Applying Deep Learning to NASA MODIS Data to Create a Community Record of Marine Low Cloud Mesoscale Morphology
Tianle Yuan, Hua Song, Robert Wood, Johannes Mohrmann, Kerry Meyer, Lazaros Oreopoulos, and Steven Platnick
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2020-61,2020
Preprint under review for AMT (discussion: open, 0 comments)
We use deep transfer learning techniques to classify satellite cloud images into different morphology types. It achieves the state-of-the-art results and can automatically process large amount of satellite data. The algorithm will help low cloud researchers to better understand their mesoscale organiizations.
MAX-DOAS measurements of tropospheric NO2 and HCHO in Munich and the comparison to OMI and TROPOMI satellite observations
Ka Lok Chan, Matthias Wiegner, Carlos Alberti, and Mark Wenig
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2020-35,2020
Preprint under review for AMT (discussion: open, 0 comments)
The manuscript presents 2D MAX-DOAS observations of vertical distribution of aerosol extinction, NO2 and HCHO in Munich. The measured surface aerosol extinction coefficients and NO2 mixing ratios are compared to in-situ monitor data. The NO2 and HCHO data are subsequently used to validate satellite measurements. The MAX-DOAS measurements are also used to investigate the spatio-temporal characteristic of NO2 and HCHO in Munich.
Ground-based observations of cloud and drizzle liquid water path in stratocumulus clouds
Maria P. Cadeddu, Virendra P. Ghate, and Mario Mech
Atmos. Meas. Tech., 13, 1485–1499, https://doi.org/10.5194/amt-13-1485-2020, 2020
A combination of ground-based active and passive observations is used to partition cloud and precipitation liquid water path in precipitating stratocumulous clouds. Results show that neglecting scattering effects from drizzle drops leads to 8–15 % overestimation of the liquid amount in the cloud. In closed-cell systems only ~20 % of the available drizzle in the cloud falls below the cloud base, compared to ~40 % in open-cell systems.
Doppler lidar at Observatoire de Haute-Provence for wind profiling up to 75 km altitude: performance evaluation and observations
Sergey M. Khaykin, Alain Hauchecorne, Robin Wing, Philippe Keckhut, Sophie Godin-Beekmann, Jacques Porteneuve, Jean-Francois Mariscal, and Jerome Schmitt
Atmos. Meas. Tech., 13, 1501–1516, https://doi.org/10.5194/amt-13-1501-2020, 2020
The article presents a powerful atmospheric instrument based on a laser radar (lidar), capable of measuring horizontal wind velocity at a wide range of altitudes. In this study, we evaluate the performance of the wind lidar at Observatoire de Haute-Provence and demonstrate the application of its measurements for studies of atmospheric dynamical processes. Finally, we present an example of early validation of the ESA Aeolus space-borne wind lidar using its ground-based predecessor.
Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: method development for probabilistic modeling of organic carbon and organic matter concentrations
Charlotte Bürki, Matteo Reggente, Ann M. Dillner, Jenny L. Hand, Stephanie L. Shaw, and Satoshi Takahama
Atmos. Meas. Tech., 13, 1517–1538, https://doi.org/10.5194/amt-13-1517-2020, 2020
Infrared spectroscopy is a chemically informative method for particulate matter characterization. However, recent work has demonstrated that predictions depend heavily on the choice of calibration model parameters. We propose a means for managing parameter uncertainties by combining available data from laboratory standards, molecular databases, and collocated ambient measurements to provide useful characterization of atmospheric organic matter on a large scale.
Real-time pollen monitoring using digital holography
Eric Sauvageat, Yanick Zeder, Kevin Auderset, Bertrand Calpini, Bernard Clot, Benoît Crouzy, Thomas Konzelmann, Gian Lieberherr, Fiona Tummon, and Konstantina Vasilatou
Atmos. Meas. Tech., 13, 1539–1550, https://doi.org/10.5194/amt-13-1539-2020, 2020
We present the first validation of the only operational automatic pollen monitoring system based on holography, the Swisens Poleno. The device produces real-time images of coarse aerosols, and by applying a machine learning algorithm we identify a range of pollen taxa with accuracy >90 %. The device was further validated in controlled chamber experiments to verify the counting ability and the performance of additional fluorescence measurements, which can further be used in pollen identification.
Applying Deep Learning to NASA MODIS Data to Create a Community Record of Marine Low Cloud Mesoscale Morphology
Tianle Yuan, Hua Song, Robert Wood, Johannes Mohrmann, Kerry Meyer, Lazaros Oreopoulos, and Steven Platnick
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-61,2020
Preprint under review for AMT (discussion: open, 0 comments)
We use deep transfer learning techniques to classify satellite cloud images into different morphology types. It achieves the state-of-the-art results and can automatically process large amount of satellite data. The algorithm will help low cloud researchers to better understand their mesoscale organiizations.
MAX-DOAS measurements of tropospheric NO2 and HCHO in Munich and the comparison to OMI and TROPOMI satellite observations
Ka Lok Chan, Matthias Wiegner, Carlos Alberti, and Mark Wenig
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-35,2020
Preprint under review for AMT (discussion: open, 0 comments)
The manuscript presents 2D MAX-DOAS observations of vertical distribution of aerosol extinction, NO2 and HCHO in Munich. The measured surface aerosol extinction coefficients and NO2 mixing ratios are compared to in-situ monitor data. The NO2 and HCHO data are subsequently used to validate satellite measurements. The MAX-DOAS measurements are also used to investigate the spatio-temporal characteristic of NO2 and HCHO in Munich.
Validation of tropospheric NO2 column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Nicolas Theys, Nader Abuhassan, Alkiviadis Bais, Folkert Boersma, Alexander Cede, Jihyo Chong, Sebastian Donner, Theano Drosoglou, Udo Frieß, José Granville, Jay R. Herman, Henk Eskes, Robert Holla, Jari Hovila, Hitoshi Irie, Yugo Kanaya, Dimitris Karagkiozidis, Natalia Kouremeti, Jean-Christopher Lambert, Jianzhong Ma, Enno Peters, Ankie Piters, Oleg Postylyakov, Andreas Richter, Julia Remmers, Hisahiro Takashima, Martin Tiefengraber, Pieter Valks, Tim Vlemmix, Thomas Wagner, and Folkard Wittrock
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-76,2020
Preprint under review for AMT (discussion: open, 0 comments)
We validate several GOME-2 and OMI tropospheric NO2 products with 23 MAX-DOAS and 16 direct sun instruments distributed worldwide. We highlight large horizontal inhomogeneities at several sites affecting the validation results and we propose a method to quantify and correct for it. We show that the application of such correction reduces the satellite underestimation in almost all heterogeneous cases, but a negative bias remains over the MAX-DOAS + direct sun network ensemble for both satellites.
Testing the near-field Gaussian plume inversion flux quantification technique using unmanned aerial vehicle sampling
Adil Shah, Joseph R. Pitt, Hugo Ricketts, J. Brian Leen, Paul I. Williams, Khristopher Kabbabe, Martin W. Gallagher, and Grant Allen
Atmos. Meas. Tech., 13, 1467–1484, https://doi.org/10.5194/amt-13-1467-2020, 2020
Methane is a potent greenhouse gas, with large flux uncertainties from facility-scale sources, such as natural gas extraction infrastructure. A recently developed flux quantification method was successfully tested by flying an unmanned aerial vehicle (UAV) downwind of 22 controlled atmospheric methane releases. The UAVs were used to derive high-precision atmospheric methane measurements. The UAV methodology was successful in both detecting the release and providing a rough flux estimate.
InnFLUX – an open-source code for conventional and disjunct eddy covariance analysis of trace gas measurements: an urban test case
Marcus Striednig, Martin Graus, Tilmann D. Märk, and Thomas G. Karl
Atmos. Meas. Tech., 13, 1447–1465, https://doi.org/10.5194/amt-13-1447-2020, 2020
The current work summarizes a long-term effort to provide an open-source code for the analysis of turbulent fluctuations of trace gases in the atmosphere by eddy covariance and disjunct eddy covariance, with a special focus on reactive gases that participate in atmospheric chemistry. The performance of the code is successfully evaluated based on measurements of minute fluxes of non-methane volatile organic compounds into the urban atmosphere.
The 2018 fire season in North America as seen by TROPOMI: aerosol layer height intercomparisons and evaluation of model-derived plume heights
Debora Griffin, Christopher Sioris, Jack Chen, Nolan Dickson, Andrew Kovachik, Martin de Graaf, Swadhin Nanda, Pepijn Veefkind, Enrico Dammers, Chris A. McLinden, Paul Makar, and Ayodeji Akingunola
Atmos. Meas. Tech., 13, 1427–1445, https://doi.org/10.5194/amt-13-1427-2020, 2020
This study looks into validating the aerosol layer height product from the recently launched TROPOspheric Monitoring Instrument (TROPOMI) for forest fire plume through comparisons with two other satellite products, and interpreting differences due to the individual measurement techniques. These satellite observations are compared to predicted plume heights from Environment and Climate Change's air quality forecast model.
Shipborne MAX-DOAS measurements for validation of TROPOMI NO2 products
Ping Wang, Ankie Piters, Jos van Geffen, Olaf Tuinder, Piet Stammes, and Stefan Kinne
Atmos. Meas. Tech., 13, 1413–1426, https://doi.org/10.5194/amt-13-1413-2020, 2020
The comparison of shipborne MAX-DOAS and TROPOMI NO2 products is important for the evaluation of the TROPOMI products. The ship cruises were mainly over remote oceans, thus we only measured background tropospheric NO2. Stratospheric NO2 was measured more accurately because there was almost no contamination from tropospheric NO2. We found that the TROPOMI stratospheric NO2 vertical column densities were slightly higher than the MAX-DOAS measurements.
Quality controls, bias, and seasonality of CO2 columns in the Boreal Forest with OCO-2, TCCON, and EM27/SUN measurements
Nicole Jacobs, William R. Simpson, Debra Wunch, Christopher W. O'Dell, Gregory B. Osterman, Frank Hase, Thomas Blumenstock, Qiansi Tu, Matthias Frey, Manvendra K. Dubey, Harrison A. Parker, Rigel Kivi, and Pauli Heikkinen
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2019-505,2020
Preprint under review for AMT (discussion: open, 0 comments)
The Boreal forest is the largest seasonally-varying biospheric carbon dioxide exchange region on Earth. This region is also undergoing amplified climate warming leading to concerns about the potential for altered regional carbon exchange. Satellite missions such as the orbiting carbon observer-2 (OCO-2) project can measure CO2 abundance over the Boreal forest, but need validation for assurance of accuracy. Therefore, we carried out ground-based validation of OCO-2 CO2 data at three locations.
Validation of tropospheric NO2 column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Nicolas Theys, Nader Abuhassan, Alkiviadis Bais, Folkert Boersma, Alexander Cede, Jihyo Chong, Sebastian Donner, Theano Drosoglou, Udo Frieß, José Granville, Jay R. Herman, Henk Eskes, Robert Holla, Jari Hovila, Hitoshi Irie, Yugo Kanaya, Dimitris Karagkiozidis, Natalia Kouremeti, Jean-Christopher Lambert, Jianzhong Ma, Enno Peters, Ankie Piters, Oleg Postylyakov, Andreas Richter, Julia Remmers, Hisahiro Takashima, Martin Tiefengraber, Pieter Valks, Tim Vlemmix, Thomas Wagner, and Folkard Wittrock
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2020-76,2020
Preprint under review for AMT (discussion: open, 0 comments)
We validate several GOME-2 and OMI tropospheric NO2 products with 23 MAX-DOAS and 16 direct sun instruments distributed worldwide. We highlight large horizontal inhomogeneities at several sites affecting the validation results and we propose a method to quantify and correct for it. We show that the application of such correction reduces the satellite underestimation in almost all heterogeneous cases, but a negative bias remains over the MAX-DOAS + direct sun network ensemble for both satellites.
Testing the near-field Gaussian plume inversion flux quantification technique using unmanned aerial vehicle sampling
Adil Shah, Joseph R. Pitt, Hugo Ricketts, J. Brian Leen, Paul I. Williams, Khristopher Kabbabe, Martin W. Gallagher, and Grant Allen
Atmos. Meas. Tech., 13, 1467–1484, https://doi.org/10.5194/amt-13-1467-2020, 2020
Methane is a potent greenhouse gas, with large flux uncertainties from facility-scale sources, such as natural gas extraction infrastructure. A recently developed flux quantification method was successfully tested by flying an unmanned aerial vehicle (UAV) downwind of 22 controlled atmospheric methane releases. The UAVs were used to derive high-precision atmospheric methane measurements. The UAV methodology was successful in both detecting the release and providing a rough flux estimate.
InnFLUX – an open-source code for conventional and disjunct eddy covariance analysis of trace gas measurements: an urban test case
Marcus Striednig, Martin Graus, Tilmann D. Märk, and Thomas G. Karl
Atmos. Meas. Tech., 13, 1447–1465, https://doi.org/10.5194/amt-13-1447-2020, 2020
The current work summarizes a long-term effort to provide an open-source code for the analysis of turbulent fluctuations of trace gases in the atmosphere by eddy covariance and disjunct eddy covariance, with a special focus on reactive gases that participate in atmospheric chemistry. The performance of the code is successfully evaluated based on measurements of minute fluxes of non-methane volatile organic compounds into the urban atmosphere.
The 2018 fire season in North America as seen by TROPOMI: aerosol layer height intercomparisons and evaluation of model-derived plume heights
Debora Griffin, Christopher Sioris, Jack Chen, Nolan Dickson, Andrew Kovachik, Martin de Graaf, Swadhin Nanda, Pepijn Veefkind, Enrico Dammers, Chris A. McLinden, Paul Makar, and Ayodeji Akingunola
Atmos. Meas. Tech., 13, 1427–1445, https://doi.org/10.5194/amt-13-1427-2020, 2020
This study looks into validating the aerosol layer height product from the recently launched TROPOspheric Monitoring Instrument (TROPOMI) for forest fire plume through comparisons with two other satellite products, and interpreting differences due to the individual measurement techniques. These satellite observations are compared to predicted plume heights from Environment and Climate Change's air quality forecast model.
Shipborne MAX-DOAS measurements for validation of TROPOMI NO2 products
Ping Wang, Ankie Piters, Jos van Geffen, Olaf Tuinder, Piet Stammes, and Stefan Kinne
Atmos. Meas. Tech., 13, 1413–1426, https://doi.org/10.5194/amt-13-1413-2020, 2020
The comparison of shipborne MAX-DOAS and TROPOMI NO2 products is important for the evaluation of the TROPOMI products. The ship cruises were mainly over remote oceans, thus we only measured background tropospheric NO2. Stratospheric NO2 was measured more accurately because there was almost no contamination from tropospheric NO2. We found that the TROPOMI stratospheric NO2 vertical column densities were slightly higher than the MAX-DOAS measurements.
Quality controls, bias, and seasonality of CO2 columns in the Boreal Forest with OCO-2, TCCON, and EM27/SUN measurements
Nicole Jacobs, William R. Simpson, Debra Wunch, Christopher W. O'Dell, Gregory B. Osterman, Frank Hase, Thomas Blumenstock, Qiansi Tu, Matthias Frey, Manvendra K. Dubey, Harrison A. Parker, Rigel Kivi, and Pauli Heikkinen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-505,2020
Preprint under review for AMT (discussion: open, 0 comments)
The Boreal forest is the largest seasonally-varying biospheric carbon dioxide exchange region on Earth. This region is also undergoing amplified climate warming leading to concerns about the potential for altered regional carbon exchange. Satellite missions such as the orbiting carbon observer-2 (OCO-2) project can measure CO2 abundance over the Boreal forest, but need validation for assurance of accuracy. Therefore, we carried out ground-based validation of OCO-2 CO2 data at three locations.
