Articles | Volume 11, issue 4
https://doi.org/10.5194/gmd-11-1537-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-1537-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
18 Apr 2018
Model description paper |
| 18 Apr 2018
| 18 Apr 2018
ARTS, the Atmospheric Radiative Transfer Simulator – version 2.2, the planetary toolbox edition
Stefan A. Buehler
CORRESPONDING AUTHOR
Meteorologisches Institut, Centrum für Erdsystem- und
Nachhaltigkeitsforschung (CEN), Fachbereich Geowissenschaften,
Fakultät für Mathematik, Informatik und Naturwissenschaften,
Universität Hamburg, Bundesstrasse 55, 20146 Hamburg, Germany
Jana Mendrok
Department of Space, Earth and Environment, Chalmers University of
Technology, 41296 Gothenburg, Sweden
Patrick Eriksson
Department of Space, Earth and Environment, Chalmers University of
Technology, 41296 Gothenburg, Sweden
Agnès Perrin
Laboratoire de Météorologie Dynamique/IPSL, UMR CNRS 8539, Ecole
Polytechnique, Université Paris-Saclay, RD36, 91128 Palaiseau CEDEX, France
Richard Larsson
National Institute of Information and Communications
Technology, 4 Chome-2-1 Nukui Kitamachi, Koganei, Tokyo 184-0015,
Japan
Oliver Lemke
Meteorologisches Institut, Centrum für Erdsystem- und
Nachhaltigkeitsforschung (CEN), Fachbereich Geowissenschaften,
Fakultät für Mathematik, Informatik und Naturwissenschaften,
Universität Hamburg, Bundesstrasse 55, 20146 Hamburg, Germany
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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
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Simon Pfreundschuh, Patrick Eriksson, Stefan A. Buehler, Manfred Brath, David Duncan, Richard Larsson, and Robin Ekelund
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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
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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
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Jörg Burdanowitz, Stefan A. Buehler, Stephan Bakan, and Christian Klepp
Atmos. Chem. Phys., 19, 9241–9252, https://doi.org/10.5194/acp-19-9241-2019, https://doi.org/10.5194/acp-19-9241-2019, 2019
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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
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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
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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.
Martin Burgdorf, Imke Hans, Marc Prange, Theresa Lang, and Stefan A. Buehler
Atmos. Meas. Tech., 11, 4005–4014, https://doi.org/10.5194/amt-11-4005-2018, https://doi.org/10.5194/amt-11-4005-2018, 2018
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We analysed observations of the Moon with the Advanced Microwave Sounding Unit-B on the NOAA-16 satellite in order to search for bias in the sounding channels. Significant bias had been detected in the past on the basis of simultaneous nadir overpasses. With the Moon providing a quite different reference flux than the on-board calibration target and Earth scenes, radio-frequency interference emerged as the best explanation for the anomalies of channel 20 of AMSU-B on NOAA-16.
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
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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.
Imke Hans, Martin Burgdorf, Viju O. John, Jonathan Mittaz, and Stefan A. Buehler
Atmos. Meas. Tech., 10, 4927–4945, https://doi.org/10.5194/amt-10-4927-2017, https://doi.org/10.5194/amt-10-4927-2017, 2017
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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
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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.
Martin Burgdorf, Stefan A. Buehler, Theresa Lang, Simon Michel, and Imke Hans
Atmos. Meas. Tech., 9, 3467–3475, https://doi.org/10.5194/amt-9-3467-2016, https://doi.org/10.5194/amt-9-3467-2016, 2016
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The upper-tropospheric humidity is an essential climate variable, which can be measured with microwave sounders in polar orbits. A stable photometric calibration of these instruments is indispensable for detecting long-term trends. We demonstrate that this can be achieved by using the Moon in a fixed phase as a flux standard for dedicated pitch maneuver observations. This method is particularly suited for future sensors with small beamwidths.
Hélène Brogniez, Stephen English, Jean-François Mahfouf, Andreas Behrendt, Wesley Berg, Sid Boukabara, Stefan Alexander Buehler, Philippe Chambon, Antonia Gambacorta, Alan Geer, William Ingram, E. Robert Kursinski, Marco Matricardi, Tatyana A. Odintsova, Vivienne H. Payne, Peter W. Thorne, Mikhail Yu. Tretyakov, and Junhong Wang
Atmos. Meas. Tech., 9, 2207–2221, https://doi.org/10.5194/amt-9-2207-2016, https://doi.org/10.5194/amt-9-2207-2016, 2016
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Because a systematic difference between measurements of water vapor performed by space-borne observing instruments in the microwave spectral domain and their numerical modeling was recently highlighted, this work discusses and gives an overview of the various errors and uncertainties associated with each element in the comparison process. Indeed, the knowledge of absolute errors in any observation of the climate system is key, more specifically because we need to detect small changes.
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
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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. 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
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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
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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.
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
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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.
V. O. John, D. E. Parker, S. A. Buehler, J. Price, and R. W. Saunders
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-10547-2013, https://doi.org/10.5194/acpd-13-10547-2013, 2013
Revised manuscript has not been submitted
Lukas Kluft, Bjorn Stevens, Manfred Brath, and Stefan A. Buehler
EGUsphere, https://doi.org/10.5194/egusphere-2024-3829, https://doi.org/10.5194/egusphere-2024-3829, 2024
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Using a single column model, we investigate the effect of the vertical distribution of clouds on climate sensitivity. We show that, depending on their height, clouds can mask or unmask the radiative response of the clear-sky atmosphere. Our single column model yields an all-sky climate sensitivity of 2.2 K, slightly less than the clear-sky value. This value can be interpreted as a baseline to which changes in surface albedo and an assumed reduction in cloud albedo would add.
Kaah P. Menang, Stefan A. Buehler, Lukas Kluft, Robin J. Hogan, and Florian E. Roemer
EGUsphere, https://doi.org/10.5194/egusphere-2024-3051, https://doi.org/10.5194/egusphere-2024-3051, 2024
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We investigated how the uncertainty in representing water vapour continuum absorption in the shortwave affects clear-sky shortwave radiative feedback. For current surface temperature, the impact is modest (<2 %). In a warmer world, continuum induced error in estimated shortwave feedback is up to ~5 %. Using the MT_CKD model in radiative transfer calculations may lead to an underestimation of the shortwave feedback. Constraining shortwave continuum will contribute to reducing these discrepancies.
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
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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
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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
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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
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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
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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.
Marc Prange, Stefan A. Buehler, and Manfred Brath
Atmos. Chem. Phys., 23, 725–741, https://doi.org/10.5194/acp-23-725-2023, https://doi.org/10.5194/acp-23-725-2023, 2023
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We investigate the representation of elevated moist layers (EMLs) in two satellite retrieval products and ERA5 reanalysis. EMLs occur in the vicinity of tropical convective storms and are thought to have an impact on their evolution through radiative heating. We provide a first dedicated assessment of EMLs in long-term data products in terms of moist layer strength, vertical thickness and altitude by comparing to collocated radiosondes over the western Pacific, a region where EMLs often occur.
Lei Shi, Carl J. Schreck III, Viju O. John, Eui-Seok Chung, Theresa Lang, Stefan A. Buehler, and Brian J. Soden
Atmos. Meas. Tech., 15, 6949–6963, https://doi.org/10.5194/amt-15-6949-2022, https://doi.org/10.5194/amt-15-6949-2022, 2022
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Four upper tropospheric humidity (UTH) datasets derived from satellite microwave and infrared sounders are evaluated to assess their consistency as part of the activities for the Global Energy and Water Exchanges (GEWEX) water vapor assessment project. The study shows that the four datasets are consistent in the interannual temporal and spatial variability of the tropics. However, differences are found in the magnitudes of the anomalies and in the changing rates during the common period.
Simon Pfreundschuh, Ingrid Ingemarsson, Patrick Eriksson, Daniel A. Vila, and Alan J. P. Calheiros
Atmos. Meas. Tech., 15, 6907–6933, https://doi.org/10.5194/amt-15-6907-2022, https://doi.org/10.5194/amt-15-6907-2022, 2022
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We used methods from the field of artificial intelligence to train an algorithm to estimate rain from satellite observations. In contrast to other methods, our algorithm not only estimates rain, but also the uncertainty of the estimate. Using independent measurements from rain gauges, we show that our method performs better than currently available methods and that the provided uncertainty estimates are reliable. Our method makes satellite-based measurements of rain more accurate and reliable.
Prabhakar Shrestha, Jana Mendrok, and Dominik Brunner
Atmos. Chem. Phys., 22, 14095–14117, https://doi.org/10.5194/acp-22-14095-2022, https://doi.org/10.5194/acp-22-14095-2022, 2022
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The study extends the Terrestrial Systems Modeling Platform with gas-phase chemistry aerosol dynamics and a radar forward operator to enable detailed studies of aerosol–cloud–precipitation interactions. This is demonstrated using a case study of a deep convective storm, which showed that the strong updraft in the convective core of the storm produced aerosol-tower-like features, which affected the size of the hydrometeors and the simulated polarimetric features (e.g., ZDR and KDP columns).
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
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Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
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
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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
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The Global Precipitation Measurement mission is an international satellite mission providing regular global rain measurements. We present two newly developed machine-learning-based implementations of one of the algorithms responsible for turning the satellite observations into rain measurements. We show that replacing the current algorithm with a neural network improves the accuracy of the measurements. A neural network that also makes use of spatial information unlocks further improvements.
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
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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.
Theresa Mieslinger, Bjorn Stevens, Tobias Kölling, Manfred Brath, Martin Wirth, and Stefan A. Buehler
Atmos. Chem. Phys., 22, 6879–6898, https://doi.org/10.5194/acp-22-6879-2022, https://doi.org/10.5194/acp-22-6879-2022, 2022
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The trades are home to a plethora of small cumulus clouds that are often barely visible to the human eye and difficult to detect with active and passive remote sensing methods. With the help of a new method and by means of high-resolution data we can detect small and particularly thin clouds. We find that optically thin clouds are a common phenomenon in the trades, covering a large area and influencing the radiative effect of clouds if they are undetected and contaminate the cloud-free signal.
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
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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.
Prabhakar Shrestha, Jana Mendrok, Velibor Pejcic, Silke Trömel, Ulrich Blahak, and Jacob T. Carlin
Geosci. Model Dev., 15, 291–313, https://doi.org/10.5194/gmd-15-291-2022, https://doi.org/10.5194/gmd-15-291-2022, 2022
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The article focuses on the exploitation of radar polarimetry for model evaluation of stratiform precipitation. The model exhibited a low bias in simulated polarimetric moments at lower levels above the melting layer where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g. fragmentation due to ice–ice collisions) and use of more reliable snow-scattering models in the forward operator to draw valid conclusions.
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
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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.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
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The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
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
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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.
Marc Prange, Manfred Brath, and Stefan A. Buehler
Atmos. Meas. Tech., 14, 7025–7044, https://doi.org/10.5194/amt-14-7025-2021, https://doi.org/10.5194/amt-14-7025-2021, 2021
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We investigate the ability of the hyperspectral infrared satellite instrument IASI to resolve moist layers in the tropical free troposphere in a model framework. Previous observational results indicated major deficiencies of passive satellite instruments in resolving moist layers around the freezing level. We conduct a first systematic hyperspectral infrared retrieval analysis of such moist layers and conclude that no inherent satellite blind spot for moist layers exists.
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
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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.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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
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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.
Philippe Baron, Satoshi Ochiai, Eric Dupuy, Richard Larsson, Huixin Liu, Naohiro Manago, Donal Murtagh, Shin-ichiro Oyama, Hideo Sagawa, Akinori Saito, Takatoshi Sakazaki, Masato Shiotani, and Makoto Suzuki
Atmos. Meas. Tech., 13, 219–237, https://doi.org/10.5194/amt-13-219-2020, https://doi.org/10.5194/amt-13-219-2020, 2020
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Submillimeter-Wave Limb-Emission Sounder 2 (SMILES-2) is a satellite mission proposed in Japan to probe the middle and upper atmosphere (20–160 km). The key products are wind, temperature and density. If selected, this mission could provide new insights into vertical coupling in the atmosphere and could help improve weather and climate models. We conducted simulation studies to assess the measurement performances in the altitude range 60–110 km, with a special focus on the geomagnetic effects.
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
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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
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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.
Jörg Burdanowitz, Stefan A. Buehler, Stephan Bakan, and Christian Klepp
Atmos. Chem. Phys., 19, 9241–9252, https://doi.org/10.5194/acp-19-9241-2019, https://doi.org/10.5194/acp-19-9241-2019, 2019
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Sensitivity of precipitation to sea surface temperature over the ocean determines how precipitation potentially changes in a warming climate. This relationship has hardly been studied over ocean due to a lack of long-term oceanic data. Our study shows how the precipitation sensitivity depends on resolution, what process limits oceanic precipitation and how the event duration depends on temperature. This provides valuable information for future climate observations, modeling and understanding.
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
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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
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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
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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.
Richard Larsson, Yasuko Kasai, Takeshi Kuroda, Shigeru Sato, Takayoshi Yamada, Hiroyuki Maezawa, Yutaka Hasegawa, Toshiyuki Nishibori, Shinichi Nakasuka, and Paul Hartogh
Geosci. Instrum. Method. Data Syst., 7, 331–341, https://doi.org/10.5194/gi-7-331-2018, https://doi.org/10.5194/gi-7-331-2018, 2018
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We are planning a Mars mission. The mission will carry an instrument capable of measuring and mapping molecular oxygen and water in the Martian atmosphere, as well as the temperature, wind, and magnetic field. Water and oxygen are vital parts of the Martian atmospheric chemistry and must be better understood. Using computer simulation results, the paper gives a description of how the measurements will work, some problems we expect to encounter, and the sensitivity of the measurements.
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
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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
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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
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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
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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
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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
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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
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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.
Martin Burgdorf, Imke Hans, Marc Prange, Theresa Lang, and Stefan A. Buehler
Atmos. Meas. Tech., 11, 4005–4014, https://doi.org/10.5194/amt-11-4005-2018, https://doi.org/10.5194/amt-11-4005-2018, 2018
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We analysed observations of the Moon with the Advanced Microwave Sounding Unit-B on the NOAA-16 satellite in order to search for bias in the sounding channels. Significant bias had been detected in the past on the basis of simultaneous nadir overpasses. With the Moon providing a quite different reference flux than the on-board calibration target and Earth scenes, radio-frequency interference emerged as the best explanation for the anomalies of channel 20 of AMSU-B on NOAA-16.
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
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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.
Imke Hans, Martin Burgdorf, Viju O. John, Jonathan Mittaz, and Stefan A. Buehler
Atmos. Meas. Tech., 10, 4927–4945, https://doi.org/10.5194/amt-10-4927-2017, https://doi.org/10.5194/amt-10-4927-2017, 2017
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In our article we present the evolution of the noise of 11 microwave radiometers used for meteorological remote sensing. We used the Allan deviation to compute an estimate of the noise on the calibration measurements. We provide graphics as an overview to enable the users of the data to decide on the usability of the data for their purposes. Moreover, our analysis enters the production of new FCDRs (Fundamental Climate Data Records) within the FIDUCEO project.
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
Niall J. Ryan, Mathias Palm, Uwe Raffalski, Richard Larsson, Gloria Manney, Luis Millán, and Justus Notholt
Earth Syst. Sci. Data, 9, 77–89, https://doi.org/10.5194/essd-9-77-2017, https://doi.org/10.5194/essd-9-77-2017, 2017
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We present a self-consistent data set of carbon monoxide (CO) in the Arctic middle atmosphere above Kiruna, Sweden, between 2008 and 2015. The data are retrieved from measurements made by the ground-based radiometer, KIMRA, and are compared to coincident CO data measured by the satellite instrument MLS. KIMRA shows agreement with MLS over the altitude range in which KIMRA is sensitive (48–84 km) and the data show the signatures of dynamic processes such as sudden stratospheric warmings.
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
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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
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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.
Martin Burgdorf, Stefan A. Buehler, Theresa Lang, Simon Michel, and Imke Hans
Atmos. Meas. Tech., 9, 3467–3475, https://doi.org/10.5194/amt-9-3467-2016, https://doi.org/10.5194/amt-9-3467-2016, 2016
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The upper-tropospheric humidity is an essential climate variable, which can be measured with microwave sounders in polar orbits. A stable photometric calibration of these instruments is indispensable for detecting long-term trends. We demonstrate that this can be achieved by using the Moon in a fixed phase as a flux standard for dedicated pitch maneuver observations. This method is particularly suited for future sensors with small beamwidths.
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
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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.
Hélène Brogniez, Stephen English, Jean-François Mahfouf, Andreas Behrendt, Wesley Berg, Sid Boukabara, Stefan Alexander Buehler, Philippe Chambon, Antonia Gambacorta, Alan Geer, William Ingram, E. Robert Kursinski, Marco Matricardi, Tatyana A. Odintsova, Vivienne H. Payne, Peter W. Thorne, Mikhail Yu. Tretyakov, and Junhong Wang
Atmos. Meas. Tech., 9, 2207–2221, https://doi.org/10.5194/amt-9-2207-2016, https://doi.org/10.5194/amt-9-2207-2016, 2016
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Because a systematic difference between measurements of water vapor performed by space-borne observing instruments in the microwave spectral domain and their numerical modeling was recently highlighted, this work discusses and gives an overview of the various errors and uncertainties associated with each element in the comparison process. Indeed, the knowledge of absolute errors in any observation of the climate system is key, more specifically because we need to detect small changes.
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
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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
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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
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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
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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
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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
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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
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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
Y. Kasai, H. Sagawa, D. Kreyling, E. Dupuy, P. Baron, J. Mendrok, K. Suzuki, T. O. Sato, T. Nishibori, S. Mizobuchi, K. Kikuchi, T. Manabe, H. Ozeki, T. Sugita, M. Fujiwara, Y. Irimajiri, K. A. Walker, P. F. Bernath, C. Boone, G. Stiller, T. von Clarmann, J. Orphal, J. Urban, D. Murtagh, E. J. Llewellyn, D. Degenstein, A. E. Bourassa, N. D. Lloyd, L. Froidevaux, M. Birk, G. Wagner, F. Schreier, J. Xu, P. Vogt, T. Trautmann, and M. Yasui
Atmos. Meas. Tech., 6, 2311–2338, https://doi.org/10.5194/amt-6-2311-2013, https://doi.org/10.5194/amt-6-2311-2013, 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
V. O. John, D. E. Parker, S. A. Buehler, J. Price, and R. W. Saunders
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-10547-2013, https://doi.org/10.5194/acpd-13-10547-2013, 2013
Revised manuscript has not been submitted
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Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Similarity-Based Analysis of Atmospheric Organic Compounds for Machine Learning Applications
Cell tracking -based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
Improving the EnSRF in the Community Inversion Framework: a case study with ICON-ART 2024.01
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
The MESSy DWARF (based on MESSy v2.55.2)
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-145, https://doi.org/10.5194/gmd-2024-145, 2024
Revised manuscript accepted for GMD
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements in 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
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Machine learning has the potential to aid the identification organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning model in atmospheric sciences.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-99, https://doi.org/10.5194/gmd-2024-99, 2024
Revised manuscript accepted for GMD
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rainfall. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and then the model skill is evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with 4 open-source models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2197, https://doi.org/10.5194/egusphere-2024-2197, 2024
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a more efficient implementation of the serial and batch versions of the Ensemble Square Root Filter (EnSRF) algorithm in CIF.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Felipe Cifuentes, Henk Eskes, Folkert Boersma, Enrico Dammers, and Charlotte Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2225, https://doi.org/10.5194/egusphere-2024-2225, 2024
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOX emissions using synthetic NO2 satellite column retrievals derived from high-resolution model simulations. The FDA accurately reproduced NOX emissions when column observations were limited to the boundary layer and when the variability of NO2 lifetime, NOX:NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces a strong model dependency, reducing the simplicity of the original FDA formulation.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Astrid Kerkweg, Timo Kirfel, Doung H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-117, https://doi.org/10.5194/gmd-2024-117, 2024
Revised manuscript accepted for GMD
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This article introduces the MESSy DWARF. Usually, the Modular Earth Submodel System (MESSy) is linked to full dynamical models to build chemistry climate models. However, due to the modular concept of MESSy, and the newly developed DWARF component, it is now possible to create simplified models containing just one or some process descriptions. This renders very useful for technical optimisation (e.g., GPU porting) and can be used to create less complex models, e.g., a chemical box model.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
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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.
The Atmospheric Radiative Transfer Simulator (ARTS) is a public domain
software for simulating...
