Articles | Volume 15, issue 4
https://doi.org/10.5194/gmd-15-1713-2022
© Author(s) 2022. 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-15-1713-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Representing low-intensity fire sensible heat output in a mesoscale atmospheric model with a canopy submodel: a case study with ARPS-CANOPY (version 5.2.12)
Michael T. Kiefer
CORRESPONDING AUTHOR
Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI 48824, USA
Warren E. Heilman
USDA Forest Service, Northern Research Station, Lansing, MI 48910, USA
Shiyuan Zhong
Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI 48824, USA
Joseph J. Charney
USDA Forest Service, Northern Research Station, Lansing, MI 48910, USA
Xindi Bian
USDA Forest Service, Northern Research Station, Lansing, MI 48910, USA
Nicholas S. Skowronski
USDA Forest Service, Northern Research Station, Morgantown, WV 26505, USA
Kenneth L. Clark
USDA Forest Service, Northern Research Station, New Lisbon, NJ 08064, USA
Michael R. Gallagher
USDA Forest Service, Northern Research Station, New Lisbon, NJ 08064, USA
John L. Hom
USDA Forest Service, Northern Research Station, Lansing, MI 48910, USA
Matthew Patterson
USDA Forest Service, Northern Research Station, Morgantown, WV 26505, USA
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Norbert Glatthor, Thomas von Clarmann, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Gabriele P. Stiller, Bernd Funke, Maya Garcia-Comas, Manuel Lopez-Puertas, Oliver Kirner, and Michelle L. Santee
EGUsphere, https://doi.org/10.5194/egusphere-2025-3352, https://doi.org/10.5194/egusphere-2025-3352, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
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We present a global climatology of MIPAS version 8 chlorine monoxide (ClO), retrieved from spaceborne observations between 2002 and 2012. Due to an improved retrieval setup, the high bias and poor vertical resolution of upper stratospheric ClO, which had affected the previous V5 data set, has been removed. Comparisons with ClO observations of the Microwave Limb Sounder generally show good agreement. Differences can be explained by simulations with an atmospheric chemistry model.
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 17, 2849–2871, https://doi.org/10.5194/amt-17-2849-2024, https://doi.org/10.5194/amt-17-2849-2024, 2024
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Short summary
We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument on board the Environmental Satellite (Envisat) during 2002 to 2012. Monitoring of these gases is of scientific interest because both of them are strong greenhouse gases. We analyze the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Gabriele P. Stiller, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Bernd Funke, Maya García-Comas, and Manuel López-Puertas
Atmos. Meas. Tech., 17, 1759–1789, https://doi.org/10.5194/amt-17-1759-2024, https://doi.org/10.5194/amt-17-1759-2024, 2024
Short summary
Short summary
CFC-11, CFC-12, and HCFC-22 contribute to the depletion of ozone and are potent greenhouse gases. They have been banned by the Montreal protocol. With MIPAS on Envisat the atmospheric composition could be observed between 2002 and 2012. We present here the retrieval of their atmospheric distributions for the final data version 8. We characterise the derived data by their error budget and their spatial resolution. An additional representation for direct comparison to models is also provided.
Manuel López-Puertas, Maya García-Comas, Bernd Funke, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 5609–5645, https://doi.org/10.5194/amt-16-5609-2023, https://doi.org/10.5194/amt-16-5609-2023, 2023
Short summary
Short summary
This paper describes a new version (V8) of ozone data from MIPAS middle-atmosphere spectra. The dataset comprises high-quality ozone profiles from 20 to 100 km, with pole-to-pole latitude coverage for the day- and nighttime, spanning 2005 until 2012. An exhaustive treatment of errors has been performed. Compared to other satellite instruments, MIPAS ozone shows a positive bias of 5 %–8 % below 70 km. In the upper mesosphere, this new version agrees much better than previous ones (within 10 %).
Maya García-Comas, Bernd Funke, Manuel López-Puertas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Belén Martínez-Mondéjar, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 5357–5386, https://doi.org/10.5194/amt-16-5357-2023, https://doi.org/10.5194/amt-16-5357-2023, 2023
Short summary
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We have released version 8 of MIPAS IMK–IAA temperatures and pointing information retrieved from MIPAS Middle and Upper Atmosphere mode version 8.03 calibrated spectra, covering 20–115 km altitude. We considered non-local thermodynamic equilibrium emission explicitly for each limb scan, essential to retrieve accurate temperatures above the mid-mesosphere. Comparisons of this temperature dataset with SABER measurements show excellent agreement, improving those of previous MIPAS versions.
Michael Kiefer, Dale F. Hurst, Gabriele P. Stiller, Stefan Lossow, Holger Vömel, John Anderson, Faiza Azam, Jean-Loup Bertaux, Laurent Blanot, Klaus Bramstedt, John P. Burrows, Robert Damadeo, Bianca Maria Dinelli, Patrick Eriksson, Maya García-Comas, John C. Gille, Mark Hervig, Yasuko Kasai, Farahnaz Khosrawi, Donal Murtagh, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Takafumi Sugita, Thomas von Clarmann, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 16, 4589–4642, https://doi.org/10.5194/amt-16-4589-2023, https://doi.org/10.5194/amt-16-4589-2023, 2023
Short summary
Short summary
We quantify biases and drifts (and their uncertainties) between the stratospheric water vapor measurement records of 15 satellite-based instruments (SATs, with 31 different retrievals) and balloon-borne frost point hygrometers (FPs) launched at 27 globally distributed stations. These comparisons of measurements during the period 2000–2016 are made using robust, consistent statistical methods. With some exceptions, the biases and drifts determined for most SAT–FP pairs are < 10 % and < 1 % yr−1.
Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Manuel López-Puertas, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 2167–2196, https://doi.org/10.5194/amt-16-2167-2023, https://doi.org/10.5194/amt-16-2167-2023, 2023
Short summary
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New global nitric oxide (NO) volume-mixing-ratio and lower-thermospheric temperature data products, retrieved from Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) spectra with the IMK-IAA MIPAS data processor, have been released. The dataset covers the entire Envisat mission lifetime and includes retrieval results from all MIPAS observation modes. The data are based on ESA version 8 calibration and were processed using an improved retrieval approach.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Carlo Arosio, Alexei Rozanov, Mark Weber, Doug Degenstein, Adam Bourassa, Daniel Zawada, Michael Kiefer, Alexandra Laeng, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Christian Retscher, Robert Damadeo, and Jerry D. Lumpe
Atmos. Meas. Tech., 16, 1881–1899, https://doi.org/10.5194/amt-16-1881-2023, https://doi.org/10.5194/amt-16-1881-2023, 2023
Short summary
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The paper presents the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments (SAGE II, OSIRIS, MIPAS, SCIAMACHY, GOMOS, ACE-FTS, OMPS-LP, POAM III, and SAGE III/ISS). The update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP).
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 1443–1460, https://doi.org/10.5194/amt-16-1443-2023, https://doi.org/10.5194/amt-16-1443-2023, 2023
Short summary
Short summary
A new ozone data set, derived from radiation measurements of the space-borne instrument MIPAS, is presented. It consists of more than 2 million single ozone profiles from 2002–2012, covering virtually all latitudes and altitudes between 5 and 70 km. Progress in data calibration and processing methods allowed for significant improvement of the data quality, compared to previous data versions. Hence, the data set will help to better understand e.g. the time evolution of ozone in the stratosphere.
Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Bernd Funke, Michael Kiefer, Anne Kleinert, Gabriele P. Stiller, Andrea Linden, and Sylvia Kellmann
Atmos. Meas. Tech., 15, 6991–7018, https://doi.org/10.5194/amt-15-6991-2022, https://doi.org/10.5194/amt-15-6991-2022, 2022
Short summary
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Errors of profiles of temperature and mixing ratios retrieved from spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding are estimated. All known and quantified sources of uncertainty are considered. Some ongoing uncertaities contribute to both the random and to the systematic errors. In some cases, one source of uncertainty propagates onto the error budget via multiple pathways. Problems arise when the correlations of errors to be propagated are unknown.
William G. Read, Gabriele Stiller, Stefan Lossow, Michael Kiefer, Farahnaz Khosrawi, Dale Hurst, Holger Vömel, Karen Rosenlof, Bianca M. Dinelli, Piera Raspollini, Gerald E. Nedoluha, John C. Gille, Yasuko Kasai, Patrick Eriksson, Christopher E. Sioris, Kaley A. Walker, Katja Weigel, John P. Burrows, and Alexei Rozanov
Atmos. Meas. Tech., 15, 3377–3400, https://doi.org/10.5194/amt-15-3377-2022, https://doi.org/10.5194/amt-15-3377-2022, 2022
Short summary
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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.
Piera Raspollini, Enrico Arnone, Flavio Barbara, Massimo Bianchini, Bruno Carli, Simone Ceccherini, Martyn P. Chipperfield, Angelika Dehn, Stefano Della Fera, Bianca Maria Dinelli, Anu Dudhia, Jean-Marie Flaud, Marco Gai, Michael Kiefer, Manuel López-Puertas, David P. Moore, Alessandro Piro, John J. Remedios, Marco Ridolfi, Harjinder Sembhi, Luca Sgheri, and Nicola Zoppetti
Atmos. Meas. Tech., 15, 1871–1901, https://doi.org/10.5194/amt-15-1871-2022, https://doi.org/10.5194/amt-15-1871-2022, 2022
Short summary
Short summary
The MIPAS instrument onboard the ENVISAT satellite provided 10 years of measurements of the atmospheric emission al limb that allow for the retrieval of latitude- and altitude-resolved atmospheric composition. We describe the improvements implemented in the retrieval algorithm used for the full mission reanalysis, which allows for the generation of the global distributions of 21 atmospheric constituents plus temperature with increased accuracy with respect to previously generated data.
Bianca Maria Dinelli, Piera Raspollini, Marco Gai, Luca Sgheri, Marco Ridolfi, Simone Ceccherini, Flavio Barbara, Nicola Zoppetti, Elisa Castelli, Enzo Papandrea, Paolo Pettinari, Angelika Dehn, Anu Dudhia, Michael Kiefer, Alessandro Piro, Jean-Marie Flaud, Manuel López-Puertas, David Moore, John Remedios, and Massimo Bianchini
Atmos. Meas. Tech., 14, 7975–7998, https://doi.org/10.5194/amt-14-7975-2021, https://doi.org/10.5194/amt-14-7975-2021, 2021
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The level-2 v8 database from the measurements of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), aboard the European Space Agency Envisat satellite, containing atmospheric fields of pressure, temperature, and volume mixing ratio of 21 trace gases, is described in this paper. The database covers all the measurements acquired by MIPAS (from July 2002 to April 2012). The number of species included makes it of particular importance for the studies of stratospheric chemistry.
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.
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Anne Kleinert, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, Daniel R. Marsh, and Gabriele P. Stiller
Atmos. Meas. Tech., 14, 4111–4138, https://doi.org/10.5194/amt-14-4111-2021, https://doi.org/10.5194/amt-14-4111-2021, 2021
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An improved dataset of vertical temperature profiles of the Earth's atmosphere in the altitude range 5–70 km is presented. These profiles are derived from measurements of the MIPAS instrument onboard ESA's Envisat satellite. The overall improvements are based on upgrades in the input data and several improvements in the data processing approach. Both of these are discussed, and an extensive error discussion is included. Enhancements of the new dataset are demonstrated by means of examples.
Norbert Glatthor, Thomas von Clarmann, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Gabriele P. Stiller, Bernd Funke, Maya Garcia-Comas, Manuel Lopez-Puertas, Oliver Kirner, and Michelle L. Santee
EGUsphere, https://doi.org/10.5194/egusphere-2025-3352, https://doi.org/10.5194/egusphere-2025-3352, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
We present a global climatology of MIPAS version 8 chlorine monoxide (ClO), retrieved from spaceborne observations between 2002 and 2012. Due to an improved retrieval setup, the high bias and poor vertical resolution of upper stratospheric ClO, which had affected the previous V5 data set, has been removed. Comparisons with ClO observations of the Microwave Limb Sounder generally show good agreement. Differences can be explained by simulations with an atmospheric chemistry model.
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 17, 2849–2871, https://doi.org/10.5194/amt-17-2849-2024, https://doi.org/10.5194/amt-17-2849-2024, 2024
Short summary
Short summary
We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument on board the Environmental Satellite (Envisat) during 2002 to 2012. Monitoring of these gases is of scientific interest because both of them are strong greenhouse gases. We analyze the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Gabriele P. Stiller, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Bernd Funke, Maya García-Comas, and Manuel López-Puertas
Atmos. Meas. Tech., 17, 1759–1789, https://doi.org/10.5194/amt-17-1759-2024, https://doi.org/10.5194/amt-17-1759-2024, 2024
Short summary
Short summary
CFC-11, CFC-12, and HCFC-22 contribute to the depletion of ozone and are potent greenhouse gases. They have been banned by the Montreal protocol. With MIPAS on Envisat the atmospheric composition could be observed between 2002 and 2012. We present here the retrieval of their atmospheric distributions for the final data version 8. We characterise the derived data by their error budget and their spatial resolution. An additional representation for direct comparison to models is also provided.
Joseph Seitz, Shiyuan Zhong, Joseph J. Charney, Warren E. Heilman, Kenneth L. Clark, Xindi Bian, Nicholas S. Skowronski, Michael R. Gallagher, Matthew Patterson, Jason Cole, Michael T. Kiefer, Rory Hadden, and Eric Mueller
Atmos. Chem. Phys., 24, 1119–1142, https://doi.org/10.5194/acp-24-1119-2024, https://doi.org/10.5194/acp-24-1119-2024, 2024
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Atmospheric turbulence affects wildland fire behaviors and heat and smoke transfer. Turbulence data collected during an experimental fire on a 10 m x 10 m densely instrumented burn plot are analyzed, and the results reveal substantial heterogeneity in fire-induced turbulence characteristics across the small plot, which highlights the necessity for coupled atmosphere–fire behavior models to have 1–2 m grid spacing so that adequate simulations of fire behavior and smoke transfer can be achieved.
Lejiang Yu, Shiyuan Zhong, Timo Vihma, Cuijuan Sui, and Bo Sun
EGUsphere, https://doi.org/10.5194/egusphere-2023-2436, https://doi.org/10.5194/egusphere-2023-2436, 2023
Preprint archived
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In contrary to the current understanding, there can be a strong connection between ENSO and the South Atlantic Subtropical Dipole (SASD). It is highly probable that the robust inverse correlation between ENSO and SASD will persist in the future. The ENSO-SASD correlation exhibits substantial multi-decadal variability over the course of a century. The change in the ENSO-SASD relation can be linked to changes in ENSO regime and convective activities over the central South Pacific Ocean.
Manuel López-Puertas, Maya García-Comas, Bernd Funke, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 5609–5645, https://doi.org/10.5194/amt-16-5609-2023, https://doi.org/10.5194/amt-16-5609-2023, 2023
Short summary
Short summary
This paper describes a new version (V8) of ozone data from MIPAS middle-atmosphere spectra. The dataset comprises high-quality ozone profiles from 20 to 100 km, with pole-to-pole latitude coverage for the day- and nighttime, spanning 2005 until 2012. An exhaustive treatment of errors has been performed. Compared to other satellite instruments, MIPAS ozone shows a positive bias of 5 %–8 % below 70 km. In the upper mesosphere, this new version agrees much better than previous ones (within 10 %).
Maya García-Comas, Bernd Funke, Manuel López-Puertas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Belén Martínez-Mondéjar, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 5357–5386, https://doi.org/10.5194/amt-16-5357-2023, https://doi.org/10.5194/amt-16-5357-2023, 2023
Short summary
Short summary
We have released version 8 of MIPAS IMK–IAA temperatures and pointing information retrieved from MIPAS Middle and Upper Atmosphere mode version 8.03 calibrated spectra, covering 20–115 km altitude. We considered non-local thermodynamic equilibrium emission explicitly for each limb scan, essential to retrieve accurate temperatures above the mid-mesosphere. Comparisons of this temperature dataset with SABER measurements show excellent agreement, improving those of previous MIPAS versions.
Michael Kiefer, Dale F. Hurst, Gabriele P. Stiller, Stefan Lossow, Holger Vömel, John Anderson, Faiza Azam, Jean-Loup Bertaux, Laurent Blanot, Klaus Bramstedt, John P. Burrows, Robert Damadeo, Bianca Maria Dinelli, Patrick Eriksson, Maya García-Comas, John C. Gille, Mark Hervig, Yasuko Kasai, Farahnaz Khosrawi, Donal Murtagh, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Takafumi Sugita, Thomas von Clarmann, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 16, 4589–4642, https://doi.org/10.5194/amt-16-4589-2023, https://doi.org/10.5194/amt-16-4589-2023, 2023
Short summary
Short summary
We quantify biases and drifts (and their uncertainties) between the stratospheric water vapor measurement records of 15 satellite-based instruments (SATs, with 31 different retrievals) and balloon-borne frost point hygrometers (FPs) launched at 27 globally distributed stations. These comparisons of measurements during the period 2000–2016 are made using robust, consistent statistical methods. With some exceptions, the biases and drifts determined for most SAT–FP pairs are < 10 % and < 1 % yr−1.
Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Manuel López-Puertas, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 2167–2196, https://doi.org/10.5194/amt-16-2167-2023, https://doi.org/10.5194/amt-16-2167-2023, 2023
Short summary
Short summary
New global nitric oxide (NO) volume-mixing-ratio and lower-thermospheric temperature data products, retrieved from Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) spectra with the IMK-IAA MIPAS data processor, have been released. The dataset covers the entire Envisat mission lifetime and includes retrieval results from all MIPAS observation modes. The data are based on ESA version 8 calibration and were processed using an improved retrieval approach.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Carlo Arosio, Alexei Rozanov, Mark Weber, Doug Degenstein, Adam Bourassa, Daniel Zawada, Michael Kiefer, Alexandra Laeng, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Christian Retscher, Robert Damadeo, and Jerry D. Lumpe
Atmos. Meas. Tech., 16, 1881–1899, https://doi.org/10.5194/amt-16-1881-2023, https://doi.org/10.5194/amt-16-1881-2023, 2023
Short summary
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The paper presents the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments (SAGE II, OSIRIS, MIPAS, SCIAMACHY, GOMOS, ACE-FTS, OMPS-LP, POAM III, and SAGE III/ISS). The update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP).
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 1443–1460, https://doi.org/10.5194/amt-16-1443-2023, https://doi.org/10.5194/amt-16-1443-2023, 2023
Short summary
Short summary
A new ozone data set, derived from radiation measurements of the space-borne instrument MIPAS, is presented. It consists of more than 2 million single ozone profiles from 2002–2012, covering virtually all latitudes and altitudes between 5 and 70 km. Progress in data calibration and processing methods allowed for significant improvement of the data quality, compared to previous data versions. Hence, the data set will help to better understand e.g. the time evolution of ozone in the stratosphere.
Lejiang Yu, Shiyuan Zhong, Timo Vihma, Cuijuan Sui, and Bo Sun
Atmos. Chem. Phys., 23, 345–353, https://doi.org/10.5194/acp-23-345-2023, https://doi.org/10.5194/acp-23-345-2023, 2023
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Previous studies have noted a significant relationship between the Subtropical Indian Ocean Dipole and the South Atlantic Ocean Dipole indices, but little is known about the stability of their relationship. We found a significant positive correlation between the two indices prior to the year 2000 but an insignificant correlation afterwards.
Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Bernd Funke, Michael Kiefer, Anne Kleinert, Gabriele P. Stiller, Andrea Linden, and Sylvia Kellmann
Atmos. Meas. Tech., 15, 6991–7018, https://doi.org/10.5194/amt-15-6991-2022, https://doi.org/10.5194/amt-15-6991-2022, 2022
Short summary
Short summary
Errors of profiles of temperature and mixing ratios retrieved from spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding are estimated. All known and quantified sources of uncertainty are considered. Some ongoing uncertaities contribute to both the random and to the systematic errors. In some cases, one source of uncertainty propagates onto the error budget via multiple pathways. Problems arise when the correlations of errors to be propagated are unknown.
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.
Piera Raspollini, Enrico Arnone, Flavio Barbara, Massimo Bianchini, Bruno Carli, Simone Ceccherini, Martyn P. Chipperfield, Angelika Dehn, Stefano Della Fera, Bianca Maria Dinelli, Anu Dudhia, Jean-Marie Flaud, Marco Gai, Michael Kiefer, Manuel López-Puertas, David P. Moore, Alessandro Piro, John J. Remedios, Marco Ridolfi, Harjinder Sembhi, Luca Sgheri, and Nicola Zoppetti
Atmos. Meas. Tech., 15, 1871–1901, https://doi.org/10.5194/amt-15-1871-2022, https://doi.org/10.5194/amt-15-1871-2022, 2022
Short summary
Short summary
The MIPAS instrument onboard the ENVISAT satellite provided 10 years of measurements of the atmospheric emission al limb that allow for the retrieval of latitude- and altitude-resolved atmospheric composition. We describe the improvements implemented in the retrieval algorithm used for the full mission reanalysis, which allows for the generation of the global distributions of 21 atmospheric constituents plus temperature with increased accuracy with respect to previously generated data.
Bianca Maria Dinelli, Piera Raspollini, Marco Gai, Luca Sgheri, Marco Ridolfi, Simone Ceccherini, Flavio Barbara, Nicola Zoppetti, Elisa Castelli, Enzo Papandrea, Paolo Pettinari, Angelika Dehn, Anu Dudhia, Michael Kiefer, Alessandro Piro, Jean-Marie Flaud, Manuel López-Puertas, David Moore, John Remedios, and Massimo Bianchini
Atmos. Meas. Tech., 14, 7975–7998, https://doi.org/10.5194/amt-14-7975-2021, https://doi.org/10.5194/amt-14-7975-2021, 2021
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The level-2 v8 database from the measurements of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), aboard the European Space Agency Envisat satellite, containing atmospheric fields of pressure, temperature, and volume mixing ratio of 21 trace gases, is described in this paper. The database covers all the measurements acquired by MIPAS (from July 2002 to April 2012). The number of species included makes it of particular importance for the studies of stratospheric chemistry.
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.
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P. M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, https://doi.org/10.5194/essd-13-2607-2021, 2021
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Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
sapfluxnetrwill facilitate new data syntheses on the ecological factors driving water use and drought responses of trees and forests.
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Anne Kleinert, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, Daniel R. Marsh, and Gabriele P. Stiller
Atmos. Meas. Tech., 14, 4111–4138, https://doi.org/10.5194/amt-14-4111-2021, https://doi.org/10.5194/amt-14-4111-2021, 2021
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An improved dataset of vertical temperature profiles of the Earth's atmosphere in the altitude range 5–70 km is presented. These profiles are derived from measurements of the MIPAS instrument onboard ESA's Envisat satellite. The overall improvements are based on upgrades in the input data and several improvements in the data processing approach. Both of these are discussed, and an extensive error discussion is included. Enhancements of the new dataset are demonstrated by means of examples.
Lejiang Yu, Shiyuan Zhong, Cuijuan Sui, and Bo Sun
Atmos. Chem. Phys., 20, 13753–13770, https://doi.org/10.5194/acp-20-13753-2020, https://doi.org/10.5194/acp-20-13753-2020, 2020
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The recent increasing trend of "warm Arctic, cold continents" has attracted much attention, but it remains debatable as to what forces are behind this phenomenon. Sea surface temperature (SST) over the central North Pacific and the North Atlantic oceans influences the trend. On an interdecadal timescale, the recent increase in the occurrences of the warm Arctic–cold Eurasia pattern is a fragment of the interdecadal variability of SST over the Atlantic Ocean and over the central Pacific Ocean.
Cited articles
Ahmadov, R., Grell, G., James, E., Freitas, S., Pereira, G., Csiszar, I.,
Tsidulko, M., Pierce, B., McKeen, S., Peckham, S., Alexander, C., Saide, P.,
and Benjamin, S.: A High-Resolution Coupled Meteorology-Smoke Modeling System
HRRR-Smoke to Simulate Air Quality over the CONUS Domain in Real Time,
Geophys. Res. Abstr., 19, EGU2017–10841,
https://meetingorganizer.copernicus.org/EGU2017/EGU2017-10841.pdf (last access: 30 September 2021),
2017. a
Ahmadov, R., James, E., Grell, G., Alexander, C., and McKeen, S.: Operational implementation of the smoke forecasting capability in the RAP/HRRR numerical weather prediction system, EGU General Assembly 2021, online, 19–30 April 2021, EGU21-14268, https://doi.org/10.5194/egusphere-egu21-14268, 2021. a
Banerjee, T., Heilman, W., Goodrick, S., Hiers, J. K., and Linn, R.: Effects of
Canopy Midstory Management and Fuel Moisture on Wildfire Behavior, Sci. Rep.-UK, 10, 17312, https://doi.org/10.1038/s41598-020-74338-9, 2020. a
Benech, B.: Experimental Study of an Artificial Convective Plume Initiated From
the Ground., J. Appl. Meteorol. Clim., 15, 127–137,
https://doi.org/10.1175/1520-0450(1976)015<0127:ESOAAC>2.0.CO;2, 1976. a
Charney, J. J., Kiefer, M. T., Zhong, S., Heilman, W. E., Nikolic, J., Bian,
X., Hom, J. L., Clark, K. L., Skowronski, N. S., Gallagher, M. R., Patterson,
M., Liu, Y., and Hawley, C.: Assessing Forest Canopy Impacts on Smoke
Concentrations Using a Coupled Numerical Model, Atmosphere, 10, 273,
https://doi.org/10.3390/atmos10050273, 2019. a, b, c
Chou, M.-D.: Parameterization for the Absorption of Solar Radiation by O2
and CO2 with Application to Climate Studies, J. Climate, 3, 209–217,
https://doi.org/10.1175/1520-0442(1990)003<0209:PFTAOS>2.0.CO;2, 1990. a
Chou, M.-D.: A Solar Radiation Model for Use in Climate Studies, J. Atmos. Sci., 49, 762–772, https://doi.org/10.1175/1520-0469(1992)049<0762:ASRMFU>2.0.CO;2,
1992. a
Chou, M.-D. and Suarez, M. J.: An Efficient Thermal Infrared Radiation
Parameterization for use in General Circulation Models, Tech. Rep. Tech. Memo 104606, NASA, NASA Center for Aerospace Information,
800 Elkridge Landing Road, Linthicum Heights, MD 21090-2934, 1994. a
Chow, F. K., Schär, C., Ban, N., Lundquist, K. A., Schlemmer, L., and Shi,
X.: Crossing Multiple Gray Zones in the Transition from Mesoscale to
Microscale Simulation over Complex Terrain, Atmosphere, 10, 274,
https://doi.org/10.3390/atmos10050274, 2019. a, b, c
Clark, K. L., Renninger, H. J., Skowronski, N., Gallagher, M., and Schäfer,
K. V. R.: Decadal-Scale Reduction in Forest Net Ecosystem Production
Following Insect Defoliation Contrasts with Short-Term Impacts of Prescribed
Fires, Forests, 9, 145, https://doi.org/10.3390/f9030145, 2018. a
Clark, K. L., Heilman, W. E., Skowronski, N. S., Gallagher, M. R., Mueller, E.,
Hadden, R. M., and Simeoni, A.: Fire Behavior, Fuel Consumption, and
Turbulence and Energy Exchange during Prescribed Fires in Pitch Pine Forests,
Atmosphere, 11, 242, https://doi.org/10.3390/atmos11030242, 2020. a, b, c
Clark, T. L., Jenkins, M. A., Coen, J., and Packham, D. R.: A Coupled
Atmosphere-Fire Model: Convective Feedback on Fire-Line Dynamics, J. Appl. Meteorol., 35, 875–901,
https://doi.org/10.1175/1520-0450(1996)035<0875:ACAMCF>2.0.CO;2, 1996. a, b
Clark, T. L., Radke, L., Coen, J., and Middleton, D.: Analysis of Scale-Scale
Convective Dynamics in a Crown Fire Using Infrared Video Camera Imagery, J. Appl. Meteorol., 38, 1401–1420,
https://doi.org/10.1175/1520-0450(1999)038<1401:AOSSCD>2.0.CO;2, 1999. a
Clark, T. L., Coen, J., and Latham, D.: Description of a Coupled
Atmosphere-Fire Model, Int. J. Wildland Fire, 13, 49–63,
https://doi.org/10.1071/WF03043, 2004. a, b
Clements, C. B., Zhong, S., Goodrick, S., Li, J., Potter, B. E., Bian, X.,
Heilman, W. E., Charney, J. J., Perna, R., Jang, M., Lee, D., Patel, M.,
Street, S., and Aumann, G.: Observing the Dynamics of Wildland Grass Fires:
FireFlux – A Field Validation Experiment, B. Am. Meteorol. Soc.,
88, 1369–1382, https://doi.org/10.1175/BAMS-88-9-1369, 2007. a
Clements, C. B., Kochanski, A. K., Seto, D., Davis, B., Camacho, C., Lareau,
N. P., Contezac, J., Restaino, J., Heilman, W. E., Krueger, S. K., Butler,
B., Ottmar, R. D., Vihnanek, R., Flynn, J., Filippi, J.-B., Barboni, T.,
Hall, D. E., Mandel, J., Jenkins, M. A., O'Brien, J., Hornsby, B., and
Teske, C.: The FireFlux II Experiment: A Model-Guided Field Experiment to
Improve Understanding of Fire–Atmosphere Interactions and Fire Spread, Int.
J. Wildland Fire, 28, 308–326, https://doi.org/10.1071/WF18089, 2019. a
Coen, J., Mahalingam, S., and Daily, J.: Infrared Imagery of Crown-Fire
Dynamics during FROSTFIRE, J. Appl. Meteorol., 43, 1241–1259,
https://doi.org/10.1175/1520-0450(2004)043<1241:IIOCDD>2.0.CO;2, 2004. a
Coen, J. L.: Simulation of the Big Elk Fire Using Coupled Atmosphere-Fire
Modeling, Int. J. Wildland Fire, 14, 49–59, https://doi.org/10.1071/WF04047, 2005. a
Coen, J. L.: Some Requirements for Simulating Wildland Fire Behavior Using
Insight from Coupled Weather–Wildland Fire Models, Fire, 1, 6,
https://doi.org/10.3390/fire1010006, 2018. a, b, c
Dupont, S. and Brunet, Y.: Influence of Foliar Density Profile on Canopy Flow:
A Large-Eddy Simulation Study, Agric. For. Meteorol., 148, 976–990,
https://doi.org/10.1016/j.agrformet.2008.01.014, 2008. a, b
Filippi, J.-B., Pialat, X., and Clements, C. B.: Assessment of
ForeFire/Meso-NH for Wildland Fire/Atmosphere Coupled Simulation of the
FireFlux Experiment, Proc. Combust. Inst., 34, 2633–2640,
https://doi.org/10.1016/j.proci.2012.07.022, 2013. a, b, c
Heilman, W. E. and Fast, J. D.: Simulations of Horizontal Roll Vortex
Development Above Lines of Extreme Surface Heating, Int. J. Wildland Fire, 2,
55–68, https://doi.org/10.1071/WF9920055, 1992. a, b
Heilman, W. E., Clements, C. B., Seto, D., Bian, X., Clark, K. L., Skowronski,
N. S., and Hom, J. L.: Observations of Fire-Induced Turbulence Regimes During
Low-Intensity Wildland Fires in Forested Environments: Implications for
Smoke Dispersion, Atmos. Sci. Lett., 16, 453–460, https://doi.org/10.1002/asl.581,
2015. a, b, c, d, e, f
Heilman, W. E., Clark, K. L., Bian, X., Charney, J. J., Zhong, S., Skowronski,
N. S., Gallagher, M. R., and Patterson, M.: Turbulent Momentum Flux Behavior
above a Fire Front in an Open-Canopied Forest, Atmosphere, 12, 956,
https://doi.org/10.3390/atmos12080956, 2021. a, b, c
Hiers, J. K., Ottmar, R., Butler, B. W., Clements, C., Vihnanek, R., Dickinson,
M. B., and O'Brien, J.: An Overview of the Prescribed Fire Combustion and
Atmospheric Dynamics Research Experiment (Rx-CADRE), in: 4th International
Fire Ecology and Management Congress: Fire as a Global Process, 30 November–5 December 2009, Savannah, GA, USA, edited by:
Rideout-Hanzak, S., https://doi.org/10.4996/fireecology.0701001, 2009. a, b
Hiers, J. K., O'Brien, J. J., Varner, J. M., Butler, B. W., Dickinson, M.,
Furman, J., Gallagher, M., Godwin, D., Goodrick, S. L., Hood, S. M., Hudak,
A., Kobziar, L. N., Linn, R., Loudermilk, E. L., McCaffrey, S., Robertson,
K., Rowell, E. M., Skowronski, N., Watts, A. C., and Yedinak, K. M.:
Prescribed Fire Science: The Case for a Refined Research Agenda, Fire Ecol.,
16, 11, https://doi.org/10.1186/s42408-020-0070-8, 2020. a
Hoffman, C. M., Linn, R., Parsons, R., Sieg, C., and Winterkamp, J.: Modeling
Spatial and Temporal Dynamics of Wind Flow and Potential Fire Behavior
Following a Mountain Pine Beetle Outbreak in a Lodgepole Pine Forest, Agric. For. Meteorol., 204, 79–93, https://doi.org/10.1016/j.agrformet.2015.01.018, 2015. a
Jenkins, M. A., Clark, T., and Coen, J.: Coupling Atmospheric and Fire Models,
in: Forest Fire: Behavior and Ecological Effects, edited by: Johnson, E. A.
and Miyanishi, K., 1st edn., Academic Press, 257–302, ISBN 978-0-12-386660-8, 2001. a
Kartsios, S., Karacostas, T. S., Pytharoulis, I., and Dimitrakopoulos, A. P.:
The Role of Heat Extinction Depth Concept to Fire Behavior: An Application
to WRF-SFIRE Model, in: Perspectives on Atmospheric Sciences, edited by:
Karacostas, T., Bais, A., and Nastos, P. T., 1st edn., Springer
International Publishing, 137–142, ISBN 978-3-319-35094-3, 2017. a, b, c
Kavanagh, K., Dickinson, M. B., and Bova, A. S.: A Way Forward for Fire-Caused
Tree Mortality Prediction: Modeling a Physiological Consequence of Fire,
Fire Ecol., 6, 80–94, https://doi.org/10.4996/fireecology.0601080, 2010. a
Kiefer, M. T., Lin, Y.-L., and Charney, J. J.: A Study of Two-Dimensional Dry
Convective Plume Modes with Variable Critical Level Height, J. Atmos. Sci.,
65, 448–469, https://doi.org/10.1175/2007JAS2301.1, 2008. a, b, c
Kiefer, M. T., Parker, M. D., and Charney, J. J.: Regimes of Dry Convection
Above Wildfires: Idealized Numerical Simulations and Dimensional Analysis,
J. Atmos. Sci., 66, 806–836, https://doi.org/10.1175/2008JAS2896.1, 2009. a, b
Kiefer, M. T., Parker, M. D., and Charney, J. J.: Regimes of Dry Convection
Above Wildfires: Sensitivity to Fireline Details, J. Atmos. Sci., 67,
611–632, https://doi.org/10.1175/2009JAS3226.1, 2010. a, b
Kiefer, M. T., Heilman, W. E., Zhong, S., Charney, J. J., Bian, X., Skowronski,
N. S., Hom, J. L., Clark, K. L., Patterson, M., and Gallagher, M. R.:
Multiscale Simulation of a Prescribed Fire Event in the New Jersey Pine
Barrens using ARPS-CANOPY, J. Appl. Meteorol. Clim., 53, 793–812,
https://doi.org/10.1175/JAMC-D-13-0131.1, 2014. a, b, c, d, e, f, g, h, i, j, k, l, m, n
Kiefer, M. T., Heilman, W. E., Zhong, S., Charney, J. J., and Bian, X.: Mean
and Turbulent Flow Downstream of a Low-Intensity Fire: Influence of Canopy
and Background Atmospheric Conditions, J. Appl. Meteorol. Clim., 54,
42–57, https://doi.org/10.1175/JAMC-D-14-0058.1, 2015. a, b
Kiefer, M. T., Heilman, W. E., Zhong, S., Charney, J. J., and Bian, X.: A study of the influence of forest gaps on fire–atmosphere interactions, Atmos. Chem. Phys., 16, 8499–8509, https://doi.org/10.5194/acp-16-8499-2016, 2016. a, b
Kiefer, M. T., Zhong, S., Heilman, W. E., Charney, J. J., and Bian, X.: A
Numerical Study of Atmospheric Perturbations Induced by Heat From a Wildland
Fire: Sensitivity to Vertical Canopy Structure and Heat Source Strength,
J. Geophys. Res., 123, 2555–2572, https://doi.org/10.1002/2017JD027904, 2018. a, b, c
Kiefer, M. T., Heilman, W. E., Zhong, S., Charney, J. J., Bian, X., Skowronski,
N. S., Clark, K. L., Gallagher, M. R., Hom, J. L., and Patterson, M.:
Representing Low-Intensity Fire Sensible Heat Output in a Mesoscale
Atmospheric Model with a Canopy Submodel: A Case Study with ARPS-CANOPY
(version 5.2.12), V1, Harvard Dataverse [data set],
https://doi.org/10.7910/DVN/JJCPND, 2021. a
Kochanski, A. K., Jenkins, M. A., Mandel, J., Beezley, J. D., Clements, C. B., and Krueger, S.: Evaluation of WRF-SFIRE performance with field observations from the FireFlux experiment, Geosci. Model Dev., 6, 1109–1126, https://doi.org/10.5194/gmd-6-1109-2013, 2013. a
Kochanski, A. K., Jenkins, M. A., Yedinak, K., Mandel, J., Beezley, J., and
Lamb, B.: Toward an Integrated System for Fire, Smoke and Air Quality
Simulations, Int. J. Wildland Fire, 25, 534–546, https://doi.org/10.1071/WF14074,
2016. a
Kochanski, A. K., Fournier, A., and Mandel, J.: Experimental Design of a
Prescribed Burn Instrumentation, Atmosphere, 9, 296,
https://doi.org/10.3390/atmos9080296, 2018. a, b, c, d
Kremens, R. L., Dickinson, M. B., and Bova, A. S.: Radiant Flux Density, Energy
Density and Fuel Consumption in Mixed-Oak Forest Surface Fires, Int. J.
Wildland Fire, 21, 722–730, https://doi.org/10.1071/WF10143, 2012. a
Linn, R., Reisner, J., Colman, J. J., and Winterkamp, J.: Studying Wildfire
Behavior Using FIRETEC, Int. J. Wildland Fire, 11, 233–246,
https://doi.org/10.1071/WF02007, 2002. a
Linn, R. R., Winterkamp, J. L., Furman, J. H., Williams, B., Hiers, J. K.,
Jonko, A., O'Brien, J. J., Yedinak, K. M., and Goodrick, S.: Modeling Low
Intensity Fires: Lessons Learned from 2012 RxCADRE, Atmosphere, 12, 139,
https://doi.org/10.3390/atmos12020139, 2021. a
Luderer, G., Trentmann, J., Winterrath, T., Textor, C., Herzog, M., Graf, H. F., and Andreae, M. O.: Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part II): sensitivity studies, Atmos. Chem. Phys., 6, 5261–5277, https://doi.org/10.5194/acp-6-5261-2006, 2006. a
Luderer, G., Trentmann, J., and O, A. M.: A New Look at the Role of
Fire-Released Moisture on the Dynamics of Atmospheric Pyro-Convection, Int.
J. Wildland Fire, 18, 554–562, https://doi.org/10.1071/WF07035, 2009. a
Mandel, J., Beezley, J. D., and Kochanski, A. K.: Coupled atmosphere-wildland fire modeling with WRF 3.3 and SFIRE 2011, Geosci. Model Dev., 4, 591–610, https://doi.org/10.5194/gmd-4-591-2011, 2011. a, b
Melvin, M. A.: 2018 National Prescribed Fire Use Survey Report, Tech. Rep.
Tech. Rep. 03-18, Coalition of Prescribed Fire Councils Inc.,
https://www.stateforesters.org/wp-content/uploads/2018/12/2018-Prescribed-Fire-Use-Survey-Report-1.pdf
(last access: 30 September 2021), 2018. a
Melvin, M. A.: 2020 National Prescribed Fire Use Report, Tech. Rep. Tech. Bull. 04-20, Coalition of Prescribed Fire Councils Inc.,
https://www.stateforesters.org/wp-content/uploads/2020/12/2020-Prescribed-Fire-Use-Report.pdf
(last access: 30 September 2021), 2020. a
Michioka, T. and Chow, F. K.: High-Resolution Large-Eddy Simulations of Scalar
Transport in Atmospheric Boundary Layer Flow over Complex Terrain, J. Appl. Meteorol. Clim., 47, 3150–3169, https://doi.org/10.1175/2008JAMC1941.1, 2008. a, b
National Interagency Fire Center: Prescribed Fire and Acres by Agency,
https://www.nifc.gov/fire-information/statistics/prescribed-fire
(last access: 30 September 2021), 2019. a
Noilhan, J. and Planton, S.: A Simple Parameterization of Land Surface
Processes for Meteorological Models, Mon. Weather Rev., 117, 536–549,
https://doi.org/10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2, 1989. a
Parker, M. D. and Johnson, R. H.: Structures and Dynamics of Quasi–2D
Mesoscale Convective Systems, J. Atmos. Sci., 61, 545–567,
https://doi.org/10.1175/1520-0469(2004)061<0545:SADOQM>2.0.CO;2, 2004. a
Peace, M., Mattner, T., Mills, G., Kepert, J., and McCaw, L.: Coupled
Fire–Atmosphere Simulations of the Rocky River Fire Using WRF-SFIRE, J. Appl. Meteorol. Clim., 55, 1151–1168, https://doi.org/10.1175/JAMC-D-15-0157.1,
2016. a
Pfeiffer, H. G. and Liebhafsky, H. A.: The Origins of Beer's Law, J. Chem. Educ., 28, 123–125, https://doi.org/10.1021/ed028p123, 1959. a
Pimont, F., Dupuy, J. L., Linn, R. R., and Dupont, S.: Impacts of Tree Canopy
Structure on Wind Flows and Fire Propagation Simulated with FIRETEC, Ann. For. Sci., 68, 523–530, https://doi.org/10.1007/s13595-011-0061-7, 2011. a, b
Pleim, J. E. and Xiu, A.: Development and Testing of a Surface Flux and
Planetary Boundary Layer Model for Application in Mesoscale Models, J. Appl. Meteorol., 34, 16–32,
https://www.jstor.org/stable/26187192 (last access: 30 September 2021), 1995. a
Powers, J. G., Klemp, J. B., Skamarock, W. C., Davis, C. A., Dudhia, J., Gill,
D. O., Coen, J. L., Gochis, D. J., Ahmadov, R., Peckham, S. E., Grell, G. A.,
Michalakes, J., Trahan, S., Benjamin, S. G., Alexander, C. R., Dimego, G. J.,
Wang, W., Schwartz, C. S., Romine, G. S., Liu, Z., Snyder, C., Chen, F.,
Barlage, M. J., Yu, W., and Duda, M. G.: The Weather Research and
Forecasting Model: Overview, System Efforts, and Future Directions,
B. Am. Meteorol. Soc., 98, 1717–1737, https://doi.org/10.1175/BAMS-D-15-00308.1,
2017. a, b
Rogers, E., DiMego, G., Black, T., Ek, M., Ferrier, B., Gayno, G., Janjic, Z.,
Lin, Y., Pyle, M., Wong, V., and Wan-Shu, W.: The NCEP North American
Mesoscale Modeling System: Recent Changes and Future Plans, in: 23rd Conf.
on Weather Analysis and Forecasting / 19th Conf. on Numerical Weather
Prediction, p. 2A.4, Am. Meteorol. Soc., Omaha, NE,
http://ams.confex.com/ams/pdfpapers/154114.pdf (last access: 30 September 2021)],
2009. a
Skowronski, N. S., Clark, K. L., Duveneck, M., and Hom, J.: Three-Dimensional
Canopy Fuel Loading Predicted Using Upward and Downward Sensing LiDAR
Systems, Remote Sens. Environ., 115, 703–714,
https://doi.org/10.1016/j.rse.2010.10.012, 2011. a
Skowronski, N. S., Gallagher, M. R., and Warner, T. A.: Decomposing the
Interactions between Fire Severity and Canopy Fuel Structure Using
Multi-Temporal, Active, and Passive Remote Sensing Approaches, Fire, 3, 7,
https://doi.org/10.3390/fire3010007, 2020. a, b
Sun, W.-Y. and Chang, C.-Z.: Diffusion Model for a Convective Layer: Part
I: Numerical Simulation of Convective Boundary Layer, J. Clim. Appl. Meteorol., 25, 1445–1453,
https://doi.org/10.1175/1520-0450(1986)025<1445:DMFACL>2.0.CO;2, 1986. a
Trentmann, J., Luderer, G., Winterrath, T., Fromm, M. D., Servranckx, R., Textor, C., Herzog, M., Graf, H.-F., and Andreae, M. O.: Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part I): reference simulation, Atmos. Chem. Phys., 6, 5247–5260, https://doi.org/10.5194/acp-6-5247-2006, 2006. a, b
Wang, J.-W. A., Sardeshmukh, P. D., Compo, G. P., Whitaker, J. S., Slivinski,
L. C., McColl, C. M., and Pegion, P. J.: Sensitivities of the NCEP Global
Forecast System, Mon. Weather Rev., 147, 1237–1256,
https://doi.org/10.1175/MWR-D-18-0239.1, 2019. a
Warner, T. A., Skowronski, N. S., and La Puma, I.: The Influence of Prescribed
Burning and Wildfire on Lidar-Estimated Forest Structure of the New Jersey
Pinelands National Reserve, Int. J. Wildland Fire, 29, 1100–1108,
https://doi.org/10.1071/WF20037, 2020. a, b
Weigel, A. P.: Ensemble Forecasts, in: Forecast Verification: A Practitioner's
Guide in Atmospheric Science, 2nd edn., edited by: Jolliffe, I. T. and Stephenson,
D. B., John Wiley & Sons, 141–166, ISBN 978-0-470-66071-3, 2011. a
Wilczak, J. M., Oncley, S. P., and Stage, S. A.: Sonic Anemometer Tilt
Correction Algorithms, Bound.-Lay. Meteorol., 99, 127–150,
https://doi.org/10.1023/A:1018966204465, 2001. a
Willmott, C. J.: On the validation of models, Phys. Geo., 2, 184–194,
https://doi.org/10.1080/02723646.1981.10642213, 1981. a, b
Wyngaard, J. C.: Toward Numerical Modeling in the “Terra Incognita”, J. Atmos. Sci., 61, 1816–1826,
https://doi.org/10.1175/1520-0469(2004)061<1816:TNMITT>2.0.CO;2, 2004. a
Xue, M., Droegemeier, K. K., and Wong, V.: The Advanced Regional
Prediction System (ARPS) – A Multi-Scale Nonhydrostatic Atmosphere
Simulation and Prediction Model. Part I: Model Dynamics and Verification,
Meteorol. Atmos. Phys., 75, 463–485, https://doi.org/10.1007/s007030070003, 2000. a, b, c, d
Xue, M., Droegemeier, K. K., Wong, V., Shapiro, A., Brewster, K., Carr, F.,
Weber, D., Liu, Y., and Wang, D.: The Advanced Regional Prediction
System (ARPS) – A Multi-Scale Nonhydrostatic Atmosphere Simulation and
Prediction Tool. Part II: Model Physics and Applications, Meteorol. Atmos. Phys., 76, 143–165, https://doi.org/10.1007/s007030170027, 2001. a, b
Short summary
We examine methods used to represent wildland fire sensible heat release in atmospheric models. A set of simulations are evaluated using observations from a low-intensity prescribed fire in the New Jersey Pine Barrens. The comparison is motivated by the need for guidance regarding the representation of low-intensity fire sensible heating in atmospheric models. Such fires are prevalent during prescribed fire operations and can impact the health and safety of fire personnel and the public.
We examine methods used to represent wildland fire sensible heat release in atmospheric models....