Articles | Volume 11, issue 3
https://doi.org/10.5194/amt-11-1333-2018
© 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-11-1333-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Atmospheric QBO and ENSO indices with high vertical resolution from GNSS radio occultation temperature measurements
Hallgeir Wilhelmsen
CORRESPONDING AUTHOR
Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria
FWF-DK Climate Change, University of Graz, Graz, Austria
Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics, University of Graz, Graz, Austria
Florian Ladstädter
Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria
Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics, University of Graz, Graz, Austria
Barbara Scherllin-Pirscher
Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Vienna, Austria
Andrea K. Steiner
Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria
FWF-DK Climate Change, University of Graz, Graz, Austria
Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics, University of Graz, Graz, Austria
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Karina von Schuckmann, Audrey Minère, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Richard Allan, Paul M. Barker, Hugo Beltrami, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nikolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Noah Smith, Andrea Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-239, https://doi.org/10.5194/essd-2022-239, 2022
Revised manuscript accepted for ESSD
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Earth climate is out of energy balance and this study quantifies how much heat has consequently accumulated over the past decades (89 %: ocean, 6 %: land, 4 %: cryosphere, 1 %: atmosphere). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris agreement’s global stocktake.
Matthieu Plu, Barbara Scherllin-Pirscher, Delia Arnold Arias, Rocio Baro, Guillaume Bigeard, Luca Bugliaro, Ana Carvalho, Laaziz El Amraoui, Kurt Eschbacher, Marcus Hirtl, Christian Maurer, Marie D. Mulder, Dennis Piontek, Lennart Robertson, Carl-Herbert Rokitansky, Fritz Zobl, and Raimund Zopp
Nat. Hazards Earth Syst. Sci., 21, 2973–2992, https://doi.org/10.5194/nhess-21-2973-2021, https://doi.org/10.5194/nhess-21-2973-2021, 2021
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Past volcanic eruptions that spread out ash over large areas, like Eyjafjallajökull in 2010, forced the cancellation of thousands of flights and had huge economic consequences.
In this article, an international team in the H2020 EU-funded EUNADICS-AV project has designed a probabilistic model approach to quantify ash concentrations. This approach is evaluated against measurements, and its potential use to mitigate the impact of future large-scale eruptions is discussed.
Ying Li, Gottfried Kirchengast, Marc Schwärz, Florian Ladstädter, and Yunbin Yuan
Atmos. Meas. Tech., 14, 2327–2343, https://doi.org/10.5194/amt-14-2327-2021, https://doi.org/10.5194/amt-14-2327-2021, 2021
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We introduce a new method to detect and monitor sudden stratospheric warming (SSW) events using Global Navigation Satellite System (GNSS) radio occultation (RO) data at high northern latitudes and demonstrate it for the well-known Jan.–Feb. 2009 event. We found that RO data are capable of SSW monitoring. Based on our method, a SSW event can be detected and tracked, and the duration and the strength of the event can be recorded. The results are consistent with other research on the 2009 event.
Pierre-Yves Tournigand, Valeria Cigala, Elzbieta Lasota, Mohammed Hammouti, Lieven Clarisse, Hugues Brenot, Fred Prata, Gottfried Kirchengast, Andrea K. Steiner, and Riccardo Biondi
Earth Syst. Sci. Data, 12, 3139–3159, https://doi.org/10.5194/essd-12-3139-2020, https://doi.org/10.5194/essd-12-3139-2020, 2020
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The detection and monitoring of volcanic clouds are important for aviation management, climate and weather forecasts. We present in this paper the first comprehensive archive collecting spatial and temporal information about volcanic clouds generated by the 11 largest eruptions of this century. We provide a complete set of state-of-the-art data allowing the development and testing of new algorithms contributing to improve the accuracy of the estimation of fundamental volcanic cloud parameters.
Marcus Hirtl, Barbara Scherllin-Pirscher, Martin Stuefer, Delia Arnold, Rocio Baro, Christian Maurer, and Marie D. Mulder
Nat. Hazards Earth Syst. Sci., 20, 3099–3115, https://doi.org/10.5194/nhess-20-3099-2020, https://doi.org/10.5194/nhess-20-3099-2020, 2020
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The paper shows the application of a new volcanic emission preprocessor for the chemical transport model WRF-Chem. The model is evaluated with different observational data sets for the eruption of the Grimsvötn volcano 2011.
Elżbieta Lasota, Andrea K. Steiner, Gottfried Kirchengast, and Riccardo Biondi
Earth Syst. Sci. Data, 12, 2679–2693, https://doi.org/10.5194/essd-12-2679-2020, https://doi.org/10.5194/essd-12-2679-2020, 2020
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In this work, we provide a comprehensive archive of tropical cyclone vertical structure for the period 2001–2018. The tropical cyclone best tracks are co-located in time and space with high-vertical-resolution atmospheric profiles (temperature, pressure, humidity and refractivity) from radio occultations and with climatological profiles. This dataset can be used to analyze the inner vertical thermodynamic structure of tropical cyclones and the pre-cyclone environment.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
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Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Marcus Hirtl, Delia Arnold, Rocio Baro, Hugues Brenot, Mauro Coltelli, Kurt Eschbacher, Helmut Hard-Stremayer, Florian Lipok, Christian Maurer, Dieter Meinhard, Lucia Mona, Marie D. Mulder, Nikolaos Papagiannopoulos, Michael Pernsteiner, Matthieu Plu, Lennart Robertson, Carl-Herbert Rokitansky, Barbara Scherllin-Pirscher, Klaus Sievers, Mikhail Sofiev, Wim Som de Cerff, Martin Steinheimer, Martin Stuefer, Nicolas Theys, Andreas Uppstu, Saskia Wagenaar, Roland Winkler, Gerhard Wotawa, Fritz Zobl, and Raimund Zopp
Nat. Hazards Earth Syst. Sci., 20, 1719–1739, https://doi.org/10.5194/nhess-20-1719-2020, https://doi.org/10.5194/nhess-20-1719-2020, 2020
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The paper summarizes the set-up and outcome of a volcanic-hazard demonstration exercise, with the goals of assessing and mitigating the impacts of volcanic ash clouds on civil and military aviation. Experts in the field simulated the sequence of procedures for an artificial eruption of the Etna volcano in Italy. The scope of the exercise ranged from the detection of the assumed event to the issuance of early warnings and optimized rerouting of flights.
Andrea K. Steiner, Florian Ladstädter, Chi O. Ao, Hans Gleisner, Shu-Peng Ho, Doug Hunt, Torsten Schmidt, Ulrich Foelsche, Gottfried Kirchengast, Ying-Hwa Kuo, Kent B. Lauritsen, Anthony J. Mannucci, Johannes K. Nielsen, William Schreiner, Marc Schwärz, Sergey Sokolovskiy, Stig Syndergaard, and Jens Wickert
Atmos. Meas. Tech., 13, 2547–2575, https://doi.org/10.5194/amt-13-2547-2020, https://doi.org/10.5194/amt-13-2547-2020, 2020
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High-quality observations are critically important for monitoring the Earth’s changing climate. We provide information on the consistency and long-term stability of observations from GPS radio occultation (RO). We assess, for the first time, RO records from multiple RO missions and all major RO data providers. Our results quantify where RO can be used for reliable trend assessment and confirm its climate quality.
Rodrigo Hierro, Andrea K. Steiner, Alejandro de la Torre, Peter Alexander, Pablo Llamedo, and Pablo Cremades
Atmos. Meas. Tech., 11, 3523–3539, https://doi.org/10.5194/amt-11-3523-2018, https://doi.org/10.5194/amt-11-3523-2018, 2018
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This paper analyzed the collocated GPS radio occultation profiles near the convective systems identified from ISCCP over two orographic regions of the Alps and Andes. Gravity wave (GW) analysis over both selected regions was also carried out. The gravity wave signature from the two case studies were investigated using mesoscale WRF simulations, ERA-Interim reanalysis data, and measured RO temperature profiles. The absence of fronts or jets during both case studies reveals similar relevant GWs.
Andrea K. Steiner, Bettina C. Lackner, and Mark A. Ringer
Atmos. Chem. Phys., 18, 4657–4672, https://doi.org/10.5194/acp-18-4657-2018, https://doi.org/10.5194/acp-18-4657-2018, 2018
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We evaluate the representation of tropical convection regimes in atmospheric climate models with satellite-based observations from GPS radio occultation. We find that models have large temperature biases in the tropopause region. In moist convection regions, models underestimate moisture up to 40 % over oceans whereas in dry regions they overestimate it by 100 %. Our findings show that RO observations are a valuable data source for the evaluation and development of next generation climate models.
Petr Pisoft, Petr Sacha, Jiri Miksovsky, Peter Huszar, Barbara Scherllin-Pirscher, and Ulrich Foelsche
Atmos. Meas. Tech., 11, 515–527, https://doi.org/10.5194/amt-11-515-2018, https://doi.org/10.5194/amt-11-515-2018, 2018
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We revise selected findings regarding utilization of Global Positioning System radio occultation density profiles for analysis of internal gravity waves. The results show that previously published results are valid only for one specific data version only. Using radiosonde profiles, we also analyze a nonhydrostatic component in temperature profiles. The last part presents detailed study on the utilization of density profiles for characterization of the wave field stability.
Barbara Angerer, Florian Ladstädter, Barbara Scherllin-Pirscher, Marc Schwärz, Andrea K. Steiner, Ulrich Foelsche, and Gottfried Kirchengast
Atmos. Meas. Tech., 10, 4845–4863, https://doi.org/10.5194/amt-10-4845-2017, https://doi.org/10.5194/amt-10-4845-2017, 2017
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We present a detailed analysis of the latest Wegener Center GPS radio occultation reprocessing (OPSv5.6) output. Knowledge of differences in data quality, as well as of data consistency, is essential when combining data from different missions to a long-term climate record. We compare quality aspects of the various processed satellite missions and present satellite-dependent variations. Temperature data from various satellites are found to be highly consistent within 8 to 25 km.
Lukas Brunner and Andrea K. Steiner
Atmos. Meas. Tech., 10, 4727–4745, https://doi.org/10.5194/amt-10-4727-2017, https://doi.org/10.5194/amt-10-4727-2017, 2017
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Atmospheric blocking is a weather pattern where a stable high pressure system blocks the westerly flow at mid-latitudes. We provide, for the first time, a global perspective on blocking and related impacts, based on satellite observations from GPS radio occultation for 2006–2016. We find strong direct and remote effects on the vertical atmospheric structure revealing significant temperature and humidity anomalies up to 15 km. The observations will help for a better insight into blocking impacts.
Barbara Scherllin-Pirscher, William J. Randel, and Joowan Kim
Atmos. Chem. Phys., 17, 793–806, https://doi.org/10.5194/acp-17-793-2017, https://doi.org/10.5194/acp-17-793-2017, 2017
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Tropical temperature variability and associated Kelvin-wave activity are investigated from 10 km to 30 km using 13 years of high-resolution observational data. Strongest temperature variability is found in the tropical tropopause region between about 16 km and 20 km, where peaks of Kelvin-wave activity are irregularly distributed in time. Detailed knowledge of dynamical processes in the tropical tropopause region is an essential part of better understanding climate variability and change.
Lukas Brunner, Andrea K. Steiner, Barbara Scherllin-Pirscher, and Martin W. Jury
Atmos. Chem. Phys., 16, 4593–4604, https://doi.org/10.5194/acp-16-4593-2016, https://doi.org/10.5194/acp-16-4593-2016, 2016
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Atmospheric blocking refers to persistent high-pressure systems which block the climatological flow at midlatitudes. We explore blocking with observations from GPS radio occultation (RO), a satellite-based remote-sensing system. Using two example cases, we find that RO data robustly capture blocking, highlighting the potential of RO observations to complement models and reanalysis as a basis for blocking research.
Riccardo Biondi, Andrea Steiner, Gottfried Kirchengast, Hugues Brenot, and Therese Rieckh
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2015-974, https://doi.org/10.5194/acp-2015-974, 2016
Revised manuscript not accepted
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Cloud structure and cloud top height are key parameters for the monitoring of volcanic cloud movement and for characterizing eruptive processes and understanding the impact on short-term climate variability.
We have studied the eruption of Nabro volcano, which has been recognized as the largest stratospheric sulfur injection since Pinatubo (1991) and we have found a clear warming signature after the eruption of Nabro persisting for a few months.
Y. Li, G. Kirchengast, B. Scherllin-Pirscher, R. Norman, Y. B. Yuan, J. Fritzer, M. Schwaerz, and K. Zhang
Atmos. Meas. Tech., 8, 3447–3465, https://doi.org/10.5194/amt-8-3447-2015, https://doi.org/10.5194/amt-8-3447-2015, 2015
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We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System-based radio occultation measurements. The new algorithm is evaluated against the OPSv5.6 algorithm developed by the Wegener Center using both simulated and real observed data. It is found that the algorithm can significantly reduce the random errors of optimized bending angles. The retrieved refractivity and temperature profiles are also benefited.
R. Biondi, A. K. Steiner, G. Kirchengast, and T. Rieckh
Atmos. Chem. Phys., 15, 5181–5193, https://doi.org/10.5194/acp-15-5181-2015, https://doi.org/10.5194/acp-15-5181-2015, 2015
F. Ladstädter, A. K. Steiner, M. Schwärz, and G. Kirchengast
Atmos. Meas. Tech., 8, 1819–1834, https://doi.org/10.5194/amt-8-1819-2015, https://doi.org/10.5194/amt-8-1819-2015, 2015
B. Scherllin-Pirscher, S. Syndergaard, U. Foelsche, and K. B. Lauritsen
Atmos. Meas. Tech., 8, 109–124, https://doi.org/10.5194/amt-8-109-2015, https://doi.org/10.5194/amt-8-109-2015, 2015
T. Rieckh, B. Scherllin-Pirscher, F. Ladstädter, and U. Foelsche
Atmos. Meas. Tech., 7, 3947–3958, https://doi.org/10.5194/amt-7-3947-2014, https://doi.org/10.5194/amt-7-3947-2014, 2014
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Radio Occultation (RO) observations featuring high vertical resolution, global availability, and high accuracy were used to investigate global characteristics of the lapse rate tropopause. Climatological tropopause characteristics for the
RO record from 2001 to 2013 extend previous studies on tropopause structure and its temporal variability. Latitudinal and longitudinal variations as well as the annual cycle and inter-annual variability were analyzed for the tropopause altitude and temperature.
J. Danzer, U. Foelsche, B. Scherllin-Pirscher, and M. Schwärz
Atmos. Meas. Tech., 7, 2883–2896, https://doi.org/10.5194/amt-7-2883-2014, https://doi.org/10.5194/amt-7-2883-2014, 2014
J. Danzer, B. Scherllin-Pirscher, and U. Foelsche
Atmos. Meas. Tech., 6, 2169–2179, https://doi.org/10.5194/amt-6-2169-2013, https://doi.org/10.5194/amt-6-2169-2013, 2013
A. K. Steiner, D. Hunt, S.-P. Ho, G. Kirchengast, A. J. Mannucci, B. Scherllin-Pirscher, H. Gleisner, A. von Engeln, T. Schmidt, C. Ao, S. S. Leroy, E. R. Kursinski, U. Foelsche, M. Gorbunov, S. Heise, Y.-H. Kuo, K. B. Lauritsen, C. Marquardt, C. Rocken, W. Schreiner, S. Sokolovskiy, S. Syndergaard, and J. Wickert
Atmos. Chem. Phys., 13, 1469–1484, https://doi.org/10.5194/acp-13-1469-2013, https://doi.org/10.5194/acp-13-1469-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Validation of Aeolus wind profiles using ground-based lidar and radiosonde observations at Réunion island and the Observatoire de Haute-Provence
Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach
High-resolution 3D winds derived from a modified WISSDOM synthesis scheme using multiple Doppler lidars and observations
Atmospheric boundary layer height from ground-based remote sensing: a review of capabilities and limitations
Assessing and mitigating the radar–radar interference in the German C-band weather radar network
Spectral replacement using machine learning methods for continuous mapping of the Geostationary Environment Monitoring Spectrometer (GEMS)
Doppler spectra from DWD's operational C-band radar birdbath scan: sampling strategy, spectral postprocessing, and multimodal analysis for the retrieval of precipitation processes
High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning
Horizontal small-scale variability of water vapor in the atmosphere: implications for intercomparison of data from different measuring systems
Satellite observations of gravity wave momentum flux in the mesosphere and lower thermosphere (MLT): feasibility and requirements
An improved near-real-time precipitation retrieval for Brazil
Observations of anomalous propagation over waters near Sweden
Radio frequency interference detection and mitigation in the DWD C-band weather radar network
Quality control and error assessment of the Aeolus L2B wind results from the Joint Aeolus Tropical Atlantic Campaign
Long-distance propagation of 162 MHz shipping information links associated with sporadic E
Estimation of refractivity uncertainties and vertical error correlations in collocated radio occultations, radiosondes, and model forecasts
DeepPrecip: a deep neural network for precipitation retrievals
Machine learning-based prediction of Alpine foehn events using GNSS troposphere products: first results for Altdorf, Switzerland
Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm
Adaptive thermal image velocimetry of spatial wind movement on landscapes using near-target infrared cameras
Image muting of mixed precipitation to improve identification of regions of heavy snow in radar data
Extending water vapor measurement capability of photon-limited differential absorption lidars through simultaneous denoising and inversion
GPROF-NN: a neural-network-based implementation of the Goddard Profiling Algorithm
Sensitivity analysis of DSD retrievals from polarimetric radar in stratiform rain based on the μ–Λ relationship
On the use of high-frequency surface wave oceanographic research radars as bistatic single-frequency oblique ionospheric sounders
A statistically optimal analysis of systematic differences between Aeolus horizontal line-of-sight winds and NOAA's Global Forecast System
Hierarchical deconvolution for incoherent scatter radar data
An alternative cloud index for estimating downwelling surface solar irradiance from various satellite imagers in the framework of a Heliosat-V method
ERUO: a spectral processing routine for the Micro Rain Radar PRO (MRR-PRO)
On the derivation of zonal and meridional wind components from Aeolus horizontal line-of-sight wind
Quantification of lightning-produced NOx over the Pyrenees and the Ebro Valley by using different TROPOMI-NO2 and cloud research products
Sensitivity analysis of attenuation in convective rainfall at X-band frequency using the mountain reference technique
A new scanning scheme and flexible retrieval for mean winds and gusts from Doppler lidar measurements
Airborne measurements of directional reflectivity over the Arctic marginal sea ice zone
High-resolution typhoon precipitation integrations using satellite infrared observations and multisource data
Continuous temperature soundings at the stratosphere and lower mesosphere with a ground-based radiometer considering the Zeeman effect
Retrieval of solar-induced chlorophyll fluorescence (SIF) from satellite measurements: comparison of SIF between TanSat and OCO-2
Identification of tropical cyclones via deep convolutional neural network based on satellite cloud images
Time evolution of temperature profiles retrieved from 13 years of infrared atmospheric sounding interferometer (IASI) data using an artificial neural network
Emissivity retrievals with FORUM's end-to-end simulator: challenges and recommendations
Detecting wave features in Doppler radial velocity radar observations
Remote sensing of solar surface radiation – a reflection of concepts, applications and input data based on experience with the effective cloud albedo
Snow microphysical retrieval from the NASA D3R radar during ICE-POP 2018
Retrieval improvements for the ALADIN Airborne Demonstrator in support of the Aeolus wind product validation
Detection and Localization of F-layer Ionospheric Irregularities with Back Propagation Method Along Radio Occultation Ray Path
Cloud-probability-based estimation of black-sky surface albedo from AVHRR data
A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations
Differential absorption lidar measurements of water vapor by the High Altitude Lidar Observatory (HALO): retrieval framework and first results
Improving thermodynamic profile retrievals from microwave radiometers by including radio acoustic sounding system (RASS) observations
Calibration of radar differential reflectivity using quasi-vertical profiles
Mathieu Ratynski, Sergey Khaykin, Alain Hauchecorne, Robin Wing, Jean-Pierre Cammas, Yann Hello, and Philippe Keckhut
Atmos. Meas. Tech., 16, 997–1016, https://doi.org/10.5194/amt-16-997-2023, https://doi.org/10.5194/amt-16-997-2023, 2023
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Aeolus is the first spaceborne wind lidar providing global wind measurements since 2018. This study offers a comprehensive analysis of Aeolus instrument performance, using ground-based wind lidars and meteorological radiosondes, at tropical and mid-latitudes sites. The analysis allows assessing the long-term evolution of the satellite's performance for more than 3 years. The results will help further elaborate the understanding of the error sources and the behavior of the Doppler wind lidar.
Anne-Claire Billault-Roux, Gionata Ghiggi, Louis Jaffeux, Audrey Martini, Nicolas Viltard, and Alexis Berne
Atmos. Meas. Tech., 16, 911–940, https://doi.org/10.5194/amt-16-911-2023, https://doi.org/10.5194/amt-16-911-2023, 2023
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Better understanding and modeling snowfall properties and processes is relevant to many fields, ranging from weather forecasting to aircraft safety. Meteorological radars can be used to gain insights into the microphysics of snowfall. In this work, we propose a new method to retrieve snowfall properties from measurements of radars with different frequencies. It relies on an original deep-learning framework, which incorporates knowledge of the underlying physics, i.e., electromagnetic scattering.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, and GyuWon Lee
Atmos. Meas. Tech., 16, 845–869, https://doi.org/10.5194/amt-16-845-2023, https://doi.org/10.5194/amt-16-845-2023, 2023
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Since the winds in clear-air conditions usually play an important role in the initiation of various weather systems and phenomena, the modified Wind Synthesis System using Doppler Measurements (WISSDOM) synthesis scheme was developed to derive high-quality and high-spatial-resolution 3D winds under clear-air conditions. The performance and accuracy of derived 3D winds from this modified scheme were evaluated with an extreme strong wind event over complex terrain in Pyeongchang, South Korea.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
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Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Michael Frech, Cornelius Hald, Maximilian Schaper, Bertram Lange, and Benjamin Rohrdantz
Atmos. Meas. Tech., 16, 295–309, https://doi.org/10.5194/amt-16-295-2023, https://doi.org/10.5194/amt-16-295-2023, 2023
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Weather radar data are the backbone of a lot of meteorological products. In order to obtain a better low-level coverage with radar data, additional systems have to be included. The frequency range in which radars are allowed to operate is limited. A potential radar-to-radar interference has to be avoided. The paper derives guidelines on how additional radars can be included into a C-band weather radar network and how interferences can be avoided.
Yeeun Lee, Myoung-Hwan Ahn, Mina Kang, and Mijin Eo
Atmos. Meas. Tech., 16, 153–168, https://doi.org/10.5194/amt-16-153-2023, https://doi.org/10.5194/amt-16-153-2023, 2023
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This study aims to verify that a partly defective hyperspectral measurement can be successfully reproduced with concise machine learning models coupled with principal component analysis. Evaluation of the approach is performed with radiances and retrieval results of ozone and cloud properties. Considering that GEMS is the first geostationary UV–VIS hyperspectral spectrometer, we expect our findings can be introduced further to similar geostationary environmental instruments to be launched soon.
Mathias Gergely, Maximilian Schaper, Matthias Toussaint, and Michael Frech
Atmos. Meas. Tech., 15, 7315–7335, https://doi.org/10.5194/amt-15-7315-2022, https://doi.org/10.5194/amt-15-7315-2022, 2022
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This study presents the new vertically pointing birdbath scan of the German C-band radar network, which provides high-resolution profiles of precipitating clouds above all DWD weather radars since the spring of 2021. Our AI-based postprocessing method for filtering and analyzing the recorded radar data offers a unique quantitative view into a wide range of precipitation events from snowfall over stratiform rain to intense frontal showers and will be used to complement DWD's operational services.
Kenneth A. Brown and Thomas G. Herges
Atmos. Meas. Tech., 15, 7211–7234, https://doi.org/10.5194/amt-15-7211-2022, https://doi.org/10.5194/amt-15-7211-2022, 2022
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The character of the airflow around and within wind farms has a significant impact on the energy output and longevity of the wind turbines in the farm. For both research and control purposes, accurate measurements of the wind speed are required, and these are often accomplished with remote sensing devices. This article pertains to a field experiment of a lidar mounted to a wind turbine and demonstrates three data post-processing techniques with efficacy at extracting useful airflow information.
Xavier Calbet, Cintia Carbajal Henken, Sergio DeSouza-Machado, Bomin Sun, and Tony Reale
Atmos. Meas. Tech., 15, 7105–7118, https://doi.org/10.5194/amt-15-7105-2022, https://doi.org/10.5194/amt-15-7105-2022, 2022
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Water vapor concentration in the atmosphere at small scales (< 6 km) is considered. The measurements show Gaussian random field behavior following Kolmogorov's theory of turbulence two-thirds law. These properties can be useful when estimating the water vapor variability within a given observed satellite scene or when different water vapor measurements have to be merged consistently.
Qiuyu Chen, Konstantin Ntokas, Björn Linder, Lukas Krasauskas, Manfred Ern, Peter Preusse, Jörn Ungermann, Erich Becker, Martin Kaufmann, and Martin Riese
Atmos. Meas. Tech., 15, 7071–7103, https://doi.org/10.5194/amt-15-7071-2022, https://doi.org/10.5194/amt-15-7071-2022, 2022
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Observations of phase speed and direction spectra as well as zonal mean net gravity wave momentum flux are required to understand how gravity waves reach the mesosphere–lower thermosphere and how they there interact with background flow. To this end we propose flying two CubeSats, each deploying a spatial heterodyne spectrometer for limb observation of the airglow. End-to-end simulations demonstrate that individual gravity waves are retrieved faithfully for the expected instrument performance.
Simon Pfreundschuh, Ingrid Ingemarsson, Patrick Eriksson, Daniel A. Vila, and Alan J. P. Calheiros
Atmos. Meas. Tech., 15, 6907–6933, https://doi.org/10.5194/amt-15-6907-2022, https://doi.org/10.5194/amt-15-6907-2022, 2022
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We used methods from the field of artificial intelligence to train an algorithm to estimate rain from satellite observations. In contrast to other methods, our algorithm not only estimates rain, but also the uncertainty of the estimate. Using independent measurements from rain gauges, we show that our method performs better than currently available methods and that the provided uncertainty estimates are reliable. Our method makes satellite-based measurements of rain more accurate and reliable.
Lars Norin
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-299, https://doi.org/10.5194/amt-2022-299, 2022
Revised manuscript accepted for AMT
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The atmosphere can cause radar beams to bend more or less towards the ground. When the atmosphere differs from standard atmospheric conditions the propagation is called anomalous. Radars affected by anomalous propagation can receive ground clutter far beyond the radar horizon. In this work 4.5 years of data from five operational Swedish weather radars are presented. Analyses of the data reveal a strong seasonal cycle and weaker diurnal cycle in ground clutter from across nearby waters.
Maximilian Schaper, Michael Frech, David Michaelis, Cornelius Hald, and Benjamin Rohrdantz
Atmos. Meas. Tech., 15, 6625–6642, https://doi.org/10.5194/amt-15-6625-2022, https://doi.org/10.5194/amt-15-6625-2022, 2022
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C-band weather radar data are commonly compromised by radio frequency interference (RFI) from external sources. It is not possible to separate a superimposed interference signal from the radar data. Therefore, the best course of action is to shut down RFI sources as quickly as possible. An automated RFI detection algorithm has been developed. Since its implementation, persistent RFI sources are eliminated much more quickly, while the number of short-lived RFI sources keeps steadily increasing.
Oliver Lux, Benjamin Witschas, Alexander Geiß, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Stephan Rahm, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech., 15, 6467–6488, https://doi.org/10.5194/amt-15-6467-2022, https://doi.org/10.5194/amt-15-6467-2022, 2022
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We discuss the influence of different quality control schemes on the results of Aeolus wind product validation and present statistical tools for ensuring consistency and comparability among diverse validation studies with regard to the specific error characteristics of the Rayleigh-clear and Mie-cloudy winds. The developed methods are applied for the validation of Aeolus winds against an ECMWF model background and airborne wind lidar data from the Joint Aeolus Tropical Atlantic Campaign.
Alex T. Chartier, Thomas R. Hanley, and Daniel J. Emmons
Atmos. Meas. Tech., 15, 6387–6393, https://doi.org/10.5194/amt-15-6387-2022, https://doi.org/10.5194/amt-15-6387-2022, 2022
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This is a study of anomalous long-distance (>1000 km) radio propagation that was identified in United States Coast Guard monitors of automatic identification system (AIS) shipping transmissions at 162 MHz. Our results indicate this long-distance propagation is caused by dense sporadic E layers in the daytime ionosphere, which were observed by nearby ionosondes at the same time. This finding is surprising because it indicates these sporadic E layers may be far more dense than previously thought.
Johannes K. Nielsen, Hans Gleisner, Stig Syndergaard, and Kent B. Lauritsen
Atmos. Meas. Tech., 15, 6243–6256, https://doi.org/10.5194/amt-15-6243-2022, https://doi.org/10.5194/amt-15-6243-2022, 2022
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This paper provides a new way to estimate uncertainties and error correlations. The method is a generalization of a known method called the
three-cornered hat: Instead of calculating uncertainties from assumed knowledge about the observation method, uncertainties and error correlations are estimated statistically from tree independent observation series, measuring the same variable. The results are useful for future estimation of atmospheric-specific humidity from the bending of radio waves.
Fraser King, George Duffy, Lisa Milani, Christopher G. Fletcher, Claire Pettersen, and Kerstin Ebell
Atmos. Meas. Tech., 15, 6035–6050, https://doi.org/10.5194/amt-15-6035-2022, https://doi.org/10.5194/amt-15-6035-2022, 2022
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Under warmer global temperatures, precipitation patterns are expected to shift substantially, with critical impact on the global water-energy budget. In this work, we develop a deep learning model for predicting snow and rain accumulation based on surface radar observations of the lower atmosphere. Our model demonstrates improved skill over traditional methods and provides new insights into the regions of the atmosphere that provide the most significant contributions to high model accuracy.
Matthias Aichinger-Rosenberger, Elmar Brockmann, Laura Crocetti, Benedikt Soja, and Gregor Moeller
Atmos. Meas. Tech., 15, 5821–5839, https://doi.org/10.5194/amt-15-5821-2022, https://doi.org/10.5194/amt-15-5821-2022, 2022
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This study develops an innovative approach for the detection and prediction of foehn winds. The approach uses products generated from GNSS (Global Navigation Satellite Systems) in combination with machine learning-based classification algorithms to detect and predict foehn winds at Altdorf, Switzerland. Results are encouraging and comparable to similar studies using meteorological data, which might qualify the method as an additional tool for short-term foehn forecasting in the future.
Gunter Stober, Alan Liu, Alexander Kozlovsky, Zishun Qiao, Ales Kuchar, Christoph Jacobi, Chris Meek, Diego Janches, Guiping Liu, Masaki Tsutsumi, Njål Gulbrandsen, Satonori Nozawa, Mark Lester, Evgenia Belova, Johan Kero, and Nicholas Mitchell
Atmos. Meas. Tech., 15, 5769–5792, https://doi.org/10.5194/amt-15-5769-2022, https://doi.org/10.5194/amt-15-5769-2022, 2022
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Precise and accurate measurements of vertical winds at the mesosphere and lower thermosphere are rare. Although meteor radars have been used for decades to observe horizontal winds, their ability to derive reliable vertical wind measurements was always questioned. In this article, we provide mathematical concepts to retrieve mathematically and physically consistent solutions, which are compared to the state-of-the-art non-hydrostatic model UA-ICON.
Benjamin Schumacher, Marwan Katurji, Jiawei Zhang, Peyman Zawar-Reza, Benjamin Adams, and Matthias Zeeman
Atmos. Meas. Tech., 15, 5681–5700, https://doi.org/10.5194/amt-15-5681-2022, https://doi.org/10.5194/amt-15-5681-2022, 2022
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This investigation presents adaptive thermal image velocimetry (A-TIV), a newly developed algorithm to spatially measure near-surface atmospheric velocities using an infrared camera mounted on uncrewed aerial vehicles. A validation and accuracy assessment of the retrieved velocity fields shows the successful application of the algorithm over short-cut grass and turf surfaces in dry conditions. This provides new opportunities for atmospheric scientists to study surface–atmosphere interactions.
Laura M. Tomkins, Sandra E. Yuter, Matthew A. Miller, and Luke R. Allen
Atmos. Meas. Tech., 15, 5515–5525, https://doi.org/10.5194/amt-15-5515-2022, https://doi.org/10.5194/amt-15-5515-2022, 2022
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Locally higher radar reflectivity values in winter storms can mean more snowfall or a transition from snow to mixtures of snow, partially melted snow, and/or rain. We use the correlation coefficient to de-emphasize regions of mixed precipitation. Visual muting is valuable for analyzing and monitoring evolving weather conditions during winter storm events.
Willem J. Marais and Matthew Hayman
Atmos. Meas. Tech., 15, 5159–5180, https://doi.org/10.5194/amt-15-5159-2022, https://doi.org/10.5194/amt-15-5159-2022, 2022
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For atmospheric science and weather prediction, it is important to make water vapor measurements in real time. A low-cost lidar instrument has been developed by Montana State University and the National Center for Atmospheric Research. We developed an advanced signal-processing method to extend the scientific capability of the lidar instrument. With the new method we show that the maximum altitude at which the MPD can make water vapor measurements can be extended up to 8 km.
Simon Pfreundschuh, Paula J. Brown, Christian D. Kummerow, Patrick Eriksson, and Teodor Norrestad
Atmos. Meas. Tech., 15, 5033–5060, https://doi.org/10.5194/amt-15-5033-2022, https://doi.org/10.5194/amt-15-5033-2022, 2022
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The Global Precipitation Measurement mission is an international satellite mission providing regular global rain measurements. We present two newly developed machine-learning-based implementations of one of the algorithms responsible for turning the satellite observations into rain measurements. We show that replacing the current algorithm with a neural network improves the accuracy of the measurements. A neural network that also makes use of spatial information unlocks further improvements.
Christos Gatidis, Marc Schleiss, and Christine Unal
Atmos. Meas. Tech., 15, 4951–4969, https://doi.org/10.5194/amt-15-4951-2022, https://doi.org/10.5194/amt-15-4951-2022, 2022
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Knowledge of the raindrop size distribution (DSD) is crucial for understanding rainfall microphysics and quantifying uncertainty in quantitative precipitation estimates. In this study a general overview of the DSD retrieval approach from a polarimetric radar is discussed, highlighting sensitivity to potential sources of errors, either directly linked to the radar measurements or indirectly through the critical modeling assumptions behind the method such as the shape–size (μ–Λ) relationship.
Stephen R. Kaeppler, Ethan S. Miller, Daniel Cole, and Teresa Updyke
Atmos. Meas. Tech., 15, 4531–4545, https://doi.org/10.5194/amt-15-4531-2022, https://doi.org/10.5194/amt-15-4531-2022, 2022
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This investigation demonstrates how useful ionospheric parameters can be extracted from existing high-frequency radars that are used for oceanographic research. The methodology presented can be used by scientists and radio amateurs to understand ionospheric dynamics.
Hui Liu, Kevin Garrett, Kayo Ide, Ross N. Hoffman, and Katherine E. Lukens
Atmos. Meas. Tech., 15, 3925–3940, https://doi.org/10.5194/amt-15-3925-2022, https://doi.org/10.5194/amt-15-3925-2022, 2022
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A total least squares (TLS) regression is used to optimally estimate linear speed-dependent biases between Aeolus Level-2B winds and short-term (6 h) forecasts of NOAA’s FV3GFS. The winds for 1–7 September 2019 are examined. Clear speed-dependent biases for both Mie and Rayleigh winds are found, particularly in the tropics and Southern Hemisphere. Use of the TLS correction improves the forecast of the 26–28 November 2019 winter storm over the USA.
Snizhana Ross, Arttu Arjas, Ilkka I. Virtanen, Mikko J. Sillanpää, Lassi Roininen, and Andreas Hauptmann
Atmos. Meas. Tech., 15, 3843–3857, https://doi.org/10.5194/amt-15-3843-2022, https://doi.org/10.5194/amt-15-3843-2022, 2022
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Radar measurements of thermal fluctuations in the Earth's ionosphere produce weak signals, and tuning to specific altitudes results in suboptimal resolution for other regions, making an accurate analysis of these changes difficult. A novel approach to improve the resolution and remove measurement noise is considered. The method can capture variable characteristics, making it ideal for the study of a large range of data. Synthetically generated examples and two measured datasets were considered.
Benoît Tournadre, Benoît Gschwind, Yves-Marie Saint-Drenan, Xuemei Chen, Rodrigo Amaro E Silva, and Philippe Blanc
Atmos. Meas. Tech., 15, 3683–3704, https://doi.org/10.5194/amt-15-3683-2022, https://doi.org/10.5194/amt-15-3683-2022, 2022
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Solar radiation received by the Earth's surface is valuable information for various fields like the photovoltaic industry or climate research. Pictures taken from satellites can be used to estimate the solar radiation from cloud reflectivity. Two issues for a good estimation are different instrumentations and orbits. We modify a widely used method that is today only used on geostationary satellites, so it can be applied on instruments on different orbits and with different sensitivities.
Alfonso Ferrone, Anne-Claire Billault-Roux, and Alexis Berne
Atmos. Meas. Tech., 15, 3569–3592, https://doi.org/10.5194/amt-15-3569-2022, https://doi.org/10.5194/amt-15-3569-2022, 2022
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The Micro Rain Radar PRO (MRR-PRO) is a meteorological radar, with a relevant set of features for deployment in remote locations. We developed an algorithm, named ERUO, for the processing of its measurements of snowfall. The algorithm addresses typical issues of the raw spectral data, such as interference lines, but also improves the quality and sensitivity of the radar variables. ERUO has been evaluated over four different datasets collected in Antarctica and in the Swiss Jura.
Isabell Krisch, Neil P. Hindley, Oliver Reitebuch, and Corwin J. Wright
Atmos. Meas. Tech., 15, 3465–3479, https://doi.org/10.5194/amt-15-3465-2022, https://doi.org/10.5194/amt-15-3465-2022, 2022
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The Aeolus satellite measures global height resolved profiles of wind along a certain line-of-sight. However, for atmospheric dynamics research, wind measurements along the three cardinal axes are most useful. This paper presents methods to convert the measurements into zonal and meridional wind components. By combining the measurements during ascending and descending orbits, we achieve good derivation of zonal wind (equatorward of 80° latitude) and meridional wind (poleward of 70° latitude).
Francisco J. Pérez-Invernón, Heidi Huntrieser, Thilo Erbertseder, Diego Loyola, Pieter Valks, Song Liu, Dale J. Allen, Kenneth E. Pickering, Eric J. Bucsela, Patrick Jöckel, Jos van Geffen, Henk Eskes, Sergio Soler, Francisco J. Gordillo-Vázquez, and Jeff Lapierre
Atmos. Meas. Tech., 15, 3329–3351, https://doi.org/10.5194/amt-15-3329-2022, https://doi.org/10.5194/amt-15-3329-2022, 2022
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Lightning, one of the major sources of nitrogen oxides in the atmosphere, contributes to the tropospheric concentration of ozone and to the oxidizing capacity of the atmosphere. In this work, we contribute to improving the estimation of lightning-produced nitrogen oxides in the Ebro Valley and the Pyrenees by using two different TROPOMI products and comparing the results.
Guy Delrieu, Anil Kumar Khanal, Frédéric Cazenave, and Brice Boudevillain
Atmos. Meas. Tech., 15, 3297–3314, https://doi.org/10.5194/amt-15-3297-2022, https://doi.org/10.5194/amt-15-3297-2022, 2022
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The RadAlp experiment aims at improving quantitative precipitation estimation in the Alps thanks to X-band polarimetric radars and in situ measurements deployed in Grenoble, France. We revisit the physics of propagation and attenuation of microwaves in rain. We perform a generalized sensitivity analysis in order to establish useful parameterization for attenuation corrections. Originality lies in the use of otherwise undesired mountain returns for constraining the considered physical model.
Julian Steinheuer, Carola Detring, Frank Beyrich, Ulrich Löhnert, Petra Friederichs, and Stephanie Fiedler
Atmos. Meas. Tech., 15, 3243–3260, https://doi.org/10.5194/amt-15-3243-2022, https://doi.org/10.5194/amt-15-3243-2022, 2022
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Doppler wind lidars (DWLs) allow the determination of wind profiles with high vertical resolution and thus provide an alternative to meteorological towers. We address the question of whether wind gusts can be derived since they are short-lived phenomena. Therefore, we compare different DWL configurations and develop a new method applicable to all of them. A fast continuous scanning mode that completes a full observation cycle within 3.4 s is found to be the best-performing configuration.
Sebastian Becker, André Ehrlich, Evelyn Jäkel, Tim Carlsen, Michael Schäfer, and Manfred Wendisch
Atmos. Meas. Tech., 15, 2939–2953, https://doi.org/10.5194/amt-15-2939-2022, https://doi.org/10.5194/amt-15-2939-2022, 2022
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Airborne radiation measurements are used to characterize the solar directional reflection of a mixture of Arctic sea ice and open-ocean surfaces in the transition zone between both surface types. The mixture reveals reflection properties of both surface types. It is shown that the directional reflection of the mixture can be reconstructed from the directional reflection of the individual surfaces, accounting for the special conditions present in the transition zone.
You Zhao, Chao Liu, Di Di, Ziqiang Ma, and Shihao Tang
Atmos. Meas. Tech., 15, 2791–2805, https://doi.org/10.5194/amt-15-2791-2022, https://doi.org/10.5194/amt-15-2791-2022, 2022
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A typhoon is a high-impact atmospheric phenomenon that causes most significant socioeconomic damage, and its precipitation observation is always needed for typhoon characteristics and disaster prevention. This study developed a typhoon precipitation fusion method to combine observations from satellite radiometers, rain gauges and reanalysis to provide much improved typhoon precipitation datasets.
Witali Krochin, Francisco Navas-Guzmán, David Kuhl, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 15, 2231–2249, https://doi.org/10.5194/amt-15-2231-2022, https://doi.org/10.5194/amt-15-2231-2022, 2022
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This study leverages atmospheric temperature measurements performed with a ground-based radiometer making use of data that was collected during a 4-year observational campaign applying a new retrieval algorithm that improves the maximal altitude range from 45 to 55 km. The measurements are validated against two independent data sets, MERRA2 reanalysis data and the meteorological analysis of NAVGEM-HA.
Lu Yao, Yi Liu, Dongxu Yang, Zhaonan Cai, Jing Wang, Chao Lin, Naimeng Lu, Daren Lyu, Longfei Tian, Maohua Wang, Zengshan Yin, Yuquan Zheng, and Sisi Wang
Atmos. Meas. Tech., 15, 2125–2137, https://doi.org/10.5194/amt-15-2125-2022, https://doi.org/10.5194/amt-15-2125-2022, 2022
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A physics-based SIF retrieval algorithm, IAPCAS/SIF, is introduced and applied to OCO-2 and TanSat measurements. The strong linear relationship between OCO-2 SIF retrieved by IAPCAS/SIF and the official product indicates the algorithm's reliability. The good consistency in the spatiotemporal patterns and magnitude of the OCO-2 and TanSat SIF products suggests that the combinative usage of multi-satellite products has potential and that such work would contribute to further research.
Biao Tong, Xiangfei Sun, Jiyang Fu, Yuncheng He, and Pakwai Chan
Atmos. Meas. Tech., 15, 1829–1848, https://doi.org/10.5194/amt-15-1829-2022, https://doi.org/10.5194/amt-15-1829-2022, 2022
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In recent years, there has been numerous research on tropical cyclone (TC) observation based on satellite cloud images (SCIs), but most methods are limited by low efficiency and subjectivity. To overcome subjectivity and improve efficiency of traditional methods, this paper uses deep learning technology to do further research on fingerprint identification of TCs. Results provide an automatic and objective method to distinguish TCs from SCIs and are convenient for subsequent research.
Marie Bouillon, Sarah Safieddine, Simon Whitburn, Lieven Clarisse, Filipe Aires, Victor Pellet, Olivier Lezeaux, Noëlle A. Scott, Marie Doutriaux-Boucher, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 1779–1793, https://doi.org/10.5194/amt-15-1779-2022, https://doi.org/10.5194/amt-15-1779-2022, 2022
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The IASI instruments have been observing Earth since 2007. We use a neural network to retrieve atmospheric temperatures. This new temperature data record is validated against other datasets and shows good agreement. We use this new dataset to compute trends over the 2008–2020 period. We found a warming of the troposphere, more important at the poles. In the stratosphere, we found that temperatures decrease everywhere except at the South Pole. The cooling is more pronounced at the South pole.
Maya Ben-Yami, Hilke Oetjen, Helen Brindley, William Cossich, Dulce Lajas, Tiziano Maestri, Davide Magurno, Piera Raspollini, Luca Sgheri, and Laura Warwick
Atmos. Meas. Tech., 15, 1755–1777, https://doi.org/10.5194/amt-15-1755-2022, https://doi.org/10.5194/amt-15-1755-2022, 2022
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Spectral emissivity is a key property of the Earth's surface. Few measurements exist in the far-infrared, despite recent work showing that its contribution is important for accurate modelling of global climate. In preparation for ESA’s EE9 FORUM mission (launch in 2026), this study takes the first steps towards the development of an operational emissivity retrieval for FORUM by investigating the sensitivity of the emissivity product to different physical and operational parameters.
Matthew A. Miller, Sandra E. Yuter, Nicole P. Hoban, Laura M. Tomkins, and Brian A. Colle
Atmos. Meas. Tech., 15, 1689–1702, https://doi.org/10.5194/amt-15-1689-2022, https://doi.org/10.5194/amt-15-1689-2022, 2022
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Apparent waves in the atmosphere and similar features in storm winds can be detected by taking the difference between successive Doppler weather radar scans measuring radar-relative storm air motions. Applying image filtering to the difference data better isolates the detected signal. This technique is a useful tool in weather research and forecasting since such waves can trigger or enhance precipitation.
Richard Müller and Uwe Pfeifroth
Atmos. Meas. Tech., 15, 1537–1561, https://doi.org/10.5194/amt-15-1537-2022, https://doi.org/10.5194/amt-15-1537-2022, 2022
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The great works of physics teach us that a central paradigm of science should be to make methods and theories as easy as possible and as complex as needed. This paper provides a brief review of remote sensing of solar surface irradiance based on this paradigm.
S. Joseph Munchak, Robert S. Schrom, Charles N. Helms, and Ali Tokay
Atmos. Meas. Tech., 15, 1439–1464, https://doi.org/10.5194/amt-15-1439-2022, https://doi.org/10.5194/amt-15-1439-2022, 2022
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The ability to measure snowfall with weather radar has greatly advanced with the development of techniques that utilize dual-polarization measurements, which provide information about the snow particle shape and orientation, and multi-frequency measurements, which provide information about size and density. This study combines these techniques with the NASA D3R radar, which provides dual-frequency polarimetric measurements, with data that were observed during the 2018 Winter Olympics.
Oliver Lux, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Benjamin Witschas, Stephan Rahm, Alexander Geiß, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech., 15, 1303–1331, https://doi.org/10.5194/amt-15-1303-2022, https://doi.org/10.5194/amt-15-1303-2022, 2022
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The article discusses modifications in the wind retrieval of the ALADIN Airborne Demonstrator (A2D) – one of the key instruments for the validation of Aeolus. Thanks to the retrieval refinements, which are demonstrated in the context of two airborne campaigns in 2019, the systematic and random wind errors of the A2D were significantly reduced, thereby enhancing its validation capabilities. Finally, wind comparisons between A2D and Aeolus for the validation of the satellite data are presented.
Vinícius Ludwig-Barbosa, Joel Rasch, Thomas Sievert, Anders Carlström, Mats I. Pettersson, Viet Thuy Vu, and Jacob Christensen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-57, https://doi.org/10.5194/amt-2022-57, 2022
Revised manuscript accepted for AMT
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The back propagation method has its capabilities and limitations regarding detection and location of irregularity regions in the ionosphere, e.g., equatorial plasma bubbles, evaluated. The assessment was performed with simulations in which different scenarios were assumed. The results showed that the location estimate is possible if the amplitude of the ionospheric is stronger than the instrument noise level. Further, multiple patches can be resolved if regions are well separated.
Terhikki Manninen, Emmihenna Jääskeläinen, Niilo Siljamo, Aku Riihelä, and Karl-Göran Karlsson
Atmos. Meas. Tech., 15, 879–893, https://doi.org/10.5194/amt-15-879-2022, https://doi.org/10.5194/amt-15-879-2022, 2022
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A new method for cloud-correcting observations of surface albedo is presented for AVHRR data. Instead of a binary cloud mask, it applies cloud probability values smaller than 20% of the A3 edition of the CLARA (CM SAF cLoud, Albedo and surface Radiation dataset from AVHRR data) record provided by the Satellite Application Facility on Climate Monitoring (CM SAF) project of EUMETSAT. According to simulations, the 90% quantile was 1.1% for the absolute albedo error and 2.2% for the relative error.
Shihan Chen, Yuanjian Yang, Fei Deng, Yanhao Zhang, Duanyang Liu, Chao Liu, and Zhiqiu Gao
Atmos. Meas. Tech., 15, 735–756, https://doi.org/10.5194/amt-15-735-2022, https://doi.org/10.5194/amt-15-735-2022, 2022
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This paper proposes a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. The spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. The present RF model framework for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII.
Brian J. Carroll, Amin R. Nehrir, Susan A. Kooi, James E. Collins, Rory A. Barton-Grimley, Anthony Notari, David B. Harper, and Joseph Lee
Atmos. Meas. Tech., 15, 605–626, https://doi.org/10.5194/amt-15-605-2022, https://doi.org/10.5194/amt-15-605-2022, 2022
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HALO is a recently developed lidar system that demonstrates new technologies and advanced algorithms for profiling water vapor as well as aerosol and cloud properties. The high-resolution, high-accuracy measurements have unique advantages within the suite of atmospheric instrumentation, such as directly trading water vapor measurement resolution for precision. This paper provides the methodology and first water vapor results, showing agreement with in situ and spaceborne sounder measurements.
Irina V. Djalalova, David D. Turner, Laura Bianco, James M. Wilczak, James Duncan, Bianca Adler, and Daniel Gottas
Atmos. Meas. Tech., 15, 521–537, https://doi.org/10.5194/amt-15-521-2022, https://doi.org/10.5194/amt-15-521-2022, 2022
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Short summary
In this paper we investigate the synergy obtained by combining active (radio acoustic sounding system – RASS) and passive (microwave radiometer) remote sensing observations to obtain temperature vertical profiles through a radiative transfer model. Inclusion of the RASS observations leads to more accurate temperature profiles from the surface to 5 km above ground, well above the maximum height of the RASS observations themselves (2000 m), when compared to the microwave radiometer used alone.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech., 15, 503–520, https://doi.org/10.5194/amt-15-503-2022, https://doi.org/10.5194/amt-15-503-2022, 2022
Short summary
Short summary
In this work, we review the use of quasi-vertical profiles for monitoring the calibration of the radar differential reflectivity ZDR. We validate the proposed method by comparing its results against the traditional approach based on measurements taken at 90°; we observed good agreement as the errors are within 0.2 dB. Additionally, we compare the results of the proposed method with ZDR derived from disdrometers; the errors are reasonable considering factors discussed in the paper.
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Short summary
Tropical atmospheric variability is often described using proxy indices of the Quasi-Biennial Oscillation and the El Niño–Southern Oscillation. We introduce new proxies derived from GNSS radio occultation (RO) satellite measurements. Using the high vertical resolution of the RO temperature fields we obtain altitude-resolved indices which can improve the description of atmospheric variability patterns and can be used in climate studies where a detailed knowledge of these patterns is required.
Tropical atmospheric variability is often described using proxy indices of the Quasi-Biennial...