Articles | Volume 17, issue 2
https://doi.org/10.5194/amt-17-515-2024
© Author(s) 2024. 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-17-515-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
25 Jan 2024
Research article | Highlight paper |
| 25 Jan 2024
| 25 Jan 2024
GPROF V7 and beyond: assessment of current and potential future versions of the GPROF passive microwave precipitation retrievals against ground radar measurements over the continental US and the Pacific Ocean
Simon Pfreundschuh
CORRESPONDING AUTHOR
Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USA
Department of Space, Earth and Environment, Chalmers University of Technology, 41296 Gothenburg, Sweden
Clément Guilloteau
Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, CA 92697, USA
Paula J. Brown
Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USA
Christian D. Kummerow
Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USA
Patrick Eriksson
Department of Space, Earth and Environment, Chalmers University of Technology, 41296 Gothenburg, Sweden
Related authors
Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson
Atmos. Meas. Tech., 17, 4337–4368, https://doi.org/10.5194/amt-17-4337-2024, https://doi.org/10.5194/amt-17-4337-2024, 2024
Short summary
Short summary
The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limitations of currently available data records of cloud properties. In this work, we address this issue by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.
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
Short summary
Short summary
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.
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
Short summary
Short summary
Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
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
Short summary
Short summary
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.
Simon Pfreundschuh, Stuart Fox, Patrick Eriksson, David Duncan, Stefan A. Buehler, Manfred Brath, Richard Cotton, and Florian Ewald
Atmos. Meas. Tech., 15, 677–699, https://doi.org/10.5194/amt-15-677-2022, https://doi.org/10.5194/amt-15-677-2022, 2022
Short summary
Short summary
We test a novel method to remotely measure ice particles in clouds. This is important because such measurements are required to improve climate and weather models. The method combines a radar with newly developed sensors measuring microwave radiation at very short wavelengths. We use observations made from aircraft flying above the cloud and compare them to real measurements from inside the cloud. This works well given that one can model the ice particles in the cloud sufficiently well.
Inderpreet Kaur, Patrick Eriksson, Simon Pfreundschuh, and David Ian Duncan
Atmos. Meas. Tech., 14, 2957–2979, https://doi.org/10.5194/amt-14-2957-2021, https://doi.org/10.5194/amt-14-2957-2021, 2021
Short summary
Short summary
Currently, cloud contamination in microwave humidity channels is addressed using filtering schemes. We present an approach to correct the cloud-affected microwave humidity radiances using a Bayesian machine learning technique. The technique combines orthogonal information from microwave channels to obtain a probabilistic prediction of the clear-sky radiances. With this approach, we are able to predict bias-free clear-sky radiances with well-represented case-specific uncertainty estimates.
Simon Pfreundschuh, Patrick Eriksson, Stefan A. Buehler, Manfred Brath, David Duncan, Richard Larsson, and Robin Ekelund
Atmos. Meas. Tech., 13, 4219–4245, https://doi.org/10.5194/amt-13-4219-2020, https://doi.org/10.5194/amt-13-4219-2020, 2020
Short summary
Short summary
The next generation of European operational weather satellites will carry a novel microwave sensor, the Ice Cloud Imager (ICI), which will provide observations of clouds at microwave frequencies that were not available before. We investigate the potential benefits of combining observations from ICI with that of a radar. We find that such combined observations provide additional information on the properties of the cloud and help to reduce uncertainties in retrieved mass and number densities.
Jonas Hagen, Klemens Hocke, Gunter Stober, Simon Pfreundschuh, Axel Murk, and Niklaus Kämpfer
Atmos. Chem. Phys., 20, 2367–2386, https://doi.org/10.5194/acp-20-2367-2020, https://doi.org/10.5194/acp-20-2367-2020, 2020
Short summary
Short summary
The middle atmosphere (30 to 70 km altitude) is stratified and, despite very strong horizontal winds, there is less mixing between the horizontal layers. An important driver for the energy exchange between the layers in this regime is atmospheric tides, which are waves that are driven by the diurnal cycle of solar heating. We measure these tides in the wind field for the first time using a ground-based passive instrument. Ultimately, such measurements could be used to improve atmospheric models.
Robin Ekelund, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 13, 501–520, https://doi.org/10.5194/amt-13-501-2020, https://doi.org/10.5194/amt-13-501-2020, 2020
Short summary
Short summary
Atmospheric ice particles (e.g. snow and ice crystals) are an important part of weather, climate, and the hydrological cycle. This study investigates whether combined satellite measurements by radar and radiometers at microwave wavelengths can be used to find the most likely shape of such ice particles. The method was limited when using only currently operating sensors (CloudSat radar and the GPM Microwave Imager) but shows promise if the upcoming Ice Cloud Imager is also considered.
David Ian Duncan, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 12, 6341–6359, https://doi.org/10.5194/amt-12-6341-2019, https://doi.org/10.5194/amt-12-6341-2019, 2019
Short summary
Short summary
The overlapping beams of some satellite observations contain spatial information that is discarded by most data processing techniques. This study applies an established technique in a new way to improve the spatial resolution of retrieval targets, effectively using the overlapping information to achieve a higher ultimate resolution. It is argued that this is a more optimal use of the total information available from current microwave sensors, using AMSR2 as an example.
David Ian Duncan, Patrick Eriksson, Simon Pfreundschuh, Christian Klepp, and Daniel C. Jones
Atmos. Chem. Phys., 19, 6969–6984, https://doi.org/10.5194/acp-19-6969-2019, https://doi.org/10.5194/acp-19-6969-2019, 2019
Short summary
Short summary
Raindrop size distributions have not been systematically studied over the oceans but are significant for remotely sensing, assimilating, and modeling rain. Here we investigate raindrop populations with new global in situ data, compare them against satellite estimates, and explore a new technique to classify the shapes of these distributions. The results indicate the inadequacy of a commonly assumed shape in some regions and the sizable impact of shape variability on satellite measurements.
Simon Pfreundschuh, Patrick Eriksson, David Duncan, Bengt Rydberg, Nina Håkansson, and Anke Thoss
Atmos. Meas. Tech., 11, 4627–4643, https://doi.org/10.5194/amt-11-4627-2018, https://doi.org/10.5194/amt-11-4627-2018, 2018
Short summary
Short summary
A novel neural-network-based retrieval method is proposed that combines the flexibility and computational efficiency of machine learning retrievals with the consistent treatment of uncertainties of Bayesian methods. Numerical experiments are presented that show the consistency of the proposed method with the Bayesian formulation as well as its ability to represent non-Gaussian retrieval errors. With this, the proposed method overcomes important limitations of traditional methods.
Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson
Atmos. Meas. Tech., 17, 5957–5987, https://doi.org/10.5194/amt-17-5957-2024, https://doi.org/10.5194/amt-17-5957-2024, 2024
Short summary
Short summary
The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.
Chia-Pang Kuo and Christian Kummerow
Atmos. Meas. Tech., 17, 5637–5653, https://doi.org/10.5194/amt-17-5637-2024, https://doi.org/10.5194/amt-17-5637-2024, 2024
Short summary
Short summary
A small satellite about the size of a shoe box, named TEMPEST, carries only a microwave sensor and is designed to measure the water cycle of the Earth from space in an economical way compared with traditional satellites, which have additional infrared sensors. To overcome the limitation, extra infrared signals from GOES-R ABI are combined with TEMPEST microwave measurements. Compared with ground observations, improved humidity information is extracted from the merged TEMPEST and ABI signals.
Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson
Atmos. Meas. Tech., 17, 4337–4368, https://doi.org/10.5194/amt-17-4337-2024, https://doi.org/10.5194/amt-17-4337-2024, 2024
Short summary
Short summary
The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limitations of currently available data records of cloud properties. In this work, we address this issue by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.
Karina McCusker, Anthony J. Baran, Chris Westbrook, Stuart Fox, Patrick Eriksson, Richard Cotton, Julien Delanoë, and Florian Ewald
Atmos. Meas. Tech., 17, 3533–3552, https://doi.org/10.5194/amt-17-3533-2024, https://doi.org/10.5194/amt-17-3533-2024, 2024
Short summary
Short summary
Polarised radiative transfer simulations are performed using an atmospheric model based on in situ measurements. These are compared to large polarisation measurements to explore whether such measurements can provide information on cloud ice, e.g. particle shape and orientation. We find that using oriented particle models with shapes based on imagery generally allows for accurate simulations. However, results are sensitive to shape assumptions such as the choice of single crystals or aggregates.
Michael Kiefer, Dale F. Hurst, Gabriele P. Stiller, Stefan Lossow, Holger Vömel, John Anderson, Faiza Azam, Jean-Loup Bertaux, Laurent Blanot, Klaus Bramstedt, John P. Burrows, Robert Damadeo, Bianca Maria Dinelli, Patrick Eriksson, Maya García-Comas, John C. Gille, Mark Hervig, Yasuko Kasai, Farahnaz Khosrawi, Donal Murtagh, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Takafumi Sugita, Thomas von Clarmann, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 16, 4589–4642, https://doi.org/10.5194/amt-16-4589-2023, https://doi.org/10.5194/amt-16-4589-2023, 2023
Short summary
Short summary
We quantify biases and drifts (and their uncertainties) between the stratospheric water vapor measurement records of 15 satellite-based instruments (SATs, with 31 different retrievals) and balloon-borne frost point hygrometers (FPs) launched at 27 globally distributed stations. These comparisons of measurements during the period 2000–2016 are made using robust, consistent statistical methods. With some exceptions, the biases and drifts determined for most SAT–FP pairs are < 10 % and < 1 % yr−1.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech., 15, 7119–7136, https://doi.org/10.5194/amt-15-7119-2022, https://doi.org/10.5194/amt-15-7119-2022, 2022
Short summary
Short summary
Vertical profiles of latent heating are derived from GOES-16 to be used in convective initialization. They are compared with other latent heating products derived from NEXRAD and GPM satellites, and the results show that their values are very similar to the radar-derived products. Finally, using latent heating derived from GOES-16 for convective initialization shows improvements in precipitation forecasts, which are comparable to the results using latent heating derived from NEXRAD.
Simon 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
Short summary
Short summary
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.
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
Short summary
Short summary
Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
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
Short summary
Short summary
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.
William G. Read, Gabriele Stiller, Stefan Lossow, Michael Kiefer, Farahnaz Khosrawi, Dale Hurst, Holger Vömel, Karen Rosenlof, Bianca M. Dinelli, Piera Raspollini, Gerald E. Nedoluha, John C. Gille, Yasuko Kasai, Patrick Eriksson, Christopher E. Sioris, Kaley A. Walker, Katja Weigel, John P. Burrows, and Alexei Rozanov
Atmos. Meas. Tech., 15, 3377–3400, https://doi.org/10.5194/amt-15-3377-2022, https://doi.org/10.5194/amt-15-3377-2022, 2022
Short summary
Short summary
This paper attempts to provide an assessment of the accuracy of 21 satellite-based instruments that remotely measure atmospheric humidity in the upper troposphere of the Earth's atmosphere. The instruments made their measurements from 1984 to the present time; however, most of these instruments began operations after 2000, and only a few are still operational. The objective of this study is to quantify the accuracy of each satellite humidity data set.
Simon Pfreundschuh, Stuart Fox, Patrick Eriksson, David Duncan, Stefan A. Buehler, Manfred Brath, Richard Cotton, and Florian Ewald
Atmos. Meas. Tech., 15, 677–699, https://doi.org/10.5194/amt-15-677-2022, https://doi.org/10.5194/amt-15-677-2022, 2022
Short summary
Short summary
We test a novel method to remotely measure ice particles in clouds. This is important because such measurements are required to improve climate and weather models. The method combines a radar with newly developed sensors measuring microwave radiation at very short wavelengths. We use observations made from aircraft flying above the cloud and compare them to real measurements from inside the cloud. This works well given that one can model the ice particles in the cloud sufficiently well.
Alan J. Geer, Peter Bauer, Katrin Lonitz, Vasileios Barlakas, Patrick Eriksson, Jana Mendrok, Amy Doherty, James Hocking, and Philippe Chambon
Geosci. Model Dev., 14, 7497–7526, https://doi.org/10.5194/gmd-14-7497-2021, https://doi.org/10.5194/gmd-14-7497-2021, 2021
Short summary
Short summary
Satellite observations of radiation from the earth can have strong sensitivity to cloud and precipitation in the atmosphere, with applications in weather forecasting and the development of models. Computing the radiation received at the satellite sensor using radiative transfer theory requires a simulation of the optical properties of a volume containing a large number of cloud and precipitation particles. This article describes the physics used to generate these
bulkoptical properties.
Jie Gong, Dong L. Wu, and Patrick Eriksson
Earth Syst. Sci. Data, 13, 5369–5387, https://doi.org/10.5194/essd-13-5369-2021, https://doi.org/10.5194/essd-13-5369-2021, 2021
Short summary
Short summary
Launched from the International Space Station, the IceCube radiometer orbited the Earth for 15 months and collected the first spaceborne radiance measurements at 874–883 GHz. This channel is uniquely important to fill in the sensitivity gap between operational visible–infrared and microwave remote sensing for atmospheric cloud ice and snow. This paper delivers the IceCube Level 1 radiance data processing algorithm and provides a data quality evaluation and discussion on its scientific merit.
Francesco Grieco, Kristell Pérot, Donal Murtagh, Patrick Eriksson, Bengt Rydberg, Michael Kiefer, Maya Garcia-Comas, Alyn Lambert, and Kaley A. Walker
Atmos. Meas. Tech., 14, 5823–5857, https://doi.org/10.5194/amt-14-5823-2021, https://doi.org/10.5194/amt-14-5823-2021, 2021
Short summary
Short summary
We present improved Odin/SMR mesospheric H2O concentration and temperature data sets, reprocessed assuming a bigger sideband leakage of the instrument. The validation study shows how the improved SMR data sets agree better with other instruments' observations than the old SMR version did. Given their unique time extension and geographical coverage, and H2O being a good tracer of mesospheric circulation, the new data sets are valuable for the study of dynamical processes and multi-year trends.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-97, https://doi.org/10.5194/amt-2021-97, 2021
Preprint withdrawn
Short summary
Short summary
Latent heating released from phase changes of water is an important factor in driving convection, and thus used in short-term weather forecast models to initiate convection. Typically, radars have been used to retrieve latent heating to be used in the forecast model, but continuous radar data are only available over land. Therefore, this study uses geostationary satellite data to retrieve latent heating so that it can be used to initiate convection in regions where radar data are not available.
Vasileios Barlakas, Alan J. Geer, and Patrick Eriksson
Atmos. Meas. Tech., 14, 3427–3447, https://doi.org/10.5194/amt-14-3427-2021, https://doi.org/10.5194/amt-14-3427-2021, 2021
Short summary
Short summary
Oriented nonspherical ice particles induce polarization that is ignored when cloud-sensitive satellite observations are used in numerical weather prediction systems. We present a simple approach for approximating particle orientation, requiring minor adaption of software and no additional calculation burden. With this approach, the system realistically simulates the observed polarization patterns, increasing the physical consistency between instruments with different polarizations.
Inderpreet Kaur, Patrick Eriksson, Simon Pfreundschuh, and David Ian Duncan
Atmos. Meas. Tech., 14, 2957–2979, https://doi.org/10.5194/amt-14-2957-2021, https://doi.org/10.5194/amt-14-2957-2021, 2021
Short summary
Short summary
Currently, cloud contamination in microwave humidity channels is addressed using filtering schemes. We present an approach to correct the cloud-affected microwave humidity radiances using a Bayesian machine learning technique. The technique combines orthogonal information from microwave channels to obtain a probabilistic prediction of the clear-sky radiances. With this approach, we are able to predict bias-free clear-sky radiances with well-represented case-specific uncertainty estimates.
Yoonjin Lee, Christian D. Kummerow, and Imme Ebert-Uphoff
Atmos. Meas. Tech., 14, 2699–2716, https://doi.org/10.5194/amt-14-2699-2021, https://doi.org/10.5194/amt-14-2699-2021, 2021
Short summary
Short summary
Convective clouds are usually associated with intense rain that can cause severe damage, and thus it is important to accurately detect convective clouds. This study develops a machine learning model that can identify convective clouds from five temporal visible and infrared images as humans can point at convective regions by finding bright and bubbling areas. The results look promising when compared to radar-derived products, which are commonly used for detecting convection.
Robin Ekelund, Patrick Eriksson, and Michael Kahnert
Atmos. Meas. Tech., 13, 6933–6944, https://doi.org/10.5194/amt-13-6933-2020, https://doi.org/10.5194/amt-13-6933-2020, 2020
Short summary
Short summary
Raindrops become flattened due to aerodynamic drag as they increase in mass and fall speed. This study calculated the electromagnetic interaction between microwave radiation and non-spheroidal raindrops. The calculations are made publicly available to the scientific community, in order to promote accurate representations of raindrops in measurements. Tests show that the drop shape can have a noticeable effect on microwave observations of heavy rainfall.
Francesco Grieco, Kristell Pérot, Donal Murtagh, Patrick Eriksson, Peter Forkman, Bengt Rydberg, Bernd Funke, Kaley A. Walker, and Hugh C. Pumphrey
Atmos. Meas. Tech., 13, 5013–5031, https://doi.org/10.5194/amt-13-5013-2020, https://doi.org/10.5194/amt-13-5013-2020, 2020
Short summary
Short summary
We present a unique – by time extension and geographical coverage – dataset of satellite observations of carbon monoxide (CO) in the mesosphere which will allow us to study dynamical processes, since CO is a very good tracer of circulation in the mesosphere. Previously, the dataset was unusable due to instrumental artefacts that affected the measurements. We identify the cause of the artefacts, eliminate them and prove the quality of the results by comparing with other instrument measurements.
Thomas von Clarmann, Douglas A. Degenstein, Nathaniel J. Livesey, Stefan Bender, Amy Braverman, André Butz, Steven Compernolle, Robert Damadeo, Seth Dueck, Patrick Eriksson, Bernd Funke, Margaret C. Johnson, Yasuko Kasai, Arno Keppens, Anne Kleinert, Natalya A. Kramarova, Alexandra Laeng, Bavo Langerock, Vivienne H. Payne, Alexei Rozanov, Tomohiro O. Sato, Matthias Schneider, Patrick Sheese, Viktoria Sofieva, Gabriele P. Stiller, Christian von Savigny, and Daniel Zawada
Atmos. Meas. Tech., 13, 4393–4436, https://doi.org/10.5194/amt-13-4393-2020, https://doi.org/10.5194/amt-13-4393-2020, 2020
Short summary
Short summary
Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. This paper summarizes related techniques and provides recommendations for unified error reporting.
Simon Pfreundschuh, Patrick Eriksson, Stefan A. Buehler, Manfred Brath, David Duncan, Richard Larsson, and Robin Ekelund
Atmos. Meas. Tech., 13, 4219–4245, https://doi.org/10.5194/amt-13-4219-2020, https://doi.org/10.5194/amt-13-4219-2020, 2020
Short summary
Short summary
The next generation of European operational weather satellites will carry a novel microwave sensor, the Ice Cloud Imager (ICI), which will provide observations of clouds at microwave frequencies that were not available before. We investigate the potential benefits of combining observations from ICI with that of a radar. We find that such combined observations provide additional information on the properties of the cloud and help to reduce uncertainties in retrieved mass and number densities.
Manfred Brath, Robin Ekelund, Patrick Eriksson, Oliver Lemke, and Stefan A. Buehler
Atmos. Meas. Tech., 13, 2309–2333, https://doi.org/10.5194/amt-13-2309-2020, https://doi.org/10.5194/amt-13-2309-2020, 2020
Short summary
Short summary
Microwave dual-polarization observations consistently show that larger atmospheric ice particles tend to have a preferred orientation. We provide a publicly available database of microwave and submillimeter wave scattering properties of oriented ice particles based on discrete dipole approximation scattering calculations. Detailed radiative transfer simulations, recreating observed polarization patterns, are additionally presented in this study.
Jonas Hagen, Klemens Hocke, Gunter Stober, Simon Pfreundschuh, Axel Murk, and Niklaus Kämpfer
Atmos. Chem. Phys., 20, 2367–2386, https://doi.org/10.5194/acp-20-2367-2020, https://doi.org/10.5194/acp-20-2367-2020, 2020
Short summary
Short summary
The middle atmosphere (30 to 70 km altitude) is stratified and, despite very strong horizontal winds, there is less mixing between the horizontal layers. An important driver for the energy exchange between the layers in this regime is atmospheric tides, which are waves that are driven by the diurnal cycle of solar heating. We measure these tides in the wind field for the first time using a ground-based passive instrument. Ultimately, such measurements could be used to improve atmospheric models.
Robin Ekelund, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 13, 501–520, https://doi.org/10.5194/amt-13-501-2020, https://doi.org/10.5194/amt-13-501-2020, 2020
Short summary
Short summary
Atmospheric ice particles (e.g. snow and ice crystals) are an important part of weather, climate, and the hydrological cycle. This study investigates whether combined satellite measurements by radar and radiometers at microwave wavelengths can be used to find the most likely shape of such ice particles. The method was limited when using only currently operating sensors (CloudSat radar and the GPM Microwave Imager) but shows promise if the upcoming Ice Cloud Imager is also considered.
Patrick Eriksson, Bengt Rydberg, Vinia Mattioli, Anke Thoss, Christophe Accadia, Ulf Klein, and Stefan A. Buehler
Atmos. Meas. Tech., 13, 53–71, https://doi.org/10.5194/amt-13-53-2020, https://doi.org/10.5194/amt-13-53-2020, 2020
Short summary
Short summary
The Ice Cloud Imager (ICI) will be the first operational satellite sensor operating at sub-millimetre wavelengths and this novel mission will thus provide important new data to weather forecasting and climate studies. The series of ICI instruments will together cover about 20 years. This article presents the basic technical characteristics of the sensor and outlines the day-one operational retrievals. An updated estimation of the expected retrieval performance is also presented.
David Ian Duncan, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 12, 6341–6359, https://doi.org/10.5194/amt-12-6341-2019, https://doi.org/10.5194/amt-12-6341-2019, 2019
Short summary
Short summary
The overlapping beams of some satellite observations contain spatial information that is discarded by most data processing techniques. This study applies an established technique in a new way to improve the spatial resolution of retrieval targets, effectively using the overlapping information to achieve a higher ultimate resolution. It is argued that this is a more optimal use of the total information available from current microwave sensors, using AMSR2 as an example.
David Ian Duncan, Patrick Eriksson, Simon Pfreundschuh, Christian Klepp, and Daniel C. Jones
Atmos. Chem. Phys., 19, 6969–6984, https://doi.org/10.5194/acp-19-6969-2019, https://doi.org/10.5194/acp-19-6969-2019, 2019
Short summary
Short summary
Raindrop size distributions have not been systematically studied over the oceans but are significant for remotely sensing, assimilating, and modeling rain. Here we investigate raindrop populations with new global in situ data, compare them against satellite estimates, and explore a new technique to classify the shapes of these distributions. The results indicate the inadequacy of a commonly assumed shape in some regions and the sizable impact of shape variability on satellite measurements.
Stefan Lossow, Farahnaz Khosrawi, Michael Kiefer, Kaley A. Walker, Jean-Loup Bertaux, Laurent Blanot, James M. Russell, Ellis E. Remsberg, John C. Gille, Takafumi Sugita, Christopher E. Sioris, Bianca M. Dinelli, Enzo Papandrea, Piera Raspollini, Maya García-Comas, Gabriele P. Stiller, Thomas von Clarmann, Anu Dudhia, William G. Read, Gerald E. Nedoluha, Robert P. Damadeo, Joseph M. Zawodny, Katja Weigel, Alexei Rozanov, Faiza Azam, Klaus Bramstedt, Stefan Noël, John P. Burrows, Hideo Sagawa, Yasuko Kasai, Joachim Urban, Patrick Eriksson, Donal P. Murtagh, Mark E. Hervig, Charlotta Högberg, Dale F. Hurst, and Karen H. Rosenlof
Atmos. Meas. Tech., 12, 2693–2732, https://doi.org/10.5194/amt-12-2693-2019, https://doi.org/10.5194/amt-12-2693-2019, 2019
Stuart Fox, Jana Mendrok, Patrick Eriksson, Robin Ekelund, Sebastian J. O'Shea, Keith N. Bower, Anthony J. Baran, R. Chawn Harlow, and Juliet C. Pickering
Atmos. Meas. Tech., 12, 1599–1617, https://doi.org/10.5194/amt-12-1599-2019, https://doi.org/10.5194/amt-12-1599-2019, 2019
Short summary
Short summary
Airborne observations of ice clouds are used to validate radiative transfer simulations using a state-of-the-art database of cloud ice optical properties. Simulations at these wavelengths are required to make use of future satellite instruments such as the Ice Cloud Imager. We show that they can generally reproduce observed cloud signals, but for a given total ice mass there is considerable sensitivity to the cloud microphysics, including the particle shape and distribution of ice mass.
Charlotta Högberg, Stefan Lossow, Farahnaz Khosrawi, Ralf Bauer, Kaley A. Walker, Patrick Eriksson, Donal P. Murtagh, Gabriele P. Stiller, Jörg Steinwagner, and Qiong Zhang
Atmos. Chem. Phys., 19, 2497–2526, https://doi.org/10.5194/acp-19-2497-2019, https://doi.org/10.5194/acp-19-2497-2019, 2019
Short summary
Short summary
Five δD (H2O) data sets obtained from satellite observations have been evaluated using profile-to-profile and climatological comparisons. The focus is on stratospheric altitudes, but results from the upper troposphere to the lower mesosphere are also provided. There are clear quantitative differences in the δD ratio in key areas of scientific interest, resulting in difficulties drawing robust conclusions on atmospheric processes affecting the water vapour budget and distribution.
Joonas Kiviranta, Kristell Pérot, Patrick Eriksson, and Donal Murtagh
Atmos. Chem. Phys., 18, 13393–13410, https://doi.org/10.5194/acp-18-13393-2018, https://doi.org/10.5194/acp-18-13393-2018, 2018
Short summary
Short summary
This paper investigates how the activity of the Sun affects the amount of nitric oxide (NO) in the upper atmosphere. If NO descends lower down in the atmosphere, it can destroy ozone. We analyze satellite measurements of NO to create a model that can simulate the amount of NO at any given time. This model can indeed simulate NO with reasonable accuracy and it can potentially be used as an input for a larger model of the atmosphere that attempts to explain how the Sun affects our atmosphere.
David Ian Duncan and Patrick Eriksson
Atmos. Chem. Phys., 18, 11205–11219, https://doi.org/10.5194/acp-18-11205-2018, https://doi.org/10.5194/acp-18-11205-2018, 2018
Short summary
Short summary
Ice cloud mass is assessed on a global scale using the latest satellite and reanalysis datasets. While ice cloud variability driven by large-scale circulations is an area of relative consensus, models and observations disagree strongly on the overall magnitude and finer-scale variability of atmospheric ice mass. The results reflect limitations of the current Earth observing system and indicate ice microphysical assumptions as the likely culprit of disagreement.
Simon Pfreundschuh, Patrick Eriksson, David Duncan, Bengt Rydberg, Nina Håkansson, and Anke Thoss
Atmos. Meas. Tech., 11, 4627–4643, https://doi.org/10.5194/amt-11-4627-2018, https://doi.org/10.5194/amt-11-4627-2018, 2018
Short summary
Short summary
A novel neural-network-based retrieval method is proposed that combines the flexibility and computational efficiency of machine learning retrievals with the consistent treatment of uncertainties of Bayesian methods. Numerical experiments are presented that show the consistency of the proposed method with the Bayesian formulation as well as its ability to represent non-Gaussian retrieval errors. With this, the proposed method overcomes important limitations of traditional methods.
Philippe Baron, Donal Murtagh, Patrick Eriksson, Jana Mendrok, Satoshi Ochiai, Kristell Pérot, Hideo Sagawa, and Makoto Suzuki
Atmos. Meas. Tech., 11, 4545–4566, https://doi.org/10.5194/amt-11-4545-2018, https://doi.org/10.5194/amt-11-4545-2018, 2018
Short summary
Short summary
This paper investigates with computer simulations the measurement performances of the satellite Stratospheric Inferred Winds (SIW) in the altitude range 10–90 km. SIW is a Swedish mission that will be launched close to 2022. It is intended to fill the current altitude gap between 30 and 70 km in wind measurements and to pursue the monitoring of temperature and key stratospheric constituents for better understanding climate change effects.
Farahnaz Khosrawi, Stefan Lossow, Gabriele P. Stiller, Karen H. Rosenlof, Joachim Urban, John P. Burrows, Robert P. Damadeo, Patrick Eriksson, Maya García-Comas, John C. Gille, Yasuko Kasai, Michael Kiefer, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Alexei Rozanov, Christopher E. Sioris, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 11, 4435–4463, https://doi.org/10.5194/amt-11-4435-2018, https://doi.org/10.5194/amt-11-4435-2018, 2018
Short summary
Short summary
Time series of stratospheric and lower mesospheric water vapour using 33 data sets from 15 satellite instruments were compared in the framework of the second SPARC water vapour assessment. We find that most data sets can be considered in observational and modelling studies addressing, e.g. stratospheric and lower mesospheric water vapour variability and trends if data-set-specific characteristics (e.g. a drift) and restrictions (e.g. temporal and spatial coverage) are taken into account.
Patrick Eriksson, Robin Ekelund, Jana Mendrok, Manfred Brath, Oliver Lemke, and Stefan A. Buehler
Earth Syst. Sci. Data, 10, 1301–1326, https://doi.org/10.5194/essd-10-1301-2018, https://doi.org/10.5194/essd-10-1301-2018, 2018
Short summary
Short summary
A main application of microwave remote sensing is to observe atmospheric particles consisting of ice. This application requires data on how particles with different shapes and sizes affect the observations. A database of such properties has been developed. The database is the most comprehensive of its type. Main strengths are a good representation of particles of aggregate type and broad frequency coverage.
Verena Grützun, Stefan A. Buehler, Lukas Kluft, Jana Mendrok, Manfred Brath, and Patrick Eriksson
Atmos. Meas. Tech., 11, 4217–4237, https://doi.org/10.5194/amt-11-4217-2018, https://doi.org/10.5194/amt-11-4217-2018, 2018
Short summary
Short summary
The global observation of ice clouds is crucial because they are important factors in the climate system but still are amongst the greatest uncertainties for estimating the Earth's energy budget in a changing climate. However, reliable global long-term measurements are scarce. Using atmospheric model data from the ICON model in combination with the radiative transfer simulator ARTS we explore the potential of passive millimeter and sub-millimeter wavelength measurements to fill that gap.
Stefan A. Buehler, Jana Mendrok, Patrick Eriksson, Agnès Perrin, Richard Larsson, and Oliver Lemke
Geosci. Model Dev., 11, 1537–1556, https://doi.org/10.5194/gmd-11-1537-2018, https://doi.org/10.5194/gmd-11-1537-2018, 2018
Short summary
Short summary
The Atmospheric Radiative Transfer Simulator (ARTS) is a public domain
software for simulating how radiation in the microwave to infrared
spectral range travels through an atmosphere. The program can simulate
satellite observations, in cloudy and clear atmospheres, and can also
be used to calculate radiative energy fluxes. The main feature of this
release is a planetary toolbox that allows simulations for the
planets Venus, Mars, and Jupiter, in addition to Earth.
Manfred Brath, Stuart Fox, Patrick Eriksson, R. Chawn Harlow, Martin Burgdorf, and Stefan A. Buehler
Atmos. Meas. Tech., 11, 611–632, https://doi.org/10.5194/amt-11-611-2018, https://doi.org/10.5194/amt-11-611-2018, 2018
Short summary
Short summary
A method to estimate the amounts of ice, liquid water, and water vapor from aircraft radiation measurements at wavelengths just over and under 1 mm is presented and its performance is estimated. The method uses an ensemble of artificial neural networks. It strongly benefits from the submillimeter frequencies reducing the error for the estimated amount of ice by a factor of 2 compared to a traditional microwave method. The method was applied to measurement of a precipitating frontal system.
Stefan Lossow, Farahnaz Khosrawi, Gerald E. Nedoluha, Faiza Azam, Klaus Bramstedt, John. P. Burrows, Bianca M. Dinelli, Patrick Eriksson, Patrick J. Espy, Maya García-Comas, John C. Gille, Michael Kiefer, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Gabriele P. Stiller, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 10, 1111–1137, https://doi.org/10.5194/amt-10-1111-2017, https://doi.org/10.5194/amt-10-1111-2017, 2017
Richard Larsson, Mathias Milz, Patrick Eriksson, Jana Mendrok, Yasuko Kasai, Stefan Alexander Buehler, Catherine Diéval, David Brain, and Paul Hartogh
Geosci. Instrum. Method. Data Syst., 6, 27–37, https://doi.org/10.5194/gi-6-27-2017, https://doi.org/10.5194/gi-6-27-2017, 2017
Short summary
Short summary
By computer simulations, we explore and quantify how to use radiation emitted by molecular oxygen in the Martian atmosphere to measure the magnetic field from the crust of the planet. This crustal magnetic field is important to understand the past evolution of Mars. Our method can measure the magnetic field at lower altitudes than has so far been done, which could give important information on the characteristics of the crustal sources if a mission with the required instrument is launched.
Ole Martin Christensen, Susanne Benze, Patrick Eriksson, Jörg Gumbel, Linda Megner, and Donal P. Murtagh
Atmos. Chem. Phys., 16, 12587–12600, https://doi.org/10.5194/acp-16-12587-2016, https://doi.org/10.5194/acp-16-12587-2016, 2016
Short summary
Short summary
This study investigates the properties of ice clouds forming in the upper summer mesosphere known as polar mesospheric clouds, and their relationship with the background atmosphere combining two different satellite instruments. We find that temperature variations in the atmosphere of the order of some hours reduce the amount of ice in these clouds and see indications of strong vertical transport in these clouds.
Isaac Moradi, Philip Arkin, Ralph Ferraro, Patrick Eriksson, and Eric Fetzer
Atmos. Chem. Phys., 16, 6913–6929, https://doi.org/10.5194/acp-16-6913-2016, https://doi.org/10.5194/acp-16-6913-2016, 2016
Short summary
Short summary
Measurements from the SAPHIR onboard Megha-Tropiques are used to evaluate the diurnal cycle of tropospheric humidity in the tropical region. The results show a large inhomogeneity in the amplitude and peak time of tropospheric humidity. The diurnal amplitude tends to be larger over convective regions than over subsidence regions. An early morning peak time is observed over most regions but there are substantial regions where the diurnal peak occurs at the other times of day.
Richard Larsson, Mathias Milz, Peter Rayer, Roger Saunders, William Bell, Anna Booton, Stefan A. Buehler, Patrick Eriksson, and Viju O. John
Atmos. Meas. Tech., 9, 841–857, https://doi.org/10.5194/amt-9-841-2016, https://doi.org/10.5194/amt-9-841-2016, 2016
Short summary
Short summary
By modeling the Special Sensor Microwave Imager/Sounder's mesospheric measurements, inversions methods can be applied to retreive mesospheric temperatures. We compare the fast forward model used by Met Office with reference simulations and find that there is a reasonable agreement between both models and measurements. Thus we recommend that the fast model is used in data assimilation to improve mesospheric temperature retrievals.
P. Forkman, O. M. Christensen, P. Eriksson, B. Billade, V. Vassilev, and V. M. Shulga
Geosci. Instrum. Method. Data Syst., 5, 27–44, https://doi.org/10.5194/gi-5-27-2016, https://doi.org/10.5194/gi-5-27-2016, 2016
Short summary
Short summary
Microwave radiometry is the only ground-based technique that can provide vertical profiles of gases in the middle atmosphere both day and night, and even during cloudy conditions. Today these measurements are performed at relatively few sites, more simple and reliable instruments are required to make the measurement technique more widely spread. In this study a compact double-sideband frequency-switched radiometer system for simultaneous observations of mesospheric CO and O3 is presented.
O. M. Christensen, P. Eriksson, J. Urban, D. Murtagh, K. Hultgren, and J. Gumbel
Atmos. Meas. Tech., 8, 1981–1999, https://doi.org/10.5194/amt-8-1981-2015, https://doi.org/10.5194/amt-8-1981-2015, 2015
Short summary
Short summary
Polar mesospheric clouds are clouds that form in the summer polar mesopause, 80km above the surface. In this study we present new measurements by the Odin satellite, which are able to determine water vapour, temperature and cloud coverage with a high resolution and a large geographical coverage. Using these data we can see structures in the clouds and background atmosphere that have not been detectable by previous measurements.
P. Eriksson, M. Jamali, J. Mendrok, and S. A. Buehler
Atmos. Meas. Tech., 8, 1913–1933, https://doi.org/10.5194/amt-8-1913-2015, https://doi.org/10.5194/amt-8-1913-2015, 2015
Short summary
Short summary
The optical properties of randomly oriented ice hydrometeors are reviewed from a perspective of microwave mass retrievals. The soft particle approximation is found to be highly problematic, and the alternative approach presented by Geer and Baordo (2014) should instead be used. We present a simplified version of this approach, and point out several critical limitations of existing DDA data.
F. Navas-Guzmán, N. Kämpfer, A. Murk, R. Larsson, S. A. Buehler, and P. Eriksson
Atmos. Meas. Tech., 8, 1863–1874, https://doi.org/10.5194/amt-8-1863-2015, https://doi.org/10.5194/amt-8-1863-2015, 2015
Short summary
Short summary
In this work we study the Zeeman effect on stratospheric O2 using ground-based microwave radiometer measurements. The interaction of the Earth magnetic field with the oxygen dipole leads to a splitting of O2 energy states which polarizes the emission spectra. A special campaign was carried out in order to measure for the first time the polarization state of the radiation due to the Zeeman effect in the main isotopologue of oxygen from ground-based microwave measurements.
V. S. Galligani, C. Prigent, E. Defer, C. Jimenez, P. Eriksson, J.-P. Pinty, and J.-P. Chaboureau
Atmos. Meas. Tech., 8, 1605–1616, https://doi.org/10.5194/amt-8-1605-2015, https://doi.org/10.5194/amt-8-1605-2015, 2015
R. Rüfenacht, A. Murk, N. Kämpfer, P. Eriksson, and S. A. Buehler
Atmos. Meas. Tech., 7, 4491–4505, https://doi.org/10.5194/amt-7-4491-2014, https://doi.org/10.5194/amt-7-4491-2014, 2014
Short summary
Short summary
Only very few techniques for wind measurements in the upper stratosphere and lower mesosphere exist. Moreover, none of these instruments is running on a continuous basis. This paper describes the development of ground-based microwave Doppler radiometry. Time series of daily wind profile measurements from four different locations at polar, mid- and tropical latitudes are presented. The agreement with ECMWF model data is good in the stratosphere, but discrepancies were found in the mesosphere.
P. Eriksson, B. Rydberg, H. Sagawa, M. S. Johnston, and Y. Kasai
Atmos. Chem. Phys., 14, 12613–12629, https://doi.org/10.5194/acp-14-12613-2014, https://doi.org/10.5194/acp-14-12613-2014, 2014
Short summary
Short summary
The sub-millimetre wavelength region has been identified as very useful for measurements of cloud ice mass. The only satellite sensors operating in this wavelength region are so far limb sounders, and results from two such instruments are presented and sample applications are demonstrated. The results have high intrinsic value, but serve also as a practical preparation for planned dedicated sub-millimetre cloud missions.
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, A. Gettelman, P. Räisänen, and M. D. Zelinka
Atmos. Chem. Phys., 14, 8701–8721, https://doi.org/10.5194/acp-14-8701-2014, https://doi.org/10.5194/acp-14-8701-2014, 2014
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, K. Wyser, and M. D. Zelinka
Atmos. Chem. Phys., 13, 12043–12058, https://doi.org/10.5194/acp-13-12043-2013, https://doi.org/10.5194/acp-13-12043-2013, 2013
O. Stähli, A. Murk, N. Kämpfer, C. Mätzler, and P. Eriksson
Atmos. Meas. Tech., 6, 2477–2494, https://doi.org/10.5194/amt-6-2477-2013, https://doi.org/10.5194/amt-6-2477-2013, 2013
O. M. Christensen and P. Eriksson
Atmos. Meas. Tech., 6, 1597–1609, https://doi.org/10.5194/amt-6-1597-2013, https://doi.org/10.5194/amt-6-1597-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Solar background radiation temperature calibration of a pure rotational Raman lidar
Exploring commercial Global Navigation Satellite System (GNSS) radio occultation (RO) products for planetary boundary layer studies in the Arctic
Research on atmospheric temperature fine measurements from the near surface to 60 km altitude based on an integrated lidar system
Testing ground-based observations of wave activity in the (lower and upper) atmosphere as possible (complementary) indicators of streamer events
Quality assessment of YUNYAO radio occultation data in the neutral atmosphere
Turbulence kinetic energy dissipation rate estimated from a WindCube Doppler lidar and the LQ7 1.3 GHz radar wind profiler in the convective boundary layer
Comparison of temperature and wind profiles between ground-based remote sensing observations and numerical weather prediction model in complex Alpine topography: the Meiringen campaign
Cluster analysis of vertical polarimetric radio occultation profiles and corresponding liquid and ice water paths from Global Precipitation Measurement (GPM) microwave data
Enhanced quantitative precipitation estimation through the opportunistic use of Ku TV-SAT links via a dual-channel procedure
The added value and potential of long-term radio occultation data for climatological wind field monitoring
Exploring dual-lidar mean and turbulence measurements over Perdigão's complex terrain
Description and validation of the Japanese algorithm for radiative flux and heating rate products with all four EarthCARE instruments: pre-launch test with A-Train
Atmospheric stability from microwave radiometer observations for on/offshore wind energy applications
Improving the estimate of higher-order moments from lidar observations near the top of the convective boundary layer
Closing the gap in the tropics: the added value of radio-occultation data for wind field monitoring across the Equator
Verification of weather-radar-based hail metrics with crowdsourced observations from Switzerland
Observing atmospheric rivers using GNSS radio occultation data
Assessment of Operational Non-Time Critical Sentinel-6A Michael Freilich Radio Occultation Data: Insights into Tropospheric GNSS Signal Cutoff Strategies and Processor Improvements
Atmospheric motion vector (AMV) error characterization and bias correction by leveraging independent lidar data: a simulation using an observing system simulation experiment (OSSE) and optical flow AMVs
Rotary-wing drone-induced flow – comparison of simulations with lidar measurements
Application of Doppler sodar in short-term forecasting of PM10 concentration in the air in Krakow (Poland)
Radiative closure tests of collocated hyperspectral microwave and infrared radiometers
Effects of clouds and aerosols on downwelling surface solar irradiance nowcasting and short-term forecasting
Verification of parameterizations for clear sky downwelling longwave irradiance in the Arctic
Global evaluation of fast radiative transfer model coefficients for early meteorological satellite sensors
Assessing sampling and retrieval errors of GPROF precipitation estimates over the Netherlands
Comparisons and quality control of wind observations in a mountainous city using wind profile radar and the Aeolus satellite
On the use of routine airborne observations for evaluation and monitoring of satellite observations of thermodynamic profiles
Daily satellite-based sunshine duration estimates over Brazil: validation and intercomparison
Statistical assessment of a Doppler radar model of TKE dissipation rate for low Richardson numbers
Extended validation of Aeolus winds with wind-profiling radars in Antarctica and Arctic Sweden
The impact of Aeolus winds on near-surface wind forecasts over tropical ocean and high-latitude regions
Long-term validation of Aeolus L2B wind products at Punta Arenas, Chile, and Leipzig, Germany
Turbulence kinetic energy dissipation rate: assessment of radar models from comparisons between 1.3 GHz wind profiler radar (WPR) and DataHawk UAV measurements
The impacts of assimilating Aeolus horizontal line-of-sight winds on numerical predictions of Hurricane Ida (2021) and a mesoscale convective system over the Atlantic Ocean
Evaluation of tropospheric water vapour and temperature profiles retrieved from MetOp-A by the Infrared and Microwave Sounding scheme
Validation of the Aeolus L2B wind product with airborne wind lidar measurements in the polar North Atlantic region and in the tropics
An improved vertical correction method for the inter-comparison and inter-validation of integrated water vapour measurements
An assessment of reprocessed GPS/MET observations spanning 1995–1997
Turbulence parameters measured by the Beijing mesosphere–stratosphere–troposphere radar in the troposphere and lower stratosphere with three models: comparison and analyses
Comparison of planetary boundary layer height from ceilometer with ARM radiosonde data
Behavior and mechanisms of Doppler wind lidar error in varying stability regimes
Inter-comparison of atmospheric boundary layer (ABL) height estimates from different profiling sensors and models in the framework of HyMeX-SOP1
Evaluation of Aeolus L2B wind product with wind profiling radar measurements and numerical weather prediction model equivalents over Australia
Comparison of global UV spectral irradiance measurements between a BTS CCD-array and a Brewer spectroradiometer
Scan strategies for wind profiling with Doppler lidar – an large-eddy simulation (LES)-based evaluation
Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty
Modelling the spectral shape of continuous-wave lidar measurements in a turbulent wind tunnel
Three-way calibration checks using ground-based, ship-based, and spaceborne radars
Rainfall retrieval algorithm for commercial microwave links: stochastic calibration
Vasura Jayaweera, Robert J. Sica, Giovanni Martucci, and Alexander Haefele
Atmos. Meas. Tech., 18, 1461–1469, https://doi.org/10.5194/amt-18-1461-2025, https://doi.org/10.5194/amt-18-1461-2025, 2025
Short summary
Short summary
Our study presents a new method, the solar background calibration method, which improves temperature determinations in rotational Raman lidar systems. By utilizing background solar radiation, this technique offers more continuous and reliable temperatures independent of external measuring instruments. This new method enhances our ability to monitor and understand atmospheric trends and their association with climate change with greater accuracy.
Manisha Ganeshan, Dong L. Wu, Joseph A. Santanello, Jie Gong, Chi Ao, Panagiotis Vergados, and Kevin J. Nelson
Atmos. Meas. Tech., 18, 1389–1403, https://doi.org/10.5194/amt-18-1389-2025, https://doi.org/10.5194/amt-18-1389-2025, 2025
Short summary
Short summary
This study explores the potential of two newly launched commercial Global Navigation Satellite System (GNSS) radio occultation (RO) satellite missions for advancing Arctic lower-atmospheric studies. The products have a good sampling of the lower Arctic atmosphere and are useful to derive the planetary boundary layer (PBL) height during winter months. This research is a step towards closing the observation gap in polar regions due to the decomissioning of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-1) GNSS RO mission and the lack of high-latitude coverage by its successor (COSMIC-2).
Zhangjun Wang, Tiantian Guo, Xianxin Li, Chao Chen, Dong Liu, Luoyuan Qu, Hui Li, and Xiufen Wang
Atmos. Meas. Tech., 18, 1405–1414, https://doi.org/10.5194/amt-18-1405-2025, https://doi.org/10.5194/amt-18-1405-2025, 2025
Short summary
Short summary
A dual-field, integrated lidar system has been developed to detect atmospheric temperatures from the near surface to 60 km over Qingdao, China. Temperature profiles from the near surface to 60 km are derived by pure rotational Raman and Rayleigh scattering techniques using a single integrated lidar system. The results prove the system can make fine measurements of the atmospheric temperature profiles from the near surface to 60 km.
Michal Kozubek, Lisa Kuchelbacher, Jaroslav Chum, Tereza Sindelarova, Franziska Trinkl, and Katerina Podolska
Atmos. Meas. Tech., 18, 1373–1388, https://doi.org/10.5194/amt-18-1373-2025, https://doi.org/10.5194/amt-18-1373-2025, 2025
Short summary
Short summary
Waves are important as main drivers of different stratispheric patterns (streamers). We analyse changes in waves and infrasound characteristics related to streamers using continuous Doppler soundings and arrays of microbarometers in Czechia. Ground measurements using infrasound arrays showed that gravity wave propagation azimuths were more random during streamers than during calm conditions. Measurements in the ionosphere during streamers did not differ from those expected for the given time.
Xiaoze Xu, Wei Han, Jincheng Wang, Zhiqiu Gao, Fenghui Li, Yan Cheng, and Naifeng Fu
Atmos. Meas. Tech., 18, 1339–1353, https://doi.org/10.5194/amt-18-1339-2025, https://doi.org/10.5194/amt-18-1339-2025, 2025
Short summary
Short summary
Commercial Global Navigation Satellite System (GNSS) radio occultation (RO) satellites are generally cheap and can generate a large volume of globally distributed observations in a short period of time. To evaluate the practical application value of these data, we must assess their quality. We evaluate the quality of YUNYAO RO data. By using the “three-cornered hat” method and comparing with data from Metop-C and COSMIC-2, it was found that the YUNYAO GNSS-RO data are of high quality.
Hubert Luce and Masanori Yabuki
Atmos. Meas. Tech., 18, 1193–1208, https://doi.org/10.5194/amt-18-1193-2025, https://doi.org/10.5194/amt-18-1193-2025, 2025
Short summary
Short summary
Over a 3-week period, simultaneous measurements were conducted using a Doppler lidar and a 1.3 GHz radar wind profiler in Japan. Although the instruments had no range overlap, turbulence kinetic energy dissipation rates were estimated through various methods in convective boundary layers. Hourly averaged estimates showed good agreement, within a factor of approximately 2, suggesting that both instruments and methods provide consistent dissipation rate values.
Alexandre Bugnard, Martine Collaud Coen, Maxime Hervo, Daniel Leuenberger, Marco Arpagaus, and Samuel Monhart
Atmos. Meas. Tech., 18, 1039–1061, https://doi.org/10.5194/amt-18-1039-2025, https://doi.org/10.5194/amt-18-1039-2025, 2025
Short summary
Short summary
Temperature (T) and wind profiles were measured by a Doppler wind lidar and a microwave radiometer in Meiringen in a medium-sized Alpine valley. Ground-based T inversions and thermal winds were studied during the 10 months of the campaign. The comparison between the observations and the COSMO-1E model provides good model performance for monthly climatologies. T inversions are however frequently missed, and important differences for particular cases are found, especially for foehn events.
Jonas E. Katona, Manuel de la Torre Juárez, Terence L. Kubar, F. Joseph Turk, Kuo-Nung Wang, and Ramon Padullés
Atmos. Meas. Tech., 18, 953–970, https://doi.org/10.5194/amt-18-953-2025, https://doi.org/10.5194/amt-18-953-2025, 2025
Short summary
Short summary
Polarimetric radio occultations (PROs) use polarized radio signals from satellites to detect moisture and precipitation in Earth's atmosphere. By applying nonlinear regression and k-means cluster analysis to over 2 years of PRO and non-PRO data, this study shows how deviations from a refractivity model relate to vertical profiles of water vapor pressure (moisture) and that differences between components of PRO signals correlate directly with vertical profiles of water path (precipitation).
Louise Gelbart, Laurent Barthès, François Mercier-Tigrine, Aymeric Chazottes, and Cécile Mallet
Atmos. Meas. Tech., 18, 351–370, https://doi.org/10.5194/amt-18-351-2025, https://doi.org/10.5194/amt-18-351-2025, 2025
Short summary
Short summary
In this paper, we present and evaluate a new method for the quantitative estimation of precipitation from a low-cost sensor. Based on previous work measuring the attenuation of an electromagnetic signal from a broadcast television satellite, we make this approach more accurate so it can be easily deployed and used operationally in areas where rainfall measurements are critical for applications like flood monitoring. In this article, the method is validated in France and applied in Côte d'Ivoire.
Irena Nimac, Julia Danzer, and Gottfried Kirchengast
Atmos. Meas. Tech., 18, 265–286, https://doi.org/10.5194/amt-18-265-2025, https://doi.org/10.5194/amt-18-265-2025, 2025
Short summary
Short summary
Due to the shortcomings of available observations, having accurate global 3D wind fields remains a challenge. A promising option is radio occultation (RO) satellite data, which enable the derivation of winds based on wind approximations. We test how well RO winds describe the ERA5 winds. We separate the total wind difference into the approximation bias and the systematic difference between the two datasets. The results show the utility of RO winds for climate monitoring and analyses.
Isadora L. Coimbra, Jakob Mann, José M. L. M. Palma, and Vasco T. P. Batista
Atmos. Meas. Tech., 18, 287–303, https://doi.org/10.5194/amt-18-287-2025, https://doi.org/10.5194/amt-18-287-2025, 2025
Short summary
Short summary
Dual-lidar measurements are explored here as a cost-effective alternative for measuring the wind at great heights. From measurements at a mountainous site, we showed that this methodology can accurately capture mean wind speeds and turbulence under different flow conditions, and we recommended optimal lidar placement and sampling rates. This methodology allows the construction of vertical wind profiles up to 430 m, surpassing traditional meteorological mast heights and single-lidar capabilities.
Akira Yamauchi, Kentaroh Suzuki, Eiji Oikawa, Miho Sekiguchi, Takashi M. Nagao, and Haruma Ishida
Atmos. Meas. Tech., 17, 6751–6767, https://doi.org/10.5194/amt-17-6751-2024, https://doi.org/10.5194/amt-17-6751-2024, 2024
Short summary
Short summary
A Japanese team developed the Level 2 atmospheric radiation flux and heating rate product for EarthCARE, which offers vertical profiles of longwave and shortwave radiative fluxes and heating rates. This study outlines the algorithm for the radiative product and its comparative validation against satellite and ground-based observations. It also analyzes errors in radiative fluxes at various scales and their dependence on cloud type, with ice-containing clouds identified as a primary error source.
Domenico Cimini, Rémi Gandoin, Stephanie Fiedler, Claudia Acquistapace, Andrea Balotti, Sabrina Gentile, Edoardo Geraldi, Christine Knist, Pauline Martinet, Saverio T. Nilo, Giandomenico Pace, Bernhard Pospichal, and Filomena Romano
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-186, https://doi.org/10.5194/amt-2024-186, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Atmospheric stability indicates whether air vertical motion is dumped or amplified. This is important for wind energy applications as it affects wind turbine wakes and thus the yield of wind parks. The paper provides an assessment of stability metrics measured by ground-based microwave radiometers in different climatological conditions and with instrument types, on- and offshore. Results indicate that special precaution may be required offshore to achieve typical onshore performances.
Tessa E. Rosenberger, David D. Turner, Thijs Heus, Girish N. Raghunathan, Timothy J. Wagner, and Julia Simonson
Atmos. Meas. Tech., 17, 6595–6602, https://doi.org/10.5194/amt-17-6595-2024, https://doi.org/10.5194/amt-17-6595-2024, 2024
Short summary
Short summary
This work used model output to show that considering the changes in boundary layer depth over time in the calculations of variables such as fluxes and variance yields more accurate results than cases where calculations were done at a constant height. This work was done to improve future observations of these variables at the top of the boundary layer.
Julia Danzer, Magdalena Pieler, and Gottfried Kirchengast
Atmos. Meas. Tech., 17, 4979–4995, https://doi.org/10.5194/amt-17-4979-2024, https://doi.org/10.5194/amt-17-4979-2024, 2024
Short summary
Short summary
We investigated the potential of radio occultation (RO) data for climate-oriented wind field monitoring, focusing on the equatorial band within ±5° latitude. In this region, the geostrophic balance breaks down, and the equatorial balance approximation takes over. The study encourages the use of RO wind fields for mesoscale climate monitoring for the equatorial region, showing a small improvement in the troposphere when including the meridional wind in the zonal-mean total wind speed.
Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius
Atmos. Meas. Tech., 17, 4529–4552, https://doi.org/10.5194/amt-17-4529-2024, https://doi.org/10.5194/amt-17-4529-2024, 2024
Short summary
Short summary
We present a verification of two products based on weather radars to detect the presence of hail and estimate its size. Radar products are remote detection of hail, so they must be verified against ground-based observations. We use reports from users of the Swiss Weather Services phone app to do the verification. We found that the product estimating the presence of hail provides fair results but that it should be recalibrated and that estimating the hail size with radar is more challenging.
Bahareh Rahimi and Ulrich Foelsche
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-81, https://doi.org/10.5194/amt-2024-81, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This study explores the use of GNSS-RO data to improve understanding of the vertical structure of humidity in Atmospheric Rivers (ARs). Specific humidity profiles and IWV values from GNSS-RO are evaluated to assess if this method offers additional insights into ARs' vertical characteristics. The results suggest that combining GNSS-RO data, with its high vertical resolution, with SSMI/S data, known for high horizontal resolution, provides a more complete view of the 3D structure of ARs.
Saverio Paolella, Axel Von Engeln, Sebastiano Padovan, Riccardo Notarpietro, Christian Marquardt, Francisco Sancho, Veronica Rivas Boscan, Nicolas Morew, and Francisco Martin Alemany
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-82, https://doi.org/10.5194/amt-2024-82, 2024
Preprint under review for AMT
Short summary
Short summary
This study evaluates the ability of the EUMETSAT Sentinel-6A RO-NTC processor to provide high quality bending angle profiles. The analysis spans from the signals SNR and phase noise to the determination of the optimal signals cut-off points in the tropospheric region. Some processor enhancements and the impact on the data quality is also discussed. Data were compared against ECMWF confirming the ability of the EUMETSAT RO processors in maintaining consistent and high-quality data.
Hai Nguyen, Derek Posselt, Igor Yanovsky, Longtao Wu, and Svetla Hristova-Veleva
Atmos. Meas. Tech., 17, 3103–3119, https://doi.org/10.5194/amt-17-3103-2024, https://doi.org/10.5194/amt-17-3103-2024, 2024
Short summary
Short summary
Accurate global wind estimation is crucial for weather prediction and environmental modeling. Our study investigates a method to refine atmospheric motion vectors (AMVs) by comparing them with high-precision active-sensor winds. Leveraging supervised learning, we discovered that using high-precision active-sensor data can significantly reduce biases in passive-sensor winds in addition to providing estimates of the wind errors, thereby improving their reliability.
Liqin Jin, Mauro Ghirardelli, Jakob Mann, Mikael Sjöholm, Stephan Thomas Kral, and Joachim Reuder
Atmos. Meas. Tech., 17, 2721–2737, https://doi.org/10.5194/amt-17-2721-2024, https://doi.org/10.5194/amt-17-2721-2024, 2024
Short summary
Short summary
Three-dimensional wind fields can be accurately measured by sonic anemometers. However, the traditional mast-mounted sonic anemometers are not flexible in various applications, which can be potentially overcome by drones. Therefore, we conducted a proof-of-concept study by applying three continuous-wave Doppler lidars to characterize the complex flow around a drone to validate the results obtained by CFD simulations. Both methods show good agreement, with a velocity difference of 0.1 m s-1.
Ewa Agnieszka Krajny, Leszek Ośródka, and Marek Jan Wojtylak
Atmos. Meas. Tech., 17, 2451–2464, https://doi.org/10.5194/amt-17-2451-2024, https://doi.org/10.5194/amt-17-2451-2024, 2024
Short summary
Short summary
The use of sodar data to support an air quality forecasting system is encouraging.
The sodar model is a complement to forecasting methods because it is useful due to its simplicity and speed of calculations. It does not require emission data, for which it is difficult to quickly verify temporal and spatial variability.
The use of simple formulas of regression models in forecasting, while maintaining their multivariate nature, facilitates the optimisation of the prediction process.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 17, 2219–2233, https://doi.org/10.5194/amt-17-2219-2024, https://doi.org/10.5194/amt-17-2219-2024, 2024
Short summary
Short summary
We conducted a radiance closure experiment using a unique combination of two hyperspectral radiometers, one operating in the microwave and the other in the infrared. By comparing the measurements of the two hyperspectrometers to synthetic radiance simulated from collocated atmospheric profiles, we affirmed the proper performance of the two instruments and quantified their radiometric uncertainty for atmospheric sounding applications.
Kyriakoula Papachristopoulou, Ilias Fountoulakis, Alkiviadis F. Bais, Basil E. Psiloglou, Nikolaos Papadimitriou, Ioannis-Panagiotis Raptis, Andreas Kazantzidis, Charalampos Kontoes, Maria Hatzaki, and Stelios Kazadzis
Atmos. Meas. Tech., 17, 1851–1877, https://doi.org/10.5194/amt-17-1851-2024, https://doi.org/10.5194/amt-17-1851-2024, 2024
Short summary
Short summary
The upgraded systems SENSE2 and NextSENSE2 focus on improving the quality of solar nowcasting and forecasting. SENSE2 provides real-time estimates of solar irradiance across a wide region every 15 min. NextSENSE2 offers short-term forecasts of irradiance up to 3 h ahead. Evaluation with actual data showed that the instantaneous comparison yields the most discrepancies due to the uncertainties of cloud-related information and satellite versus ground-based spatial representativeness limitations.
Giandomenico Pace, Alcide di Sarra, Filippo Cali Quaglia, Virginia Ciardini, Tatiana Di Iorio, Antonio Iaccarino, Daniela Meloni, Giovanni Muscari, and Claudio Scarchilli
Atmos. Meas. Tech., 17, 1617–1632, https://doi.org/10.5194/amt-17-1617-2024, https://doi.org/10.5194/amt-17-1617-2024, 2024
Short summary
Short summary
This study investigates the performances of 17 formulas to determine the clear sky longwave downward irradiance in the Arctic environment. The formulas need to be tuned to the environmental conditions of the studied region and, to date, few of them have been developed and/or tested in the Arctic. The best formulas provide biases and root mean squared errors respectively smaller than 1 and 5 W m-2. We intend to use these results to estimate the longwave cloud radiative perturbation.
Bruna Barbosa Silveira, Emma Catherine Turner, and Jérôme Vidot
Atmos. Meas. Tech., 17, 1279–1296, https://doi.org/10.5194/amt-17-1279-2024, https://doi.org/10.5194/amt-17-1279-2024, 2024
Short summary
Short summary
A fast radiative transfer model, used to speed up the full spectral simulation of meteorological satellite channels in weather forecast models, is tested using 25 000 modelled atmospheres. The differences between calculations from the fast and the high-resolution reference models are examined for nine historic weather satellite instruments. The study confirms that a reduced set of 83 atmospheric profiles is robust enough to estimate the scale of the differences obtained from the larger sample.
Linda Bogerd, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 247–259, https://doi.org/10.5194/amt-17-247-2024, https://doi.org/10.5194/amt-17-247-2024, 2024
Short summary
Short summary
Algorithms merge satellite radiometer data from various frequency channels, each tied to a different footprint size. We studied the uncertainty associated with sampling (over the Netherlands using 4 years of data) as precipitation is highly variable in space and time by simulating ground-based data as satellite footprints. Though sampling affects precipitation estimates, it doesn’t explain all discrepancies. Overall, uncertainties in the algorithm seem more influential than how data is sampled.
Hua Lu, Min Xie, Wei Zhao, Bojun Liu, Tijian Wang, and Bingliang Zhuang
Atmos. Meas. Tech., 17, 167–179, https://doi.org/10.5194/amt-17-167-2024, https://doi.org/10.5194/amt-17-167-2024, 2024
Short summary
Short summary
Observations of vertical wind in regions with complex terrain are essential, but they are always sparse and have poor representation. Data verification and quality control are conducted on the wind profile radar and Aeolus wind products in this study, trying to compensate for the limitations of wind field observations. The results shed light on the comprehensive applications of multi-source wind profile data in complicated terrain regions with sparse ground-based wind observations.
Timothy J. Wagner, Thomas August, Tim Hultberg, and Ralph A. Petersen
Atmos. Meas. Tech., 17, 1–14, https://doi.org/10.5194/amt-17-1-2024, https://doi.org/10.5194/amt-17-1-2024, 2024
Short summary
Short summary
Commercial passenger and freight aircraft need to know the temperature and pressure of the environments they fly through in order to safely operate. In this paper, we investigate how these observations can be used to evaluate and monitor the performance of satellite observations. Normally weather balloons are used for this, but in places like the United States there are many more airplane flights than weather balloon launches. This makes it much easier to compare them to satellites.
Maria Lívia L. M. Gava, Simone M. S. Costa, and Anthony C. S. Porfírio
Atmos. Meas. Tech., 16, 5429–5441, https://doi.org/10.5194/amt-16-5429-2023, https://doi.org/10.5194/amt-16-5429-2023, 2023
Short summary
Short summary
This study assesses the effectiveness of two geostationary satellite-based sunshine duration datasets over Brazil. Statistical parameters were used to evaluate the performance of the products. The results showed generally good agreement between satellite and ground observations, with some regional discrepancies. Overall, both satellite products offer reliable data for various applications, which benefit from their high spatial resolution and low time latency.
Hubert Luce, Lakshmi Kantha, and Hiroyuki Hashiguchi
Atmos. Meas. Tech., 16, 5091–5101, https://doi.org/10.5194/amt-16-5091-2023, https://doi.org/10.5194/amt-16-5091-2023, 2023
Short summary
Short summary
The potential ability of clear air radars to measure turbulence kinetic energy (TKE) dissipation rate ε in the atmosphere is a major asset of these instruments because of their continuous measurements. In the present work, we successfully tested the relevance of a model relating ε to the width of the Doppler spectrum peak and wind shear for shear-generated turbulence and we provide a physical interpretation of an empirical model in this context.
Sheila Kirkwood, Evgenia Belova, Peter Voelger, Sourav Chatterjee, and Karathazhiyath Satheesan
Atmos. Meas. Tech., 16, 4215–4227, https://doi.org/10.5194/amt-16-4215-2023, https://doi.org/10.5194/amt-16-4215-2023, 2023
Short summary
Short summary
We compared 2 years of wind measurements by the Aeolus satellite with winds from two wind-profiler radars in Arctic Sweden and coastal Antarctica. Biases are similar in magnitude to results from other locations. They are smaller than in earlier studies due to more comparison points and improved criteria for data rejection. On the other hand, the standard deviation is somewhat higher because of degradation of the Aeolus lidar.
Haichen Zuo and Charlotte Bay Hasager
Atmos. Meas. Tech., 16, 3901–3913, https://doi.org/10.5194/amt-16-3901-2023, https://doi.org/10.5194/amt-16-3901-2023, 2023
Short summary
Short summary
Aeolus is a satellite equipped with a Doppler wind lidar to detect global wind profiles. This study evaluates the impact of Aeolus winds on surface wind forecasts over tropical oceans and high-latitude regions based on the ECMWF observing system experiments. We find that Aeolus can slightly improve surface wind forecasts for the region > 60° N, especially from day 5 onwards. For other study regions, the impact of Aeolus is nearly neutral or limited, which requires further investigation.
Holger Baars, Joshua Walchester, Elizaveta Basharova, Henriette Gebauer, Martin Radenz, Johannes Bühl, Boris Barja, Ulla Wandinger, and Patric Seifert
Atmos. Meas. Tech., 16, 3809–3834, https://doi.org/10.5194/amt-16-3809-2023, https://doi.org/10.5194/amt-16-3809-2023, 2023
Short summary
Short summary
In 2018, the Aeolus satellite of the European Space Agency (ESA) was launched to improve weather forecasts through global measurements of wind profiles. Given the novel lidar technique onboard, extensive validation efforts have been needed to verify the observations. For this reason, we performed long-term validation measurements in Germany and Chile. We found significant improvement in the data products due to a new algorithm version and can confirm the general validity of Aeolus observations.
Hubert Luce, Lakshmi Kantha, Hiroyuki Hashiguchi, Dale Lawrence, Abhiram Doddi, Tyler Mixa, and Masanori Yabuki
Atmos. Meas. Tech., 16, 3561–3580, https://doi.org/10.5194/amt-16-3561-2023, https://doi.org/10.5194/amt-16-3561-2023, 2023
Short summary
Short summary
Doppler radars can be used to estimate turbulence kinetic energy dissipation rates in the atmosphere. The performance of various models is evaluated from comparisons between UHF wind profiler and in situ measurements with UAVs. For the first time, we assess a model supposed to be valid for weak stratification or strong shear conditions. This model provides better agreements with in situ measurements than the classical model based on the hypothesis of a stable stratification.
Chengfeng Feng and Zhaoxia Pu
Atmos. Meas. Tech., 16, 2691–2708, https://doi.org/10.5194/amt-16-2691-2023, https://doi.org/10.5194/amt-16-2691-2023, 2023
Short summary
Short summary
This study demonstrates the positive impacts of assimilating Aeolus Mie-cloudy and Rayleigh-clear near-real-time horizontal line-of-sight winds on the analysis and forecasts of Hurricane Ida (2021) and a mesoscale convective system associated with an African easterly wave using the mesoscale community Weather Research and Forecasting model and the NCEP Gridpoint Statistical Interpolation-based three-dimensional ensemble-variational hybrid data assimilation system.
Tim Trent, Richard Siddans, Brian Kerridge, Marc Schröder, Noëlle A. Scott, and John Remedios
Atmos. Meas. Tech., 16, 1503–1526, https://doi.org/10.5194/amt-16-1503-2023, https://doi.org/10.5194/amt-16-1503-2023, 2023
Short summary
Short summary
Modern weather satellites provide essential information on our lower atmosphere's moisture content and temperature structure. This measurement record will span over 40 years, making it a valuable resource for climate studies. This study characterizes atmospheric temperature and humidity profiles from a European Space Agency climate project. Using weather balloon measurements, we demonstrated the performance of this dataset was within the tolerances required for future climate studies.
Benjamin Witschas, Christian Lemmerz, Alexander Geiß, Oliver Lux, Uwe Marksteiner, Stephan Rahm, Oliver Reitebuch, Andreas Schäfler, and Fabian Weiler
Atmos. Meas. Tech., 15, 7049–7070, https://doi.org/10.5194/amt-15-7049-2022, https://doi.org/10.5194/amt-15-7049-2022, 2022
Short summary
Short summary
In August 2018, the first wind lidar Aeolus was launched into space and has since then been providing data of the global wind field. The primary goal of Aeolus was the improvement of numerical weather prediction. To verify the quality of Aeolus wind data, DLR performed four airborne validation campaigns with two wind lidar systems. In this paper, we report on results from the two later campaigns, performed in Iceland and the tropics.
Olivier Bock, Pierre Bosser, and Carl Mears
Atmos. Meas. Tech., 15, 5643–5665, https://doi.org/10.5194/amt-15-5643-2022, https://doi.org/10.5194/amt-15-5643-2022, 2022
Short summary
Short summary
Integrated water vapour measurements are often compared for the calibration and validation of instruments or techniques. Measurements made at different altitudes must be corrected to account for the vertical variation of water vapour. This paper shows that the widely used empirical correction model has severe limitations that are overcome using the proposed model. The method is applied to the inter-comparison of GPS and satellite microwave radiometer data in a tropical mountainous area.
Anthony J. Mannucci, Chi O. Ao, Byron A. Iijima, Thomas K. Meehan, Panagiotis Vergados, E. Robert Kursinski, and William S. Schreiner
Atmos. Meas. Tech., 15, 4971–4987, https://doi.org/10.5194/amt-15-4971-2022, https://doi.org/10.5194/amt-15-4971-2022, 2022
Short summary
Short summary
The Global Positioning System (GPS) radio occultation (RO) technique is a satellite-based method for producing highly accurate vertical profiles of atmospheric temperature and pressure. RO profiles are used to monitor global climate trends, particularly in that region of the atmosphere that includes the lower stratosphere. Two data sets spanning 1995–1997 that were produced from the first RO satellite are highly accurate and can be used to assess global atmospheric models.
Ze Chen, Yufang Tian, Yinan Wang, Yongheng Bi, Xue Wu, Juan Huo, Linjun Pan, Yong Wang, and Daren Lü
Atmos. Meas. Tech., 15, 4785–4800, https://doi.org/10.5194/amt-15-4785-2022, https://doi.org/10.5194/amt-15-4785-2022, 2022
Short summary
Short summary
Small-scale turbulence plays a vital role in the vertical exchange of heat, momentum and mass in the atmosphere. There are currently three models that can use spectrum width data of MST radar to calculate turbulence parameters. However, few studies have explored the applicability of the three calculation models. We compared and analysed the turbulence parameters calculated by three models. These results can provide a reference for the selection of models for calculating turbulence parameters.
Damao Zhang, Jennifer Comstock, and Victor Morris
Atmos. Meas. Tech., 15, 4735–4749, https://doi.org/10.5194/amt-15-4735-2022, https://doi.org/10.5194/amt-15-4735-2022, 2022
Short summary
Short summary
The planetary boundary layer is the lowest part of the atmosphere. Its structure and depth (PBLHT) significantly impact air quality, global climate, land–atmosphere interactions, and a wide range of atmospheric processes. To test the robustness of the ceilometer-estimated PBLHT under different atmospheric conditions, we compared ceilometer- and radiosonde-estimated PBLHTs using multiple years of U.S. DOE ARM measurements at various ARM observatories located around the world.
Rachel Robey and Julie K. Lundquist
Atmos. Meas. Tech., 15, 4585–4622, https://doi.org/10.5194/amt-15-4585-2022, https://doi.org/10.5194/amt-15-4585-2022, 2022
Short summary
Short summary
Our work investigates the behavior of errors in remote-sensing wind lidar measurements due to turbulence. Using a virtual instrument, we measured winds in simulated atmospheric flows and decomposed the resulting error. Dominant error mechanisms, particularly vertical velocity variations and interactions with shear, were identified in ensemble data over three test cases. By analyzing the underlying mechanisms, the response of the error behavior to further varying flow conditions may be projected.
Donato Summa, Fabio Madonna, Noemi Franco, Benedetto De Rosa, and Paolo Di Girolamo
Atmos. Meas. Tech., 15, 4153–4170, https://doi.org/10.5194/amt-15-4153-2022, https://doi.org/10.5194/amt-15-4153-2022, 2022
Short summary
Short summary
The evolution of the atmospheric boundary layer height (ABLH) has an important impact on meteorology. However, the complexity of the phenomena occurring within the ABL and the influence of advection and local accumulation processes often prevent an unambiguous determination of the ABLH. The paper reports results from an inter-comparison effort involving different sensors and techniques to measure the ABLH. Correlations between the ABLH and other atmospheric variables are also assessed.
Haichen Zuo, Charlotte Bay Hasager, Ioanna Karagali, Ad Stoffelen, Gert-Jan Marseille, and Jos de Kloe
Atmos. Meas. Tech., 15, 4107–4124, https://doi.org/10.5194/amt-15-4107-2022, https://doi.org/10.5194/amt-15-4107-2022, 2022
Short summary
Short summary
The Aeolus satellite was launched in 2018 for global wind profile measurement. After successful operation, the error characteristics of Aeolus wind products have not yet been studied over Australia. To complement earlier validation studies, we evaluated the Aeolus Level-2B11 wind product over Australia with ground-based wind profiling radar measurements and numerical weather prediction model equivalents. The results show that the Aeolus can detect winds with sufficient accuracy over Australia.
Carmen González, José M. Vilaplana, José A. Bogeat, and Antonio Serrano
Atmos. Meas. Tech., 15, 4125–4133, https://doi.org/10.5194/amt-15-4125-2022, https://doi.org/10.5194/amt-15-4125-2022, 2022
Short summary
Short summary
Monitoring ultraviolet (UV) radiation is important since it can have harmful effects on the biosphere. Array spectroradiometers are increasingly used to measure UV as they are more versatile than scanning spectroradiometers. In this study, the long-term performance of the BTS-2048-UV-S-WP array spectroradiometer was assessed. The results show that the BTS can reliably measure both the UV index and UV radiation in the 300–360 nm range. Moreover, the BTS was stable and showed no seasonal behavior.
Charlotte Rahlves, Frank Beyrich, and Siegfried Raasch
Atmos. Meas. Tech., 15, 2839–2856, https://doi.org/10.5194/amt-15-2839-2022, https://doi.org/10.5194/amt-15-2839-2022, 2022
Short summary
Short summary
Lidars can measure the wind profile in the lower part of the atmosphere, provided that the wind field is horizontally uniform and does not change during the time of the measurement. These requirements are mostly not fulfilled in reality, and the lidar wind measurement will thus hold a certain error. We investigate different strategies for lidar wind profiling using a lidar simulator implemented in a numerical simulation of the wind field. Our findings can help to improve wind measurements.
Katherine E. Lukens, Kayo Ide, Kevin Garrett, Hui Liu, David Santek, Brett Hoover, and Ross N. Hoffman
Atmos. Meas. Tech., 15, 2719–2743, https://doi.org/10.5194/amt-15-2719-2022, https://doi.org/10.5194/amt-15-2719-2022, 2022
Short summary
Short summary
Winds that are crucial to weather forecasting derived from two different techniques – tracking satellite images (AMVs) and direct measurement of molecular and aerosol motions by Doppler lidar (Aeolus satellite winds) – are compared. We find that AMVs and Aeolus winds are highly correlated. Aeolus Mie-cloudy winds have great potential value as a comparison standard for AMVs. Larger differences are found in the Southern Hemisphere related to higher wind speed and higher vertical variation in wind.
Marijn Floris van Dooren, Anantha Padmanabhan Kidambi Sekar, Lars Neuhaus, Torben Mikkelsen, Michael Hölling, and Martin Kühn
Atmos. Meas. Tech., 15, 1355–1372, https://doi.org/10.5194/amt-15-1355-2022, https://doi.org/10.5194/amt-15-1355-2022, 2022
Short summary
Short summary
The remote sensing technique lidar is widely used for wind speed measurements for both industrial and academic applications. Lidars can measure wind statistics accurately but cannot fully capture turbulent fluctuations in the high-frequency range, since they are partly filtered out. This paper therefore investigates the turbulence spectrum measured by a continuous-wave lidar and analytically models the lidar's measured spectrum with a Lorentzian filter function and a white noise term.
Alain Protat, Valentin Louf, Joshua Soderholm, Jordan Brook, and William Ponsonby
Atmos. Meas. Tech., 15, 915–926, https://doi.org/10.5194/amt-15-915-2022, https://doi.org/10.5194/amt-15-915-2022, 2022
Short summary
Short summary
This study uses collocated ship-based, ground-based, and spaceborne radar observations to validate the concept of using the GPM spaceborne radar observations to calibrate national weather radar networks to the accuracy required for operational severe weather applications such as rainfall and hail nowcasting.
Wagner Wolff, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 15, 485–502, https://doi.org/10.5194/amt-15-485-2022, https://doi.org/10.5194/amt-15-485-2022, 2022
Short summary
Short summary
The existing infrastructure for cellular communication is promising for ground-based rainfall remote sensing. Rain-induced signal attenuation is used in dedicated algorithms for retrieving rainfall depth along commercial microwave links (CMLs) between cell phone towers. This processing is a source of many uncertainties about input data, algorithm structures, parameters, CML network, and local climate. Application of a stochastic optimization method leads to improved CML rainfall estimates.
Cited articles
Anonymous referee: Referee comment 2, Comment on egusphere-2023-1310, https://doi.org/10.5194/egusphere-2023-1310-RC2, 2023. a, b
Boukabara, S.-A., Garrett, K., Chen, W., Iturbide-Sanchez, F., Grassotti, C., Kongoli, C., Chen, R., Liu, Q., Yan, B., Weng, F., Ferraro, R., Kleespies, T. J., and Meng, H.: MiRS: An All-Weather 1DVAR Satellite Data Assimilation and Retrieval System, IEEE T. Geosci. Remote, 49, 3249–3272, https://doi.org/10.1109/TGRS.2011.2158438, 2011. a
Cifelli, R., Chandrasekar, V., Lim, S., Kennedy, P. C., Wang, Y., and Rutledge, S. A.: A New Dual-Polarization Radar Rainfall Algorithm: Application in Colorado Precipitation Events, J. Atmos. Ocean. Tech., 28, 352–364, https://doi.org/10.1175/2010JTECHA1488.1, 2011. a
GPM Science Team: GPM SSMIS on F17 (GPROF) Climate-based Radiometer Precipitation Profiling 1.5 hours 12 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/SSMIS/F17/GPROFCLIM/2A/07, 2022a. a
GPM Science Team: GPM AMSR-2 on GCOM-W1 (GPROF) Climate-based Radiometer Precipitation Profiling L2A 1.5 hours 10 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/AMSR2/GCOMW1/GPROFCLIM/2A/07, 2022b. a
GPM Science Team: GPM GMI (GPROF) Climate-based Radiometer Precipitation Profiling L2A 1.5 hours 4 km x 4 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/GMI/GPROFCLIM/2A/07, 2022c. a
GPM Science Team: GPM MHS on NOAA-19 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/MHS/NOAA19/GPROFCLIM/2A/07, 2022d. a
GPM Science Team: GPM ATMS on SUOMI-NPP (GPROF) Radiometer Precipitation Profiling L2 1.5 hours 16 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/ATMS/NPP/GPROFCLIM/2A/07, 2022e. a
Grecu, M., Olson, W. S., Munchak, S. J., Ringerud, S., Liao, L., Haddad, Z., Kelley, B. L., and McLaughlin, S. F.: The GPM Combined Algorithm, J. Atmos. Ocean. Tech., 33, 2225–2245, https://doi.org/10.1175/JTECH-D-16-0019.1, 2016. a, b, c
Guilloteau, C., Foufoula-Georgiou, E., and Kummerow, C. D.: Global multiscale evaluation of satellite passive microwave retrieval of precipitation during the TRMM and GPM eras: Effective resolution and regional diagnostics for future algorithm development, J. Hydrometeorol., 18, 3051–3070, https://doi.org/10.1175/JHM-D-17-0087.1, 2017. a
Hegerl, G. C., Black, E., Allan, R. P., Ingram, W. J., Polson, D., Trenberth, K. E., Chadwick, R. S., Arkin, P. A., Sarojini, B. B., Becker, A., Dai, A., Durack, P. J., Easterling, D., Fowler, H. J., Kendon, E. J., Huffman, G. J., Liu, C., Marsh, R., New, M., Osborn, T. J., Skliris, N., Stott, P. A., Vidale, P.-L., Wijffels, S. E., Wilcox, L. J., Willett, K. M., and Zhang, X.: Challenges in Quantifying Changes in the Global Water Cycle, B. Am. Meteorol. Soc., 96, 1097–1115, https://doi.org/10.1175/BAMS-D-13-00212.1, 2015. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D., Kojima, M., Oki, R., Nakamura, K., and Iguchi, T.: The Global Precipitation Measurement Mission, B. Am. Meteorol. Soc., 95, 701–722, https://doi.org/10.1175/BAMS-D-13-00164.1, 2014. a
Hoyer, S. and Hamman, J.: xarray: N-D labeled arrays and datasets in Python, Journal of Open Research Software, 5, 10, https://doi.org/10.5334/jors.148, 2017. a
Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K.-L., Joyce, R. J., Kidd, C., Nelkin, E. J., Sorooshian, S., Stocker, E. F., Tan, J., Wolff, D. B., and Xie, P.: Integrated Multi-satellite Retrievals for the Global Precipitation Measurement (GPM) Mission (IMERG), Springer International Publishing, Cham, ISBN 978-3-030-24568-9, 343–353, https://doi.org/10.1007/978-3-030-24568-9_19, 2020. a
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci. Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Kerr, C. A. and Alsheimer, F.: Storm-Scale Predictability and Analysis of the 13 April 2020 Central Savannah River Area Tornado Outbreak, Weather Forecast., 37, 901–913, https://doi.org/10.1175/WAF-D-21-0185.1, 2022. a
Kirschbaum, D. B., Huffman, G. J., Adler, R. F., Braun, S., Garrett, K., Jones, E., McNally, A., Skofronick-Jackson, G., Stocker, E., Wu, H., and Zaitchik, B. F.: NASA's Remotely Sensed Precipitation: A Reservoir for Applications Users, B. Am. Meteorol. Soc., 98, 1169–1184, https://doi.org/10.1175/BAMS-D-15-00296.1, 2017. a
Kirstetter, P.-E., Hong, Y., Gourley, J. J., Chen, S., Flamig, Z., Zhang, J., Schwaller, M., Petersen, W., and Amitai, E.: Toward a Framework for Systematic Error Modeling of Spaceborne Precipitation Radar with NOAA/NSSL Ground Radar-Based National Mosaic QPE, J. Hydrometeorol., 13, 1285–1300, https://doi.org/10.1175/JHM-D-11-0139.1, 2012. a, b, c
Kummerow, C. D., Randel, D. L., Kulie, M., Wang, N.-Y., Ferraro, R., Joseph Munchak, S., and Petkovic, V.: The Evolution of the Goddard Profiling Algorithm to a Fully Parametric Scheme, J. Atmos. Ocean. Tech., 32, 2265–2280, https://doi.org/10.1175/JTECH-D-15-0039.1, 2015. a
Met Office: Cartopy: a cartographic python library with a matplotlib interface, Exeter, Devon, http://scitools.org.uk/cartopy (last access: 1 April 2023), 2010–2015. a
Olson, W.: GPM DPR and GMI Combined Precipitation L2B 1.5 hours 5 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/DPRGMI/CMB/2B/07, 2022. a
Perez, F. and Granger, B. E.: IPython: A System for Interactive Scientific Computing, Comput. Sci. Eng., 9, 21–29, https://doi.org/10.1109/MCSE.2007.53, 2007. a
Pfreundschuh, S.: GPROF-NN: A neural network based implementation of the Goddard Profiling Algorithm (v0.1.1), Zenodo [code], https://doi.org/10.5281/zenodo.10257786, 2023. a, b
Raspaud, M., Hoese, D., Lahtinen, P., Finkensieper, S., Holl, G., Proud, S., Dybbroe, A., Meraner, A., Feltz, J., Zhang, X., Joro, S., Roberts, W., Ørum Rasmussen, L., Strandgren, BENR0, Méndez, J. H. B., Zhu, Y., Daruwala, R., Jasmin, T., mherbertson, Kliche, C., Barnie, T., Sigurðsson, E., Garcia, R. K., Leppelt, T., TT, ColinDuff, Egede, U., LTMeyer, and Itkin, M.: pytroll/satpy: Version 0.33.1, Zenodo [code], https://doi.org/10.5281/zenodo.5789830, 2021. a
Ryzhkov, A. V., Giangrande, S. E., Melnikov, V. M., and Schuur, T. J.: Calibration Issues of Dual-Polarization Radar Measurements, J. Atmos. Ocean. Tech., 22, 1138–1155, https://doi.org/10.1175/JTECH1772.1, 2005. a
Skofronick-Jackson, G., Petersen, W. A., Berg, W., Kidd, C., Stocker, E. F., Kirschbaum, D. B., Kakar, R., Braun, S. A., Huffman, G. J., Iguchi, T., Kirstetter, P. E., Kummerow, C., Meneghini, R., Oki, R., Olson, W. S., Takayabu, Y. N., Furukawa, K., and Wilheit, T.: The Global Precipitation Measurement (GPM) Mission for Science and Society, B. Am. Meteorol. Soc., 98, 1679–1695, https://doi.org/10.1175/BAMS-D-15-00306.1, 2017. a
Tapiador, F., Navarro, A., Levizzani, V., García-Ortega, E., Huffman, G., Kidd, C., Kucera, P., Kummerow, C., Masunaga, H., Petersen, W., Roca, R., Sánchez, J.-L., Tao, W.-K., and Turk, F.: Global precipitation measurements for validating climate models, Atmos. Res., 197, 1–20, https://doi.org/10.1016/j.atmosres.2017.06.021, 2017. a
The Python Language Foundation: The Python Language Reference, Python Language Foundation, https://docs.python.org/3/reference/index.html (last access: 1 April 2023), 2018. a
van der Walt, S., Colbert, S. C., and Varoquaux, G.: The NumPy Array: A Structure for Efficient Numerical Computation, Comput. Sci. Eng., 13, 22–30, https://doi.org/10.1109/MCSE.2011.37, 2011. a
Executive editor
This work validates retrievals from the latest operational version of the NASA Goddard Profiling Algorithm (GPROF), currently version 7, and it quantitatively demonstrates the performance improvements with respect to previous versions (GPROF v05) at various spatial and temporal resolutions. It also presents new, not yet operationally implemented, machine learning based versions of GPROF (GPROF-NN).
This work validates retrievals from the latest operational version of the NASA Goddard Profiling...
Short summary
The latest version of the GPROF retrieval algorithm that produces global precipitation estimates using observations from the Global Precipitation Measurement mission is validated against ground-based radars. The validation shows that the algorithm accurately estimates precipitation on scales ranging from continental to regional. In addition, we validate candidates for the next version of the algorithm and identify principal challenges for further improving space-borne rain measurements.
The latest version of the GPROF retrieval algorithm that produces global precipitation estimates...
