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The influence of the signal-to-noise ratio upon radio occultation inversion quality

The influence of the signal-to-noise ratio upon radio occultation inversion quality
Michael Gorbunov
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2020-114,2020
Preprint under review for AMT (discussion: open, 0 comments)

In this paper, we investigate the influence of the signal-to-noise ratio (SNR) upon the radio occultation (RO) retrieval quality. We perform two series of numerical simulations: (1) with artificial RO data and, (2) with real COSMIC observations. We superimpose the simulated white noise with varying magnitudes upon both types of the observation data and evaluate the response in the statistics. The statistics use the reference fields of the analyses of European Centre for Medium-Range Weather Forecasts (ECMWF). Our simulations indicate that the effect of additive white noise has a threshold character: the influence of the noise is very low up to some threshold, but when the threshold is exceeded, the influence increases dramatically. Another conclusion is that, given RO observations of fair quality, the enhancement of the SNR cannot be expected to provide significant improvement in retrieval quality.

Integrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a Ceilometer and Microwave Radiometer

Integrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a Ceilometer and Microwave Radiometer
Jae-Sik Min, Moon-Soo Park, Jung-Hoon Chae, and Minsoo Kang
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2020-18,2020
Preprint under review for AMT (discussion: open, 0 comments)
An algorithm for an integrated system for ABLH estimation (ISABLE) was developed and applied to the vertical profile data obtained by a ceilometer and a microwave radiometer in Seoul City, Korea. The ISABLE algorithm could find an optimal ABLH from post-processing including k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques. The ABLH determined by ISABLE exhibited better performances than those obtained by most conventional methods.

High-humidity tandem differential mobility analyzer for accurate determination of aerosol hygroscopic growth, microstructure, and activity coefficients over a wide range of relative humidity

Atmos.Meas.Tech. discussions - Wed, 04/22/2020 - 17:54
High-humidity tandem differential mobility analyzer for accurate determination of aerosol hygroscopic growth, microstructure, and activity coefficients over a wide range of relative humidity
Eugene F. Mikhailov and Sergey S. Vlasenko
Atmos. Meas. Tech., 13, 2035–2056, https://doi.org/10.5194/amt-13-2035-2020, 2020
Here we present the high-humidity tandem differential hygroscopicity analyzer (HHTDMA) and a new method to measure the hygroscopic growth of aerosol particles with in situ restructuring to minimize the influence of particle shape. Our results demonstrate that the HHTDMA system described in this work allows us to determine the thermodynamic characteristics of aqueous solutions with an accuracy close to that obtained by bulk methods.

The influence of the signal-to-noise ratio upon radio occultation inversion quality

Atmos.Meas.Tech. discussions - Wed, 04/22/2020 - 17:54
The influence of the signal-to-noise ratio upon radio occultation inversion quality
Michael Gorbunov
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-114,2020
Preprint under review for AMT (discussion: open, 0 comments)

In this paper, we investigate the influence of the signal-to-noise ratio (SNR) upon the radio occultation (RO) retrieval quality. We perform two series of numerical simulations: (1) with artificial RO data and, (2) with real COSMIC observations. We superimpose the simulated white noise with varying magnitudes upon both types of the observation data and evaluate the response in the statistics. The statistics use the reference fields of the analyses of European Centre for Medium-Range Weather Forecasts (ECMWF). Our simulations indicate that the effect of additive white noise has a threshold character: the influence of the noise is very low up to some threshold, but when the threshold is exceeded, the influence increases dramatically. Another conclusion is that, given RO observations of fair quality, the enhancement of the SNR cannot be expected to provide significant improvement in retrieval quality.

Integrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a Ceilometer and Microwave Radiometer

Atmos.Meas.Tech. discussions - Wed, 04/22/2020 - 17:54
Integrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a Ceilometer and Microwave Radiometer
Jae-Sik Min, Moon-Soo Park, Jung-Hoon Chae, and Minsoo Kang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-18,2020
Preprint under review for AMT (discussion: open, 0 comments)
An algorithm for an integrated system for ABLH estimation (ISABLE) was developed and applied to the vertical profile data obtained by a ceilometer and a microwave radiometer in Seoul City, Korea. The ISABLE algorithm could find an optimal ABLH from post-processing including k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques. The ABLH determined by ISABLE exhibited better performances than those obtained by most conventional methods.

South Asia faces increased double-threat of extreme heat, extreme pollution

GeoSpace: Earth & Space Science - Tue, 04/21/2020 - 19:29

By Leslie Lee

Scientists know that extreme heat has a negative impact on the human body — causing distress in the respiratory and cardiovascular systems. They also know that extreme air pollution can also have serious impacts on the human body. But as climate change impacts continue globally, how often will humans be threatened by both of those extremes when they occur simultaneously?

A new study in the AGU journal AGU Advances, answers that question for South Asia.

High‐particulate matter conditions at India Gate. Credit: Adnan Abidi/REUTERS.

“South Asia is a hot-spot for future climate change impacts,” said Yangyang Xu, an atmospheric scientist at Texas A&M University and lead author of the new study. Extreme heat occurrences worldwide have increased in recent decades, and at the same time, many cities are facing severe air pollution problems, featuring episodes of high particulate matter (PM) pollution, he said. This study provides an integrated assessment of human exposure to rare days of both extreme heat and high PM levels.

“Our assessment projects that occurrences of heat extremes will increase in frequency by 75% by 2050, that is an increase from 45 days a year to 78 days in a year,” Xu said. More concerning is the rare joint events of both extreme heat and extreme PM will increase in frequency by 175% by 2050. Climate change is not just a global average number, it is something you can feel in your neighborhood. 

The study’s regional focus was South Asia: Afghanistan, Bangladesh, Bhutan, India, Myanmar, Nepal, and Pakistan. The scientists used a high-resolution, decadal-long model simulation, using a state-of-the-science regional chemistry-climate model. Xu led the first of its kind research project, and scientists from the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, led the development of the fully coupled chemistry-climate model and performed model simulations for the present-day and future conditions.

“These models allow chemistry and climate to affect each other at every time step,” said Rajesh Kumar, a project scientist at NCAR and co-author of the new study. The study was also co-authored by Mary Barth and Gerald A. Meehl, both senior scientists at NCAR, with most of the analysis done by Texas A&M atmospheric sciences graduate student Xiaokang Wu.

As climate change impacts continue to become reality, it is important for scientists to consider human impacts of multiple extreme conditions happening simultaneously, Xu said. Projected increases in humidity and temperature are expected to cause extreme heat stress for the people of South Asia, where the population is projected to increase from 1.5 billion people to 2 billion by 2050.

“It is important to extend this analysis on the co-variability of heat and haze extremes in other regions of the world, such as the industrial regions of the U.S., Europe, and East Asia,” Barth said.

The analysis also showed that the fraction of land exposed to prolonged dual-extreme days increases by more than tenfold in 2050, much larger than the increase when assessed individually.

“I think this study raises a lot of important concerns, and much more research is needed over other parts of the world on these compounded extremes, the risks they pose, and their potential human health effects,” Xu said.

Leslie Lee is the communications coordinator for the College of Geosciences at Texas A&M  University. This post was originally published on the Texas A&M website.

The post South Asia faces increased double-threat of extreme heat, extreme pollution appeared first on GeoSpace.

Sources of error in open-path FTIR measurements of N2O and CO2 emitted from agricultural fields

Atmos.Meas.Tech. discussions - Tue, 04/21/2020 - 18:53
Sources of error in open-path FTIR measurements of N2O and CO2 emitted from agricultural fields
Cheng-Hsien Lin, Richard H. Grant, Albert J. Heber, and Cliff T. Johnston
Atmos. Meas. Tech., 13, 2001–2013, https://doi.org/10.5194/amt-13-2001-2020, 2020
Gas quantification using the open-path Fourier transform infrared spectrometer (OP-FTIR) is subject to interferences of environmental variables, leading to errors in gas concentration calculations. This study investigated the effects of ambient water vapour content, temperature, path lengths, and wind speed on the quantification of N2O and CO2 concentrations, which can help the OP-FTIR users to avoid these errors and improve the precision and accuracy of the atmospheric gas quantification.

Sources of error in open-path FTIR measurements of N2O and CO2 emitted from agricultural fields

Sources of error in open-path FTIR measurements of N2O and CO2 emitted from agricultural fields
Cheng-Hsien Lin, Richard H. Grant, Albert J. Heber, and Cliff T. Johnston
Atmos. Meas. Tech., 13, 2001–2013, https://doi.org/10.5194/amt-13-2001-2020, 2020
Gas quantification using the open-path Fourier transform infrared spectrometer (OP-FTIR) is subject to interferences of environmental variables, leading to errors in gas concentration calculations. This study investigated the effects of ambient water vapour content, temperature, path lengths, and wind speed on the quantification of N2O and CO2 concentrations, which can help the OP-FTIR users to avoid these errors and improve the precision and accuracy of the atmospheric gas quantification.

On the estimation of vertical air velocity and detection of atmospheric turbulence from the ascent rate of balloon soundings

On the estimation of vertical air velocity and detection of atmospheric turbulence from the ascent rate of balloon soundings
Hubert Luce and Hiroyuki Hashiguchi
Atmos. Meas. Tech., 13, 1989–1999, https://doi.org/10.5194/amt-13-1989-2020, 2020
Vertical ascent rate Vb of meteorological balloons is sometimes used for retrieving vertical air velocity, an important parameter for meteorological applications. Comparisons with concurrent radar and unmanned aerial vehicle (UAV) measurements of atmospheric turbulence showed that Vb can be increased in turbulent layers due to the probable decrease in the drag coefficient of the balloon. We conclude that Vb can also potentially be used for the detection of atmospheric turbulence.

Characterization and first results from LACIS-T: a moist-air wind tunnel to study aerosol–cloud–turbulence interactions

Characterization and first results from LACIS-T: a moist-air wind tunnel to study aerosol–cloud–turbulence interactions
Dennis Niedermeier, Jens Voigtländer, Silvio Schmalfuß, Daniel Busch, Jörg Schumacher, Raymond A. Shaw, and Frank Stratmann
Atmos. Meas. Tech., 13, 2015–2033, https://doi.org/10.5194/amt-13-2015-2020, 2020
In this paper, we present the new moist-air wind tunnel LACIS-T (Turbulent Leipzig Aerosol Cloud Interaction Simulator). It is used to study cloud physical processes in general and interactions between turbulence and cloud microphysical processes in particular. The operating principle of LACIS-T is explained, and the first results are depicted from deliquescence and droplet formation experiments observing clear indications on the effect of turbulence on these microphysical processes.

Evaluation of the reflectivity calibration of W-band radars based on observations in rain

Evaluation of the reflectivity calibration of W-band radars based on observations in rain
Alexander Myagkov, Stefan Kneifel, and Thomas Rose
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2020-133,2020
Preprint under review for AMT (discussion: open, 0 comments)
This study shows two methods to evaluate the reflectivity calibration of W-band cloud radars. Both methods use natural rain as a reference target. The first method is based on spectral polarimetric observations and requires a polarimetric cloud radar with a scanner. The second method utilizes disdrometer observations and can be applied to scanning and vertically pointed radars. Both methods show consistent results and can be applied for the operational monitoring of the measurement quality.

On the estimation of vertical air velocity and detection of atmospheric turbulence from the ascent rate of balloon soundings

Atmos.Meas.Tech. discussions - Tue, 04/21/2020 - 18:43
On the estimation of vertical air velocity and detection of atmospheric turbulence from the ascent rate of balloon soundings
Hubert Luce and Hiroyuki Hashiguchi
Atmos. Meas. Tech., 13, 1989–1999, https://doi.org/10.5194/amt-13-1989-2020, 2020
Vertical ascent rate Vb of meteorological balloons is sometimes used for retrieving vertical air velocity, an important parameter for meteorological applications. Comparisons with concurrent radar and unmanned aerial vehicle (UAV) measurements of atmospheric turbulence showed that Vb can be increased in turbulent layers due to the probable decrease in the drag coefficient of the balloon. We conclude that Vb can also potentially be used for the detection of atmospheric turbulence.

Characterization and first results from LACIS-T: a moist-air wind tunnel to study aerosol–cloud–turbulence interactions

Atmos.Meas.Tech. discussions - Tue, 04/21/2020 - 18:43
Characterization and first results from LACIS-T: a moist-air wind tunnel to study aerosol–cloud–turbulence interactions
Dennis Niedermeier, Jens Voigtländer, Silvio Schmalfuß, Daniel Busch, Jörg Schumacher, Raymond A. Shaw, and Frank Stratmann
Atmos. Meas. Tech., 13, 2015–2033, https://doi.org/10.5194/amt-13-2015-2020, 2020
In this paper, we present the new moist-air wind tunnel LACIS-T (Turbulent Leipzig Aerosol Cloud Interaction Simulator). It is used to study cloud physical processes in general and interactions between turbulence and cloud microphysical processes in particular. The operating principle of LACIS-T is explained, and the first results are depicted from deliquescence and droplet formation experiments observing clear indications on the effect of turbulence on these microphysical processes.

Evaluation of the reflectivity calibration of W-band radars based on observations in rain

Atmos.Meas.Tech. discussions - Tue, 04/21/2020 - 18:43
Evaluation of the reflectivity calibration of W-band radars based on observations in rain
Alexander Myagkov, Stefan Kneifel, and Thomas Rose
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-133,2020
Preprint under review for AMT (discussion: open, 0 comments)
This study shows two methods to evaluate the reflectivity calibration of W-band cloud radars. Both methods use natural rain as a reference target. The first method is based on spectral polarimetric observations and requires a polarimetric cloud radar with a scanner. The second method utilizes disdrometer observations and can be applied to scanning and vertically pointed radars. Both methods show consistent results and can be applied for the operational monitoring of the measurement quality.

Continued carbon dioxide emissions will impair human cognition

GeoSpace: Earth & Space Science - Tue, 04/21/2020 - 14:33

As the 21st century progresses, rising atmospheric carbon dioxide (CO2) concentrations will cause urban and indoor levels of the gas to increase, and that may significantly reduce our basic decision-making ability and complex strategic thinking, according to a new study. By the end of the century, people could be exposed to indoor CO2 levels up to 1,400 parts per million (ppm)—more than three times today’s outdoor levels, and well beyond what humans have ever experienced.

“It’s amazing how high CO2 levels get in enclosed spaces,” said climate researcher Kris Karnauskas, lead author of the new study published in the AGU journal GeoHealth. “It affects everybody—from little kids packed into classrooms to scientists, business people and decision-makers to regular folks in their houses and apartments.” Karnauskas is an associate professor at the University of Colorado Boulder (CU Boulder) and a fellow at the Cooperative Institute for Research in Environmental Sciences (CIRES).

“Building ventilation typically modulates CO2 levels in buildings, but there are situations when there are too many people and not enough fresh air to dilute the CO2,” said Shelly Miller, professor in CU Boulder’s school of engineering and coauthor of the new study. Carbon dioxide can also build up in poorly ventilated spaces over longer periods of time, such as overnight while sleeping in bedrooms, she said.

Put simply, when we breathe air with high CO2 levels, the CO2 levels in our blood rise, reducing the amount of oxygen that reaches our brains. Studies show that this can increase sleepiness and anxiety, and impair cognitive function.

Rising CO2 levels in outdoor air can cause indoor air in crowded spaces to reach levels that impair cognitive ability. Credit: AGU.

We all know the feeling: Sit too long in a stuffy, crowded lecture hall or conference room and many of us begin to feel drowsy or dull. In general, CO2 concentrations are higher indoors than outdoors, the authors wrote. And outdoor CO2 in urban areas is higher than in pristine locations. The CO2 concentrations in buildings are a result of both the gas that is otherwise in equilibrium with the outdoors, but also the CO2 generated by building occupants as they exhale.

Atmospheric CO2 levels have been rising since the Industrial Revolution, reaching a 414 ppm peak at NOAA’s Mauna Loa Observatory in Hawaii in 2019. In the ongoing scenario in which people on Earth do not reduce greenhouse gas emissions, the Intergovernmental Panel on Climate Change predicts outdoor CO2 levels could climb to 930 ppm by 2100. And urban areas typically have around 100 ppm CO2 higher than this background.

Karnauskas and his colleagues developed a comprehensive approach that considers predicted future outdoor CO2 concentrations and the impact of localized urban emissions, a model of the relationship between indoor and outdoor CO2 levels and the impact on human cognition. They found that if the outdoor CO2 concentrations do rise to 930 ppm, that would nudge the indoor concentrations to a harmful level of 1,400 ppm.

“At this level, some studies have demonstrated compelling evidence for significant cognitive impairment,” said Anna Schapiro, assistant professor of psychology at the University of Pennsylvania and a coauthor of the new study. “Though the literature contains some conflicting findings and much more research is needed, it appears that high-level cognitive domains like decision-making and planning are especially susceptible to increasing CO2 concentrations.”

In fact, at 1,400 ppm, CO2 concentrations may cut our basic decision-making ability by 25 percent, and complex strategic thinking by around 50 percent, the authors found.

The cognitive impacts of rising CO2 levels represent what scientists call a “direct” effect of the gas’ concentration, much like ocean acidification. In both cases, elevated CO2 itself—not the subsequent warming it also causes—is what triggers harm.

The team says there may be ways to adapt to higher indoor CO2 levels, but the best way to prevent levels from reaching harmful levels is to reduce fossil fuel emissions. This would require globally adopted mitigation strategies such as those set forth by the Paris Agreement of the United Nations Framework Convention on Climate Change.

Karnauskas and his coauthors hope these findings will spark further research on the ‘hidden’ impacts of climate change such as those on cognition. “This is a complex problem, and our study is at the beginning. It’s not just a matter of predicting global (outdoor) CO2 levels,” he said. “It’s going from the global background emissions to concentrations in the urban environment, to the indoor concentrations, and finally the resulting human impact. We need even broader, interdisciplinary teams of researchers to explore this: investigating each step in our own silos will not be enough.”

This post was originally published on the CIRES website.

The post Continued carbon dioxide emissions will impair human cognition appeared first on GeoSpace.

Calibration of global MODIS cloud amount using CALIOP cloud profiles

Calibration of global MODIS cloud amount using CALIOP cloud profiles
Andrzej Z. Kotarba
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2020-111,2020
Preprint under review for AMT (discussion: open, 2 comments)
Paper evaluates the operational approach for producing global (Level3 product) cloud amount based on MODIS cloud masks (Level2). Using CALIPSO we calculate the actual cloud fractions for each cloud mask category, which are 21.5 %, 27.7 %, 66.6 %, and 94.7 % instead of assumed 0 %, 0 %, 100 % and 100 %. Consequently we find the operational procedure unreliable, especially on a regional/ local scale. A methods is suggested how to correct/calibrate MODIS global data using CALIPSO detections.

Calibration of global MODIS cloud amount using CALIOP cloud profiles

Atmos.Meas.Tech. discussions - Mon, 04/20/2020 - 18:43
Calibration of global MODIS cloud amount using CALIOP cloud profiles
Andrzej Z. Kotarba
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-111,2020
Preprint under review for AMT (discussion: open, 2 comments)
Paper evaluates the operational approach for producing global (Level3 product) cloud amount based on MODIS cloud masks (Level2). Using CALIPSO we calculate the actual cloud fractions for each cloud mask category, which are 21.5 %, 27.7 %, 66.6 %, and 94.7 % instead of assumed 0 %, 0 %, 100 % and 100 %. Consequently we find the operational procedure unreliable, especially on a regional/ local scale. A methods is suggested how to correct/calibrate MODIS global data using CALIPSO detections.

Studying boundary layer methane isotopy and vertical mixing processes at a rewetted peatland site using an unmanned aircraft system

Atmos.Meas.Tech. discussions - Fri, 04/17/2020 - 19:02
Studying boundary layer methane isotopy and vertical mixing processes at a rewetted peatland site using an unmanned aircraft system
Astrid Lampert, Falk Pätzold, Magnus O. Asmussen, Lennart Lobitz, Thomas Krüger, Thomas Rausch, Torsten Sachs, Christian Wille, Denis Sotomayor Zakharov, Dominik Gaus, Stephan Bansmer, and Ellen Damm
Atmos. Meas. Tech., 13, 1937–1952, https://doi.org/10.5194/amt-13-1937-2020, 2020
Methane has high climate warming potential. Sources of methane can be distinguished by the isotopic composition. To investigate the origin of methane, an airborne sampling system has been developed that can take air samples worldwide and at various altitudes. The article shows the performance of the overall system, from taking samples to laboratory analyses. As known methane source, a rewetted peatland site, was studied, and the vertical distribution of the isotopic composition is investigated.

SegCloud: a novel cloud image segmentation model using a deep convolutional neural network for ground-based all-sky-view camera observation

Atmos.Meas.Tech. discussions - Fri, 04/17/2020 - 19:02
SegCloud: a novel cloud image segmentation model using a deep convolutional neural network for ground-based all-sky-view camera observation
Wanyi Xie, Dong Liu, Ming Yang, Shaoqing Chen, Benge Wang, Zhenzhu Wang, Yingwei Xia, Yong Liu, Yiren Wang, and Chaofang Zhang
Atmos. Meas. Tech., 13, 1953–1961, https://doi.org/10.5194/amt-13-1953-2020, 2020

Cloud detection and cloud properties have substantial applications in weather forecast, signal attenuation analysis, and other cloud-related fields. Cloud image segmentation is the fundamental and important step in deriving cloud cover. However, traditional segmentation methods rely on low-level visual features of clouds and often fail to achieve satisfactory performance. Deep convolutional neural networks (CNNs) can extract high-level feature information of objects and have achieved remarkable success in many image segmentation fields. On this basis, a novel deep CNN model named SegCloud is proposed and applied for accurate cloud segmentation based on ground-based observation. Architecturally, SegCloud possesses a symmetric encoder–decoder structure. The encoder network combines low-level cloud features to form high-level, low-resolution cloud feature maps, whereas the decoder network restores the obtained high-level cloud feature maps to the same resolution of input images. The Softmax classifier finally achieves pixel-wise classification and outputs segmentation results. SegCloud has powerful cloud discrimination capability and can automatically segment whole-sky images obtained by a ground-based all-sky-view camera. The performance of SegCloud is validated by extensive experiments, which show that SegCloud is effective and accurate for ground-based cloud segmentation and achieves better results than traditional methods do. The accuracy and practicability of SegCloud are further proven by applying it to cloud cover estimation.

Studying boundary layer methane isotopy and vertical mixing processes at a rewetted peatland site using an unmanned aircraft system

Studying boundary layer methane isotopy and vertical mixing processes at a rewetted peatland site using an unmanned aircraft system
Astrid Lampert, Falk Pätzold, Magnus O. Asmussen, Lennart Lobitz, Thomas Krüger, Thomas Rausch, Torsten Sachs, Christian Wille, Denis Sotomayor Zakharov, Dominik Gaus, Stephan Bansmer, and Ellen Damm
Atmos. Meas. Tech., 13, 1937–1952, https://doi.org/10.5194/amt-13-1937-2020, 2020
Methane has high climate warming potential. Sources of methane can be distinguished by the isotopic composition. To investigate the origin of methane, an airborne sampling system has been developed that can take air samples worldwide and at various altitudes. The article shows the performance of the overall system, from taking samples to laboratory analyses. As known methane source, a rewetted peatland site, was studied, and the vertical distribution of the isotopic composition is investigated.

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