Articles | Volume 16, issue 1
https://doi.org/10.5194/gmd-16-47-2023
© Author(s) 2023. 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-16-47-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application
Peter J. M. Bosman
CORRESPONDING AUTHOR
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
Maarten C. Krol
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
Related authors
No articles found.
Alessandro Zanchetta, Steven van Heuven, Joram Hooghiem, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Markus Leuenberger, Peter Nyfeler, Sophia Louise Baartman, Maarten Krol, and Huilin Chen
EGUsphere, https://doi.org/10.5194/egusphere-2025-3079, https://doi.org/10.5194/egusphere-2025-3079, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
Continuous vertical profiles and discrete stratospheric samples of carbonyl sulfide (COS) were collected deploying the balloon-borne AirCore, LISA and BigLISA samplers and measured on a Quantum Cascade Laser Spectrometer (QCLS). Our measurements show good accordance with previous COS observations. Moreover, laboratory tests of ozone (O3) scrubbers proved squalene to remove O3 very efficiently without biasing the measurements of other trace gases.
Getachew Agmuas Adnew, Gerbrand Koren, Neha Mehendale, Sergey Gromov, Maarten Krol, and Thomas Röckmann
Atmos. Meas. Tech., 18, 2701–2719, https://doi.org/10.5194/amt-18-2701-2025, https://doi.org/10.5194/amt-18-2701-2025, 2025
Short summary
Short summary
This study presents high-precision measurements of ∆′17O(CO2). Key findings include the extension of the N2O–∆′17O correlation to the upper troposphere and the identification of significant differences in the N2O–∆′17O slope in StratoClim samples. Additionally, the ∆′17O measurements are used to estimate global stratospheric production and surface removal of ∆′17O, providing an independent estimate of global vegetation CO2 exchange.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
Short summary
Short summary
We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Sophie L. Baartman, Steven M. Driever, Maarten Wassenaar, Linda M. J. Kooijmans, Nerea Ubierna Lopez, Leon Mossink, Maria E. Popa, Ara Cho, Lisa Wingate, Thomas Röckmann, Steven M. A. C. van Heuven, and Maarten C. Krol
EGUsphere, https://doi.org/10.5194/egusphere-2025-215, https://doi.org/10.5194/egusphere-2025-215, 2025
Short summary
Short summary
Carbonyl sulfide (COS) and carbon dioxide (CO2) uptake fluxes and isotope discrimination was measured in sunflower and papyrus plants, using a plant chamber approach and varying light availability. COS and CO2 isotope discrimination in plants have never been jointly measured before. COS isotope discrimination did not differ between the species, nor with changing light. CO2 fluxes and isotope values provided additional useful information for data interpretation.
Alba Mols, Klaas Folkert Boersma, Hugo Denier van der Gon, and Maarten Krol
EGUsphere, https://doi.org/10.5194/egusphere-2025-49, https://doi.org/10.5194/egusphere-2025-49, 2025
Short summary
Short summary
We created a new method to estimate city air pollution (NOx emissions) using satellite data. Testing showed our approach works well to track how pollution spreads in urban areas. By combining observations with prior knowledge, we improved the accuracy of emission estimates. Applying this method in Paris, we found emissions were 9 % lower than expected and dropped significantly during COVID-19 lockdowns. Our method offers a reliable way to monitor pollution and support environmental policies.
Maarten Krol, Bart van Stratum, Isidora Anglou, and Klaas Folkert Boersma
Atmos. Chem. Phys., 24, 8243–8262, https://doi.org/10.5194/acp-24-8243-2024, https://doi.org/10.5194/acp-24-8243-2024, 2024
Short summary
Short summary
This paper presents detailed plume simulations of nitrogen oxides and carbon dioxide that are emitted from four large industrial facilities world-wide. Results from the high-resolution simulations that include atmospheric chemistry are compared to nitrogen dioxide observations from satellites. We find good performance of the model and show that common assumptions that are used in simplified models need revision. This work is important for the monitoring of emissions using satellite data.
Sandro Meier, Erik F. M. Koene, Maarten Krol, Dominik Brunner, Alexander Damm, and Gerrit Kuhlmann
Atmos. Chem. Phys., 24, 7667–7686, https://doi.org/10.5194/acp-24-7667-2024, https://doi.org/10.5194/acp-24-7667-2024, 2024
Short summary
Short summary
Nitrogen oxides (NOx = NO + NO2) are important air pollutants. This study addresses the challenge of accurately estimating NOx emissions from NO2 satellite observations. We develop a realistic model to convert NO2 to NOx by using simulated plumes from various power plants. We apply the model to satellite NO2 observations, significantly reducing biases in estimated NOx emissions. The study highlights the potential for a consistent, high-resolution estimation of NOx emissions using satellite data.
Jin Ma, Linda M. J. Kooijmans, Norbert Glatthor, Stephen A. Montzka, Marc von Hobe, Thomas Röckmann, and Maarten C. Krol
Atmos. Chem. Phys., 24, 6047–6070, https://doi.org/10.5194/acp-24-6047-2024, https://doi.org/10.5194/acp-24-6047-2024, 2024
Short summary
Short summary
The global budget of atmospheric COS can be optimised by inverse modelling using TM5-4DVAR, with the co-constraints of NOAA surface observations and MIPAS satellite data. We found reduced COS biosphere uptake from inversions and improved land and ocean separation using MIPAS satellite data assimilation. Further improvements are expected from better quantification of COS ocean and biosphere fluxes.
Farhan R. Nursanto, Roy Meinen, Rupert Holzinger, Maarten C. Krol, Xinya Liu, Ulrike Dusek, Bas Henzing, and Juliane L. Fry
Atmos. Chem. Phys., 23, 10015–10034, https://doi.org/10.5194/acp-23-10015-2023, https://doi.org/10.5194/acp-23-10015-2023, 2023
Short summary
Short summary
Particulate matter (PM) is a harmful air pollutant that depends on the complex mixture of natural and anthropogenic emissions into the atmosphere. Thus, in different regions and seasons, the way that PM is formed and grows can differ. In this study, we use a combined statistical analysis of the chemical composition and particle size distribution to determine what drives particle formation and growth across seasons, using varying wind directions to elucidate the role of different sources.
Alessandro Zanchetta, Linda M. J. Kooijmans, Steven van Heuven, Andrea Scifo, Hubertus A. Scheeren, Ivan Mammarella, Ute Karstens, Jin Ma, Maarten Krol, and Huilin Chen
Biogeosciences, 20, 3539–3553, https://doi.org/10.5194/bg-20-3539-2023, https://doi.org/10.5194/bg-20-3539-2023, 2023
Short summary
Short summary
Carbonyl sulfide (COS) has been suggested as a tool to estimate carbon dioxide (CO2) uptake by plants during photosynthesis. However, understanding its sources and sinks is critical to preventing biases in this estimate. Combining observations and models, this study proves that regional sources occasionally influence the measurements at the 60 m tall Lutjewad tower (1 m a.s.l.; 53°24′ N, 6°21′ E) in the Netherlands. Moreover, it estimates nighttime COS fluxes to be −3.0 ± 2.6 pmol m−2 s−1.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, https://doi.org/10.5194/bg-20-2573-2023, 2023
Short summary
Short summary
Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Ilse Aben, Hugo A. C. Denier van der Gon, and Maarten C. Krol
Atmos. Chem. Phys., 22, 16053–16071, https://doi.org/10.5194/acp-22-16053-2022, https://doi.org/10.5194/acp-22-16053-2022, 2022
Short summary
Short summary
Hydroxyl radical (OH) is the important chemical species that determines the lifetime of some greenhouse gases and trace gases. OH plays a vital role in air pollution chemistry. OH has a short lifetime and is extremely difficult to measure directly. OH concentrations derived from the chemistry transport model (CTM) have uncertainties of >50 %. Therefore, in this study, OH is derived indirectly using satellite date in urban plumes.
Stijn Naus, Lucas G. Domingues, Maarten Krol, Ingrid T. Luijkx, Luciana V. Gatti, John B. Miller, Emanuel Gloor, Sourish Basu, Caio Correia, Gerbrand Koren, Helen M. Worden, Johannes Flemming, Gabrielle Pétron, and Wouter Peters
Atmos. Chem. Phys., 22, 14735–14750, https://doi.org/10.5194/acp-22-14735-2022, https://doi.org/10.5194/acp-22-14735-2022, 2022
Short summary
Short summary
We assimilate MOPITT CO satellite data in the TM5-4D-Var inverse modelling framework to estimate Amazon fire CO emissions for 2003–2018. We show that fire emissions have decreased over the analysis period, coincident with a decrease in deforestation rates. However, interannual variations in fire emissions are large, and they correlate strongly with soil moisture. Our results reveal an important role for robust, top-down fire CO emissions in quantifying and attributing Amazon fire intensity.
Anja Ražnjević, Chiel van Heerwaarden, and Maarten Krol
Atmos. Meas. Tech., 15, 3611–3628, https://doi.org/10.5194/amt-15-3611-2022, https://doi.org/10.5194/amt-15-3611-2022, 2022
Short summary
Short summary
We evaluate two widely used observational techniques (Other Test Method (OTM) 33A and car drive-bys) that estimate point source gas emissions. We performed our analysis on high-resolution plume dispersion simulation. For car drive-bys we found that at least 15 repeated measurements were needed to get within 40 % of the true emissions. OTM 33A produced large errors in estimation (50 %–200 %) due to its sensitivity to dispersion coefficients and underlying simplifying assumptions.
Anja Ražnjević, Chiel van Heerwaarden, Bart van Stratum, Arjan Hensen, Ilona Velzeboer, Pim van den Bulk, and Maarten Krol
Atmos. Chem. Phys., 22, 6489–6505, https://doi.org/10.5194/acp-22-6489-2022, https://doi.org/10.5194/acp-22-6489-2022, 2022
Short summary
Short summary
Mobile measurement techniques (e.g., instruments placed in cars) are often employed to identify and quantify individual sources of greenhouse gases. Due to road restrictions, those observations are often sparse (temporally and spatially). We performed high-resolution simulations of plume dispersion, with realistic weather conditions encountered in the field, to reproduce the measurement process of a methane plume emitted from an oil well and provide additional information about the plume.
Stelios Myriokefalitakis, Elisa Bergas-Massó, María Gonçalves-Ageitos, Carlos Pérez García-Pando, Twan van Noije, Philippe Le Sager, Akinori Ito, Eleni Athanasopoulou, Athanasios Nenes, Maria Kanakidou, Maarten C. Krol, and Evangelos Gerasopoulos
Geosci. Model Dev., 15, 3079–3120, https://doi.org/10.5194/gmd-15-3079-2022, https://doi.org/10.5194/gmd-15-3079-2022, 2022
Short summary
Short summary
We here describe the implementation of atmospheric multiphase processes in the EC-Earth Earth system model. We provide global budgets of oxalate, sulfate, and iron-containing aerosols, along with an analysis of the links among atmospheric composition, aqueous-phase processes, and aerosol dissolution, supported by comparison to observations. This work is a first step towards an interactive calculation of the deposition of bioavailable atmospheric iron coupled to the model’s ocean component.
Juhi Nagori, Narcisa Nechita-Bândă, Sebastian Oscar Danielache, Masumi Shinkai, Thomas Röckmann, and Maarten Krol
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-68, https://doi.org/10.5194/acp-2022-68, 2022
Publication in ACP not foreseen
Short summary
Short summary
The sulfur isotopes (32S and 34S) were studied to understand the sources, sinks and processes of carbonyl sulphide (COS) in the atmosphere. COS is an important source of sulfur aerosol in the stratosphere (SSA). Few measurements of COS and SSA exist, but with our 1D model, we were able to match them and show the importance of COS to sulfate formation. Moreover, we are able to highlight some important processes for the COS budget and where measurements may fill a gap in current knowledge.
Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, https://doi.org/10.5194/bg-18-6547-2021, 2021
Short summary
Short summary
The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
Auke J. Visser, Laurens N. Ganzeveld, Ignacio Goded, Maarten C. Krol, Ivan Mammarella, Giovanni Manca, and K. Folkert Boersma
Atmos. Chem. Phys., 21, 18393–18411, https://doi.org/10.5194/acp-21-18393-2021, https://doi.org/10.5194/acp-21-18393-2021, 2021
Short summary
Short summary
Dry deposition is an important sink for tropospheric ozone that affects ecosystem carbon uptake, but process understanding remains incomplete. We apply a common deposition representation in atmospheric chemistry models and a multi-layer canopy model to multi-year ozone deposition observations. The multi-layer canopy model performs better on diurnal timescales compared to the common approach, leading to a substantially improved simulation of ozone deposition and vegetation ozone impact metrics.
Vilma Kangasaho, Aki Tsuruta, Leif Backman, Pyry Mäkinen, Sander Houweling, Arjo Segers, Maarten Krol, Ed Dlugokencky, Sylvia Michel, James White, and Tuula Aalto
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-843, https://doi.org/10.5194/acp-2021-843, 2021
Revised manuscript not accepted
Short summary
Short summary
Understanding the composition of carbon isotopes can help to better understand the changes in methane budgets. This study investigates how methane sources affect the seasonal cycle of the methane carbon-13 isotope during 2000–2012 using an atmospheric transport model. We found that emissions from both anthropogenic and natural sources contribute. The findings raise a need to revise the magnitudes, proportion, and seasonal cycles of anthropogenic sources and northern wetland emissions.
Johannes G. M. Barten, Laurens N. Ganzeveld, Gert-Jan Steeneveld, and Maarten C. Krol
Atmos. Chem. Phys., 21, 10229–10248, https://doi.org/10.5194/acp-21-10229-2021, https://doi.org/10.5194/acp-21-10229-2021, 2021
Short summary
Short summary
We present an evaluation of ocean and snow/ice O3 deposition in explaining observed hourly surface O3 at 25 pan-Arctic sites using an atmospheric meteorology/chemistry model. The model includes a mechanistic representation of ocean O3 deposition as a function of ocean biogeochemical and mixing conditions. The mechanistic representation agrees better with O3 observations in terms of magnitude and temporal variability especially in the High Arctic (> 70° N).
Stijn Naus, Stephen A. Montzka, Prabir K. Patra, and Maarten C. Krol
Atmos. Chem. Phys., 21, 4809–4824, https://doi.org/10.5194/acp-21-4809-2021, https://doi.org/10.5194/acp-21-4809-2021, 2021
Short summary
Short summary
Following up on previous box model studies, we employ a 3D transport model to estimate variations in the hydroxyl radical (OH) from observations of methyl chloroform (MCF). We derive small interannual OH variations that are consistent with variations in the El Niño–Southern Oscillation. We also find evidence for the release of MCF from oceans in atmospheric gradients of MCF. Both findings highlight the added value of a 3D transport model since box model studies did not identify these effects.
Jin Ma, Linda M. J. Kooijmans, Ara Cho, Stephen A. Montzka, Norbert Glatthor, John R. Worden, Le Kuai, Elliot L. Atlas, and Maarten C. Krol
Atmos. Chem. Phys., 21, 3507–3529, https://doi.org/10.5194/acp-21-3507-2021, https://doi.org/10.5194/acp-21-3507-2021, 2021
Short summary
Short summary
Carbonyl sulfide is an important trace gas in the atmosphere and useful to estimating gross primary productivity in ecosystems, but its sources and sinks remain highly uncertain. Therefore, we applied inverse model system TM5-4DVAR to better constrain the global budget. Our finding is in line with earlier studies, pointing to missing sources in the tropics and more uptake in high latitudes. We also stress the necessity of more ground-based observations and satellite data assimilation in future.
Stelios Myriokefalitakis, Nikos Daskalakis, Angelos Gkouvousis, Andreas Hilboll, Twan van Noije, Jason E. Williams, Philippe Le Sager, Vincent Huijnen, Sander Houweling, Tommi Bergman, Johann Rasmus Nüß, Mihalis Vrekoussis, Maria Kanakidou, and Maarten C. Krol
Geosci. Model Dev., 13, 5507–5548, https://doi.org/10.5194/gmd-13-5507-2020, https://doi.org/10.5194/gmd-13-5507-2020, 2020
Short summary
Short summary
This work documents and evaluates the detailed tropospheric gas-phase chemical mechanism MOGUNTIA in the three-dimensional chemistry transport model TM5-MP. The Rosenbrock solver, as generated by the KPP software, is implemented in the chemistry code, which can successfully replace the classical Euler backward integration method. The MOGUNTIA scheme satisfactorily simulates a large suite of oxygenated volatile organic compounds (VOCs) that are observed in the atmosphere at significant levels.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Henk Eskes, Ilse Aben, Hugo A. C. Denier van der Gon, Maarten C. Krol, Han Dolman, Tobias Borsdorff, and Alba Lorente
Atmos. Chem. Phys., 20, 10295–10310, https://doi.org/10.5194/acp-20-10295-2020, https://doi.org/10.5194/acp-20-10295-2020, 2020
Short summary
Short summary
Rapid urbanization has increased the consumption of fossil fuel, contributing the degradation of urban air quality. Burning efficiency is a major factor determining the impact of fuel burning on the environment. We quantify the burning efficiency of fossil fuel use over six megacities using satellite remote sensing data. City governance can use these results to understand air pollution scenarios and to formulate effective air pollution control strategies.
Cited articles
Barbaro, E., Vilà-Guerau de Arellano, J., Ouwersloot, H. G.,
Schröter, J. S., Donovan, D. P., and Krol, M. C.: Aerosols in the
convective boundary layer: Shortwave radiation effects on the coupled
land-atmosphere system, J. Geophys. Res.-Atmos., 119,
5845–5863, https://doi.org/10.1002/2013JD021237, 2014. a
Bastrikov, V., MacBean, N., Bacour, C., Santaren, D., Kuppel, S., and Peylin, P.: Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2), Geosci. Model Dev., 11, 4739–4754, https://doi.org/10.5194/gmd-11-4739-2018, 2018. a, b, c
Bergamaschi, P., Frankenberg, C., Meirink, J. F., Krol, M., Villani, M. G.,
Houweling, S., Dentener, F., Dlugokencky, E. J., Miller, J. B., Gatti, L. V.,
Engel, A., and Levin, I.: Inverse modeling of global and regional CH4
emissions using SCIAMACHY satellite retrievals, J. Geophys.
Res.-Atmos., 114, 1–28, https://doi.org/10.1029/2009JD012287, 2009. a
Bosman, P. and Krol, M.: PBosmanatm/ICLASS: ICLASS v1.1, Zenodo [code and data set],
https://doi.org/10.5281/zenodo.7239147, 2022. a
Bosveld, F., Van Meijgaard, E., Moors, E., and Werner, C.: Interpretation of
flux observations along the Cabauw 200 m meteorological tower, in: 16th
Symposium on Boundary Layers and Turbulence 6.18, 1–4, Portland, USA, https://ams.confex.com/ams/BLTAIRSE/webprogram/Paper78632.html (last access: 9 December 2022),
2004. a
Bosveld, F. C., Baas, P., Beljaars, A. C. M., Holtslag, A. A. M., de Arellano,
J. V.-G., and van de Wiel, B. J. H.: Fifty Years of Atmospheric
Boundary-Layer Research at Cabauw Serving Weather, Air Quality and Climate,
Bound.-Lay. Meteorol., 177, 583–612, https://doi.org/10.1007/s10546-020-00541-w,
2020. a, b
Casso-Torralba, P., de Arellano, J. V. G., Bosveld, F., Soler, M. R.,
Vermeulen, A., Werner, C., and Moors, E.: Diurnal and vertical variability
of the sensible heat and carbon dioxide budgets in the atmospheric surface
layer, J. Geophys. Res.-Atmos., 113, D12119,
https://doi.org/10.1029/2007JD009583, 2008. a, b, c, d, e
Chevallier, F.: Impact of correlated observation errors on inverted CO2 surface
fluxes from OCO measurements, Geophys. Res. Lett., 34, L24804,
https://doi.org/10.1029/2007GL030463, 2007. a
Chevallier, F., Fisher, M., Peylin, P., Serrar, S., Bousquet, P., Bréon,
F.-M., Chédin, A., and Ciais, P.: Inferring CO2 sources and sinks from
satellite observations: Method and application to TOVS data, J.
Geophys. Res., 110, D24309, https://doi.org/10.1029/2005JD006390, 2005. a
Chevallier, F., Bréon, F.-M., and Rayner, P. J.: Contribution of the
Orbiting Carbon Observatory to the estimation of CO2 sources and sinks:
Theoretical study in a variational data assimilation framework, J.
Geophys. Res., 112, D09307, https://doi.org/10.1029/2006JD007375, 2007. a
Chevallier, F., Ciais, P., Conway, T. J., Aalto, T., Anderson, B. E., Bousquet,
P., Brunke, E. G., Ciattaglia, L., Esaki, Y., Fröhlich, M., Gomez, A.,
Gomez-Pelaez, A. J., Haszpra, L., Krummel, P. B., Langenfelds, R. L.,
Leuenberger, M., Machida, T., Maignan, F., Matsueda, H., Morguí, J. A.,
Mukai, H., Nakazawa, T., Peylin, P., Ramonet, M., Rivier, L., Sawa, Y.,
Schmidt, M., Steele, L. P., Vay, S. A., Vermeulen, A. T., Wofsy, S., and
Worthy, D.: CO2 surface fluxes at grid point scale estimated from a global 21
year reanalysis of atmospheric measurements, J. Geophys. Res.,
115, D21307, https://doi.org/10.1029/2010JD013887, 2010. a
Commane, R., Meredith, L. K., Baker, I. T., Berry, J. A., Munger, J. W.,
Montzka, S. A., Templer, P. H., Juice, S. M., Zahniser, M. S., and Wofsy,
S. C.: Seasonal fluxes of carbonyl sulfide in a midlatitude forest,
P. Natl. Acad. Sci. USA, 112, 14162–14167,
2015. a
Doicu, A., Trautmann, T., and Schreier, F.: Numerical Regularization for
Atmospheric Inverse Problems, Springer Praxis Books in environmentral
sciences, https://doi.org/10.1007/978-3-642-05439-6, 2010. a
Drought 2018 Team and ICOS Atmosphere Thematic Centre: Drought-2018 atmospheric CO2 Mole Fraction product for 48 stations (96 sample heights), https://doi.org/10.18160/ERE9-9D85, 2020. a
Friend, A. D.: Modelling Canopy CO2 Fluxes: Are “Big-Leaf” Simplifications
Justified?, Global Ecol. Biogeogr., 10, 603–619,
2001. a
Henze, D. K., Hakami, A., and Seinfeld, J. H.: Development of the adjoint of
GEOS-Chem, Atmospheric Chemistry and Physics, 7, 2413–2433,
https://doi.org/10.5194/acp-7-2413-2007, 2007. a
Hunter, J.: Matplotlib: A 2D Graphics Environment, Comput. Sci.
Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Jarvis, P.: The interpretation of the variations in leaf water potential and
stomatal conductance found in canopies in the field, Philos.
T. Roy. Soc. Lond. B, 273,
593–610, https://doi.org/10.1098/rstb.1976.0035, 1976. a
Kaminski, T., Knorr, W., Scholze, M., Gobron, N., Pinty, B., Giering, R., and Mathieu, P.-P.: Consistent assimilation of MERIS FAPAR and atmospheric CO2 into a terrestrial vegetation model and interactive mission benefit analysis, Biogeosciences, 9, 3173–3184, https://doi.org/10.5194/bg-9-3173-2012, 2012. a
Krol, M. C., Meirink, J. F., Bergamaschi, P., Mak, J. E., Lowe, D.,
Jöckel, P., Houweling, S., and Röckmann, T.: What can 14CO
measurements tell us about OH?, Atmospheric Chemistry and Physics, 8,
5033–5044, https://doi.org/10.5194/acp-8-5033-2008, 2008. a
Liu, H., Randerson, J. T., Lindfors, J., Massman, W. J., and Foken, T.:
Consequences of incomplete surface energy balance closure for CO2 fluxes
from open-path CO2/H2O infrared gas analysers, Bound.-Lay. Meteorol.,
120, 65–85, https://doi.org/10.1007/s10546-005-9047-z, 2006. a
Ma, J., Kooijmans, L. M. J., Cho, A., Montzka, S. A., Glatthor, N., Worden, J. R., Kuai, L., Atlas, E. L., and Krol, M. C.: Inverse modelling of carbonyl sulfide: implementation, evaluation and implications for the global budget, Atmos. Chem. Phys., 21, 3507–3529, https://doi.org/10.5194/acp-21-3507-2021, 2021. a
Mäkelä, J., Knauer, J., Aurela, M., Black, A., Heimann, M., Kobayashi, H., Lohila, A., Mammarella, I., Margolis, H., Markkanen, T., Susiluoto, J., Thum, T., Viskari, T., Zaehle, S., and Aalto, T.: Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH, Geosci. Model Dev., 12, 4075–4098, https://doi.org/10.5194/gmd-12-4075-2019, 2019. a
Margulis, S. A. and Entekhabi, D.: A Coupled Land Surface–Boundary Layer
Model and Its Adjoint, J. Hydrometeorol., 2, 274–296,
https://doi.org/10.1175/1525-7541(2001)002<0274:ACLSBL>2.0.CO;2, 2001a. a
Margulis, S. A. and Entekhabi, D.: Feedback between the land surface energy
balance and atmospheric boundary layer diagnosed through a model and its
adjoint, J. Hydrometeorol., 2, 599–620,
https://doi.org/10.1175/1525-7541(2001)002<0599:FBTLSE>2.0.CO;2, 2001b. a
McNorton, J., Wilson, C., Gloor, M., Parker, R. J., Boesch, H., Feng, W., Hossaini, R., and Chipperfield, M. P.: Attribution of recent increases in atmospheric methane through 3-D inverse modelling, Atmos. Chem. Phys., 18, 18149–18168, https://doi.org/10.5194/acp-18-18149-2018, 2018. a
Meirink, J. F., Bergamaschi, P., and Krol, M. C.: Four-dimensional variational data assimilation for inverse modelling of atmospheric methane emissions: method and comparison with synthesis inversion, Atmos. Chem. Phys., 8, 6341–6353, https://doi.org/10.5194/acp-8-6341-2008, 2008. a, b
Michalak, A. M., Hirsch, A., Bruhwiler, L., Gurney, K. R., Peters, W., and
Tans, P. P.: Maximum likelihood estimation of covariance parameters for
Bayesian atmospheric trace gas surface flux inversions, J.
Geophys. Res.-Atmos., 110, D24107,
https://doi.org/10.1029/2005JD005970, 2005. a, b
Miller, S. M., Michalak, A. M., and Levi, P. J.: Atmospheric inverse modeling with known physical bounds: an example from trace gas emissions, Geosci. Model Dev., 7, 303–315, https://doi.org/10.5194/gmd-7-303-2014, 2014. a
Monin, A. and Obukhov, A.: Basic laws of turbulent mixing in the atmosphere
near the ground, Tr. Akad. Nauk SSSR Geophiz. Inst., 24, 1963–1987, 1954. a
Nash, S. G.: A survey of truncated-Newton methods, J. Comput.
Appl. Math., 124, 45–59, https://doi.org/10.1016/S0377-0427(00)00426-X,
2000. a, b
Oncley, S. P., Foken, T., Vogt, R., Kohsiek, W., DeBruin, H. A. R., Bernhofer,
C., Christen, A., van Gorsel, E., Grantz, D., Feigenwinter, C., Lehner, I.,
Liebethal, C., Liu, H., Mauder, M., Pitacco, A., Ribeiro, L., and Weidinger,
T.: The Energy Balance Experiment EBEX-2000. Part I: overview and energy
balance, Bound.-Lay. Meteorol., 123, 1–28,
https://doi.org/10.1007/s10546-007-9161-1, 2007. a, b
Ouwersloot, H. G., Vilà-Guerau de Arellano, J., Nölscher, A. C., Krol, M. C., Ganzeveld, L. N., Breitenberger, C., Mammarella, I., Williams, J., and Lelieveld, J.: Characterization of a boreal convective boundary layer and its impact on atmospheric chemistry during HUMPPA-COPEC-2010, Atmos. Chem. Phys., 12, 9335–9353, https://doi.org/10.5194/acp-12-9335-2012, 2012. a
Raoult, N. M., Jupp, T. E., Cox, P. M., and Luke, C. M.: Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0, Geosci. Model Dev., 9, 2833–2852, https://doi.org/10.5194/gmd-9-2833-2016, 2016. a, b, c
Renner, M., Brenner, C., Mallick, K., Wizemann, H.-D., Conte, L., Trebs, I., Wei, J., Wulfmeyer, V., Schulz, K., and Kleidon, A.: Using phase lags to evaluate model biases in simulating the diurnal cycle of evapotranspiration: a case study in Luxembourg, Hydrol. Earth Syst. Sci., 23, 515–535, https://doi.org/10.5194/hess-23-515-2019, 2019. a, b, c
Rödenbeck, C., Houweling, S., Gloor, M., and Heimann, M.: CO2 flux history 1982–2001 inferred from atmospheric data using a global inversion of atmospheric transport, Atmos. Chem. Phys., 3, 1919–1964, https://doi.org/10.5194/acp-3-1919-2003, 2003. a
Santaren, D., Peylin, P., Bacour, C., Ciais, P., and Longdoz, B.: Ecosystem model optimization using in situ flux observations: benefit of Monte Carlo versus variational schemes and analyses of the year-to-year model performances, Biogeosciences, 11, 7137–7158, https://doi.org/10.5194/bg-11-7137-2014, 2014. a
Schulte, R., van Zanten, M., Rutledge-Jonker, S., Swart, D., Wichink Kruit,
R., Krol, M., van Pul, W., and Vilà-Guerau de Arellano, J.:
Unraveling the diurnal atmospheric ammonia budget of a prototypical
convective boundary layer, Atmo. Environ., 249, 118153,
https://doi.org/10.1016/J.ATMOSENV.2020.118153, 2021. a
Schürmann, G. J., Kaminski, T., Köstler, C., Carvalhais, N., Voßbeck, M., Kattge, J., Giering, R., Rödenbeck, C., Heimann, M., and Zaehle, S.: Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0, Geosci. Model Dev., 9, 2999–3026, https://doi.org/10.5194/gmd-9-2999-2016, 2016. a
Stewart, J.: Modelling surface conductance of pine forest, Agr.
Forest Meteoro., 43, 19–35, https://doi.org/10.1016/0168-1923(88)90003-2, 1988. a
Stull, R. B.: An introduction to boundary layer meteorology, Kluwer Academic
Publishers, Dordrecht, https://doi.org/10.1007/978-94-009-3027-8, 1988. a, b, c
Tang, J. and Zhuang, Q.: Equifinality in parameterization of process-based
biogeochemistry models: A significant uncertainty source to the estimation of
regional carbon dynamics, J. Geophys. Res.-Biogeo.,
113, https://doi.org/10.1029/2008JG000757, 2008. a
Tarantola, A.: Inverse problem theory and methods for model parameter
estimation, in: Other Titles in Applied Mathematics, Society for Industrial and Applied Mathematics (siam),
Philadelphia, USA, https://doi.org/10.1137/1.9780898717921, 2005. a, b
The Global Monitoring Laboratory of the National Oceanic and Atmospheric Administration:
Observation Package (ObsPack) Data Products,
https://gml.noaa.gov/ccgg/obspack/,
last access: 9 December 2022. a
The Royal Netherlands Meteorological Institute (KNMI):
KNMI Data Platform,
https://dataplatform.knmi.nl/dataset/?tags=Insitu&tags=CESAR,
last access: 9 December 2022. a
The SciPy community: scipy.optimize.fmin_tnc,
https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.fmin_tnc.html, last access: 9 December 2022. a
van der Walt, S., Colbert, S., and Varoquaux, G.: The NumPy Array: A Structure
for Efficient Numerical Computation, Comput. Sci. Eng.,
13, 22–30, https://doi.org/10.1109/MCSE.2011.37, 2011. a
van Heerwaarden, C. C., Vilà-Guerau de Arellano, J., Moene, A. F., and
Holtslag, A. A. M.: Interactions between dry-air entrainment, surface
evaporation and convective boundary-layer development, Q. J.
Roy. Meteor. Soc., 135, 1277–1291, https://doi.org/10.1002/qj.431,
2009. a
van Heerwaarden, C. C., Vilà-Guerau de Arellano, J., Gounou, A.,
Guichard, F., and Couvreux, F.: Understanding the daily cycle of
evapotranspiration: A method to quantify the influence of forcings and
feedbacks, J. Hydrometeorol., 11, 1405–1422,
https://doi.org/10.1175/2010JHM1272.1, 2010. a
Vermeulen, A. T., Hensen, A., Popa, M. E., van den Bulk, W. C. M., and Jongejan, P. A. C.: Greenhouse gas observations from Cabauw Tall Tower (1992–2010), Atmos. Meas. Tech., 4, 617–644, https://doi.org/10.5194/amt-4-617-2011, 2011. a
Vesala, T., Suni, T., Rannik, Ü., Keronen, P., Markkanen, T., Sevanto,
S., Grönholm, T., Smolander, S., Kulmala, M., Ilvesniemi, H., Ojansuu,
R., Uotila, A., Levula, J., Mäkelä, A., Pumpanen, J., Kolari, P.,
Kulmala, L., Altimir, N., Berninger, F., Nikinmaa, E., and Hari, P.: Effect
of thinning on surface fluxes in a boreal forest, Global Biogeochem. Cy., 19, GB2001,
https://doi.org/10.1029/2004GB002316, 2005. a
Vilà-Guerau De Arellano, J., Van Heerwaarden, C. C., and Lelieveld,
J.: Modelled suppression of boundary-layer clouds by plants in a CO2-rich
atmosphere, Nat. Geosci., 5, 701–704, https://doi.org/10.1038/ngeo1554, 2012. a, b, c, d
Vilà-Guerau De Arellano, J., Van Heerwaarden, C. C., Van Stratum,
B. J., and Van Den Dries, K.: Atmospheric boundary layer: Integrating air
chemistry and land interactions, Cambridge University Press,
https://doi.org/10.1017/CBO9781316117422, 2015. a, b, c
Whelan, M. E., Lennartz, S. T., Gimeno, T. E., Wehr, R., Wohlfahrt, G., Wang, Y., Kooijmans, L. M. J., Hilton, T. W., Belviso, S., Peylin, P., Commane, R., Sun, W., Chen, H., Kuai, L., Mammarella, I., Maseyk, K., Berkelhammer, M., Li, K.-F., Yakir, D., Zumkehr, A., Katayama, Y., Ogée, J., Spielmann, F. M., Kitz, F., Rastogi, B., Kesselmeier, J., Marshall, J., Erkkilä, K.-M., Wingate, L., Meredith, L. K., He, W., Bunk, R., Launois, T., Vesala, T., Schmidt, J. A., Fichot, C. G., Seibt, U., Saleska, S., Saltzman, E. S., Montzka, S. A., Berry, J. A., and Campbell, J. E.: Reviews and syntheses: Carbonyl sulfide as a multi-scale tracer for carbon and water cycles, Biogeosciences, 15, 3625–3657, https://doi.org/10.5194/bg-15-3625-2018, 2018. a, b
Wouters, H., Petrova, I. Y., van Heerwaarden, C. C., Vilà-Guerau de Arellano, J., Teuling, A. J., Meulenberg, V., Santanello, J. A., and Miralles, D. G.: Atmospheric boundary layer dynamics from balloon soundings worldwide: CLASS4GL v1.0, Geosci. Model Dev., 12, 2139–2153, https://doi.org/10.5194/gmd-12-2139-2019, 2019.
a
Ye, H., You, W., Zang, Z., Pan, X., Wang, D., Zhou, N., Hu, Y., Liang, Y., and
Yan, P.: Observing system simulation experiment (OSSE)-quantitative
evaluation of lidar observation networks to improve 3D aerosol forecasting in
China, Atmo. Res., 270, 106069,
https://doi.org/10.1016/j.atmosres.2022.106069, 2022. a
Ziehn, T., Scholze, M., and Knorr, W.: On the capability of Monte Carlo and
adjoint inversion techniques to derive posterior parameter uncertainties in
terrestrial ecosystem models, Global Biogeochem. Cy., 26, GB3025,
https://doi.org/10.1029/2011GB004185, 2012. a, b
Short summary
We describe an inverse modelling framework constructed around a simple model for the atmospheric boundary layer. This framework can be fed with various observation types to study the boundary layer and land–atmosphere exchange. With this framework, it is possible to estimate model parameters and the associated uncertainties. Some of these parameters are difficult to obtain directly by observations. An example application for a grassland in the Netherlands is included.
We describe an inverse modelling framework constructed around a simple model for the atmospheric...