Development and technical paper 17 Nov 2015
Development and technical paper | 17 Nov 2015
A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP)
N. Kljun et al.
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We present an ecological model called SPEAD where various phytoplankton compete for a nutrient. Phytoplankton in SPEAD is characterized by two continuously distributed traits: optimal temperature and nutrient half-saturation. Trait diversity is sustained by allowing the traits to mutate at each generation. We showed that SPEAD agreed well with a more classical discrete model for only a fraction of its cost. We also identified realistic values for the mutation rates, to be used in future models.
Christopher T. Reinhard, Stephanie L. Olson, Sandra Kirtland Turner, Cecily Pälike, Yoshiki Kanzaki, and Andy Ridgwell
Geosci. Model Dev., 13, 5687–5706, https://doi.org/10.5194/gmd-13-5687-2020, https://doi.org/10.5194/gmd-13-5687-2020, 2020
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We provide documentation and testing of new developments for the oceanic and atmospheric methane cycles in the cGENIE Earth system model. The model is designed to explore Earth's methane cycle across a wide range of timescales and scenarios, in particular assessing the mean climate state and climate perturbations in Earth's deep past. We further document the impact of atmospheric oxygen levels and ocean chemistry on fluxes of methane to the atmosphere from the ocean biosphere.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
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We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Petra Lasch-Born, Felicitas Suckow, Christopher P. O. Reyer, Martin Gutsch, Chris Kollas, Franz-Werner Badeck, Harald K. M. Bugmann, Rüdiger Grote, Cornelia Fürstenau, Marcus Lindner, and Jörg Schaber
Geosci. Model Dev., 13, 5311–5343, https://doi.org/10.5194/gmd-13-5311-2020, https://doi.org/10.5194/gmd-13-5311-2020, 2020
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The process-based model 4C has been developed to study climate impacts on forests and is now freely available as an open-source tool. This paper provides a comprehensive description of the 4C version (v2.2) for scientific users of the model and presents an evaluation of 4C. The evaluation focused on forest growth, carbon water, and heat fluxes. We conclude that 4C is widely applicable, reliable, and ready to be released to the scientific community to use and further develop the model.
Christian Seiler, Joe R. Melton, Vivek K. Arora, and Libo Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-294, https://doi.org/10.5194/gmd-2020-294, 2020
Revised manuscript accepted for GMD
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This study evaluates how well the CLASSIC Land Surface Model reproduces the energy, water, and carbon cycle when compared to a wide range of global observations. Special attention is paid to how uncertainties in the data used to drive and evaluate the model affect model skill. Our results show the importance of incorporating uncertainties when evaluating land surface models, and that failing to do so may potentially misguide future model development.
Zhengang Wang, Jianxiu Qiu, and Kristof Van Oost
Geosci. Model Dev., 13, 4977–4992, https://doi.org/10.5194/gmd-13-4977-2020, https://doi.org/10.5194/gmd-13-4977-2020, 2020
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This study developed a spatially distributed carbon cycling model applicable in an eroding landscape. It includes all three carbon isotopes so that it is able to represent the carbon isotopic compositions. The model is able to represent the observations that eroding area is enriched in 13C and depleted of 14C compared to depositional area. Our simulations show that the spatial variability of carbon isotopic properties in an eroding landscape is mainly caused by the soil redistribution.
Yuan Zhang, Olivier Boucher, Philippe Ciais, Laurent Li, and Nicolas Bellouin
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-267, https://doi.org/10.5194/gmd-2020-267, 2020
Revised manuscript accepted for GMD
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We investigated different methods to reconstruct spatio-temporal distribution of the fraction of diffuse radiation (Fdf) to qualtify the aerosol impacts on GPP using ORCHIDEE_DF land surface model. We find that climatologically-averaging methods which dampens the variability of Fdf can cause significant bias in the modeled diffuse radiation impacts on GPP. Better methods to do the reconstruction of Fdf are recommended.
Alexey N. Shiklomanov, Michael C. Dietze, Istem Fer, Toni Viskari, and Shawn P. Serbin
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-324, https://doi.org/10.5194/gmd-2020-324, 2020
Revised manuscript accepted for GMD
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Airborne and satellite images are a great resource for calibrating and evaluating computer models of ecosystems. Typically, researchers derive ecosystem properties from these images and then compare model against these derived properties. Here, we present an alternative approach where we modify a model to predict what the satellite would see more directly. We then show how this approach can be used to calibrate model parameters using airborne data from forest sites in the northeast US.
Brian N. Bailey, María A. Ponce de León, and E. Scott Krayenhoff
Geosci. Model Dev., 13, 4789–4808, https://doi.org/10.5194/gmd-13-4789-2020, https://doi.org/10.5194/gmd-13-4789-2020, 2020
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Numerous models of plant radiation interception based on a range of assumptions are available in the literature, but the importance of each assumption is not well understood. In this work, we evaluate several assumptions common in simple models of radiation interception in canopies with widely spaced plants by comparing against a detailed 3-D model. This yielded a simple model based on readily measurable parameters that could accurately predict interception for a wide range of architectures.
Julius Vira, Peter Hess, Jeff Melkonian, and William R. Wieder
Geosci. Model Dev., 13, 4459–4490, https://doi.org/10.5194/gmd-13-4459-2020, https://doi.org/10.5194/gmd-13-4459-2020, 2020
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Mostly emitted by the agricultural sector, ammonia has an important role in atmospheric chemistry. We developed a model to simulate how ammonia emissions respond to changes in temperature and soil moisture, and we evaluated agricultural ammonia emissions globally. The simulated emissions agree with earlier estimates over many regions, but the results highlight the variability of ammonia emissions and suggest that emissions in warm climates may be higher than previously thought.
Emily Kyker-Snowman, William R. Wieder, Serita D. Frey, and A. Stuart Grandy
Geosci. Model Dev., 13, 4413–4434, https://doi.org/10.5194/gmd-13-4413-2020, https://doi.org/10.5194/gmd-13-4413-2020, 2020
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Microbes drive carbon (C) and nitrogen (N) transformations in soil, and soil models have started to include explicit microbial physiology and functioning to try to reduce uncertainty in soil–climate feedbacks. Here, we add N cycling to a microbially explicit soil C model and reproduce C and N dynamics in soil during litter decomposition across a range of sites. We discuss model-generated hypotheses about soil C and N cycling and highlight the need for landscape-scale model evaluation data.
Leonardo Calle and Benjamin Poulter
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-258, https://doi.org/10.5194/gmd-2020-258, 2020
Revised manuscript accepted for GMD
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We developed a model to simulate and track the age of ecosystems on Earth. We found that the effect of ecosystem age on net primary production and ecosystem respiration is as important as climate in large areas of every vegetated continent. The LPJ-wsl v2.0 age-class model simulates the upper limit of age-class distributions on Earth and represents another step forward towards understanding the role of demography in global ecosystems.
Jinxuan Chen, Christoph Gerbig, Julia Marshall, and Kai Uwe Totsche
Geosci. Model Dev., 13, 4091–4106, https://doi.org/10.5194/gmd-13-4091-2020, https://doi.org/10.5194/gmd-13-4091-2020, 2020
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One of the essential challenge for atmospheric CO2 forecasting is predicting CO2 flux variation on synoptic timescale. For CAMS CO2 forecast, a process-based vegetation model is used.
In this research we evaluate another type of model (i.e., the light-use-efficiency model VPRM), which is a data-driven approach and thus ideal for realistic estimation, on its ability of flux prediction. Errors from different sources are assessed, and overall the model is capable of CO2 flux prediction.
Yuma Sakai, Hideki Kobayashi, and Tomomichi Kato
Geosci. Model Dev., 13, 4041–4066, https://doi.org/10.5194/gmd-13-4041-2020, https://doi.org/10.5194/gmd-13-4041-2020, 2020
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Chlorophyll fluorescence is one of the energy release pathways of excess incident light in the photosynthetic process. The canopy-scale Sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf-level photosynthesis to global GPP, can be observed from satellites. We develop the three-dimensional Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind SIF emission from complex forest canopies.
Femke Lutz, Stephen Del Grosso, Stephen Ogle, Stephen Williams, Sara Minoli, Susanne Rolinski, Jens Heinke, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 13, 3905–3923, https://doi.org/10.5194/gmd-13-3905-2020, https://doi.org/10.5194/gmd-13-3905-2020, 2020
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Previous findings have shown deviations between the LPJmL5.0-tillage model and results from meta-analyses on global estimates of tillage effects on N2O emissions. By comparing model results with observational data of four experimental sites and outputs from field-scale DayCent model simulations, we show that advancing information on agricultural management, as well as the representation of soil moisture dynamics, improves LPJmL5.0-tillage and the estimates of tillage effects on N2O emissions.
Tingting Li, Yanyu Lu, Lingfei Yu, Wenjuan Sun, Qing Zhang, Wen Zhang, Guocheng Wang, Zhangcai Qin, Lijun Yu, Hailing Li, and Ran Zhang
Geosci. Model Dev., 13, 3769–3788, https://doi.org/10.5194/gmd-13-3769-2020, https://doi.org/10.5194/gmd-13-3769-2020, 2020
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Reliable models are required to estimate global wetland CH4 emissions, which are the largest and most uncertain source of atmospheric CH4. This paper evaluated CH4MODwetland and TEM models against CH4 measurements from different continents and wetland types. Based on best-model performance, we estimated 117–125 Tg yr−1 of global CH4 emissions from wetlands for the period 2000–2010. Efforts should be made to reduce estimate uncertainties for different wetland types and regions.
Jennifer E. Dentith, Ruza F. Ivanovic, Lauren J. Gregoire, Julia C. Tindall, and Laura F. Robinson
Geosci. Model Dev., 13, 3529–3552, https://doi.org/10.5194/gmd-13-3529-2020, https://doi.org/10.5194/gmd-13-3529-2020, 2020
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We have added a new tracer (13C) into the ocean of the FAMOUS climate model to study large-scale circulation and the marine carbon cycle. The model captures the large-scale spatial pattern of observations but the simulated values are consistently higher than observed. In the first instance, our new tracer is therefore useful for recalibrating the physical and biogeochemical components of the model.
Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P. Harrison, Sally Archibald, Dominique Bachelet, Matthew Forrest, Thomas Hickler, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Lars Nieradzik, Sam S. Rabin, I. Colin Prentice, Tim Sheehan, Stephen Sitch, Lina Teckentrup, Apostolos Voulgarakis, and Chao Yue
Geosci. Model Dev., 13, 3299–3318, https://doi.org/10.5194/gmd-13-3299-2020, https://doi.org/10.5194/gmd-13-3299-2020, 2020
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Global fire–vegetation models are widely used, but there has been limited evaluation of how well they represent various aspects of fire regimes. Here we perform a systematic evaluation of simulations made by nine FireMIP models in order to quantify their ability to reproduce a range of fire and vegetation benchmarks. While some FireMIP models are better at representing certain aspects of the fire regime, no model clearly outperforms all other models across the full range of variables assessed.
Yifei Dai, Long Cao, and Bin Wang
Geosci. Model Dev., 13, 3119–3144, https://doi.org/10.5194/gmd-13-3119-2020, https://doi.org/10.5194/gmd-13-3119-2020, 2020
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NESM v3 is one of the CMIP6 registered Earth system models. We evaluate its ocean carbon cycle component and present its present-day and future oceanic CO2 uptake based on the CMIP6 historical and SSP5–8.5 scenarios. We hope that this paper can serve as a documentation of the marine biogeochemical cycle in NESM v3. Also, the model defects found and their underlying causes analyzed in this paper could help users and further model development.
Joe R. Melton, Vivek K. Arora, Eduard Wisernig-Cojoc, Christian Seiler, Matthew Fortier, Ed Chan, and Lina Teckentrup
Geosci. Model Dev., 13, 2825–2850, https://doi.org/10.5194/gmd-13-2825-2020, https://doi.org/10.5194/gmd-13-2825-2020, 2020
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We transitioned the CLASS-CTEM land surface model to an open-source community model format by modernizing the code base to make the model easier to use and understand, providing a complete software environment to run the model within, developing a benchmarking suite for model evaluation, and creating an infrastructure to support community involvement. The new model, the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC), is now available for the community to use and develop.
Magnus Dahler Norling, Leah Amber Jackson-Blake, José-Luis Guerrero Calidonio, and James Edward Sample
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-26, https://doi.org/10.5194/gmd-2020-26, 2020
Revised manuscript accepted for GMD
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In order for researchers to more quickly prototype and build models of natural systems we have created the Mobius framework. Such models can for instance be used to ask questions about what the impacts of land use changes are to water quality in a river or lake, or the response of biological systems to climate change etc. The Mobius framework makes it quick to build models that run fast, which enables the user to explore many different scenarios and model formulations.
Giovanni Denaro, Daniela Salvagio Manta, Alessandro Borri, Maria Bonsignore, Davide Valenti, Enza Quinci, Andrea Cucco, Bernardo Spagnolo, Mario Sprovieri, and Andrea De Gaetano
Geosci. Model Dev., 13, 2073–2093, https://doi.org/10.5194/gmd-13-2073-2020, https://doi.org/10.5194/gmd-13-2073-2020, 2020
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The HR3DHG (high-resolution 3D mercury model) investigates the spatiotemporal behavior, in seawater and marine sediments, of three mercury species (elemental, inorganic, and organic mercury) in a highly polluted marine environment (Augusta Bay, southern Italy). The model shows fair agreement with the experimental data collected during six different oceanographic cruises and can possibly be used for a detailed exploration of the effects of climate change on mercury distribution.
Elisa Lovecchio and Timothy M. Lenton
Geosci. Model Dev., 13, 1865–1883, https://doi.org/10.5194/gmd-13-1865-2020, https://doi.org/10.5194/gmd-13-1865-2020, 2020
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We present here the newly developed BPOP box model. BPOP is aimed at studying the impact of large-scale changes in the biological pump, i.e. the cycle of production, export and remineralization of the marine organic matter, on the nutrient and oxygen concentrations in the shelf and open ocean. This model has been developed to investigate the global consequences of the evolution of larger and heavier phytoplankton cells but can be applied to a variety of past and future case studies.
Benjamin D. Stocker, Han Wang, Nicholas G. Smith, Sandy P. Harrison, Trevor F. Keenan, David Sandoval, Tyler Davis, and I. Colin Prentice
Geosci. Model Dev., 13, 1545–1581, https://doi.org/10.5194/gmd-13-1545-2020, https://doi.org/10.5194/gmd-13-1545-2020, 2020
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Estimating terrestrial photosynthesis relies on satellite data of vegetation cover and models simulating the efficiency by which light absorbed by vegetation is used for CO2 assimilation. This paper presents the P-model, a light use efficiency model derived from a carbon–water optimality principle, and evaluates its predictions of ecosystem-level photosynthesis against globally distributed observations. The model is implemented and openly accessible as an R package (rpmodel).
Louis de Wergifosse, Frédéric André, Nicolas Beudez, François de Coligny, Hugues Goosse, François Jonard, Quentin Ponette, Hugues Titeux, Caroline Vincke, and Mathieu Jonard
Geosci. Model Dev., 13, 1459–1498, https://doi.org/10.5194/gmd-13-1459-2020, https://doi.org/10.5194/gmd-13-1459-2020, 2020
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Given their key role in the simulation of climate impacts on tree growth, phenological and water balance processes must be integrated in models simulating forest dynamics under a changing environment. Here, we describe these processes integrated in HETEROFOR, a model accounting simultaneously for the functional, structural and spatial complexity to explore the forest response to forestry practices. The model evaluation using phenological and soil water content observations is quite promising.
Arjun Chakrawal, Anke M. Herrmann, John Koestel, Jerker Jarsjö, Naoise Nunan, Thomas Kätterer, and Stefano Manzoni
Geosci. Model Dev., 13, 1399–1429, https://doi.org/10.5194/gmd-13-1399-2020, https://doi.org/10.5194/gmd-13-1399-2020, 2020
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Soils are heterogeneous, which results in a nonuniform spatial distribution of substrates and the microorganisms feeding on them. Our results show that the variability in the spatial distribution of substrates and microorganisms at the pore scale is crucial because it affects how fast substrates are used by microorganisms and thus the decomposition rate observed at the soil core scale. This work provides a methodology to include microscale heterogeneity in soil carbon cycling models.
Victoria Naipal, Ronny Lauerwald, Philippe Ciais, Bertrand Guenet, and Yilong Wang
Geosci. Model Dev., 13, 1201–1222, https://doi.org/10.5194/gmd-13-1201-2020, https://doi.org/10.5194/gmd-13-1201-2020, 2020
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In this study we present the Carbon Erosion DYNAMics model (CE-DYNAM) that links sediment dynamics resulting from water erosion with the soil carbon cycle along a cascade of hillslopes, floodplains, and rivers. The model can simulate the removal of soil and carbon from eroding areas and their destination at regional scale. We calibrated and validated the model for the Rhine catchment, and we show that soil erosion is a potential large net carbon sink over the period 1850–2005.
Kelly Kearney, Albert Hermann, Wei Cheng, Ivonne Ortiz, and Kerim Aydin
Geosci. Model Dev., 13, 597–650, https://doi.org/10.5194/gmd-13-597-2020, https://doi.org/10.5194/gmd-13-597-2020, 2020
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We describe an ecosystem model for the Bering Sea. Biological components in the Bering Sea can be found in the water column, on and within the bottom sediments, and within the porous lower layer of seasonal sea ice. This model simulates the exchange of material between nutrients and plankton within all three environments. Here, we thoroughly document the model and assess its skill in capturing key biophysical features across the Bering Sea.
Matthias J. R. Speich, Massimiliano Zappa, Marc Scherstjanoi, and Heike Lischke
Geosci. Model Dev., 13, 537–564, https://doi.org/10.5194/gmd-13-537-2020, https://doi.org/10.5194/gmd-13-537-2020, 2020
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Climate change is expected to substantially affect natural processes, and simulation models are a valuable tool to anticipate these changes. In this study, we combine two existing models that each describe one aspect of the environment: forest dynamics and the terrestrial water cycle. The coupled model better described observed patterns in vegetation structure. We also found that including the effect of water availability on tree height and rooting depth improved the model.
Simon P. K. Bowring, Ronny Lauerwald, Bertrand Guenet, Dan Zhu, Matthieu Guimberteau, Pierre Regnier, Ardalan Tootchi, Agnès Ducharne, and Philippe Ciais
Geosci. Model Dev., 13, 507–520, https://doi.org/10.5194/gmd-13-507-2020, https://doi.org/10.5194/gmd-13-507-2020, 2020
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In this second part of the study, we performed simulations of the carbon and water budget of the Lena catchment with the land surface model ORCHIDEE MICT-LEAK, enabled to simulate dissolved organic carbon (DOC) production in soils and its transport and fate in high-latitude inland waters. We compare simulations using this model to existing data sources to show that it is capable of reproducing dissolved carbon fluxes of potentially great importance for the future of the global permafrost.
Carme Font, Francesco Bregoli, Vicenç Acuña, Sergi Sabater, and Rafael Marcé
Geosci. Model Dev., 12, 5213–5228, https://doi.org/10.5194/gmd-12-5213-2019, https://doi.org/10.5194/gmd-12-5213-2019, 2019
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GLOBAL-FATE is an open-source, multiplatform, and flexible model that simulates the fate of pharmaceutical-like compounds in the global river network. The model considers the consumption of pharmaceuticals by humans, differentiates between pharmaceutical load treated in wastewater treatment plants from that directly delivered to streams and rivers, and integrates lakes and reservoirs in calculations. GLOBAL-FATE is a powerful tool for pollutant impact studies at the global scale.
Luke Gregor, Alice D. Lebehot, Schalk Kok, and Pedro M. Scheel Monteiro
Geosci. Model Dev., 12, 5113–5136, https://doi.org/10.5194/gmd-12-5113-2019, https://doi.org/10.5194/gmd-12-5113-2019, 2019
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The ocean plays a vital role in mitigating climate change by taking up atmospheric carbon dioxide (CO2). Historically sparse ship-based measurements of surface ocean CO2 make direct estimates of CO2 exchange changes unreliable. We introduce a machine-learning ensemble approach to fill these observational gaps. Our method performs incrementally better relative to past methods, leading to our hypothesis that we are perhaps reaching the limitation of machine-learning algorithms' capability.
Markus Drüke, Matthias Forkel, Werner von Bloh, Boris Sakschewski, Manoel Cardoso, Mercedes Bustamante, Jürgen Kurths, and Kirsten Thonicke
Geosci. Model Dev., 12, 5029–5054, https://doi.org/10.5194/gmd-12-5029-2019, https://doi.org/10.5194/gmd-12-5029-2019, 2019
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This work shows the successful application of a systematic model–data integration setup, as well as the implementation of a new fire danger formulation, in order to optimize a process-based fire-enabled dynamic global vegetation model. We have demonstrated a major improvement in the fire representation within LPJmL4-SPITFIRE in terms of the spatial pattern and the interannual variability of burned area in South America as well as in the modelling of biomass and the distribution of plant types.
Nicolas Vuichard, Palmira Messina, Sebastiaan Luyssaert, Bertrand Guenet, Sönke Zaehle, Josefine Ghattas, Vladislav Bastrikov, and Philippe Peylin
Geosci. Model Dev., 12, 4751–4779, https://doi.org/10.5194/gmd-12-4751-2019, https://doi.org/10.5194/gmd-12-4751-2019, 2019
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In this research, we present a new version of the global terrestrial ecosystem model ORCHIDEE in which carbon and nitrogen cycles are coupled. We evaluate its skills at simulating primary production at 78 sites and at a global scale. Based on a set of additional simulations in which carbon and nitrogen cycles are coupled and uncoupled, we show that the functional responses of the model with carbon–nitrogen interactions better agree with our current understanding of photosynthesis.
Tea Thum, Silvia Caldararu, Jan Engel, Melanie Kern, Marleen Pallandt, Reiner Schnur, Lin Yu, and Sönke Zaehle
Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, https://doi.org/10.5194/gmd-12-4781-2019, 2019
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To predict the response of the vegetation to climate change, we need global models that describe the relevant processes taking place in the vegetation. Recently, we have obtained more in-depth understanding of vegetation processes and the role of nutrients in the biogeochemical cycles. We have developed a new global vegetation model that includes carbon, water, nitrogen, and phosphorus cycles. We show that the model is successful in evaluation against a wide range of observations.
Dave van Wees and Guido R. van der Werf
Geosci. Model Dev., 12, 4681–4703, https://doi.org/10.5194/gmd-12-4681-2019, https://doi.org/10.5194/gmd-12-4681-2019, 2019
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For this paper, a novel high spatial-resolution fire emission model based on the Global Fire Emissions Database (GFED) modelling framework was developed and compared to a coarser-resolution version of the same model. Our findings highlight the importance of fine spatial resolution when modelling global-scale fire emissions, especially considering the comparison of model pixels to individual field measurements and the model representation of heterogeneity in the landscape.
Yoshiki Kanzaki, Bernard P. Boudreau, Sandra Kirtland Turner, and Andy Ridgwell
Geosci. Model Dev., 12, 4469–4496, https://doi.org/10.5194/gmd-12-4469-2019, https://doi.org/10.5194/gmd-12-4469-2019, 2019
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This paper provides eLABS, an extension of the lattice-automaton bioturbation simulator LABS. In our new model, the benthic animal behavior interacts and changes dynamically with oxygen and organic matter concentrations and the water flows caused by benthic animals themselves, in a 2-D marine-sediment grid. The model can address the mechanisms behind empirical observations of bioturbation based on the interactions between physical, chemical and biological aspects of marine sediment.
Marcos Longo, Ryan G. Knox, David M. Medvigy, Naomi M. Levine, Michael C. Dietze, Yeonjoo Kim, Abigail L. S. Swann, Ke Zhang, Christine R. Rollinson, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4309–4346, https://doi.org/10.5194/gmd-12-4309-2019, https://doi.org/10.5194/gmd-12-4309-2019, 2019
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Our paper describes the Ecosystem Demography model. This computer program calculates how plants and ground exchange heat, water, and carbon with the air, and how plants grow, reproduce and die in different climates. Most models simplify forests to an average big tree. We consider that tall, deep-rooted trees get more light and water than small plants, and that some plants can with shade and drought. This diversity helps us to better explain how plants live and interact with the atmosphere.
Marcos Longo, Ryan G. Knox, Naomi M. Levine, Abigail L. S. Swann, David M. Medvigy, Michael C. Dietze, Yeonjoo Kim, Ke Zhang, Damien Bonal, Benoit Burban, Plínio B. Camargo, Matthew N. Hayek, Scott R. Saleska, Rodrigo da Silva, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4347–4374, https://doi.org/10.5194/gmd-12-4347-2019, https://doi.org/10.5194/gmd-12-4347-2019, 2019
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The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates. To test if our calculations were reasonable, we compared our results with field and satellite measurements. Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air. However, it must improve the tree growth rates and how fast dead plants decompose.
Elias C. Massoud, Chonggang Xu, Rosie A. Fisher, Ryan G. Knox, Anthony P. Walker, Shawn P. Serbin, Bradley O. Christoffersen, Jennifer A. Holm, Lara M. Kueppers, Daniel M. Ricciuto, Liang Wei, Daniel J. Johnson, Jeffrey Q. Chambers, Charlie D. Koven, Nate G. McDowell, and Jasper A. Vrugt
Geosci. Model Dev., 12, 4133–4164, https://doi.org/10.5194/gmd-12-4133-2019, https://doi.org/10.5194/gmd-12-4133-2019, 2019
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We conducted a comprehensive sensitivity analysis to understand behaviors of a demographic vegetation model within a land surface model. By running the model 5000 times with changing input parameter values, we found that (1) the photosynthetic capacity controls carbon fluxes, (2) the allometry is important for tree growth, and (3) the targeted carbon storage is important for tree survival. These results can provide guidance on improved model parameterization for a better fit to observations.
Jarmo Mäkelä, Jürgen Knauer, Mika Aurela, Andrew Black, Martin Heimann, Hideki Kobayashi, Annalea Lohila, Ivan Mammarella, Hank Margolis, Tiina Markkanen, Jouni Susiluoto, Tea Thum, Toni Viskari, Sönke Zaehle, and Tuula Aalto
Geosci. Model Dev., 12, 4075–4098, https://doi.org/10.5194/gmd-12-4075-2019, https://doi.org/10.5194/gmd-12-4075-2019, 2019
Short summary
Short summary
We assess the differences of six stomatal conductance formulations, embedded into a land–vegetation model JSBACH, on 10 boreal coniferous evergreen forest sites. We calibrate the model parameters using all six functions in a multi-year experiment, as well as for a separate drought event at one of the sites, using the adaptive population importance sampler. The analysis reveals weaknesses in the stomatal conductance formulation-dependent model behaviour that we are able to partially amend.
Cited articles
Aubinet, M., Chermanne, B., Vandenhaute, M., Longdoz, B., Yernaux, M., and Laitat, E.: Long Term Carbon Dioxide Exchange Above a Mixed Forest in the Belgian Ardennes, Agr. Forest Meteorol., 108, 293–315, 2001.
Baldocchi, D.: Flux Footprints Within and Over Forest Canopies, Bound.-Lay. Meteorol., 85, 273–292, 1997.
Barcza, Z., Kern, A., Haszpra, L., and Kljun, N.: Spatial Representativeness of Tall Tower Eddy Covariance Measurements Using Remote Sensing and Footprint Analysis, Agr. Forest Meteorol., 149, 795–807, 2009.
Batchvarova, E. and Gryning, S.-E.: Applied Model for the Growth of the Daytime Mixed Layer, Bound.-Lay. Meteorol., 56, 261–274, 1991.
Chang, J. C. and Hanna, S. R.: Air Quality Model Performance Evaluation, Meteorol. Atmos. Phys., 87, 167–196, 2004.
Chasmer, L., Kljun, N., Barr, A., Black, A., Hopkinson, C., McCaughey, J., and Treitz, P.: Influences of Vegetation Structure and Elevation on CO2 Uptake in a Mature Jack Pine Forest in Saskatchewan, Canada, Can. J. Forest Res., 38, 2746–2761, 2008.
Chasmer, L., Barr, A. G., Hopkinson, C., McCaughey, J. H., Treitz, P., Black, T. A., and Shashkov, A.: Scaling and Assessment of GPP from MODIS Using a Combination of Airborne Lidar and Eddy Covariance Measurements over Jack Pine Forests, Remote Sens. Environ., 113, 82–93, 2009.
Deardorff, J. W. and Willis, G. E.: A Parameterization of Diffusion into the Mixed Layer, J. Appl. Meteor., 14, 1451–1458, 1975.
de Haan, P. and Rotach, M. W.: A Novel Approach to Atmospheric Dispersion Modelling: the Puff-Particle Model (PPM), Q. J. Roy. Meteorol. Soc., 124, 2771–2792, 1998.
Detto, M., Montaldo, N., Albertson, J. D., Mancini, M., and Katul, G.: Soil Moisture and Vegetation Controls on Evapotranspiration in a Heterogeneous Mediterranean Ecosystem on Sardinia, Italy, Water Resour. Res., 42, W08419, https://doi.org/10.1029/2005WR004693, 2006.
Flesch, T. K.: The Footprint for Flux Measurements, from Backward Lagrangian Stochastic Models, Bound.-Lay. Meteorol., 78, 399–404, 1996.
Gelybó, G., Barcza, Z., Kern, A., and Kljun, N.: Effect of Spatial Heterogeneity on the Validation of Remote Sensing based GPP Estimations, Agr. Forest Meteorol., 174, 43–53, 2013.
Göckede, M., Foken, T., Aubinet, M., Aurela, M., Banza, J., Bernhofer, C., Bonnefond, J. M., Brunet, Y., Carrara, A., Clement, R., Dellwik, E., Elbers, J., Eugster, W., Fuhrer, J., Granier, A., Grünwald, T., Heinesch, B., Janssens, I. A., Knohl, A., Koeble, R., Laurila, T., Longdoz, B., Manca, G., Marek, M., Markkanen, T., Mateus, J., Matteucci, G., Mauder, M., Migliavacca, M., Minerbi, S., Moncrieff, J., Montagnani, L., Moors, E., Ourcival, J.-M., Papale, D., Pereira, J., Pilegaard, K., Pita, G., Rambal, S., Rebmann, C., Rodrigues, A., Rotenberg, E., Sanz, M. J., Sedlak, P., Seufert, G., Siebicke, L., Soussana, J. F., Valentini, R., Vesala, T., Verbeeck, H., and Yakir, D.: Quality control of CarboEurope flux data – Part 1: Coupling footprint analyses with flux data quality assessment to evaluate sites in forest ecosystems, Biogeosciences, 5, 433–450, https://doi.org/10.5194/bg-5-433-2008, 2008.
Grimmond, C. S. B. and Oke, T. R.: Aerodynamic Properties of Urban Areas Derived from Analysis of Surface Form, J. Appl. Meteorol., 38, 1262–1292, 1999.
Haenel, H.-D. and Grünhage, L.: Footprint Analysis: A Closed Analytical Solution Based on Height-Dependent Profiles of Wind Speed and Eddy Viscosity, Bound.-Lay. Meteorol., 93, 395–409, 1999.
Hanna, S. R. and Chang, J. C.: Hybrid Plume Dispersion Model (HPDM) Improvements and Testing at Three Field Sites, Atmos. Environ., 27A, 1491–1508, 1993.
Hanna, S. R., Chang, J. C., and Strimaitis, D. G.: Hazardous Gas Model Evaluation with Field Observations, Atmos. Environ., 27A, 2265–2281, 1993.
Hellsten, A., Luukkonen, S. M., Steinfeld, G., Kanani-Suhring, F., Markkanen, T., Järvi, L., Vesala , T., and Raasch, S.: Footprint Evaluation for Flux and Concentration Measurements for an Urban-like Canopy with Coupled Lagrangian Stochastic and Large-eddy Simulation Models, Bound.-Lay. Meteorol., 157, 191–217, 2015.
Högström, U.: Review of Some Basic Characteristics of the Atmospheric Surface Layer, Bound.-Lay. Meteorol., 78, 215–246, 1996.
Holtslag, A. A. M. and Nieuwstadt, F. T. M.: Scaling the Atmospheric Boundary-Layer, Bound.-Lay. Meteorol., 36, 201–209, 1986.
Horst, T. W. and Weil, J. C.: Footprint Estimation for Scalar Flux Measurements in the Atmospheric Surface Layer, Bound.-Lay. Meteorol., 59, 279–296, 1992.
Horst, T. W. and Weil, J. C.: How Far is Far Enough?: The Fetch Requirements for Micrometeorological Measurement of Surface Fluxes, J. Atmos. Ocean. Tech., 11, 1018–1025, 1994.
Hsieh, C. I., Katul, G., and Chi, T.: An Approximate Analytical Model for Footprint Estimation of Scalar Fluxes in Thermally Stratified Atmospheric Flows, Adv. Water Resour., 23, 765–772, 2000.
Hsieh, C. I., Siqueira, M., Katul, G., and Chu, C.-R.: Predicting Scalar Source-Sink and Flux Distributions Within a Forest Canopy Using a 2-D Lagrangian Stochastic Dispersion Model, Bound.-Lay. Meteorol., 109, 113–138, 2003.
Hutjes, R. W. A., Vellinga, O. S., Gioli, B., and Miglietta, F.: Dis-aggregation of Airborne Flux Measurements Using Footprint Analysis, Agr. Forest Meteorol., 150, 966–983, 2010.
Kim, J., Guo, Q., Baldocchi, D. D., Leclerc, M. Y., Xu, L., and Schmid, H. P.: Upscaling Fluxes from Tower to Landscape: Overlaying Flux Footprints on High-resolution (IKONOS) Images of Vegetation Cover, Agr. Forest Meteorol., 136, 132–146, 2006.
Kljun, N., Rotach, M. W., and Schmid, H. P.: A 3D Backward Lagrangian Footprint Model for a Wide Range of Boundary Layer Stratifications, Bound.-Lay. Meteorol., 103, 205–226, 2002.
Kljun, N., Kormann, R., Rotach, M. W., and Meixner, F. X.: Comparison of the L}agrangian Footprint Model {LPDM-B with an Analytical Footprint Model, Bound.-Lay. Meteorol., 106, 349–355, 2003.
Kljun, N., Kastner-Klein, P., Fedorovich, E., and Rotach, M. W.: Evaluation of Lagrangian Footprint Model Using Data from a Wind Tunnel Convective Boundary Layer, Agr. Forest Meteorol., 127, 189–201, 2004a.
Kljun, N., Rotach, M. W., and Calanca, P.: A Simple Parameterisation for Flux Footprint Predictions, Bound.-Lay. Meteorol., 112, 503–523, 2004b.
Kormann, R. and Meixner, F. X.: An Analytical Footprint Model for Non-Neutral Stratification, Bound.-Lay. Meteorol., 99, 207–224, 2001.
Kustas, W. P., Anderson, M. C., French, A. N., and Vickers, D.: Using a Remote Sensing Field Experiment to Investigate Flux-footprint Relations and Flux Sampling Distributions for Tower and Aircraft-based Observations, Adv. Water Resour., 29, 355–368, 2006.
Lagarias, J. C., Reeds, J. A., Wright, M. H., and Wright, P. E.: Convergence Properties of the Nelder-Mead Simplex Method in Low Dimensions, SIAM J. Optimiz., 9, 112–147, 1998.
Leclerc, M. Y. and Foken, T.: Footprints in Micrometeorology and Ecology, 1st Edn., Springer, Heidelberg, Germany, New York, USA, Dordrecht, the Netherlands, London, UK, 2014.
Leclerc, M. Y. and Thurtell, G. W.: Footprint Prediction of Scalar Fluxes Using a Markovian Analysis, Bound.-Lay. Meteorol., 52, 247–258, 1990.
Leclerc, M. Y., Shen, S., and Lamb, B.: Observations and Large-Eddy Simulation Modeling of Footprints in the Lower Convective Boundary Layer, J. Geophys. Res., 102, 9323–9334, 1997.
Li, F., Kustas, W. P., Anderson, M. C., Prueger, J. H., and Scott, R. L.: Effect of Remote Sensing Spatial Resolution on Interpreting Tower-based Flux Observations, Remote Sens. Environ., 112, 337–349, 2008.
Lindroth, A., Grelle, A., and Morén, A.-S.: Long-term Measurements of Boreal Forest Carbon Balance Reveal Large Temperature Sensitivity, Glob. Change Biol., 4, 443–450, 1998.
Luhar, A. K. and Rao, K. S.: Source Footprint Analysis for Scalar Fluxes Measured in Flows over an Inhomogeneous Surface, NATO Chal. M., 18, 315–322, 1994.
Markkanen, T., Steinfeld, G., Kljun, N., Raasch, S., and Foken, T.: Comparison of conventional Lagrangian stochastic footprint models against LES driven footprint estimates, Atmos. Chem. Phys., 9, 5575–5586, https://doi.org/10.5194/acp-9-5575-2009, 2009.
Mauder, M., Desjardins, R. L., and MacPherson, I.: Creating Surface Flux Maps from Airborne Measurements: Application to the Mackenzie Area GEWEX Study MAGS 1999, Bound.-Lay. Meteorol., 129, 431–450, 2008.
Mauder, M., Cuntz, M., Drüe, C., Graf, A., Rebmann, C., Schmid, H. P., Schmidt, M., and Steinbrecher, R.: A strategy for Quality and Uncertainty assessment of Long-term Eddy-covariance Measurements, Agr. Forest Meteorol., 169, 122–135, 2013.
Maurer, K. D., Hardiman, B. S., Vogel, C. S., and Bohrer, G.: Canopy-structure effects on surface roughness parameters: Observations in a Great Lakes mixed-deciduous forest, Agr. Forest Meteorol., 177, 24–34, 2013.
Metzger, S., Junkermann, W., Mauder, M., Beyrich, F., Butterbach-Bahl, K., Schmid, H. P., and Foken, T.: Eddy-covariance flux measurements with a weight-shift microlight aircraft, Atmos. Meas. Tech., 5, 1699–1717, https://doi.org/10.5194/amt-5-1699-2012, 2012.
Nagy, M. T., Janssens, I. A., Yuste, J. C., Carrara, A., and Ceulemans, R.: Footprint-adjusted Net Ecosystem CO2 Exchange and Carbon Balance Components of a Temperate Forest, Agr. Forest Meteorol., 139, 344–360, 2006.
Nieuwstadt, F. T. M.: Application of Mixed-Layer Similarity to the Observed Dispersion from a Ground-Level Source, J. Appl. Meteorol., 19, 157–162, 1980.
Nieuwstadt, F. T. M.: The Steady-state Height and Resistance Laws of the Nocturnal Boundary Layer: Theory Compared with Cabauw Observations, Bound.-Lay. Meteorol., 20, 3–17, 1981.
Pasquill, F. and Smith, F. B.: Atmospheric Diffusion, Ellis Horwood Limited, 3rd Edn., J. Wiley and Sons, New York, USA, 1983.
Rahman, A. F., Gamon, J. A., Fuentes, D. A., Roberts, D. A., and Prentiss, D.: Modeling Spatially Distributed Ecosystem Flux of Boreal Forest Using Hyperspectral Indices from AVIRIS Imagery, J. Geophys. Res.-Atmos., 106, 33579–33591, 2001.
Rannik, Ü., Aubinet, M., Kurbanmuradov, O., Sabelfeld, K. K., Markkanen, T., and Vesala, T.: Footprint Analysis for Measurements over a Heterogeneous Forest, Bound.-Lay. Meteorol., 97, 137–166, 2000.
Raupach, M. R., Antonia, R. A., and Rajagopalan, S.: Rough-Wall Turbulent Boundary Layers, Appl. Mech. Rev., 44, 1–25, 1991.
Rebmann, C., Göckede, M., Foken, T., Aubinet, M., Aurela, M., Berbigier, P., Bernhofer, C., Buchmann, N., Carrara, A., Cescatti, A., Ceulemans, R., Clement, R., Elbers, J. A., Granier, A., Grünwald, T., Guyon, D., Havránková, K., Heinesch, B., Knohl, A., Laurila, T., Longdoz, B., Marcolla, B., Markkanen, T., Miglietta, F., Moncrieff, K., Montagnani, L., Moors, E., Nardino, M., Ourcival, J.-M., Rambal, S., Rannik, Ü., Rotenberg, E., Sedlak, P., Unterhuber, G., Vesala, T., and Yakir, D.: Quality Analysis Applied on Eddy Covariance Measurements at Complex Forest Sites Using Footprint Modelling, Theor. Appl. Climatol., 80, 121–141, 2005.
Rotach, M. W.: Determination of the Zero Plane Displacement in an Urban Environment, Bound.-Lay. Meteorol., 67, 187–193, 1994.
Rotach, M. W. and Calanca, P.: Microclimate, in: Encyclopedia of Atmospheric Sciences, edited by: North, G. R., Vol. 1, 258–264, Academic Press, Elsevier Science Publishing Co. Inc., London, UK, 2nd Edn., 2014.
Rotach, M. W., Gryning, S.-E., and Tassone, C.: A Two-Dimensional Lagrangian Stochastic Dispersion Model for Daytime Conditions, Q. J. Roy. Meteorol. Soc., 122, 367–389, 1996.
Rotach, M. W., Gryning, S.-E., Batchvarova, E., Christen, A., and Vogt, R.: Pollutant Dispersion Close to an Urban Surface: the BUBBLE Tracer Experiment, Meteorol. Atmos. Phys., 87, 39–56, 2004.
Schmid, H. P.: Source Areas for Scalars and Scalar Fluxes, Bound.-Lay. Meteorol., 67, 293–318, 1994.
Schmid, H. P.: Experimental Design for Flux Measurements: Matching Scales of Observations and Fluxes, Agr. Forest Meteorol., 87, 179–200, 1997.
Schmid, H. P.: Footprint Modeling for Vegetation Atmosphere Exchange Studies: A Review and Perspective, Agr. Forest Meteorol., 113, 159–184, 2002.
Schmid, H. P. and Lloyd, C. R.: Spatial Representativeness and the Location Bias of Flux Footprints over Inhomogeneous Areas, Agr. Forest Meteorol., 93, 195–209, 1999.
Schmid, H. P. and Oke, T. R.: A Model to Estimate the Source Area Contributing to Turbulent Exchange in the Surface Layer over Patchy Terrain, Q. J. Roy. Meteorol. Soc., 116, 965–988, 1990.
Schuepp, P. H., Leclerc, M. Y., Macpherson, J. I., and Desjardins, R. L.: Footprint Prediction of Scalar Fluxes from Analytical Solutions of the Diffusion Equation, Bound.-Lay. Meteorol., 50, 355–373, 1990.
Seibert, P., Beyrich, F., Gryning, S.-E., Joffre, S., Rasmussen, A., and Tercier, P.: Review and Intercomparison of Operational Methods for the Determination of the Mixing Height, Atmos. Environ., 34, 1001–1027, 2000.
Sogachev, A. and Lloyd, J.: Using a One-And-a-Half Order Closure Model of the Atmospheric Boundary Layer for Surface Flux Footprint Estimation, Bound.-Lay. Meteorol., 112, 467–502, 2004.
Sogachev, A., Leclerc, M. Y., Karipot, A., Zhang, G., and Vesala, T.: Effect of Clearcuts on Footprints and Flux Measurements Above a Forest Canopy, Agr. Forest Meteorol., 133, 182–196, 2005.
Steinfeld, G., Raasch, S., and Markkanen, T.: Footprints in Homogeneously and Heterogeneously Driven Boundary Layers Derived from a Lagrangian Stochastic Particle Model Embedded into Large-Eddy Simulation, Bound.-Lay. Meteorol., 129, 225–248, 2008.
Stull, R. B.: An Introduction to Boundary Layer Meteorology, Kluwer Academic Publishers, Dordrecht, the Netherlands, 680 pp., 1988.
Sutherland, G., Chasmer, L. E., Petrone, R. M., Kljun, N., and Devito, K. J.: Evaluating the Use of Spatially Varying Versus Bulk Average 3D Vegetation Structural Inputs to Modelled Evapotranspiration Within Heterogeneous Land Cover Types, Ecohydrology, 7, 1545–1559, 2014.
Taylor, G. I.: Diffusion by Continuous Movements, P. Lond. Math. Soc., 20, 196–211, 1921.
Tennekes, H.: Similarity Laws and Scale Relations in Planetary Boundary Layers, in: Workshop on Micrometeorology, edited by: Haugen, D. A., Amer. Meteorol. Soc., Boston, USA, 1973.
Thomson, D. J.: Criteria for the Selection of Stochastic Models of Particle Trajectories in Turbulent Flows, J. Fluid Mech., 180, 529–556, 1987.
Vesala, T., Kljun, N., Rannik, Ü., Rinne, J., Sogachev, A., Markkanen, T., Sabelfeld, K., Foken, T., and Leclerc, M.: Flux and Concentration Footprint Modelling: State of the Art, Environ. Pollut., 152, 653–666, 2008.
Wang, W. and Davis, K. J.: A Numerical Study of the Influence of a Clearcut on Eddy-Covariance Fluxes of CO2 Measured Above a Forest, Agr. Forest Meteorol., 148, 1488–1500, 2008.
Weil, J. C. and Horst, T. W.: Footprint Estimates for Atmospheric Flux Measurements in the Convective Boundary Layer, in: Precipitation Scavening and Atmosphere – Surface Exchange, edited by: Schartz, S. and Slinn, W., Vol. 2, 717–728, Hemisphere Publishing, Washington, D.C., USA, 1992.
Wilson, J. D. and Swaters, G. E.: The Source Area Influencing a Measurement in the Planetary Boundary Layer: The "Footprint" and the "Distribution of Contact Distance", Bound.-Lay. Meteorol., 55, 25–46, 1991.
Zilitinkevich, S. S.: On the Determination of the Height of the Ekman Boundary Layer, Bound.-Lay. Meteorol., 3, 141–145, 1972.
Zilitinkevich, S. S. and Mironov, D. V.: A Mulit-Limit Formulation for the Equilibrium Depth of a Stably Stratified Boundary Layer, Bound.-Lay. Meteorol., 81, 325–351, 1996.
Zilitinkevich, S. S., Esau, I., and Baklanov, A.: Further Comments on the Equilibrium Height of Neutral and Stable Planetary Boundary Layers, Q. J. Roy. Meteorol. Soc., 133, 265–271, 2007.
Zilitinkevich, S. S., Tyuryakov, S. A., Troitskaya, Y. I., and Mareev, E. A.: Theoretical Models of the Height of the Atmospheric Boundary Layer and Turbulent Entrainment at Its Upper Boundary, Izv. Atmos. Ocean. Phys., 48, 133–142, 2012.
Short summary
Flux footprint models describe the surface area of influence of a flux measurement. They are used for designing flux tower sites, and for interpretation of flux measurements. The two-dimensional footprint parameterisation (FFP) presented here is suitable for processing large data sets, and, unlike other fast footprint models, FFP is applicable to daytime or night-time measurements, fluxes from short masts over grassland to tall towers over mature forests, and even to airborne flux measurements.
Flux footprint models describe the surface area of influence of a flux measurement. They are...