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Atmospheric Measurement Techniques
An interactive open-access journal of the European Geosciences Union
Journal topic
- About
- Editorial board
- Articles
- Special issues
- Highlight articles
- Manuscript tracking
- Subscribe to alerts
- Peer review
- For authors
- For reviewers
- EGU publications
- Imprint
- Data protection
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IF 3.400
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index 70h5-index 49
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Abstracted/indexed
AMT | Articles | Volume 12, issue 3
Atmos. Meas. Tech., 12, 1755–1766, 2019
https://doi.org/10.5194/amt-12-1755-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-12-1755-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 12, 1755–1766, 2019
https://doi.org/10.5194/amt-12-1755-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-12-1755-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article 18 Mar 2019
Research article | 18 Mar 2019
Albedo-Ice Regression method for determining ice water content of polar mesospheric clouds using ultraviolet observations from space
Gary E. Thomas et al.Related authors
Matthew T. DeLand and Gary E. Thomas
Atmos. Chem. Phys., 19, 7913–7925, https://doi.org/10.5194/acp-19-7913-2019, https://doi.org/10.5194/acp-19-7913-2019, 2019
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We have extended our 40-year satellite data record of polar mesospheric cloud (PMC) behavior by adding data from a new instrument. Long-term trends in PMC ice water content derived from this record are smaller since 1998 compared to the first part of our data record. The PMC response to solar activity has decreased in the Northern Hemisphere but increased in the Southern Hemisphere, for reasons that are not understood.
Lina Broman, Susanne Benze, Jörg Gumbel, Ole Martin Christensen, and Cora E. Randall
Atmos. Chem. Phys., 19, 12455–12475, https://doi.org/10.5194/acp-19-12455-2019, https://doi.org/10.5194/acp-19-12455-2019, 2019
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Combining satellite observations of polar mesospheric clouds are complicated due to satellite geometry and measurement technique. In this study, tomographic limb observations are compared to observations from a nadir-viewing satellite using a common volume approach. We present a technique that overcomes differences in scattering conditions and observation geometry. The satellites show excellent agreement, which lays the basis for future insights into horizontal and vertical cloud processes.
Matthew T. DeLand and Gary E. Thomas
Atmos. Chem. Phys., 19, 7913–7925, https://doi.org/10.5194/acp-19-7913-2019, https://doi.org/10.5194/acp-19-7913-2019, 2019
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We have extended our 40-year satellite data record of polar mesospheric cloud (PMC) behavior by adding data from a new instrument. Long-term trends in PMC ice water content derived from this record are smaller since 1998 compared to the first part of our data record. The PMC response to solar activity has decreased in the Northern Hemisphere but increased in the Southern Hemisphere, for reasons that are not understood.
Mark E. Hervig, Benjamin T. Marshall, Scott M. Bailey, David E. Siskind, James M. Russell III, Charles G. Bardeen, Kaley A. Walker, and Bernd Funke
Atmos. Meas. Tech., 12, 3111–3121, https://doi.org/10.5194/amt-12-3111-2019, https://doi.org/10.5194/amt-12-3111-2019, 2019
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The Solar Occultation for Ice Experiment (SOFIE) has measured nitric oxide (NO) from satellite since 2007. The observations are validated through error analysis and comparisons with other satellite observations. Calculated SOFIE NO uncertainties are less than 50 % for altitudes from 40 to 140 km. SOFIE agrees with other measurements to within 50 % for altitudes from roughly 50 to 105 km for spacecraft sunrise and 50 to 140 km for sunsets.
Pingping Rong, Jia Yue, James M. Russell III, David E. Siskind, and Cora E. Randall
Atmos. Chem. Phys., 18, 883–899, https://doi.org/10.5194/acp-18-883-2018, https://doi.org/10.5194/acp-18-883-2018, 2018
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There is a massive manifestation of atmospheric gravity waves (GWs) in polar mesospheric clouds (PMCs) at the summer mesopause, which serves as indicators of the atmospheric dynamics and climate change. We obtained a universal power law that governs the GW display morphology and clarity level throughout the wave population residing in PMCs. Higher clarity refers to more distinct exhibition of the features. A GW tracking algorithm is used to identify the waves and to sort the albedo power.
Bernd Funke, William Ball, Stefan Bender, Angela Gardini, V. Lynn Harvey, Alyn Lambert, Manuel López-Puertas, Daniel R. Marsh, Katharina Meraner, Holger Nieder, Sanna-Mari Päivärinta, Kristell Pérot, Cora E. Randall, Thomas Reddmann, Eugene Rozanov, Hauke Schmidt, Annika Seppälä, Miriam Sinnhuber, Timofei Sukhodolov, Gabriele P. Stiller, Natalia D. Tsvetkova, Pekka T. Verronen, Stefan Versick, Thomas von Clarmann, Kaley A. Walker, and Vladimir Yushkov
Atmos. Chem. Phys., 17, 3573–3604, https://doi.org/10.5194/acp-17-3573-2017, https://doi.org/10.5194/acp-17-3573-2017, 2017
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Simulations from eight atmospheric models have been compared to tracer and temperature observations from seven satellite instruments in order to evaluate the energetic particle indirect effect (EPP IE) during the perturbed northern hemispheric (NH) winter 2008/2009. Models are capable to reproduce the EPP IE in dynamically and geomagnetically quiescent NH winter conditions. The results emphasize the need for model improvements in the dynamical representation of elevated stratopause events.
Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, Chris A. McLinden, Peter F. Bernath, Adam E. Bourassa, John P. Burrows, Doug A. Degenstein, Bernd Funke, Didier Fussen, Gloria L. Manney, C. Thomas McElroy, Donal Murtagh, Cora E. Randall, Piera Raspollini, Alexei Rozanov, James M. Russell III, Makoto Suzuki, Masato Shiotani, Joachim Urban, Thomas von Clarmann, and Joseph M. Zawodny
Atmos. Meas. Tech., 9, 5781–5810, https://doi.org/10.5194/amt-9-5781-2016, https://doi.org/10.5194/amt-9-5781-2016, 2016
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This study validates version 3.5 of the ACE-FTS NOy species data sets by comparing diurnally scaled ACE-FTS data to correlative data from 11 other satellite limb sounders. For all five species examined (NO, NO2, HNO3, N2O5, and ClONO2), there is good agreement between ACE-FTS and the other data sets in various regions of the atmosphere. In these validated regions, these NOy data products can be used for further investigation into the composition, dynamics, and climate of the stratosphere.
Owen B. Toon, Charles Bardeen, and Rolando Garcia
Atmos. Chem. Phys., 16, 13185–13212, https://doi.org/10.5194/acp-16-13185-2016, https://doi.org/10.5194/acp-16-13185-2016, 2016
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About 66 million years ago, a large fraction of the planet's species, including the non-avian dinosaurs, vanished when an asteroid hit the Yucatan Peninsula, likely triggering the largest short-term climate change in geologic history. Yet there have been no modern simulations of this climate change. We outline the initial conditions needed for such global climate simulations. There is much unknown about the aftermath of the impact. We discuss uncertainties and suggest new observations.
David E. Siskind, Gerald E. Nedoluha, Fabrizio Sassi, Pingping Rong, Scott M. Bailey, Mark E. Hervig, and Cora E. Randall
Atmos. Chem. Phys., 16, 7957–7967, https://doi.org/10.5194/acp-16-7957-2016, https://doi.org/10.5194/acp-16-7957-2016, 2016
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The strong descent of wintertime mesospheric air into the stratosphere has been of great recent interest. Here, we show that because mesospheric air is depleted in methane, it implies that chlorine will be found more in its active form, chlorine monoxide. This is a new way for mesosphere/stratosphere coupling to affect ozone. Second, these effects seem to persist longer than previously thought. Studies of the summer upper stratosphere should consider the conditions from the previous winter.
Steven T. Massie, Julien Delanoë, Charles G. Bardeen, Jonathan H. Jiang, and Lei Huang
Atmos. Chem. Phys., 16, 6091–6105, https://doi.org/10.5194/acp-16-6091-2016, https://doi.org/10.5194/acp-16-6091-2016, 2016
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Changes in cloud vertical structure (i.e. the shape of cloud ice water content (IWC) vertical structure) due to variations in aerosol, observed by three different satellite experiments (MODIS, OMI, and MLS) are calculated in the Tropics during 2007–2010. This topic is of interest because aerosol-cloud interactions are the largest source of uncertainty in climate models. Analysis of the effects of MODIS aerosol, OMI absorptive aerosol, and MLS CO (an absorptive aerosol proxy) upon deep convective
A. Laeng, U. Grabowski, T. von Clarmann, G. Stiller, N. Glatthor, M. Höpfner, S. Kellmann, M. Kiefer, A. Linden, S. Lossow, V. Sofieva, I. Petropavlovskikh, D. Hubert, T. Bathgate, P. Bernath, C. D. Boone, C. Clerbaux, P. Coheur, R. Damadeo, D. Degenstein, S. Frith, L. Froidevaux, J. Gille, K. Hoppel, M. McHugh, Y. Kasai, J. Lumpe, N. Rahpoe, G. Toon, T. Sano, M. Suzuki, J. Tamminen, J. Urban, K. Walker, M. Weber, and J. Zawodny
Atmos. Meas. Tech., 7, 3971–3987, https://doi.org/10.5194/amt-7-3971-2014, https://doi.org/10.5194/amt-7-3971-2014, 2014
C. H. Jackman, C. E. Randall, V. L. Harvey, S. Wang, E. L. Fleming, M. López-Puertas, B. Funke, and P. F. Bernath
Atmos. Chem. Phys., 14, 1025–1038, https://doi.org/10.5194/acp-14-1025-2014, https://doi.org/10.5194/acp-14-1025-2014, 2014
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
A new approach to estimate supersaturation fluctuations in stratocumulus cloud using ground-based remote-sensing measurements
ELIFAN, an algorithm for the estimation of cloud cover from sky imagers
Estimating solar irradiance using sky imagers
Toward autonomous surface-based infrared remote sensing of polar clouds: retrievals of cloud optical and microphysical properties
Use of spectral cloud emissivities and their related uncertainties to infer ice cloud boundaries: methodology and assessment using CALIPSO cloud products
The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow
Calibration of the 2007–2017 record of Atmospheric Radiation Measurements cloud radar observations using CloudSat
All-sky assimilation of infrared radiances sensitive to mid- and upper-tropospheric moisture and cloud
peakTree: a framework for structure-preserving radar Doppler spectra analysis
Development and validation of a supervised machine learning radar Doppler spectra peak-finding algorithm
Footprint-scale cloud type mixtures and their impacts on Atmospheric Infrared Sounder cloud property retrievals
Retrieval of cloud properties from sky radiometer observed spectral zenith radiances
Estimation of liquid water path below the melting layer in stratiform precipitation systems using radar measurements during MC3E
Correlated observation error models for assimilating all-sky infrared radiances
Cloud identification and classification from high spectral resolution data in the far infrared and mid-infrared
Investigating the liquid water path over the tropical Atlantic with synergistic airborne measurements
Homogeneity criteria from AVHRR information within IASI pixels in a numerical weather prediction context
Sensitivity of liquid cloud optical thickness and effective radius retrievals to cloud bow and glory conditions using two SEVIRI imagers
Evolution of DARDAR-CLOUD ice cloud retrievals: new parameters and impacts on the retrieved microphysical properties
Ice crystal number concentration from measurements of lidar, cloud radar and radar wind profiler
FRESCO-B: a fast cloud retrieval algorithm using oxygen B-band measurements from GOME-2
Application of high-dimensional fuzzy k-means cluster analysis to CALIOP/CALIPSO version 4.1 cloud–aerosol discrimination
Cloud products from the Earth Polychromatic Imaging Camera (EPIC): algorithms and initial evaluation
Cloud base height retrieval from multi-angle satellite data
Retrieval of liquid water cloud properties from POLDER-3 measurements using a neural network ensemble approach
Marine liquid cloud geometric thickness retrieved from OCO-2's oxygen A-band spectrometer
An algorithm to retrieve ice water content profiles in cirrus clouds from the synergy of ground-based lidar and thermal infrared radiometer measurements
Detecting cloud contamination in passive microwave satellite measurements over land
Cloud geometry from oxygen-A-band observations through an aircraft side window
Remote sensing of cloud droplet radius profiles using solar reflectance from cloud sides – Part 1: Retrieval development and characterization
A cloud identification algorithm over the Arctic for use with AATSR–SLSTR measurements
X-band dual-polarization radar-based hydrometeor classification for Brazilian tropical precipitation systems
Discriminating between clouds and aerosols in the CALIOP version 4.1 data products
A high-level cloud detection method utilizing the GOSAT TANSO-FTS water vapor saturated band
CALIPSO lidar calibration at 1064 nm: version 4 algorithm
Boundary-layer water vapor profiling using differential absorption radar
CALIPSO lidar calibration at 532 nm: version 4 daytime algorithm
The MIPAS/Envisat climatology (2002–2012) of polar stratospheric cloud volume density profiles
Extinction and optical depth retrievals for CALIPSO's Version 4 data release
First fully diurnal fog and low cloud satellite detection reveals life cycle in the Namib
Cloud classification of ground-based infrared images combining manifold and texture features
Clutter mitigation, multiple peaks, and high-order spectral moments in 35 GHz vertically pointing radar velocity spectra
A neural network approach to estimating a posteriori distributions of Bayesian retrieval problems
Parameterizing cloud top effective radii from satellite retrieved values, accounting for vertical photon transport: quantification and correction of the resulting bias in droplet concentration and liquid water path retrievals
All-sky information content analysis for novel passive microwave instruments in the range from 23.8 to 874.4 GHz
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
Comparisons of bispectral and polarimetric retrievals of marine boundary layer cloud microphysics: case studies using a LES–satellite retrieval simulator
The Community Cloud retrieval for CLimate (CC4CL) – Part 1: A framework applied to multiple satellite imaging sensors
The Community Cloud retrieval for CLimate (CC4CL) – Part 2: The optimal estimation approach
High-dynamic-range imaging for cloud segmentation
Fan Yang, Robert McGraw, Edward P. Luke, Damao Zhang, Pavlos Kollias, and Andrew M. Vogelmann
Atmos. Meas. Tech., 12, 5817–5828, https://doi.org/10.5194/amt-12-5817-2019, https://doi.org/10.5194/amt-12-5817-2019, 2019
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In-cloud supersaturation is crucial for droplet activation, growth, and drizzle initiation but is poorly known and hardly measured. Here we provide a novel method to estimate supersaturation fluctuation in stratocumulus clouds using remote-sensing measurements, and results show that our estimated supersaturation agrees reasonably well with in situ measurements. Our method provides a unique way to estimate supersaturation in stratocumulus clouds from long-term ground-based observations.
Marie Lothon, Paul Barnéoud, Omar Gabella, Fabienne Lohou, Solène Derrien, Sylvain Rondi, Marjolaine Chiriaco, Sophie Bastin, Jean-Charles Dupont, Martial Haeffelin, Jordi Badosa, Nicolas Pascal, and Nadège Montoux
Atmos. Meas. Tech., 12, 5519–5534, https://doi.org/10.5194/amt-12-5519-2019, https://doi.org/10.5194/amt-12-5519-2019, 2019
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In the context of an atmospheric network of instrumented sites equipped with sky cameras for cloud monitoring, we present an algorithm named ELIFAN, which aims to estimate the cloud cover amount from full-sky visible daytime images. ELIFAN is based on red-to-blue ratio thresholding applied on the image pixels and on the use of a blue-sky library. We present its principle and its performance and highlight the interest of combining several complementary instruments.
Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee, and Stefan Winkler
Atmos. Meas. Tech., 12, 5417–5429, https://doi.org/10.5194/amt-12-5417-2019, https://doi.org/10.5194/amt-12-5417-2019, 2019
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Ground-based whole-sky cameras are now extensively used for the localized monitoring of clouds. In this paper, we derive a model for estimating solar irradiance using the pictures taken by those imagers. Unlike pyranometers, these sky images contain information about cloud coverage and can be used to derive cloud movement. An accurate estimation of solar irradiance using solely those images is thus a first step towards short-term solar energy generation forecasting.
Penny M. Rowe, Christopher J. Cox, Steven Neshyba, and Von P. Walden
Atmos. Meas. Tech., 12, 5071–5086, https://doi.org/10.5194/amt-12-5071-2019, https://doi.org/10.5194/amt-12-5071-2019, 2019
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A better understanding of polar clouds is needed for predicting climate change, including cloud thickness and the sizes and amounts of liquid droplets and ice crystals. These properties can be estimated from an instrument (an infrared spectrometer) that sits on the surface and measures how much infrared radiation is emitted by the cloud. In this work we use model data to investigate how well such an instrument could retrieve cloud properties for different instrument and error characteristics.
Hye-Sil Kim, Bryan A. Baum, and Yong-Sang Choi
Atmos. Meas. Tech., 12, 5039–5054, https://doi.org/10.5194/amt-12-5039-2019, https://doi.org/10.5194/amt-12-5039-2019, 2019
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This study demonstrates that ice cloud emissivity uncertainties at 11, 12, and 13.3 µm can be used to provide a reasonable range of ice cloud layer boundaries. We test this methodology using MODIS Collection 6 cloud properties over the western North Pacific Ocean during August 2015. The cloud boundaries for single-layer optically thin ice clouds show good agreement with those from CALIOP version 4 products, with biases increasing for optically thick and multilayered clouds.
Shannon L. Mason, Robin J. Hogan, Christopher D. Westbrook, Stefan Kneifel, Dmitri Moisseev, and Leonie von Terzi
Atmos. Meas. Tech., 12, 4993–5018, https://doi.org/10.5194/amt-12-4993-2019, https://doi.org/10.5194/amt-12-4993-2019, 2019
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The mass contents of snowflakes are critical to remotely sensed estimates of snowfall. The signatures of snow measured at three radar frequencies can distinguish fluffy, fractal snowflakes from dense and more homogeneous rimed snow. However, we show that the shape of the particle size spectrum also has a significant impact on triple-frequency radar signatures and must be accounted for when making triple-frequency radar estimates of snow that include variations in particle structure and density.
Pavlos Kollias, Bernat Puigdomènech Treserras, and Alain Protat
Atmos. Meas. Tech., 12, 4949–4964, https://doi.org/10.5194/amt-12-4949-2019, https://doi.org/10.5194/amt-12-4949-2019, 2019
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Profiling millimeter-wavelength radars are the cornerstone instrument of surface-based observatories. Calibrating these radars is important for establishing a long record of observations suitable for model evaluation and improvement. Here, the CloudSat CPR is used to assess the calibration of a record over 10 years long of ARM cloud radar observations (a total of 44 years). The results indicate that correction coefficients are needed to improve record reliability and usability.
Alan J. Geer, Stefano Migliorini, and Marco Matricardi
Atmos. Meas. Tech., 12, 4903–4929, https://doi.org/10.5194/amt-12-4903-2019, https://doi.org/10.5194/amt-12-4903-2019, 2019
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Satellite radiance observations have only recently become usable in conditions of cloud and precipitation for the initialization of weather forecasts. The move to
all-skyassimilation started with data from the microwave part of the spectrum, with substantial benefit to the quality of operational forecasts. The current work shows a framework in which cloudy infrared data, with its stronger and more non-linear sensitivity, can also benefit operational-quality forecasts.
Martin Radenz, Johannes Bühl, Patric Seifert, Hannes Griesche, and Ronny Engelmann
Atmos. Meas. Tech., 12, 4813–4828, https://doi.org/10.5194/amt-12-4813-2019, https://doi.org/10.5194/amt-12-4813-2019, 2019
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Clouds may be composed of more than one particle population even at the smallest scales. Cloud radar observations can contain information on multiple particle species, showing up as distinct peaks and subpeaks in the Doppler spectrum. We propose the use of binary tree structures to recursively structure these peaks. Two case studies from different locations and instruments illustrate how this approach can be used to disentangle particle populations in multilayered mixed-phase clouds.
Heike Kalesse, Teresa Vogl, Cosmin Paduraru, and Edward Luke
Atmos. Meas. Tech., 12, 4591–4617, https://doi.org/10.5194/amt-12-4591-2019, https://doi.org/10.5194/amt-12-4591-2019, 2019
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In a cloud, different particles like liquid water droplets and ice particles can exist simultaneously. To study the evolution of cloud particles from cloud top to bottom one has to find out how many different types of particles with different fall velocities are present. This can be done by analyzing the number of peaks in upward-looking cloud radar Doppler spectra. A new machine-learning algorithm (named PEAKO) that determines the number of peaks is introduced and compared to existing methods.
Alexandre Guillaume, Brian H. Kahn, Eric J. Fetzer, Qing Yue, Gerald J. Manipon, Brian D. Wilson, and Hook Hua
Atmos. Meas. Tech., 12, 4361–4377, https://doi.org/10.5194/amt-12-4361-2019, https://doi.org/10.5194/amt-12-4361-2019, 2019
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A method is described to classify cloud mixtures of cloud top types, termed cloud scenes, using cloud type classification derived from the CloudSat radar. The scale dependence of the cloud scenes is quantified. The cloud scenes are used to assess the characteristics of spatially collocated Atmospheric Infrared Sounder (AIRS) thermodynamic-phase and ice cloud property retrievals within scenes of varying cloud type complexity.
Pradeep Khatri, Hironobu Iwabuchi, Tadahiro Hayasaka, Hitoshi Irie, Tamio Takamura, Akihiro Yamazaki, Alessandro Damiani, Husi Letu, and Qin Kai
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-273, https://doi.org/10.5194/amt-2019-273, 2019
Revised manuscript accepted for AMT
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In an attempt of making the cloud retrieval from surface more common and convenient, we developed a cloud retrieval algorithm applicable for sun photometer and sky radiometer belonging to AERONET and SKYNET. It is based on an optimum method by fitting measured transmittances with modeled values. Further, a cost-effective and easy-to-use calibration procedure is proposed and validated using data obtained from standard method. A detail error analysis is performed and quality assessment is done.
Jingjing Tian, Xiquan Dong, Baike Xi, Christopher R. Williams, and Peng Wu
Atmos. Meas. Tech., 12, 3743–3759, https://doi.org/10.5194/amt-12-3743-2019, https://doi.org/10.5194/amt-12-3743-2019, 2019
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Liquid water path (LWP) is a combination of rain liquid water path (RLWP) and cloud liquid water path (CLWP) in stratiform precipitation systems. LWP partitioning is important but poorly understood. Here we estimate the RLWP and CLWP below the melting base simultaneously and separately using ceilometer and radar measurements. Results show that the occurrence of cloud particles below the melting base is low; however, when cloud particles exist, the CLWP value is much larger than the RLWP.
Alan J. Geer
Atmos. Meas. Tech., 12, 3629–3657, https://doi.org/10.5194/amt-12-3629-2019, https://doi.org/10.5194/amt-12-3629-2019, 2019
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Using more satellite data in cloudy areas helps improve weather forecasts, but all-sky assimilation is still tricky, particularly for infrared data. To allow the use of hyperspectral infrared sounder radiances in all-sky conditions, an error model is developed that, in the presence of cloud, broadens the correlations between channels and increases error variances. After fixing problems of gravity wave and bias amplification, the results of all-sky assimilation trials were promising.
Tiziano Maestri, William Cossich, and Iacopo Sbrolli
Atmos. Meas. Tech., 12, 3521–3540, https://doi.org/10.5194/amt-12-3521-2019, https://doi.org/10.5194/amt-12-3521-2019, 2019
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An innovative and flexible methodology for cloud identification and classification, CIC, is tested on a synthetic dataset of high spectral resolution radiances in the far- and mid-infrared part of the spectrum, simulating measurements from the FORUM (Far Infrared Outgoing Radiation Understanding and Monitoring) mission. Results show that classification scores are greatly increased when far-infrared channels are accounted for and the identification of thin cirrus clouds is improved.
Marek Jacob, Felix Ament, Manuel Gutleben, Heike Konow, Mario Mech, Martin Wirth, and Susanne Crewell
Atmos. Meas. Tech., 12, 3237–3254, https://doi.org/10.5194/amt-12-3237-2019, https://doi.org/10.5194/amt-12-3237-2019, 2019
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Tropical clouds are a key climate component but are still not fully understood. Therefore, we analyze airborne remote sensing measurements that were taken in the dry and wet seasons over the Atlantic east of Barbados. From these we derive sub-kilometer resolution data of vertically integrated atmospheric water vapor and liquid water. Results show that although the humidity is lower in the dry season, clouds are more frequent, contain more water, and produce more rain than in the wet season.
Imane Farouk, Nadia Fourrié, and Vincent Guidard
Atmos. Meas. Tech., 12, 3001–3017, https://doi.org/10.5194/amt-12-3001-2019, https://doi.org/10.5194/amt-12-3001-2019, 2019
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A selection for homogeneous scenes for the assimilation of IASI radiances is proposed by using information on the collocated imager pixels inside each infrared observation. A revised method for the selection, which represents a compromise between two methods to select homogeneous scenes using homogeneity criteria already proposed in the literature, has a positive impact on the observation minus the simulation statistics. It has been tested in a numerical weather prediction model for clear sky.
Nikos Benas, Jan Fokke Meirink, Martin Stengel, and Piet Stammes
Atmos. Meas. Tech., 12, 2863–2879, https://doi.org/10.5194/amt-12-2863-2019, https://doi.org/10.5194/amt-12-2863-2019, 2019
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Cloud glory and bow phenomena cause irregularities in satellite-based retrievals of cloud optical and microphysical properties. Here we combine two geostationary satellites over the same areas to analyze retrievals under those conditions. Results show a high sensitivity of retrievals to the assumed width of the cloud droplet size distribution and provide insights into possible improvements in satellite retrievals by appropriately adjusting this assumed parameter.
Quitterie Cazenave, Marie Ceccaldi, Julien Delanoë, Jacques Pelon, Silke Groß, and Andrew Heymsfield
Atmos. Meas. Tech., 12, 2819–2835, https://doi.org/10.5194/amt-12-2819-2019, https://doi.org/10.5194/amt-12-2819-2019, 2019
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The impact of ice clouds on the water cycle and radiative budget is still uncertain due to the complexity of cloud processes that makes it difficult to acquire adequate observations of ice cloud properties and parameterize them into climate and weather prediction models. In this paper we present the latest refinements brought to the DARDAR-CLOUD product, which contains ice cloud microphysical properties retrieved from the cloud radar and lidar measurements from the A-Train space mission.
Johannes Bühl, Patric Seifert, Martin Radenz, Holger Baars, and Albert Ansmann
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-154, https://doi.org/10.5194/amt-2019-154, 2019
Revised manuscript accepted for AMT
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In the present paper, we present a novel remote-sensing technique for the measurement of ice crystal number concentrations in clouds. The fall velocity of ice crystals measured with a combination of cloud radar and radar wind profiler is used in order to derive information about ice crystal size and number concentration. In contrast to existing methods based on the combination of lidar and cloud radar, the present method can also be used in optically thick clouds.
Marine Desmons, Ping Wang, Piet Stammes, and L. Gijsbert Tilstra
Atmos. Meas. Tech., 12, 2485–2498, https://doi.org/10.5194/amt-12-2485-2019, https://doi.org/10.5194/amt-12-2485-2019, 2019
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The FRESCO algorithm is a simple, fast and robust algorithm used to retrieve cloud information during operational satellite data processing. FRESCO retrieves effective cloud fraction and cloud pressure from measurements in the oxygen A band around 761 nm. In this paper, we propose a new version of the algorithm, called FRESCO-B, which is based on measurements in the oxygen B band around 687 nm. Such a method leads to more accurate retrievals for vegetated surfaces.
Shan Zeng, Mark Vaughan, Zhaoyan Liu, Charles Trepte, Jayanta Kar, Ali Omar, David Winker, Patricia Lucker, Yongxiang Hu, Brian Getzewich, and Melody Avery
Atmos. Meas. Tech., 12, 2261–2285, https://doi.org/10.5194/amt-12-2261-2019, https://doi.org/10.5194/amt-12-2261-2019, 2019
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We use a fuzzy k-means (FKM) classifier to assess the ability of the CALIPSO cloud–aerosol discrimination (CAD) algorithm to correctly distinguish between clouds and aerosols detected in the CALIPSO lidar backscatter signals. FKM is an unsupervised learning algorithm, so the classifications it derives are wholly independent from those reported by the CAD scheme. For a full month of measurements, the two techniques agree in ~ 95 % of all cases, providing strong evidence for CAD correctness.
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.
Christoph Böhm, Odran Sourdeval, Johannes Mülmenstädt, Johannes Quaas, and Susanne Crewell
Atmos. Meas. Tech., 12, 1841–1860, https://doi.org/10.5194/amt-12-1841-2019, https://doi.org/10.5194/amt-12-1841-2019, 2019
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The cloud base height (CBH) is important for air traffic, for describing the energy budget of the Earth and for other applications. Ground-based CBH measurements are only available for individual sites and mostly limited to land. Satellites are a powerful tool for global coverage. While the cloud top height is derived operationally, the derivation of CBH from space is more difficult as the clouds hide their base. Here, we present a method to retrieve the CBH from multi-angle satellite data.
Antonio Di Noia, Otto P. Hasekamp, Bastiaan van Diedenhoven, and Zhibo Zhang
Atmos. Meas. Tech., 12, 1697–1716, https://doi.org/10.5194/amt-12-1697-2019, https://doi.org/10.5194/amt-12-1697-2019, 2019
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We present a neural network algorithm for the retrieval of cloud physical properties from multi-angle polarimetric measurements. We have trained the algorithm on a large dataset of synthetic measurements and applied it to a year of POLDER-3 data. A comparison against MODIS cloud products reveals that our algorithm is capable of performing cloud property retrievals on a global scale and possibly improves the estimates of cloud effective radius over land with respect to existing POLDER-3 products.
Mark Richardson, Jussi Leinonen, Heather Q. Cronk, James McDuffie, Matthew D. Lebsock, and Graeme L. Stephens
Atmos. Meas. Tech., 12, 1717–1737, https://doi.org/10.5194/amt-12-1717-2019, https://doi.org/10.5194/amt-12-1717-2019, 2019
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We retrieve cloud properties, including geometric thickness, by combining hyperspectral Orbiting Carbon Observatory-2 (OCO-2) A-band measurements with CALIPSO lidar. This uses cloudy scene data that are not used in OCO-2's main mission, which is aimed at clear-sky atmospheric CO2 abundance. This is the first retrieval using such hyperspectral information and promises to provide a unique constraint on the properties of low liquid clouds over the ocean.
Friederike Hemmer, Laurent C.-Labonnote, Frédéric Parol, Gérard Brogniez, Bahaiddin Damiri, and Thierry Podvin
Atmos. Meas. Tech., 12, 1545–1568, https://doi.org/10.5194/amt-12-1545-2019, https://doi.org/10.5194/amt-12-1545-2019, 2019
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The paper presents a novel method to retrieve microphysical properties of cirrus clouds from the synergy of lidar and thermal infrared radiometer measurements. It highlights the advantages of combining two independent data sets resulting in a better characterization of the observed target. Our algorithm may help to improve the description of the backscattering features of the ice crystals composing the cloud and thereby improve our understanding of their interactions with atmospheric radiation.
Samuel Favrichon, Catherine Prigent, Carlos Jimenez, and Filipe Aires
Atmos. Meas. Tech., 12, 1531–1543, https://doi.org/10.5194/amt-12-1531-2019, https://doi.org/10.5194/amt-12-1531-2019, 2019
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Land surface parameters (such as temperature) can be extracted from passive microwave satellite observations, with less cloud contamination than in the infrared. A cloud contamination index is proposed to detect cloud contamination for multiple frequency ranges (from 10 to 190 GHz), to be applicable to the successive generations of MW instruments. Even with a reduced number of low-frequency channels over land, the index reaches an accuracy of ≥ 70 % in detecting contaminated observations.
Tobias Zinner, Ulrich Schwarz, Tobias Kölling, Florian Ewald, Evelyn Jäkel, Bernhard Mayer, and Manfred Wendisch
Atmos. Meas. Tech., 12, 1167–1181, https://doi.org/10.5194/amt-12-1167-2019, https://doi.org/10.5194/amt-12-1167-2019, 2019
Florian Ewald, Tobias Zinner, Tobias Kölling, and Bernhard Mayer
Atmos. Meas. Tech., 12, 1183–1206, https://doi.org/10.5194/amt-12-1183-2019, https://doi.org/10.5194/amt-12-1183-2019, 2019
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This paper presents a new method for gaining insights into the vertical evolution of cloud droplet effective radii by using reflected solar radiation from cloud sides. The paper investigates how bi-spectral effective radius retrievals are affected by unknown cloud surface orientations and presents a method to mitigate this effect. Based on these findings, this study develops a statistical effective radius retrieval for airborne, side-looking imaging sensors.
Soheila Jafariserajehlou, Linlu Mei, Marco Vountas, Vladimir Rozanov, John P. Burrows, and Rainer Hollmann
Atmos. Meas. Tech., 12, 1059–1076, https://doi.org/10.5194/amt-12-1059-2019, https://doi.org/10.5194/amt-12-1059-2019, 2019
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We developed a new algorithm for cloud identification over the Arctic. This algorithm called ASCIA, utilizes time-series measurements of Advanced Along-Track Scanning Radiometer (AATSR) on Envisat and Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3A and -3B.
The data product of ASCIA is compared with three satellite products: ASCIA shows an improved performance compared to them. We validated ASCIA by ground-based measurements and a promising agreement is achieved.
Jean-François Ribaud, Luiz Augusto Toledo Machado, and Thiago Biscaro
Atmos. Meas. Tech., 12, 811–837, https://doi.org/10.5194/amt-12-811-2019, https://doi.org/10.5194/amt-12-811-2019, 2019
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The dominant hydrometeor types associated with Brazilian tropical precipitation systems are identified for the Amazon region during both the wet and dry seasons. Overall the stratiform regions are composed of five hydrometeor classes: drizzle, rain, wet snow, aggregates, and ice crystals, whereas convective echoes are generally associated with light rain, moderate rain, heavy rain, graupel, aggregates and ice crystals.
Zhaoyan Liu, Jayanta Kar, Shan Zeng, Jason Tackett, Mark Vaughan, Melody Avery, Jacques Pelon, Brian Getzewich, Kam-Pui Lee, Brian Magill, Ali Omar, Patricia Lucker, Charles Trepte, and David Winker
Atmos. Meas. Tech., 12, 703–734, https://doi.org/10.5194/amt-12-703-2019, https://doi.org/10.5194/amt-12-703-2019, 2019
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We describe the enhancements made to the cloud–aerosol discrimination (CAD) algorithms used to produce the CALIPSO version 4 (V4) data products. Revisions to the CAD probability distribution functions have greatly improved the recognition of aerosol layers lofted into the upper troposphere, and CAD is now applied to all layers detected in the stratosphere and all layers detected at single-shot resolution. Detailed comparisons show significant improvements relative to previous versions.
Nawo Eguchi and Yukio Yoshida
Atmos. Meas. Tech., 12, 389–403, https://doi.org/10.5194/amt-12-389-2019, https://doi.org/10.5194/amt-12-389-2019, 2019
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A detection method for high-level cloud, such as ice clouds, is developed using the water vapor saturated channels (2 μm) of the solar reflected spectrum observed by the TANSO-FTS on board GOSAT. The clouds detected by this method are optically relatively thin (0.01 or less) and located at high altitudes. Approximately 85 % of the results from this method for clouds with a cloud-top altitude above 5 km agree with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) cloud classification.
Mark Vaughan, Anne Garnier, Damien Josset, Melody Avery, Kam-Pui Lee, Zhaoyan Liu, William Hunt, Jacques Pelon, Yongxiang Hu, Sharon Burton, Johnathan Hair, Jason L. Tackett, Brian Getzewich, Jayanta Kar, and Sharon Rodier
Atmos. Meas. Tech., 12, 51–82, https://doi.org/10.5194/amt-12-51-2019, https://doi.org/10.5194/amt-12-51-2019, 2019
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The version 4 (V4) release of the CALIPSO data products includes substantial improvements to the calibration of the CALIOP 1064 nm channel. In this paper we review the fundamentals of 1064 nm lidar calibration, explain the motivations for the changes made to the algorithm, and describe the mechanics of the V4 calibration technique. Internal consistency checks and comparisons to collocated high spectral resolution lidar measurements show the V4 1064 nm calibration coefficients to within ~ 3 %.
Richard J. Roy, Matthew Lebsock, Luis Millán, Robert Dengler, Raquel Rodriguez Monje, Jose V. Siles, and Ken B. Cooper
Atmos. Meas. Tech., 11, 6511–6523, https://doi.org/10.5194/amt-11-6511-2018, https://doi.org/10.5194/amt-11-6511-2018, 2018
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The measurement of water vapor profiles inside clouds with high spatial resolution represents an outstanding problem in atmospheric remote sensing. Here we present measurements from a proof-of-concept millimeter-wave (170 GHz) cloud radar aimed at filling this observational gap, and demonstrate the ability to retrieve in-cloud water vapor profiles with high precision and resolution. This technology could meaningfully impact future satellite-based measurements of water vapor.
Brian J. Getzewich, Mark A. Vaughan, William H. Hunt, Melody A. Avery, Kathleen A. Powell, Jason L. Tackett, David M. Winker, Jayanta Kar, Kam-Pui Lee, and Travis D. Toth
Atmos. Meas. Tech., 11, 6309–6326, https://doi.org/10.5194/amt-11-6309-2018, https://doi.org/10.5194/amt-11-6309-2018, 2018
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We describe the new architecture of the version 4 (V4) CALIOP 532 nm daytime calibration procedures. Critical differences from the versions include moving the night-to-day calibration transfer region into the lower stratosphere coupled to a multi-dimensional data averaging scheme. Comparisons to collocated high spectral resolution lidar (HSRL) measurements shows that the V4 532 nm daytime attenuated backscatter coefficients replicate the HSRL data to within 1.0 % ± 3.5 %.
Michael Höpfner, Terry Deshler, Michael Pitts, Lamont Poole, Reinhold Spang, Gabriele Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 11, 5901–5923, https://doi.org/10.5194/amt-11-5901-2018, https://doi.org/10.5194/amt-11-5901-2018, 2018
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Polar stratospheric clouds (PSC) have major relevance to the processes leading to polar ozone depletion. A good understanding of these particles is a prerequisite to predict their role in a changing climate. We present the first global set of PSC volume density profiles derived from the MIPAS satellite measurements covering the entire mission period between 2002 and 2012. A comparison to CALIOP lidar measurements is provided. The dataset can serve as a basis for evaluation of atmospheric models.
Stuart A. Young, Mark A. Vaughan, Anne Garnier, Jason L. Tackett, James D. Lambeth, and Kathleen A. Powell
Atmos. Meas. Tech., 11, 5701–5727, https://doi.org/10.5194/amt-11-5701-2018, https://doi.org/10.5194/amt-11-5701-2018, 2018
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This paper describes comprehensive upgrades to the algorithms used to retrieve altitude-resolved profiles of cloud and aerosol extinction coefficients from the elastic backscatter measurements made by the space-based CALIPSO lidar. The CALIPSO version 4 data products generated by these new algorithms are explored in detail, and the many areas of improvement are highlighted using extensive comparisons both to previous versions and to collocated measurements made by space-based passive sensors.
Hendrik Andersen and Jan Cermak
Atmos. Meas. Tech., 11, 5461–5470, https://doi.org/10.5194/amt-11-5461-2018, https://doi.org/10.5194/amt-11-5461-2018, 2018
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Fog and low clouds (FLCs) are a valuable source of water for many ecosystems in the Namib. This study presents the first fully diurnal satellite detection of FLCs, revealing the spatial and temporal patterns in the Namib. A validation is conducted against station measurements in the central Namib and shows a high overall accuracy. The average timing and persistence of FLCs seem to depend on the distance to the coast, suggesting that the region is dominated by advection-driven FLCs.
Qixiang Luo, Yong Meng, Lei Liu, Xiaofeng Zhao, and Zeming Zhou
Atmos. Meas. Tech., 11, 5351–5361, https://doi.org/10.5194/amt-11-5351-2018, https://doi.org/10.5194/amt-11-5351-2018, 2018
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In this paper, a novel cloud classification method is proposed to group images into five cloud types based on manifold and texture features. The proposed method is comprised of three stages: data pre-processing, feature extraction and classification. Compared to the recent cloud type recognition methods, the experimental results illustrate that the proposed method acquires a higher recognition rate with an increase of 2%–10% on the ground-based infrared datasets.
Christopher R. Williams, Maximilian Maahn, Joseph C. Hardin, and Gijs de Boer
Atmos. Meas. Tech., 11, 4963–4980, https://doi.org/10.5194/amt-11-4963-2018, https://doi.org/10.5194/amt-11-4963-2018, 2018
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This study presents three signal-processing methods to improve estimates derived from a vertically pointing 35 GHz cloud radar deployed at Oliktok Point, Alaska. The first method removes ground clutter from the Doppler velocity spectra. The second method estimates multiple peaks and high-order moments from the improved spectra. The third method removes high-frequency variability in high-order moments by shifting original 2 s spectra to a common reference before averaging over a 15 s interval.
Simon Pfreundschuh, Patrick Eriksson, David Duncan, Bengt Rydberg, Nina Håkansson, and Anke Thoss
Atmos. Meas. Tech., 11, 4627–4643, https://doi.org/10.5194/amt-11-4627-2018, https://doi.org/10.5194/amt-11-4627-2018, 2018
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A novel neural-network-based retrieval method is proposed that combines the flexibility and computational efficiency of machine learning retrievals with the consistent treatment of uncertainties of Bayesian methods. Numerical experiments are presented that show the consistency of the proposed method with the Bayesian formulation as well as its ability to represent non-Gaussian retrieval errors. With this, the proposed method overcomes important limitations of traditional methods.
Daniel P. Grosvenor, Odran Sourdeval, and Robert Wood
Atmos. Meas. Tech., 11, 4273–4289, https://doi.org/10.5194/amt-11-4273-2018, https://doi.org/10.5194/amt-11-4273-2018, 2018
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We provide a parameterized correction to the retrieval of cloud effective radius from satellite instruments to account for the assumption that the retrieved value is representative of that at cloud top, whereas in reality it is representative of that lower down. The error leads to errors (which we quantify) in the retrieved cloud droplet concentrations of up to 38 % for stratocumulus regions and also to liquid water path errors, both of which can be corrected using our parameterizations.
Verena Grützun, Stefan A. Buehler, Lukas Kluft, Jana Mendrok, Manfred Brath, and Patrick Eriksson
Atmos. Meas. Tech., 11, 4217–4237, https://doi.org/10.5194/amt-11-4217-2018, https://doi.org/10.5194/amt-11-4217-2018, 2018
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The global observation of ice clouds is crucial because they are important factors in the climate system but still are amongst the greatest uncertainties for estimating the Earth's energy budget in a changing climate. However, reliable global long-term measurements are scarce. Using atmospheric model data from the ICON model in combination with the radiative transfer simulator ARTS we explore the potential of passive millimeter and sub-millimeter wavelength measurements to fill that gap.
Alexander Vasilkov, Eun-Su Yang, Sergey Marchenko, Wenhan Qin, Lok Lamsal, Joanna Joiner, Nickolay Krotkov, David Haffner, Pawan K. Bhartia, and Robert Spurr
Atmos. Meas. Tech., 11, 4093–4107, https://doi.org/10.5194/amt-11-4093-2018, https://doi.org/10.5194/amt-11-4093-2018, 2018
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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.
Daniel J. Miller, Zhibo Zhang, Steven Platnick, Andrew S. Ackerman, Frank Werner, Celine Cornet, and Kirk Knobelspiesse
Atmos. Meas. Tech., 11, 3689–3715, https://doi.org/10.5194/amt-11-3689-2018, https://doi.org/10.5194/amt-11-3689-2018, 2018
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Prior satellite comparisons of bispectral and polarimetric cloud droplet size retrievals exhibited systematic biases. However, similar airborne instrument retrievals have been found to be quite similar to one another. This study explains this discrepancy in terms of differing sensitivity to vertical profile, as well as spatial and angular resolution. This is accomplished by using a satellite retrieval simulator – an LES cloud model coupled to radiative transfer and cloud retrieval algorithms.
Oliver Sus, Martin Stengel, Stefan Stapelberg, Gregory McGarragh, Caroline Poulsen, Adam C. Povey, Cornelia Schlundt, Gareth Thomas, Matthew Christensen, Simon Proud, Matthias Jerg, Roy Grainger, and Rainer Hollmann
Atmos. Meas. Tech., 11, 3373–3396, https://doi.org/10.5194/amt-11-3373-2018, https://doi.org/10.5194/amt-11-3373-2018, 2018
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This paper presents a new cloud detection and classification framework, CC4CL. It applies a sophisticated optimal estimation method to derive cloud variables from satellite data of various polar-orbiting platforms and sensors (AVHRR, MODIS, AATSR). CC4CL provides explicit uncertainty quantification and long-term consistency for decadal timeseries at various spatial resolutions. We analysed 5 case studies to show that cloud height estimates are very realistic unless optically thin clouds overlap.
Gregory R. McGarragh, Caroline A. Poulsen, Gareth E. Thomas, Adam C. Povey, Oliver Sus, Stefan Stapelberg, Cornelia Schlundt, Simon Proud, Matthew W. Christensen, Martin Stengel, Rainer Hollmann, and Roy G. Grainger
Atmos. Meas. Tech., 11, 3397–3431, https://doi.org/10.5194/amt-11-3397-2018, https://doi.org/10.5194/amt-11-3397-2018, 2018
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Satellites are vital for measuring cloud properties necessary for climate prediction studies. We present a method to retrieve cloud properties from satellite based radiometric measurements. The methodology employed is known as optimal estimation and belongs in the class of statistical inversion methods based on Bayes' theorem. We show, through theoretical retrieval simulations, that the solution is stable and accurate to within 10–20% depending on cloud thickness.
Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee, and Stefan Winkler
Atmos. Meas. Tech., 11, 2041–2049, https://doi.org/10.5194/amt-11-2041-2018, https://doi.org/10.5194/amt-11-2041-2018, 2018
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Sky–cloud images obtained from ground-based sky cameras are usually captured using a fish-eye lens with a wide field of view. However, the sky exhibits a large variation in the scene luminance. In most cases, the circumsolar region is overexposed, and the regions near the horizon are underexposed. In this paper, we propose HDRCloudSeg – an effective method for cloud segmentation using high-dynamic-range (HDR) imaging. We describe the entire process and also release a new database.
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Polar mesospheric clouds are an upper atmospheric phenomenon of great interest in that they provide information about a previously inaccessible atmospheric region, the coldest of the planet. This paper provides the basis for converting raw radiance measurements of clouds, made by diverse satellite instrumentation, into a physically based quantity, the cloud ice water content. The new algorithm allows intercomparisons of data collected using diverse optical methods.
Polar mesospheric clouds are an upper atmospheric phenomenon of great interest in that they...
Atmospheric Measurement Techniques
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