Articles | Volume 13, issue 11
https://doi.org/10.5194/essd-13-5369-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-5369-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The first global 883 GHz cloud ice survey: IceCube Level 1 data calibration, processing and analysis
GESTAR, Universities Space Research Association, Columbia, MD, United States
NASA Goddard Space Flight Center, Greenbelt, MD, United States
Dong L. Wu
NASA Goddard Space Flight Center, Greenbelt, MD, United States
Patrick Eriksson
Department of Space, Earth and Environment, Chalmers University of Technology, Gothenburg, Sweden
Related authors
Jie Gong, Dong L. Wu, Michelle Badalov, Manisha Ganeshan, and Minghua Zheng
Atmos. Meas. Tech., 18, 4025–4043, https://doi.org/10.5194/amt-18-4025-2025, https://doi.org/10.5194/amt-18-4025-2025, 2025
Short summary
Short summary
Marine boundary layer (MABL) water vapor is among the key factors to couple the ocean and atmosphere, but it is also among the hardest to retrieve from a satellite remote sensing perspective. Here we propose a novel way to retrieve MABL specific humidity profiles using the GNSS (Global Navigation Satellite System) Level-1 signal-to-noise ratio. Using a machine learning approach, we successfully obtained a retrieval product that outperforms the ERA-5 reanalysis and operational Level-2 retrievals globally, except in the deep tropics.
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).
Dong L. Wu, Valery A. Yudin, Kyu-Myong Kim, Mohar Chattopadhyay, Lawrence Coy, Ruth S. Lieberman, C. C. Jude H. Salinas, Jae N. Lee, Jie Gong, and Guiping Liu
Atmos. Meas. Tech., 18, 843–863, https://doi.org/10.5194/amt-18-843-2025, https://doi.org/10.5194/amt-18-843-2025, 2025
Short summary
Short summary
Global Navigation Satellite System radio occultation data help monitor climate and weather prediction but are affected by residual ionospheric errors (RIEs). A new excess-phase-gradient method detects and corrects RIEs, showing both positive and negative values, varying by latitude, time, and solar activity. Tests show that RIE impacts polar stratosphere temperatures in models, with differences up to 3–4 K. This highlights the need for RIE correction to improve the accuracy of data assimilation.
Jie Gong, Xiping Zeng, Dong L. Wu, S. Joseph Munchak, Xiaowen Li, Stefan Kneifel, Davide Ori, Liang Liao, and Donifan Barahona
Atmos. Chem. Phys., 20, 12633–12653, https://doi.org/10.5194/acp-20-12633-2020, https://doi.org/10.5194/acp-20-12633-2020, 2020
Short summary
Short summary
This work provides a novel way of using polarized passive microwave measurements to study the interlinked cloud–convection–precipitation processes. The magnitude of differences between polarized radiances is found linked to ice microphysics (shape, size, orientation and density), mesoscale dynamic and thermodynamic structures, and surface precipitation. We conclude that passive sensors with multiple polarized channel pairs may serve as cheaper and useful substitutes for spaceborne radar sensors.
Jie Gong, Dong L. Wu, Michelle Badalov, Manisha Ganeshan, and Minghua Zheng
Atmos. Meas. Tech., 18, 4025–4043, https://doi.org/10.5194/amt-18-4025-2025, https://doi.org/10.5194/amt-18-4025-2025, 2025
Short summary
Short summary
Marine boundary layer (MABL) water vapor is among the key factors to couple the ocean and atmosphere, but it is also among the hardest to retrieve from a satellite remote sensing perspective. Here we propose a novel way to retrieve MABL specific humidity profiles using the GNSS (Global Navigation Satellite System) Level-1 signal-to-noise ratio. Using a machine learning approach, we successfully obtained a retrieval product that outperforms the ERA-5 reanalysis and operational Level-2 retrievals globally, except in the deep tropics.
Daniel J. Emmons, Cornelius Csar Jude H. Salinas, Dong L. Wu, Nimalan Swarnalingam, Eugene V. Dao, Jorge L. Chau, Yosuke Yamazaki, Kyle E. Fitch, and Victoriya V. Forsythe
EGUsphere, https://doi.org/10.5194/egusphere-2025-3731, https://doi.org/10.5194/egusphere-2025-3731, 2025
This preprint is open for discussion and under review for Annales Geophysicae (ANGEO).
Short summary
Short summary
The E-region of the Earth’s ionosphere plays an important role in atmospheric energy balance and High Frequency radio propagation. In this paper, we compare predictions from two recently developed ionospheric models to observations by ionospheric sounders (ionosondes). Overall, the models show reasonable agreement with the observations. However, there are several areas for improvement in the models as well as questions about the accuracy of the automatically processed ionosonde dataset.
Eleanor May and Patrick Eriksson
EGUsphere, https://doi.org/10.5194/egusphere-2025-2190, https://doi.org/10.5194/egusphere-2025-2190, 2025
Short summary
Short summary
The vertical distribution of atmospheric ice impacts Earth's weather and climate. The Ice Cloud Imager (ICI) will measure at microwave and sub-millimetre frequencies, which are well suited to detect atmospheric ice. In this study, a machine learning model is trained on ICI simulations. Results show that the vertical distribution of ice can be derived from ICI observations, and that ICI could offer a valuable data source that complements existing radar- and lidar-based measurements.
Patrick Eriksson, Anders Emrich, Kalle Kempe, Johan Riesbeck, Alhassan Aljarosha, Olivier Auriacombe, Joakim Kugelberg, Enne Hekma, Roland Albers, Axel Murk, Søren Møller Pedersen, Laurenz John, Jan Stake, Peter McEvoy, Bengt Rydberg, Adam Dybbroe, Anke Thoss, Alessio Canestri, Christophe Accadia, Paolo Colucci, Daniele Gherardi, and Ville Kangas
EGUsphere, https://doi.org/10.5194/egusphere-2025-1769, https://doi.org/10.5194/egusphere-2025-1769, 2025
Short summary
Short summary
The Arctic Weather Satellite (AWS), developed by the European Space Agency, highlights a new approach in satellite design, aiming to expand the network of operational microwave sensors cost-effectively. Launched in August 2024, AWS features a 19-channel microwave cross-track radiometer. Notably, it introduces groundbreaking channels at 325.15 GHz. In addition, AWS acts as the stepping stone to a suggested constellation of satellites, denoted as EUMETSAT Polar System Sterna.
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).
Dong L. Wu, Valery A. Yudin, Kyu-Myong Kim, Mohar Chattopadhyay, Lawrence Coy, Ruth S. Lieberman, C. C. Jude H. Salinas, Jae N. Lee, Jie Gong, and Guiping Liu
Atmos. Meas. Tech., 18, 843–863, https://doi.org/10.5194/amt-18-843-2025, https://doi.org/10.5194/amt-18-843-2025, 2025
Short summary
Short summary
Global Navigation Satellite System radio occultation data help monitor climate and weather prediction but are affected by residual ionospheric errors (RIEs). A new excess-phase-gradient method detects and corrects RIEs, showing both positive and negative values, varying by latitude, time, and solar activity. Tests show that RIE impacts polar stratosphere temperatures in models, with differences up to 3–4 K. This highlights the need for RIE correction to improve the accuracy of data assimilation.
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.
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.
Simon Pfreundschuh, Clément Guilloteau, Paula J. Brown, Christian D. Kummerow, and Patrick Eriksson
Atmos. Meas. Tech., 17, 515–538, https://doi.org/10.5194/amt-17-515-2024, https://doi.org/10.5194/amt-17-515-2024, 2024
Short summary
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.
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.
Cornelius Csar Jude H. Salinas, Dong L. Wu, Jae N. Lee, Loren C. Chang, Liying Qian, and Hanli Liu
Atmos. Chem. Phys., 23, 1705–1730, https://doi.org/10.5194/acp-23-1705-2023, https://doi.org/10.5194/acp-23-1705-2023, 2023
Short summary
Short summary
Upper mesospheric carbon monoxide's (CO) photochemical lifetime is longer than dynamical timescales. This work uses satellite observations and model simulations to establish that the migrating diurnal tide and its seasonal and interannual variabilities drive CO primarily through vertical advection. Vertical advection is a transport process that is currently difficult to observe. This work thus shows that we can use CO as a tracer for vertical advection across seasonal and interannual timescales.
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.
Ákos Horváth, James L. Carr, Dong L. Wu, Julia Bruckert, Gholam Ali Hoshyaripour, and Stefan A. Buehler
Atmos. Chem. Phys., 22, 12311–12330, https://doi.org/10.5194/acp-22-12311-2022, https://doi.org/10.5194/acp-22-12311-2022, 2022
Short summary
Short summary
We estimate plume heights for the April 2021 La Soufrière daytime eruptions using GOES-17 near-limb side views and GOES-16–MODIS stereo views. These geometric heights are then compared with brightness-temperature-based radiometric height estimates to characterize the biases of the latter. We also show that the side view method can be applied to infrared imagery and thus nighttime eruptions, albeit with larger uncertainty.
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.
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.
Ákos Horváth, James L. Carr, Olga A. Girina, Dong L. Wu, Alexey A. Bril, Alexey A. Mazurov, Dmitry V. Melnikov, Gholam Ali Hoshyaripour, and Stefan A. Buehler
Atmos. Chem. Phys., 21, 12189–12206, https://doi.org/10.5194/acp-21-12189-2021, https://doi.org/10.5194/acp-21-12189-2021, 2021
Short summary
Short summary
We give a detailed description of a new technique to estimate the height of volcanic eruption columns from near-limb geostationary imagery. Such oblique angle observations offer spectacular side views of eruption columns protruding from the Earth ellipsoid and thereby facilitate a height-by-angle estimation method. Due to its purely geometric nature, the new technique is unaffected by the limitations of traditional brightness-temperature-based height retrievals.
Ákos Horváth, Olga A. Girina, James L. Carr, Dong L. Wu, Alexey A. Bril, Alexey A. Mazurov, Dmitry V. Melnikov, Gholam Ali Hoshyaripour, and Stefan A. Buehler
Atmos. Chem. Phys., 21, 12207–12226, https://doi.org/10.5194/acp-21-12207-2021, https://doi.org/10.5194/acp-21-12207-2021, 2021
Short summary
Short summary
We demonstrate the side view plume height estimation technique described in Part 1 on seven volcanic eruptions from 2019 and 2020, including the 2019 Raikoke eruption. We explore the strengths and limitations of the new technique in comparison to height estimation from brightness temperatures, stereo observations, and ground-based video footage.
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.
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.
Jie Gong, Xiping Zeng, Dong L. Wu, S. Joseph Munchak, Xiaowen Li, Stefan Kneifel, Davide Ori, Liang Liao, and Donifan Barahona
Atmos. Chem. Phys., 20, 12633–12653, https://doi.org/10.5194/acp-20-12633-2020, https://doi.org/10.5194/acp-20-12633-2020, 2020
Short summary
Short summary
This work provides a novel way of using polarized passive microwave measurements to study the interlinked cloud–convection–precipitation processes. The magnitude of differences between polarized radiances is found linked to ice microphysics (shape, size, orientation and density), mesoscale dynamic and thermodynamic structures, and surface precipitation. We conclude that passive sensors with multiple polarized channel pairs may serve as cheaper and useful substitutes for spaceborne radar sensors.
Clark J. Weaver, Pawan K. Bhartia, Dong L. Wu, Gordon J. Labow, and David E. Haffner
Atmos. Meas. Tech., 13, 5715–5723, https://doi.org/10.5194/amt-13-5715-2020, https://doi.org/10.5194/amt-13-5715-2020, 2020
Short summary
Short summary
Currently, we do not know whether clouds will accelerate or moderate climate. We look to the past and ask whether cloudiness has changed over the last 4 decades. Using a suite of nine satellite instruments, we need to ensure that the first satellite, which was launched in 1980 and died in 1991, observed the same measurement as the eight other satellite instruments used in the record. If the instruments were measuring length and observing a 1.00 m long stick, they would all see 0.99 to 1.01 m.
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.
Guoyong Wen, Alexander Marshak, Si-Chee Tsay, Jay Herman, Ukkyo Jeong, Nader Abuhassan, Robert Swap, and Dong Wu
Atmos. Chem. Phys., 20, 10477–10491, https://doi.org/10.5194/acp-20-10477-2020, https://doi.org/10.5194/acp-20-10477-2020, 2020
Short summary
Short summary
We combine the ground-based observations and radiative transfer model to quantify the impact of the 2017 solar eclipse on surface shortwave irradiation reduction. We find that the eclipse caused local reductions of time-averaged surface flux of about 379 W m-2 (50 %) and 329 W m-2 (46 %) during the ~ 3 h course of the eclipse at the Casper and Columbia sites, respectively. We estimate that the Moon’s shadow caused a reduction of approximately 7 %–8 % in global average surface broadband SW radiation.
Cited articles
Bosilovich, M. G., Robertson, F. R., Takacs, L., Molod, A., and Mocko, D.:
Atmospheric water valance and variability in the MERRA-2 reanalysis, J. Climate, 30, 1177–1196, https://doi.org/10.1175/JCLI-D-16-0338.1, 2017. a, b
Buehler, S. A., Jiménez, C., Evans, K. F., Eriksson, P., Rydberg, B., Heymsfield, A. J., Stubenrauch, C. J., Lohmann, U., Emde, C., John, V. O., Sreerekha, T. R., and Davis, C. P.: A concept for a satellite mission to measure cloud ice water path, ice particle size, and cloud altitude, Q. J. Roy. Meteor. Soc., 133, 109–128, https://doi.org/10.1002/qj.143, 2007. a
Buehler, S. A., Mendrok, J., Eriksson, P., Perrin, A., Larsson, R., and Lemke, O.: ARTS, the Atmospheric Radiative Transfer Simulator – version 2.2, the planetary toolbox edition, Geosci. Model Dev., 11, 1537–1556, https://doi.org/10.5194/gmd-11-1537-2018, 2018. a, b
Davis, S., Hlavka, D., Jensen, E., Rosenlof, K., Yang, Q., Schmidt, S., Borrmann, S., Frey, W., Lawson, P., Voemel, H., and Bui, T. P.: In situ and lidar observations of tropopause subvisible cirrus clouds during TC4, J. Geophys. Res., 115, D00J17, https://doi.org/10.1029/2009JD013093, 2010. a
Duncan, D. I. and Eriksson, P.: An update on global atmospheric ice estimates from satellite observations and reanalyses, Atmos. Chem. Phys., 18, 11205–11219, https://doi.org/10.5194/acp-18-11205-2018, 2018. a
Eliasson, S., Buehler, S. A., Milz, M., Eriksson, P., and John, V. O.: Assessing observed and modelled spatial distributions of ice water path using satellite data, Atmos. Chem. Phys., 11, 375–391, https://doi.org/10.5194/acp-11-375-2011, 2011. a, b, c, d
Eriksson, P., Ekström, M., Rydberg, B., and Murtagh, D. P.: First Odin sub-mm retrievals in the tropical upper troposphere: ice cloud properties, Atmos. Chem. Phys., 7, 471–483, https://doi.org/10.5194/acp-7-471-2007, 2007. a
Eriksson, P., Rydberg, B., Sagawa, H., Johnston, M. S., and Kasai, Y.: Overview and sample applications of SMILES and Odin-SMR retrievals of upper tropospheric humidity and cloud ice mass, Atmos. Chem. Phys., 14, 12613–12629, https://doi.org/10.5194/acp-14-12613-2014, 2014. a, b, c
Eriksson, P., Rydberg, B., Mattioli, V., Thoss, A., Accadia, C., Klein, U., and Buehler, S. A.: Towards an operational Ice Cloud Imager (ICI) retrieval product, Atmos. Meas. Tech., 13, 53–71, https://doi.org/10.5194/amt-13-53-2020, 2020. a
Evans, K. F., Wang, J. R., O'C Starr, D., Heymsfield, G., Li, L., Tian, L., Lawson, R. P., Heymsfield, A. J., and Bansemer, A.: Ice hydrometeor profile retrieval algorithm for high-frequency microwave radiometers: application to the CoSSIR instrument during TC4, Atmos. Meas. Tech., 5, 2277–2306, https://doi.org/10.5194/amt-5-2277-2012, 2012. a, b
Field, P. R., Heymsfield, A. J., and Bansemer, A.: Snow size distribution parameterization for midlatitude and tropical ice clouds, J. Atmos. Sci., 64, 4346–4365, https://doi.org/10.1175/2007JAS2344.1, 2007. a
Fox, S.: An evaluation of radiative transfer simulations of cloudy scenes from a numerical weather prediction model at sub-millimetre frequencies using airborne observations, Remote Sens., 12, 2758, https://doi.org/10.3390/rs12172758, 2020. a
Garnier, A., Pelon, J., Dubuisson, P., Yang, P., Faivre, M., Chomette, O., Pascal, N., Lucker, P., and Murray, T.: Retrieval of Cloud Properties Using CALIPSO Imaging Infrared Radiometer. Part II: Effective Diameter and Ice Water Path, J. Appl. Meteorol. Clim., 52, 2582–2599, https://doi.org/10.1175/JAMC-D-12-0328.1, 2013. a, b
Garnier, A., Pelon, J., Pascal, N., Vaughan, M. A., Dubuisson, P., Yang, P., and Mitchell, D. L.: Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part II: Results over oceans, Atmos. Meas. Tech., 14, 3277–3299, https://doi.org/10.5194/amt-14-3277-2021, 2020. a
Geer, A. J. and Baordo, F.: Improved scattering radiative transfer for frozen hydrometeors at microwave frequencies, Atmos. Meas. Tech., 7, 1839–1860, https://doi.org/10.5194/amt-7-1839-2014, 2014. a
Gong, J. and Wu, D. L.: CloudSat-constrained cloud ice water path and cloud top height retrievals from MHS 157 and 183.3 GHz radiances, Atmos. Meas. Tech., 7, 1873–1890, https://doi.org/10.5194/amt-7-1873-2014, 2014. a, b, c
Gong, J. and Wu, D. L.: Microphysical properties of frozen particles inferred from Global Precipitation Measurement (GPM) Microwave Imager (GMI) polarimetric measurements, Atmos. Chem. Phys., 17, 2741–2757, https://doi.org/10.5194/acp-17-2741-2017, 2017. a
Grützun, V., Buehler, S. A., Kluft, L., Mendrok, J., Brath, M., and Eriksson, P.: All-sky information content analysis for novel passive microwave instruments in the range from 23.8 to 874.4 GHz, Atmos. Meas. Tech., 11, 4217–4237, https://doi.org/10.5194/amt-11-4217-2018, 2018. a, b
Hammar, A., Sobis, P., Drakinskiy, V., Emrich, A., Wadefalk, N., Schleeh, J., and Stake, J.: Low noise 874 GHz receivers for the International Submillimetre Airborne Radiometer (ISMAR), Review of Scientifc Instruments, 89, 055104, https://doi.org/10.1063/1.5017583, 2018. a
Kulie, M. S., Bennartz, R., Greenwald, T. J., Chen, Y., and Weng, F.: Uncertainties in microwave properties of frozen precipitation: Implications for remote sensing and data assimilation, J. Atmos. Sci., 67, 3471–3487,
https://doi.org/10.1175/2010JAS3520.1, 2010. a
Li, J.-L. F., Waliser, D. E., Stephens, G., and Lee, S. W.: Characterizing and understanding cloud ice and radiation budgets in global climate models and reanalysis, AMS monograph Attribute to Late Professor M. Yanai, Chap. 13, 13.1–13.20, https://doi.org/10.1175/AMSMONOGRAPHS-D-15-0007.1, 2016. a
McFarquhar, G. M. and Heymsfield, A. J.: Parameterization of tropical cirrus ice crystal size distributions and implications for radiative transfer: Results from CEPEX, J. Atmos. Sci., 54, 2187–2200, 1997. a
Millan, L., Read, W., Kasai, Y., Lambert, A., Livesey, N., Mendrok, J., Sagawa, H., Sano, T., Shiotani, M. and Wu, D. L.:
SMILES ice cloud products, J. Geophys. Res.-Atmos., 118, 6468–6477, https://doi.org/10.1002/jgrd.50322, 2013. a
Moradi, I., Ferraro, R. R., Soden, B. J., Eriksson, P., and Arkin, P.:
Retrieving Layer-Averaged Tropospheric Humidity from Advanced Technology Microwave Sounder Water Vapor Channels, IEEE T. Geosci. Remote, 53, 6675–6688, https://doi.org/10.1109/TGRS.2015.2445832, 2015. a
NAS (National Academy of Sciences of Medicine and Engineering, Division on Engineering and Physical Sciences, Space Studies Board, Committee on the Decadal Survey for Earth Science and Applications from Space): Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space: An overview for decision makers and the public, The National Academies Press, Washington, DC, ISBN-10:0309467578, 716 pp., 2017.
Nesbitt, S. W and Zipser, E. J.: The Diurnal Cycle of Rainfall and Convective Intensity according to Three Years of TRMM Measurements, J. Climate, 16, 1456–1475, https://doi.org/10.1175/1520-0442(2003)016<1456:TDCORA>2.0.CO;2, 2003. a, b
Platnick, S., Meyer, K. G., King, M. D., Wind, G., Amarasinghe, N., Marchant, B., Arnold, G. T., Zhang, Z., Hubanks, P. A., Holz, R. E., Yang, P., Ridgway, W. L., and Riedi, J.: The MODIS Cloud Optical and Microphysical Products: Collection 6 Updates and Examples From Terra and Aqua, IEEE T. Geosci. Remote, 55, 502–525, https://doi.org/10.1109/TGRS.2016.2610522, 2017. a, b
Sassen, K., Wang, Z., and Liu, D.: Cirrus clouds and deep convection in the tropics: Insights from CALIPSO and CloudSat, J. Geophys. Res., 114, D00H06,
https://doi.org/10.1029/2009JD011916, 2009. a
Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M. (Eds.): Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp., 2013. a
Tang, G.-L., Yang, P., and Wu, D. L.: Sensitivity study of ice crystal optical properties in the 874 GHz submillimeter band, J. Quant. Spectrosc. Ra., 178, 416–421, https://doi.org/10.1016/j.jqsrt.2015.12.008, 2015. a
Waliser, D. E., Li, J.-L., Woods, C. P., Austin, R. T., Bacmeister, J., Chern, J., Del Genio, A., Jiang, J. H., Kuang, Z., Meng, H., Minnis, P., Platnick, S., Rossow, W. B., Stephens, G. L., Sun-Mack, S., Tao, W.-K., Tompkins, A. M., Vane, D. G., Walker, C., and Wu, D. L.: Cloud ice: A climate model challenge with signs and expectations of progress, J. Geophys. Res., 114, D00A21, https://doi.org/10.1029/2008JD010015, 2009.
a
Wang, C., Platnick, S., Zhang, Z., Meyer, K., Wind, G., and Yang, P.: Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 2. Retrieval evaluation, J. Geophys. Res. Atmos., 121, 5827–5845, https://doi.org/10.1002/2015JD024528, 2016. a, b, c
Wang, T., Wu, D. L., Gong, J., and Wang, C.: Long-term observations of upper-tropospheric cloud ice from MLS, J. Geophyss. Res.-Atmos., 126, e2020JD034058, https://doi.org/10.1029/2020JD034058, 2021. a
Wu, D. L. and Jiang, J. H.: EOS MLS algorithm theoretical basis for cloud measurements, NASA Jet Propulsion Lab
Report number: D-19299/CL#04-2160, available at: https://mls.jpl.nasa.gov/data/eos_cloud_atbd.pdf (last access: 11 November 2021), 2004. a
Wu, D. L., Jiang, J. H., and Davis, C. P.: EOS MLS cloud ice measurements and cloudy-sky radiative transfer model, IEEE T. Geosci. Remote, 44, 1156–1165, https://doi.org/10.1109/TGRS.2006.869994, 2006. a, b
Wu, D. L., Lambert, A., Read, W. G., Eriksson, P., and Gong, J.: MLS and CALIOP Cloud Ice Measurements in the Upper Troposphere: A Constraint from Microwave on Cloud Microphysics, J. Appl. Meteorol. Clim., 53, 157–165, https://doi.org/10.1175/JAMC-D-13-041.1, 2014. a
Wu, D. L., Piepmeier, J. R., Esper, J., Ehsan, N., Racette, P. E., Johnson, T. E., Abresch, B. S. and Bryerton, E.:
Chapter 1: IceCube: Submm-wave Technology Development for Future Science on a CubeSat, available at: https://atmospheres.gsfc.nasa.gov/uploads/images_db/IceCubeChapter-clean.pdf (last access: 11 November 2021), 2019. a, b, c, d, e, f, g
Yang, S. and Smith, E. A.: Convective–Stratiform Precipitation Variability at Seasonal Scale from 8 Yr of TRMM Observations: Implications for Multiple Modes of Diurnal Variability, J. Climate, 21, 4087–4114, https://doi.org/10.1175/2008JCLI2096.1, 2008. a
Zhang, Z. and Monosmith, B.: Dual-643 GHz and 874 GHz Airborne Radiometers for Ice Cloud Measurements, IEEE Int. Geoscience and Remote Sensing Symposium (IGARSS), Boston, MA, USA, 7–11 July 2008, 2, 1172–1175, 2008. a
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.
Launched from the International Space Station, the IceCube radiometer orbited the Earth for 15...
Altmetrics
Final-revised paper
Preprint