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Atmospheric Measurement Techniques
An interactive open-access journal of the European Geosciences Union
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- About
- Editorial board
- Articles
- Special issues
- Highlight articles
- Manuscript tracking
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- For authors
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IF 3.668
3.707CiteScore
6.3SNIP 1.383
SJR 1.525
index 77h5-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
Short summary
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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 machine-learning-based cloud detection and thermodynamic-phase classification algorithm using passive spectral observations
SegCloud: a novel cloud image segmentation model using a deep convolutional neural network for ground-based all-sky-view camera observation
Spatial distribution of cloud droplet size properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) measurements
Towards objective identification and tracking of convective outflow boundaries in next-generation geostationary satellite imagery
Cloud detection over snow and ice with oxygen A- and B-band observations from the Earth Polychromatic Imaging Camera (EPIC)
Ground-based observations of cloud and drizzle liquid water path in stratocumulus clouds
Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: evaluation of candidate approaches with MODIS observations
Estimation of cloud optical thickness, single scattering albedo and effective droplet radius using a shortwave radiative closure study in Payerne
Three-dimensional wind profiles using a stabilized shipborne cloud radar in wind profiler mode
Exploration of machine learning methods for the classification of infrared limb spectra of polar stratospheric clouds
Improvement in cloud retrievals from VIIRS through the use of infrared absorption channels constructed from VIIRS-CrIS data fusion
CALIOP V4 Cloud Thermodynamic Phase Assignment and the Impact of Near-Nadir Viewing Angles
Towards an operational Ice Cloud Imager (ICI) retrieval product
Ice crystal number concentration from lidar, cloud radar and radar wind profiler measurements
Retrieval of cloud properties from spectral zenith radiances observed by sky radiometers
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
Low-level liquid cloud properties during ORACLES retrieved using airborne polarimetric measurements and a neural network algorithm
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
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
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
Chenxi Wang, Steven Platnick, Kerry Meyer, Zhibo Zhang, and Yaping Zhou
Atmos. Meas. Tech., 13, 2257–2277, https://doi.org/10.5194/amt-13-2257-2020, https://doi.org/10.5194/amt-13-2257-2020, 2020
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A machine-learning (ML)-based approach that can be used for cloud mask and phase detection is developed. An all-day model that uses infrared (IR) observations and a daytime model that uses shortwave and IR observations from a passive instrument are trained separately for different surface types. The training datasets are selected by using reference pixel types from collocated space lidar. The ML approach is validated carefully and the overall performance is better than traditional methods.
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, https://doi.org/10.5194/amt-13-1953-2020, 2020
Brent A. McBride, J. Vanderlei Martins, Henrique M. J. Barbosa, William Birmingham, and Lorraine A. Remer
Atmos. Meas. Tech., 13, 1777–1796, https://doi.org/10.5194/amt-13-1777-2020, https://doi.org/10.5194/amt-13-1777-2020, 2020
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Clouds play a large role in the way our Earth system distributes energy. The measurement of cloud droplet size distribution (DSD) is one way to connect small-scale cloud processes to scattered radiation. Our small satellite instrument, the Airborne Hyper-Angular Rainbow Polarimeter, is the first to infer DSDs over a wide spatial cloud field using polarized light. This study improves the way we interpret cloud properties and shows that high-quality science does not require a large taxpayer cost.
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, https://doi.org/10.5194/amt-13-1593-2020, 2020
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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.
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, https://doi.org/10.5194/amt-13-1575-2020, 2020
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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.
Maria P. Cadeddu, Virendra P. Ghate, and Mario Mech
Atmos. Meas. Tech., 13, 1485–1499, https://doi.org/10.5194/amt-13-1485-2020, https://doi.org/10.5194/amt-13-1485-2020, 2020
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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.
Frank Werner and Hartwig Deneke
Atmos. Meas. Tech., 13, 1089–1111, https://doi.org/10.5194/amt-13-1089-2020, https://doi.org/10.5194/amt-13-1089-2020, 2020
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The reliability of remotely sensed cloud variables from space depends on the horizontal resolution of the instrument. This study presents and evaluates several candidate approaches for increasing the spatial resolution of observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) from the native 3 km scale to a horizontal resolution of 1 km. It is shown that uncertainties in the derived cloud products can be significantly mitigated by applying an appropriate downscaling scheme.
Christine Aebi, Julian Gröbner, Stelios Kazadzis, Laurent Vuilleumier, Antonis Gkikas, and Niklaus Kämpfer
Atmos. Meas. Tech., 13, 907–923, https://doi.org/10.5194/amt-13-907-2020, https://doi.org/10.5194/amt-13-907-2020, 2020
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Clouds are one of the largest sources of uncertainties in climate models. The current study estimates the cloud optical thickness (COT), the effective droplet radius and the single scattering albedo of stratus–altostratus and cirrus–cirrostratus clouds in Payerne, Switzerland, by combining ground- and satellite-based measurements and radiative transfer models. The estimated values are thereafter compared with data retrieved from other methods. The mean COT is distinct for different seasons.
Alain Protat and Ian McRobert
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-34, https://doi.org/10.5194/amt-2020-34, 2020
Revised manuscript accepted for AMT
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Three-dimensional (3D) wind motions play a major role in driving the life cycle of clouds. In this pilot study we have developed a technique to measure the 3D winds in clouds, using a shipborne Doppler cloud radar on a stabilized platform. The stabilized platform is driven to point in a series of predefined directions to collect the required measurements. Comparisons with radiosondes demonstrate that accurate 1-minute resolution 3D wind motions can be obtained from this instrumental setup.
Rocco Sedona, Lars Hoffmann, Reinhold Spang, Gabriele Cavallaro, Sabine Griessbach, Michael Höpfner, Matthias Book, and Morris Riedel
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-481, https://doi.org/10.5194/amt-2019-481, 2020
Preprint under review for AMT
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Polar stratospheric clouds (PSC) play a key role in polar ozone depletion in the stratosphere. In this paper, we explore the potential of applying machine learning (ML) methods to classify PSC observations of infrared spectra to classify PSC types. ML methods have proved to reach results in line with those obtained using well-established approaches. Among the considered ML methods, Random Forest (RF) seems to be the most promising one, being able to produce explainable classification results.
Yue Li, Bryan A. Baum, Andrew K. Heidinger, W. Paul Menzel, and Elisabeth Weisz
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-497, https://doi.org/10.5194/amt-2019-497, 2020
Revised manuscript accepted for AMT
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Use of VIIRS-CrIS fusion products, which provide VIIRS with MODIS-like IR sounding channels, improves cloud mask, cloud phase, and cloud top height retrievals when compared to those using VIIRS data only. NOAA CLAVR-x cloud retrievals for both Suomi-NPP and NOAA-20 data are evaluated through comparisons to the CALIPSO V4 and MODIS Collection 6.1 cloud products. Cloud height retrievals show significant improvement for semitransparent ice clouds, with a reduction in retrieval uncertainties.
Melody A. Avery, Robert A. Ryan, Brian J. Getzewich, Mark A. Vaughan, David M. Winker, Yongxiang Hu, Anne Garnier, Jacques Pelon, and Carolus A. Verhappen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-388, https://doi.org/10.5194/amt-2019-388, 2020
Revised manuscript accepted for AMT
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CALIOP data users will find more cloud layers detected in V4, with edges that extend further than in V3, for an increase in total atmospheric cloud volume of 6–9 % for high-confidence cloud phases and 1–2 % for all cloudy bins, including cloud fringes and unknown phases. In V4 there are also fewer cloud layers identified as horizontally-oriented ice, particularly in the 3° off-nadir view. Depolarization at 532 nm is the predominant parameter determining cloud thermodynamic phase.
Patrick Eriksson, Bengt Rydberg, Vinia Mattioli, Anke Thoss, Christophe Accadia, Ulf Klein, and Stefan A. Buehler
Atmos. Meas. Tech., 13, 53–71, https://doi.org/10.5194/amt-13-53-2020, https://doi.org/10.5194/amt-13-53-2020, 2020
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The Ice Cloud Imager (ICI) will be the first operational satellite sensor operating at sub-millimetre wavelengths and this novel mission will thus provide important new data to weather forecasting and climate studies. The series of ICI instruments will together cover about 20 years. This article presents the basic technical characteristics of the sensor and outlines the day-one operational retrievals. An updated estimation of the expected retrieval performance is also presented.
Johannes Bühl, Patric Seifert, Martin Radenz, Holger Baars, and Albert Ansmann
Atmos. Meas. Tech., 12, 6601–6617, https://doi.org/10.5194/amt-12-6601-2019, https://doi.org/10.5194/amt-12-6601-2019, 2019
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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 values from cloud radar and a 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.
Pradeep Khatri, Hironobu Iwabuchi, Tadahiro Hayasaka, Hitoshi Irie, Tamio Takamura, Akihiro Yamazaki, Alessandro Damiani, Husi Letu, and Qin Kai
Atmos. Meas. Tech., 12, 6037–6047, https://doi.org/10.5194/amt-12-6037-2019, https://doi.org/10.5194/amt-12-6037-2019, 2019
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In an attempt to make cloud retrievals from the surface more common and convenient, we developed a cloud retrieval algorithm applicable for sky radiometers. 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 the standard method. A detailed error analysis and quality assessment are also performed.
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.
Daniel J. Miller, Michal Segal-Rozenhaimer, Kirk Knobelspiesse, Jens Redemann, Brian Cairns, Mikhail Alexandrov, Bastiaan van Diedenhoven, and Andrzej Wasilewski
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-327, https://doi.org/10.5194/amt-2019-327, 2019
Revised manuscript accepted for AMT
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A neural network (NN) is developed that can be used to relate multi-angular and multi-spectral polarimetric remote sensing observations to retrievals of cloud microphysical properties. The NN is applied to Research Scanning Polarimeter observations obtained during the ORACLES field campaign and compared to other collocated cloud remote sensing retrievals of cloud effective radius and optical thickness. This approach can advance more complex iterative algorithms by providing a quick first guess.
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.
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.
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.
Cited articles
AIM CIPS Science Team: Cloud Imaging and Particle Size (CIPS) Instrument Overview, available at: http://lasp.colorado.edu/aim/, last access:
12 March 2019.
Bailey, S. M., Thomas, G. E., Rusch, D. W., Merkel, A. W., Jeppesen, C.,
Carstens, J. N., Randall, C. E., McClintock, W. E., and Russell III, J. M.: Phase
functions of polar mesospheric cloud ice as observed by the CIPS instrument
on the AIM satellite, J. Atmos.
Sol.-Terr. Phy., 71, 373–380, https://doi.org/10.1016/j.jastp.2008.09.039, 2009.
Bardeen, C. G., Toon, O. B., Jensen, E. J., Hervig, M. E., Randall, C. E.,
Benze, S., Marsh, D. R., and Merkel, A.: Numerical simulations of the
three-dimensional distribution of polar mesospheric clouds and comparisons
with Cloud Imaging and Particle Size (CIPS) experiment and the Solar
Occultation For Ice Experiment (SOFIE) observations, J. Geophys. Res., 115,
D10204, https://doi.org/10.1029/2009JD012451, 2010.
Baumgarten, G., Fiedler, J., and Rapp, M.: On microphysical processes of noctilucent
clouds (NLC): observations and modeling of mean and width of the particle
size-distribution, Atmos. Chem. Phys., 10, 6661–6668, https://doi.org/10.5194/acp-10-6661-2010, 2010.
Benze, S., Randall, C. E., DeLand, M. T., Thomas, G. E., Rusch, D. W.,
Bailey, S. M., Russell III, J. M., McClintock, W., Merkel, A. W., and
Jeppesen, C.: Comparison of polar mesospheric cloud measurements from the
Cloud Imaging and Particle Size experiment and the Solar Backscatter
Ultraviolet instrument in 2007, J. Atmos. Sol.-Terr. Phy., 71, 365–372, 2009.
Benze, S., Randall, C. E., Karlsson, B., Harvey, V. L., DeLand, M. T., Thomas,
G. E., and Shettle, E. P.: On the onset of polar mesospheric cloud seasons as
observed by SBUV, J. Geophys. Res., 117, D07104, https://doi.org/10.1029/2011JD017350, 2012.
DeLand, M. T. and Thomas, G. E.: Updated PMC trends derived from SBUV data,
J. Geophys. Res.-Atmos., 120, 2140–2166, https://doi.org/10.1002/2014JD022253, 2015.
DeLand, M. T., Shettle, E. P., Thomas, G. E., and Olivero, J. J.: A
quarter-century of satellite PMC observations, J. Atmos. Sol.-Terr. Phy.,
68, 9–29, 2006.
Englert, C. R. and Stevens, M. H.: Polar mesospheric cloud mass and the ice
budget: 1. Quantitative interpretation of mid-UV cloud brightness
observations, J. Geophys. Res., 112, D08204, https://doi.org/10.1029/2006JD007533, 2007.
Gordley, L. L., Hervig, M. E., Fish, C., Russell III, J. M., Bailey, S. M.,
Cook, J., Hansen, J., Shumway, A., Paxton, G., Deaver, L., Marshall, T.,
Burton, J., Magill, B., Brown, C., Thompson, E., and Kemp, J.: The solar
occultation for ice experiment, J. Atmos. Sol.-Terr. Phy., 71, 300–315,
2009.
Hansen, J. E. and Travis, L. D.: Light scattering in planetary atmospheres,
Space Sci. Rev., 16, 527–610, 1974.
Hervig, M. E. and Gordley, L. L.: Temperature, shape, and phase of
mesospheric ice from Solar Occultation for Ice Experiment observations, J.
Geophys. Res., 115, D15208, https://doi.org/10.1029/2010JD013918, 2010.
Hervig, M. E. and Stevens, M. H.: Interpreting the 35-year SBUV PMC record
with SOFIE observations, J. Geophys. Res.-Atmos., 119, 12689–12705,
https://doi.org/10.1002/2014JD021923,2014.
Hervig, J. E., Gordley, L. L., Stevens, M. H., Russell III, J. M., Bailey, S.
M., and Baumgarten, G.: Interpretation of SOFIE PMC measurements: Cloud
identification and derivation of mass density, particle shape, and particle
size, J. Atmos. Sol.-Terr. Phy., 71, 316–330, 2009.
Hervig, M. E., Berger, U., and Siskind, D. E.: Decadal variability in PMCs
and implications for changing temperature and water vapor in the upper
mesosphere, J. Geophys Res.-Atmos., 121, 2383–2392, https://doi.org/10.1002/2015JD024439, 2016.
Hultgren, K. and Gumbel, J.: Tomographic and spectral views on the lifecyle
of polar mesospheric clouds from ODIN/OSIRIS, J. Geophys Res.-Atmos., 119, 14129–14143, https://doi.org/10.1002/2014JD022435, 2014.
Lübken, F.-J., Berger, U., and Baumgarten, G.: On the anthropogenic
impact on long-term evolution of noctilucent clouds, Geophys. Res. Lett.,
45, 6681–6689, https://doi.org/10.1029/2018GL077719,
2018.
Lumpe, J. D.,
Bailey, S. M., Carstens, J. N., Randall, C. E., Rusch, D. W., Thomas, G. E., Nielsen, K.,
Jeppesen, C., McClintock, W. E., Merkel, A. W., Riesberg, L., Templeman, B.,
Baumgarten, G., and Russell IlI, J. M.: Retrieval of polar mesospheric cloud
properties from CIPS: algorithm description, error analysis and cloud
detection sensitivity, J. Atmos. Sol.-Terr. Phy., 104, 167–196, https://doi.org/10.1016/j.jastp.2013.06.007, 2013.
McClintock, W. E., Rusch, D. W., Thomas, G. E., Merkel, A. W, Lankton, M. R.,
Drake, V. A., Bailey, S. M., and Russell III, J. M.: The cloud imaging and
particle size experiment on the Aeronomy of Ice in the mesosphere mission:
Instrument concept, design, calibration, and on-orbit performance, J. Atmos. Sol.-Terr. Phy., 71,
340–355, https://doi.org/10.1016/j.jastp.2008.10.011, 2009.
Mishchenko, M. I. and Travis, L. D.: Capabilities and limitations of a current
Fortran implementation of the T-matrix method for randomly oriented,
rotationally symmetric scatterers, J. Quant. Spectrosc. Ra., 60,
309–324, 1998.
Rapp, M. and Thomas, G. E.: Modeling the microphysics of mesospheric ice
particles: Assessment of current capabilities and basic sensitivities, J.
Atmos. Sol.-Terr. Phy., 68, 715–744, 2006.
Rusch, D. W., Thomas, G. E., McClintock, W., Merkel, A. W., Bailey, S. M.,
Russell III, J. M., Randall, C. E., Jeppesen, C., and Callan, M.: The cloud
imaging and particle size experiment on the aeronomy of ice in the
mesosphere mission: Cloud morphology for the northern 2007 season, J. Atmos.
Sol.-Terr. Phy., 71, 356–364, 2009.
Russell III, J. M., Bailey, S. M., Gordley, L. L., Rusch, D. W.,
Horányi, M., Hervig, M. E., Thomas, G. E., Randall, C. E.,
Siskind, D. E., Stevens, M. H., Summers, M. E., Taylor, M. J., Englert, C.
R., Espy, P. J., McClintock, W. E., and Merkel, A. W.: The Aeronomy of Ice in
the Mesosphere (AIM) mission: Overview and early science results, J. Atmos.
Sol.-Terr. Phy., 71, 289–299, 2009.
Thomas, G. E. and McKay, C. P.: On the mean particle size and water content of
polar mesospheric clouds, Planet. Space Sci., 33, 1209–1224, 1985.
Thomas, G. E., Olivero, J. J., Jensen, E. J., Schröder, W.,
and Toon, O. B.: Relation between increasing methane and the presence of ice
clouds at the mesopause, Nature, 338, 490–492, 1989.
Thomas, G. E., McPeters, R. D., and Jensen, E. J.: Satellite observations of
polar mesospheric clouds by the Solar Backscattered Ultraviolet radiometer:
Evidence of a solar cycle dependence, J. Geophys. Res., 96, 927–939, 1991.
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Short summary
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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