Articles | Volume 11, issue 10
https://doi.org/10.5194/amt-11-5471-2018
© Author(s) 2018. 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-11-5471-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Oct 2018
Research article |
| 05 Oct 2018
| 05 Oct 2018
Retrieval of snowflake microphysical properties from multifrequency radar observations
Jussi Leinonen
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Joint Institute for Earth System Science and Engineering, University of California, Los Angeles, California, USA
Matthew D. Lebsock
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Simone Tanelli
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Ousmane O. Sy
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Brenda Dolan
Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado, USA
Randy J. Chase
Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
Joseph A. Finlon
Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
Annakaisa von Lerber
Radar Science, Finnish Meteorological Institute, Helsinki, Finland
Dmitri Moisseev
Radar Science, Finnish Meteorological Institute, Helsinki, Finland
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, Finland
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Julia Schneider, Kristina Höhler, Paavo Heikkilä, Jorma Keskinen, Barbara Bertozzi, Pia Bogert, Tobias Schorr, Nsikanabasi Silas Umo, Franziska Vogel, Zoé Brasseur, Yusheng Wu, Simo Hakala, Jonathan Duplissy, Dmitri Moisseev, Markku Kulmala, Michael P. Adams, Benjamin J. Murray, Kimmo Korhonen, Liqing Hao, Erik S. Thomson, Dimitri Castarède, Thomas Leisner, Tuukka Petäjä, and Ottmar Möhler
Atmos. Chem. Phys., 21, 3899–3918, https://doi.org/10.5194/acp-21-3899-2021, https://doi.org/10.5194/acp-21-3899-2021, 2021
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By triggering the formation of ice crystals, ice-nucleating particles (INP) strongly influence cloud formation. Continuous, long-term measurements are needed to characterize the atmospheric INP variability. Here, a first long-term time series of INP spectra measured in the boreal forest for more than 1 year is presented, showing a clear seasonal cycle. It is shown that the seasonal dependency of INP concentrations and prevalent INP types is driven by the abundance of biogenic aerosol.
Tanel Voormansik, Roberto Cremonini, Piia Post, and Dmitri Moisseev
Hydrol. Earth Syst. Sci., 25, 1245–1258, https://doi.org/10.5194/hess-25-1245-2021, https://doi.org/10.5194/hess-25-1245-2021, 2021
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A long set of operational polarimetric weather radar rainfall accumulations from Estonia and Italy are generated and investigated. Results show that the combined product of specific differential phase and horizontal reflectivity yields the best results when compared to rain gauge measurements. The specific differential-phase-based product overestimates weak precipitation, and the horizontal-reflectivity-based product underestimates heavy rainfall in all analysed accumulation periods.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
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Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Luis Millán, Richard Roy, and Matthew Lebsock
Atmos. Meas. Tech., 13, 5193–5205, https://doi.org/10.5194/amt-13-5193-2020, https://doi.org/10.5194/amt-13-5193-2020, 2020
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This paper describes the feasibility of using a differential absorption radar technique for the remote sensing of total column water vapor from a spaceborne platform.
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.
F. Joseph Turk, Svetla Hristova-Veleva, Stephen L. Durden, Simone Tanelli, Ousmane Sy, G. David Emmitt, Steve Greco, and Sara Q. Zhang
Atmos. Meas. Tech., 13, 4521–4537, https://doi.org/10.5194/amt-13-4521-2020, https://doi.org/10.5194/amt-13-4521-2020, 2020
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The mechanisms linking convection and air motion are major factors in much of the uncertainty in weather prediction, but complementary measurements of these quantities are rarely taken in close proximity. These quantities are shown from the 2017 Convective Processes Experiment (CPEX), wherein cloud and vertical air motion winds derived from the APR-2 airborne Doppler radar are combined with joint Doppler wind lidar (DAWN) measurements in the aerosol-rich regions surrounding the convection.
Haoran Li, Jussi Tiira, Annakaisa von Lerber, and Dmitri Moisseev
Atmos. Chem. Phys., 20, 9547–9562, https://doi.org/10.5194/acp-20-9547-2020, https://doi.org/10.5194/acp-20-9547-2020, 2020
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A method for classifying rimed and unrimed snow based on X- and Ka-band Doppler radar measurements is developed and applied to synergetic radar observations collected during BAECC 2014. The results show that the radar-observed melting layer properties are highly related to the precipitation intensity. The previously reported bright band sagging is mainly connected to the increase in precipitation intensity, while riming plays a secondary role.
Tuukka Petäjä, Ella-Maria Duplissy, Ksenia Tabakova, Julia Schmale, Barbara Altstädter, Gerard Ancellet, Mikhail Arshinov, Yurii Balin, Urs Baltensperger, Jens Bange, Alison Beamish, Boris Belan, Antoine Berchet, Rossana Bossi, Warren R. L. Cairns, Ralf Ebinghaus, Imad El Haddad, Beatriz Ferreira-Araujo, Anna Franck, Lin Huang, Antti Hyvärinen, Angelika Humbert, Athina-Cerise Kalogridis, Pavel Konstantinov, Astrid Lampert, Matthew MacLeod, Olivier Magand, Alexander Mahura, Louis Marelle, Vladimir Masloboev, Dmitri Moisseev, Vaios Moschos, Niklas Neckel, Tatsuo Onishi, Stefan Osterwalder, Aino Ovaska, Pauli Paasonen, Mikhail Panchenko, Fidel Pankratov, Jakob B. Pernov, Andreas Platis, Olga Popovicheva, Jean-Christophe Raut, Aurélie Riandet, Torsten Sachs, Rosamaria Salvatori, Roberto Salzano, Ludwig Schröder, Martin Schön, Vladimir Shevchenko, Henrik Skov, Jeroen E. Sonke, Andrea Spolaor, Vasileios K. Stathopoulos, Mikko Strahlendorff, Jennie L. Thomas, Vito Vitale, Sterios Vratolis, Carlo Barbante, Sabine Chabrillat, Aurélien Dommergue, Konstantinos Eleftheriadis, Jyri Heilimo, Kathy S. Law, Andreas Massling, Steffen M. Noe, Jean-Daniel Paris, André S. H. Prévôt, Ilona Riipinen, Birgit Wehner, Zhiyong Xie, and Hanna K. Lappalainen
Atmos. Chem. Phys., 20, 8551–8592, https://doi.org/10.5194/acp-20-8551-2020, https://doi.org/10.5194/acp-20-8551-2020, 2020
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The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. Here we summarize initial results from our integrative project exploring the Arctic environment and pollution to deliver data products, metrics, and indicators for stakeholders.
Jussi Leinonen and Alexis Berne
Atmos. Meas. Tech., 13, 2949–2964, https://doi.org/10.5194/amt-13-2949-2020, https://doi.org/10.5194/amt-13-2949-2020, 2020
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The appearance of snowflakes provides a signature of the atmospheric processes that created them. To get this information from large numbers of snowflake images, automated analysis using computer image recognition is needed. In this work, we use a neural network that learns the structure of the snowflake images to divide a snowflake dataset into classes corresponding to different sizes and structures. Unlike with most comparable methods, only minimal input from a human expert is needed.
Jussi Tiira and Dmitri Moisseev
Atmos. Meas. Tech., 13, 1227–1241, https://doi.org/10.5194/amt-13-1227-2020, https://doi.org/10.5194/amt-13-1227-2020, 2020
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Modern weather radars are sensitive for properties of precipitating snow particles, such as their sizes, shapes and number concentration. Vertical profiles of such radar measurements can be used for studying the processes through which snow is formed. We created a profile classification method for this purpose, and we show how it can be used for automatic identification of snow growth processes. Being able to identify the processes is expected to improve radar-based precipitation estimation.
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.
Jeffrey S. Reid, Derek J. Posselt, Kathleen Kaku, Robert A. Holz, Gao Chen, Edwin W. Eloranta, Ralph E. Kuehn, Sarah Woods, Jianglong Zhang, Bruce Anderson, T. Paul Bui, Glenn S. Diskin, Patrick Minnis, Michael J. Newchurch, Simone Tanelli, Charles R. Trepte, K. Lee Thornhill, and Luke D. Ziemba
Atmos. Chem. Phys., 19, 11413–11442, https://doi.org/10.5194/acp-19-11413-2019, https://doi.org/10.5194/acp-19-11413-2019, 2019
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The scientific community often focuses on the vertical transport of pollutants by clouds for those with bases at the planetary boundary layer (such as typical fair-weather cumulus) and the outflow from thunderstorms at their tops. We demonstrate complex aerosol and cloud features formed in mid-level thunderstorm outflow. These layers have strong relationships to mid-level tropospheric clouds, an important but difficult to model or monitor cloud regime for climate studies.
Luis F. Millán, Matthew D. Lebsock, and Joao Teixeira
Atmos. Chem. Phys., 19, 8491–8502, https://doi.org/10.5194/acp-19-8491-2019, https://doi.org/10.5194/acp-19-8491-2019, 2019
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The synergy of the collocated Advanced Microwave Scanning Radiometer (AMSR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global estimates of marine boundary layer water vapor. AMSR provides the total column water vapor, while MODIS provides the water vapor above the cloud layers. The difference between the two gives the vapor between the surface and the cloud top, which may be interpreted as the boundary layer water vapor.
Joseph A. Finlon, Greg M. McFarquhar, Stephen W. Nesbitt, Robert M. Rauber, Hugh Morrison, Wei Wu, and Pengfei Zhang
Atmos. Chem. Phys., 19, 3621–3643, https://doi.org/10.5194/acp-19-3621-2019, https://doi.org/10.5194/acp-19-3621-2019, 2019
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A new approach describing the relationship between ice crystal mass (m) and dimension (D) is derived, characterizing it as a set of
equally realizableparameters based on the natural variability in cloud conditions observed by aircraft over the Great Plains. Results from this approach address shortcomings of microphysical parameterization schemes and remote sensing retrievals that employ a single m–D relation for a given ice species or environment.
Mark Richardson, Jussi Leinonen, Heather Q. Cronk, James McDuffie, Matthew D. Lebsock, and Graeme L. Stephens
Atmos. Meas. Tech., 12, 1717–1737, https://doi.org/10.5194/amt-12-1717-2019, https://doi.org/10.5194/amt-12-1717-2019, 2019
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We retrieve cloud properties, including geometric thickness, by combining hyperspectral Orbiting Carbon Observatory-2 (OCO-2) A-band measurements with CALIPSO lidar. This uses cloudy scene data that are not used in OCO-2's main mission, which is aimed at clear-sky atmospheric CO2 abundance. This is the first retrieval using such hyperspectral information and promises to provide a unique constraint on the properties of low liquid clouds over the ocean.
Gwo-Jong Huang, Viswanathan N. Bringi, Andrew J. Newman, Gyuwon Lee, Dmitri Moisseev, and Branislav M. Notaroš
Atmos. Meas. Tech., 12, 1409–1427, https://doi.org/10.5194/amt-12-1409-2019, https://doi.org/10.5194/amt-12-1409-2019, 2019
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This paper proposes a method for snow rate (SR) estimation using observations collected by NASA dual-frequency dual-polarized (D3R) radar during the GPM Cold-season Precipitation Experiment (GCPEx). The new method utilizes dual-wavelength radar reflectivity ratio (DWR) and 2-D-video disdrometer (2DVD) measurements to improve SR estimation accuracy. It is validated by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a Pluvio gauge for an entire GCPEx synoptic event.
Richard J. Roy, Matthew Lebsock, Luis Millán, Robert Dengler, Raquel Rodriguez Monje, Jose V. Siles, and Ken B. Cooper
Atmos. Meas. Tech., 11, 6511–6523, https://doi.org/10.5194/amt-11-6511-2018, https://doi.org/10.5194/amt-11-6511-2018, 2018
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The measurement of water vapor profiles inside clouds with high spatial resolution represents an outstanding problem in atmospheric remote sensing. Here we present measurements from a proof-of-concept millimeter-wave (170 GHz) cloud radar aimed at filling this observational gap, and demonstrate the ability to retrieve in-cloud water vapor profiles with high precision and resolution. This technology could meaningfully impact future satellite-based measurements of water vapor.
David Ian Duncan, Christian D. Kummerow, Brenda Dolan, and Veljko Petković
Atmos. Meas. Tech., 11, 4389–4411, https://doi.org/10.5194/amt-11-4389-2018, https://doi.org/10.5194/amt-11-4389-2018, 2018
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Satellites are fairly good at detecting and quantifying rainfall over oceans, but the light rainfall characteristic of high latitudes and stratocumulus areas is harder to sense for passive sensors. The method presented extends the sensitivity of passive measurements to light rain by leveraging radar data and measurements of raindrop distributions. This method may help to close the gap between global precipitation estimates at high latitudes and maximize the utility of passive sensors.
Marta Tecla Falconi, Annakaisa von Lerber, Davide Ori, Frank Silvio Marzano, and Dmitri Moisseev
Atmos. Meas. Tech., 11, 3059–3079, https://doi.org/10.5194/amt-11-3059-2018, https://doi.org/10.5194/amt-11-3059-2018, 2018
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Estimating snowfall intensity from satellite and ground-based radar missions requires accurate retrieval models. Reflectivity–snowfall relations are obtained at cm and mm wavelengths using data recorded during the Biogenic Aerosols Effects on Clouds and Climate (BAECC) campaign in Finland. Lightly, moderately and heavily rimed snow cases are identified. Numerical simulations are performed to relate snowflake microphysical (video disdrometer) and multifrequency backscattering properties (radars).
Brian H. Kahn, Georgios Matheou, Qing Yue, Thomas Fauchez, Eric J. Fetzer, Matthew Lebsock, João Martins, Mathias M. Schreier, Kentaroh Suzuki, and João Teixeira
Atmos. Chem. Phys., 17, 9451–9468, https://doi.org/10.5194/acp-17-9451-2017, https://doi.org/10.5194/acp-17-9451-2017, 2017
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The global-scale patterns of subtropical marine boundary layer clouds are investigated with coincident NASA A-train satellite and reanalysis data. This study is novel in that all data are used at the finest spatial and temporal resolution possible. Our results are consistent with surface-based data and suggest that the combination of satellite and reanalysis data sets have potential to add to the global context of our understanding of the subtropical cumulus-dominated marine boundary layer.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
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After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
Roberto Cremonini, Dmitri Moisseev, and Venkatachalam Chandrasekar
Atmos. Meas. Tech., 9, 5063–5075, https://doi.org/10.5194/amt-9-5063-2016, https://doi.org/10.5194/amt-9-5063-2016, 2016
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Although high-spatial-resolution weather radar observations are of primary relevance for urban hydrology, weather radar siting and characterization are challenging in an urban environment. Buildings, masts and trees cause partial beam blockages and clutter that seriously affect the observations. For the first time, this paper investigates the benefits of using airborne laser scanner (ALS) data for quantitative estimations of partial beam blockages in an urban environment.
Jussi Tiira, Dmitri N. Moisseev, Annakaisa von Lerber, Davide Ori, Ali Tokay, Larry F. Bliven, and Walter Petersen
Atmos. Meas. Tech., 9, 4825–4841, https://doi.org/10.5194/amt-9-4825-2016, https://doi.org/10.5194/amt-9-4825-2016, 2016
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In this study winter measurements collected in Southern Finland are used to document microphysical properties of falling snow. It is shown that a new video imager can be used for such studies. Snow properties do vary between winters.
Luis Millán, Matthew Lebsock, Nathaniel Livesey, and Simone Tanelli
Atmos. Meas. Tech., 9, 2633–2646, https://doi.org/10.5194/amt-9-2633-2016, https://doi.org/10.5194/amt-9-2633-2016, 2016
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We discuss the theoretical capabilities of a radar technique to measure profiles of water vapor in cloudy/precipitating areas. The method uses two radar pulses at different frequencies near the 183 GHz H2O absorption line to determine water vapor profiles by measuring the differential absorption on and off the line. Results of inverting synthetic data assuming a satellite radar are presented.
M. D. Lebsock, K. Suzuki, L. F. Millán, and P. M. Kalmus
Atmos. Meas. Tech., 8, 3631–3645, https://doi.org/10.5194/amt-8-3631-2015, https://doi.org/10.5194/amt-8-3631-2015, 2015
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This paper describes the feasibility of using a differential absorption radar technique for the remote sensing of water vapor within clouds near the Earth surface from a spaceborne platform. The proposed methodology is shown to be theoretically achievable and complimentary to existing water vapor remote sensing methods.
S. Sanghavi, M. Lebsock, and G. Stephens
Atmos. Meas. Tech., 8, 3601–3616, https://doi.org/10.5194/amt-8-3601-2015, https://doi.org/10.5194/amt-8-3601-2015, 2015
J. Leinonen, M. D. Lebsock, S. Tanelli, K. Suzuki, H. Yashiro, and Y. Miyamoto
Atmos. Meas. Tech., 8, 3493–3517, https://doi.org/10.5194/amt-8-3493-2015, https://doi.org/10.5194/amt-8-3493-2015, 2015
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Using multiple frequencies in cloud and precipitation radars enables them to be both sensitive enough to detect thin clouds and to penetrate heavy precipitation, profiling the entire vertical structure of the atmospheric component of the water cycle. Here, we evaluate the performance of a potential future three-frequency space-based radar system by simulating its observations using data from a high-resolution global atmospheric model.
L. Millán, M. Lebsock, N. Livesey, S. Tanelli, and G. Stephens
Atmos. Meas. Tech., 7, 3959–3970, https://doi.org/10.5194/amt-7-3959-2014, https://doi.org/10.5194/amt-7-3959-2014, 2014
A. Hirsikko, E. J. O'Connor, M. Komppula, K. Korhonen, A. Pfüller, E. Giannakaki, C. R. Wood, M. Bauer-Pfundstein, A. Poikonen, T. Karppinen, H. Lonka, M. Kurri, J. Heinonen, D. Moisseev, E. Asmi, V. Aaltonen, A. Nordbo, E. Rodriguez, H. Lihavainen, A. Laaksonen, K. E. J. Lehtinen, T. Laurila, T. Petäjä, M. Kulmala, and Y. Viisanen
Atmos. Meas. Tech., 7, 1351–1375, https://doi.org/10.5194/amt-7-1351-2014, https://doi.org/10.5194/amt-7-1351-2014, 2014
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Improving solution availability and temporal consistency of an optimal-estimation physical retrieval for ground-based thermodynamic boundary layer profiling
An improved geolocation methodology for spaceborne radar and lidar systems
Combining low- and high-frequency microwave radiometer measurements from the MOSAiC expedition for enhanced water vapour products
HAMSTER: Hyperspectral Albedo Maps dataset with high Spatial and TEmporal Resolution
Global-scale gravity wave analysis methodology for the ESA Earth Explorer 11 candidate CAIRT
Retrieval of pseudo-BRDF-adjusted surface reflectance at 440 nm from the Geostationary Environmental Monitoring Spectrometer (GEMS)
Drop size distribution retrieval using dual-polarization radar at C-band and S-band
Thermal tides in the middle atmosphere at mid-latitudes measured with a ground-based microwave radiometer
Global sensitivity analysis of simulated remote sensing polarimetric observations over snow
Improving the Gaussianity of radar reflectivity departures between observations and simulations using symmetric rain rates
On the temperature stability requirements of free-running Nd:YAG lasers for atmospheric temperature profiling through the rotational Raman technique
Limitations in wavelet analysis of non-stationary atmospheric gravity wave signatures in temperature profiles
A new non-linearity correction method for the spectrum from the Geostationary Inferometric Infrared Sounder on board Fengyun-4 satellites and its preliminary assessments
Determination of high-precision tropospheric delays using crowdsourced smartphone GNSS data
Unfiltering of the EarthCARE Broadband Radiometer (BBR) observations: the BM-RAD product
Variance estimations in the presence of intermittent interference and their applications to incoherent scatter radar signal processing
A clustering-based method for identifying and tracking squall lines
A multi-instrument fuzzy logic boundary-layer-top detection algorithm
Aeolus Lidar Surface Returns (LSR) at 355 nm as a new Aeolus L2A Phase-F product
Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models
Scale separation for gravity wave analysis from 3D temperature observations in the mesosphere and lower thermosphere (MLT) region
Estimating the refractivity bias of FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) radio occultation in the deep troposphere
High Spectral Resolution Lidar – generation 2 (HSRL-2) retrievals of ocean surface wind speed: methodology and evaluation
Retrieval of top-of-atmosphere fluxes from combined EarthCARE LiDAR, imager and broadband radiometer observations: the BMA-FLX product
Dual adaptive differential threshold method for automated detection of faint and strong echo features in radar observations of winter storms
Noise filtering options for conically scanning Doppler lidar measurements with low pulse accumulation
Comparative experimental validation of microwave hyperspectral atmospheric soundings in clear-sky conditions
Measuring rainfall using microwave links: the influence of temporal sampling
Drone-based photogrammetry combined with deep learning to estimate hail size distributions and melting of hail on the ground
Determination of low-level temperature profiles from microwave radiometer observations during rain
The High lAtitude sNowfall Detection and Estimation aLgorithm for ATMS (HANDEL-ATMS): a new algorithm for snowfall retrieval at high latitudes
Next-generation radiance unfiltering process for the Clouds and the Earth's Radiant Energy System instrument
Improved rain event detection in commercial microwave link time series via combination with MSG SEVIRI data
A directional surface reflectance climatology determined from TROPOMI observations
Investigation of gravity waves using measurements from a sodium temperature/wind lidar operated in multi-direction mode
Sampling the diurnal and annual cycles of the Earth’s energy imbalance with constellations of satellite-borne radiometers
An improved BRDF hotspot model and its use in VLIDORT for studying the impact of atmospheric scattering on hotspot directional signatures in the atmosphere
A multi-decadal time series of upper stratospheric temperature profiles from Odin-OSIRIS limb-scattered spectra
Observations of Tall-Building Wakes Using a Scanning Doppler Lidar
CALOTRITON: a convective boundary layer height estimation algorithm from ultra-high-frequency (UHF) wind profiler data
Enhancing consistency of microphysical properties of precipitation across the melting layer in dual-frequency precipitation radar data
Analysis of the measurement uncertainty for a 3D wind-LiDAR
Profiling the molecular destruction rates of temperature and humidity as well as the turbulent kinetic energy dissipation in the convective boundary layer
Forward operator for polarimetric radio occultation measurements
Assessing atmospheric gravity wave spectra in the presence of observational gaps
Joint 1DVar retrievals of tropospheric temperature and water vapor from Global Navigation Satellite System radio occultation (GNSS-RO) and microwave radiometer observations
Mispointing characterization and Doppler velocity correction for the conically scanning WIVERN Doppler radar
Radar and environment-based hail damage estimates using machine learning
A new power-law model for μ–Λ relationships in convective and stratiform rainfall
Suppression of precipitation bias in wind velocities from continuous-wave Doppler lidars
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
Atmos. Meas. Tech., 17, 6603–6624, https://doi.org/10.5194/amt-17-6603-2024, https://doi.org/10.5194/amt-17-6603-2024, 2024
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Continuous profile observations of temperature and humidity in the lowest part of the atmosphere are essential for the evaluation of numerical weather prediction models and data assimilation for better weather forecasts. Such profiles can be retrieved from passive ground-based remote sensing instruments like infrared spectrometers and microwave radiometers. In this study, we describe three recent modifications to the retrieval framework TROPoe for improved temperature and humidity profiles.
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024, https://doi.org/10.5194/amt-17-6301-2024, 2024
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The paper presents a comprehensive approach to improve the geolocation accuracy of spaceborne radar and lidar systems, crucial for the successful interpretation of data from the upcoming EarthCARE mission. The paper details the technical background of the presented methods and various examples of geolocation analyses, including a short period of CloudSat observations when the star tracker was not operating properly and lifetime statistics from the CloudSat and CALIPSO missions.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
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We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Giulia Roccetti, Luca Bugliaro, Felix Gödde, Claudia Emde, Ulrich Hamann, Mihail Manev, Michael Fritz Sterzik, and Cedric Wehrum
Atmos. Meas. Tech., 17, 6025–6046, https://doi.org/10.5194/amt-17-6025-2024, https://doi.org/10.5194/amt-17-6025-2024, 2024
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The amount of sunlight reflected by the Earth’s surface (albedo) is vital for the Earth's radiative system. While satellite instruments offer detailed spatial and temporal albedo maps, they only cover seven wavelength bands. We generate albedo maps that fully span the visible and near-infrared range using a machine learning algorithm. These maps reveal how the reflectivity of different land surfaces varies throughout the year. Our dataset enhances the understanding of the Earth's energy balance.
Sebastian Rhode, Peter Preusse, Jörn Ungermann, Inna Polichtchouk, Kaoru Sato, Shingo Watanabe, Manfred Ern, Karlheinz Nogai, Björn-Martin Sinnhuber, and Martin Riese
Atmos. Meas. Tech., 17, 5785–5819, https://doi.org/10.5194/amt-17-5785-2024, https://doi.org/10.5194/amt-17-5785-2024, 2024
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We investigate the capabilities of a proposed satellite mission, CAIRT, for observing gravity waves throughout the middle atmosphere and present the necessary methodology for in-depth wave analysis. Our findings suggest that such a satellite mission is highly capable of resolving individual wave parameters and could give new insights into the role of gravity waves in general atmospheric circulation and atmospheric processes.
Suyoung Sim, Sungwon Choi, Daeseong Jung, Jongho Woo, Nayeon Kim, Sungwoo Park, Honghee Kim, Ukkyo Jeong, Hyunkee Hong, and Kyung-Soo Han
Atmos. Meas. Tech., 17, 5601–5618, https://doi.org/10.5194/amt-17-5601-2024, https://doi.org/10.5194/amt-17-5601-2024, 2024
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This study evaluates the use of background surface reflectance (BSR) derived from a semi-empirical bidirectional reflectance distribution function (BRDF) model based on GEMS satellite images. Analysis shows that BSR provides improved accuracy and stability compared to Lambertian-equivalent reflectivity (LER). These results indicate that BSR can significantly enhance climate analysis and air quality monitoring, making it a promising tool for accurate environmental satellite applications.
Daniel Durbin, Yadong Wang, and Pao-Liang Chang
Atmos. Meas. Tech., 17, 5397–5411, https://doi.org/10.5194/amt-17-5397-2024, https://doi.org/10.5194/amt-17-5397-2024, 2024
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A method for determining drop size distributions (DSDs) for rain using radar measurements from two frequencies at two polarizations is presented. Following some preprocessing and quality control, radar measurements are incorporated into a model that uses swarm intelligence to seek the most suitable DSD to produce the input measurements.
Witali Krochin, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 17, 5015–5028, https://doi.org/10.5194/amt-17-5015-2024, https://doi.org/10.5194/amt-17-5015-2024, 2024
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Atmospheric tides are global-scale oscillations with periods of a fraction of a day. Their observation in the middle atmosphere is challenging and rare, as it requires continuous measurements with a high temporal resolution. In this paper, temperature time series of a ground-based microwave radiometer were analyzed with a spectral filter to derive thermal tide amplitudes and phases in an altitude range of 25–50 km at the geographical locations of Payerne and Bern (Switzerland).
Matteo Ottaviani, Gabriel Harris Myers, and Nan Chen
Atmos. Meas. Tech., 17, 4737–4756, https://doi.org/10.5194/amt-17-4737-2024, https://doi.org/10.5194/amt-17-4737-2024, 2024
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We analyze simulated polarization observations over snow to investigate the capabilities of remote sensing to determine surface and atmospheric properties in snow-covered regions. Polarization measurements are demonstrated to aid in the determination of snow grain shape, ice crystal roughness, and the vertical distribution of impurities in the snow–atmosphere system, data that are critical for estimating snow albedo for use in climate models.
Yudong Gao, Lidou Huyan, Zheng Wu, and Bojun Liu
Atmos. Meas. Tech., 17, 4675–4686, https://doi.org/10.5194/amt-17-4675-2024, https://doi.org/10.5194/amt-17-4675-2024, 2024
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A symmetric error model built by symmetric rain rates handles the non-Gaussian error structure of the reflectivity error. The accuracy and linearization of rain rates can further improve the Gaussianity.
José Alex Zenteno-Hernández, Adolfo Comerón, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo
Atmos. Meas. Tech., 17, 4687–4694, https://doi.org/10.5194/amt-17-4687-2024, https://doi.org/10.5194/amt-17-4687-2024, 2024
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We study how the spectral characteristics of a solid-state laser in an atmospheric temperature profiling lidar using the Raman technique impact the temperature retrieval accuracy. We find that the spectral widening, with respect to a seeded laser, has virtually no impact, while crystal-rod temperature variations in the laser must be kept within a range of 1 K for the uncertainty in the atmospheric temperature below 1 K. The study is carried out through spectroscopy simulations.
Robert Reichert, Natalie Kaifler, and Bernd Kaifler
Atmos. Meas. Tech., 17, 4659–4673, https://doi.org/10.5194/amt-17-4659-2024, https://doi.org/10.5194/amt-17-4659-2024, 2024
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Imagine you want to determine how quickly the pitch of a passing ambulance’s siren changes. If the vehicle is traveling slowly, the pitch changes only slightly, but if it is traveling fast, the pitch also changes rapidly. In a similar way, the wind in the middle atmosphere modulates the wavelength of atmospheric gravity waves. We have investigated the question of how strong the maximum wind may be so that the change in wavelength can still be determined with the help of wavelet transformation.
Qiang Guo, Yuning Liu, Xin Wang, and Wen Hui
Atmos. Meas. Tech., 17, 4613–4627, https://doi.org/10.5194/amt-17-4613-2024, https://doi.org/10.5194/amt-17-4613-2024, 2024
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Non-linearity (NL) correction is a critical procedure to guarantee that the calibration accuracy of a spaceborne sensor approaches a reasonable level. Different from the classical method, a new NL correction method for a spaceborne Fourier transform spectrometer is proposed. To overcome the inaccurate linear coefficient from two-point calibration influencing NL correction, an iteration algorithm is established that is suitable for NL correction of both infrared and microwave sensors.
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024, https://doi.org/10.5194/amt-17-4303-2024, 2024
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Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
Almudena Velázquez Blázquez, Edward Baudrez, Nicolas Clerbaux, and Carlos Domenech
Atmos. Meas. Tech., 17, 4245–4256, https://doi.org/10.5194/amt-17-4245-2024, https://doi.org/10.5194/amt-17-4245-2024, 2024
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The Broadband Radiometer measures shortwave and total-wave radiances filtered by the spectral response of the instrument. To obtain unfiltered solar and thermal radiances, the effect of the spectral response needs to be corrected for, done within the BM-RAD processor. Errors in the unfiltering are propagated into fluxes; thus, accurate unfiltering is required for their proper estimation (within BMA-FLX). Unfiltering errors are estimated to be <0.5 % for the shortwave and <0.1 % for the longwave.
Qihou Zhou, Yanlin Li, and Yun Gong
Atmos. Meas. Tech., 17, 4197–4209, https://doi.org/10.5194/amt-17-4197-2024, https://doi.org/10.5194/amt-17-4197-2024, 2024
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We discuss several robust estimators to compute the variance of a normally distributed random variable to deal with interference. Compared to rank-based estimators, the methods based on the geometric mean are more accurate and are computationally more efficient. We apply three robust estimators to incoherent scatter power and velocity processing, along with the traditional sample mean estimator. The best estimator is a hybrid estimator that combines the sample mean and a robust estimator.
Zhao Shi, Yuxiang Wen, and Jianxin He
Atmos. Meas. Tech., 17, 4121–4135, https://doi.org/10.5194/amt-17-4121-2024, https://doi.org/10.5194/amt-17-4121-2024, 2024
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The squall line is a type of convective system. Squall lines are often associated with damaging weather, so identifying and tracking squall lines plays an important role in early meteorological disaster warnings. A clustering-based method is proposed in this article. It can identify the squall lines within the radar scanning range with an accuracy rate of 95.93 %. It can also provide the three-dimensional structure and movement tracking results for each squall line.
Elizabeth N. Smith and Jacob T. Carlin
Atmos. Meas. Tech., 17, 4087–4107, https://doi.org/10.5194/amt-17-4087-2024, https://doi.org/10.5194/amt-17-4087-2024, 2024
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Boundary-layer height observations remain sparse in time and space. In this study we create a new fuzzy logic method for synergistically combining boundary-layer height estimates from a suite of instruments. These estimates generally compare well to those from radiosondes; plus, the approach offers near-continuous estimates through the entire diurnal cycle. Suspected reasons for discrepancies are discussed. The code for the newly presented fuzzy logic method is provided for the community to use.
Lev D. Labzovskii, Gerd-Jan van Zadelhoff, David P. Donovan, Jos de Kloe, L. Gijsbert Tilstra, Ad Stoffelen, Damien Josset, and Piet Stammes
EGUsphere, https://doi.org/10.5194/egusphere-2024-1926, https://doi.org/10.5194/egusphere-2024-1926, 2024
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The Atmospheric Laser Doppler Instrument (ALADIN) on the Aeolus satellite was the first of its kind to measure high-resolution vertical profiles of aerosols and cloud properties from space. We present an algorithm, producing Aeolus lidar surface returns (LSR) containing useful information for measuring UV reflectivity. Aeolus LSR matched well with existing UV reflectivity data from other satellites like GOME-2 and TROPOMI and demonstrated excellent sensitivity to modelled snow cover.
Laura Bianco, Bianca Adler, Ludovic Bariteau, Irina V. Djalalova, Timothy Myers, Sergio Pezoa, David D. Turner, and James M. Wilczak
Atmos. Meas. Tech., 17, 3933–3948, https://doi.org/10.5194/amt-17-3933-2024, https://doi.org/10.5194/amt-17-3933-2024, 2024
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The Tropospheric Remotely Observed Profiling via Optimal Estimation physical retrieval is used to retrieve temperature and humidity profiles from various combinations of passive and active remote sensing instruments, surface platforms, and numerical weather prediction models. The retrieved profiles are assessed against collocated radiosonde in non-cloudy conditions to assess the sensitivity of the retrievals to different input combinations. Case studies with cloudy conditions are also inspected.
Björn Linder, Peter Preusse, Qiuyu Chen, Ole Martin Christensen, Lukas Krasauskas, Linda Megner, Manfred Ern, and Jörg Gumbel
Atmos. Meas. Tech., 17, 3829–3841, https://doi.org/10.5194/amt-17-3829-2024, https://doi.org/10.5194/amt-17-3829-2024, 2024
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The Swedish research satellite MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is designed to study atmospheric waves in the mesosphere and lower thermosphere. These waves perturb the temperature field, and thus, by observing three-dimensional temperature fluctuations, their properties can be quantified. This pre-study uses synthetic MATS data generated from a general circulation model to investigate how well wave properties can be retrieved.
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng Yung Huang
Atmos. Meas. Tech., 17, 3605–3623, https://doi.org/10.5194/amt-17-3605-2024, https://doi.org/10.5194/amt-17-3605-2024, 2024
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This research examines the characteristics of low-level GNSS radio occultation (RO) refractivity bias over ocean and land and its dependency on the RO retrieval uncertainty, atmospheric temperature, and moisture. We propose methods for estimating the region-dependent refractivity bias. Our methods can be applied to calibrate the refractivity bias under different atmospheric conditions and thus improve the applications of the GNSS RO data in the deep troposphere.
Sanja Dmitrovic, Johnathan W. Hair, Brian L. Collister, Ewan Crosbie, Marta A. Fenn, Richard A. Ferrare, David B. Harper, Chris A. Hostetler, Yongxiang Hu, John A. Reagan, Claire E. Robinson, Shane T. Seaman, Taylor J. Shingler, Kenneth L. Thornhill, Holger Vömel, Xubin Zeng, and Armin Sorooshian
Atmos. Meas. Tech., 17, 3515–3532, https://doi.org/10.5194/amt-17-3515-2024, https://doi.org/10.5194/amt-17-3515-2024, 2024
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This study introduces and evaluates a new ocean surface wind speed product from the NASA Langley Research Center (LARC) airborne High-Spectral-Resolution Lidar – Generation 2 (HSRL-2) during the NASA ACTIVATE mission. We show that HSRL-2 surface wind speed data are accurate when compared to ground-truth dropsonde measurements. Therefore, the HSRL-2 instrument is able obtain accurate, high-resolution surface wind speed data in airborne field campaigns.
Almudena Velázquez Blázquez, Carlos Domenech, Edward Baudrez, Nicolas Clerbaux, Carla Salas Molar, and Nils Madenach
EGUsphere, https://doi.org/10.5194/egusphere-2024-1539, https://doi.org/10.5194/egusphere-2024-1539, 2024
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This paper focuses on the BMA-FLX processor, in which thermal and solar top-of-atmosphere radiative fluxes are obtained from longwave and shortwave radiances measured along-track by the EarthCARE Broadband Radiometer (BBR). The BBR measurements, at three fixed viewing angles (fore, nadir, aft) are co-registered either at the surface or at a reference level. A combined flux from the three BRR views is obtained. The algorithm has been successfully validated against test scenes.
Laura M. Tomkins, Sandra E. Yuter, and Matthew A. Miller
Atmos. Meas. Tech., 17, 3377–3399, https://doi.org/10.5194/amt-17-3377-2024, https://doi.org/10.5194/amt-17-3377-2024, 2024
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We have created a new method to better identify enhanced features in radar data from winter storms. Unlike the clear-cut features seen in warm-season storms, features in winter storms are often fuzzier with softer edges. Our technique is unique because it uses two adaptive thresholds that change based on the background radar values. It can identify both strong and subtle features in the radar data and takes into account uncertainties in the detection process.
Eileen Päschke and Carola Detring
Atmos. Meas. Tech., 17, 3187–3217, https://doi.org/10.5194/amt-17-3187-2024, https://doi.org/10.5194/amt-17-3187-2024, 2024
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Little noise in radial velocity Doppler lidar measurements can contribute to large errors in retrieved turbulence variables. In order to distinguish between plausible and erroneous measurements we developed new filter techniques that work independently of the choice of a specific threshold for the signal-to-noise ratio. The performance of these techniques is discussed both by means of assessing the filter results and by comparing retrieved turbulence variables versus independent measurements.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
EGUsphere, https://doi.org/10.5194/egusphere-2024-1045, https://doi.org/10.5194/egusphere-2024-1045, 2024
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This study evaluates and compares a new microwave hyperspectrometer with an infrared hyperspectrometer for clear-sky temperature and water vapor retrievals. The analysis reveals that the information content of the infrared hyperspectrometer exceeds that of the microwave hyperspectrometer and provides higher vertical resolution in ground-based zenith measurements. Leveraging the ground-airborne synergy between the two instruments yielded optimal-sounding results.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024, https://doi.org/10.5194/amt-17-2811-2024, 2024
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Microwave links, often part of mobile phone networks, can be used to measure rainfall along the link path by determining the signal loss caused by rainfall. We use high-frequency data of multiple microwave links to recreate commonly used sampling strategies. For time intervals up to 1 min, the influence of sampling strategies on estimated rainfall intensities is relatively little, while for intervals longer than 5–15 min, the sampling strategy can have significant influences on the estimates.
Martin Lainer, Killian P. Brennan, Alessandro Hering, Jérôme Kopp, Samuel Monhart, Daniel Wolfensberger, and Urs Germann
Atmos. Meas. Tech., 17, 2539–2557, https://doi.org/10.5194/amt-17-2539-2024, https://doi.org/10.5194/amt-17-2539-2024, 2024
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This study uses deep learning (the Mask R-CNN model) on drone-based photogrammetric data of hail on the ground to estimate hail size distributions (HSDs). Traditional hail sensors' limited areas complicate the full HSD retrieval. The HSD of a supercell event on 20 June 2021 is retrieved and contains > 18 000 hailstones. The HSD is compared to automatic hail sensor measurements and those of weather-radar-based MESHS. Investigations into ground hail melting are performed by five drone flights.
Andreas Foth, Moritz Lochmann, Pablo Saavedra Garfias, and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2024-919, https://doi.org/10.5194/egusphere-2024-919, 2024
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Microwave radiometers are usually not able to provide atmospheric quantities such as temperature profiles during rain. Here, we present a method based on a selection of specific frequencies and elevation angles from the microwave radiometer observation. A comparison with a numerical weather prediction model shows that the presented method allows to resolve temperature profiles during rain with rain rates up to 2 mm h−1 which was not possible before with state-of-the-art retrievals.
Andrea Camplani, Daniele Casella, Paolo Sanò, and Giulia Panegrossi
Atmos. Meas. Tech., 17, 2195–2217, https://doi.org/10.5194/amt-17-2195-2024, https://doi.org/10.5194/amt-17-2195-2024, 2024
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The paper describes a new machine-learning-based snowfall retrieval algorithm for Advanced Technology Microwave Sounder observations developed to retrieve high-latitude snowfall events. The main novelty of the approach is the radiometric characterization of the background surface at the time of the overpass, which is ancillary to the retrieval process. The algorithm shows a unique capability to retrieve snowfall in the environmental conditions typical of high latitudes.
Lusheng Liang, Wenying Su, Sergio Sejas, Zachary Eitzen, and Norman G. Loeb
Atmos. Meas. Tech., 17, 2147–2163, https://doi.org/10.5194/amt-17-2147-2024, https://doi.org/10.5194/amt-17-2147-2024, 2024
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This paper describes an updated process to obtain unfiltered radiation from CERES satellite instruments by incorporating the most recent developments in radiative transfer modeling and ancillary input datasets (e.g., realistic representation of land surface radiation and climatology of surface temperatures and aerosols) during the past 20 years. The resulting global mean of instantaneous SW and LW fluxes is changed by less than 0.5 W m−2 with regional differences as large as 2.0 W m−2.
Maximilian Graf, Andreas Wagner, Julius Polz, Llorenç Lliso, José Alberto Lahuerta, Harald Kunstmann, and Christian Chwala
Atmos. Meas. Tech., 17, 2165–2182, https://doi.org/10.5194/amt-17-2165-2024, https://doi.org/10.5194/amt-17-2165-2024, 2024
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Commercial microwave links (CMLs) can be used for rainfall retrieval. The detection of rainy periods in their attenuation time series is a crucial processing step. We investigate the usage of rainfall data from MSG SEVIRI for this task, compare this approach with existing methods, and introduce a novel combined approach. The results show certain advantages for SEVIRI-based methods, particularly for CMLs where existing methods perform poorly. Our novel combination yields the best performance.
Lieuwe G. Tilstra, Martin de Graaf, Victor J. H. Trees, Pavel Litvinov, Oleg Dubovik, and Piet Stammes
Atmos. Meas. Tech., 17, 2235–2256, https://doi.org/10.5194/amt-17-2235-2024, https://doi.org/10.5194/amt-17-2235-2024, 2024
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This paper introduces a new surface albedo climatology of directionally dependent Lambertian-equivalent reflectivity (DLER) observed by TROPOMI on the Sentinel-5 Precursor satellite. The database contains monthly fields of DLER for 21 wavelength bands at a relatively high spatial resolution of 0.125 by 0.125 degrees. The anisotropy of the surface reflection is handled by parameterisation of the viewing angle dependence.
Bing Cao and Alan Z. Liu
Atmos. Meas. Tech., 17, 2123–2146, https://doi.org/10.5194/amt-17-2123-2024, https://doi.org/10.5194/amt-17-2123-2024, 2024
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A narrow-band sodium lidar measures atmospheric waves but is limited to vertical variations. We propose to utilize phase shifts among observations from different laser beams to derive horizontal wave information. Two gravity wave packets were identified by this method. Both waves were found to interact with thin evanescent layers, partially reflected, but transmitted energy to higher altitudes. The method can detect more medium-frequency gravity waves for similar lidar systems worldwide.
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
EGUsphere, https://doi.org/10.5194/egusphere-2024-356, https://doi.org/10.5194/egusphere-2024-356, 2024
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The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back to space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance, and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.
Xiaozhen Xiong, Xu Liu, Robert Spurr, Ming Zhao, Qiguang Yang, Wan Wu, and Liqiao Lei
Atmos. Meas. Tech., 17, 1965–1978, https://doi.org/10.5194/amt-17-1965-2024, https://doi.org/10.5194/amt-17-1965-2024, 2024
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The term “hotspot” refers to the sharp increase in reflectance occurring when incident (solar) and reflected (viewing) directions coincide in the backscatter direction. The accurate simulation of hotspot directional signatures is important for many remote sensing applications, but current models typically require large values of computations to represent the hotspot accurately. This paper provides a numerically improved hotspot BRDF model that converges much faster and is used in VLIDORT.
Daniel Zawada, Kimberlee Dubé, Taran Warnock, Adam Bourassa, Susann Tegtmeier, and Douglas Degenstein
Atmos. Meas. Tech., 17, 1995–2010, https://doi.org/10.5194/amt-17-1995-2024, https://doi.org/10.5194/amt-17-1995-2024, 2024
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There remain large uncertainties in long-term changes of stratospheric–atmospheric temperatures. We have produced a time series of more than 20 years of satellite-based temperature measurements from the OSIRIS instrument in the upper–middle stratosphere. The dataset is publicly available and intended to be used for a better understanding of changes in stratospheric temperatures.
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
EGUsphere, https://doi.org/10.5194/egusphere-2024-937, https://doi.org/10.5194/egusphere-2024-937, 2024
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A doppler lidar was placed in highly built-up area in London to measure wakes from tall buildings during a period of one year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
Alban Philibert, Marie Lothon, Julien Amestoy, Pierre-Yves Meslin, Solène Derrien, Yannick Bezombes, Bernard Campistron, Fabienne Lohou, Antoine Vial, Guylaine Canut-Rocafort, Joachim Reuder, and Jennifer K. Brooke
Atmos. Meas. Tech., 17, 1679–1701, https://doi.org/10.5194/amt-17-1679-2024, https://doi.org/10.5194/amt-17-1679-2024, 2024
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We present a new algorithm, CALOTRITON, for the retrieval of the convective boundary layer depth with ultra-high-frequency radar measurements. CALOTRITON is partly based on the principle that the top of the convective boundary layer is associated with an inversion and a decrease in turbulence. It is evaluated using ceilometer and radiosonde data. It is able to qualify the complexity of the vertical structure of the low troposphere and detect internal or residual layers.
Kamil Mroz, Alessandro Battaglia, and Ann M. Fridlind
Atmos. Meas. Tech., 17, 1577–1597, https://doi.org/10.5194/amt-17-1577-2024, https://doi.org/10.5194/amt-17-1577-2024, 2024
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In this study, we examine the extent to which radar measurements from space can inform us about the properties of clouds and precipitation. Surprisingly, our analysis showed that the amount of ice turning into rain was lower than expected in the current product. To improve on this, we came up with a new way to extract information about the size and concentration of particles from radar data. As long as we use this method in the right conditions, we can even estimate how dense the ice is.
Wolf Knöller, Gholamhossein Bagheri, Philipp von Olshausen, and Michael Wilczek
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-184, https://doi.org/10.5194/amt-2023-184, 2024
Revised manuscript accepted for AMT
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Three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. This paper presents a detailed study of the measurement uncertainty of a three-beam wind-LiDAR designed for mounting on airborne platforms. Considering the geometrical constraints, the analysis provides quantitative estimates for the measurement uncertainty of all components of the 3D wind vector. As a result, we propose an optimized post-processing for error reduction.
Volker Wulfmeyer, Christoph Senff, Florian Späth, Andreas Behrendt, Diego Lange, Robert M. Banta, W. Alan Brewer, Andreas Wieser, and David D. Turner
Atmos. Meas. Tech., 17, 1175–1196, https://doi.org/10.5194/amt-17-1175-2024, https://doi.org/10.5194/amt-17-1175-2024, 2024
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A simultaneous deployment of Doppler, temperature, and water-vapor lidar systems is used to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of weather forecast and climate models.
Daisuke Hotta, Katrin Lonitz, and Sean Healy
Atmos. Meas. Tech., 17, 1075–1089, https://doi.org/10.5194/amt-17-1075-2024, https://doi.org/10.5194/amt-17-1075-2024, 2024
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Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) is a new type of GNSS observations that can detect heavy precipitation along the ray path between the emitter and receiver satellites. As a first step towards using these observations in numerical weather prediction (NWP), we developed a computer code that simulates GNSS-PRO observations from forecast fields produced by an NWP model. The quality of the developed simulator is evaluated with a number of case studies.
Mohamed Mossad, Irina Strelnikova, Robin Wing, and Gerd Baumgarten
Atmos. Meas. Tech., 17, 783–799, https://doi.org/10.5194/amt-17-783-2024, https://doi.org/10.5194/amt-17-783-2024, 2024
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This numerical study addresses observational gaps' impact on atmospheric gravity wave spectra. Three methods, fast Fourier transform (FFT), generalized Lomb–Scargle periodogram (GLS), and Haar structure function (HSF), were tested on synthetic data. HSF is best for spectra with negative slopes. GLS excels for flat and positive slopes and identifying dominant frequencies. Accurately estimating these aspects is crucial for understanding gravity wave dynamics and energy transfer in the atmosphere.
Kuo-Nung Wang, Chi O. Ao, Mary G. Morris, George A. Hajj, Marcin J. Kurowski, Francis J. Turk, and Angelyn W. Moore
Atmos. Meas. Tech., 17, 583–599, https://doi.org/10.5194/amt-17-583-2024, https://doi.org/10.5194/amt-17-583-2024, 2024
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In this article, we described a joint retrieval approach combining two techniques, RO and MWR, to obtain high vertical resolution and solve for temperature and moisture independently. The results show that the complicated structure in the lower troposphere can be better resolved with much smaller biases, and the RO+MWR combination is the most stable scenario in our sensitivity analysis. This approach is also applied to real data (COSMIC-2/Suomi-NPP) to show the promise of joint RO+MWR retrieval.
Filippo Emilio Scarsi, Alessandro Battaglia, Frederic Tridon, Paolo Martire, Ranvir Dhillon, and Anthony Illingworth
Atmos. Meas. Tech., 17, 499–514, https://doi.org/10.5194/amt-17-499-2024, https://doi.org/10.5194/amt-17-499-2024, 2024
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The WIVERN mission, one of the two candidates to be the ESA's Earth Explorer 11 mission, aims at providing measurements of horizontal winds in cloud and precipitation systems through a conically scanning W-band Doppler radar. This work discusses four methods that can be used to characterize and correct the Doppler velocity error induced by the antenna mispointing. The proposed methodologies can be extended to other Doppler concepts featuring conically scanning or slant viewing Doppler systems.
Luis Ackermann, Joshua Soderholm, Alain Protat, Rhys Whitley, Lisa Ye, and Nina Ridder
Atmos. Meas. Tech., 17, 407–422, https://doi.org/10.5194/amt-17-407-2024, https://doi.org/10.5194/amt-17-407-2024, 2024
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The paper addresses the crucial topic of hail damage quantification using radar observations. We propose a new radar-derived hail product that utilizes a large dataset of insurance hail damage claims and radar observations. A deep neural network was employed, trained with local meteorological variables and the radar observations, to better quantify hail damage. Key meteorological variables were identified to have the most predictive capability in this regard.
Christos Gatidis, Marc Schleiss, and Christine Unal
Atmos. Meas. Tech., 17, 235–245, https://doi.org/10.5194/amt-17-235-2024, https://doi.org/10.5194/amt-17-235-2024, 2024
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A common method to retrieve important information about the microphysical structure of rain (DSD retrievals) requires a constrained relationship between the drop size distribution parameters. The most widely accepted empirical relationship is between μ and Λ. The relationship shows variability across the different types of rainfall (convective or stratiform). The new proposed power-law model to represent the μ–Λ relation provides a better physical interpretation of the relationship coefficients.
Liqin Jin, Jakob Mann, Nikolas Angelou, and Mikael Sjöholm
Atmos. Meas. Tech., 16, 6007–6023, https://doi.org/10.5194/amt-16-6007-2023, https://doi.org/10.5194/amt-16-6007-2023, 2023
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By sampling the spectra from continuous-wave Doppler lidars very fast, the rain-induced Doppler signal can be suppressed and the bias in the wind velocity estimation can be reduced. The method normalizes 3 kHz spectra by their peak values before averaging them down to 50 Hz. Over 3 h, we observe a significant reduction in the bias of the lidar data relative to the reference sonic data when the largest lidar focus distance is used. The more it rains, the more the bias is reduced.
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Short summary
We developed a technique for inferring the physical properties (amount, size and density) of falling snow from radar observations made using multiple different frequencies. We tested this method using measurements from airborne radar and compared the results to direct measurements from another aircraft, as well as ground-based radar. The results demonstrate that multifrequency radars have significant advantages over those with a single frequency in determining the snow size and density.
We developed a technique for inferring the physical properties (amount, size and density) of...
