Articles | Volume 14, issue 11
https://doi.org/10.5194/amt-14-7243-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-7243-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Triple-frequency radar retrieval of microphysical properties of snow
National Centre for Earth Observation, University of Leicester, Leicester, UK
Alessandro Battaglia
Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Turin, Italy
National Centre for Earth Observation, University of Leicester, Leicester, UK
Cuong Nguyen
Flight Research Laboratory, National Research Council Canada, Ottawa, Canada
Andrew Heymsfield
National Center for Atmospheric Research, Boulder, Colorado, USA
Alain Protat
Australian Bureau of Meteorology, Melbourne, Victoria, Australia
Mengistu Wolde
Flight Research Laboratory, National Research Council Canada, Ottawa, Canada
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Some of the new generation of cloud and precipitation spaceborne radars will adopt conical scanning. This will make some of the standard calibration techniques impractical. This work presents a methodology to cross-calibrate radars in orbits by matching the reflectivity probability density function of ice clouds observed by the to-be-calibrated and by the reference radar in quasi-coincident locations. Results show that cross-calibration within 1 dB (26 %) is feasible.
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The article examines the relationship between the characteristics of rain and the properties of the ice cloud from which the rain originated. Our results confirm the widely accepted assumption that the mass flux through the melting zone is well preserved with an exception of extreme aggregation and riming conditions. Moreover, it is shown that the mean (mass-weighted) size of particles above and below the melting zone is strongly linked, with the former being on average larger.
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Yongjie Huang, Wei Wu, Greg M. McFarquhar, Ming Xue, Hugh Morrison, Jason Milbrandt, Alexei V. Korolev, Yachao Hu, Zhipeng Qu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, and Ivan Heckman
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Alain Protat, Valentin Louf, Joshua Soderholm, Jordan Brook, and William Ponsonby
Atmos. Meas. Tech., 15, 915–926, https://doi.org/10.5194/amt-15-915-2022, https://doi.org/10.5194/amt-15-915-2022, 2022
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Cuong M. Nguyen, Mengistu Wolde, Alessandro Battaglia, Leonid Nichman, Natalia Bliankinshtein, Samuel Haimov, Kenny Bala, and Dirk Schuettemeyer
Atmos. Meas. Tech., 15, 775–795, https://doi.org/10.5194/amt-15-775-2022, https://doi.org/10.5194/amt-15-775-2022, 2022
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An analysis of airborne triple-frequency radar and almost perfectly co-located coincident in situ data from an Arctic storm confirms the main findings of modeling work with radar dual-frequency ratios (DFRs) at different zones of the DFR plane associated with different ice habits. High-resolution CPI images provide accurate identification of rimed particles within the DFR plane. The relationships between the triple-frequency signals and cloud microphysical properties are also presented.
Ruhi S. Humphries, Melita D. Keywood, Sean Gribben, Ian M. McRobert, Jason P. Ward, Paul Selleck, Sally Taylor, James Harnwell, Connor Flynn, Gourihar R. Kulkarni, Gerald G. Mace, Alain Protat, Simon P. Alexander, and Greg McFarquhar
Atmos. Chem. Phys., 21, 12757–12782, https://doi.org/10.5194/acp-21-12757-2021, https://doi.org/10.5194/acp-21-12757-2021, 2021
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The Southern Ocean region is one of the most pristine in the world and serves as an important proxy for the pre-industrial atmosphere. Improving our understanding of the natural processes in this region is likely to result in the largest reductions in the uncertainty of climate and earth system models. In this paper we present a statistical summary of the latitudinal gradient of aerosol and cloud condensation nuclei concentrations obtained from five voyages spanning the Southern Ocean.
Konstantin Baibakov, Samuel LeBlanc, Keyvan Ranjbar, Norman T. O'Neill, Mengistu Wolde, Jens Redemann, Kristina Pistone, Shao-Meng Li, John Liggio, Katherine Hayden, Tak W. Chan, Michael J. Wheeler, Leonid Nichman, Connor Flynn, and Roy Johnson
Atmos. Chem. Phys., 21, 10671–10687, https://doi.org/10.5194/acp-21-10671-2021, https://doi.org/10.5194/acp-21-10671-2021, 2021
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We find that the airborne measurements of the vertical extinction due to aerosols (aerosol optical depth, AOD) obtained in the Athabasca Oil Sands Region (AOSR) can significantly exceed ground-based values. This can have an effect on estimating the AOSR radiative impact and is relevant to satellite validation based on ground-based measurements. We also show that the AOD can marginally increase as the plumes are being transported away from the source and the new particles are being formed.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
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Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.
Katherine Hayden, Shao-Meng Li, Paul Makar, John Liggio, Samar G. Moussa, Ayodeji Akingunola, Robert McLaren, Ralf M. Staebler, Andrea Darlington, Jason O'Brien, Junhua Zhang, Mengistu Wolde, and Leiming Zhang
Atmos. Chem. Phys., 21, 8377–8392, https://doi.org/10.5194/acp-21-8377-2021, https://doi.org/10.5194/acp-21-8377-2021, 2021
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We developed a method using aircraft measurements to determine lifetimes with respect to dry deposition for oxidized sulfur and nitrogen compounds over the boreal forest in Alberta, Canada. Atmospheric lifetimes were significantly shorter than derived from chemical transport models with differences related to modelled dry deposition velocities. The shorter lifetimes suggest models need to reassess dry deposition treatment and predictions of sulfur and nitrogen in the atmosphere and ecosystems.
Katia Lamer, Mariko Oue, Alessandro Battaglia, Richard J. Roy, Ken B. Cooper, Ranvir Dhillon, and Pavlos Kollias
Atmos. Meas. Tech., 14, 3615–3629, https://doi.org/10.5194/amt-14-3615-2021, https://doi.org/10.5194/amt-14-3615-2021, 2021
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Observations collected during the 25 February 2020 deployment of the VIPR at the Stony Brook Radar Observatory clearly demonstrate the potential of G-band radars for cloud and precipitation research. The field experiment, which coordinated an X-, Ka-, W- and G-band radar, revealed that the differential reflectivity from Ka–G band pair provides larger signals than the traditional Ka–W pairing underpinning an increased sensitivity to smaller amounts of liquid and ice water mass and sizes.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Xuguang Wang, Hugh Morrison, Alexander Ryzhkov, Yachao Hu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, Jason Milbrandt, Alexei V. Korolev, and Ivan Heckman
Atmos. Chem. Phys., 21, 6919–6944, https://doi.org/10.5194/acp-21-6919-2021, https://doi.org/10.5194/acp-21-6919-2021, 2021
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Numerous small ice crystals in the tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. This study evaluated the numerical models against the airborne observations and investigated the potential cloud processes that could lead to the production of these large numbers of small ice crystals. It is found that key microphysical processes are still lacking or misrepresented in current numerical models to realistically simulate the phenomenon.
Kamil Mróz, Alessandro Battaglia, Stefan Kneifel, Leonie von Terzi, Markus Karrer, and Davide Ori
Atmos. Meas. Tech., 14, 511–529, https://doi.org/10.5194/amt-14-511-2021, https://doi.org/10.5194/amt-14-511-2021, 2021
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The article examines the relationship between the characteristics of rain and the properties of the ice cloud from which the rain originated. Our results confirm the widely accepted assumption that the mass flux through the melting zone is well preserved with an exception of extreme aggregation and riming conditions. Moreover, it is shown that the mean (mass-weighted) size of particles above and below the melting zone is strongly linked, with the former being on average larger.
Robert Jackson, Scott Collis, Valentin Louf, Alain Protat, Die Wang, Scott Giangrande, Elizabeth J. Thompson, Brenda Dolan, and Scott W. Powell
Atmos. Meas. Tech., 14, 53–69, https://doi.org/10.5194/amt-14-53-2021, https://doi.org/10.5194/amt-14-53-2021, 2021
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About 4 years of 2D video disdrometer data in Darwin are used to develop and validate rainfall retrievals for tropical convection in C- and X-band radars in Darwin. Using blended techniques previously used for Colorado and Manus and Gan islands, with modified coefficients in each estimator, provided the most optimal results. Using multiple radar observables to develop a rainfall retrieval provided a greater advantage than using a single observable, including using specific attenuation.
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.
Annette K. Miltenberger, Paul R. Field, Adrian H. Hill, and Andrew J. Heymsfield
Atmos. Chem. Phys., 20, 7979–8001, https://doi.org/10.5194/acp-20-7979-2020, https://doi.org/10.5194/acp-20-7979-2020, 2020
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Orographic wave clouds offer a natural laboratory to investigate cloud microphysical processes and their representation in atmospheric models. They impact the larger-scale flow by a vertical redistribution of moisture and aerosol. We use detailed observations from the ICE-L campaign to evaluate the representation of these clouds in a state-of-the-art numerical weather prediction model and explore the impact of environmental conditions on the vertical redistribution of moisture.
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.
Katia Lamer, Pavlos Kollias, Alessandro Battaglia, and Simon Preval
Atmos. Meas. Tech., 13, 2363–2379, https://doi.org/10.5194/amt-13-2363-2020, https://doi.org/10.5194/amt-13-2363-2020, 2020
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According to ground-based radar observations, 50 % of liquid low-level clouds over the Atlantic extend below 1.2 km and are thinner than 400 m, thus limiting their detection from space. Using an emulator, we estimate that a 250 m resolution radar would capture cloud base better than the CloudSat radar which misses about 52 %. The more sensitive EarthCARE radar is expected to capture cloud cover but stretch cloud. This calls for the operation of interlaced pulse modes for future space missions.
Alexei Korolev, Ivan Heckman, Mengistu Wolde, Andrew S. Ackerman, Ann M. Fridlind, Luis A. Ladino, R. Paul Lawson, Jason Milbrandt, and Earle Williams
Atmos. Chem. Phys., 20, 1391–1429, https://doi.org/10.5194/acp-20-1391-2020, https://doi.org/10.5194/acp-20-1391-2020, 2020
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This study attempts identification of mechanisms of secondary ice production (SIP) based on the observation of small faceted ice crystals. It was found that in both mesoscale convective systems and frontal clouds, SIP was observed right above the melting layer and extended to the higher altitudes with colder temperatures. A principal conclusion of this work is that the freezing drop shattering mechanism is plausibly accounting for the measured ice concentrations in the observed condition.
Adrien Guyot, Jayaram Pudashine, Alain Protat, Remko Uijlenhoet, Valentijn R. N. Pauwels, Alan Seed, and Jeffrey P. Walker
Hydrol. Earth Syst. Sci., 23, 4737–4761, https://doi.org/10.5194/hess-23-4737-2019, https://doi.org/10.5194/hess-23-4737-2019, 2019
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We characterised for the first time the rainfall microphysics for Southern Hemisphere temperate latitudes. Co-located instruments were deployed to provide information on the sampling effect and spatio-temporal variabilities at micro scales. Substantial differences were found across the instruments, increasing with increasing values of the rain rate. Specific relations for reflectivity–rainfall are presented together with related uncertainties for drizzle and stratiform and convective rainfall.
Cuong M. Nguyen, Mengistu Wolde, and Alexei Korolev
Atmos. Meas. Tech., 12, 5897–5911, https://doi.org/10.5194/amt-12-5897-2019, https://doi.org/10.5194/amt-12-5897-2019, 2019
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This paper presents a methodology for high ice water content (HIWC) (up to 3.5 g m−3) retrieval from a dual-polarization side-looking X-band airborne radar. Zdr and Kdp are used to mitigate the effects of ice crystal shape and orientation on the variation in IWC – specific differential phase (Kdp) joint distribution. Empirical analysis shows that the proposed method improves the estimation bias by 35 % and increases the correlation by 4 % on average, compared to the method using Kdp alone.
Ingo Wohltmann, Ralph Lehmann, Georg A. Gottwald, Karsten Peters, Alain Protat, Valentin Louf, Christopher Williams, Wuhu Feng, and Markus Rex
Geosci. Model Dev., 12, 4387–4407, https://doi.org/10.5194/gmd-12-4387-2019, https://doi.org/10.5194/gmd-12-4387-2019, 2019
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We present a trajectory-based model for simulating the transport of air parcels by convection. Our model extends the approach of existing models by explicitly simulating vertical updraft velocities inside the clouds and the time that an air parcel spends inside the convective event.
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.
Mengistu Wolde, Alessandro Battaglia, Cuong Nguyen, Andrew L. Pazmany, and Anthony Illingworth
Atmos. Meas. Tech., 12, 253–269, https://doi.org/10.5194/amt-12-253-2019, https://doi.org/10.5194/amt-12-253-2019, 2019
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This paper presents an implementation of polarization diversity pulse-pair processing (PDPP) on the National Research Council of Canada airborne W-band radar (NAW) system. A description of the NAW PDPP pulsing schemes and an analysis of comprehensive airborne data collected in diverse weather conditions in Canada is presented. The analysis shows a successful airborne measurement of Doppler velocity exceeding 100 m s−1 using PDPP approach, the first such measurement from a moving platform.
Robert C. Jackson, Scott M. Collis, Valentin Louf, Alain Protat, and Leon Majewski
Atmos. Chem. Phys., 18, 17687–17704, https://doi.org/10.5194/acp-18-17687-2018, https://doi.org/10.5194/acp-18-17687-2018, 2018
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This paper looks at a 17 year database of echo top heights of thunderstorms in Darwin retrieved by CPOL. We find that the echo top heights are generally bimodal, corresponding to cumulus congestus and deep convection, and show a greater bimodality during an inactive MJO. Furthermore, we find that convective cell areas are larger in break conditions compared to monsoon conditions, but only during MJO-inactive conditions.
Brian H. Kahn, Hanii Takahashi, Graeme L. Stephens, Qing Yue, Julien Delanoë, Gerald Manipon, Evan M. Manning, and Andrew J. Heymsfield
Atmos. Chem. Phys., 18, 10715–10739, https://doi.org/10.5194/acp-18-10715-2018, https://doi.org/10.5194/acp-18-10715-2018, 2018
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The Atmospheric Infrared Sounder (AIRS) satellite instrument shows statistically significant global trends in ice cloud properties between September 2002 and August 2016. The trends are not explained by known AIRS instrument limitations. Significant differences in the ice cloud particle size is found between convective clouds and thin ice clouds in the tropics. These results will be a useful benchmark for other studies of global ice cloud properties.
Sabour Baray, Andrea Darlington, Mark Gordon, Katherine L. Hayden, Amy Leithead, Shao-Meng Li, Peter S. K. Liu, Richard L. Mittermeier, Samar G. Moussa, Jason O'Brien, Ralph Staebler, Mengistu Wolde, Doug Worthy, and Robert McLaren
Atmos. Chem. Phys., 18, 7361–7378, https://doi.org/10.5194/acp-18-7361-2018, https://doi.org/10.5194/acp-18-7361-2018, 2018
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Methane emissions from major oil sands facilities in the Athabasca Oil Sands Region (AOSR) of Alberta were measured in the summer of 2013 using two related aircraft mass-balance approaches. Tailings ponds and fugitive emissions of methane from open pit mines were found to be the major sources of methane in the region. Total methane emissions in the AOSR were measured to be ~ 20 tonnes of CH4 per hour, which is 48 % higher than the Canadian Greenhouse Gas Reporting Program Emissions Inventory.
Christopher R. Yost, Kristopher M. Bedka, Patrick Minnis, Louis Nguyen, J. Walter Strapp, Rabindra Palikonda, Konstantin Khlopenkov, Douglas Spangenberg, William L. Smith Jr., Alain Protat, and Julien Delanoe
Atmos. Meas. Tech., 11, 1615–1637, https://doi.org/10.5194/amt-11-1615-2018, https://doi.org/10.5194/amt-11-1615-2018, 2018
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Accretion of cloud ice particles upon engine or instrument probe surfaces can cause engine malfunction or even power loss, and therefore it is important for aircraft to avoid flight through clouds that may have produced large quantities of ice particles. This study introduces a method by which potentially hazardous conditions can be detected using satellite imagery. It was found that potentially hazardous conditions were often located near or beneath very cold clouds and thunderstorm updrafts.
Jing Yang, Zhien Wang, and Andrew Heymsfield
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-714, https://doi.org/10.5194/acp-2017-714, 2017
Revised manuscript not accepted
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This study shows the freezing time is longer for large drops than small drops. Due to instrumental limitations, freezing drops cannot be identified until they exhibit obvious shape deformation. In models, drop freezing is assumed to be instantaneous, which is not realistic; thus, the model yields a broader
first icePSD than is observed. This study allows us to interpret the observed ice PSDs in developing convective clouds, and notes the deficiency of instantaneous drop freezing in models.
McKenna W. Stanford, Adam Varble, Ed Zipser, J. Walter Strapp, Delphine Leroy, Alfons Schwarzenboeck, Rodney Potts, and Alain Protat
Atmos. Chem. Phys., 17, 9599–9621, https://doi.org/10.5194/acp-17-9599-2017, https://doi.org/10.5194/acp-17-9599-2017, 2017
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Radar reflectivity is a valuable observational tool used to guide numerical weather model improvement. Biases in simulated reflectivity help identify potential errors in physical process and property representation in models. This study uniquely compares simulated and observed tropical convective systems to establish that a commonly documented high bias in radar reflectivity values at least partially results from the production of simulated ice particle sizes that are larger than observed.
John Liggio, Samar G. Moussa, Jeremy Wentzell, Andrea Darlington, Peter Liu, Amy Leithead, Katherine Hayden, Jason O'Brien, Richard L. Mittermeier, Ralf Staebler, Mengistu Wolde, and Shao-Meng Li
Atmos. Chem. Phys., 17, 8411–8427, https://doi.org/10.5194/acp-17-8411-2017, https://doi.org/10.5194/acp-17-8411-2017, 2017
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The emission and formation of gaseous organic acids from the oil sands industry in Canada is explored through aircraft measurements directly over and downwind wind of industrial facilities. Results demonstrated that the formation of organic acids through atmospheric chemical reactions dominated over the direct emissions from mining activities but could not be explicitly modeled. The results highlight the need for improved understanding of photochemical mechanisms leading to these species.
Ulrich Schumann, Robert Baumann, Darrel Baumgardner, Sarah T. Bedka, David P. Duda, Volker Freudenthaler, Jean-Francois Gayet, Andrew J. Heymsfield, Patrick Minnis, Markus Quante, Ehrhard Raschke, Hans Schlager, Margarita Vázquez-Navarro, Christiane Voigt, and Zhien Wang
Atmos. Chem. Phys., 17, 403–438, https://doi.org/10.5194/acp-17-403-2017, https://doi.org/10.5194/acp-17-403-2017, 2017
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The initially linear clouds often seen behind aircraft are known as contrails. Contrails are prototype cirrus clouds forming under well-known conditions, but with less certain life cycle and climate effects. This paper collects contrail data from a large set of measurements and compares them among each other and with models. The observations show consistent contrail properties over a wide range of aircraft and atmosphere conditions. The dataset is available for further research.
Jing Yang, Zhien Wang, Andrew J. Heymsfield, and Jeffrey R. French
Atmos. Chem. Phys., 16, 10159–10173, https://doi.org/10.5194/acp-16-10159-2016, https://doi.org/10.5194/acp-16-10159-2016, 2016
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This study provides statistics of the vertical air motion characteristics in convective clouds using aircraft in situ measurements from three field campaigns. Small-scale drafts are frequently observed and make important contributions to total air mass flux. The probability density functions and profiles of the observed vertical velocity and air mass flux are provided. The differences among the three field campaigns are compared. Factors influencing the vertical air motions are discussed.
Martin Schnaiter, Emma Järvinen, Paul Vochezer, Ahmed Abdelmonem, Robert Wagner, Olivier Jourdan, Guillaume Mioche, Valery N. Shcherbakov, Carl G. Schmitt, Ugo Tricoli, Zbigniew Ulanowski, and Andrew J. Heymsfield
Atmos. Chem. Phys., 16, 5091–5110, https://doi.org/10.5194/acp-16-5091-2016, https://doi.org/10.5194/acp-16-5091-2016, 2016
M. W. Shephard, C. A. McLinden, K. E. Cady-Pereira, M. Luo, S. G. Moussa, A. Leithead, J. Liggio, R. M. Staebler, A. Akingunola, P. Makar, P. Lehr, J. Zhang, D. K. Henze, D. B. Millet, J. O. Bash, L. Zhu, K. C. Wells, S. L. Capps, S. Chaliyakunnel, M. Gordon, K. Hayden, J. R. Brook, M. Wolde, and S.-M. Li
Atmos. Meas. Tech., 8, 5189–5211, https://doi.org/10.5194/amt-8-5189-2015, https://doi.org/10.5194/amt-8-5189-2015, 2015
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This study provides direct validations of Tropospheric Emission Spectrometer (TES) satellite retrieved profiles against coincident aircraft profiles of carbon monoxide, ammonia, methanol, and formic acid, all of which are of interest for air quality. The comparisons are performed over the Canadian oil sands region during an intensive field campaign in support of the Joint Canada-Alberta Implementation Plan for the Oil Sands Monitoring (JOSM). Initial model evaluations are also provided.
M. Gordon, S.-M. Li, R. Staebler, A. Darlington, K. Hayden, J. O'Brien, and M. Wolde
Atmos. Meas. Tech., 8, 3745–3765, https://doi.org/10.5194/amt-8-3745-2015, https://doi.org/10.5194/amt-8-3745-2015, 2015
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Aircraft-based measurements of air pollutants from sources in the Canadian oil sands were made during a summer intensive field campaign in 2013. This paper describes the top-down emission rate retrieval algorithm (TERRA) to determine facility emissions of pollutants, using SO2 and CH4 as examples. Uncertainty of the emission rates estimated with TERRA is estimated as less than 30%, which is primarily due to the unknown SO2 and CH4 mixing ratios near the surface below the lowest flight level.
C. Liu, P. Yang, P. Minnis, N. Loeb, S. Kato, A. Heymsfield, and C. Schmitt
Atmos. Chem. Phys., 14, 13719–13737, https://doi.org/10.5194/acp-14-13719-2014, https://doi.org/10.5194/acp-14-13719-2014, 2014
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An ice cloud model is developed by assuming an ice cloud to be an ensemble of columns and aggregates with specific habit fractions at each particle size bin. The microphysical and optical properties of this two-habit model (THM) are compared with both laboratory and in situ measurements. When the THM is applied to ice cloud property retrieval, excellent spectral consistency is achieved. A comparison between observed and theoretical polarized reflectivities illustrates the applicability of THM.
T. Eidhammer, H. Morrison, A. Bansemer, A. Gettelman, and A. J. Heymsfield
Atmos. Chem. Phys., 14, 10103–10118, https://doi.org/10.5194/acp-14-10103-2014, https://doi.org/10.5194/acp-14-10103-2014, 2014
M. Diao, M. A. Zondlo, A. J. Heymsfield, L. M. Avallone, M. E. Paige, S. P. Beaton, T. Campos, and D. C. Rogers
Atmos. Chem. Phys., 14, 2639–2656, https://doi.org/10.5194/acp-14-2639-2014, https://doi.org/10.5194/acp-14-2639-2014, 2014
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization
Particle inertial effects on radar Doppler spectra simulation
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data
Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS
Global evaluation of Doppler velocity errors of EarthCARE cloud-profiling radar using a global storm-resolving simulation
Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product
Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products
Across-track extension of retrieved cloud and aerosol properties for the EarthCARE mission: the ACMB-3D product
Insights into 3D cloud radiative transfer effects for the Orbiting Carbon Observatory
Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data
A neural network-based method for generating synthetic 1.6 μm near-infrared satellite images
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 1: Model description and Jacobian calculation
Simulation and sensitivity analysis for cloud and precipitation measurements via spaceborne millimeter-wave radar
The Virga-Sniffer – a new tool to identify precipitation evaporation using ground-based remote-sensing observations
Near-global distributions of overshooting tops derived from Terra and Aqua MODIS observations
Climatology of estimated liquid water content and scaling factor for warm clouds using radar–microwave radiometer synergy
Optimizing cloud motion estimation on the edge with phase correlation and optical flow
A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations
The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission
Deep convective cloud system size and structure across the global tropics and subtropics
Segmentation of polarimetric radar imagery using statistical texture
High-spatial-resolution retrieval of cloud droplet size distribution from polarized observations of the cloudbow
Evaluation of the spectral misalignment on the Earth Clouds, Aerosols and Radiation Explorer/multi-spectral imager cloud product
Retrieval of terahertz ice cloud properties from airborne measurements based on the irregularly shaped Voronoi ice scattering models
Latent heating profiles from GOES-16 and its impacts on precipitation forecasts
A CO2-independent cloud mask from Infrared Atmospheric Sounding Interferometer (IASI) radiances for climate applications
Numerical Model Generation of Test Frames for Pre-launch Studies of EarthCARE’s Retrieval Algorithms and Data Management System
Retrieval of ice water path from the Microwave Humidity Sounder (MWHS) aboard FengYun-3B (FY-3B) satellite polarimetric measurements based on a deep neural network
Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals
Improved spectral processing for a multi-mode pulse compression Ka–Ku-band cloud radar system
Uncertainty-bounded estimates of ash cloud properties using the ORAC algorithm: application to the 2019 Raikoke eruption
Ice water path retrievals from Meteosat-9 using quantile regression neural networks
An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties
Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks
Segmentation-based multi-pixel cloud optical thickness retrieval using a convolutional neural network
Top-of-the-atmosphere reflected shortwave radiative fluxes from GOES-R
Optimizing radar scan strategies for tracking isolated deep convection using observing system simulation experiments
A kriging-based analysis of cloud liquid water content using CloudSat data
High-resolution satellite-based cloud detection for the analysis of land surface effects on boundary layer clouds
Retrievals of ice microphysical properties using dual-wavelength polarimetric radar observations during stratiform precipitation events
The surface longwave cloud radiative effect derived from space lidar observations
Cloud phase and macrophysical properties over the Southern Ocean during the MARCUS field campaign
Detection of supercooled liquid water containing clouds with ceilometers: development and evaluation of deterministic and data-driven retrievals
An all-sky camera image classification method using cloud cover features
Determination of atmospheric column condensate using active and passive remote sensing technology
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
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Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
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We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
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We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
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We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
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JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
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This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
Christian Matar, Céline Cornet, Frédéric Parol, Laurent C.-Labonnote, Frédérique Auriol, and Marc Nicolas
Atmos. Meas. Tech., 16, 3221–3243, https://doi.org/10.5194/amt-16-3221-2023, https://doi.org/10.5194/amt-16-3221-2023, 2023
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The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular measurements to retrieve COT and Reff. The corresponding uncertainties related to measurement errors, which are up to 6 and 12 %, the non-retrieved parameters, which are less than 0.5 %, and the cloud model assumptions show that the heterogeneous vertical profiles and the 3D radiative transfer effects lead to average uncertainties of 5 and 4 % for COT and 13 and 9 % for Reff.
Yuichiro Hagihara, Yuichi Ohno, Hiroaki Horie, Woosub Roh, Masaki Satoh, and Takuji Kubota
Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
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The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
Kamil Mroz, Bernat Puidgomènech Treserras, Alessandro Battaglia, Pavlos Kollias, Aleksandra Tatarevic, and Frederic Tridon
Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
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We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
Anja Hünerbein, Sebastian Bley, Stefan Horn, Hartwig Deneke, and Andi Walther
Atmos. Meas. Tech., 16, 2821–2836, https://doi.org/10.5194/amt-16-2821-2023, https://doi.org/10.5194/amt-16-2821-2023, 2023
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The Multi-Spectral Imager (MSI) on board the EarthCARE satellite will provide the information needed for describing the cloud and aerosol properties in the cross-track direction, complementing the measurements from the Cloud Profiling Radar, Atmospheric Lidar and Broad-Band Radiometer. The accurate discrimination between clear and cloudy pixels is an essential first step. Therefore, the cloud mask algorithm provides a cloud flag, cloud phase and cloud type product for the MSI observations.
Zhipeng Qu, Howard W. Barker, Jason N. S. Cole, and Mark W. Shephard
Atmos. Meas. Tech., 16, 2319–2331, https://doi.org/10.5194/amt-16-2319-2023, https://doi.org/10.5194/amt-16-2319-2023, 2023
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This paper describes EarthCARE’s L2 product ACM-3D. It includes the scene construction algorithm (SCA) used to produce the indexes for reconstructing 3D atmospheric scene based on satellite nadir retrievals. It also provides the information about the buffer zone sizes of 3D assessment domains and the ranking scores for selecting the best 3D assessment domains. These output variables are needed to run 3D radiative transfer models for the radiative closure assessment of EarthCARE’s L2 retrievals.
Steven T. Massie, Heather Cronk, Aronne Merrelli, Sebastian Schmidt, and Steffen Mauceri
Atmos. Meas. Tech., 16, 2145–2166, https://doi.org/10.5194/amt-16-2145-2023, https://doi.org/10.5194/amt-16-2145-2023, 2023
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This paper provides insights into the effects of clouds on Orbiting Carbon Observatory (OCO-2) measurements of CO2. Calculations are carried out that indicate the extent to which this satellite experiment underestimates CO2, due to these cloud effects, as a function of the distance between the surface observation footprint and the nearest cloud. The paper discusses how to lessen the influence of these cloud effects.
Armin Blanke, Andrew J. Heymsfield, Manuel Moser, and Silke Trömel
Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023, https://doi.org/10.5194/amt-16-2089-2023, 2023
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We present an evaluation of current retrieval techniques in the ice phase applied to polarimetric radar measurements with collocated in situ observations of aircraft conducted over the Olympic Mountains, Washington State, during winter 2015. Radar estimates of ice properties agreed most with aircraft observations in regions with pronounced radar signatures, but uncertainties were identified that indicate issues of some retrievals, particularly in warmer temperature regimes.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
EGUsphere, https://doi.org/10.5194/egusphere-2023-353, https://doi.org/10.5194/egusphere-2023-353, 2023
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This study extends MFASIS to simulate 1.6 μm NIR channel reflectances with a neural network, enabling its use in model evaluation and data assimilation. A two-layer model was developed for cloud structure with optimized reflectance errors using IFS forecasts and ICON-D2 hindcasts. Mean absolute reflectance error achieved was 0.01 or less, much smaller than typical differences between observations and models.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 1803–1847, https://doi.org/10.5194/amt-16-1803-2023, https://doi.org/10.5194/amt-16-1803-2023, 2023
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We describe a new method for measuring the 3D spatial variations in water within clouds using the reflected light of the Sun viewed at multiple different angles by satellites. This is a great improvement over older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Leilei Kou, Zhengjian Lin, Haiyang Gao, Shujun Liao, and Piman Ding
Atmos. Meas. Tech., 16, 1723–1744, https://doi.org/10.5194/amt-16-1723-2023, https://doi.org/10.5194/amt-16-1723-2023, 2023
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Forward modeling of spaceborne millimeter-wave radar composed of eight submodules is presented. We quantify the uncertainties in radar reflectivity that may be caused by the physical model parameters via a sensitivity analysis. The simulations with improved and conventional settings are compared with CloudSat data, and the simulation results are evaluated and analyzed. The results are instructive to the optimization of forward modeling and microphysical parameter retrieval.
Heike Kalesse-Los, Anton Kötsche, Andreas Foth, Johannes Röttenbacher, Teresa Vogl, and Jonas Witthuhn
Atmos. Meas. Tech., 16, 1683–1704, https://doi.org/10.5194/amt-16-1683-2023, https://doi.org/10.5194/amt-16-1683-2023, 2023
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The Virga-Sniffer, a new modular open-source Python package tool to characterize full precipitation evaporation (so-called virga) from ceilometer cloud base height and vertically pointing cloud radar reflectivity time–height fields, is described. Results of its first application to RV Meteor observations during the EUREC4A field experiment in January–February 2020 are shown. About half of all detected clouds with bases below the trade inversion height were found to produce virga.
Yulan Hong, Stephen W. Nesbitt, Robert J. Trapp, and Larry Di Girolamo
Atmos. Meas. Tech., 16, 1391–1406, https://doi.org/10.5194/amt-16-1391-2023, https://doi.org/10.5194/amt-16-1391-2023, 2023
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Deep convective updrafts form overshooting tops (OTs) when they extend into the upper troposphere and lower stratosphere. An OT often indicates hazardous weather conditions. The global distribution of OTs is useful for understanding global severe weather conditions. The Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and Terra satellites provides 2 decades of records on the Earth–atmosphere system with stable orbits, which are used in this study to derive 20-year OT climatology.
Pragya Vishwakarma, Julien Delanoë, Susana Jorquera, Pauline Martinet, Frederic Burnet, Alistair Bell, and Jean-Charles Dupont
Atmos. Meas. Tech., 16, 1211–1237, https://doi.org/10.5194/amt-16-1211-2023, https://doi.org/10.5194/amt-16-1211-2023, 2023
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Cloud observations are necessary to characterize the cloud properties at local and global scales. The observations must be translated to cloud geophysical parameters. This paper presents the estimation of liquid water content (LWC) using radar and microwave radiometer (MWR) measurements. Liquid water path from MWR scales LWC and retrieves the scaling factor (ln a). The retrievals are compared with in situ observations. A climatology of ln a is built to estimate LWC using only radar information.
Bhupendra A. Raut, Paytsar Muradyan, Rajesh Sankaran, Robert C. Jackson, Seongha Park, Sean A. Shahkarami, Dario Dematties, Yongho Kim, Joseph Swantek, Neal Conrad, Wolfgang Gerlach, Sergey Shemyakin, Pete Beckman, Nicola J. Ferrier, and Scott M. Collis
Atmos. Meas. Tech., 16, 1195–1209, https://doi.org/10.5194/amt-16-1195-2023, https://doi.org/10.5194/amt-16-1195-2023, 2023
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We studied the stability of a blockwise phase correlation (PC) method to estimate cloud motion using a total sky imager (TSI). Shorter frame intervals and larger block sizes improve stability, while image resolution and color channels have minor effects. Raindrop contamination can be identified by the rotational motion of the TSI mirror. The correlations of cloud motion vectors (CMVs) from the PC method with wind data vary from 0.38 to 0.59. Optical flow vectors are more stable than PC vectors.
William K. Jones, Matthew W. Christensen, and Philip Stier
Atmos. Meas. Tech., 16, 1043–1059, https://doi.org/10.5194/amt-16-1043-2023, https://doi.org/10.5194/amt-16-1043-2023, 2023
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Geostationary weather satellites have been used to detect storm clouds since their earliest applications. However, this task remains difficult as imaging satellites cannot observe the strong vertical winds that are characteristic of storm clouds. Here we introduce a new method that allows us to detect the early development of storms and continue to track them throughout their lifetime, allowing us to study how their early behaviour affects subsequent weather.
Andrew M. Sayer, Luca Lelli, Brian Cairns, Bastiaan van Diedenhoven, Amir Ibrahim, Kirk D. Knobelspiesse, Sergey Korkin, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 969–996, https://doi.org/10.5194/amt-16-969-2023, https://doi.org/10.5194/amt-16-969-2023, 2023
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This paper presents a method to estimate the height of the top of clouds above Earth's surface using satellite measurements. It is based on light absorption by oxygen in Earth's atmosphere, which darkens the signal that a satellite will see at certain wavelengths of light. Clouds "shield" the satellite from some of this darkening, dependent on cloud height (and other factors), because clouds scatter light at these wavelengths. The method will be applied to the future NASA PACE mission.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-6, https://doi.org/10.5194/amt-2023-6, 2023
Revised manuscript accepted for AMT
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A new database is constructed from satellites comprising millions of deep convective clouds that spans the global tropics and subtropics and greater than 20 years. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirical study of the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
EGUsphere, https://doi.org/10.5194/egusphere-2023-181, https://doi.org/10.5194/egusphere-2023-181, 2023
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We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 16, 645–667, https://doi.org/10.5194/amt-16-645-2023, https://doi.org/10.5194/amt-16-645-2023, 2023
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In this work, we analyze polarized cloudbow observations by the airborne camera system specMACS to retrieve the cloud droplet size distribution defined by the effective radius (reff) and the effective variance (veff). Two case studies of trade-wind cumulus clouds observed during the EUREC4A field campaign are presented. The results are combined into maps of reff and veff with a very high spatial resolution (100 m × 100 m) that allow new insights into cloud microphysics.
Minrui Wang, Takashi Y. Nakajima, Woosub Roh, Masaki Satoh, Kentaroh Suzuki, Takuji Kubota, and Mayumi Yoshida
Atmos. Meas. Tech., 16, 603–623, https://doi.org/10.5194/amt-16-603-2023, https://doi.org/10.5194/amt-16-603-2023, 2023
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SMILE (a spectral misalignment in which a shift in the center wavelength appears as a distortion in the spectral image) was detected during our recent work. To evaluate how it affects the cloud retrieval products, we did a simulation of EarthCARE-MSI forward radiation, evaluating the error in simulated scenes from a global cloud system-resolving model and a satellite simulator. Our results indicated that the error from SMILE was generally small and negligible for oceanic scenes.
Ming Li, Husi Letu, Hiroshi Ishimoto, Shulei Li, Lei Liu, Takashi Y. Nakajima, Dabin Ji, Huazhe Shang, and Chong Shi
Atmos. Meas. Tech., 16, 331–353, https://doi.org/10.5194/amt-16-331-2023, https://doi.org/10.5194/amt-16-331-2023, 2023
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Influenced by the representativeness of ice crystal scattering models, the existing terahertz ice cloud remote sensing inversion algorithms still have significant uncertainties. We developed an ice cloud remote sensing retrieval algorithm of the ice water path and particle size from aircraft-based terahertz radiation measurements based on the Voronoi model. Validation revealed that the Voronoi model performs better than the sphere and hexagonal column models.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech., 15, 7119–7136, https://doi.org/10.5194/amt-15-7119-2022, https://doi.org/10.5194/amt-15-7119-2022, 2022
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Vertical profiles of latent heating are derived from GOES-16 to be used in convective initialization. They are compared with other latent heating products derived from NEXRAD and GPM satellites, and the results show that their values are very similar to the radar-derived products. Finally, using latent heating derived from GOES-16 for convective initialization shows improvements in precipitation forecasts, which are comparable to the results using latent heating derived from NEXRAD.
Simon Whitburn, Lieven Clarisse, Marc Crapeau, Thomas August, Tim Hultberg, Pierre François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 6653–6668, https://doi.org/10.5194/amt-15-6653-2022, https://doi.org/10.5194/amt-15-6653-2022, 2022
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With more than 15 years of measurements, the IASI radiance dataset is becoming a reference climate data record. Its exploitation for satellite applications requires an accurate and unbiased detection of cloud scenes. Here, we present a new cloud detection algorithm for IASI that is both sensitive and consistent over time. It is based on the use of a neural network, relying on IASI radiance information only and taking as a reference the last version of the operational IASI L2 cloud product.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-300, https://doi.org/10.5194/amt-2022-300, 2022
Revised manuscript accepted for AMT
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The Level 2 algorithms development of EarthCARE satellite mission requires realistic three-dimensional cloud and aerosols scenes along the satellite orbits. One of the best way to produce these scenes is to use high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This manuscript describes the production and validation of three EarthCARE test scenes.
Wenyu Wang, Zhenzhan Wang, Qiurui He, and Lanjie Zhang
Atmos. Meas. Tech., 15, 6489–6506, https://doi.org/10.5194/amt-15-6489-2022, https://doi.org/10.5194/amt-15-6489-2022, 2022
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This paper uses a neural network approach to retrieve the ice water path from FY-3B/MWHS polarimetric measurements, focusing on its unique 150 GHz quasi-polarized channels. The Level 2 product of CloudSat is used as the reference value for the neural network. The results show that the polarization information is helpful for the retrieval in scenes with thicker cloud ice, and the 150 GHz channels give a significant improvement compared to using only 183 GHz channels.
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
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The article investigates different S5P TROPOMI cloud retrieval algorithms for tropospheric trace gas retrievals. The cloud products show differences primarily over snow and ice and for scenes under sun glint. Some issues regarding across-track dependence are found for the cloud fractions as well as for the cloud heights.
Han Ding, Haoran Li, and Liping Liu
Atmos. Meas. Tech., 15, 6181–6200, https://doi.org/10.5194/amt-15-6181-2022, https://doi.org/10.5194/amt-15-6181-2022, 2022
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In this study, a framework for processing the Doppler spectra observations of a multi-mode pulse compression Ka–Ku cloud radar system is presented. We first proposed an approach to identify and remove the clutter signals in the Doppler spectrum. Then, we developed a new algorithm to remove the range sidelobe at the modes implementing the pulse compression technique. The radar observations from different modes were then merged using the shift-then-average method.
Andrew T. Prata, Roy G. Grainger, Isabelle A. Taylor, Adam C. Povey, Simon R. Proud, and Caroline A. Poulsen
Atmos. Meas. Tech., 15, 5985–6010, https://doi.org/10.5194/amt-15-5985-2022, https://doi.org/10.5194/amt-15-5985-2022, 2022
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Satellite observations are often used to track ash clouds and estimate their height, particle sizes and mass; however, satellite-based techniques are always associated with some uncertainty. We describe advances in a satellite-based technique that is used to estimate ash cloud properties for the June 2019 Raikoke (Russia) eruption. Our results are significant because ash warning centres increasingly require uncertainty information to correctly interpret,
aggregate and utilise the data.
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
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Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger
Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, https://doi.org/10.5194/amt-15-5415-2022, 2022
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Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
Willi Schimmel, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert
Atmos. Meas. Tech., 15, 5343–5366, https://doi.org/10.5194/amt-15-5343-2022, https://doi.org/10.5194/amt-15-5343-2022, 2022
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This study introduces the novel Doppler radar spectra-based machine learning approach VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn). VOODOO is a powerful probability-based extension to the existing Cloudnet hydrometeor target classification, enabling the detection of liquid-bearing cloud layers beyond complete lidar attenuation via user-defined p* threshold. VOODOO performs best for (multi-layer) stratiform and deep mixed-phase clouds with liquid water path > 100 g m−2.
Vikas Nataraja, Sebastian Schmidt, Hong Chen, Takanobu Yamaguchi, Jan Kazil, Graham Feingold, Kevin Wolf, and Hironobu Iwabuchi
Atmos. Meas. Tech., 15, 5181–5205, https://doi.org/10.5194/amt-15-5181-2022, https://doi.org/10.5194/amt-15-5181-2022, 2022
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A convolutional neural network (CNN) is introduced to retrieve cloud optical thickness (COT) from passive cloud imagery. The CNN, trained on large eddy simulations from the Sulu Sea, learns from spatial information at multiple scales to reduce cloud inhomogeneity effects. By considering the spatial context of a pixel, the CNN outperforms the traditional independent pixel approximation (IPA) across several cloud morphology metrics.
Rachel T. Pinker, Yingtao Ma, Wen Chen, Istvan Laszlo, Hongqing Liu, Hye-Yun Kim, and Jaime Daniels
Atmos. Meas. Tech., 15, 5077–5094, https://doi.org/10.5194/amt-15-5077-2022, https://doi.org/10.5194/amt-15-5077-2022, 2022
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Scene-dependent narrow-to-broadband transformations are developed to facilitate the use of observations from the Advanced Baseline Imager (ABI), the primary instrument on GOES-R, to derive surface shortwave radiative fluxes. This is a first NOAA product at the high resolution of about 5 k over the contiguous United States (CONUS) region. The product is archived and can be downloaded from the NOAA Comprehensive Large Array-data Stewardship System (CLASS).
Mariko Oue, Stephen M. Saleeby, Peter J. Marinescu, Pavlos Kollias, and Susan C. van den Heever
Atmos. Meas. Tech., 15, 4931–4950, https://doi.org/10.5194/amt-15-4931-2022, https://doi.org/10.5194/amt-15-4931-2022, 2022
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This study provides an optimization of radar observation strategies to better capture convective cell evolution in clean and polluted environments as well as a technique for the optimization. The suggested optimized radar observation strategy is to better capture updrafts at middle and upper altitudes and precipitation particle evolution of isolated deep convective clouds. This study sheds light on the challenge of designing remote sensing observation strategies in pre-field campaign periods.
Jean-Marie Lalande, Guillaume Bourmaud, Pierre Minvielle, and Jean-François Giovannelli
Atmos. Meas. Tech., 15, 4411–4429, https://doi.org/10.5194/amt-15-4411-2022, https://doi.org/10.5194/amt-15-4411-2022, 2022
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In this paper we describe the implementation of an interpolation–prediction estimator applied to cloud properties derived from CloudSat observations. The objective is to evaluate the uncertainty associated with the estimated quantity. The model developed in this study can be valuable for satellite applications (GPS, telecommunication) as well as for cloud product comparisons. This paper is didactic and beneficial for anyone interested in kriging estimators.
Julia Fuchs, Hendrik Andersen, Jan Cermak, Eva Pauli, and Rob Roebeling
Atmos. Meas. Tech., 15, 4257–4270, https://doi.org/10.5194/amt-15-4257-2022, https://doi.org/10.5194/amt-15-4257-2022, 2022
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Two cloud-masking approaches, a local and a regional approach, using high-resolution satellite data are developed and validated for the region of Paris to improve applicability for analyses of urban effects on low clouds. We found that cloud masks obtained from the regional approach are more appropriate for the high-resolution analysis of locally induced cloud processes. Its applicability is tested for the analysis of typical fog conditions over different surface types.
Eleni Tetoni, Florian Ewald, Martin Hagen, Gregor Köcher, Tobias Zinner, and Silke Groß
Atmos. Meas. Tech., 15, 3969–3999, https://doi.org/10.5194/amt-15-3969-2022, https://doi.org/10.5194/amt-15-3969-2022, 2022
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We use the C-band POLDIRAD and the Ka-band MIRA-35 to perform snowfall dual-wavelength polarimetric radar measurements. We develop an ice microphysics retrieval for mass, apparent shape, and median size of the particle size distribution by comparing observations to T-matrix ice spheroid simulations while varying the mass–size relationship. We furthermore show how the polarimetric measurements from POLDIRAD help to narrow down ambiguities between ice particle shape and size.
Assia Arouf, Hélène Chepfer, Thibault Vaillant de Guélis, Marjolaine Chiriaco, Matthew D. Shupe, Rodrigo Guzman, Artem Feofilov, Patrick Raberanto, Tristan S. L'Ecuyer, Seiji Kato, and Michael R. Gallagher
Atmos. Meas. Tech., 15, 3893–3923, https://doi.org/10.5194/amt-15-3893-2022, https://doi.org/10.5194/amt-15-3893-2022, 2022
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We proposed new estimates of the surface longwave (LW) cloud radiative effect (CRE) derived from observations collected by a space-based lidar on board the CALIPSO satellite and radiative transfer computations. Our estimate appropriately captures the surface LW CRE annual variability over bright polar surfaces, and it provides a dataset more than 13 years long.
Baike Xi, Xiquan Dong, Xiaojian Zheng, and Peng Wu
Atmos. Meas. Tech., 15, 3761–3777, https://doi.org/10.5194/amt-15-3761-2022, https://doi.org/10.5194/amt-15-3761-2022, 2022
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This study develops an innovative method to determine the cloud phases over the Southern Ocean (SO) using the combination of radar and lidar measurements during the ship-based field campaign of MARCUS. Results from our study show that the low-level, deep, and shallow cumuli are dominant, and the mixed-phase clouds occur more than single phases over the SO. The mixed-phase cloud properties are similar to liquid-phase (ice-phase) clouds in the midlatitudes (polar) region of the SO.
Adrien Guyot, Alain Protat, Simon P. Alexander, Andrew R. Klekociuk, Peter Kuma, and Adrian McDonald
Atmos. Meas. Tech., 15, 3663–3681, https://doi.org/10.5194/amt-15-3663-2022, https://doi.org/10.5194/amt-15-3663-2022, 2022
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Ceilometers are instruments that are widely deployed as part of operational networks. They are usually not able to detect cloud phase. Here, we propose an evaluation of various methods to detect supercooled liquid water with ceilometer observations, using an extensive dataset from Davis, Antarctica. Our results highlight the possibility for ceilometers to detect supercooled liquid water in clouds.
Xiaotong Li, Baozhu Wang, Bo Qiu, and Chao Wu
Atmos. Meas. Tech., 15, 3629–3639, https://doi.org/10.5194/amt-15-3629-2022, https://doi.org/10.5194/amt-15-3629-2022, 2022
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The all-sky camera images can reflect the local cloud cover, which is considerable for astronomical observatory site selection. Therefore, the realization of automatic classification of the images is very important. In this paper, three cloud cover features are proposed to classify the images. The proposed method is evaluated on a large dataset, and the method achieves an accuracy of 96.58 % and F1_score of 96.24 %, which greatly improves the efficiency of automatic processing of the images.
Huige Di, Yun Yuan, Qing Yan, Wenhui Xin, Shichun Li, Jun Wang, Yufeng Wang, Lei Zhang, and Dengxin Hua
Atmos. Meas. Tech., 15, 3555–3567, https://doi.org/10.5194/amt-15-3555-2022, https://doi.org/10.5194/amt-15-3555-2022, 2022
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It is necessary to correctly evaluate the amount of cloud water resources in an area. Currently, there is a lack of effective observation methods for atmospheric column condensate evaluation. We propose a method for atmospheric column condensate by combining millimetre cloud radar, lidar and microwave radiometers. The method can realise determination of atmospheric column condensate. The variation of cloud before precipitation is considered, and the atmospheric column is deduced and obtained.
Cited articles
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Spaceborne Cloud and Precipitation Radars: Status, Challenges, and Ways Forward,
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Short summary
A method for estimating microphysical properties of ice clouds based on radar measurements is presented. The algorithm exploits the information provided by differences in the radar response at different frequency bands in relation to changes in the snow morphology. The inversion scheme is based on a statistical relation between the radar simulations and the properties of snow calculated from in-cloud sampling.
A method for estimating microphysical properties of ice clouds based on radar measurements is...