Research article 14 May 2013
Research article | 14 May 2013
Ground-based remote sensing of thin clouds in the Arctic
T. J. Garrett and C. Zhao
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Current world economic production is rising relative to energy consumption. This increase in “production efficiency” suggests that carbon dioxide emissions can be decoupled from economic activity through technological change. We show instead a nearly fixed relationship between energy consumption and a new economic quantity, historically cumulative economic production. The strong link to the past implies inertia may play a more dominant role in societal evolution than is generally assumed.
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An old problem for accurately predicting weather and climate is knowing the mass and density of snowflakes as a function of their size. Few measurements have been obtained because snowflakes are so small and fragile. The most widely used sample is of just 376 snowflakes obtained in the early 1970s in Washington State. We developed a new instrument for automatic measurement of snowflake mass and density. Our analysis shows that snowflakes have a lower density than is often assumed.
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This paper describes a new instrument for quantifying the physical characteristic of hydrometeors such as snow and rain. The device can measure the mass, size, density, and type of individual hydrometeors and their bulk properties. The instrument is called the Differential Emissivity Imaging Disdrometer or DEID and is composed of a thermal camera and hotplate. The DEID measures hydrometeors at sampling frequencies up to 1 Hz with masses and effective diameters greater than 1 μg and 200 μm.
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Monte Carlo simulations are used to establish baseline precipitation measurement uncertainties according to World Meteorological Organization standards. Measurement accuracy depends on instrument sampling area, time interval, and precipitation rate. Simulations are compared with field measurements taken by an emerging hotplate precipitation sensor. We find that the current collection area is sufficient for light rain, but a larger collection area is required to detect moderate to heavy rain.
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Earth Syst. Dynam., 6, 673–688, https://doi.org/10.5194/esd-6-673-2015, https://doi.org/10.5194/esd-6-673-2015, 2015
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GCMs and economic models are often coupled for climate scenarios. Here, what is examined is how well a simple non-equilibrium thermodynamic model can represent the multi-decadal growth of global civilization. Initialized with growth trends from the 1950s, the model attains high skill at hindcasting how fast the GDP and energy consumption grew during the 2000s. This opens treating the coupled economy and climate as a physically deterministic response to available flows of energy and matter.
B. van Diedenhoven, B. Cairns, A. M. Fridlind, A. S. Ackerman, and T. J. Garrett
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Timothy J. Garrett, Matheus R. Grasselli, and Stephen Keen
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2021-21, https://doi.org/10.5194/esd-2021-21, 2021
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Current world economic production is rising relative to energy consumption. This increase in “production efficiency” suggests that carbon dioxide emissions can be decoupled from economic activity through technological change. We show instead a nearly fixed relationship between energy consumption and a new economic quantity, historically cumulative economic production. The strong link to the past implies inertia may play a more dominant role in societal evolution than is generally assumed.
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Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-44, https://doi.org/10.5194/amt-2021-44, 2021
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Kyle E. Fitch, Chaoxun Hang, Ahmad Talaei, and Timothy J. Garrett
Atmos. Meas. Tech., 14, 1127–1142, https://doi.org/10.5194/amt-14-1127-2021, https://doi.org/10.5194/amt-14-1127-2021, 2021
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Snow measurements are very sensitive to wind. Here, we compare airflow and snowfall simulations to Arctic observations for a Multi-Angle Snowflake Camera to show that measurements of fall speed, orientation, and size are accurate only with a double wind fence and winds below 5 m s−1. In this case, snowflakes tend to fall with a nearly horizontal orientation; the largest flakes are as much as 5 times more likely to be observed. Adjustments are needed for snow falling in naturally turbulent air.
Karlie Rees and Timothy J. Garrett
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-393, https://doi.org/10.5194/amt-2020-393, 2020
Preprint under review for AMT
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Quentin Coopman, Timothy J. Garrett, Jérôme Riedi, Sabine Eckhardt, and Andreas Stohl
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T. J. Garrett
Earth Syst. Dynam., 6, 673–688, https://doi.org/10.5194/esd-6-673-2015, https://doi.org/10.5194/esd-6-673-2015, 2015
Short summary
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GCMs and economic models are often coupled for climate scenarios. Here, what is examined is how well a simple non-equilibrium thermodynamic model can represent the multi-decadal growth of global civilization. Initialized with growth trends from the 1950s, the model attains high skill at hindcasting how fast the GDP and energy consumption grew during the 2000s. This opens treating the coupled economy and climate as a physically deterministic response to available flows of energy and matter.
B. van Diedenhoven, B. Cairns, A. M. Fridlind, A. S. Ackerman, and T. J. Garrett
Atmos. Chem. Phys., 13, 3185–3203, https://doi.org/10.5194/acp-13-3185-2013, https://doi.org/10.5194/acp-13-3185-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-387, https://doi.org/10.5194/amt-2020-387, 2020
Revised manuscript accepted for AMT
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The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results are presented in a companion (Part II) paper.
Vasileios Barlakas, Alan J. Geer, and Patrick Eriksson
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-442, https://doi.org/10.5194/amt-2020-442, 2020
Revised manuscript accepted for AMT
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Oriented non-spherical ice particles induce polarization that is ignored when cloud-sensitive satellite observations are used in numerical weather prediction systems. We present a simple approach for approximating particle orientation, requiring minor adaption of software and no additional calculation burden. With this approach, the system realistically simulates the observed polarization patterns, increasing the physical consistency between instruments with different polarizations.
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-388, https://doi.org/10.5194/amt-2020-388, 2020
Revised manuscript accepted for AMT
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The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part II) shows retrievals over ocean and describes the improvements made with respect to version 3 as a result of the significant changes implemented in the version 4 algorithms, which are presented in a companion paper (Part I).
Irene Bartolome Garcia, Reinhold Spang, Jörn Ungermann, Sabine Griessbach, Martina Krämer, Michael Höpfner, and Martin Riese
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-394, https://doi.org/10.5194/amt-2020-394, 2020
Revised manuscript accepted for AMT
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Cirrus clouds contribute to the general radiation budget of the Earth. Measuring optically thin clouds is challenging but the IR limb sounder GLORIA possess the necessary technical characteristics to make it possible. This study analyses data from the WISE campaign obtained with GLORIA. We developed a cloud detection method and derived characteristics of the observed cirrus like cloud top, cloud bottom or position with respect to the tropopause.
Benjamin R. Scarino, Kristopher Bedka, Rajendra Bhatt, Konstantin Khlopenkov, David R. Doelling, and William L. Smith Jr.
Atmos. Meas. Tech., 13, 5491–5511, https://doi.org/10.5194/amt-13-5491-2020, https://doi.org/10.5194/amt-13-5491-2020, 2020
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This paper highlights a technique for facilitating anvil cloud detection based on visible observations that relies on comparative analysis with expected cloud reflectance for a given set of angles. A 1-year database of anvil-identified pixels, as determined from IR observations, from several geostationary satellites was used to construct a bidirectional reflectance distribution function model to quantify typical anvil reflectance across almost all expected viewing, solar, and azimuth angles.
Bangsheng Yin, Qilong Min, Emily Morgan, Yuekui Yang, Alexander Marshak, and Anthony B. Davis
Atmos. Meas. Tech., 13, 5259–5275, https://doi.org/10.5194/amt-13-5259-2020, https://doi.org/10.5194/amt-13-5259-2020, 2020
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Frédéric Tridon, Alessandro Battaglia, and Stefan Kneifel
Atmos. Meas. Tech., 13, 5065–5085, https://doi.org/10.5194/amt-13-5065-2020, https://doi.org/10.5194/amt-13-5065-2020, 2020
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The droplets and ice crystals composing clouds and precipitation interact with microwaves and can therefore be observed by radars, but they can also attenuate the signal they emit. By combining the observations made by two ground-based radars, this study describes an original approach for estimating such attenuation. As a result, the latter can be not only corrected in the radar observations but also exploited for providing an accurate characterization of droplet and ice crystal properties.
Mark Richardson, Matthew D. Lebsock, James McDuffie, and Graeme L. Stephens
Atmos. Meas. Tech., 13, 4947–4961, https://doi.org/10.5194/amt-13-4947-2020, https://doi.org/10.5194/amt-13-4947-2020, 2020
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We previously combined CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar data and reflected-sunlight measurements from OCO-2 (Orbiting Carbon Observatory 2) for information about low clouds over oceans. The satellites are no longer formation-flying, so this work is a step towards getting new information about these clouds using only OCO-2. We can rapidly and accurately identify liquid oceanic clouds and obtain their height better than a widely used passive sensor.
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., 13, 4539–4563, https://doi.org/10.5194/amt-13-4539-2020, https://doi.org/10.5194/amt-13-4539-2020, 2020
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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 cloud phases. In V4 there are many 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.
Vladimir S. Kostsov, Dmitry V. Ionov, and Anke Kniffka
Atmos. Meas. Tech., 13, 4565–4587, https://doi.org/10.5194/amt-13-4565-2020, https://doi.org/10.5194/amt-13-4565-2020, 2020
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Previously, observations from satellites provided evidence for systematic differences between the values of the cloud liquid water path over land and water areas in northern Europe. An attempt is made to detect such differences by means of ground-based microwave measurements performed near the coastline of the Gulf of Finland. The results demonstrate the existence of the cloud liquid water path gradient, which is positive as in the case of the satellite measurements (larger values over land).
Simon Pfreundschuh, Patrick Eriksson, Stefan A. Buehler, Manfred Brath, David Duncan, Richard Larsson, and Robin Ekelund
Atmos. Meas. Tech., 13, 4219–4245, https://doi.org/10.5194/amt-13-4219-2020, https://doi.org/10.5194/amt-13-4219-2020, 2020
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The next generation of European operational weather satellites will carry a novel microwave sensor, the Ice Cloud Imager (ICI), which will provide observations of clouds at microwave frequencies that were not available before. We investigate the potential benefits of combining observations from ICI with that of a radar. We find that such combined observations provide additional information on the properties of the cloud and help to reduce uncertainties in retrieved mass and number densities.
Yue Li, Bryan A. Baum, Andrew K. Heidinger, W. Paul Menzel, and Elisabeth Weisz
Atmos. Meas. Tech., 13, 4035–4049, https://doi.org/10.5194/amt-13-4035-2020, https://doi.org/10.5194/amt-13-4035-2020, 2020
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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 S-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.
Florian Tornow, Carlos Domenech, Howard W. Barker, René Preusker, and Jürgen Fischer
Atmos. Meas. Tech., 13, 3909–3922, https://doi.org/10.5194/amt-13-3909-2020, https://doi.org/10.5194/amt-13-3909-2020, 2020
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Clouds reflect sunlight unevenly, which makes it difficult to quantify the portion reflected back to space via satellite observation. To improve quantification, we propose a new statistical model that incorporates more satellite-inferred cloud and atmospheric properties than state-of-the-art models. We use concepts from radiative transfer theory that we statistically optimize to fit observations. The new model often explains past satellite observations better and predicts reflection plausibly.
Rocco Sedona, Lars Hoffmann, Reinhold Spang, Gabriele Cavallaro, Sabine Griessbach, Michael Höpfner, Matthias Book, and Morris Riedel
Atmos. Meas. Tech., 13, 3661–3682, https://doi.org/10.5194/amt-13-3661-2020, https://doi.org/10.5194/amt-13-3661-2020, 2020
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Polar stratospheric clouds (PSCs) 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.
Alain Protat and Ian McRobert
Atmos. Meas. Tech., 13, 3609–3620, https://doi.org/10.5194/amt-13-3609-2020, https://doi.org/10.5194/amt-13-3609-2020, 2020
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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 min resolution 3D wind motions can be obtained from this instrumental setup.
Daniel J. Miller, Michal Segal-Rozenhaimer, Kirk Knobelspiesse, Jens Redemann, Brian Cairns, Mikhail Alexandrov, Bastiaan van Diedenhoven, and Andrzej Wasilewski
Atmos. Meas. Tech., 13, 3447–3470, https://doi.org/10.5194/amt-13-3447-2020, https://doi.org/10.5194/amt-13-3447-2020, 2020
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A neural network (NN) is developed and used to retrieve cloud microphysical properties from multiangular and multispectral polarimetric remote sensing observations. The NN is applied to research scanning polarimeter (RSP) observations obtained during the ORACLES field campaign and compared to other co-located remote sensing retrievals of cloud effective radius and optical thickness. A NN approach can advance more complex iterative search retrieval algorithms by providing a quick initial guess.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-38, https://doi.org/10.5194/amt-2020-38, 2020
Revised manuscript accepted for AMT
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This study suggests two methods to detect convection using one-minute data from GOES-16: one method detecting early convective clouds using their vertical growth rate and the other method detecting mature convective clouds using their lumpy cloud top surfaces. Applying the two methods to one-month data showed that the accuracy of the combined methods was 85.8 % and showed its potential to be used in regions where radar data are not available.
Holger Sihler, Steffen Beirle, Steffen Dörner, Marloes Gutenstein-Penning de Vries, Christoph Hörmann, Christian Borger, Simon Warnach, and Thomas Wagner
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-182, https://doi.org/10.5194/amt-2020-182, 2020
Revised manuscript accepted for AMT
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MICRU is an algorithm for the retrieval of effective cloud fractions (CF) from satellite measurements. CF describe the amount of clouds, which have a significant impact on the vertical sensitivity profile of trace-gases like NO2 and HCHO. MICRU retrieves small CF with an accuracy of 0.04 over the entire satellite swath. It features an empirical surface reflectivity model accounting for physical anisotropy (BRDF, sun glitter) and instrumental effects. MICRU is also applicable to imager data.
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.
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.
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.
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