Joanna Joiner, Johanna Tamminen, J. Pepijn Veefkind, Pawan K. Bhartia, Deborah C. Stein Zweers, Bryan N. Duncan, David G. Streets, Henk Eskes, Ronald van der A, Chris McLinden, Vitali Fioletov, Simon Carn, Jos de Laat, Matthew DeLand, Sergey Marchenko, Richard McPeters, Jerald Ziemke, Dejian Fu, Xiong Liu, Kenneth Pickering, Arnoud Apituley, Gonzalo González Abad, Antti Arola, Folkert Boersma, Christopher Chan Miller, Kelly Chance, Martin de Graaf, Janne Hakkarainen, Seppo Hassinen, Iolanda Ialongo, Quintus Kleipool, Nickolay Krotkov, Can Li, Lok Lamsal, Paul Newman, Caroline Nowlan, Raid Suleiman, Lieuwe Gijsbert Tilstra, Omar Torres, Huiqun Wang, and Krzysztof Wargan
Atmos. Chem. Phys., 18, 5699–5745, https://doi.org/10.5194/acp-18-5699-2018, https://doi.org/10.5194/acp-18-5699-2018, 2018
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The aim of this paper is to highlight the many successes of the Ozone Monitoring Instrument (OMI) spanning more than 13 years. Data from OMI have been used in a wide range of applications. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. OMI data continue to be used for new research and applications.
Jungbin Mok, Nickolay A. Krotkov, Omar Torres, Hiren Jethva, Zhanqing Li, Jhoon Kim, Ja-Ho Koo, Sujung Go, Hitoshi Irie, Gordon Labow, Thomas F. Eck, Brent N. Holben, Jay Herman, Robert P. Loughman, Elena Spinei, Seoung Soo Lee, Pradeep Khatri, and Monica Campanelli
Atmos. Meas. Tech., 11, 2295–2311, https://doi.org/10.5194/amt-11-2295-2018, https://doi.org/10.5194/amt-11-2295-2018, 2018
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Measuring aerosol absorption from the shortest ultraviolet (UV) to the near-infrared (NIR) wavelengths is important for studies of climate, tropospheric photochemistry, human health, and agricultural productivity. We estimate the accuracy and demonstrate consistency of aerosol absorption retrievals from different instruments, after accounting for spectrally varying surface albedo and gaseous absorption.
Anders V. Lindfors, Jukka Kujanpää, Niilo Kalakoski, Anu Heikkilä, Kaisa Lakkala, Tero Mielonen, Maarten Sneep, Nickolay A. Krotkov, Antti Arola, and Johanna Tamminen
Atmos. Meas. Tech., 11, 997–1008, https://doi.org/10.5194/amt-11-997-2018, https://doi.org/10.5194/amt-11-997-2018, 2018
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This paper describes the algorithm that will be used for estimating surface UV radiation from TROPOMI (TROPOspheric Monitoring Instrument) measurements. TROPOMI is the only payload of the Sentinel-5 Precursor (S5P), which is a polar-orbiting satellite mission of the European Space Agency (ESA). The presented algorithm has been tested using input based on previous satellite measurements. These preliminary results indicate that the algorithm is functioning according to expectations.
Zhong Chen, Pawan K. Bhartia, Robert Loughman, and Peter Colarco
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-4, https://doi.org/10.5194/amt-2018-4, 2018
Revised manuscript has not been submitted
Diego G. Loyola, Sebastián Gimeno García, Ronny Lutz, Athina Argyrouli, Fabian Romahn, Robert J. D. Spurr, Mattia Pedergnana, Adrian Doicu, Víctor Molina García, and Olena Schüssler
Atmos. Meas. Tech., 11, 409–427, https://doi.org/10.5194/amt-11-409-2018, https://doi.org/10.5194/amt-11-409-2018, 2018
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In this paper we present the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) mission: OCRA (Optical Cloud Recognition Algorithm) retrieves the cloud fraction using measurements in the UV–VIS spectral regions, and ROCINN (Retrieval of Cloud Information using Neural Networks) retrieves the cloud top height and optical thickness using measurements in and around the oxygen A-band in the NIR.
Juseon Bak, Xiong Liu, Jae-Hwan Kim, David P. Haffner, Kelly Chance, Kai Yang, and Kang Sun
Atmos. Meas. Tech., 10, 4373–4388, https://doi.org/10.5194/amt-10-4373-2017, https://doi.org/10.5194/amt-10-4373-2017, 2017
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This paper verifies and corrects the Ozone Mapping and Profiler Suite (OMPS) nadir mapper (NM) level 1B v2.0 measurements to retrieve reliable ozone profile and tropospheric ozone using an optimal estimation inversion with the fitting window of 302.5–340 nm. We apply "soft calibration" and "common mode correction" to OMPS radiances to eliminate systematic errors in the fitting residuals and derive random-noise measurement errors accounting for both OMPS radiances and forward model calculation.
Jerald R. Ziemke, Sarah A. Strode, Anne R. Douglass, Joanna Joiner, Alexander Vasilkov, Luke D. Oman, Junhua Liu, Susan E. Strahan, Pawan K. Bhartia, and David P. Haffner
Atmos. Meas. Tech., 10, 4067–4078, https://doi.org/10.5194/amt-10-4067-2017, https://doi.org/10.5194/amt-10-4067-2017, 2017
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We combine satellite measurements of ozone and cloud properties from the Aura OMI and MLS instruments for 2004–2016 to measure ozone in the mid–upper levels of deep convective clouds. Our results ascribe upward injection of low boundary layer ozone (varying from low to high amounts) as a major driver of the measured concentrations of ozone in thick clouds. Our OMI/MLS generated ozone product is made available to the public for use in science applications.
Vitali Fioletov, Chris A. McLinden, Shailesh K. Kharol, Nickolay A. Krotkov, Can Li, Joanna Joiner, Michael D. Moran, Robert Vet, Antoon J. H. Visschedijk, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys., 17, 12597–12616, https://doi.org/10.5194/acp-17-12597-2017, https://doi.org/10.5194/acp-17-12597-2017, 2017
Viktoria F. Sofieva, Erkki Kyrölä, Marko Laine, Johanna Tamminen, Doug Degenstein, Adam Bourassa, Chris Roth, Daniel Zawada, Mark Weber, Alexei Rozanov, Nabiz Rahpoe, Gabriele Stiller, Alexandra Laeng, Thomas von Clarmann, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Claus Zehner, Robert Damadeo, Joseph Zawodny, Natalya Kramarova, and Pawan K. Bhartia
Atmos. Chem. Phys., 17, 12533–12552, https://doi.org/10.5194/acp-17-12533-2017, https://doi.org/10.5194/acp-17-12533-2017, 2017
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We present a merged dataset of ozone profiles from several satellite instruments: SAGE II, GOMOS, SCIAMACHY, MIPAS, OSIRIS, ACE-FTS and OMPS. For merging, we used the latest versions of the original ozone datasets.
The merged SAGE–CCI–OMPS dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997.
Wolfgang Steinbrecht, Lucien Froidevaux, Ryan Fuller, Ray Wang, John Anderson, Chris Roth, Adam Bourassa, Doug Degenstein, Robert Damadeo, Joe Zawodny, Stacey Frith, Richard McPeters, Pawan Bhartia, Jeannette Wild, Craig Long, Sean Davis, Karen Rosenlof, Viktoria Sofieva, Kaley Walker, Nabiz Rahpoe, Alexei Rozanov, Mark Weber, Alexandra Laeng, Thomas von Clarmann, Gabriele Stiller, Natalya Kramarova, Sophie Godin-Beekmann, Thierry Leblanc, Richard Querel, Daan Swart, Ian Boyd, Klemens Hocke, Niklaus Kämpfer, Eliane Maillard Barras, Lorena Moreira, Gerald Nedoluha, Corinne Vigouroux, Thomas Blumenstock, Matthias Schneider, Omaira García, Nicholas Jones, Emmanuel Mahieu, Dan Smale, Michael Kotkamp, John Robinson, Irina Petropavlovskikh, Neil Harris, Birgit Hassler, Daan Hubert, and Fiona Tummon
Atmos. Chem. Phys., 17, 10675–10690, https://doi.org/10.5194/acp-17-10675-2017, https://doi.org/10.5194/acp-17-10675-2017, 2017
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Thanks to the 1987 Montreal Protocol and its amendments, ozone-depleting chlorine (and bromine) in the stratosphere has declined slowly since the late 1990s. Improved and extended long-term ozone profile observations from satellites and ground-based stations confirm that ozone is responding as expected and has increased by about 2 % per decade since 2000 in the upper stratosphere, around 40 km altitude. At lower altitudes, however, ozone has not changed significantly since 2000.
Nickolay A. Krotkov, Lok N. Lamsal, Edward A. Celarier, William H. Swartz, Sergey V. Marchenko, Eric J. Bucsela, Ka Lok Chan, Mark Wenig, and Marina Zara
Atmos. Meas. Tech., 10, 3133–3149, https://doi.org/10.5194/amt-10-3133-2017, https://doi.org/10.5194/amt-10-3133-2017, 2017
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We describe the new version 3 OMI NO2 standard product (SPv3) based on significant improvements in both the estimation of the SCDs and the AMFs. The new SCDs and stratospheric VCDs are systematically lower (by ~ 10–40 %) than previous estimates. Tropospheric VCDs are also reduced over polluted areas. Initial evaluation over unpolluted areas has shown that the new SPv3 products agree better with independent satellite- and ground-based FTIR measurements.
Georgina M. Miles, Richard Siddans, Roy G. Grainger, Alfred J. Prata, Bradford Fisher, and Nickolay Krotkov
Atmos. Meas. Tech., 10, 2687–2702, https://doi.org/10.5194/amt-10-2687-2017, https://doi.org/10.5194/amt-10-2687-2017, 2017
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Volcanic eruptions are important in the way they perturb the climate and help us understand atmospheric processes. We show a new method to measure the SO2 released by explosive volcanic eruptions using the HIRS/2 satellite instrument, which measured atmospheric temperature and H2O. We apply the technique to the 1991 eruption of Cerro Hudson and show it is possible to detect SO2 with a good degree of accuracy. This method and instrument can potentially generate a climate-significant record.
Guanyu Huang, Xiong Liu, Kelly Chance, Kai Yang, Pawan K. Bhartia, Zhaonan Cai, Marc Allaart, Gérard Ancellet, Bertrand Calpini, Gerrie J. R. Coetzee, Emilio Cuevas-Agulló, Manuel Cupeiro, Hugo De Backer, Manvendra K. Dubey, Henry E. Fuelberg, Masatomo Fujiwara, Sophie Godin-Beekmann, Tristan J. Hall, Bryan Johnson, Everette Joseph, Rigel Kivi, Bogumil Kois, Ninong Komala, Gert König-Langlo, Giovanni Laneve, Thierry Leblanc, Marion Marchand, Kenneth R. Minschwaner, Gary Morris, Michael J. Newchurch, Shin-Ya Ogino, Nozomu Ohkawara, Ankie J. M. Piters, Françoise Posny, Richard Querel, Rinus Scheele, Frank J. Schmidlin, Russell C. Schnell, Otto Schrems, Henry Selkirk, Masato Shiotani, Pavla Skrivánková, René Stübi, Ghassan Taha, David W. Tarasick, Anne M. Thompson, Valérie Thouret, Matthew B. Tully, Roeland Van Malderen, Holger Vömel, Peter von der Gathen, Jacquelyn C. Witte, and Margarita Yela
Atmos. Meas. Tech., 10, 2455–2475, https://doi.org/10.5194/amt-10-2455-2017, https://doi.org/10.5194/amt-10-2455-2017, 2017
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It is essential to understand the data quality of +10-year OMI ozone product and impacts of the “row anomaly” (RA). We validate the OMI Ozone Profile (PROFOZ) product from Oct 2004 to Dec 2014 against ozonesonde observations globally. Generally, OMI has good agreement with ozonesondes. The spatiotemporal variation of retrieval performance suggests the need to improve OMI’s radiometric calibration especially during the post-RA period to maintain the long-term stability.
V. M. Erik Schenkeveld, Glen Jaross, Sergey Marchenko, David Haffner, Quintus L. Kleipool, Nico C. Rozemeijer, J. Pepijn Veefkind, and Pieternel F. Levelt
Atmos. Meas. Tech., 10, 1957–1986, https://doi.org/10.5194/amt-10-1957-2017, https://doi.org/10.5194/amt-10-1957-2017, 2017
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The Ozone Monitoring Instrument (OMI) has been flying on NASA’s EOS Aura satellite since July 15, 2004. It has measured the concentration of trace gasses in the atmosphere, like ozone, NO2 and SO2. This article describes the trend in performance and calibration parameters of OMI during 12 years of flight. The degradation of the CCD detectors, solar diffusers, spectral calibration and row anomaly are shown. The instrument shows overall degradation that is better than expected.
Yan Zhang, Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, and Chris McLinden
Atmos. Meas. Tech., 10, 1495–1509, https://doi.org/10.5194/amt-10-1495-2017, https://doi.org/10.5194/amt-10-1495-2017, 2017
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In this study, we demonstrate a very good consistency of the SO2 retrievals from OMI and OMPS using our state-of-the-art principal component analysis technique. Four full years of OMI and OMPS SO2 retrievals, during 2012–2015 have been analyzed over some of the world’s most polluted regions: eastern China, Mexico, and South Africa. The consistency of retrievals between OMI and OMPS make it possible to continue the long-term global SO2 pollution monitoring.
Michael P. Barkley, Gonzalo González Abad, Thomas P. Kurosu, Robert Spurr, Sara Torbatian, and Christophe Lerot
Atmos. Chem. Phys., 17, 4687–4709, https://doi.org/10.5194/acp-17-4687-2017, https://doi.org/10.5194/acp-17-4687-2017, 2017
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Using Ozone Monitoring Instrument (OMI) trace gas vertical column observations of NO2, HCHO, SO2, and CHOCHO, we have conducted a robust and detailed time series analysis to assess changes in local air quality for over 1000 locations (focussing on urban, oil refinery, oil port, and power plant targets) over the Middle East for 2005–2014. We find that for many locations in the Middle East, OMI observes a degradation in air quality during this time period.
Alba Lorente, K. Folkert Boersma, Huan Yu, Steffen Dörner, Andreas Hilboll, Andreas Richter, Mengyao Liu, Lok N. Lamsal, Michael Barkley, Isabelle De Smedt, Michel Van Roozendael, Yang Wang, Thomas Wagner, Steffen Beirle, Jin-Tai Lin, Nickolay Krotkov, Piet Stammes, Ping Wang, Henk J. Eskes, and Maarten Krol
Atmos. Meas. Tech., 10, 759–782, https://doi.org/10.5194/amt-10-759-2017, https://doi.org/10.5194/amt-10-759-2017, 2017
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Choices and assumptions made to represent the state of the atmosphere introduce an uncertainty of 42 % in the air mass factor calculation in trace gas satellite retrievals in polluted regions. The AMF strongly depends on the choice of a priori trace gas profile, surface albedo data set and the correction method to account for clouds and aerosols. We call for well-designed validation exercises focusing on situations when AMF structural uncertainty has the highest impact on satellite retrievals.
Sergey M. Khaykin, Sophie Godin-Beekmann, Philippe Keckhut, Alain Hauchecorne, Julien Jumelet, Jean-Paul Vernier, Adam Bourassa, Doug A. Degenstein, Landon A. Rieger, Christine Bingen, Filip Vanhellemont, Charles Robert, Matthew DeLand, and Pawan K. Bhartia
Atmos. Chem. Phys., 17, 1829–1845, https://doi.org/10.5194/acp-17-1829-2017, https://doi.org/10.5194/acp-17-1829-2017, 2017
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The article is devoted to the long-term evolution and variability of stratospheric aerosol, which plays an important role in climate change and the ozone layer. We use 22-year long continuous observations using laser radar soundings in southern France and satellite-based observations to distinguish between natural aerosol variability (caused by volcanic eruptions) and human-induced change in aerosol concentration. An influence of growing pollution above Asia on stratospheric aerosol is found.
Can Li, Nickolay A. Krotkov, Simon Carn, Yan Zhang, Robert J. D. Spurr, and Joanna Joiner
Atmos. Meas. Tech., 10, 445–458, https://doi.org/10.5194/amt-10-445-2017, https://doi.org/10.5194/amt-10-445-2017, 2017
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In this paper, we describe the new-generation OMI volcanic SO2 algorithm based on our principal component analysis (PCA) retrieval technique. We demonstrate significant improvement in the our new OMI volcanic SO2 data, with the retrieval noise reduced by a factor of 2 as compared with the previous dataset. The algorithm also improves the accuracy for large volcanic eruptions. It is also capable of producing consistent retrievals between different instruments.
Alexander Vasilkov, Wenhan Qin, Nickolay Krotkov, Lok Lamsal, Robert Spurr, David Haffner, Joanna Joiner, Eun-Su Yang, and Sergey Marchenko
Atmos. Meas. Tech., 10, 333–349, https://doi.org/10.5194/amt-10-333-2017, https://doi.org/10.5194/amt-10-333-2017, 2017
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We show how the surface reflection can vary day to day in the blue part of the sun's spectrum where we measure the pollutant gas nitrogen dioxide using a satellite instrument called OMI. We use information from an imaging spectrometer on another satellite, MODIS, to estimate the angular surface effects. We can then use models of how the sunlight travels through the atmosphere to predict how the angle-dependent surface reflection will impact the values of pollutant levels inferred by OMI.
Leslie Moy, Pawan K. Bhartia, Glen Jaross, Robert Loughman, Natalya Kramarova, Zhong Chen, Ghassan Taha, Grace Chen, and Philippe Xu
Atmos. Meas. Tech., 10, 167–178, https://doi.org/10.5194/amt-10-167-2017, https://doi.org/10.5194/amt-10-167-2017, 2017
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UV backscatter limb sounding sensors have difficulty determining altitude registration to the accuracy needed for long-term ozone monitoring. We describe two methods to achieve this by comparing radiance measurements to models. Wavelengths and altitudes chosen minimize errors from aerosol interference, calibration errors, and ozone assumptions. The techniques are inexpensive, more comprehensive than external sources of attitude information, and track drifts in our altitude to better than 100 m.
Iolanda Ialongo, Jay Herman, Nick Krotkov, Lok Lamsal, K. Folkert Boersma, Jari Hovila, and Johanna Tamminen
Atmos. Meas. Tech., 9, 5203–5212, https://doi.org/10.5194/amt-9-5203-2016, https://doi.org/10.5194/amt-9-5203-2016, 2016
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We present the comparison between satellite- and ground-based atmospheric NO2 observations in Helsinki (Finland). The results show that, despite some limitations due to cloud contamination and low solar angles, satellite data are able to describe urban air quality features such as the weekly and seasonal cycles. The results support air quality satellite data exploitation at high latitudes and prepare for similar applications for future missions.
Hiren Jethva, Omar Torres, Lorraine Remer, Jens Redemann, John Livingston, Stephen Dunagan, Yohei Shinozuka, Meloe Kacenelenbogen, Michal Segal Rosenheimer, and Rob Spurr
Atmos. Meas. Tech., 9, 5053–5062, https://doi.org/10.5194/amt-9-5053-2016, https://doi.org/10.5194/amt-9-5053-2016, 2016
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Validation of the above-cloud aerosol optical depth retrieved using the "color ratio" method applied to MODIS cloudy-sky
measurements against airborne direct measurements made by NASA’s AATS and 4STAR sun photometers during SAFARI-2000,
ACE-ASIA 2001, and SEAC4RS 2013 reveals a good level of agreement (difference < 0.1), in which most matchups are found
be constrained within the estimated uncertainties associated with the MODIS retrievals (-10 % to +50 %).
Vitali E. Fioletov, Chris A. McLinden, Nickolay Krotkov, Can Li, Joanna Joiner, Nicolas Theys, Simon Carn, and Mike D. Moran
Atmos. Chem. Phys., 16, 11497–11519, https://doi.org/10.5194/acp-16-11497-2016, https://doi.org/10.5194/acp-16-11497-2016, 2016
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We introduce the first space-based catalogue of SO2 emission sources seen by OMI. The inventory contains about 500 sources. They account for about a half of all SO2 emissions; the remaining half is likely related to sources emitting less than 30 kt yr−1 and not detected by OMI. The sources are grouped by type (volcanoes, power plants, oil- and gas-related sources, and smelters) and country. The catalogue presented herein can be used for verification of available SO2 emission inventories.
Cristen Adams, Elise N. Normand, Chris A. McLinden, Adam E. Bourassa, Nicholas D. Lloyd, Douglas A. Degenstein, Nickolay A. Krotkov, Maria Belmonte Rivas, K. Folkert Boersma, and Henk Eskes
Atmos. Meas. Tech., 9, 4103–4122, https://doi.org/10.5194/amt-9-4103-2016, https://doi.org/10.5194/amt-9-4103-2016, 2016
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A new "OMI-minus-OSIRIS" (OmO) prototype dataset for tropospheric NO2 was created by combining information from the OMI satellite instrument, which is sensitive to NO2 in both the troposphere and stratosphere, with information from the OSIRIS satellite instrument, which measures NO2 in the stratosphere. This paper demonstrates that this approach is feasible and could be applied to future geostationary missions.
Joanna Joiner, Yasuko Yoshida, Luis Guanter, and Elizabeth M. Middleton
Atmos. Meas. Tech., 9, 3939–3967, https://doi.org/10.5194/amt-9-3939-2016, https://doi.org/10.5194/amt-9-3939-2016, 2016
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We examine new ways to use existing satellite instruments to retrieve red solar-induced fluorescence (SIF) over land and ocean. Our 8-year record of red SIF observations over land with the Global Ozone Monitoring Instrument 2 (GOME-2) shows for the first time reductions in response to drought. High-quality ocean fluorescence can also be derived with GOME-2 and similar instruments by utilizing their rich measurements of different colors.
Gonzalo González Abad, Alexander Vasilkov, Colin Seftor, Xiong Liu, and Kelly Chance
Atmos. Meas. Tech., 9, 2797–2812, https://doi.org/10.5194/amt-9-2797-2016, https://doi.org/10.5194/amt-9-2797-2016, 2016
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The multi-spectral possibilities of the OMPS Nadir Mapper instrument are exploited here to perform formaldehyde retrievals. Orbiting the Earth at 824 km, OMPS observes the atmosphere in a time frame similar to instruments belonging to NASA's A-Train constellation, 01:30. We show that OMPS is well suited to measure formaldehyde despite its spectral resolution of 1nm. The comparison of OMPS retrievals with OMI products show good temporal correlation.
Pawan Gupta, Joanna Joiner, Alexander Vasilkov, and Pawan K. Bhartia
Atmos. Meas. Tech., 9, 2813–2826, https://doi.org/10.5194/amt-9-2813-2016, https://doi.org/10.5194/amt-9-2813-2016, 2016
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The A-train constellation of satellites provides a unique opportunity to analyze near-simultaneous data from several of these sensors. In this paper, retrievals of cloud/aerosols parameters and total column ozone (TCO) from the Aura Ozone Monitoring Instrument (OMI) have been used to develop a variety of neural networks that estimate TOA SWF globally over ocean and land using only OMI data as inputs. Application of our method to other ultraviolet sensors may provide unique estimates of TOA SWF.
Jinfeng Chang, Philippe Ciais, Mario Herrero, Petr Havlik, Matteo Campioli, Xianzhou Zhang, Yongfei Bai, Nicolas Viovy, Joanna Joiner, Xuhui Wang, Shushi Peng, Chao Yue, Shilong Piao, Tao Wang, Didier A. Hauglustaine, Jean-Francois Soussana, Anna Peregon, Natalya Kosykh, and Nina Mironycheva-Tokareva
Biogeosciences, 13, 3757–3776, https://doi.org/10.5194/bg-13-3757-2016, https://doi.org/10.5194/bg-13-3757-2016, 2016
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We derived the global maps of grassland management intensity of 1901–2012, including the minimum area of managed grassland with fraction of mown/grazed part. These maps, to our knowledge for the first time, provide global, time-dependent information for drawing up global estimates of management impact on biomass production and yields and for global vegetation models to enable simulations of carbon stocks and GHG budgets beyond simple tuning of grassland productivities to account for management.
Nickolay A. Krotkov, Chris A. McLinden, Can Li, Lok N. Lamsal, Edward A. Celarier, Sergey V. Marchenko, William H. Swartz, Eric J. Bucsela, Joanna Joiner, Bryan N. Duncan, K. Folkert Boersma, J. Pepijn Veefkind, Pieternel F. Levelt, Vitali E. Fioletov, Russell R. Dickerson, Hao He, Zifeng Lu, and David G. Streets
Atmos. Chem. Phys., 16, 4605–4629, https://doi.org/10.5194/acp-16-4605-2016, https://doi.org/10.5194/acp-16-4605-2016, 2016
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We examine changes in SO2 and NO2 over the world's most polluted regions during the first decade of Aura OMI observations. Over the eastern US, both NO2 and SO2 levels decreased by 40 % and 80 %, respectively. OMI confirmed large reductions in SO2 over eastern Europe's largest coal power plants. The North China Plain has the world's most severe SO2 pollution, but a decreasing trend been observed since 2011, with a 50 % reduction in 2012–2014. India's SO2 and NO2 levels are growing at a fast pace.
Zhong Chen, Matthew DeLand, and Pawan K. Bhartia
Atmos. Meas. Tech., 9, 1239–1246, https://doi.org/10.5194/amt-9-1239-2016, https://doi.org/10.5194/amt-9-1239-2016, 2016
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Melanie S. Hammer, Randall V. Martin, Aaron van Donkelaar, Virginie Buchard, Omar Torres, David A. Ridley, and Robert J. D. Spurr
Atmos. Chem. Phys., 16, 2507–2523, https://doi.org/10.5194/acp-16-2507-2016, https://doi.org/10.5194/acp-16-2507-2016, 2016
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We interpret satellite observations to infer the global absorption properties of brown carbon (BrC) aerosols. We incorporate these BrC absorption properties into a chemical transport model to estimate global direct radiative effects and changes in hydroxyl radical (OH) concentrations. To our knowledge, this is the first time the effect of BrC absorption on atmospheric photochemistry has been considered in a global chemical transport model.
U. Jeong, J. Kim, C. Ahn, O. Torres, X. Liu, P. K. Bhartia, R. J. D. Spurr, D. Haffner, K. Chance, and B. N. Holben
Atmos. Chem. Phys., 16, 177–193, https://doi.org/10.5194/acp-16-177-2016, https://doi.org/10.5194/acp-16-177-2016, 2016
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An aerosol retrieval and error analysis algorithm using OMI measurements based on an optimal-estimation method was developed in this study. The aerosol retrievals were validated using the DRAGON campaign products. The estimated errors of the retrievals represented the actual biases between retrieval and AERONET measurements well. The retrievals, with their estimated uncertainties, are expected to be valuable for relevant studies, such as trace gas retrieval and data assimilation.
J.-T. Lin, M.-Y. Liu, J.-Y. Xin, K. F. Boersma, R. Spurr, R. Martin, and Q. Zhang
Atmos. Chem. Phys., 15, 11217–11241, https://doi.org/10.5194/acp-15-11217-2015, https://doi.org/10.5194/acp-15-11217-2015, 2015
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We conduct an improved OMI-based retrieval of tropospheric NO2 VCDs (POMINO) over China by explicitly accounting for aerosol optical effects and surface reflectance anisotropy. Compared to the traditional implicit aerosol treatment, an explicit treatment greatly lowers NO2 VCDs and subsequently estimated NOx emissions over eastern China, but with large spatiotemporal dependence. An explicit treatment also better captures high-pollution days. Effects of surface reflectance treatments are smaller.
W. Hewson, M. P. Barkley, G. Gonzalez Abad, H. Bösch, T. Kurosu, R. Spurr, and L. G. Tilstra
Atmos. Meas. Tech., 8, 4055–4074, https://doi.org/10.5194/amt-8-4055-2015, https://doi.org/10.5194/amt-8-4055-2015, 2015
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This work presents the air mass factor (AMF) algorithm in use at the University of Leicester, which introduces scene-specific variables into a per-observation full radiative transfer AMF calculation, including increasing spatial resolution of key environmental parameter databases, input variable area weighting, instrument-specific scattering weight calculation, and inclusion of an ozone vertical profile climatology.
M. Coldewey-Egbers, D. G. Loyola, M. Koukouli, D. Balis, J.-C. Lambert, T. Verhoelst, J. Granville, M. van Roozendael, C. Lerot, R. Spurr, S. M. Frith, and C. Zehner
Atmos. Meas. Tech., 8, 3923–3940, https://doi.org/10.5194/amt-8-3923-2015, https://doi.org/10.5194/amt-8-3923-2015, 2015
N. R. P. Harris, B. Hassler, F. Tummon, G. E. Bodeker, D. Hubert, I. Petropavlovskikh, W. Steinbrecht, J. Anderson, P. K. Bhartia, C. D. Boone, A. Bourassa, S. M. Davis, D. Degenstein, A. Delcloo, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, N. Jones, M. J. Kurylo, E. Kyrölä, M. Laine, S. T. Leblanc, J.-C. Lambert, B. Liley, E. Mahieu, A. Maycock, M. de Mazière, A. Parrish, R. Querel, K. H. Rosenlof, C. Roth, C. Sioris, J. Staehelin, R. S. Stolarski, R. Stübi, J. Tamminen, C. Vigouroux, K. A. Walker, H. J. Wang, J. Wild, and J. M. Zawodny
Atmos. Chem. Phys., 15, 9965–9982, https://doi.org/10.5194/acp-15-9965-2015, https://doi.org/10.5194/acp-15-9965-2015, 2015
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Trends in the vertical distribution of ozone are reported for new and recently revised data sets. The amount of ozone-depleting compounds in the stratosphere peaked in the second half of the 1990s. We examine the trends before and after that peak to see if any change in trend is discernible. The previously reported decreases are confirmed. Furthermore, the downward trend in upper stratospheric ozone has not continued. The possible significance of any increase is discussed in detail.
P. Köhler, L. Guanter, and J. Joiner
Atmos. Meas. Tech., 8, 2589–2608, https://doi.org/10.5194/amt-8-2589-2015, https://doi.org/10.5194/amt-8-2589-2015, 2015
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The paper presents recent developments for the retrieval of sun-induced fluorescence (SIF) from medium spectral resolution space-borne spectrometers such as the Global Ozone Monitoring Experiment (GOME-2) and the Scanning Imaging Absorption SpectroMeter for Atmospheric ChartographY (SCIAMACHY). Beside using simulated radiances to evaluate the retrieval performance, the method has also been used to estimate SIF at 740 nm using real spectra from GOME-2 and for the first time, from SCIAMACHY.
I. Ialongo, J. Hakkarainen, R. Kivi, P. Anttila, N. A. Krotkov, K. Yang, C. Li, S. Tukiainen, S. Hassinen, and J. Tamminen
Atmos. Meas. Tech., 8, 2279–2289, https://doi.org/10.5194/amt-8-2279-2015, https://doi.org/10.5194/amt-8-2279-2015, 2015
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The SO2 observations from OMI and OMPS satellite instruments are compared to ground-based measurements during the Icelandic Holuhraun fissure eruption in September 2014. The best agreement with the Brewer observations in Sodankylä, Finland can be found, assuming the SO2 predominantly located in the lowest levels of the atmosphere. The analysis of the SO2 surface concentrations in northern Finland supports the hypothesis that the volcanic plume was located very close to the surface.
V. Buchard, A. M. da Silva, P. R. Colarco, A. Darmenov, C. A. Randles, R. Govindaraju, O. Torres, J. Campbell, and R. Spurr
Atmos. Chem. Phys., 15, 5743–5760, https://doi.org/10.5194/acp-15-5743-2015, https://doi.org/10.5194/acp-15-5743-2015, 2015
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MERRAero is an aerosol reanalysis based on the GEOS-5 earth system model that incorporates an online aerosol module and assimilation of AOD from MODIS sensors. This study assesses the quality of MERRAero absorption using independent OMI observations. In addition to comparisons to OMI absorption AOD, we have developed a radiative transfer interface to simulate the UV aerosol index from assimilated aerosol fields at OMI footprint. Also, we fully diagnose the model using MISR, AERONET and CALIPSO.
L. Guanter, I. Aben, P. Tol, J. M. Krijger, A. Hollstein, P. Köhler, A. Damm, J. Joiner, C. Frankenberg, and J. Landgraf
Atmos. Meas. Tech., 8, 1337–1352, https://doi.org/10.5194/amt-8-1337-2015, https://doi.org/10.5194/amt-8-1337-2015, 2015
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This paper investigates the potential of the upcoming TROPOspheric Monitoring Instrument (TROPOMI) instrument for the retrieval of the chlorophyll fluorescence signal emitted in the 650–850nm spectral range by the photosynthetic machinery of green plants. We find that TROPOMI will allow substantial improvements in the space monitoring of fluorescence with respect to current spaceborne instruments such as GOME-2 and SCIAMACHY.
R. Loughman, D. Flittner, E. Nyaku, and P. K. Bhartia
Atmos. Chem. Phys., 15, 3007–3020, https://doi.org/10.5194/acp-15-3007-2015, https://doi.org/10.5194/acp-15-3007-2015, 2015
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The Gauss--Seidel limb scattering (GSLS) radiative transfer model simulates the transfer of solar radiation through the atmosphere. Several recent changes have been added that improve the accuracy and flexibility of the GSLS radiance calculations. The single-scattered radiance errors have been reduced from 4% in earlier studies to 0.3%, while total radiance errors generally decline from 10% to 1-3%. In all cases, the tangent height dependence of the GSLS radiance error is greatly reduced.
J. Bak, X. Liu, J. H. Kim, K. Chance, and D. P. Haffner
Atmos. Chem. Phys., 15, 667–683, https://doi.org/10.5194/acp-15-667-2015, https://doi.org/10.5194/acp-15-667-2015, 2015
L. N. Lamsal, N. A. Krotkov, E. A. Celarier, W. H. Swartz, K. E. Pickering, E. J. Bucsela, J. F. Gleason, R. V. Martin, S. Philip, H. Irie, A. Cede, J. Herman, A. Weinheimer, J. J. Szykman, and T. N. Knepp
Atmos. Chem. Phys., 14, 11587–11609, https://doi.org/10.5194/acp-14-11587-2014, https://doi.org/10.5194/acp-14-11587-2014, 2014
A. Rocha-Lima, J. V. Martins, L. A. Remer, N. A. Krotkov, M. H. Tabacniks, Y. Ben-Ami, and P. Artaxo
Atmos. Chem. Phys., 14, 10649–10661, https://doi.org/10.5194/acp-14-10649-2014, https://doi.org/10.5194/acp-14-10649-2014, 2014
S. Choi, J. Joiner, Y. Choi, B. N. Duncan, A. Vasilkov, N. Krotkov, and E. Bucsela
Atmos. Chem. Phys., 14, 10565–10588, https://doi.org/10.5194/acp-14-10565-2014, https://doi.org/10.5194/acp-14-10565-2014, 2014
N. Hao, M. E. Koukouli, A. Inness, P. Valks, D. G. Loyola, W. Zimmer, D. S. Balis, I. Zyrichidou, M. Van Roozendael, C. Lerot, and R. J. D. Spurr
Atmos. Meas. Tech., 7, 2937–2951, https://doi.org/10.5194/amt-7-2937-2014, https://doi.org/10.5194/amt-7-2937-2014, 2014
A. Vasilkov, J. Joiner, and C. Seftor
Atmos. Meas. Tech., 7, 2897–2906, https://doi.org/10.5194/amt-7-2897-2014, https://doi.org/10.5194/amt-7-2897-2014, 2014
I. Ialongo, J. Hakkarainen, N. Hyttinen, J.-P. Jalkanen, L. Johansson, K. F. Boersma, N. Krotkov, and J. Tamminen
Atmos. Chem. Phys., 14, 7795–7805, https://doi.org/10.5194/acp-14-7795-2014, https://doi.org/10.5194/acp-14-7795-2014, 2014
E. Hache, J.-L. Attié, C. Tourneur, P. Ricaud, L. Coret, W. A. Lahoz, L. El Amraoui, B. Josse, P. Hamer, J. Warner, X. Liu, K. Chance, M. Höpfner, R. Spurr, V. Natraj, S. Kulawik, A. Eldering, and J. Orphal
Atmos. Meas. Tech., 7, 2185–2201, https://doi.org/10.5194/amt-7-2185-2014, https://doi.org/10.5194/amt-7-2185-2014, 2014
A. Parrish, I. S. Boyd, G. E. Nedoluha, P. K. Bhartia, S. M. Frith, N. A. Kramarova, B. J. Connor, G. E. Bodeker, L. Froidevaux, M. Shiotani, and T. Sakazaki
Atmos. Chem. Phys., 14, 7255–7272, https://doi.org/10.5194/acp-14-7255-2014, https://doi.org/10.5194/acp-14-7255-2014, 2014
E. W. Chiou, P. K. Bhartia, R. D. McPeters, D. G. Loyola, M. Coldewey-Egbers, V. E. Fioletov, M. Van Roozendael, R. Spurr, C. Lerot, and S. M. Frith
Atmos. Meas. Tech., 7, 1681–1692, https://doi.org/10.5194/amt-7-1681-2014, https://doi.org/10.5194/amt-7-1681-2014, 2014
B. Hassler, I. Petropavlovskikh, J. Staehelin, T. August, P. K. Bhartia, C. Clerbaux, D. Degenstein, M. De Mazière, B. M. Dinelli, A. Dudhia, G. Dufour, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, J. Granville, N. R. P. Harris, K. Hoppel, D. Hubert, Y. Kasai, M. J. Kurylo, E. Kyrölä, J.-C. Lambert, P. F. Levelt, C. T. McElroy, R. D. McPeters, R. Munro, H. Nakajima, A. Parrish, P. Raspollini, E. E. Remsberg, K. H. Rosenlof, A. Rozanov, T. Sano, Y. Sasano, M. Shiotani, H. G. J. Smit, G. Stiller, J. Tamminen, D. W. Tarasick, J. Urban, R. J. van der A, J. P. Veefkind, C. Vigouroux, T. von Clarmann, C. von Savigny, K. A. Walker, M. Weber, J. Wild, and J. M. Zawodny
Atmos. Meas. Tech., 7, 1395–1427, https://doi.org/10.5194/amt-7-1395-2014, https://doi.org/10.5194/amt-7-1395-2014, 2014
C. A. McLinden, V. Fioletov, K. F. Boersma, S. K. Kharol, N. Krotkov, L. Lamsal, P. A. Makar, R. V. Martin, J. P. Veefkind, and K. Yang
Atmos. Chem. Phys., 14, 3637–3656, https://doi.org/10.5194/acp-14-3637-2014, https://doi.org/10.5194/acp-14-3637-2014, 2014
N. A. Kramarova, E. R. Nash, P. A. Newman, P. K. Bhartia, R. D. McPeters, D. F. Rault, C. J. Seftor, P. Q. Xu, and G. J. Labow
Atmos. Chem. Phys., 14, 2353–2361, https://doi.org/10.5194/acp-14-2353-2014, https://doi.org/10.5194/acp-14-2353-2014, 2014
V. Buchard, A. M. da Silva, P. Colarco, N. Krotkov, R. R. Dickerson, J. W. Stehr, G. Mount, E. Spinei, H. L. Arkinson, and H. He
Atmos. Chem. Phys., 14, 1929–1941, https://doi.org/10.5194/acp-14-1929-2014, https://doi.org/10.5194/acp-14-1929-2014, 2014
J.-T. Lin, R. V. Martin, K. F. Boersma, M. Sneep, P. Stammes, R. Spurr, P. Wang, M. Van Roozendael, K. Clémer, and H. Irie
Atmos. Chem. Phys., 14, 1441–1461, https://doi.org/10.5194/acp-14-1441-2014, https://doi.org/10.5194/acp-14-1441-2014, 2014
J. Joiner, L. Guanter, R. Lindstrot, M. Voigt, A. P. Vasilkov, E. M. Middleton, K. F. Huemmrich, Y. Yoshida, and C. Frankenberg
Atmos. Meas. Tech., 6, 2803–2823, https://doi.org/10.5194/amt-6-2803-2013, https://doi.org/10.5194/amt-6-2803-2013, 2013
E. J. Bucsela, N. A. Krotkov, E. A. Celarier, L. N. Lamsal, W. H. Swartz, P. K. Bhartia, K. F. Boersma, J. P. Veefkind, J. F. Gleason, and K. E. Pickering
Atmos. Meas. Tech., 6, 2607–2626, https://doi.org/10.5194/amt-6-2607-2013, https://doi.org/10.5194/amt-6-2607-2013, 2013
P. K. Bhartia, R. D. McPeters, L. E. Flynn, S. Taylor, N. A. Kramarova, S. Frith, B. Fisher, and M. DeLand
Atmos. Meas. Tech., 6, 2533–2548, https://doi.org/10.5194/amt-6-2533-2013, https://doi.org/10.5194/amt-6-2533-2013, 2013
J. Cuesta, M. Eremenko, X. Liu, G. Dufour, Z. Cai, M. Höpfner, T. von Clarmann, P. Sellitto, G. Foret, B. Gaubert, M. Beekmann, J. Orphal, K. Chance, R. Spurr, and J.-M. Flaud
Atmos. Chem. Phys., 13, 9675–9693, https://doi.org/10.5194/acp-13-9675-2013, https://doi.org/10.5194/acp-13-9675-2013, 2013
N. A. Kramarova, P. K. Bhartia, S. M. Frith, R. D. McPeters, and R. S. Stolarski
Atmos. Meas. Tech., 6, 2089–2099, https://doi.org/10.5194/amt-6-2089-2013, https://doi.org/10.5194/amt-6-2089-2013, 2013
N. A. Kramarova, S. M. Frith, P. K. Bhartia, R. D. McPeters, S. L. Taylor, B. L. Fisher, G. J. Labow, and M. T. DeLand
Atmos. Chem. Phys., 13, 6887–6905, https://doi.org/10.5194/acp-13-6887-2013, https://doi.org/10.5194/acp-13-6887-2013, 2013
A. Vasilkov, J. Joiner, and R. Spurr
Atmos. Meas. Tech., 6, 981–990, https://doi.org/10.5194/amt-6-981-2013, https://doi.org/10.5194/amt-6-981-2013, 2013
J. Wang, S. Park, J. Zeng, C. Ge, K. Yang, S. Carn, N. Krotkov, and A. H. Omar
Atmos. Chem. Phys., 13, 1895–1912, https://doi.org/10.5194/acp-13-1895-2013, https://doi.org/10.5194/acp-13-1895-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Optimal estimation of cloud properties from thermal infrared observations with a combination of deep learning and radiative transfer simulation
3D cloud masking across a broad swath using multi-angle polarimetry and deep learning
Dual-frequency (Ka-band and G-band) radar estimates of liquid water content profiles in shallow clouds
Retrieval of cloud fraction and optical thickness of liquid water clouds over the ocean from multi-angle polarization observations
Severe-hail detection with C-band dual-polarisation radars using convolutional neural networks
Retrieval of cloud fraction using machine learning algorithms based on FY-4A AGRI observations
PEAKO and peakTree: tools for detecting and interpreting peaks in cloud radar Doppler spectra – capabilities and limitations
An advanced spatial coregistration of cloud properties for the atmospheric Sentinel missions: application to TROPOMI
Contrail altitude estimation using GOES-16 ABI data and deep learning
The Ice Cloud Imager: retrieval of frozen water column properties
Supercooled liquid water cloud classification using lidar backscatter peak properties
Marine cloud base height retrieval from MODIS cloud properties using machine learning
How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties
ampycloud: an open-source algorithm to determine cloud base heights and sky coverage fractions from ceilometer data
Retrieving cloud base height and geometric thickness using the oxygen A-band channel of GCOM-C/SGLI
Simulation and detection efficiency analysis for measurements of polar mesospheric clouds using a spaceborne wide-field-of-view ultraviolet imager
The Chalmers Cloud Ice Climatology: retrieval implementation and validation
The algorithm of microphysical-parameter profiles of aerosol and small cloud droplets based on the dual-wavelength lidar data
Bayesian cloud-top phase determination for Meteosat Second Generation
Lidar–radar synergistic method to retrieve ice, supercooled water and mixed-phase cloud properties
Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements
A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations
Discriminating between "Drizzle or rain" and sea salt aerosols in Cloudnet for measurements over the Barbados Cloud Observatory
JAXA Level 2 cloud and precipitation microphysics retrievals based on EarthCARE CPR, ATLID and MSI
Identification of ice-over-water multilayer clouds using multispectral satellite data in an artificial neural network
A new approach to crystal habit retrieval from far-infrared spectral radiance measurements
Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds
Peering into the heart of thunderstorm clouds: Insights from cloud radar and spectral polarimetry
Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI
A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations
Infrared Radiometric Image Classification and Segmentation of Cloud Structure Using Deep-learning Framework for Ground-based Infrared Thermal Camera Observations
Geometrical and optical properties of cirrus clouds in Barcelona, Spain: analysis with the two-way transmittance method of 4 years of lidar measurements
Determination of the vertical distribution of in-cloud particle shape using SLDR-mode 35 GHz scanning cloud radar
Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data
The EarthCARE mission: science data processing chain overview
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products
Raman lidar-derived optical and microphysical properties of ice crystals within thin Arctic clouds during PARCS campaign
Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements
Deep convective cloud system size and structure across the global tropics and subtropics
A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images
Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system
Segmentation of polarimetric radar imagery using statistical texture
Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization
Particle inertial effects on radar Doppler spectra simulation
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
He Huang, Quan Wang, Chao Liu, and Chen Zhou
Atmos. Meas. Tech., 17, 7129–7141, https://doi.org/10.5194/amt-17-7129-2024, https://doi.org/10.5194/amt-17-7129-2024, 2024
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This study introduces a cloud property retrieval method which integrates traditional radiative transfer simulations with a machine learning method. Retrievals from a machine learning algorithm are used to provide a priori states, and a radiative transfer model is used to create lookup tables for later iteration processes. The new method combines the advantages of traditional and machine learning algorithms, and it is applicable to both daytime and nighttime conditions.
Sean R. Foley, Kirk D. Knobelspiesse, Andrew M. Sayer, Meng Gao, James Hays, and Judy Hoffman
Atmos. Meas. Tech., 17, 7027–7047, https://doi.org/10.5194/amt-17-7027-2024, https://doi.org/10.5194/amt-17-7027-2024, 2024
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Measuring the shape of clouds helps scientists understand how the Earth will continue to respond to climate change. Satellites measure clouds in different ways. One way is to take pictures of clouds from multiple angles and to use the differences between the pictures to measure cloud structure. However, doing this accurately can be challenging. We propose a way to use machine learning to recover the shape of clouds from multi-angle satellite data.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, and Pavlos Kollias
Atmos. Meas. Tech., 17, 6965–6981, https://doi.org/10.5194/amt-17-6965-2024, https://doi.org/10.5194/amt-17-6965-2024, 2024
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This article presents a novel technique to estimate liquid water content (LWC) profiles in shallow warm clouds using a pair of collocated Ka-band (35 GHz) and G-band (239 GHz) radars. We demonstrate that the use of a G-band radar allows retrieving the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.
Claudia Emde, Veronika Pörtge, Mihail Manev, and Bernhard Mayer
Atmos. Meas. Tech., 17, 6769–6789, https://doi.org/10.5194/amt-17-6769-2024, https://doi.org/10.5194/amt-17-6769-2024, 2024
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We introduce an innovative method to retrieve the cloud fraction and optical thickness of liquid water clouds over the ocean based on polarimetry. This is well suited for satellite observations providing multi-angle polarization measurements. Cloud fraction and cloud optical thickness can be derived from measurements at two viewing angles: one within the cloudbow and one in the sun glint region.
Vincent Forcadell, Clotilde Augros, Olivier Caumont, Kévin Dedieu, Maxandre Ouradou, Cloé David, Jordi Figueras i Ventura, Olivier Laurantin, and Hassan Al-Sakka
Atmos. Meas. Tech., 17, 6707–6734, https://doi.org/10.5194/amt-17-6707-2024, https://doi.org/10.5194/amt-17-6707-2024, 2024
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This study demonstrates the potential of enhancing severe-hail detection through the application of convolutional neural networks (CNNs) to dual-polarization radar data. It is shown that current methods can be calibrated to significantly enhance their performance for severe-hail detection. This study establishes the foundation for the solution of a more complex problem: the estimation of the maximum size of hailstones on the ground using deep learning applied to radar data.
Jinyi Xia and Li Guan
Atmos. Meas. Tech., 17, 6697–6706, https://doi.org/10.5194/amt-17-6697-2024, https://doi.org/10.5194/amt-17-6697-2024, 2024
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This study presents a method for estimating cloud cover from FY-4A AGRI observations using random forest (RF) and multilayer perceptron (MLP) algorithms. The results demonstrate excellent performance in distinguishing clear-sky scenes and reducing errors in cloud cover estimation. It shows significant improvements compared to existing methods.
Teresa Vogl, Martin Radenz, Fabiola Ramelli, Rosa Gierens, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 6547–6568, https://doi.org/10.5194/amt-17-6547-2024, https://doi.org/10.5194/amt-17-6547-2024, 2024
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In this study, we present a toolkit of two Python algorithms to extract information from Doppler spectra measured by ground-based cloud radars. In these Doppler spectra, several peaks can be formed due to populations of droplets/ice particles with different fall velocities coexisting in the same measurement time and height. The two algorithms can detect peaks and assign them to certain particle types, such as small cloud droplets or fast-falling ice particles like graupel.
Athina Argyrouli, Diego Loyola, Fabian Romahn, Ronny Lutz, Víctor Molina García, Pascal Hedelt, Klaus-Peter Heue, and Richard Siddans
Atmos. Meas. Tech., 17, 6345–6367, https://doi.org/10.5194/amt-17-6345-2024, https://doi.org/10.5194/amt-17-6345-2024, 2024
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This paper describes a new treatment of the spatial misregistration of cloud properties for Sentinel-5 Precursor, when the footprints of different spectral bands are not perfectly aligned. The methodology exploits synergies between spectrometers and imagers, like TROPOMI and VIIRS. The largest improvements have been identified for heterogeneous scenes at cloud edges. This approach is generic and can also be applied to future Sentinel-4 and Sentinel-5 instruments.
Vincent R. Meijer, Sebastian D. Eastham, Ian A. Waitz, and Steven R. H. Barrett
Atmos. Meas. Tech., 17, 6145–6162, https://doi.org/10.5194/amt-17-6145-2024, https://doi.org/10.5194/amt-17-6145-2024, 2024
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Aviation's climate impact is partly due to contrails: the clouds that form behind aircraft and which can linger for hours under certain atmospheric conditions. Accurately forecasting these conditions could allow aircraft to avoid forming these contrails and thus reduce their environmental footprint. Our research uses deep learning to identify three-dimensional contrail locations in two-dimensional satellite imagery, which can be used to assess and improve these forecasts.
Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson
Atmos. Meas. Tech., 17, 5957–5987, https://doi.org/10.5194/amt-17-5957-2024, https://doi.org/10.5194/amt-17-5957-2024, 2024
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The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.
Luke Edgar Whitehead, Adrian James McDonald, and Adrien Guyot
Atmos. Meas. Tech., 17, 5765–5784, https://doi.org/10.5194/amt-17-5765-2024, https://doi.org/10.5194/amt-17-5765-2024, 2024
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Supercooled liquid water cloud is important to represent in weather and climate models, particularly in the Southern Hemisphere. Previous work has developed a new machine learning method for measuring supercooled liquid water in Antarctic clouds using simple lidar observations. We evaluate this technique using a lidar dataset from Christchurch, New Zealand, and develop an updated algorithm for accurate supercooled liquid water detection at mid-latitudes.
Julien Lenhardt, Johannes Quaas, and Dino Sejdinovic
Atmos. Meas. Tech., 17, 5655–5677, https://doi.org/10.5194/amt-17-5655-2024, https://doi.org/10.5194/amt-17-5655-2024, 2024
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Clouds play a key role in the regulation of the Earth's climate. Aspects like the height of their base are of essential interest to quantify their radiative effects but remain difficult to derive from satellite data. In this study, we combine observations from the surface and satellite retrievals of cloud properties to build a robust and accurate method to retrieve the cloud base height, based on a computer vision model and ordinal regression.
Johanna Mayer, Bernhard Mayer, Luca Bugliaro, Ralf Meerkötter, and Christiane Voigt
Atmos. Meas. Tech., 17, 5161–5185, https://doi.org/10.5194/amt-17-5161-2024, https://doi.org/10.5194/amt-17-5161-2024, 2024
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This study uses radiative transfer calculations to characterize the relation of two satellite channel combinations (namely infrared window brightness temperature differences – BTDs – of SEVIRI) to the thermodynamic cloud phase. A sensitivity analysis reveals the complex interplay of cloud parameters and their contribution to the observed phase dependence of BTDs. This knowledge helps to design optimal cloud-phase retrievals and to understand their potential and limitations.
Frédéric P. A. Vogt, Loris Foresti, Daniel Regenass, Sophie Réthoré, Néstor Tarin Burriel, Mervyn Bibby, Przemysław Juda, Simone Balmelli, Tobias Hanselmann, Pieter du Preez, and Dirk Furrer
Atmos. Meas. Tech., 17, 4891–4914, https://doi.org/10.5194/amt-17-4891-2024, https://doi.org/10.5194/amt-17-4891-2024, 2024
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ampycloud is a new algorithm developed at MeteoSwiss to characterize the height and sky coverage fraction of cloud layers above aerodromes via ceilometer data. This algorithm was devised as part of a larger effort to fully automate the creation of meteorological aerodrome reports (METARs) at Swiss civil airports. The ampycloud algorithm is implemented as a Python package that is made publicly available to the community under the 3-Clause BSD license.
Takashi M. Nagao, Kentaroh Suzuki, and Makoto Kuji
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-141, https://doi.org/10.5194/amt-2024-141, 2024
Revised manuscript accepted for AMT
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In satellite remote sensing, estimating cloud base height (CBH) is more challenging than estimating cloud top height because the cloud base is obscured by the cloud itself. We developed an algorithm using the specific channel (known as the oxygen A-band channel) of the SGLI instrument on JAXA’s GCOM-C satellite to estimate CBH together with other cloud properties. This algorithm can provide global distributions of CBH across various cloud types, including liquid, ice, and mixed-phase clouds.
Ke Ren, Haiyang Gao, Shuqi Niu, Shaoyang Sun, Leilei Kou, Yanqing Xie, Liguo Zhang, and Lingbing Bu
Atmos. Meas. Tech., 17, 4825–4842, https://doi.org/10.5194/amt-17-4825-2024, https://doi.org/10.5194/amt-17-4825-2024, 2024
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Ultraviolet imaging technology has significantly advanced the research and development of polar mesospheric clouds (PMCs). In this study, we proposed the wide-field-of-view ultraviolet imager (WFUI) and built a forward model to evaluate the detection capability and efficiency. The results demonstrate that the WFUI performs well in PMC detection and has high detection efficiency. The relationship between ice water content and detection efficiency follows an exponential function distribution.
Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson
Atmos. Meas. Tech., 17, 4337–4368, https://doi.org/10.5194/amt-17-4337-2024, https://doi.org/10.5194/amt-17-4337-2024, 2024
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The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limitations of currently available data records of cloud properties. In this work, we address this issue by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.
Huige Di, Xinhong Wang, Ning Chen, Jing Guo, Wenhui Xin, Shichun Li, Yan Guo, Qing Yan, Yufeng Wang, and Dengxin Hua
Atmos. Meas. Tech., 17, 4183–4196, https://doi.org/10.5194/amt-17-4183-2024, https://doi.org/10.5194/amt-17-4183-2024, 2024
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This study proposes an inversion method for atmospheric-aerosol or cloud microphysical parameters based on dual-wavelength lidar data. It is suitable for the inversion of uniformly mixed and single-property aerosol layers or small cloud droplets. For aerosol particles, the inversion range that this algorithm can achieve is 0.3–1.7 μm. For cloud droplets, it is 1.0–10 μm. This algorithm can quickly obtain the microphysical parameters of atmospheric particles and has better robustness.
Johanna Mayer, Luca Bugliaro, Bernhard Mayer, Dennis Piontek, and Christiane Voigt
Atmos. Meas. Tech., 17, 4015–4039, https://doi.org/10.5194/amt-17-4015-2024, https://doi.org/10.5194/amt-17-4015-2024, 2024
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ProPS (PRObabilistic cloud top Phase retrieval for SEVIRI) is a method to detect clouds and their thermodynamic phase with a geostationary satellite, distinguishing between clear sky and ice, mixed-phase, supercooled and warm liquid clouds. It uses a Bayesian approach based on the lidar–radar product DARDAR. The method allows studying cloud phases, especially mixed-phase and supercooled clouds, rarely observed from geostationary satellites. This can be used for comparison with climate models.
Clémantyne Aubry, Julien Delanoë, Silke Groß, Florian Ewald, Frédéric Tridon, Olivier Jourdan, and Guillaume Mioche
Atmos. Meas. Tech., 17, 3863–3881, https://doi.org/10.5194/amt-17-3863-2024, https://doi.org/10.5194/amt-17-3863-2024, 2024
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Radar–lidar synergy is used to retrieve ice, supercooled water and mixed-phase cloud properties, making the most of the radar sensitivity to ice crystals and the lidar sensitivity to supercooled droplets. A first analysis of the output of the algorithm run on the satellite data is compared with in situ data during an airborne Arctic field campaign, giving a mean percent error of 49 % for liquid water content and 75 % for ice water content.
Gerald G. Mace
Atmos. Meas. Tech., 17, 3679–3695, https://doi.org/10.5194/amt-17-3679-2024, https://doi.org/10.5194/amt-17-3679-2024, 2024
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The number of cloud droplets per unit volume, Nd, in a cloud is important for understanding aerosol–cloud interaction. In this study, we develop techniques to derive cloud droplet number concentration from lidar measurements combined with other remote sensing measurements such as cloud radar and microwave radiometers. We show that deriving Nd is very uncertain, although a synergistic algorithm seems to produce useful characterizations of Nd and effective particle size.
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, https://doi.org/10.5194/amt-17-3583-2024, 2024
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This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Johanna Roschke, Jonas Witthuhn, Marcus Klingebiel, Moritz Haarig, Andreas Foth, Anton Kötsche, and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2024-894, https://doi.org/10.5194/egusphere-2024-894, 2024
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We present a technique to discriminate between the Cloudnet target classification of "Drizzle or rain" and sea salt aerosols that is applicable to marine Cloudnet sites. The method is crucial for investigating the occurrence of precipitation and significantly improves the Cloudnet target classification scheme for the measurements over the Barbados Cloud Observatory (BCO). A first-ever analysis of the Cloudnet product including the new "haze echo" target over two years at the BCO is presented.
Kaori Sato, Hajime Okamoto, Tomoaki Nishizawa, Yoshitaka Jin, Takashi Nakajima, Minrui Wang, Masaki Satoh, Woosub Roh, Hiroshi Ishimoto, and Rei Kudo
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-99, https://doi.org/10.5194/amt-2024-99, 2024
Revised manuscript accepted for AMT
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This study introduces the JAXA EarthCARE L2 cloud product using satellite observations and simulated EarthCARE data. The outputs from the product feature a 3D global view of the dominant ice habit categories and corresponding microphysics. Habit and size distribution transitions from cloud to precipitation will be quantified by the L2 cloud algorithms. With Doppler data, the products can be beneficial for further understanding of the coupling of cloud microphysics, radiation, and dynamics.
Sunny Sun-Mack, Patrick Minnis, Yan Chen, Gang Hong, and William L. Smith Jr.
Atmos. Meas. Tech., 17, 3323–3346, https://doi.org/10.5194/amt-17-3323-2024, https://doi.org/10.5194/amt-17-3323-2024, 2024
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Multilayer clouds (MCs) affect the radiation budget differently than single-layer clouds (SCs) and need to be identified in satellite images. A neural network was trained to identify MCs by matching imagery with lidar/radar data. This method correctly identifies ~87 % SCs and MCs with a net accuracy gain of 7.5 % over snow-free surfaces. It is more accurate than most available methods and constitutes a first step in providing a reasonable 3-D characterization of the cloudy atmosphere.
Gianluca Di Natale, Marco Ridolfi, and Luca Palchetti
Atmos. Meas. Tech., 17, 3171–3186, https://doi.org/10.5194/amt-17-3171-2024, https://doi.org/10.5194/amt-17-3171-2024, 2024
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This work aims to define a new approach to retrieve the distribution of the main ice crystal shapes occurring inside ice and cirrus clouds from infrared spectral measurements. The capability of retrieving these shapes of the ice crystals from satellites will allow us to extend the currently available climatologies to be used as physical constraints in general circulation models. This could could allow us to improve their accuracy and prediction performance.
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech., 17, 3011–3028, https://doi.org/10.5194/amt-17-3011-2024, https://doi.org/10.5194/amt-17-3011-2024, 2024
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We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on the multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere. The MS effect on lidar signals always decreases with the increasing distance from the cloud far edge. The decrease is the direct consequence of the fact that the forward peak of particle phase functions is much larger than the receiver field of view.
Ho Yi Lydia Mak and Christine Unal
EGUsphere, https://doi.org/10.5194/egusphere-2024-1232, https://doi.org/10.5194/egusphere-2024-1232, 2024
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The dynamics of thunderclouds is studied using cloud radar. Supercooled liquid water and conical graupel are likely present, while chain-like ice crystals may occur at cloud top. Ice crystals are vertically aligned seconds before lightning and resume their usual horizontal alignment afterwards in some cases. Updrafts and downdrafts are found near cloud core and edges respectively. Turbulence is strong. Radar measurement modes that are more suited for investigating thunderstorms are recommended.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-40, https://doi.org/10.5194/amt-2024-40, 2024
Revised manuscript accepted for AMT
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Our study investigates the impact of cloud shadows on satellite-based aerosol index measurements over Europe by TROPOMI. Using a cloud shadow detection algorithm and simulations, we found that the overall effect on the aerosol index is minimal. Interestingly, we measured that cloud shadows are significantly bluer than their shadow-free surroundings, but the traditional algorithm already (partly) automatically corrects for this increased blueness.
Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, and Matthias Tesche
Atmos. Meas. Tech., 17, 1739–1757, https://doi.org/10.5194/amt-17-1739-2024, https://doi.org/10.5194/amt-17-1739-2024, 2024
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We present a novel method for studying aerosol–cloud interactions. It combines cloud-relevant aerosol concentrations from polar-orbiting lidar observations with the development of individual clouds from geostationary observations. Application to 1 year of data gives first results on the impact of aerosols on the concentration and size of cloud droplets and on cloud phase in the regime of heterogeneous ice formation. The method could enable the systematic investigation of warm and cold clouds.
Kélian Sommer, Wassim Kabalan, and Romain Brunet
EGUsphere, https://doi.org/10.5194/egusphere-2024-101, https://doi.org/10.5194/egusphere-2024-101, 2024
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Our research introduces a novel deep-learning approach for classifying and segmenting ground-based infrared thermal images, a crucial step in cloud monitoring. Tests on self-captured data showcase its excellent accuracy in distinguishing image types and in structure segmentation. With potential applications in astronomical observations, our work pioneers a robust solution for ground-based sky quality assessment, promising advancements in the photometric observations experiments.
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
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In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024, https://doi.org/10.5194/amt-17-999-2024, 2024
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The vertical distribution of particle shape (VDPS) method, introduced in this study, aids in characterizing the density-weighted shape of cloud particles from scanning slanted linear depolarization ratio (SLDR)-mode cloud radar observations. The VDPS approach represents a new, versatile way to study microphysical processes by combining a spheroidal scattering model with real measurements of SLDR.
Sarah Brüning, Stefan Niebler, and Holger Tost
Atmos. Meas. Tech., 17, 961–978, https://doi.org/10.5194/amt-17-961-2024, https://doi.org/10.5194/amt-17-961-2024, 2024
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We apply the Res-UNet to derive a comprehensive 3D cloud tomography from 2D satellite data over heterogeneous landscapes. We combine observational data from passive and active remote sensing sensors by an automated matching algorithm. These data are fed into a neural network to predict cloud reflectivities on the whole satellite domain between 2.4 and 24 km height. With an average RMSE of 2.99 dBZ, we contribute to closing data gaps in the representation of clouds in observational data.
Michael Eisinger, Fabien Marnas, Kotska Wallace, Takuji Kubota, Nobuhiro Tomiyama, Yuichi Ohno, Toshiyuki Tanaka, Eichi Tomita, Tobias Wehr, and Dirk Bernaerts
Atmos. Meas. Tech., 17, 839–862, https://doi.org/10.5194/amt-17-839-2024, https://doi.org/10.5194/amt-17-839-2024, 2024
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The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) is an ESA–JAXA satellite mission to be launched in 2024. We presented an overview of the EarthCARE processors' development, with processors developed by teams in Europe, Japan, and Canada. EarthCARE will allow scientists to evaluate the representation of cloud, aerosol, precipitation, and radiative flux in weather forecast and climate models, with the objective to better understand cloud processes and improve weather and climate models.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
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The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
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The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
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The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Damao Zhang, Andrew M. Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William I. Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
Atmos. Meas. Tech., 16, 5827–5846, https://doi.org/10.5194/amt-16-5827-2023, https://doi.org/10.5194/amt-16-5827-2023, 2023
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Cloud droplet number concentration can be retrieved from remote sensing measurements. Aircraft measurements are used to validate four ground-based retrievals of cloud droplet number concentration. We demonstrate that retrieved cloud droplet number concentrations align well with aircraft measurements for overcast clouds, but they may substantially differ for broken clouds. The ensemble of various retrievals can help quantify retrieval uncertainties and identify reliable retrieval scenarios.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
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A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
Atmos. Meas. Tech., 16, 5305–5326, https://doi.org/10.5194/amt-16-5305-2023, https://doi.org/10.5194/amt-16-5305-2023, 2023
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Near-infrared satellite images have information on clouds that is complementary to what is available from the visible and infrared parts of the spectrum. Using this information for data assimilation and model evaluation requires a fast, accurate forward operator to compute synthetic images from numerical weather prediction model output. We discuss a novel, neural-network-based approach for the 1.6 µm near-infrared channel that is suitable for this purpose and also works for other solar channels.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, https://doi.org/10.5194/amt-16-4927-2023, 2023
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The EarthCARE satellite mission Level 2 algorithm development requires realistic 3D cloud and aerosol scenes along the satellite orbits. One of the best ways to produce these scenes is to use a high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This paper describes the production and validation of three EarthCARE test scenes.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
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We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
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Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
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We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
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We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
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We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
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JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
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Short summary
We discuss a new cloud algorithm that retrieves effective cloud fraction and cloud altitude and pressure from the oxygen dimer absorption band at 477 nm. The algorithm accounts for how changes in the sun–satellite geometry affect the surface reflection. The cloud fraction and pressure are used as inputs to the OMI algorithm that retrieves a pollutant gas called nitrogen dioxide. Impacts of the application of the newly developed cloud algorithm on the OMI nitrogen dioxide retrieval are discussed.
We discuss a new cloud algorithm that retrieves effective cloud fraction and cloud altitude and...
