Articles | Volume 6, issue 4
Geosci. Model Dev., 6, 1243–1259, 2013
https://doi.org/10.5194/gmd-6-1243-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue: Coupled chemistry–meteorology modelling: status and...
Geosci. Model Dev., 6, 1243–1259, 2013
https://doi.org/10.5194/gmd-6-1243-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper 22 Aug 2013
Model description paper | 22 Aug 2013
Coupling between the JULES land-surface scheme and the CCATT-BRAMS atmospheric chemistry model (JULES-CCATT-BRAMS1.0): applications to numerical weather forecasting and the CO2 budget in South America
D. S. Moreira et al.
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Demerval S. Moreira, Karla M. Longo, Saulo R. Freitas, Marcia A. Yamasoe, Lina M. Mercado, Nilton E. Rosário, Emauel Gloor, Rosane S. M. Viana, John B. Miller, Luciana V. Gatti, Kenia T. Wiedemann, Lucas K. G. Domingues, and Caio C. S. Correia
Atmos. Chem. Phys., 17, 14785–14810, https://doi.org/10.5194/acp-17-14785-2017, https://doi.org/10.5194/acp-17-14785-2017, 2017
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Fire in the Amazon forest produces a large amount of smoke that is released into the atmosphere and covers a large portion of South America for about 3 months each year. The smoke affects the energy and CO2 budgets. Using a numerical atmospheric model, we demonstrated that the smoke changes the forest from a source to a sink of CO2 to the atmosphere. The smoke ultimately acts to at least partially compensate for the forest carbon lost due to fire emissions.
Saulo R. Freitas, Jairo Panetta, Karla M. Longo, Luiz F. Rodrigues, Demerval S. Moreira, Nilton E. Rosário, Pedro L. Silva Dias, Maria A. F. Silva Dias, Enio P. Souza, Edmilson D. Freitas, Marcos Longo, Ariane Frassoni, Alvaro L. Fazenda, Cláudio M. Santos e Silva, Cláudio A. B. Pavani, Denis Eiras, Daniela A. França, Daniel Massaru, Fernanda B. Silva, Fernando C. Santos, Gabriel Pereira, Gláuber Camponogara, Gonzalo A. Ferrada, Haroldo F. Campos Velho, Isilda Menezes, Julliana L. Freire, Marcelo F. Alonso, Madeleine S. Gácita, Maurício Zarzur, Rafael M. Fonseca, Rafael S. Lima, Ricardo A. Siqueira, Rodrigo Braz, Simone Tomita, Valter Oliveira, and Leila D. Martins
Geosci. Model Dev., 10, 189–222, https://doi.org/10.5194/gmd-10-189-2017, https://doi.org/10.5194/gmd-10-189-2017, 2017
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We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) where different previous versions for weather, chemistry, and the carbon cycle were unified in a single harmonized software system. This version also has a new set of state-of-the-art physical parametrizations and higher computational parallel and memory usage efficiency. BRAMS has been applied for research and operational weather and air quality forecasting, largely in South America.
M. M. Bela, K. M. Longo, S. R. Freitas, D. S. Moreira, V. Beck, S. C. Wofsy, C. Gerbig, K. Wiedemann, M. O. Andreae, and P. Artaxo
Atmos. Chem. Phys., 15, 757–782, https://doi.org/10.5194/acp-15-757-2015, https://doi.org/10.5194/acp-15-757-2015, 2015
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In the Amazon Basin, gases that lead to the formation of ozone (O3), an air pollutant and greenhouse gas, are emitted from fire, urban and biogenic sources. This study presents the first basin wide aircraft measurements of O3 during the dry-to-wet and wet-to-dry transition seasons, which show extremely low values above undisturbed forest and increases from fires. This work also demonstrates the capabilities and limitations of regional atmospheric chemistry models in representing O3 in Amazonia.
J. R. Rozante, D. S. Moreira, R. C. M. Godoy, and A. A. Fernandes
Geosci. Model Dev., 7, 2333–2343, https://doi.org/10.5194/gmd-7-2333-2014, https://doi.org/10.5194/gmd-7-2333-2014, 2014
K. M. Longo, S. R. Freitas, M. Pirre, V. Marécal, L. F. Rodrigues, J. Panetta, M. F. Alonso, N. E. Rosário, D. S. Moreira, M. S. Gácita, J. Arteta, R. Fonseca, R. Stockler, D. M. Katsurayama, A. Fazenda, and M. Bela
Geosci. Model Dev., 6, 1389–1405, https://doi.org/10.5194/gmd-6-1389-2013, https://doi.org/10.5194/gmd-6-1389-2013, 2013
Chris Wilson, Martyn P. Chipperfield, Manuel Gloor, Robert J. Parker, Hartmut Boesch, Joey McNorton, Luciana V. Gatti, John B. Miller, Luana S. Basso, and Sarah A. Monks
Atmos. Chem. Phys., 21, 10643–10669, https://doi.org/10.5194/acp-21-10643-2021, https://doi.org/10.5194/acp-21-10643-2021, 2021
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Methane (CH4) is an important greenhouse gas emitted from wetlands like those found in the basin of the Amazon River. Using an atmospheric model and observations from GOSAT, we quantified CH4 emissions from Amazonia during the previous decade. We found that the largest emissions came from a region in the eastern basin and that emissions there were rising faster than in other areas of South America. This finding was supported by CH4 observations made on aircraft within the basin.
Chandan Sarangi, Tirthankar Chakraborty, Sachchidanand Tripathi, Mithun Krishnan, Ross Morrison, Jonathan Evans, and Lina Mercado
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-40, https://doi.org/10.5194/acp-2021-40, 2021
Preprint under review for ACP
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Generally, transpiration fluxes by vegetation are reduced under heat stress to conserve water. However, in-situ observations over North India shows that, the strength of the inverse association between transpiration and atmospheric vapor pressure deficit is seen to be weakening in presence of heavy aerosol loading. This finding not only implicates the significant role of aerosols on modifying the evaporative fraction, but also warrant in-depth analysis of aerosol-plant-temperature-EF continuum.
Marcia Akemi Yamasoe, Nilton Manuel Évora Rosário, Samantha Novaes Santos Martins Almeida, and Martin Wild
Atmos. Chem. Phys., 21, 6593–6603, https://doi.org/10.5194/acp-21-6593-2021, https://doi.org/10.5194/acp-21-6593-2021, 2021
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Spatio-temporal disparity to assess global dimming and brightening phenomena has been a critical topic. For instance, few studies addressed surface solar irradiation (SSR) long-term trend in South America. In this study, SSR, sunshine duration (SD) and the diurnal temperature range (DTR) are analysed for São Paulo, Brazil. We found a dimming phase, identified by SSR, SD and DTR, extending till 1983. Then, while SSR is still declining, consistent with cloud increasing, SD and DTR are increasing.
Jessica C. A. Baker, Luis Garcia-Carreras, Manuel Gloor, John H. Marsham, Wolfgang Buermann, Humberto R. da Rocha, Antonio D. Nobre, Alessandro Carioca de Araujo, and Dominick V. Spracklen
Hydrol. Earth Syst. Sci., 25, 2279–2300, https://doi.org/10.5194/hess-25-2279-2021, https://doi.org/10.5194/hess-25-2279-2021, 2021
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Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to measure over large areas. In this study, we compare spatial patterns, seasonality, and recent trends in Amazon ET from a water-budget analysis with estimates from satellites, reanalysis, and global climate models. We find large differences between products, showing that many widely used datasets and climate models may not provide a reliable representation of this crucial variable over the Amazon.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
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On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Dipayan Paul, Hubertus A. Scheeren, Henk G. Jansen, Bert A. M. Kers, John B. Miller, Andrew M. Crotwell, Sylvia E. Michel, Luciana V. Gatti, Lucas G. Domingues, Caio S. C. Correia, Raiane A. L. Neves, Harro A. J. Meijer, and Wouter Peters
Atmos. Meas. Tech., 13, 4051–4064, https://doi.org/10.5194/amt-13-4051-2020, https://doi.org/10.5194/amt-13-4051-2020, 2020
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For reliable measurements of CO2 mole fractions and its stable isotope composition in air samples, one needs to carefully dry them during collection. Here we describe evaluation of a portable, consumable-free and power-free Nafion-based drying system that is currently being used for sample collection over the Amazon. Laboratory tests indicate that this Nafion-based system does not influence the mole fraction measurements of CH4, CO, N2O, SF6, and CO2 and the stable isotope composition of CO2.
Saulo R. Freitas, Georg A. Grell, and Haiqin Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-38, https://doi.org/10.5194/gmd-2020-38, 2020
Preprint under review for GMD
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Convection Parameterization is a component of atmospheric models aiming to represent the statistical effects of sub-grid scale convective clouds. Because the atmosphere contains circulations with a broad spectrum of scales, the truncation needed to run models in computers requires the introduction of parameterizations to account for processes that are not explicitly resolved. We detail recent developments in the Grell-Freitas CP, which has been applied in several regional and global models.
Renato Kerches Braghiere, Marcia Akemi Yamasoe, Nilton Manuel Évora do Rosário, Humberto Ribeiro da Rocha, José de Souza Nogueira, and Alessandro Carioca de Araújo
Atmos. Chem. Phys., 20, 3439–3458, https://doi.org/10.5194/acp-20-3439-2020, https://doi.org/10.5194/acp-20-3439-2020, 2020
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We evaluate how the interaction of smoke with sun light impacts the exchange of energy and mass between vegetation and the atmosphere using a machine learning technique. We found an effect of the smoke on CO2, energy, and water fluxes, linking the effects of smoke with temperature, humidity, and winds. CO2 exchange increased by up to 55 % in the presence of smoke. A decrease of 12 % was observed for a site with simpler vegetation. Energy fluxes were negatively impacted for all study sites.
Karina E. Williams, Anna B. Harper, Chris Huntingford, Lina M. Mercado, Camilla T. Mathison, Pete D. Falloon, Peter M. Cox, and Joon Kim
Geosci. Model Dev., 12, 3207–3240, https://doi.org/10.5194/gmd-12-3207-2019, https://doi.org/10.5194/gmd-12-3207-2019, 2019
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Data from the First ISLSCP Field Experiment, 1987–1989, is used to assess how well the JULES land-surface model simulates water stress in tallgrass prairie vegetation. We find that JULES simulates a decrease in key carbon and water cycle variables during the dry period, as expected, but that it does not capture the shape of the diurnal cycle on these days. These results will be used to inform future model development as part of wider evaluation efforts.
Richard Coppell, Emanuel Gloor, and Joseph Holden
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-51, https://doi.org/10.5194/gmd-2019-51, 2019
Preprint under review for GMD
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(1) We developed a new Sphagnum model for ecosystem exchange. (2) The model is implemented in TRIFFID which is part of the JULES land surface model. (3) Outputs compare well to empirical field data. (4) JULES can now better incorporate peatland-climate feedbacks.
Florent F. Malavelle, Jim M. Haywood, Lina M. Mercado, Gerd A. Folberth, Nicolas Bellouin, Stephen Sitch, and Paulo Artaxo
Atmos. Chem. Phys., 19, 1301–1326, https://doi.org/10.5194/acp-19-1301-2019, https://doi.org/10.5194/acp-19-1301-2019, 2019
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Diffuse light can increase the efficiency of vegetation photosynthesis. Diffuse light results from scattering by either clouds or aerosols in the atmosphere. During the dry season biomass burning (BB) on the edges of the Amazon rainforest contributes significantly to the aerosol burden over the entire region. We show that despite a modest effect of change in light conditions, the overall impact of BB aerosols on the vegetation is still important when indirect climate feedbacks are considered.
Joe McNorton, Chris Wilson, Manuel Gloor, Rob J. Parker, Hartmut Boesch, Wuhu Feng, Ryan Hossaini, and Martyn P. Chipperfield
Atmos. Chem. Phys., 18, 18149–18168, https://doi.org/10.5194/acp-18-18149-2018, https://doi.org/10.5194/acp-18-18149-2018, 2018
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Since 2007 atmospheric methane (CH4) has been unexpectedly increasing following a 6-year hiatus. We have used an atmospheric model to attribute regional sources and global sinks of CH4 using observations for the 2003–2015 period. Model results show the renewed growth is best explained by decreased atmospheric removal, decreased biomass burning emissions, and an increased energy sector (mainly from Africa–Middle East and Southern Asia–Oceania) and wetland emissions (mainly from northern Eurasia).
Chris Huntingford, Rebecca J. Oliver, Lina M. Mercado, and Stephen Sitch
Biogeosciences, 15, 5415–5422, https://doi.org/10.5194/bg-15-5415-2018, https://doi.org/10.5194/bg-15-5415-2018, 2018
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Raised ozone levels impact plant stomatal opening and thus photosynthesis. Most models describe this as a suppression of stomata opening. Field evidence suggests more complexity, as ozone damage may make stomatal response
sluggish. In some circumstances, this causes stomata to be more open – a concern during drought conditions – by increasing transpiration. To guide interpretation and modelling of field measurements, we present an equation for sluggish effects, via a single tau parameter.
Fernando Santos, Karla Longo, Alex Guenther, Saewung Kim, Dasa Gu, Dave Oram, Grant Forster, James Lee, James Hopkins, Joel Brito, and Saulo Freitas
Atmos. Chem. Phys., 18, 12715–12734, https://doi.org/10.5194/acp-18-12715-2018, https://doi.org/10.5194/acp-18-12715-2018, 2018
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We investigated the impact of biomass burning on the chemical composition of trace gases in the Amazon. The findings corroborate the influence of biomass burning activity not only on direct emissions of particulate matter but also on the oxidative capacity to produce secondary organic aerosol. The scientists plan to use this information to improve the numerical model simulation with a better representativeness of the chemical processes, which can impact on global climate prediction.
Paul I. Palmer, Simon O'Doherty, Grant Allen, Keith Bower, Hartmut Bösch, Martyn P. Chipperfield, Sarah Connors, Sandip Dhomse, Liang Feng, Douglas P. Finch, Martin W. Gallagher, Emanuel Gloor, Siegfried Gonzi, Neil R. P. Harris, Carole Helfter, Neil Humpage, Brian Kerridge, Diane Knappett, Roderic L. Jones, Michael Le Breton, Mark F. Lunt, Alistair J. Manning, Stephan Matthiesen, Jennifer B. A. Muller, Neil Mullinger, Eiko Nemitz, Sebastian O'Shea, Robert J. Parker, Carl J. Percival, Joseph Pitt, Stuart N. Riddick, Matthew Rigby, Harjinder Sembhi, Richard Siddans, Robert L. Skelton, Paul Smith, Hannah Sonderfeld, Kieran Stanley, Ann R. Stavert, Angelina Wenger, Emily White, Christopher Wilson, and Dickon Young
Atmos. Chem. Phys., 18, 11753–11777, https://doi.org/10.5194/acp-18-11753-2018, https://doi.org/10.5194/acp-18-11753-2018, 2018
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This paper provides an overview of the Greenhouse gAs Uk and Global Emissions (GAUGE) experiment. GAUGE was designed to quantify nationwide GHG emissions of the UK, bringing together measurements and atmospheric transport models. This novel experiment is the first of its kind. We anticipate it will inform the blueprint for countries that are building a measurement infrastructure in preparation for global stocktakes, which are a key part of the Paris Agreement.
Rebecca J. Oliver, Lina M. Mercado, Stephen Sitch, David Simpson, Belinda E. Medlyn, Yan-Shih Lin, and Gerd A. Folberth
Biogeosciences, 15, 4245–4269, https://doi.org/10.5194/bg-15-4245-2018, https://doi.org/10.5194/bg-15-4245-2018, 2018
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Potential gains in terrestrial carbon sequestration over Europe from elevated CO2 can be partially offset by concurrent rises in tropospheric O3. The land surface model JULES was run in a factorial suite of experiments showing that by 2050 simulated GPP was reduced by 4 to 9 % due to plant O3 damage. Large regional variations exist with larger impacts identified for temperate compared to boreal regions. Plant O3 damage was greatest over the twentieth century and declined into the future.
Anna B. Harper, Andrew J. Wiltshire, Peter M. Cox, Pierre Friedlingstein, Chris D. Jones, Lina M. Mercado, Stephen Sitch, Karina Williams, and Carolina Duran-Rojas
Geosci. Model Dev., 11, 2857–2873, https://doi.org/10.5194/gmd-11-2857-2018, https://doi.org/10.5194/gmd-11-2857-2018, 2018
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Dynamic global vegetation models are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES is a DGVM that represents the land surface in the UK Earth System Model. We compared simulated gross and net primary productivity of vegetation, vegetation distribution, and aspects of the transient carbon cycle to observational datasets. JULES was able to accurately reproduce many aspects of the terrestrial carbon cycle with the recent improvements.
Paulo R. Teixeira, Saulo R. de Freitas, Francis W. Correia, and Antonio O. Manzi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-81, https://doi.org/10.5194/gmd-2018-81, 2018
Publication in GMD not foreseen
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Emissions of gases and particulates in urban areas are associated with a mixture of various sources, both natural and anthropogenic. Understanding and quantifying these emissions is necessary in studies of climate change, local air pollution issues, and weather modification. This work will also contribute to improved air quality numerical simulations, provide more accurate scenarios for policymakers and regulatory agencies to develop strategies for controlling the vehicular emissions.
Przemyslaw Zelazowski, Chris Huntingford, Lina M. Mercado, and Nathalie Schaller
Geosci. Model Dev., 11, 541–560, https://doi.org/10.5194/gmd-11-541-2018, https://doi.org/10.5194/gmd-11-541-2018, 2018
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This paper describes the calibration of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) impact modelling system against 22 global climate models (GCMs) in the CMIP3 database.
IMOGEN uses "pattern scaling" to emulate GCMs, and with such linearity enables projections to be made for alternative future scenarios of atmospheric greenhouse gas concentrations. It is also coupled to the JULES land surface model, to allow impact assessments.
IMOGEN uses "pattern scaling" to emulate GCMs, and with such linearity enables projections to be made for alternative future scenarios of atmospheric greenhouse gas concentrations. It is also coupled to the JULES land surface model, to allow impact assessments.
Demerval S. Moreira, Karla M. Longo, Saulo R. Freitas, Marcia A. Yamasoe, Lina M. Mercado, Nilton E. Rosário, Emauel Gloor, Rosane S. M. Viana, John B. Miller, Luciana V. Gatti, Kenia T. Wiedemann, Lucas K. G. Domingues, and Caio C. S. Correia
Atmos. Chem. Phys., 17, 14785–14810, https://doi.org/10.5194/acp-17-14785-2017, https://doi.org/10.5194/acp-17-14785-2017, 2017
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Fire in the Amazon forest produces a large amount of smoke that is released into the atmosphere and covers a large portion of South America for about 3 months each year. The smoke affects the energy and CO2 budgets. Using a numerical atmospheric model, we demonstrated that the smoke changes the forest from a source to a sink of CO2 to the atmosphere. The smoke ultimately acts to at least partially compensate for the forest carbon lost due to fire emissions.
Liang Feng, Paul I. Palmer, Hartmut Bösch, Robert J. Parker, Alex J. Webb, Caio S. C. Correia, Nicholas M. Deutscher, Lucas G. Domingues, Dietrich G. Feist, Luciana V. Gatti, Emanuel Gloor, Frank Hase, Rigel Kivi, Yi Liu, John B. Miller, Isamu Morino, Ralf Sussmann, Kimberly Strong, Osamu Uchino, Jing Wang, and Andreas Zahn
Atmos. Chem. Phys., 17, 4781–4797, https://doi.org/10.5194/acp-17-4781-2017, https://doi.org/10.5194/acp-17-4781-2017, 2017
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We use the GEOS-Chem global 3-D model of atmospheric chemistry and transport and an ensemble Kalman filter to simultaneously infer regional fluxes of methane (CH4) and carbon dioxide (CO2) directly from GOSAT retrievals of XCH4:XCO2, using sparse ground-based CH4 and CO2 mole fraction data to anchor the ratio. Our results show that assimilation of GOSAT data significantly reduced the posterior uncertainty and changed the a priori spatial distribution of CH4 emissions.
Joana A. Rizzolo, Cybelli G. G. Barbosa, Guilherme C. Borillo, Ana F. L. Godoi, Rodrigo A. F. Souza, Rita V. Andreoli, Antônio O. Manzi, Marta O. Sá, Eliane G. Alves, Christopher Pöhlker, Isabella H. Angelis, Florian Ditas, Jorge Saturno, Daniel Moran-Zuloaga, Luciana V. Rizzo, Nilton E. Rosário, Theotonio Pauliquevis, Rosa M. N. Santos, Carlos I. Yamamoto, Meinrat O. Andreae, Paulo Artaxo, Philip E. Taylor, and Ricardo H. M. Godoi
Atmos. Chem. Phys., 17, 2673–2687, https://doi.org/10.5194/acp-17-2673-2017, https://doi.org/10.5194/acp-17-2673-2017, 2017
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Particles collected from the air above the Amazon Basin during the wet season were identified as Saharan dust. Soluble minerals were analysed to assess the bioavailability of iron. Dust deposited onto the canopy and topsoil can likely benefit organisms such as fungi and lichens. The ongoing deposition of Saharan dust across the Amazon rainforest provides an iron-rich source of essential macronutrients and micronutrients to plant roots, and also directly to plant leaves during the wet season.
Madeleine Sánchez Gácita, Karla M. Longo, Julliana L. M. Freire, Saulo R. Freitas, and Scot T. Martin
Atmos. Chem. Phys., 17, 2373–2392, https://doi.org/10.5194/acp-17-2373-2017, https://doi.org/10.5194/acp-17-2373-2017, 2017
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This study uses an adiabatic cloud model to simulate the activation of smoke aerosol particles in the Amazon region as cloud condensation nuclei (CCN). The relative importance of variability in hygroscopicity, mixing state, and activation kinetics for the activated fraction and maximum supersaturation is assessed. Our findings on uncertainties and sensitivities provide guidance on appropriate simplifications that can be used for modeling of smoke aerosols within general circulation models.
Saulo R. Freitas, Jairo Panetta, Karla M. Longo, Luiz F. Rodrigues, Demerval S. Moreira, Nilton E. Rosário, Pedro L. Silva Dias, Maria A. F. Silva Dias, Enio P. Souza, Edmilson D. Freitas, Marcos Longo, Ariane Frassoni, Alvaro L. Fazenda, Cláudio M. Santos e Silva, Cláudio A. B. Pavani, Denis Eiras, Daniela A. França, Daniel Massaru, Fernanda B. Silva, Fernando C. Santos, Gabriel Pereira, Gláuber Camponogara, Gonzalo A. Ferrada, Haroldo F. Campos Velho, Isilda Menezes, Julliana L. Freire, Marcelo F. Alonso, Madeleine S. Gácita, Maurício Zarzur, Rafael M. Fonseca, Rafael S. Lima, Ricardo A. Siqueira, Rodrigo Braz, Simone Tomita, Valter Oliveira, and Leila D. Martins
Geosci. Model Dev., 10, 189–222, https://doi.org/10.5194/gmd-10-189-2017, https://doi.org/10.5194/gmd-10-189-2017, 2017
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We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) where different previous versions for weather, chemistry, and the carbon cycle were unified in a single harmonized software system. This version also has a new set of state-of-the-art physical parametrizations and higher computational parallel and memory usage efficiency. BRAMS has been applied for research and operational weather and air quality forecasting, largely in South America.
Ben T. Johnson, James M. Haywood, Justin M. Langridge, Eoghan Darbyshire, William T. Morgan, Kate Szpek, Jennifer K. Brooke, Franco Marenco, Hugh Coe, Paulo Artaxo, Karla M. Longo, Jane P. Mulcahy, Graham W. Mann, Mohit Dalvi, and Nicolas Bellouin
Atmos. Chem. Phys., 16, 14657–14685, https://doi.org/10.5194/acp-16-14657-2016, https://doi.org/10.5194/acp-16-14657-2016, 2016
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Biomass burning is a large source of carbonaceous aerosols, which scatter and absorb solar radiation, and modify cloud properties. We evaluate the simulation of biomass burning aerosol processes and properties in the HadGEM3 climate model using observations, including those from the South American Biomass Burning Analysis. We find that modelled aerosol optical depths are underestimated unless aerosol emissions (Global Fire Emission Database v3) are increased by a factor of 1.6–2.0.
Bradley O. Christoffersen, Manuel Gloor, Sophie Fauset, Nikolaos M. Fyllas, David R. Galbraith, Timothy R. Baker, Bart Kruijt, Lucy Rowland, Rosie A. Fisher, Oliver J. Binks, Sanna Sevanto, Chonggang Xu, Steven Jansen, Brendan Choat, Maurizio Mencuccini, Nate G. McDowell, and Patrick Meir
Geosci. Model Dev., 9, 4227–4255, https://doi.org/10.5194/gmd-9-4227-2016, https://doi.org/10.5194/gmd-9-4227-2016, 2016
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We developed a plant hydraulics model for tropical forests based on established plant physiological theory, and parameterized it by conducting a pantropical hydraulic trait survey. We show that a substantial amount of trait diversity can be represented in the model by a reduced set of trait dimensions. The fully parameterized model is able capture tree-level variation in water status and improves simulations of total ecosystem transpiration, showing how to incorporate hydraulic traits in models.
M. N. Deeter, S. Martínez-Alonso, L. V. Gatti, M. Gloor, J. B. Miller, L. G. Domingues, and C. S. C. Correia
Atmos. Meas. Tech., 9, 3999–4012, https://doi.org/10.5194/amt-9-3999-2016, https://doi.org/10.5194/amt-9-3999-2016, 2016
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Satellite methods allow biomass burning emissions to be accurately quantified with high spatial and temporal resolution. With that ultimate goal, we analyze satellite retrievals of carbon monoxide from the MOPITT instrument over the Amazon Basin. Validation results for four Amazonian sites indicate a significant negative bias in retrieved lower-tropospheric CO concentrations. The interannual variability of biomass burning emissions from 2000 to 2015 is also studied using the MOPITT record.
Carolin Walter, Saulo R. Freitas, Christoph Kottmeier, Isabel Kraut, Daniel Rieger, Heike Vogel, and Bernhard Vogel
Atmos. Chem. Phys., 16, 9201–9219, https://doi.org/10.5194/acp-16-9201-2016, https://doi.org/10.5194/acp-16-9201-2016, 2016
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Buoyancy produced by vegetation fires can lead to substantial plume rise with consequences for the dispersion of aerosol emitted by the fires. To study this effect a 1-D plume rise model was included into the regional online integrated model system COSMO-ART. Comparing model results and satellite data for a case study of 2010 Canadian wildfires shows, that the plume rise model outperforms prescribed emission height. The radiative impact of the aerosol leads to a pronounced temperature change.
Anna B. Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Mercado, Margriet Groenendijk, Eddy Robertson, Jens Kattge, Gerhard Bönisch, Owen K. Atkin, Michael Bahn, Johannes Cornelissen, Ülo Niinemets, Vladimir Onipchenko, Josep Peñuelas, Lourens Poorter, Peter B. Reich, Nadjeda A. Soudzilovskaia, and Peter van Bodegom
Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, https://doi.org/10.5194/gmd-9-2415-2016, 2016
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Dynamic global vegetation models (DGVMs) are used to predict the response of vegetation to climate change. We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base. The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.
Gabriel Pereira, Ricardo Siqueira, Nilton E. Rosário, Karla L. Longo, Saulo R. Freitas, Francielle S. Cardozo, Johannes W. Kaiser, and Martin J. Wooster
Atmos. Chem. Phys., 16, 6961–6975, https://doi.org/10.5194/acp-16-6961-2016, https://doi.org/10.5194/acp-16-6961-2016, 2016
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Fires associated with land use and land cover changes release large amounts of aerosols and trace gases into the atmosphere. Although several inventories of biomass burning emissions cover Brazil, there are still considerable uncertainties and differences among them. However, results indicate that emission derived via similar methods tend to agree with one other, but aerosol emissions from fires with particularly high biomass consumption still lead to an underestimation.
Sudhanshu Pandey, Sander Houweling, Maarten Krol, Ilse Aben, Frédéric Chevallier, Edward J. Dlugokencky, Luciana V. Gatti, Emanuel Gloor, John B. Miller, Rob Detmers, Toshinobu Machida, and Thomas Röckmann
Atmos. Chem. Phys., 16, 5043–5062, https://doi.org/10.5194/acp-16-5043-2016, https://doi.org/10.5194/acp-16-5043-2016, 2016
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This study investigates the constraint provided by measurements of Xratio (XCH4/XCO2) from space on surface fluxes of CH4 and CO2. We apply the ratio inversion method described in Pandey et al. (2015) to Xratio retrievals from the GOSAT with the TM5-4DVAR inverse modeling system, to constrain the surface fluxes of CH4 and CO2 for 2009 and 2010. The results are compared to proxy CH4 inversions using model-derived-XCO2 mixing ratios from CarbonTracker and MACC.
R. Paugam, M. Wooster, S. Freitas, and M. Val Martin
Atmos. Chem. Phys., 16, 907–925, https://doi.org/10.5194/acp-16-907-2016, https://doi.org/10.5194/acp-16-907-2016, 2016
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Landscape fire plume height controls fire emissions release in the atmosphere, in particular their transport that may also affect the longevity, chemical conversion, and fate of the plumes chemical constituents. Here, we review how such landscape-scale fire smoke plume injection heights are represented in large-scale atmospheric transport models aiming to represent the impacts of wildfire emissions on component of the Earth system.
L. Molina, G. Broquet, P. Imbach, F. Chevallier, B. Poulter, D. Bonal, B. Burban, M. Ramonet, L. V. Gatti, S. C. Wofsy, J. W. Munger, E. Dlugokencky, and P. Ciais
Atmos. Chem. Phys., 15, 8423–8438, https://doi.org/10.5194/acp-15-8423-2015, https://doi.org/10.5194/acp-15-8423-2015, 2015
R. Paugam, M. Wooster, J. Atherton, S. R. Freitas, M. G. Schultz, and J. W. Kaiser
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-9815-2015, https://doi.org/10.5194/acpd-15-9815-2015, 2015
Revised manuscript not accepted
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The transport of Biomass Burning emissions in Chemical Transport Model rely on parametrization of plumes injection height. Using fire observation selected to ensure match-up of fire-atmosphere-plume dynamics; a popular plume rise model was improved and optimized. The resulting model shows response to the effect of atmospheric stability consistent with previous findings and is able to predict higher injection height than any other tested parametrizations, giving a closer match with observation.
S. Archer-Nicholls, D. Lowe, E. Darbyshire, W. T. Morgan, M. M. Bela, G. Pereira, J. Trembath, J. W. Kaiser, K. M. Longo, S. R. Freitas, H. Coe, and G. McFiggans
Geosci. Model Dev., 8, 549–577, https://doi.org/10.5194/gmd-8-549-2015, https://doi.org/10.5194/gmd-8-549-2015, 2015
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The regional WRF-Chem model was used to study aerosol particles from biomass burning in South America. The modelled estimates of fire plume injection heights were found to be too high, with serious implications for modelled aerosol vertical distribution, transport and impacts on local climate. A modified emission scenario was developed which improved the predicted injection height. Model results were compared and evaluated against in situ measurements from the 2012 SAMBBA flight campaign.
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
M. M. Bela, K. M. Longo, S. R. Freitas, D. S. Moreira, V. Beck, S. C. Wofsy, C. Gerbig, K. Wiedemann, M. O. Andreae, and P. Artaxo
Atmos. Chem. Phys., 15, 757–782, https://doi.org/10.5194/acp-15-757-2015, https://doi.org/10.5194/acp-15-757-2015, 2015
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In the Amazon Basin, gases that lead to the formation of ozone (O3), an air pollutant and greenhouse gas, are emitted from fire, urban and biogenic sources. This study presents the first basin wide aircraft measurements of O3 during the dry-to-wet and wet-to-dry transition seasons, which show extremely low values above undisturbed forest and increases from fires. This work also demonstrates the capabilities and limitations of regional atmospheric chemistry models in representing O3 in Amazonia.
M. O. Johnson, M. Gloor, M. J. Kirkby, and J. Lloyd
Biogeosciences, 11, 6873–6894, https://doi.org/10.5194/bg-11-6873-2014, https://doi.org/10.5194/bg-11-6873-2014, 2014
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We present a soil evolution model which incorporates the major processes of pedogenesis: mineral weathering, leaching, erosion, bioturbation, nutrient cycling and organic carbon inputs. We compare the modelled soil properties with soil chronosequences from Hawaii and demonstrate that the model captures well the key components of soil development. The model also highlights the important role that vegetation plays in accelerating the weathering and the release of globally important nutrients.
J. Brito, L. V. Rizzo, W. T. Morgan, H. Coe, B. Johnson, J. Haywood, K. Longo, S. Freitas, M. O. Andreae, and P. Artaxo
Atmos. Chem. Phys., 14, 12069–12083, https://doi.org/10.5194/acp-14-12069-2014, https://doi.org/10.5194/acp-14-12069-2014, 2014
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This paper details the physical--chemical characteristics of aerosols in a region strongly impacted by biomass burning in the western part of the Brazilian Amazon region. For such, a large suite of state-of-the-art instruments for realtime analysis was deployed at a ground site. Among the key findings, we observe the strong prevalence of organic aerosols associated to fire emissions, with important climate effects, and indications of its very fast processing in the atmosphere.
C. Wilson, M. P. Chipperfield, M. Gloor, and F. Chevallier
Geosci. Model Dev., 7, 2485–2500, https://doi.org/10.5194/gmd-7-2485-2014, https://doi.org/10.5194/gmd-7-2485-2014, 2014
J. R. Rozante, D. S. Moreira, R. C. M. Godoy, and A. A. Fernandes
Geosci. Model Dev., 7, 2333–2343, https://doi.org/10.5194/gmd-7-2333-2014, https://doi.org/10.5194/gmd-7-2333-2014, 2014
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
N. M. Fyllas, E. Gloor, L. M. Mercado, S. Sitch, C. A. Quesada, T. F. Domingues, D. R. Galbraith, A. Torre-Lezama, E. Vilanova, H. Ramírez-Angulo, N. Higuchi, D. A. Neill, M. Silveira, L. Ferreira, G. A. Aymard C., Y. Malhi, O. L. Phillips, and J. Lloyd
Geosci. Model Dev., 7, 1251–1269, https://doi.org/10.5194/gmd-7-1251-2014, https://doi.org/10.5194/gmd-7-1251-2014, 2014
M. R. Raupach, M. Gloor, J. L. Sarmiento, J. G. Canadell, T. L. Frölicher, T. Gasser, R. A. Houghton, C. Le Quéré, and C. M. Trudinger
Biogeosciences, 11, 3453–3475, https://doi.org/10.5194/bg-11-3453-2014, https://doi.org/10.5194/bg-11-3453-2014, 2014
G. A. Grell and S. R. Freitas
Atmos. Chem. Phys., 14, 5233–5250, https://doi.org/10.5194/acp-14-5233-2014, https://doi.org/10.5194/acp-14-5233-2014, 2014
B. W. LaFranchi, G. Pétron, J. B. Miller, S. J. Lehman, A. E. Andrews, E. J. Dlugokencky, B. Hall, B. R. Miller, S. A. Montzka, W. Neff, P. C. Novelli, C. Sweeney, J. C. Turnbull, D. E. Wolfe, P. P. Tans, K. R. Gurney, and T. P. Guilderson
Atmos. Chem. Phys., 13, 11101–11120, https://doi.org/10.5194/acp-13-11101-2013, https://doi.org/10.5194/acp-13-11101-2013, 2013
R. Locatelli, P. Bousquet, F. Chevallier, A. Fortems-Cheney, S. Szopa, M. Saunois, A. Agusti-Panareda, D. Bergmann, H. Bian, P. Cameron-Smith, M. P. Chipperfield, E. Gloor, S. Houweling, S. R. Kawa, M. Krol, P. K. Patra, R. G. Prinn, M. Rigby, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 9917–9937, https://doi.org/10.5194/acp-13-9917-2013, https://doi.org/10.5194/acp-13-9917-2013, 2013
A. F. dos Santos, S. R. Freitas, J. G. Z. de Mattos, H. F. de Campos Velho, M. A. Gan, E. F. P. da Luz, and G. A. Grell
Adv. Geosci., 35, 123–136, https://doi.org/10.5194/adgeo-35-123-2013, https://doi.org/10.5194/adgeo-35-123-2013, 2013
K. M. Longo, S. R. Freitas, M. Pirre, V. Marécal, L. F. Rodrigues, J. Panetta, M. F. Alonso, N. E. Rosário, D. S. Moreira, M. S. Gácita, J. Arteta, R. Fonseca, R. Stockler, D. M. Katsurayama, A. Fazenda, and M. Bela
Geosci. Model Dev., 6, 1389–1405, https://doi.org/10.5194/gmd-6-1389-2013, https://doi.org/10.5194/gmd-6-1389-2013, 2013
V. Beck, C. Gerbig, T. Koch, M. M. Bela, K. M. Longo, S. R. Freitas, J. O. Kaplan, C. Prigent, P. Bergamaschi, and M. Heimann
Atmos. Chem. Phys., 13, 7961–7982, https://doi.org/10.5194/acp-13-7961-2013, https://doi.org/10.5194/acp-13-7961-2013, 2013
M. Stuefer, S. R. Freitas, G. Grell, P. Webley, S. Peckham, S. A. McKeen, and S. D. Egan
Geosci. Model Dev., 6, 457–468, https://doi.org/10.5194/gmd-6-457-2013, https://doi.org/10.5194/gmd-6-457-2013, 2013
N. E. Rosário, K. M. Longo, S. R. Freitas, M. A. Yamasoe, and R. M. Fonseca
Atmos. Chem. Phys., 13, 2923–2938, https://doi.org/10.5194/acp-13-2923-2013, https://doi.org/10.5194/acp-13-2923-2013, 2013
S. Strada, S. R. Freitas, C. Mari, K. M. Longo, and R. Paugam
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-721-2013, https://doi.org/10.5194/gmdd-6-721-2013, 2013
Preprint withdrawn
D. A. Belikov, S. Maksyutov, M. Krol, A. Fraser, M. Rigby, H. Bian, A. Agusti-Panareda, D. Bergmann, P. Bousquet, P. Cameron-Smith, M. P. Chipperfield, A. Fortems-Cheiney, E. Gloor, K. Haynes, P. Hess, S. Houweling, S. R. Kawa, R. M. Law, Z. Loh, L. Meng, P. I. Palmer, P. K. Patra, R. G. Prinn, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 1093–1114, https://doi.org/10.5194/acp-13-1093-2013, https://doi.org/10.5194/acp-13-1093-2013, 2013
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Oil palm modelling in the global land surface model ORCHIDEE-MICT
Testing the reliability of interpretable neural networks in geoscience using the Madden–Julian oscillation
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fv3gfs-wrapper: a Python wrapper of the FV3GFS atmospheric model
Recalibrating decadal climate predictions – what is an adequate model for the drift?
Multi-variate factorisation of numerical simulations
Inclusion of a suite of weathering tracers in the cGENIE Earth system model – muffin release v.0.9.23
The ENEA-REG system (v1.0), a multi-component regional Earth system model: sensitivity to different atmospheric components over the Med-CORDEX (Coordinated Regional Climate Downscaling Experiment) region
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TransEBM v. 1.0: description, tuning, and validation of a transient model of the Earth's energy balance in two dimensions
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The GPU version of LASG/IAP Climate System Ocean Model version 3 (LICOM3) under the heterogeneous-compute interface for portability (HIP) framework and its large-scale application
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Yidi Xu, Philippe Ciais, Le Yu, Wei Li, Xiuzhi Chen, Haicheng Zhang, Chao Yue, Kasturi Kanniah, Arthur P. Cracknell, and Peng Gong
Geosci. Model Dev., 14, 4573–4592, https://doi.org/10.5194/gmd-14-4573-2021, https://doi.org/10.5194/gmd-14-4573-2021, 2021
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In this study, we implemented the specific morphology, phenology and harvest process of oil palm in the global land surface model ORCHIDEE-MICT. The improved model generally reproduces the same leaf area index, biomass density and life cycle fruit yield as observations. This explicit representation of oil palm in a global land surface model offers a useful tool for understanding the ecological processes of oil palm growth and assessing the environmental impacts of oil palm plantations.
Benjamin A. Toms, Karthik Kashinath, Prabhat, and Da Yang
Geosci. Model Dev., 14, 4495–4508, https://doi.org/10.5194/gmd-14-4495-2021, https://doi.org/10.5194/gmd-14-4495-2021, 2021
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We test whether a type of machine learning called neural networks can be used trustfully within the geosciences. We do so by challenging the networks to understand the spatial patterns of a commonly studied geoscientific phenomenon. The neural networks can correctly identify the spatial patterns, which lends confidence that similar networks can be used for more uncertain problems. The results of this study may give geoscientists confidence when using neural networks in their research.
Klaus Klingmüller and Jos Lelieveld
Geosci. Model Dev., 14, 4429–4441, https://doi.org/10.5194/gmd-14-4429-2021, https://doi.org/10.5194/gmd-14-4429-2021, 2021
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Soil moisture is of great importance for weather and climate. We present a machine learning model that produces accurate predictions of satellite-observed surface soil moisture, based on meteorological data from a climate model. It can be used as soil moisture parametrisation in climate models and to produce comprehensive global soil moisture datasets. Moreover, it may motivate similar applications of machine learning in climate science.
Jeremy McGibbon, Noah D. Brenowitz, Mark Cheeseman, Spencer K. Clark, Johann P. S. Dahm, Eddie C. Davis, Oliver D. Elbert, Rhea C. George, Lucas M. Harris, Brian Henn, Anna Kwa, W. Andre Perkins, Oliver Watt-Meyer, Tobias F. Wicky, Christopher S. Bretherton, and Oliver Fuhrer
Geosci. Model Dev., 14, 4401–4409, https://doi.org/10.5194/gmd-14-4401-2021, https://doi.org/10.5194/gmd-14-4401-2021, 2021
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FV3GFS is a weather and climate model written in Fortran. It uses Fortran so that it can run fast, but this makes it hard to add features if you do not (or even if you do) know Fortran. We have written a Python interface to FV3GFS that lets you import the Fortran model as a Python package. We show examples of how this is used to write
modelscripts, which reproduce or build on what the Fortran model can do. You could do this same wrapping for any compiled model, not just FV3GFS.
Alexander Pasternack, Jens Grieger, Henning W. Rust, and Uwe Ulbrich
Geosci. Model Dev., 14, 4335–4355, https://doi.org/10.5194/gmd-14-4335-2021, https://doi.org/10.5194/gmd-14-4335-2021, 2021
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Decadal climate ensemble forecasts are increasingly being used to guide adaptation measures. To ensure the applicability of these probabilistic predictions, inherent systematic errors of the prediction system must be adjusted. Since it is not clear which statistical model is optimal for this purpose, we propose a recalibration strategy with a systematic model selection based on non-homogeneous boosting for identifying the most relevant features for both ensemble mean and ensemble spread.
Daniel J. Lunt, Deepak Chandan, Alan M. Haywood, George M. Lunt, Jonathan C. Rougier, Ulrich Salzmann, Gavin A. Schmidt, and Paul J. Valdes
Geosci. Model Dev., 14, 4307–4317, https://doi.org/10.5194/gmd-14-4307-2021, https://doi.org/10.5194/gmd-14-4307-2021, 2021
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Often in science we carry out experiments with computers in which several factors are explored, for example, in the field of climate science, how the factors of greenhouse gases, ice, and vegetation affect temperature. We can explore the relative importance of these factors by
swapping in and outdifferent values of these factors, and can also carry out experiments with many different combinations of these factors. This paper discusses how best to analyse the results from such experiments.
Markus Adloff, Andy Ridgwell, Fanny M. Monteiro, Ian J. Parkinson, Alexander J. Dickson, Philip A. E. Pogge von Strandmann, Matthew S. Fantle, and Sarah E. Greene
Geosci. Model Dev., 14, 4187–4223, https://doi.org/10.5194/gmd-14-4187-2021, https://doi.org/10.5194/gmd-14-4187-2021, 2021
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We present the first representation of the trace metals Sr, Os, Li and Ca in a 3D Earth system model (cGENIE). The simulation of marine metal sources (weathering, hydrothermal input) and sinks (deposition) reproduces the observed concentrations and isotopic homogeneity of these metals in the modern ocean. With these new tracers, cGENIE can be used to test hypotheses linking these metal cycles and the cycling of other elements like O and C and simulate their dynamic response to external forcing.
Alessandro Anav, Adriana Carillo, Massimiliano Palma, Maria Vittoria Struglia, Ufuk Utku Turuncoglu, and Gianmaria Sannino
Geosci. Model Dev., 14, 4159–4185, https://doi.org/10.5194/gmd-14-4159-2021, https://doi.org/10.5194/gmd-14-4159-2021, 2021
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The Mediterranean Basin is a complex region, characterized by the presence of pronounced topography and a complex land–sea distribution including a considerable number of islands and straits; these features generate strong local atmosphere–sea interactions.
Regional Earth system models have been developed and used to study both present and future Mediterranean climate systems. The main aims of this paper are to present and evaluate the newly developed regional Earth system model ENEA-REG.
Markus Drüke, Werner von Bloh, Stefan Petri, Boris Sakschewski, Sibyll Schaphoff, Matthias Forkel, Willem Huiskamp, Georg Feulner, and Kirsten Thonicke
Geosci. Model Dev., 14, 4117–4141, https://doi.org/10.5194/gmd-14-4117-2021, https://doi.org/10.5194/gmd-14-4117-2021, 2021
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In this study, we couple the well-established and comprehensively validated state-of-the-art dynamic LPJmL5 global vegetation model to the CM2Mc coupled climate model (CM2Mc-LPJmL v.1.0). Several improvements to LPJmL5 were implemented to allow a fully functional biophysical coupling. The new climate model is able to capture important biospheric processes, including fire, mortality, permafrost, hydrological cycling and the the impacts of managed land (crop growth and irrigation).
Dirk Barbi, Nadine Wieters, Paul Gierz, Miguel Andrés-Martínez, Deniz Ural, Fatemeh Chegini, Sara Khosravi, and Luisa Cristini
Geosci. Model Dev., 14, 4051–4067, https://doi.org/10.5194/gmd-14-4051-2021, https://doi.org/10.5194/gmd-14-4051-2021, 2021
Cléa Denamiel, Petra Pranić, Damir Ivanković, Iva Tojčić, and Ivica Vilibić
Geosci. Model Dev., 14, 3995–4017, https://doi.org/10.5194/gmd-14-3995-2021, https://doi.org/10.5194/gmd-14-3995-2021, 2021
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The atmospheric results of the Adriatic Sea and Coast (AdriSC) climate simulation (1987–2017) are evaluated against available observational datasets in the Adriatic region. Generally, the AdriSC model performs better than regional climate models that have resolutions that are 4 times more coarse, except concerning summer temperatures, which are systematically underestimated. High-resolution climate models may thus provide new insights about the local impacts of global warming in the Adriatic.
Guy Munhoven
Geosci. Model Dev., 14, 3603–3631, https://doi.org/10.5194/gmd-14-3603-2021, https://doi.org/10.5194/gmd-14-3603-2021, 2021
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Sea-floor sediments play an important role in biogeochemical cycling of elements (e.g. carbon, silicon, nutrients) in the ocean. Realistic sediment modules are, however, not yet commonly used in global ocean biogeochemical models. Here we present MEDUSA, a model of the processes taking place in the surface sea-floor sediments which control the interaction between the sediments and the ocean. MEDUSA can be configured to meet the exact needs of any given ocean biogeochemical model.
Max Kulinich, Yanan Fan, Spiridon Penev, Jason P. Evans, and Roman Olson
Geosci. Model Dev., 14, 3539–3551, https://doi.org/10.5194/gmd-14-3539-2021, https://doi.org/10.5194/gmd-14-3539-2021, 2021
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We present a novel stochastic approach based on Markov chains to estimate climate model weights of multi-model ensemble means. This approach showed improved performance (better correlation with observations) over existing alternatives during cross-validation and model-as-truth tests. The results of this comparative analysis should serve to motivate further studies in applications of Markov chain and other nonlinear methods to find optimal model weights for constructing ensemble means.
Jens Pfafferott, Sascha Rißmann, Matthias Sühring, Farah Kanani-Sühring, and Björn Maronga
Geosci. Model Dev., 14, 3511–3519, https://doi.org/10.5194/gmd-14-3511-2021, https://doi.org/10.5194/gmd-14-3511-2021, 2021
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The building model is integrated via an urban surface model into the urban climate model.
There is a strong interaction between the built environment and the urban climate.
According to the building energy concept, the energy demand results in a waste heat; this is directly transferred to the urban environment.
The impact of buildings on the urban climate is defined by different physical building parameters with different technical facilities for ventilation, heating and cooling.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
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We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
Geosci. Model Dev., 14, 3159–3184, https://doi.org/10.5194/gmd-14-3159-2021, https://doi.org/10.5194/gmd-14-3159-2021, 2021
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This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
Jun'ya Takakura, Shinichiro Fujimori, Kiyoshi Takahashi, Naota Hanasaki, Tomoko Hasegawa, Yukiko Hirabayashi, Yasushi Honda, Toshichika Iizumi, Chan Park, Makoto Tamura, and Yasuaki Hijioka
Geosci. Model Dev., 14, 3121–3140, https://doi.org/10.5194/gmd-14-3121-2021, https://doi.org/10.5194/gmd-14-3121-2021, 2021
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To simplify calculating economic impacts of climate change, statistical methods called emulators are developed and evaluated. There are trade-offs between model complexity and emulation performance. Aggregated economic impacts can be approximated by relatively simple emulators, but complex emulators are necessary to accommodate finer-scale economic impacts.
Meng-Zhuo Zhang, Zhongfeng Xu, Ying Han, and Weidong Guo
Geosci. Model Dev., 14, 3079–3094, https://doi.org/10.5194/gmd-14-3079-2021, https://doi.org/10.5194/gmd-14-3079-2021, 2021
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The Multivariable Integrated Evaluation Tool (MVIETool) is a simple-to-use and straightforward tool designed for evaluation and intercomparison of climate models in terms of vector fields or multiple fields. The tool incorporates some new improvements in vector field evaluation (VFE) and multivariable integrated evaluation (MVIE) methods, which are introduced in this paper.
Sam J. Silva, Po-Lun Ma, Joseph C. Hardin, and Daniel Rothenberg
Geosci. Model Dev., 14, 3067–3077, https://doi.org/10.5194/gmd-14-3067-2021, https://doi.org/10.5194/gmd-14-3067-2021, 2021
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The activation of aerosol into cloud droplets is an important but uncertain process in the Earth system. The physical and chemical interactions that govern this process are too computationally expensive to explicitly resolve in modern Earth system models. Here, we demonstrate how hybrid machine learning approaches can provide a potential path forward, enabling the representation of the more detailed physics and chemistry at a reduced computational cost while still retaining physical information.
Nicholas J. Leach, Stuart Jenkins, Zebedee Nicholls, Christopher J. Smith, John Lynch, Michelle Cain, Tristram Walsh, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev., 14, 3007–3036, https://doi.org/10.5194/gmd-14-3007-2021, https://doi.org/10.5194/gmd-14-3007-2021, 2021
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This paper presents an update of the FaIR simple climate model, which can estimate the impact of anthropogenic greenhouse gas and aerosol emissions on the global climate. This update aims to significantly increase the structural simplicity of the model, making it more understandable and transparent. This simplicity allows it to be implemented in a wide range of environments, including Excel. We suggest that it could be used widely in academia, corporate research, and education.
Tongwen Wu, Rucong Yu, Yixiong Lu, Weihua Jie, Yongjie Fang, Jie Zhang, Li Zhang, Xiaoge Xin, Laurent Li, Zaizhi Wang, Yiming Liu, Fang Zhang, Fanghua Wu, Min Chu, Jianglong Li, Weiping Li, Yanwu Zhang, Xueli Shi, Wenyan Zhou, Junchen Yao, Xiangwen Liu, He Zhao, Jinghui Yan, Min Wei, Wei Xue, Anning Huang, Yaocun Zhang, Yu Zhang, Qi Shu, and Aixue Hu
Geosci. Model Dev., 14, 2977–3006, https://doi.org/10.5194/gmd-14-2977-2021, https://doi.org/10.5194/gmd-14-2977-2021, 2021
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This paper presents the high-resolution version of the Beijing Climate Center (BCC) Climate System Model, BCC-CSM2-HR, and describes its climate simulation performance including the atmospheric temperature and wind; precipitation; and the tropical climate phenomena such as TC, MJO, QBO, and ENSO. BCC-CSM2-HR is our model version contributing to the HighResMIP. We focused on its updates and differential characteristics from its predecessor, the medium-resolution version BCC-CSM2-MR.
Olivier Marti, Sébastien Nguyen, Pascale Braconnot, Sophie Valcke, Florian Lemarié, and Eric Blayo
Geosci. Model Dev., 14, 2959–2975, https://doi.org/10.5194/gmd-14-2959-2021, https://doi.org/10.5194/gmd-14-2959-2021, 2021
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State-of-the-art Earth system models, like the ones used in CMIP6, suffer from temporal inconsistencies at the ocean–atmosphere interface. In this study, a mathematically consistent iterative Schwarz method is used as a reference. Its tremendous computational cost makes it unusable for production runs, but it allows us to evaluate the error made when using legacy coupling schemes. The impact on the climate at longer timescales of days to decades is not evaluated.
Steven R. Brus, Phillip J. Wolfram, Luke P. Van Roekel, and Jessica D. Meixner
Geosci. Model Dev., 14, 2917–2938, https://doi.org/10.5194/gmd-14-2917-2021, https://doi.org/10.5194/gmd-14-2917-2021, 2021
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Wind-generated waves are an important process in the global climate system. They mediate many interactions between the ocean, atmosphere, and sea ice. Models which describe these waves are computationally expensive and have often been excluded from coupled Earth system models. To address this, we have developed a capability for the WAVEWATCH III model which allows model resolution to be varied globally across the coastal open ocean. This allows for improved accuracy at reduced computing time.
Elisa Ziegler and Kira Rehfeld
Geosci. Model Dev., 14, 2843–2866, https://doi.org/10.5194/gmd-14-2843-2021, https://doi.org/10.5194/gmd-14-2843-2021, 2021
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Past climate changes are the only record of how the climate responds to changes in conditions on Earth, but simulations with complex climate models are challenging. We extended a simple climate model such that it simulates the development of temperatures over time. In the model, changes in carbon dioxide and ice distribution affect the simulated temperatures the most. The model is very efficient and can therefore be used to examine past climate changes happening over long periods of time.
Qun Liu, Matthew Collins, Penelope Maher, Stephen I. Thomson, and Geoffrey K. Vallis
Geosci. Model Dev., 14, 2801–2826, https://doi.org/10.5194/gmd-14-2801-2021, https://doi.org/10.5194/gmd-14-2801-2021, 2021
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Clouds play an vital role in Earth's energy budget, and even a small change in cloud fields can have a large impact on the climate system. They also bring lots of uncertainties to climate models. Here we implement a simple diagnostic cloud scheme in order to reproduce the general radiative properties of clouds. The scheme can capture some key features of the cloud fraction and cloud radiative properties and thus provide a useful tool to explore unsolved problems relating to clouds.
Martina Messmer, Santos J. González-Rojí, Christoph C. Raible, and Thomas F. Stocker
Geosci. Model Dev., 14, 2691–2711, https://doi.org/10.5194/gmd-14-2691-2021, https://doi.org/10.5194/gmd-14-2691-2021, 2021
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Sensitivity experiments with the WRF model are run to find an optimal parameterization setup for precipitation around Mount Kenya at a scale that resolves convection (1 km). Precipitation is compared against many weather stations and gridded observational data sets. Both the temporal correlation of precipitation sums and pattern correlations show that fewer nests lead to a more constrained simulation with higher correlation. The Grell–Freitas cumulus scheme obtains the most accurate results.
Pengfei Wang, Jinrong Jiang, Pengfei Lin, Mengrong Ding, Junlin Wei, Feng Zhang, Lian Zhao, Yiwen Li, Zipeng Yu, Weipeng Zheng, Yongqiang Yu, Xuebin Chi, and Hailong Liu
Geosci. Model Dev., 14, 2781–2799, https://doi.org/10.5194/gmd-14-2781-2021, https://doi.org/10.5194/gmd-14-2781-2021, 2021
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Global ocean general circulation models are a fundamental tool for oceanography research, ocean forecast, and climate change research. The increasing resolution will greatly improve simulations of the models, but it also demands much more computing resources. In this study, we have ported an ocean general circulation model to a heterogeneous computing system and have developed a 3–5 km model version. A 14-year integration has been conducted and the preliminary results have been evaluated.
Chao Sun, Li Liu, Ruizhe Li, Xinzhu Yu, Hao Yu, Biao Zhao, Guansuo Wang, Juanjuan Liu, Fangli Qiao, and Bin Wang
Geosci. Model Dev., 14, 2635–2657, https://doi.org/10.5194/gmd-14-2635-2021, https://doi.org/10.5194/gmd-14-2635-2021, 2021
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Data assimilation (DA) provides better initial states of model runs by combining observations and models. This work focuses on the technical challenges in developing a coupled ensemble-based DA system and proposes a new DA framework DAFCC1 based on C-Coupler2. DAFCC1 enables users to conveniently integrate a DA method into a model with automatic and efficient data exchanges. A sample DA system that combines GSI/EnKF and FIO-AOW demonstrates the effectiveness of DAFCC1.
Andrew J. Wiltshire, Eleanor J. Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Cox, Taraka Davies-Barnard, Pierre Friedlingstein, Anna B. Harper, Spencer Liddicoat, Stephen Sitch, and Sönke Zaehle
Geosci. Model Dev., 14, 2161–2186, https://doi.org/10.5194/gmd-14-2161-2021, https://doi.org/10.5194/gmd-14-2161-2021, 2021
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Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle, which is included within the UK Earth System model to improve projections of climate change and impacts on ecosystems.
Pirkka Ollinaho, Glenn D. Carver, Simon T. K. Lang, Lauri Tuppi, Madeleine Ekblom, and Heikki Järvinen
Geosci. Model Dev., 14, 2143–2160, https://doi.org/10.5194/gmd-14-2143-2021, https://doi.org/10.5194/gmd-14-2143-2021, 2021
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OpenEnsemble 1.0 is a novel dataset that aims to open ensemble or probabilistic weather forecasting research up to the academic community. The dataset contains atmospheric states that are required for running model forecasts of atmospheric evolution. Our capacity to observe the atmosphere is limited; thus, a single reconstruction of the atmospheric state contains some errors. Our dataset provides sets of 50 slightly different atmospheric states so that these errors can be taken into account.
Yan Sun, Daniel S. Goll, Jinfeng Chang, Philippe Ciais, Betrand Guenet, Julian Helfenstein, Yuanyuan Huang, Ronny Lauerwald, Fabienne Maignan, Victoria Naipal, Yilong Wang, Hui Yang, and Haicheng Zhang
Geosci. Model Dev., 14, 1987–2010, https://doi.org/10.5194/gmd-14-1987-2021, https://doi.org/10.5194/gmd-14-1987-2021, 2021
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We evaluated the performance of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 against remote sensing, ground-based measurement networks and ecological databases. The simulated carbon, nitrogen and phosphorus fluxes among different spatial scales are generally in good agreement with data-driven estimates. However, the recent carbon sink in the Northern Hemisphere is substantially underestimated. Potential causes and model development priorities are discussed.
Hui Wan, Shixuan Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, and Huiping Yan
Geosci. Model Dev., 14, 1921–1948, https://doi.org/10.5194/gmd-14-1921-2021, https://doi.org/10.5194/gmd-14-1921-2021, 2021
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Numerical models used in weather and climate research and prediction unavoidably contain numerical errors resulting from temporal discretization, and the impact of such errors can be substantial. Complex process interactions often make it difficult to pinpoint the exact sources of such errors. This study uses a series of sensitivity experiments to identify components in a global atmosphere model that are responsible for time step sensitivities in various cloud regimes.
Johannes Horak, Marlis Hofer, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Geosci. Model Dev., 14, 1657–1680, https://doi.org/10.5194/gmd-14-1657-2021, https://doi.org/10.5194/gmd-14-1657-2021, 2021
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This process-based evaluation of the atmospheric model ICAR is conducted to derive recommendations to increase the likelihood of its results being correct for the right reasons. We conclude that a different diagnosis of the atmospheric background state is necessary, as well as a model top at an elevation of at least 10 km. Alternative boundary conditions at the top were not found to be effective in reducing this model top elevation. The results have wide implications for future ICAR studies.
Yong Wang, Guang J. Zhang, Shaocheng Xie, Wuyin Lin, George C. Craig, Qi Tang, and Hsi-Yen Ma
Geosci. Model Dev., 14, 1575–1593, https://doi.org/10.5194/gmd-14-1575-2021, https://doi.org/10.5194/gmd-14-1575-2021, 2021
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A stochastic deep convection parameterization is implemented into the US Department of Energy Energy Exascale Earth System Model Atmosphere Model version 1 (EAMv1). Compared to the default model, the well-known problem of
too much light rain and too little heavy rainis largely alleviated over the tropics with the stochastic scheme. Results from this study provide important insights into the model performance of EAMv1 when stochasticity is included in the deep convective parameterization.
Sonia Jerez, Laura Palacios-Peña, Claudia Gutiérrez, Pedro Jiménez-Guerrero, Jose María López-Romero, Enrique Pravia-Sarabia, and Juan Pedro Montávez
Geosci. Model Dev., 14, 1533–1551, https://doi.org/10.5194/gmd-14-1533-2021, https://doi.org/10.5194/gmd-14-1533-2021, 2021
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This research explores the role of aerosols when modeling surface solar radiation at regional scales (over Europe). A set of model experiments was performed with and without dynamical modeling of atmospheric aerosols and their direct and indirect effects on radiation. Results showed significant differences in the simulated solar radiation, mainly driven by the aerosol impact on cloudiness, which calls for caution when interpreting model experiments that do not include aerosols.
Sara Top, Lola Kotova, Lesley De Cruz, Svetlana Aniskevich, Leonid Bobylev, Rozemien De Troch, Natalia Gnatiuk, Anne Gobin, Rafiq Hamdi, Arne Kriegsmann, Armelle Reca Remedio, Abdulla Sakalli, Hans Van De Vyver, Bert Van Schaeybroeck, Viesturs Zandersons, Philippe De Maeyer, Piet Termonia, and Steven Caluwaerts
Geosci. Model Dev., 14, 1267–1293, https://doi.org/10.5194/gmd-14-1267-2021, https://doi.org/10.5194/gmd-14-1267-2021, 2021
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Detailed climate data are needed to assess the impact of climate change on human and natural systems. The performance of two high-resolution regional climate models, ALARO-0 and REMO2015, was investigated over central Asia, a vulnerable region where detailed climate information is scarce. In certain subregions the produced climate data are suitable for impact studies, but bias adjustment is required for subregions where significant biases have been identified.
Yaqiong Lu and Xianyu Yang
Geosci. Model Dev., 14, 1253–1265, https://doi.org/10.5194/gmd-14-1253-2021, https://doi.org/10.5194/gmd-14-1253-2021, 2021
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Crop growth in land surface models normally requires high-temporal-resolution climate data, but such high-temporal-resolution climate data are not provided by many climate model simulations due to expensive storage, which limits modeling choices if there is an interest in a particular climate simulation that only saved monthly outputs. Our work provides an alternative way to use the monthly climate for crop yield projections. Such an approach could be easily adopted by other crop models.
John G. Virgin, Christopher G. Fletcher, Jason N. S. Cole, Knut von Salzen, and Toni Mitovski
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-11, https://doi.org/10.5194/gmd-2021-11, 2021
Revised manuscript accepted for GMD
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Equilibrium climate sensitivity, or the amount of warming the Earth would exhibit a result of a doubling of atmospheric CO2, is a common metric used in assessments of climate models. Here, we compare climate sensitivity between two versions of the Canadian Earth System Model. We find the newest iteration of the model (version 5) to have higher climate sensitivity due to reductions in low level clouds, which reflect radiation and cool the planet, as the surface warms.
Rumi Ohgaito, Akitomo Yamamoto, Tomohiro Hajima, Ryouta O'ishi, Manabu Abe, Hiroaki Tatebe, Ayako Abe-Ouchi, and Michio Kawamiya
Geosci. Model Dev., 14, 1195–1217, https://doi.org/10.5194/gmd-14-1195-2021, https://doi.org/10.5194/gmd-14-1195-2021, 2021
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Using the MIROC-ES2L Earth system model, selected time periods of the past were simulated. The ability to simulate the past is also an evaluation of the performance of the model in projecting global warming. Simulations for 21 000, 6000, and 127 000 years ago, and a simulation for 1000 years starting in 850 CE were simulated. The results showed that the model can generally describe past climate change.
Qiong Zhang, Ellen Berntell, Josefine Axelsson, Jie Chen, Zixuan Han, Wesley de Nooijer, Zhengyao Lu, Qiang Li, Qiang Zhang, Klaus Wyser, and Shuting Yang
Geosci. Model Dev., 14, 1147–1169, https://doi.org/10.5194/gmd-14-1147-2021, https://doi.org/10.5194/gmd-14-1147-2021, 2021
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Paleoclimate modelling has long been regarded as a strong out-of-sample test bed of the climate models that are used for the projection of future climate changes. Here, we document the model experimental setups for the three past warm periods with EC-Earth3-LR and present the results on the large-scale features. The simulations demonstrate good performance of the model in capturing the climate response under different climate forcings.
Gill M. Martin, Richard C. Levine, José M. Rodriguez, and Michael Vellinga
Geosci. Model Dev., 14, 1007–1035, https://doi.org/10.5194/gmd-14-1007-2021, https://doi.org/10.5194/gmd-14-1007-2021, 2021
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Our study highlights a number of different techniques that can be employed to investigate the sources of model error. We demonstrate how this methodology can be used to identify the regions and model components responsible for the development of long-standing errors in the Asian summer monsoon. Once these are known, further work can be done to explore the local processes contributing to this behaviour and their sensitivity to changes in physical parameterisations and/or model resolution.
Silje Lund Sørland, Roman Brogli, Praveen Kumar Pothapakula, Emmanuele Russo, Jonas Van de Walle, Bodo Ahrens, Ivonne Anders, Edoardo Bucchignani, Edouard L. Davin, Marie-Estelle Demory, Alessandro Dosio, Hendrik Feldmann, Barbara Früh, Beate Geyer, Klaus Keuler, Donghyun Lee, Delei Li, Nicole P. M. van Lipzig, Seung-Ki Min, Hans-Jürgen Paniz, Burkhardt Rockel, Christoph Schär, Christian Steger, and Wim Thiery
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-443, https://doi.org/10.5194/gmd-2020-443, 2021
Revised manuscript accepted for GMD
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We review the contribution from the CLM-Community to regional climate projections following the CORDEX framework over Europe, South Asia, East Asia, Australasia and Africa. How the model configuration, horizontal and vertical resolution and choice of driving data is influencing the model performance for the five domains is assessed, with the purpose to aid the planning and design of regional climate simulations in the future.
Trang Van Pham, Christian Steger, Burkhardt Rockel, Klaus Keuler, Ingo Kirchner, Mariano Mertens, Daniel Rieger, Günther Zängl, and Barbara Früh
Geosci. Model Dev., 14, 985–1005, https://doi.org/10.5194/gmd-14-985-2021, https://doi.org/10.5194/gmd-14-985-2021, 2021
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A new regional climate model was prepared based on a weather forecast model. Slow processes of the climate system such as ocean state development and greenhouse gas emissions were implemented. A model infrastructure and evaluation tools were also prepared to facilitate long-term simulations and model evalution. The first ICON-CLM results were close to observations and comparable to those from COSMO-CLM, the recommended model being used at the Deutscher Wetterdienst and CLM Community.
Klaus Wyser, Torben Koenigk, Uwe Fladrich, Ramon Fuentes-Franco, Mehdi Pasha Karami, and Tim Kruschke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-428, https://doi.org/10.5194/gmd-2020-428, 2021
Revised manuscript accepted for GMD
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This paper describes the large ensemble done by SMHI with the EC-Earth3 climate model. The ensemble comprises 50 realisations of the historical experiment and four different future projections for CMIP6. We describe the creation of the initial states for the large ensemble and the reduced set of output variables. A first look at the results illustrates the changes in the climate during this century and puts them in relation to the uncertainty from the model's internal variability.
Michael Steiner, Beiping Luo, Thomas Peter, Michael C. Pitts, and Andrea Stenke
Geosci. Model Dev., 14, 935–959, https://doi.org/10.5194/gmd-14-935-2021, https://doi.org/10.5194/gmd-14-935-2021, 2021
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We evaluate polar stratospheric clouds (PSCs) as simulated by the chemistry–climate model (CCM) SOCOLv3.1 in comparison with measurements by the CALIPSO satellite. A cold bias results in an overestimated PSC area and mountain-wave ice is underestimated, but we find overall good temporal and spatial agreement of PSC occurrence and composition. This work confirms previous studies indicating that simplified PSC schemes may also achieve good approximations of the fundamental properties of PSCs.
Zhaoyuan Yu, Dongshuang Li, Zhengfang Zhang, Wen Luo, Yuan Liu, Zengjie Wang, and Linwang Yuan
Geosci. Model Dev., 14, 875–887, https://doi.org/10.5194/gmd-14-875-2021, https://doi.org/10.5194/gmd-14-875-2021, 2021
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Few lossy compression methods consider both the global and local multidimensional coupling correlations, which could lead to information loss in data compression. Here we develop an adaptive lossy compression method, Adaptive-HGFDR, to capture both the global and local variation of multidimensional coupling correlations and improve approximation accuracy. The method can achieve good compression performances for most flux variables with significant spatiotemporal heterogeneity.
Franziska Winterstein and Patrick Jöckel
Geosci. Model Dev., 14, 661–674, https://doi.org/10.5194/gmd-14-661-2021, https://doi.org/10.5194/gmd-14-661-2021, 2021
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Atmospheric methane is currently a hot topic in climate research. This is partly due to its chemically active nature. We introduce a simplified approach to simulate methane in climate models to enable large sensitivity studies by reducing computational cost but including the crucial feedback of methane on stratospheric water vapour. We further provide options to simulate the isotopic content of methane and to generate output for an inverse optimization technique for emission estimation.
Ruth Petrie, Sébastien Denvil, Sasha Ames, Guillaume Levavasseur, Sandro Fiore, Chris Allen, Fabrizio Antonio, Katharina Berger, Pierre-Antoine Bretonnière, Luca Cinquini, Eli Dart, Prashanth Dwarakanath, Kelsey Druken, Ben Evans, Laurent Franchistéguy, Sébastien Gardoll, Eric Gerbier, Mark Greenslade, David Hassell, Alan Iwi, Martin Juckes, Stephan Kindermann, Lukasz Lacinski, Maria Mirto, Atef Ben Nasser, Paola Nassisi, Eric Nienhouse, Sergey Nikonov, Alessandra Nuzzo, Clare Richards, Syazwan Ridzwan, Michel Rixen, Kim Serradell, Kate Snow, Ag Stephens, Martina Stockhause, Hans Vahlenkamp, and Rick Wagner
Geosci. Model Dev., 14, 629–644, https://doi.org/10.5194/gmd-14-629-2021, https://doi.org/10.5194/gmd-14-629-2021, 2021
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This paper describes the infrastructure that is used to distribute Coupled Model Intercomparison Project Phase 6 (CMIP6) data around the world for analysis by the climate research community. It is expected that there will be ~20 PB (petabytes) of data available for analysis. The operations team performed a series of preparation "data challenges" to ensure all components of the infrastructure were operational for when the data became available for timely data distribution and subsequent analysis.
Camilla Mathison, Andrew J. Challinor, Chetan Deva, Pete Falloon, Sébastien Garrigues, Sophie Moulin, Karina Williams, and Andy Wiltshire
Geosci. Model Dev., 14, 437–471, https://doi.org/10.5194/gmd-14-437-2021, https://doi.org/10.5194/gmd-14-437-2021, 2021
Short summary
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Sequential cropping (also known as multiple or double cropping) is a common cropping system, particularly in tropical regions. Typically, land surface models only simulate a single crop per year. To understand how sequential crops influence surface fluxes, we implement sequential cropping in JULES to simulate all the crops grown within a year at a given location in a seamless way. We demonstrate the method using a site in Avignon, four locations in India and a regional run for two Indian states.
Chao Wang, Xingqin An, Qing Hou, Zhaobin Sun, Yanjun Li, and Jiangtao Li
Geosci. Model Dev., 14, 337–350, https://doi.org/10.5194/gmd-14-337-2021, https://doi.org/10.5194/gmd-14-337-2021, 2021
Cited articles
Andreae, M. O.: Biomass burning: its history, use and distribution and its impact on environmental quality and global climate, in: Global Biomass Burning, Atmospheric, Climatic and Biospheric Implications, edited by: Levine, J. S., MIT Press, Cambridge, Mass., 3–21, 1991.
Andreae, M. O., Rosenfeld, D., Artaxo, P., Costa, A. A., Frank, G. P., Longo, K. M., and Silva-Dias, M. A. F.: Smoking rain clouds over the Amazon, Science, 303, 1337–1342, https://doi.org/10.1126/science.1092779, 2004.
Artaxo, P., Martins, J. V., Yamasoe, M. A., Procópio, A. S., Pauliquevis, T. M., Andreae, M. O., Guyon, P., Gatti, L. V., and Leal, A. M. C.: Physical and chemical properties of aerosols in the wet and dry seasons in Rondônia, Amazonia, J. Geophys. Res., 107, 8081, https://doi.org/10.1029/2001JD000666, 2002.
Baker, T. R., Phillips, O. L., Malhi, Y., Almeida, S., Arroyo, L., Di Fiore, A., Erwin, T., Higuchi, N., Killeen, T. J., Laurance, S. G., Laurance, W. F., Lewis, S. L., Monteagudo, A., Neill, D. A., Núñez Vargas, P., Pitman, N. C. A., Silva, J. N. M., and Vásquez Martínez, R.: Increasing biomass in Amazonian forest plots, Philos. T. Roy. Soc. B, 359, 353–365, https://doi.org/10.1098/rstb.2003.1422, 2004.
Batjes, N. H.: Documentation to ISRIC-WISE Global Data Set of Derived Soil Properties on a 1/2 Deg by 1/2 Deg Grid (Version 1.0), Working Paper and Preprint 96/05, ISRIC, Wageningen, 1996.
Berge, E.: Coupling of wet scavenging of sulphur to clouds in a numerical weather prediction model, Tellus B, 45, 1–22, https://doi.org/10.1034/j.1600-0889.1993.00001.x, 1993.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R .L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Bouttier, F. and Kelly, G.: Observing-system experiments in the ECMWF 4-D-Var data assimilation system, Q. J. Roy. Meteor. Soc., 127, 1469–1488, doi10.1002/qj.49712757419, 2001.
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011.
Collatz, G. J., Ball, J. T., Grivet, C., and Berry, J. A.: Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer, Agr. Forest Meteorol., 54, 107–136, https://doi.org/10.1016/0168-1923(91)90002-8, 1991.
Collatz, G. J., Ribas-Carbo, M., and Berry, J. A.: Coupled photosynthesis-stomatal conductance model for leaves of C4 plants, Funct. Plant Biol., 19, 519–538, 1992.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P. , Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H. , Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Essery, R. L. H., Best, M. J., Betts, R. A., Cox, P. M., and Taylor, C. M.: Explicit Representation of Subgrid Heterogeneity in a GCM Land Surface Scheme, J. Hydrometeorol., 4, 530–543, ISSN: 1525-755X, https://doi.org/10.1175/1525-7541(2003)004<0530:EROSHI>2.0.CO;2, 2003.
Flatau, P. J., Tripoli, G. J., Verlinde, J., and Cotton, W. R.: The CSU-RAMS cloud microphysical Module: General Theory and Code Documentation, Technical Report 451, Dep. Atmos. Sci., Colorado State University, Fort Collins, CO, USA, 88 pp., 1989.
Freitas, S. R., Longo, K. M., Alonso, M. F., Pirre, M., Marecal, V., Grell, G., Stockler, R., Mello, R. F., and Sánchez Gácita, M.: PREP-CHEM-SRC – 1.0: a preprocessor of trace gas and aerosol emission fields for regional and global atmospheric chemistry models, Geosci. Model Dev., 4, 419–433, https://doi.org/10.5194/gmd-4-419-2011, 2011.
Freitas, S. R., Longo, K. M., Chatfield, R., Latham, D., Silva Dias, M. A. F., Andreae, M. O., Prins, E., Santos, J. C., Gielow, R., and Carvalho Jr., J. A.: Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models, Atmos. Chem. Phys., 7, 3385–3398, https://doi.org/10.5194/acp-7-3385-2007, 2007.
Freitas, S. R., Longo, K. M., Silva Dias, M. A. F., Chatfield, R., Silva Dias, P., Artaxo, P., Andreae, M. O., Grell, G., Rodrigues, L. F., Fazenda, A., and Panetta, J.: The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) – Part 1: Model description and evaluation, Atmos. Chem. Phys., 9, 2843–2861, https://doi.org/10.5194/acp-9-2843-2009, 2009.
Freitas, S. R., Longo, K. M., Silva Dias, M. A. F., Silva Dias, P. L., Chatfield, R., Prins, E., Artaxo, P., Grell, G. A., and Recuero, F. S.: Monitoring the transport of biomass burning emissions in South America, Environ. Fluid Mech., 5, 135–167, https://doi.org/10.1007/s10652-005-0243-7, 2005.
Freitas, S. R., Rodrigues, L. F., Longo, K. M., and Panetta, J.: Impact of a monotonic advection scheme with low numerical diffusion on transport modeling of emissions from biomass burning, J. Adv. Model. Earth Syst., 4, M01001, https://doi.org/10.1029/2011MS000084, 2012.
Gatti, L. V., Miller, J. B., D'Amelio, M. T. S., Martinewski, A., Basso, L. S., Gloor, M. E., Wofsy, S., and Tans, P.: Vertical profiles of CO2 above eastern Amazonia suggest a net carbon flux to the atmosphere and balanced biosphere between 2000 and 2009, Tellus B, 62, 581–594, https://doi.org/10.1111/j.1600-0889.2010.00484.x, 2010.
Gedney, N., Cox, P. M., Betts, R. A., Boucher, O., Huntingford, C., and Stott, P. A.: Detection of a direct carbon dioxide effect in continental river runoff records, Nature, 439, 835–838, https://doi.org/10.1038/nature04504, 2006.
Gesch, D. B., Verdin, K. L., and Greenlee, S. K.: New land surface digital elevation model covers the Earth, EOS T. Am. Geophys. Un., 80, 69–70, 1999.
Gevaerd, R. and Freitas, S. R.: Estimativa operacional da umidade do solo para inicializaçãao de modelos de previssão numérica da atmosfera. Parte I: Descrição da metodologia e validação, Revista Brasileira de Meteorologia, 21, 1–15, 2006 (in Brazil).
Gregory, D. and Smith, R. N. B.: Canopy, Surface and Soil Hydrology, Unified Model Documentation Paper 25, Meteorological Office, London Rd, Bracknell, Berkshire, RG12 2SY, 1990.
Grell, G. A. and Dévényi, D.: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques, Geophys. Res. Lett., 29, 38-1–38-4, https://doi.org/10.1029/2002GL015311, 2002.
Hughes, J. K., Valdes, P. J., and Betts, R.: Dynamics of a global-scale vegetation model, Ecol. Model., 198, 452–462, 2006.
Jacobs, C. M. J.: Direct impact of atmospheric CO2 enrichment on regional transpiration, Ph.D. thesis, Department of Meteorology, Wageningen Agricultural University, the Netherlands, 179 pp., 1994.
Kaufman, Y. J.: Remote sensing of direct and indirect aerosol forcing, in: Aerosol Forcing of Climate, edited by: Charlson, R. J. and Heintzenberg, J., John Wiley & Sons, New York, 297–332, 1995.
Keeling, C. D.: Climate change and carbon dioxide: an introduction, P. Natl. Acad. Sci. USA, 94, 8273–8274, 1997.
Koren, I., Kaufman, Y. J., Remer, L. A., and Martins, J. V.: Measurement of the effect of Amazon smoke on inhibition of cloud formation, Science, 303, 1342–1345, https://doi.org/10.1126/science.1089424, 2004.
Krol, M., Houweling, S., Bregman, B., van den Broek, M., Segers, A., van Velthoven, P., Peters, W., Dentener, F., and Bergamaschi, P.: The two-way nested global chemistry-transport zoom model TM5: algorithm and applications, Atmos. Chem. Phys., 5, 417–432, https://doi.org/10.5194/acp-5-417-2005, 2005.
Longo, K. M., Freitas, S. R., Andreae, M. O., Setzer, A., Prins, E., and Artaxo, P.: The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) – Part 2: Model sensitivity to the biomass burning inventories, Atmos. Chem. Phys., 10, 5785–5795, https://doi.org/10.5194/acp-10-5785-2010, 2010.
Longo, K. M., Freitas, S. R., Pirre, M., Marécal, V., Rodrigues, L. F., Panetta, J., Alonso, M. F., Rosário, N. E., Moreira, D. S., Gácita, M. S., Fonseca, R., Stockler, R., Katsurayama, D. M., Fazenda, A., and Bela, M.: The chemistry CATT-BRAMS model (CCATT-BRAMS 4.5): a regional atmospheric model system for integrated air quality and weather forecasting and research, Geosci. Model Dev. Discuss., 6, 1173–1222, https://doi.org/10.5194/gmdd-6-1173-2013, 2013.
Meesters, A. G. C. A., Tolk, L. F., and Dolman, A. J.: Mass conservation above slopes in the Regional Atmospheric Modelling System (RAMS), Environ. Fluid Mech., 8, 239–248, https://doi.org/10.1007/s10652-008-9072-9, 2008.
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys., 20, 851–875, https://doi.org/10.1029/RG020i004p00851, 1982.
Mercado, L. M., Bellouin, N., Sitch, S., Boucher, O., Huntingford, C., Wild, M., and Cox, P. M.: Impact of changes in diffuse radiation on the global land carbon sink, Nature, 458, 1014–1017, https://doi.org/10.1038/nature07949, 2009.
Mercado, L. M., Huntingford, C., Gash, J. H. C., Cox, P. M., and Jogireddy, V.: Improving the representation of radiation interception and photosynthesis for climate model applications, Tellus B, 59, 553–565, https://doi.org/10.1111/j.1600-0889.2007.00256.x, 2007.
Olson, J. S.: Global Ecosystem Framework-Definitions, USGS EROS Data Center Internal Report, Sioux Falls, 37 pp., 1994.
Peters, W., Jacobson, A. R., Sweeney, C., Andrews, A. E., Conway, T. J., Masarie, K., Miller, J. B., Bruhwiler, L. M. P., Pétron, G., Hirsch, A. I., Worthy, D. E. J., van der Werf, G. R., Randerson, J. T., Wennberg, P. O., Krol, M. C., and Tans, P. P.: An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker, P. Natl. Acad. Sci. USA, 104, 18925–18930, https://doi.org/10.1073/pnas.0708986104, 2007.
Prins, E. M., Feltz, J. M., Menzel, W. P., and Ward, D. E.: An overview of GOES-8 diurnal fire and smoke results for SCAR-B and 1995 fire season in South America, J. Geophys. Res., 103, 31821–31835, https://doi.org/10.1029/98JD01720, 1998.
Procopio, A. S., Remer, L. A., Artaxo, P., Kaufman, Y. J., and Holben, B. N.: Modeled spectral optical properties for smoke aerosols in Amazonia, Geophys. Res. Lett., 30, 2265, https://doi.org/10.1029/2003GL018063, 2003.
Reid, J. S., Hobbs, P. V., Ferek, R. J., Blake, D. R., Martins, J. V., Dunlap, M. R., and Liousse, C.: Physical, chemical, and optical properties of regional hazes dominated by smoke in Brazil, J. Geophys. Res., 103, 32059–32080, https://doi.org/10.1029/98JD00458, 1998.
Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C., and Wang, W.: An improved in situ and satellite SST analysis for climate, J. Climate, 15, 1609–1625, https://doi.org/10.1175/1520-0442(2002)0152.0.CO;2, 2002.
Rosário, N. E., Longo, K. M., Freitas, S. R., Yamasoe, M. A., and Fonseca, R. M.: Modeling the South American regional smoke plume: aerosol optical depth variability and surface shortwave flux perturbation, Atmos. Chem. Phys., 13, 2923–2938, https://doi.org/10.5194/acp-13-2923-2013, 2013.
Rosenfeld, D.: TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall, Geophys. Res. Lett., 26, 3105–3108, 1999.
Rossato, L, Alvalá, R. C. S., and Tomasella, J.: Distribuição geográfica da capacidade de armazenamento de água e das propriedades físicas do solo no Brasil, in: X Congresso Brasileiro de Meteorologia/VIII Congresso da FLISMET, Brasília, DF, Brazil, 1998 (in Portuguese).
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics – from Air Pollution to Climate Change, 2nd Edn., ISSN: 978-0-471-72018-8, John Wiley & Sons, New York, 1998.
Sestini, M. F., Reimer, E. S., Valeriano, D. M., Alvalá, R. C. S., Mello, E. M. K., Chan, C. S., and Nobre, C. A.: Mapa de cobertura da terra da Amazônia legal para uso em modelos meteorológicos, Simpósio Brasileiro de Sensoriamento Remoto, 11, 2901–2906, 2003 (in Portuguese).
Sitch, S., Cox, P. M., Collins, W. J., and Huntingford, C.: Indirect radiative forcing of climate change through ozone effects on the land-carbon sink, Nature, 448, 791–794, https://doi.org/10.1038/nature06059, 2007.
Souza, E. P.: Estudo Teórico e Numérico da Relaçãao entre Convecção e Superfícies Heterogêneas na Região Amazônica, Ph.D. thesis, DCA/IAG, São Paulo University (USP), São Paulo, SP, Brazil, 1999 (in Portuguese).
Toon, O. B., Turco, R. P., Westphal, D., Malone, R., and Liu, M.: A multidimensional model for aerosols: description of computational analogs, J. Atmos. Sci., 45, 2123–2144, https://doi.org/10.1175/1520-0469(1988)0452.0.CO;2, 1988.
Tremback, C. J., Powell, J., Cotton, W. R., and Pielke, R. A.: The forward-in-time upstream advection scheme: extension to higher orders, Mon. Weather Rev., 115, 540–555, https://doi.org/10.1175/1520-0493(1987)1152.0.CO;2, 1987.
Tripoli, G. J. and Cotton, W. R.: The Colorado State University three-dimensional cloud mesoscale model, 1982: Part I: General theoretical framework and sensitivity experiments, Journal de Recherches Atmosphériques, 16, 185–220, 1982.
Walko, R., Band, L., Baron, J., Kittel, F., Lammers, R., Lee, T., Ojima, D., Pielke, R., Taylor, C., Tague, C., Tremback, C., and Vidale, P.: Coupled atmosphere–biophysics–hydrology models for environmental modeling, J. Appl. Meteorol., 39, 931–944, 2000.
Wesley, M. L.: Parameterization of surface resistance to gaseous dry deposition in regional numerical models, Atmos. Environ., 16, 1293–1304, 1989.
Xu, J.-Yu and Zhong, Q.: The Effect of Error Growth and Propagation on the Predictability of Quantitative Precipitation in a Cloud-Resolving Model, Atmos. Ocean. Sci. Lett., 2, 79–84, 2009.
Yamasoe, M. A., von Randow, C., Manzi, A. O., Schafer, J. S., Eck, T. F., and Holben, B. N.: Effect of smoke and clouds on the transmissivity of photosynthetically active radiation inside the canopy, Atmos. Chem. Phys., 6, 1645–1656, https://doi.org/10.5194/acp-6-1645-2006, 2006.
Yang, Z. L., Dickinson, R. E., Henderson-Sellers, A., and Pitman, A. J.: Preliminary study of spin-up processes in land surface models with the first stage data of Project for Intercomparison of Land Surface Parameterization Schemes Phase 1(a), J. Geophys. Res., 100, 16553–16578, https://doi.org/10.1029/95JD01076, 1995.
Zhang, F., Odins, A. M., and Nielsen-Gammon, J. W.: : Mesoscale Predictability of an Extreme Warm-Season Precipitation Event, Weather Forecast., 21, 149–166, https://doi.org/10.1175/WAF909.1, 2006.
Zobler, L.: Global Soil Types, 1-Degree Grid (Zobler), data set, available at: http://www.daac.ornl.gov from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA, last access: 7 December 2012, https://doi.org/10.3334/ORNLDAAC/418, 1999.
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