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An instrument for in situ measurement of total ozone reactivity

Atmos.Meas.Tech. discussions - Thu, 04/02/2020 - 18:44
An instrument for in situ measurement of total ozone reactivity
Roberto Sommariva, Louisa J. Kramer, Leigh R. Crilley, Mohammed S. Alam, and William J. Bloss
Atmos. Meas. Tech., 13, 1655–1670, https://doi.org/10.5194/amt-13-1655-2020, 2020
Ozone is a key atmospheric pollutant formed through chemical processing of natural and anthropogenic emissions and removed by reaction with organic compounds emitted by plants. We describe a new instrument – the Total Ozone Reactivity System or TORS – that measures the total loss of ozone in the troposphere. The objective of the TORS instrument is to provide an estimate of the organic compounds emitted by plants which are not measured and thus to improve our understanding of the ozone budget.

Comparison of GTO-ECV and adjusted MERRA-2 total ozone columns from the last 2 decades and assessment of interannual variability

Atmos.Meas.Tech. discussions - Thu, 04/02/2020 - 18:44
Comparison of GTO-ECV and adjusted MERRA-2 total ozone columns from the last 2 decades and assessment of interannual variability
Melanie Coldewey-Egbers, Diego G. Loyola, Gordon Labow, and Stacey M. Frith
Atmos. Meas. Tech., 13, 1633–1654, https://doi.org/10.5194/amt-13-1633-2020, 2020
We compare total ozone columns from the satellite-based GOME-type Total Ozone Essential Climate Variable record and the adjusted Modern Era Retrospective Analysis for Research and Applications version 2 reanalysis during their overlap period from 1995 to 2018. Ozone columns and anomalies show a very good agreement in terms of spatial and temporal patterns. In the tropics the interannual variability is assessed by means of an EOF analysis and both data records show a remarkable consistency.

An LES-based airborne Doppler lidar simulator and its application to wind profiling in inhomogeneous flow conditions

An LES-based airborne Doppler lidar simulator and its application to wind profiling in inhomogeneous flow conditions
Philipp Gasch, Andreas Wieser, Julie K. Lundquist, and Norbert Kalthoff
Atmos. Meas. Tech., 13, 1609–1631, https://doi.org/10.5194/amt-13-1609-2020, 2020
We present an airborne Doppler lidar simulator (ADLS) based on high-resolution atmospheric wind fields (LES). The ADLS is used to evaluate the retrieval accuracy of airborne wind profiling under turbulent, inhomogeneous wind field conditions inside the boundary layer. With the ADLS, the error due to the violation of the wind field homogeneity assumption used for retrieval can be revealed. For the conditions considered, flow inhomogeneities exert a dominant influence on wind profiling error.

Towards objective identification and tracking of convective outflow boundaries in next-generation geostationary satellite imagery

Towards objective identification and tracking of convective outflow boundaries in next-generation geostationary satellite imagery
Jason M. Apke, Kyle A. Hilburn, Steven D. Miller, and David A. Peterson
Atmos. Meas. Tech., 13, 1593–1608, https://doi.org/10.5194/amt-13-1593-2020, 2020
Objective identification of deep convection outflow boundaries (OFBs) in next-generation geostationary satellite imagery is explored here using motion derived from a tuned advanced optical flow algorithm. Motion discontinuity preservation within the derivation is found crucial for successful OFB tracking between images, which yields new meteorological data for objective systems to use. These results provide the first step towards a fully automated satellite-based OFB identification algorithm.

Cloud detection over snow and ice with oxygen A- and B-band observations from the Earth Polychromatic Imaging Camera (EPIC)

Cloud detection over snow and ice with oxygen A- and B-band observations from the Earth Polychromatic Imaging Camera (EPIC)
Yaping Zhou, Yuekui Yang, Meng Gao, and Peng-Wang Zhai
Atmos. Meas. Tech., 13, 1575–1591, https://doi.org/10.5194/amt-13-1575-2020, 2020
Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and the bright and cold surfaces; the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) has very limited channels. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios for cloud detection over snow and ice surfaces.

Distributed observations of wind direction using microstructures attached to actively heated fiber-optic cables

Distributed observations of wind direction using microstructures attached to actively heated fiber-optic cables
Karl Lapo, Anita Freundorfer, Lena Pfister, Johann Schneider, John Selker, and Christoph Thomas
Atmos. Meas. Tech., 13, 1563–1573, https://doi.org/10.5194/amt-13-1563-2020, 2020
Most observations of the atmosphere are point observations, which only measure a small area around the sensor. This limitation creates problems for a number of disciplines, especially those that focus on how the surface and atmosphere exchange heat, mass, and momentum. We used distributed temperature sensing with fiber optics to demonstrate a key breakthrough in observing wind direction in a distributed way, i.e., not at a point, using small structures attached to the fiber-optic cables.

Development of a new nanoparticle sizer equipped with a 12-channel multi-port differential mobility analyzer and multi-condensation particle counters

Development of a new nanoparticle sizer equipped with a 12-channel multi-port differential mobility analyzer and multi-condensation particle counters
Hong Ku Lee, Handol Lee, and Kang-Ho Ahn
Atmos. Meas. Tech., 13, 1551–1562, https://doi.org/10.5194/amt-13-1551-2020, 2020
We developed a nanoparticle sizer (NPS), consisting of a multi-port differential mobility analyzer (MP-DMA) with 12 sampling ports and multi-condensation particle counters (M-CPCs) for fast measurement of particle size distribution. The NPS can successfully capture the changes in particle size distribution under fast-changing particle concentration conditions. In this study, particle emissions from cooking activity are analyzed as an exemplary real-world application.

Cloud detection over snow and ice with oxygen A- and B-band observations from the Earth Polychromatic Imaging Camera (EPIC)

Atmos.Meas.Tech. discussions - Wed, 04/01/2020 - 18:56
Cloud detection over snow and ice with oxygen A- and B-band observations from the Earth Polychromatic Imaging Camera (EPIC)
Yaping Zhou, Yuekui Yang, Meng Gao, and Peng-Wang Zhai
Atmos. Meas. Tech., 13, 1575–1591, https://doi.org/10.5194/amt-13-1575-2020, 2020
Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and the bright and cold surfaces; the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) has very limited channels. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios for cloud detection over snow and ice surfaces.

Distributed observations of wind direction using microstructures attached to actively heated fiber-optic cables

Atmos.Meas.Tech. discussions - Wed, 04/01/2020 - 18:56
Distributed observations of wind direction using microstructures attached to actively heated fiber-optic cables
Karl Lapo, Anita Freundorfer, Lena Pfister, Johann Schneider, John Selker, and Christoph Thomas
Atmos. Meas. Tech., 13, 1563–1573, https://doi.org/10.5194/amt-13-1563-2020, 2020
Most observations of the atmosphere are point observations, which only measure a small area around the sensor. This limitation creates problems for a number of disciplines, especially those that focus on how the surface and atmosphere exchange heat, mass, and momentum. We used distributed temperature sensing with fiber optics to demonstrate a key breakthrough in observing wind direction in a distributed way, i.e., not at a point, using small structures attached to the fiber-optic cables.

Development of a new nanoparticle sizer equipped with a 12-channel multi-port differential mobility analyzer and multi-condensation particle counters

Atmos.Meas.Tech. discussions - Wed, 04/01/2020 - 18:56
Development of a new nanoparticle sizer equipped with a 12-channel multi-port differential mobility analyzer and multi-condensation particle counters
Hong Ku Lee, Handol Lee, and Kang-Ho Ahn
Atmos. Meas. Tech., 13, 1551–1562, https://doi.org/10.5194/amt-13-1551-2020, 2020
We developed a nanoparticle sizer (NPS), consisting of a multi-port differential mobility analyzer (MP-DMA) with 12 sampling ports and multi-condensation particle counters (M-CPCs) for fast measurement of particle size distribution. The NPS can successfully capture the changes in particle size distribution under fast-changing particle concentration conditions. In this study, particle emissions from cooking activity are analyzed as an exemplary real-world application.

Flooding Stunted 2019 Cropland Growing Season, Resulting in More Atmospheric CO2

GeoSpace: Earth & Space Science - Tue, 03/31/2020 - 19:11

By Robert Perkins

Severe flooding throughout the Midwest—which triggered a delayed growing season for crops in the region—led to a reduction of 100 million metric tons of net carbon uptake during June and July of 2019, according to a new study.

For reference, the massive California wildfires of 2018 released an estimated 12.4 million metric tons of carbon into the atmosphere. And although part of this deficit due to floods was compensated for later in the growing season, the combined effects are likely to have resulted in a 15 percent reduction in crop productivity relative to 2018, the study authors say.

The study, published March 31, 2020, in the journal AGU Advances, describes how the carbon uptake was measured using satellite data. Researchers used a novel marker of photosynthesis known as solar-induced fluorescence to quantify the reduced carbon uptake due to the delay in the crops’ growth. Independent observations of atmospheric CO2 levels were then employed to confirm the reduction in carbon uptake.

“We were able to show that it’s possible to monitor the impacts of floods on crop growth on a daily basis in near real time from space, which is critical to future ecological forecasting and mitigation,” says Yi Yin, research scientist at Caltech and lead author of the study.

Record rainfalls soaked the Midwest during the spring and early summer of 2019. For three consecutive months (April, May, and June), the National Oceanic and Atmospheric Administration reported that 12-month precipitation measurements had hit all-time highs. The resulting floods not only damaged homes and infrastructure but also impacted agricultural productivity, delaying the planting of crops in large parts of the Corn Belt, which stretches from Kansas and Nebraska in the west to Ohio in the east.

To assess the environmental impact of the delayed growing season, scientists at Caltech and JPL, which Caltech manages for NASA, turned to satellite data. As plants convert carbon dioxide (CO2) and sunlight into oxygen and energy through photosynthesis, a small amount of the sunlight they absorb is emitted back in the form of a very faint glow. The glow, known as solar-induced fluorescence, or SIF, is far too dim for us to see with bare eyes, but it can be measured through a process called satellite spectrophotometry.

The Caltech-JPL team quantified SIF using measurements from a European Space Agency (ESA) satellite-borne instrument to track the growth of crops with unprecedented detail. They found that the seasonal cycle of the 2019 crop growth was delayed by around two weeks and the maximum seasonal photosynthesis was reduced by about 15 percent. The stunted growing season was estimated to have led to a reduction in carbon uptake by plants of around 100 million metric tons from June to July 2019.

“SIF is the most accurate signal of photosynthesis by far that can be observed from space,” says Christian Frankenberg, professor of environmental science and engineering at Caltech. “And since plants absorb carbon dioxide during photosynthesis, we wanted to see if SIF could track the reductions in crop carbon uptake during the 2019 floods.”

To find out, the team analyzed atmospheric CO2 measurements from NASA’s Orbiting Carbon Observatory-2 (OCO-2) satellite as well as from aircraft from NASA’s Atmospheric Carbon and Transport America (ACT-America) project. “We found that the SIF-based estimates of reduced uptake are consistent with elevated atmospheric CO2 when the two quantities are connected by atmospheric transport models,” says Brendan Bryne, co-corresponding author of the study and a NASA postdoc fellow at JPL.

“This study illuminates our ability to monitor the ecosystem and its impact on atmospheric CO2 in near real time from space. These new tools allow for global sensing of biospheric uptake of carbon dioxide,” says Paul Wennberg, the R. Stanton Avery Professor of Atmospheric Chemistry and Environmental Science and Engineering, director of the Ronald and Maxine Linde Center for Global Environmental Science, and founding member of the Orbiting Carbon Observatory project.

The paper is titled “Cropland carbon uptake delayed and reduced by 2019 Midwest floods.” Co-authors at Caltech include Junjie Liu, visiting associate in environmental science and engineering; Philipp Köhler, research scientist; Liyin He (MS ’18), graduate student; Rupesh Jeyaram, undergraduate student; and Vincent Humphrey, postdoctoral scholar. Other co-authors include Troy Magney of UC Davis; Kenneth J. Davis, Tobias Gerken, and Sha Feng of Pennsylvania State University; and Joshua P. Digangi of NASA. This research was funded by NASA.

This post was originally published on the Caltech website.

The post Flooding Stunted 2019 Cropland Growing Season, Resulting in More Atmospheric CO2 appeared first on GeoSpace.

Ground-based observations of cloud and drizzle liquid water path in stratocumulus clouds

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

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

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

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

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

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

Atmos.Meas.Tech. discussions - Tue, 03/31/2020 - 18:56
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

Atmos.Meas.Tech. discussions - Tue, 03/31/2020 - 18:56
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

Atmos.Meas.Tech. discussions - Tue, 03/31/2020 - 18:56
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.

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