Articles | Volume 7, issue 5
Geosci. Model Dev., 7, 2193–2222, 2014
https://doi.org/10.5194/gmd-7-2193-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 7, 2193–2222, 2014
https://doi.org/10.5194/gmd-7-2193-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
30 Sep 2014
Development and technical paper
| 30 Sep 2014
Modeling stomatal conductance in the earth system: linking leaf water-use efficiency and water transport along the soil–plant–atmosphere continuum
G. B. Bonan et al.
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Projecting biogeochemical responses to environmental change requires multi-scaled perspectives. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon cycle–climate feedbacks. Here, we apply and evaluate representations of microbial functional diversity across scales and find that such representations may be critical to accurately project soil carbon dynamics in a changing world.
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
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Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-160, https://doi.org/10.5194/bg-2022-160, 2022
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Model-Data Fusion (MDF) allows us to combine ecosystem models with earth observation data. Fragmented landscapes, with a mosaic of contrasting ecosystems, pose a challenge for MDF. We develop a novel MDF framework to estimate the carbon balance of fragmented landscapes and show the importance of accounting for ecosystem heterogeneity to prevent scale-dependent bias in estimated carbon fluxes, disturbance fluxes in particular, and to ensure ecological fidelity of the calibrated models.
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Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, and Alexandra G. Konings
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Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
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Sophie Flack-Prain, Patrick Meir, Yadvinder Malhi, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 16, 4463–4484, https://doi.org/10.5194/bg-16-4463-2019, https://doi.org/10.5194/bg-16-4463-2019, 2019
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Thomas Luke Smallman and Mathew Williams
Geosci. Model Dev., 12, 2227–2253, https://doi.org/10.5194/gmd-12-2227-2019, https://doi.org/10.5194/gmd-12-2227-2019, 2019
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Photosynthesis and evapotranspiration are processes with global significance for climate, carbon and water cycling. Process-orientated simulation of these processes and their interactions have till now come at high computational cost. Here we present a new coupled model of intermediate complexity operating at orders of magnitude greater speed. Independent evaluation at FLUXNET sites for a single, global parameterization shows good agreement, with a typical R2 value of ~ 0.60.
Efrén López-Blanco, Jean-François Exbrayat, Magnus Lund, Torben R. Christensen, Mikkel P. Tamstorf, Darren Slevin, Gustaf Hugelius, Anthony A. Bloom, and Mathew Williams
Earth Syst. Dynam., 10, 233–255, https://doi.org/10.5194/esd-10-233-2019, https://doi.org/10.5194/esd-10-233-2019, 2019
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The terrestrial CO2 exchange in Arctic ecosystems plays an important role in the global carbon cycle and is particularly sensitive to the ongoing warming experienced in recent years. To improve our understanding of the atmosphere–biosphere interplay, we evaluated the state of the terrestrial pan-Arctic carbon cycling using a promising data assimilation system in the first 15 years of the 21st century. This is crucial when it comes to making predictions about the future state of the carbon cycle.
Vasileios Myrgiotis, Mathew Williams, Robert M. Rees, and Cairistiona F. E. Topp
Biogeosciences, 16, 1641–1655, https://doi.org/10.5194/bg-16-1641-2019, https://doi.org/10.5194/bg-16-1641-2019, 2019
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This study focuses on a northwestern European cropland region and shows that the type of crop growing on a soil has notable effects on the emission of nitrous oxide (N2O – a greenhouse gas) from that soil. It was found that N2O emissions from soils under oilseed cultivation are significantly higher than soils under cereal cultivation. This variation is mostly explained by the fact that oilseeds require more nitrogen (fertiliser) than cereals, especially at early crop growth stages.
Anne Sofie Lansø, Thomas Luke Smallman, Jesper Heile Christensen, Mathew Williams, Kim Pilegaard, Lise-Lotte Sørensen, and Camilla Geels
Biogeosciences, 16, 1505–1524, https://doi.org/10.5194/bg-16-1505-2019, https://doi.org/10.5194/bg-16-1505-2019, 2019
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Emily D. White, Matthew Rigby, Mark F. Lunt, T. Luke Smallman, Edward Comyn-Platt, Alistair J. Manning, Anita L. Ganesan, Simon O'Doherty, Ann R. Stavert, Kieran Stanley, Mathew Williams, Peter Levy, Michel Ramonet, Grant L. Forster, Andrew C. Manning, and Paul I. Palmer
Atmos. Chem. Phys., 19, 4345–4365, https://doi.org/10.5194/acp-19-4345-2019, https://doi.org/10.5194/acp-19-4345-2019, 2019
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Understanding carbon dioxide (CO2) fluxes from the terrestrial biosphere on a national scale is important for evaluating land use strategies to mitigate climate change. We estimate emissions of CO2 from the UK biosphere using atmospheric data in a top-down approach. Our findings show that bottom-up estimates from models of biospheric fluxes overestimate the amount of CO2 uptake in summer. This suggests these models wrongly estimate or omit key processes, e.g. land disturbance due to harvest.
Gordon B. Bonan, Edward G. Patton, Ian N. Harman, Keith W. Oleson, John J. Finnigan, Yaqiong Lu, and Elizabeth A. Burakowski
Geosci. Model Dev., 11, 1467–1496, https://doi.org/10.5194/gmd-11-1467-2018, https://doi.org/10.5194/gmd-11-1467-2018, 2018
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Land surface models neglect the roughness sublayer and parameterize within-canopy turbulence in an ad hoc manner. We implemented a roughness sublayer parameterization in a multilayer canopy model to test if this theory provides a tractable parameterization extending from the ground through the canopy and the roughness sublayer. The multilayer canopy improves simulations compared with the Community Land Model (CLM4.5) while also advancing the theoretical basis for surface flux parameterizations.
Jean-François Exbrayat, A. Anthony Bloom, Pete Falloon, Akihiko Ito, T. Luke Smallman, and Mathew Williams
Earth Syst. Dynam., 9, 153–165, https://doi.org/10.5194/esd-9-153-2018, https://doi.org/10.5194/esd-9-153-2018, 2018
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We use global observations of current terrestrial net primary productivity (NPP) to constrain the uncertainty in large ensemble 21st century projections of NPP under a "business as usual" scenario using a skill-based multi-model averaging technique. Our results show that this procedure helps greatly reduce the uncertainty in global projections of NPP. We also identify regions where uncertainties in models and observations remain too large to confidently conclude a sign of the change of NPP.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gabriel Abramowitz, Martin G. De Kauwe, Bradley Evans, Vanessa Haverd, Longhui Li, Caitlin Moore, Youngryel Ryu, Simon Scheiter, Stanislaus J. Schymanski, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 14, 4711–4732, https://doi.org/10.5194/bg-14-4711-2017, https://doi.org/10.5194/bg-14-4711-2017, 2017
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This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems. We provide a particular focus on three dynamic processes (phenology, root-water access, and fire) that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models. We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area.
Efrén López-Blanco, Magnus Lund, Mathew Williams, Mikkel P. Tamstorf, Andreas Westergaard-Nielsen, Jean-François Exbrayat, Birger U. Hansen, and Torben R. Christensen
Biogeosciences, 14, 4467–4483, https://doi.org/10.5194/bg-14-4467-2017, https://doi.org/10.5194/bg-14-4467-2017, 2017
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An improvement in our process-based understanding of CO2 exchanges in the Arctic and their climate sensitivity is critical. With continued warming temperatures and longer growing seasons, tundra systems will likely increase rates of C cycling, although shifts in sink strength could take place, challenging the forecast of upcoming C states. In this context, we investigated the functional responses of C exchange to environmental characteristics across 8 consecutive years in West Greenland.
Darren Slevin, Simon F. B. Tett, Jean-François Exbrayat, A. Anthony Bloom, and Mathew Williams
Geosci. Model Dev., 10, 2651–2670, https://doi.org/10.5194/gmd-10-2651-2017, https://doi.org/10.5194/gmd-10-2651-2017, 2017
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.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gab Abramowitz, Martin G. De Kauwe, Remko Duursma, Bradley Evans, Vanessa Haverd, Longhui Li, Youngryel Ryu, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, https://doi.org/10.5194/bg-13-3245-2016, 2016
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In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems. We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. Our assessment of model performance uses a novel benchmarking system that scores a model’s predictive ability based on how well it is utilizing its driving information. On average, we found the models as a group display only moderate levels of performance.
A. A. Ali, C. Xu, A. Rogers, R. A. Fisher, S. D. Wullschleger, E. C. Massoud, J. A. Vrugt, J. D. Muss, N. G. McDowell, J. B. Fisher, P. B. Reich, and C. J. Wilson
Geosci. Model Dev., 9, 587–606, https://doi.org/10.5194/gmd-9-587-2016, https://doi.org/10.5194/gmd-9-587-2016, 2016
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We have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA V1.0) to predict the photosynthetic capacities at the global scale based on the optimization of key leaf-level metabolic processes. LUNA model predicts that future climatic changes would mostly affect plant photosynthetic capabilities in high-latitude regions and that Earth system models using fixed photosynthetic capabilities are likely to substantially overestimate future global photosynthesis.
R. A. Fisher, S. Muszala, M. Verteinstein, P. Lawrence, C. Xu, N. G. McDowell, R. G. Knox, C. Koven, J. Holm, B. M. Rogers, A. Spessa, D. Lawrence, and G. Bonan
Geosci. Model Dev., 8, 3593–3619, https://doi.org/10.5194/gmd-8-3593-2015, https://doi.org/10.5194/gmd-8-3593-2015, 2015
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Predicting the distribution of vegetation under novel climates is important, both to understand how climate change will impact ecosystem services, but also to understand how vegetation changes might affect the carbon, energy and water cycles. Historically, predictions have been heavily dependent upon observations of existing vegetation boundaries. In this paper, we attempt to predict ecosystem boundaries from the ``bottom up'', and illustrate the complexities and promise of this approach.
C. Safta, D. M. Ricciuto, K. Sargsyan, B. Debusschere, H. N. Najm, M. Williams, and P. E. Thornton
Geosci. Model Dev., 8, 1899–1918, https://doi.org/10.5194/gmd-8-1899-2015, https://doi.org/10.5194/gmd-8-1899-2015, 2015
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In this paper we propose a probabilistic framework for an uncertainty quantification study of a carbon cycle model and focus on the comparison between steady-state and transient
simulation setups. We study model parameters via global sensitivity analysis and employ a Bayesian approach to calibrate these parameters using NEE observations at the Harvard Forest site. The calibration results are then used to assess the predictive skill of the model via posterior predictive checks.
W. R. Wieder, A. S. Grandy, C. M. Kallenbach, P. G. Taylor, and G. B. Bonan
Geosci. Model Dev., 8, 1789–1808, https://doi.org/10.5194/gmd-8-1789-2015, https://doi.org/10.5194/gmd-8-1789-2015, 2015
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Projecting biogeochemical responses to environmental change requires multi-scaled perspectives. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon cycle–climate feedbacks. Here, we apply and evaluate representations of microbial functional diversity across scales and find that such representations may be critical to accurately project soil carbon dynamics in a changing world.
L. Rowland, A. Harper, B. O. Christoffersen, D. R. Galbraith, H. M. A. Imbuzeiro, T. L. Powell, C. Doughty, N. M. Levine, Y. Malhi, S. R. Saleska, P. R. Moorcroft, P. Meir, and M. Williams
Geosci. Model Dev., 8, 1097–1110, https://doi.org/10.5194/gmd-8-1097-2015, https://doi.org/10.5194/gmd-8-1097-2015, 2015
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This study evaluates the capability of five vegetation models to simulate the response of forest productivity to changes in temperature and drought, using data collected from an Amazonian forest. This study concludes that model consistencies in the responses of net canopy carbon production to temperature and precipitation change were the result of inconsistently modelled leaf-scale process responses and substantial variation in modelled leaf area responses.
A. A. Bloom and M. Williams
Biogeosciences, 12, 1299–1315, https://doi.org/10.5194/bg-12-1299-2015, https://doi.org/10.5194/bg-12-1299-2015, 2015
D. Slevin, S. F. B. Tett, and M. Williams
Geosci. Model Dev., 8, 295–316, https://doi.org/10.5194/gmd-8-295-2015, https://doi.org/10.5194/gmd-8-295-2015, 2015
J. R. Buzan, K. Oleson, and M. Huber
Geosci. Model Dev., 8, 151–170, https://doi.org/10.5194/gmd-8-151-2015, https://doi.org/10.5194/gmd-8-151-2015, 2015
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We implemented the HumanIndexMod, which calculates 13 diagnostic heat stress metrics, into the Community Land Model (CLM4.5). The goal of this module is to have a common predictive framework for measuring heat stress globally. These metrics are in operational use by weather forecasters, industry, and agriculture. We show metric-dependent results of regional partitioning of extreme moisture and temperature levels in a 1901-2010 simulation.
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
R. Q. Thomas and M. Williams
Geosci. Model Dev., 7, 2015–2037, https://doi.org/10.5194/gmd-7-2015-2014, https://doi.org/10.5194/gmd-7-2015-2014, 2014
G. Xenakis and M. Williams
Geosci. Model Dev., 7, 1519–1533, https://doi.org/10.5194/gmd-7-1519-2014, https://doi.org/10.5194/gmd-7-1519-2014, 2014
W. R. Wieder, A. S. Grandy, C. M. Kallenbach, and G. B. Bonan
Biogeosciences, 11, 3899–3917, https://doi.org/10.5194/bg-11-3899-2014, https://doi.org/10.5194/bg-11-3899-2014, 2014
S. Levis, M. D. Hartman, and G. B. Bonan
Geosci. Model Dev., 7, 613–620, https://doi.org/10.5194/gmd-7-613-2014, https://doi.org/10.5194/gmd-7-613-2014, 2014
T. L. Smallman, M. Williams, and J. B. Moncrieff
Biogeosciences, 11, 735–747, https://doi.org/10.5194/bg-11-735-2014, https://doi.org/10.5194/bg-11-735-2014, 2014
C. D. Koven, W. J. Riley, Z. M. Subin, J. Y. Tang, M. S. Torn, W. D. Collins, G. B. Bonan, D. M. Lawrence, and S. C. Swenson
Biogeosciences, 10, 7109–7131, https://doi.org/10.5194/bg-10-7109-2013, https://doi.org/10.5194/bg-10-7109-2013, 2013
D. Lombardozzi, J. P. Sparks, and G. Bonan
Biogeosciences, 10, 6815–6831, https://doi.org/10.5194/bg-10-6815-2013, https://doi.org/10.5194/bg-10-6815-2013, 2013
R. Q. Thomas, G. B. Bonan, and C. L. Goodale
Biogeosciences, 10, 3869–3887, https://doi.org/10.5194/bg-10-3869-2013, https://doi.org/10.5194/bg-10-3869-2013, 2013
B. M. Rogers, J. T. Randerson, and G. B. Bonan
Biogeosciences, 10, 699–718, https://doi.org/10.5194/bg-10-699-2013, https://doi.org/10.5194/bg-10-699-2013, 2013
Related subject area
Climate and Earth system modeling
URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research
Combining regional mesh refinement with vertically enhanced physics to target marine stratocumulus biases as demonstrated in the Energy Exascale Earth System Model version 1
Evaluation of native Earth system model output with ESMValTool v2.6.0
WRF–ML v1.0: a bridge between WRF v4.3 and machine learning parameterizations and its application to atmospheric radiative transfer
The Euro-Mediterranean Center on Climate Change (CMCC) decadal prediction system
Climate impacts of parameterizing subgrid variation and partitioning of land surface heat fluxes to the atmosphere with the NCAR CESM1.2
Accelerated photosynthesis routine in LPJmL4
Improving scalability of Earth system models through coarse-grained component concurrency – a case study with the ICON v2.6.5 modelling system
Temperature forecasting by deep learning methods
Pathfinder v1.0.1: a Bayesian-inferred simple carbon–climate model to explore climate change scenarios
Inclusion of a cold hardening scheme to represent frost tolerance is essential to model realistic plant hydraulics in the Arctic–boreal zone in CLM5.0-FATES-Hydro
Implementation and evaluation of the GEOS-Chem chemistry module version 13.1.2 within the Community Earth System Model v2.1
Assessment of JSBACHv4.30 as a land component of ICON-ESM-V1 in comparison to its predecessor JSBACHv3.2 of MPI-ESM1.2
Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED)
Impact of increased resolution on the representation of the Canary upwelling system in climate models
Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI): protocol and initial results from the first simulations
Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)
Impact of physical parameterizations on wind simulation with WRF V3.9.1.1 under stable conditions at planetary boundary layer gray-zone resolution: a case study over the coastal regions of North China
Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States
SURFER v2.0: a flexible and simple model linking anthropogenic CO2 emissions and solar radiation modification to ocean acidification and sea level rise
Analysis of Systematic Biases in Tropospheric Hydrostatic Delay Models and Construction of Correction Model
A new bootstrap technique to quantify uncertainty in estimates of ground surface temperature and ground heat flux histories from geothermal data
Modeling the topographic influence on aboveground biomass using a coupled model of hillslope hydrology and ecosystem dynamics
Impacts of the ice-particle size distribution shape parameter on climate simulations with the Community Atmosphere Model Version 6 (CAM6)
A modeling framework to understand historical and projected ocean climate change in large coupled ensembles
TriCCo v1.1.0 – a cubulation-based method for computing connected components on triangular grids
Estimation of missing building height in OpenStreetMap data: a French case study using GeoClimate 0.0.1
The Moist Quasi-Geostrophic Coupled Model: MQ-GCM 2.0
Cell tracking of convective rainfall: sensitivity of climate-change signal to tracking algorithm and cell definition (Cell-TAO v1.0)
Transport parameterization of the Polar SWIFT model (version 2)
Analog data assimilation for the selection of suitable general circulation models
Uncertainty and sensitivity analysis for probabilistic weather and climate-risk modelling: an implementation in CLIMADA v.3.1.0
Grid refinement in ICON v2.6.4
Simulating marine neodymium isotope distributions using ND v1.0 coupled to the ocean component of the FAMOUS-MOSES1 climate model: sensitivities to reversible scavenging efficiency and benthic source distributions
Classification of tropical cyclone containing images using a convolutional neural network: performance and sensitivity to the learning dataset
The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514)
Further improvement and evaluation of nudging in the E3SM Atmosphere Model version 1 (EAMv1): simulations of the mean climate, weather events, and anthropogenic aerosol effects
HORAYZON v1.2: an efficient and flexible ray-tracing algorithm to compute horizon and sky view factor
LPJ-GUESS/LSMv1.0: a next-generation land surface model with high ecological realism
Downscaling multi-model climate projection ensembles with deep learning (DeepESD): contribution to CORDEX EUR-44
Intercomparison of four algorithms for detecting tropical cyclones using ERA5
Inland lake temperature initialization via coupled cycling with atmospheric data assimilation
wavetrisk-2.1: an adaptive dynamical core for ocean modelling
Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime
AWI-CM3 coupled climate model: description and evaluation experiments for a prototype post-CMIP6 model
The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2
Comparison and evaluation of updates to WRF-Chem (v3.9) biogenic emissions using MEGAN
Checkerboard patterns in E3SMv2 and E3SM-MMFv2
AttentionFire_v1.0: interpretable machine learning fire model for burned area predictions over tropics
MIdASv0.2.1 – MultI-scale bias AdjuStment
Markus Köhli, Martin Schrön, Steffen Zacharias, and Ulrich Schmidt
Geosci. Model Dev., 16, 449–477, https://doi.org/10.5194/gmd-16-449-2023, https://doi.org/10.5194/gmd-16-449-2023, 2023
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In the last decades, Monte Carlo codes were often consulted to study neutrons near the surface. As an alternative for the growing community of CRNS, we developed URANOS. The main model features are tracking of particle histories from creation to detection, detector representations as layers or geometric shapes, a voxel-based geometry model, and material setup based on color codes in ASCII matrices or bitmap images. The entire software is developed in C++ and features a graphical user interface.
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
Geosci. Model Dev., 16, 335–352, https://doi.org/10.5194/gmd-16-335-2023, https://doi.org/10.5194/gmd-16-335-2023, 2023
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Models that are used to simulate and predict climate often have trouble representing specific cloud types, such as stratocumulus, that are particularly thin in the vertical direction. It has been found that increasing the model resolution can help improve this problem. In this paper, we develop a novel framework that increases the horizontal and vertical resolutions only for areas of the globe that contain stratocumulus, hence reducing the model runtime while providing better results.
Manuel Schlund, Birgit Hassler, Axel Lauer, Bouwe Andela, Patrick Jöckel, Rémi Kazeroni, Saskia Loosveldt Tomas, Brian Medeiros, Valeriu Predoi, Stéphane Sénési, Jérôme Servonnat, Tobias Stacke, Javier Vegas-Regidor, Klaus Zimmermann, and Veronika Eyring
Geosci. Model Dev., 16, 315–333, https://doi.org/10.5194/gmd-16-315-2023, https://doi.org/10.5194/gmd-16-315-2023, 2023
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for routine evaluation of Earth system models. Originally, ESMValTool was designed to process reformatted output provided by large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP). Here, we describe a new extension of ESMValTool that allows for reading and processing native climate model output, i.e., data that have not been reformatted before.
Xiaohui Zhong, Zhijian Ma, Yichen Yao, Lifei Xu, Yuan Wu, and Zhibin Wang
Geosci. Model Dev., 16, 199–209, https://doi.org/10.5194/gmd-16-199-2023, https://doi.org/10.5194/gmd-16-199-2023, 2023
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More and more researchers use deep learning models to replace physics-based parameterizations to accelerate weather simulations. However, embedding the ML models within the weather models is difficult as they are implemented in different languages. This work proposes a coupling framework to allow ML-based parameterizations to be coupled with the Weather Research and Forecasting (WRF) model. We also demonstrate using the coupler to couple the ML-based radiation schemes with the WRF model.
Dario Nicolì, Alessio Bellucci, Paolo Ruggieri, Panos J. Athanasiadis, Stefano Materia, Daniele Peano, Giusy Fedele, Riccardo Hénin, and Silvio Gualdi
Geosci. Model Dev., 16, 179–197, https://doi.org/10.5194/gmd-16-179-2023, https://doi.org/10.5194/gmd-16-179-2023, 2023
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Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of the near-term climate and are useful for informing decision-makers on future climate-related risks. The predictive skill for key variables is assessed from the operational decadal prediction system compared with non-initialized historical simulations so as to quantify the added value of initialization.
Ming Yin, Yilun Han, Yong Wang, Wenqi Sun, Jianbo Deng, Daoming Wei, Ying Kong, and Bin Wang
Geosci. Model Dev., 16, 135–156, https://doi.org/10.5194/gmd-16-135-2023, https://doi.org/10.5194/gmd-16-135-2023, 2023
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All global climate models (GCMs) use the grid-averaged surface heat fluxes to drive the atmosphere, and thus their horizontal variations within the grid cell are averaged out. In this regard, a novel scheme considering the variation and partitioning of the surface heat fluxes within the grid cell is developed. The scheme reduces the long-standing rainfall biases on the southern and eastern margins of the Tibetan Plateau. The performance of key variables at the global scale is also evaluated.
Jenny Niebsch, Werner von Bloh, Kirsten Thonicke, and Ronny Ramlau
Geosci. Model Dev., 16, 17–33, https://doi.org/10.5194/gmd-16-17-2023, https://doi.org/10.5194/gmd-16-17-2023, 2023
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The impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are used to study the effects of multiple processes in the biosphere under climate change. There is a demand for a better computational performance of the models. In this paper, the photosynthesis model in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We found a better numerical solution of a nonlinear equation. A significant run time reduction was possible.
Leonidas Linardakis, Irene Stemmler, Moritz Hanke, Lennart Ramme, Fatemeh Chegini, Tatiana Ilyina, and Peter Korn
Geosci. Model Dev., 15, 9157–9176, https://doi.org/10.5194/gmd-15-9157-2022, https://doi.org/10.5194/gmd-15-9157-2022, 2022
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In Earth system modelling, we are facing the challenge of making efficient use of very large machines, with millions of cores. To meet this challenge we will need to employ multi-level and multi-dimensional parallelism. Component concurrency, being a function parallel technique, offers an additional dimension to the traditional data-parallel approaches. In this paper we examine the behaviour of component concurrency and identify the conditions for its optimal application.
Bing Gong, Michael Langguth, Yan Ji, Amirpasha Mozaffari, Scarlet Stadtler, Karim Mache, and Martin G. Schultz
Geosci. Model Dev., 15, 8931–8956, https://doi.org/10.5194/gmd-15-8931-2022, https://doi.org/10.5194/gmd-15-8931-2022, 2022
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Inspired by the success of deep learning in various domains, we test the applicability of video prediction methods by generative adversarial network (GAN)-based deep learning to predict the 2 m temperature over Europe. Our video prediction models have skill in predicting the diurnal cycle of 2 m temperature up to 12 h ahead. Complemented by probing the relevance of several model parameters, this study confirms the potential of deep learning in meteorological forecasting applications.
Thomas Bossy, Thomas Gasser, and Philippe Ciais
Geosci. Model Dev., 15, 8831–8868, https://doi.org/10.5194/gmd-15-8831-2022, https://doi.org/10.5194/gmd-15-8831-2022, 2022
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We developed a new simple climate model designed to fill a perceived gap within the existing simple climate models by fulfilling three key requirements: calibration using Bayesian inference, the possibility of coupling with integrated assessment models, and the capacity to explore climate scenarios compatible with limiting climate impacts. Here, we describe the model and its calibration using the latest data from complex CMIP6 models and the IPCC AR6, and we assess its performance.
Marius S. A. Lambert, Hui Tang, Kjetil S. Aas, Frode Stordal, Rosie A. Fisher, Yilin Fang, Junyan Ding, and Frans-Jan W. Parmentier
Geosci. Model Dev., 15, 8809–8829, https://doi.org/10.5194/gmd-15-8809-2022, https://doi.org/10.5194/gmd-15-8809-2022, 2022
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In this study, we implement a hardening mortality scheme into CTSM5.0-FATES-Hydro and evaluate how it impacts plant hydraulics and vegetation growth. Our work shows that the hydraulic modifications prescribed by the hardening scheme are necessary to model realistic vegetation growth in cold climates, in contrast to the default model that simulates almost nonexistent and declining vegetation due to abnormally large water loss through the roots.
Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Haipeng Lin, Elizabeth W. Lundgren, Steve Goldhaber, Steven R. H. Barrett, and Daniel J. Jacob
Geosci. Model Dev., 15, 8669–8704, https://doi.org/10.5194/gmd-15-8669-2022, https://doi.org/10.5194/gmd-15-8669-2022, 2022
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We bring the state-of-the-science chemistry module GEOS-Chem into the Community Earth System Model (CESM). We show that some known differences between results from GEOS-Chem and CESM's CAM-chem chemistry module may be due to the configuration of model meteorology rather than inherent differences in the model chemistry. This is a significant step towards a truly modular Earth system model and allows two strong but currently separate research communities to benefit from each other's advances.
Rainer Schneck, Veronika Gayler, Julia E. M. S. Nabel, Thomas Raddatz, Christian H. Reick, and Reiner Schnur
Geosci. Model Dev., 15, 8581–8611, https://doi.org/10.5194/gmd-15-8581-2022, https://doi.org/10.5194/gmd-15-8581-2022, 2022
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The versions of ICON-A and ICON-Land/JSBACHv4 used for this study constitute the first milestone in the development of the new ICON Earth System Model ICON-ESM. JSBACHv4 is the successor of JSBACHv3, and most of the parameterizations of JSBACHv4 are re-implementations from JSBACHv3. We assess and compare the performance of JSBACHv4 and JSBACHv3. Overall, the JSBACHv4 results are as good as JSBACHv3, but both models reveal the same main shortcomings, e.g. the depiction of the leaf area index.
Dave van Wees, Guido R. van der Werf, James T. Randerson, Brendan M. Rogers, Yang Chen, Sander Veraverbeke, Louis Giglio, and Douglas C. Morton
Geosci. Model Dev., 15, 8411–8437, https://doi.org/10.5194/gmd-15-8411-2022, https://doi.org/10.5194/gmd-15-8411-2022, 2022
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We present a global fire emission model based on the GFED model framework with a spatial resolution of 500 m. The higher resolution allowed for a more detailed representation of spatial heterogeneity in fuels and emissions. Specific modules were developed to model, for example, emissions from fire-related forest loss and belowground burning. Results from the 500 m model were compared to GFED4s, showing that global emissions were relatively similar but that spatial differences were substantial.
Adama Sylla, Emilia Sanchez Gomez, Juliette Mignot, and Jorge López-Parages
Geosci. Model Dev., 15, 8245–8267, https://doi.org/10.5194/gmd-15-8245-2022, https://doi.org/10.5194/gmd-15-8245-2022, 2022
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Increasing model resolution depends on the subdomain of the Canary upwelling considered. In the Iberian Peninsula, the high-resolution (HR) models do not seem to better simulate the upwelling indices, while in Morocco to the Senegalese coast, the HR models show a clear improvement. Thus increasing the resolution of a global climate model does not necessarily have to be the only way to better represent the climate system. There is still much work to be done in terms of physical parameterizations.
Jadwiga H. Richter, Daniele Visioni, Douglas G. MacMartin, David A. Bailey, Nan Rosenbloom, Brian Dobbins, Walker R. Lee, Mari Tye, and Jean-Francois Lamarque
Geosci. Model Dev., 15, 8221–8243, https://doi.org/10.5194/gmd-15-8221-2022, https://doi.org/10.5194/gmd-15-8221-2022, 2022
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Solar climate intervention using stratospheric aerosol injection is a proposed method of reducing global mean temperatures to reduce the worst consequences of climate change. We present a new modeling protocol aimed at simulating a plausible deployment of stratospheric aerosol injection and reproducibility of simulations using other Earth system models: Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI).
Gonzalo A. Ferrada, Meng Zhou, Jun Wang, Alexei Lyapustin, Yujie Wang, Saulo R. Freitas, and Gregory R. Carmichael
Geosci. Model Dev., 15, 8085–8109, https://doi.org/10.5194/gmd-15-8085-2022, https://doi.org/10.5194/gmd-15-8085-2022, 2022
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The smoke from fires is composed of different compounds that interact with the atmosphere and can create poor air-quality episodes. Here, we present a new fire inventory based on satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS). We named this inventory the VIIRS-based Fire Emission Inventory (VFEI). Advantages of VFEI are its high resolution (~500 m) and that it provides information for many species. VFEI is publicly available and has provided data since 2012.
Entao Yu, Rui Bai, Xia Chen, and Lifang Shao
Geosci. Model Dev., 15, 8111–8134, https://doi.org/10.5194/gmd-15-8111-2022, https://doi.org/10.5194/gmd-15-8111-2022, 2022
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A large number of simulations are conducted to investigate how different physical parameterization schemes impact surface wind simulations under stable weather conditions over the coastal regions of North China using the Weather Research and Forecasting model with a horizontal grid spacing of 0.5 km. Results indicate that the simulated wind speed is most sensitive to the planetary boundary layer schemes, followed by short-wave/long-wave radiation schemes and microphysics schemes.
Xingying Huang, Andrew Gettelman, William C. Skamarock, Peter Hjort Lauritzen, Miles Curry, Adam Herrington, John T. Truesdale, and Michael Duda
Geosci. Model Dev., 15, 8135–8151, https://doi.org/10.5194/gmd-15-8135-2022, https://doi.org/10.5194/gmd-15-8135-2022, 2022
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We focus on the recent development of a state-of-the-art storm-resolving global climate model and investigate how this next-generation model performs for precipitation prediction over the western USA. Results show realistic representations of precipitation with significantly enhanced snowpack over complex terrains. The model evaluation advances the unified modeling of large-scale forcing constraints and realistic fine-scale features to advance multi-scale climate predictions and changes.
Marina Martínez Montero, Michel Crucifix, Victor Couplet, Nuria Brede, and Nicola Botta
Geosci. Model Dev., 15, 8059–8084, https://doi.org/10.5194/gmd-15-8059-2022, https://doi.org/10.5194/gmd-15-8059-2022, 2022
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We present SURFER, a lightweight model that links CO2 emissions and geoengineering to ocean acidification and sea level rise from glaciers, ocean thermal expansion and Greenland and Antarctic ice sheets. The ice sheet module adequately describes the tipping points of both Greenland and Antarctica. SURFER is understandable, fast, accurate up to several thousands of years, capable of emulating results obtained by state of the art models and well suited for policy analyses.
Haopeng Fan, Siran Li, Zhongmiao Sun, Guorui Xiao, Xinxing Li, and Xiaogang Liu
EGUsphere, https://doi.org/10.5194/egusphere-2022-898, https://doi.org/10.5194/egusphere-2022-898, 2022
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The bias of traditional tropospheric zenith hydrostatic delay (ZHD) model is usually thought negligible, yet it still reaches 10 mm sometimes and would lead to mm-level position errors for space geodetic observations. Therefore, We analyzed the bias’ characteristics and present a grid model to correct the traditional ZHD formula. When we verified the efficiency based on data from ECMWF (European Centre for Medium-Range Weather Forecasts), it turned out that ZHD biases were rectified by ~50 %.
Francisco José Cuesta-Valero, Hugo Beltrami, Stephan Gruber, Almudena García-García, and J. Fidel González-Rouco
Geosci. Model Dev., 15, 7913–7932, https://doi.org/10.5194/gmd-15-7913-2022, https://doi.org/10.5194/gmd-15-7913-2022, 2022
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Inversions of subsurface temperature profiles provide past long-term estimates of ground surface temperature histories and ground heat flux histories at timescales of decades to millennia. Theses estimates complement high-frequency proxy temperature reconstructions and are the basis for studying continental heat storage. We develop and release a new bootstrap method to derive meaningful confidence intervals for the average surface temperature and heat flux histories from any number of profiles.
Yilin Fang, L. Ruby Leung, Charles D. Koven, Gautam Bisht, Matteo Detto, Yanyan Cheng, Nate McDowell, Helene Muller-Landau, S. Joseph Wright, and Jeffrey Q. Chambers
Geosci. Model Dev., 15, 7879–7901, https://doi.org/10.5194/gmd-15-7879-2022, https://doi.org/10.5194/gmd-15-7879-2022, 2022
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We develop a model that integrates an Earth system model with a three-dimensional hydrology model to explicitly resolve hillslope topography and water flow underneath the land surface to understand how local-scale hydrologic processes modulate vegetation along water availability gradients. Our coupled model can be used to improve the understanding of the diverse impact of local heterogeneity and water flux on nutrient availability and plant communities.
Wentao Zhang, Xiangjun Shi, and Chunsong Lu
Geosci. Model Dev., 15, 7751–7766, https://doi.org/10.5194/gmd-15-7751-2022, https://doi.org/10.5194/gmd-15-7751-2022, 2022
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The two-moment bulk cloud microphysics scheme used in CAM6 was modified to consider the impacts of the ice-crystal size distribution shape parameter (μi). After that, how the μi impacts cloud microphysical processes and then climate simulations is clearly illustrated by offline tests and CAM6 model experiments. Our results and findings are useful for the further development of μi-related parameterizations.
Yona Silvy, Clément Rousset, Eric Guilyardi, Jean-Baptiste Sallée, Juliette Mignot, Christian Ethé, and Gurvan Madec
Geosci. Model Dev., 15, 7683–7713, https://doi.org/10.5194/gmd-15-7683-2022, https://doi.org/10.5194/gmd-15-7683-2022, 2022
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A modeling framework is introduced to understand and decompose the mechanisms causing the ocean temperature, salinity and circulation to change since the pre-industrial period and into 21st century scenarios of global warming. This framework aims to look at the response to changes in the winds and in heat and freshwater exchanges at the ocean interface in global climate models, throughout the 1850–2100 period, to unravel their individual effects on the changing physical structure of the ocean.
Aiko Voigt, Petra Schwer, Noam von Rotberg, and Nicole Knopf
Geosci. Model Dev., 15, 7489–7504, https://doi.org/10.5194/gmd-15-7489-2022, https://doi.org/10.5194/gmd-15-7489-2022, 2022
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In climate science, it is helpful to identify coherent objects, for example, those formed by clouds. However, many models now use unstructured grids, which makes it harder to identify coherent objects. We present a new method that solves this problem by moving model data from an unstructured triangular grid to a structured cubical grid. We implement the method in an open-source Python package and show that the method is ready to be applied to climate model data.
Jérémy Bernard, Erwan Bocher, Elisabeth Le Saux Wiederhold, François Leconte, and Valéry Masson
Geosci. Model Dev., 15, 7505–7532, https://doi.org/10.5194/gmd-15-7505-2022, https://doi.org/10.5194/gmd-15-7505-2022, 2022
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OpenStreetMap is a collaborative project aimed at creaing a free dataset containing topographical information. Since these data are available worldwide, they can be used as standard data for geoscience studies. However, most buildings miss the height information that constitutes key data for numerous fields (urban climate, noise propagation, air pollution). In this work, the building height is estimated using statistical modeling using indicators that characterize the building's environment.
Sergey Kravtsov, Ilijana Mastilovic, Andrew McC. Hogg, William K. Dewar, and Jeffrey R. Blundell
Geosci. Model Dev., 15, 7449–7469, https://doi.org/10.5194/gmd-15-7449-2022, https://doi.org/10.5194/gmd-15-7449-2022, 2022
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Climate is a complex system whose behavior is shaped by multitudes of processes operating on widely different spatial scales and timescales. In hierarchical modeling, one goes back and forth between highly idealized process models and state-of-the-art models coupling the entire range of climate subsystems to identify specific phenomena and understand their dynamics. The present contribution highlights an intermediate climate model focussing on midlatitude ocean–atmosphere interactions.
Edmund P. Meredith, Uwe Ulbrich, and Henning W. Rust
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-202, https://doi.org/10.5194/gmd-2022-202, 2022
Revised manuscript accepted for GMD
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Cell tracking algorithms allow the properties of a convective cell to be studied across its lifetime and, in particular, how these respond to climate change. We investigated whether the design of the algorithm can affect the magnitude of the climate-change signal. The algorithm’s criteria for identifying a cell were found to have a strong impact on the warming response. The sensitivity of the warming response to different algorithm settings and cell types should thus be fully explored.
Ingo Wohltmann, Daniel Kreyling, and Ralph Lehmann
Geosci. Model Dev., 15, 7243–7255, https://doi.org/10.5194/gmd-15-7243-2022, https://doi.org/10.5194/gmd-15-7243-2022, 2022
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The study evaluates the performance of the Data Assimilation Research Testbed (DART), equipped with the recently added forward operator Radiative Transfer for TOVS (RTTOV), in assimilating FY-4A visible images into the Weather Research and Forecasting (WRF) model. The ability of the WRF-DART/RTTOV system to improve the forecasting skills for a tropical storm over East Asia and the Western Pacific is demonstrated in an Observing System Simulation Experiment framework.
Juan Ruiz, Pierre Ailliot, Thi Tuyet Trang Chau, Pierre Le Bras, Valérie Monbet, Florian Sévellec, and Pierre Tandeo
Geosci. Model Dev., 15, 7203–7220, https://doi.org/10.5194/gmd-15-7203-2022, https://doi.org/10.5194/gmd-15-7203-2022, 2022
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We present a new approach to validate numerical simulations of the current climate. The method can take advantage of existing climate simulations produced by different centers combining an analog forecasting approach with data assimilation to quantify how well a particular model reproduces a sequence of observed values. The method can be applied with different observations types and is implemented locally in space and time significantly reducing the associated computational cost.
Chahan M. Kropf, Alessio Ciullo, Laura Otth, Simona Meiler, Arun Rana, Emanuel Schmid, Jamie W. McCaughey, and David N. Bresch
Geosci. Model Dev., 15, 7177–7201, https://doi.org/10.5194/gmd-15-7177-2022, https://doi.org/10.5194/gmd-15-7177-2022, 2022
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Mathematical models are approximations, and modellers need to understand and ideally quantify the arising uncertainties. Here, we describe and showcase the first, simple-to-use, uncertainty and sensitivity analysis module of the open-source and open-access climate-risk modelling platform CLIMADA. This may help to enhance transparency and intercomparison of studies among climate-risk modellers, help focus future research, and lead to better-informed decisions on climate adaptation.
Günther Zängl, Daniel Reinert, and Florian Prill
Geosci. Model Dev., 15, 7153–7176, https://doi.org/10.5194/gmd-15-7153-2022, https://doi.org/10.5194/gmd-15-7153-2022, 2022
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This article describes the implementation of grid refinement in the ICOsahedral Nonhydrostatic (ICON) model, which has been jointly developed at several German institutions and constitutes a unified modeling system for global and regional numerical weather prediction and climate applications. The grid refinement allows using a higher resolution in regional domains and transferring the information back to the global domain by means of a feedback mechanism.
Suzanne Robinson, Ruza Ivanovic, Lauren Gregoire, Julia Tindall, Tina van de Flierdt, Yves Plancherel, Frerk Pöppelmeier, Kazuyo Tachikawa, and Paul Valdes
EGUsphere, https://doi.org/10.5194/egusphere-2022-606, https://doi.org/10.5194/egusphere-2022-606, 2022
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We present the implementation of neodymium (Nd) isotopes into the ocean model of FAMOUS (ND v1.0). Nd fluxes from seafloor sediment alongside incorporation of Nd onto sinking particles represent the major global sources and sinks. However, model-data mismatch in the North Pacific and northern North Atlantic suggest that certain reactive components of the sediment interact the most with seawater. Our results are important for interpreting Nd isotopes in terms of ocean circulation.
Sébastien Gardoll and Olivier Boucher
Geosci. Model Dev., 15, 7051–7073, https://doi.org/10.5194/gmd-15-7051-2022, https://doi.org/10.5194/gmd-15-7051-2022, 2022
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Tropical cyclones (TCs) are one of the most devastating natural disasters, which justifies monitoring and prediction in the context of a changing climate. In this study, we have adapted and tested a convolutional neural network (CNN) for the classification of reanalysis outputs (ERA5 and MERRA-2 labeled by HURDAT2) according to the presence or absence of TCs. We tested the impact of interpolation and of "mixing and matching" the training and test sets on the performance of the CNN.
Marco A. Giorgetta, William Sawyer, Xavier Lapillonne, Panagiotis Adamidis, Dmitry Alexeev, Valentin Clément, Remo Dietlicher, Jan Frederik Engels, Monika Esch, Henning Franke, Claudia Frauen, Walter M. Hannah, Benjamin R. Hillman, Luis Kornblueh, Philippe Marti, Matthew R. Norman, Robert Pincus, Sebastian Rast, Daniel Reinert, Reiner Schnur, Uwe Schulzweida, and Bjorn Stevens
Geosci. Model Dev., 15, 6985–7016, https://doi.org/10.5194/gmd-15-6985-2022, https://doi.org/10.5194/gmd-15-6985-2022, 2022
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This work presents a first version of the ICON atmosphere model that works not only on CPUs, but also on GPUs. This GPU-enabled ICON version is benchmarked on two GPU machines and a CPU machine. While the weak scaling is very good on CPUs and GPUs, the strong scaling is poor on GPUs. But the high performance of GPU machines allowed for first simulations of a short period of the quasi-biennial oscillation at very high resolution with explicit convection and gravity wave forcing.
Shixuan Zhang, Kai Zhang, Hui Wan, and Jian Sun
Geosci. Model Dev., 15, 6787–6816, https://doi.org/10.5194/gmd-15-6787-2022, https://doi.org/10.5194/gmd-15-6787-2022, 2022
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This study investigates the nudging implementation in the EAMv1 model. We find that (1) revising the sequence of calculations and using higher-frequency constraining data to improve the performance of a simulation nudged to EAMv1’s own meteorology, (2) using the relocated nudging tendency and 3-hourly ERA5 reanalysis to obtain a better agreement between nudged simulations and observations, and (3) using wind-only nudging are recommended for the estimates of global mean aerosol effects.
Christian R. Steger, Benjamin Steger, and Christoph Schär
Geosci. Model Dev., 15, 6817–6840, https://doi.org/10.5194/gmd-15-6817-2022, https://doi.org/10.5194/gmd-15-6817-2022, 2022
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Terrain horizon and sky view factor are crucial quantities for many geoscientific applications; e.g. they are used to account for effects of terrain on surface radiation in climate and land surface models. Because typical terrain horizon algorithms are inefficient for high-resolution (< 30 m) elevation data, we developed a new algorithm based on a ray-tracing library. A comparison with two conventional methods revealed both its high performance and its accuracy for complex terrain.
David Martín Belda, Peter Anthoni, David Wårlind, Stefan Olin, Guy Schurgers, Jing Tang, Benjamin Smith, and Almut Arneth
Geosci. Model Dev., 15, 6709–6745, https://doi.org/10.5194/gmd-15-6709-2022, https://doi.org/10.5194/gmd-15-6709-2022, 2022
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We present a number of augmentations to the ecosystem model LPJ-GUESS, which will allow us to use it in studies of the interactions between the land biosphere and the climate. The new module enables calculation of fluxes of energy and water into the atmosphere that are consistent with the modelled vegetation processes. The modelled fluxes are in fair agreement with observations across 21 sites from the FLUXNET network.
Jorge Baño-Medina, Rodrigo Manzanas, Ezequiel Cimadevilla, Jesús Fernández, Jose González-Abad, Antonio S. Cofiño, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 6747–6758, https://doi.org/10.5194/gmd-15-6747-2022, https://doi.org/10.5194/gmd-15-6747-2022, 2022
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Deep neural networks are used to produce downscaled regional climate change projections over Europe for temperature and precipitation for the first time. The resulting dataset, DeepESD, is analyzed against state-of-the-art downscaling methodologies, reproducing more accurately the observed climate in the historical period and showing plausible future climate change signals with low computational requirements.
Stella Bourdin, Sébastien Fromang, William Dulac, Julien Cattiaux, and Fabrice Chauvin
Geosci. Model Dev., 15, 6759–6786, https://doi.org/10.5194/gmd-15-6759-2022, https://doi.org/10.5194/gmd-15-6759-2022, 2022
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When studying tropical cyclones in a large dataset, one needs objective and automatic procedures to detect their specific pattern. Applying four different such algorithms to a reconstruction of the climate, we show that the choice of the algorithm is crucial to the climatology obtained. Mainly, the algorithms differ in their sensitivity to weak storms so that they provide different frequencies and durations. We review the different options to consider for the choice of the tracking methodology.
Stanley G. Benjamin, Tatiana G. Smirnova, Eric P. James, Eric J. Anderson, Ayumi Fujisaki-Manome, John G. W. Kelley, Greg E. Mann, Andrew D. Gronewold, Philip Chu, and Sean G. T. Kelley
Geosci. Model Dev., 15, 6659–6676, https://doi.org/10.5194/gmd-15-6659-2022, https://doi.org/10.5194/gmd-15-6659-2022, 2022
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Application of 1-D lake models coupled within earth-system prediction models will improve accuracy but requires accurate initialization of lake temperatures. Here, we describe a lake initialization method by cycling within a weather prediction model to constrain lake temperature evolution. We compared these lake temperature values with other estimates and found much reduced errors (down to 1-2 K). The lake cycling initialization is now applied to two operational US NOAA weather models.
Nicholas K.-R. Kevlahan and Florian Lemarié
Geosci. Model Dev., 15, 6521–6539, https://doi.org/10.5194/gmd-15-6521-2022, https://doi.org/10.5194/gmd-15-6521-2022, 2022
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WAVETRISK-2.1 is an innovative climate model for the world's oceans. It uses state-of-the-art techniques to change the model's resolution locally, from O(100 km) to O(5 km), as the ocean changes. This dynamic adaptivity makes optimal use of available supercomputer resources, and allows two-dimensional global scales and three-dimensional submesoscales to be captured in the same simulation. WAVETRISK-2.1 is designed to be coupled its companion global atmosphere model, WAVETRISK-1.x.
Meng Huang, Po-Lun Ma, Nathaniel W. Chaney, Dalei Hao, Gautam Bisht, Megan D. Fowler, Vincent E. Larson, and L. Ruby Leung
Geosci. Model Dev., 15, 6371–6384, https://doi.org/10.5194/gmd-15-6371-2022, https://doi.org/10.5194/gmd-15-6371-2022, 2022
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The land surface in one grid cell may be diverse in character. This study uses an explicit way to account for that subgrid diversity in a state-of-the-art Earth system model (ESM) and explores its implications for the overlying atmosphere. We find that the shallow clouds are increased significantly with the land surface diversity. Our work highlights the importance of accurately representing the land surface and its interaction with the atmosphere in next-generation ESMs.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
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We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
Stephen G. Yeager, Nan Rosenbloom, Anne A. Glanville, Xian Wu, Isla Simpson, Hui Li, Maria J. Molina, Kristen Krumhardt, Samuel Mogen, Keith Lindsay, Danica Lombardozzi, Will Wieder, Who M. Kim, Jadwiga H. Richter, Matthew Long, Gokhan Danabasoglu, David Bailey, Marika Holland, Nicole Lovenduski, Warren G. Strand, and Teagan King
Geosci. Model Dev., 15, 6451–6493, https://doi.org/10.5194/gmd-15-6451-2022, https://doi.org/10.5194/gmd-15-6451-2022, 2022
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The Earth system changes over a range of time and space scales, and some of these changes are predictable in advance. Short-term weather forecasts are most familiar, but recent work has shown that it is possible to generate useful predictions several seasons or even a decade in advance. This study focuses on predictions over intermediate timescales (up to 24 months in advance) and shows that there is promising potential to forecast a variety of changes in the natural environment.
Mauro Morichetti, Sasha Madronich, Giorgio Passerini, Umberto Rizza, Enrico Mancinelli, Simone Virgili, and Mary Barth
Geosci. Model Dev., 15, 6311–6339, https://doi.org/10.5194/gmd-15-6311-2022, https://doi.org/10.5194/gmd-15-6311-2022, 2022
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In the present study, we explore the effect of making simple changes to the existing WRF-Chem MEGAN v2.04 emissions to provide MEGAN updates that can be used independently of the land surface model chosen. The changes made to the MEGAN algorithm implemented in WRF-Chem were the following: (i) update of the emission activity factors, (ii) update of emission factor values for each plant functional type (PFT), and (iii) the assignment of the emission factor by PFT to isoprene.
Walter Hannah, Kyle Pressel, Mikhail Ovchinnikov, and Gregory Elsaesser
Geosci. Model Dev., 15, 6243–6257, https://doi.org/10.5194/gmd-15-6243-2022, https://doi.org/10.5194/gmd-15-6243-2022, 2022
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An unphysical checkerboard signal is identified in two configurations of the atmospheric component of E3SM. The signal is very persistent and visible after averaging years of data. The signal is very difficult to study because it is often mixed with realistic weather. A method is presented to detect checkerboard patterns and compare the model with satellite observations. The causes of the signal are identified, and a solution for one configuration is discussed.
Fa Li, Qing Zhu, William Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James Randerson
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-195, https://doi.org/10.5194/gmd-2022-195, 2022
Revised manuscript accepted for GMD
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In this work, we developed an interpretable machine learning model to predict sub-seasonal and near future wildfire burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 month) from local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning model result in high accurate predictions of wildfire burned area, also will help develop relevant early warming and management system for tropical wildfire.
Peter Berg, Thomas Bosshard, Wei Yang, and Klaus Zimmermann
Geosci. Model Dev., 15, 6165–6180, https://doi.org/10.5194/gmd-15-6165-2022, https://doi.org/10.5194/gmd-15-6165-2022, 2022
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When performing impact analyses with climate models, one is often confronted with the issue that the models have significant bias. Commonly, the modelled climatological temperature deviates from the observed climate by a few degrees or it rains excessively in the model. MIdAS employs a novel statistical model to translate the model climatology toward that observed using novel methodologies and modern tools. The coding platform allows opportunities to develop methods for high-resolution models.
Cited articles
Baldocchi, D. and Meyers, T.: On using eco-physiological, micrometeorological and biogeochemical theory to evaluate carbon dioxide, water vapor and trace gas fluxes over vegetation: a perspective, Agr. Forest Meteorol., 90, 1–25, 1998.
Baldocchi, D. D. and Wilson, K. B.: Modeling CO2 and water vapor exchange of a temperate broadleaved forest across hourly to decadal time scales, Ecol. Model., 142, 155–184, 2001.
Baldocchi, D. D., Wilson, K. B., and Gu, L.: How the environment, canopy structure and canopy physiological functioning influence carbon, water and energy fluxes of a temperate broad-leaved deciduous forest – an assessment with the biophysical model CANOAK, Tree Physiol., 22, 1065–1077, 2002.
Ball, J. T., Woodrow, I. E., and Berry, J. A.: A model predicting stomatal conductance and its contribution to the control of photosynthesis under different environmental conditions, in: Progress in Photosynthesis Research, Vol. 4, edited by: Biggins, J., Martinus Nijhoff, the Netherlands, 221–224, 1987.
Bonan, G. B.: Land–atmosphere CO2 exchange simulated by a land surface process model coupled to an atmospheric general circulation model, J. Geophys. Res., 100D, 2817–2831, 1995.
Bonan, G. B., Lawrence, P. J., Oleson, K. W., Levis, S., Jung, M., Reichstein, M., Lawrence, D. M., and Swenson, S. C.: Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data, J. Geophys. Res., 116, G02014, https://doi.org/10.1029/2010JG001593, 2011.
Bonan, G. B., Oleson, K. W., Fisher, R. A., Lasslop, G., and Reichstein, M.: Reconciling leaf physiological traits and canopy flux data: use of the TRY and FLUXNET databases in the Community Land Model version 4, J. Geophys. Res., 117, G02026, https://doi.org/10.1029/2011JG001913, 2012.
Choat, B., Jansen, S., Brodribb, T. J., Cochard, H., Delzon, S., Bhaskar, R., Bucci, S. J., Field, T. S., Gleason, S. M., Hacke, U. G., Jacobsen, A. L., Lens, F., Maherali, H., Martínez-Vilalta, J., Mayr, S., Mencuccini, M., Mitchell, P. J., Nardini, A., Pittermann, J., Pratt, R. B., Sperry, J. S., Westoby, M., Wright, I. J., and Zanne, A. E.: Global convergence in the vulnerability of forests to drought, Nature, 491, 752–755, 2012.
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, 1991.
Cowan, I. R.: Stomatal behavior and environment, Adv. Bot. Res., 4, 117–228, 1977.
Cowan, I. R. and Farquhar, G. D.: Stomatal function in relation to leaf metabolism and environment, in: Integration of Activity in the Higher Plant, edited by: Jennings, D. H., Cambridge University Press, Cambridge, 471–505, 1977.
Cox, P. M., Huntingford, C., and Harding, R. J.: A canopy conductance and photosynthesis model for use in a GCM land surface scheme, J. Hydrol., 212–213, 79–94, 1998.
De Kauwe, M. G., Medlyn, B. E., Zaehle, S., Walker, A. P., Dietze, M. C., Hickler, T., Jain, A. K., Luo, Y., Parton, W. J., Prentice, I. C., Smith, B., Thornton, P. E., Wang, S., Wang, Y.-P., Warlind, D., Weng, E., Crous, K. Y., Ellsworth, D. S., Hanson, P. J., Kim, H.-S., Warren, J. M., Oren, R., and Norby, R. J.: Forest water use and water use efficiency at elevated CO2: a model–data intercomparison at two contrasting temperate forest FACE sites, Global Change Biol., 19, 1759–1779, 2013.
Duursma, R. A. and Medlyn, B. E.: MAESPA: a model to study interactions between water limitation, environmental drivers and vegetation function at tree and stand levels, with an example application to [CO2] × drought interactions, Geosci. Model Dev., 5, 919–940, https://doi.org/10.5194/gmd-5-919-2012, 2012.
Egea, G., Verhoef, A., and Vidale, P. L.: Towards an improved and more flexible representation of water stress in coupled photosynthesis–stomatal conductance models, Agr. Forest Meteorol., 151, 1370–1384, 2011.
Ewers, B. E., Oren, R., and Sperry, J. S.: Influence of nutrient versus water supply on hydraulic architecture and water balance in Pinus taeda, Plant Cell Environ., 23, 1055–1066, 2000.
Ewers, B. E., Gower, S. T., Bond-Lamberty, B., and Wang, C. K.: Effects of stand age and tree species on canopy transpiration and average stomatal conductance of boreal forests, Plant Cell Environ., 28, 660–678, 2005.
Farquhar, G. D., von Caemmerer, S., and Berry, J. A.: A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149, 78–90, 1980.
Federer, C. A., Vörösmarty, C., and Fekete, B.: Sensitivity of annual evaporation to soil and root properties in two models of contrasting complexity, J. Hydrometeorol., 4, 1276–1290, 2003.
Fisher, R. A., Williams, M., Lobo do Vale, R., Lola da Costa, A., and Meir, P.: Evidence from Amazonian forests is consistent with isohydric control of leaf water potential, Plant Cell Environ., 29, 151–165, 2006.
Fisher, R. A., Williams, M., Lola da Costa, A., Malhi, Y., da Costa, R. F., Almeida, S., and Meir, P.: The response of an Eastern Amazonian rain forest to drought stress: results and modelling analyses from a throughfall exclusion experiment, Global Change Biol., 13, 2361–2378, 2007.
Foken, T.: The energy balance closure problem: an overview, Ecol. Appl., 18, 1351–1367, 2008.
Friend, A. D.: PGEN: an integrated model of leaf photosynthesis, transpiration, and conductance, Ecol. Model., 77, 233–255, 1995.
Gardner, W. R.: Dynamic aspects of water availability to plants, Soil Sci., 89, 63–73, 1960.
Goldstein, G., Andrade, J. L., Meinzer, F. C., Holbrook, N. M., Cavelier, J., Jackson, P., and Celis, A.: Stem water storage and diurnal patterns of water use in tropical forest canopy trees, Plant Cell Environ., 21, 397–406, 1998.
Hendricks Franssen, H. J., Stöckli, R., Lehner, I., Rotenberg, E., and Seneviratne, S. I.: Energy balance closure of eddy-covariance data: a multisite analysis for European FLUXNET stations, Agr. Forest Meteorol., 150, 1553–1567, 2010.
Hetherington, A. M. and Woodward, F. I.: The role of stomata in sensing and driving environmental change, Nature, 424, 901–908, 2003.
Hill, T. C., Williams, M., Woodward, F. I., and Moncrieff, J. B.: Constraining ecosystem processes from tower fluxes and atmospheric profiles, Ecol. Appl., 21, 1474–1489, 2011.
Hollinger, D. Y., Goltz, S. M., Davidson, E. A., Lee, J. T., Tu, K., and Valentine, H. T.: Seasonal patterns and environmental control of carbon dioxide and water vapour exchange in an ecotonal boreal forest, Global Change Biol., 5, 891–902, 1999.
Jackson, R. B., Mooney, H. A., and Schulze, E.-D.: A global budget for fine root biomass, surface area, and nutrient contents, Proc. Natl. Acad. Sci. USA, 94, 7362–7366, 1997.
Kattge, J. and Knorr, W.: Temperature acclimation in a biochemical model of photosynthesis: a reanalysis of data from 36 species, Plant Cell Environ., 30, 1176–1190, 2007.
Kattge, J., Knorr, W., Raddatz, T., and Wirth, C.: Quantifying photosynthetic capacity and its relationship to leaf nitrogen content for global-scale terrestrial biosphere models, Global Change Biol., 15, 976–991, 2009.
Katul, G. G., Palmroth, S., and Oren, R.: Leaf stomatal responses to vapour pressure deficit under current and CO2-enriched atmosphere explained by the economics of gas exchange, Plant Cell Environ., 32, 968–979, 2009.
Katul, G., Manzoni, S., Palmroth, S. and Oren, R.: A stomatal optimization theory to describe the effects of atmospheric CO2 on leaf photosynthesis and transpiration, Ann. Bot., 105, 431–442, 2010.
Körner, C.: Leaf diffusive conductances in the major vegetation types of the globe, in: Ecophysiology of Photosynthesis, edited by: Schulze, E.-D. and Caldwell, M. M., Springer-Verlag, Berlin, 463–490, 1994.
Koven, C. D., Riley, W. J., Subin, Z. M., Tang, J. Y., Torn, M. S., Collins, W. D., Bonan, G. B., Lawrence, D. M., and Swenson, S. C.: The effect of vertically resolved soil biogeochemistry and alternate soil C and N models on C dynamics of CLM4, Biogeosciences, 10, 7109–7131, https://doi.org/10.5194/bg-10-7109-2013, 2013.
Leuning, R.: A critical appraisal of a combined stomatal–photosynthesis model for C3 plants, Plant Cell Environ., 18, 339–355, 1995.
Leuning, R., van Gorsel, E., Massman, W. J., and Issac, P. R.: Reflections on the surface energy imbalance problem, Agr. Forest Meteorol., 156, 65–74, 2012.
Lloyd, J., Patiño, S., Paiva, R. Q., Nardoto, G. B., Quesada, C. A., Santos, A. J. B., Baker, T. R., Brand, W. A., Hilke, I., Gielmann, H., Raessler, M., Luizão, F. J., Martinelli, L. A., and Mercado, L. M.: Optimisation of photosynthetic carbon gain and within-canopy gradients of associated foliar traits for Amazon forest trees, Biogeosciences, 7, 1833–1859, https://doi.org/10.5194/bg-7-1833-2010, 2010.
Manzoni, S., Vico, G., Porporato, A., and Katul. G .: Biological constraints on water transport in the soil–plant–atmosphere system, Adv. Water Resour., 51, 292–304, 2013.
McDowell, N. G., Fisher, R. A., Xu, C., Domec, J. C., Hölttä, T., Mackay, D. S., Sperry, J. S., Boutz, A., Dickman, L., Gehres, N., Limousin, J. M., Macalady, A., Martínez-Vilalta, J., Mencuccini, M., Plaut, J. A., Ogée, J., Pangle, R. E., Rasse, D. P., Ryan, M. G., Sevanto, S., Waring, R. H., Williams, A. P., Yepez, E. A., and Pockman, W. T.: Evaluating theories of drought-induced vegetation mortality using a multimodel–experiment framework, New Phytol., 200, 304–321, 2013.
Medlyn, B. E., Duursma, R. A., and Zeppel, M. J. B.: Forest productivity under climate change: a checklist for evaluating model studies, WIREs Climate Change, 2, 332–355, 2011a.
Medlyn, B. E., Duursma, R. A., Eamus, D., Ellsworth, D. S., Prentice, I. C., Barton, C. V. M., Crous, K. Y., de Angelis, P., Freeman, M., and Wingate, L.: Reconciling the optimal and empirical approaches to modelling stomatal conductance, Global Change Biol., 17, 2134–2144, 2011b.
Meinzer, F. C.: Co-ordination of vapour and liquid phase water transport properties in plants, Plant Cell Environ., 25, 265–274, 2002.
Meinzer, F. C., Goldstein, G., Jackson, P., Holbrook, N. M., Gutiérrez, M. V., and Cavelier, J.: Environmental and physiological regulation of transpiration in tropical forest gap species: the influence of boundary layer and hydraulic properties, Oecologia, 101, 514–522, 1995.
Mencuccini, M.: The ecological significance of long-distance water transport: short-term regulation, long-term acclimation and the hydraulic costs of stature across plant life forms, Plant Cell Environ., 26, 163–182, 2003.
Newman, E. I.: Resistance to water flow in soil and plant. I. Soil resistance in relation to amounts of root: theoretical estimates, J. Appl. Ecol., 6, 1–12, 1969.
Norman, J. M.: Modeling the complete crop canopy, in: Modification of the Aerial Environment of Plants, edited by: Barfield, B. J. and Gerber, J. F., Am. Soc. of Agric. Eng., St. Joseph, Mich, 249–277, 1979.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M., Koven, C. D., Levis, S., Li, F., Riley, W. J., Subin, Z. M., Swenson, S. C., Thornton, P. E., Bozbiyik, A., Fisher, R., Heald, C. L., Kluzek, E., Lamarque, J.-F., Lawrence, P. J., Leung, L. R., Lipscomb, W., Muszala, S., Ricciuto, D. M., Sacks, W., Sun, Y., Tang, J., and Yang, Z.-L.: Technical description of version 4.5 of the Community Land Model (CLM), NCAR Tech. Note NCAR/TN-503+STR, National Center for Atmospheric Research, Boulder, Colorado, 420 pp., 2013.
Ollinger, S. V., Richardson, A. D., Martin, M. E., Hollinger, D. Y., Frolking, S. E., Reich, P. B., Plourde, L. C., Katul, G. G., Munger, J. W., Oren, R., Smith, M.-L., Paw U, K. T., Bolstad, P. V., Cook, B. D., Day, M. C., Martin, T. A., Monson, R. K., and Schmid, H. P.: Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks, Proc. Natl. Acad. Sci. USA, 105, 19336–19341, 2008.
Oren, R., Sperry, J. S., Katul, G. G., Pataki, D. E., Ewers, B. E., Phillips, N., and Schäfer, K. V. R.: Survey and synthesis of intra- and interspecific variation in stomatal sensitivity to vapour pressure deficit, Plant Cell Environ., 22, 1515–1526, 1999.
Peltoniemi, M. S., Duursma, R. A., and Medlyn, B. E.: Co-optimal distribution of leaf nitrogen and hydraulic conductance in plant canopies, Tree Physiol., 32, 510–519, 2012.
Richardson, A. D., Hollinger, D. Y., Burba, G. G., Davis, K. J., Flanagan, L. B., Katul, G. G., Munger, J. W., Ricciuto, D. M., Stoy, P. C., Suyker, A. E., Verma, S. B., and Wofsy, S. C.: A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes, Agr. Forest Meteorol., 136, 1–18, 2006.
Richardson, A. D., Aubinet, M., Barr, A. G., Hollinger, D. Y., Ibrom, A., Lasslop, G. and Reichstein, M.: Uncertainty quantification, in: Eddy Covariance: A Practical Guide to Measurement and Data Analysis, edited by: Aubinet, M., Vesala, T. and Papale, D., Springer, Dordrecht, 173–209, 2012.
Rieger, M. and Litvin, P.: Root system hydraulic conductivity in species with contrasting root anatomy, J. Exper. Bot., 50, 201–209, 1999.
Saliendra, N. Z., Sperry, J. S., and Comstock, J. P.: Influence of leaf water status on stomatal response to humidity, hydraulic conductance, and soil drought in Betula occidentalis, Planta, 196, 357–366, 1995.
Schaefer, K., Schwalm, C. R., Williams, C., Arain, M. A., Barr, A., Chen, J. M., Davis, K. J., Dimitrov, D., Hilton, T. W., Hollinger, D. Y., Humphreys, E., Poulter, B., Raczka, B. M., Richardson, A. D., Sahoo, A., Thornton, P., Vargas, R., Verbeeck, H., Anderson, R., Baker, I., Black, T. A., Bolstad, P., Chen, J., Curtis, P. S., Desai, A. R., Dietze, M., Dragoni, D., Gough, C., Grant, R. F., Gu, L., Jain, A., Kucharik, C., Law, B., Liu, S., Lokipitiya, E., Margolis, H. A., Matamala, R., McCaughey, J. H., Monson, R., Munger, J. W., Oechel, W., Peng, C., Price, D. T., Ricciuto, D., Riley, W. J., Roulet, N., Tian, H., Tonitto, C., Torn, M., Weng, E., and Zhou, X.: A model–data comparison of gross primary productivity: results from the North American Carbon Program site synthesis, J. Geophys. Res., 117, G03010, https://doi.org/10.1029/2012JG001960, 2012.
Schmid, H. P., Grimmond, C. S. B., Cropley, F., Offerle, B., and Su, H.-B.: Measurements of CO2 and energy fluxes over a mixed hardwood forest in the mid-western United States, Agr. Forest Meteorol., 103, 357–374, 2000.
Schmid, H. P., Su, H.-B., Vogel, C. S., and Curtis, P. S.: Ecosystem–atmosphere exchange of carbon dioxide over a mixed hardwood forest in northern lower Michigan, J. Geophys. Res., 108, 4417, https://doi.org/10.1029/2002JD003011, 2003.
Schwalm, C. R., Williams, C. A., Schaefer, K., Anderson, R., Arain, M. A., Baker, I., Barr, A., Black, T. A., Chen,G., Chen, J. M., Ciais, P., Davis, K. J., Desai, A., Dietze, M., Dragoni, D., Fischer, M. L., Flanagan, L. B., Grant, R., Gu, L., Hollinger, D., Izaurralde, R. C., Kucharik, C., Lafleur, P., Law, B. E., Li, L., Li, Z., Liu, S., Lokupitiya, E., Luo, Y., Ma, S., Margolis, H., Matamala, R., McCaughey, H., Monson, R. K., Oechel, W. C., Peng, C., Poulter, B., Price, D. T., Riciutto, D. M., Riley, W., Sahoo, A. K., Sprintsin, M., Sun, J., Tian, H., Tonitto, C., Verbeeck, H., and Verma, S. B.: A model-data intercomparison of CO2 exchange across North America: results from the North American Carbon Program site synthesis, J. Geophys. Res., 115, G00H05, https://doi.org/10.1029/2009JG001229, 2010.
Schwarz, P. A., Law, B. E., Williams, M., Irvine, J., Kurpius, M., and Moore, D.: Climatic versus biotic constraints on carbon and water fluxes in seasonally drought-affected ponderosa pine ecosystems, Global Biogeochem. Cy., 18, GB4007, https://doi.org/10.1029/2004GB002234, 2004.
Sellers, P. J., Randall, D. A., Collatz, G. J., Berry, J. A., Field, C. B., Dazlich, D. A., Zhang, C., Collelo, G. D., and Bounoua, L.: A revised land surface parameterization (SiB2) for atmospheric GCMs, Part I: Model formulation, J. Climate, 9, 676–705, 1996.
Shimizu, M., Ishida, A., and Hogetsu, T.: Root hydraulic conductivity and whole-plant water balance in tropical saplings following a shade-to-sun transfer, Oecologia, 143, 189–197, 2005.
Siqueira, M. B., Katul, G. G., Sampson, D. A., Stoy, P. C., Juang, J.-Y., McCarthy, H. R., and Oren, R: Multiscale model intercomparisons of CO2 and H2O exchange rates in a maturing southeastern US pine forest, Global Change Biol., 12, 1189–1207, 2006.
Sperry, J. S., Adler, F. R., Campbell, G. S., and Comstock, J. P.: Limitation of plant water use by rhizosphere and xylem conductance: results from a model, Plant Cell Environ., 21, 347–359, 1998.
Sperry, J. S., Hacke, U. G., Oren, R., and Comstock, J. P.: Water deficits and hydraulic limits to leaf water supply, Plant Cell Environ., 25, 251–263, 2002.
Stöckli, R., Lawrence, D. M., Niu, G.-Y., Oleson, K. W., Thornton, P. E., Yang, Z.-L., Bonan, G. B., Denning, A. S., and Running, S. W.: Use of FLUXNET in the Community Land Model development, J. Geophys. Res., 113, G01025, https://doi.org/10.1029/2007JG000562, 2008.
Stoy, P. C., Katul, G. G., Siqueira, M. B. S., Juang, J.-Y., Novick, K. A., McCarthy, H. R., Oishi, A. C., Uebelherr, J. M., Kim, H.-S., and Oren, R.: Separating the effects of climate and vegetation on evapotranspiration along a successional chronosequence in the southeastern US, Global Change Biol., 12, 2115–2135, 2006.
Stoy, P. C., Mauder, M., Foken, T., Marcolla, B., Boegh, E., Ibrom, A., Arain, M. A., Arneth, A., Aurela, M., Bernhofer, C., Cescatti, A., Dellwik, E., Duce, P., Gianelle, D., van Gorsel, E., Kiely, G., Knohl, A., Margolis, H., McCaughey, H., Merbold, L., Montagnani, L., Papale, D., Reichstein, R., Saunders, M., Serrano-Ortiz, P., Sottocornola, M., Spano, D., Vaccari, F., and Varlagin, A.: A data-driven analysis of energy balance closure across FLUXNET research sites: the role of landscape scale heterogeneity, Agr. Forest Meteorol., 171/172, 137–152, 2013.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single diagram, J. Geophys. Res., 106D, 7183–7192, 2001.
Tuzet, A., Perrier, A., and Leuning, R.: A coupled model of stomatal conductance, photosynthesis and transpiration, Plant Cell Environ., 26, 1097–1116, 2003.
Thomas, C. K., Law, B. E., Irvine, J., Martin, J. G., Pettijohn, J. C., and Davis, K. J.: Seasonal hydrology explains interannual and seasonal variation in carbon and water exchange in a semiarid mature ponderosa pine forest in central Oregon, J. Geophys. Res., 114, G04006, https://doi.org/10.1029/2009JG001010, 2009.
Tyree, M. T., Cochard, H., Cruiziat, P., Sinclair, B., and Ameglio, T.: Drought-induced leaf shedding in walnut: evidence for vulnerability segmentation, Plant Cell Environ., 16, 879–882, 1993.
Tyree, M. T., Yang, S., Cruiziat, P., and Sinclair, B.: Novel methods of measuring hydraulic conductivity of tree root systems and interpretation using AMAIZED: a maize-root dynamic model for water and solute transport, Plant Physiol., 104, 189–199, 1994.
Tyree, M. T., Velez, V., and Dalling, J. W.: Growth dynamics of root and shoot hydraulic conductance in seedlings of five neotropical tree species: scaling to show possible adaptation to differing light regimes, Oecologia, 114, 293–298, 1998.
Urbanski, S., Barford, C., Wofsy, S., Kucharik, C., Pyle, E., Budney, J., McKain, K., Fitzjarrald, D., Czikowsky, M., and Munger, J. W.: Factors controlling CO2 exchange on timescales from hourly to decadal at Harvard Forest, J. Geophys. Res., 112, G02020, https://doi.org/10.1029/2006JG000293, 2007.
Verhoef, A. and Egea, G.: Modeling plant transpiration under limited soil water: Comparison of different plant and soil hydraulic parameterizations and preliminary implications for their use in land surface models, Agr. Forest Meteorol., 191, 22–32, 2014.
Vico, G., Manzoni, S., Palmroth, S., Weih, M., and Katul, G.: A perspective on optimal leaf stomatal conductance under CO2 and light co-limitations, Agr. Forest Meteorol., 182/183, 191–199, 2013.
Williams, M., Rastetter, E. B., Fernandes, D. N., Goulden, M. L., Wofsy, S. C., Shaver, G. R., Melillo, J. M., Munger, J. W., Fan, S.-M., and Nadelhoffer, K. J.: Modelling the soil–plant–atmosphere continuum in a Quercus–Acer stand at Harvard Forest: the regulation of stomatal conductance by light, nitrogen and soil/plant hydraulic properties, Plant Cell Environ., 19, 911–927, 1996.
Williams, M., Malhi, Y., Nobre, A. D., Rastetter, E. B., Grace, J., and Pereira, M. G. P.: Seasonal variation in net carbon exchange and evapotranspiration in a Brazilian rain forest: a modelling analysis, Plant Cell Environ., 21, 953–968, 1998.
Williams, M., Eugster, W., Rastetter, E. B., McFadden, J. P., and Chapin III, F. S.: The controls on net ecosystem productivity along an Arctic transect: a model comparison with flux measurements, Global Change Biol., 6, 116–126, 2000.
Williams, M., Law, B. E., Anthoni, P. M., and Unsworth, M. H.: Use of a simulation model and ecosystem flux data to examine carbon–water interactions in ponderosa pine, Tree Physiol., 21, 287–298, 2001a.
Williams, M., Bond, B. J., and Ryan, M. G.: Evaluating different soil and plant hydraulic constraints on tree function using a model and sap flow data from ponderosa pine, Plant Cell Environ., 24, 679–690, 2001b.
Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z., Bongers, F., Cavender-Bares, J., Chapin, T., Cornelissen, J. H. C., Diemer, M., Flexas, J., Garnier, E., Groom, P. K., Gulias, J., Hikosaka, K., Lamont, B. B., Lee, T., Lee, W., Lusk, C., Midgley, J. J., Navas, M.-L., Niinemets, Ü., Oleksyn, J., Osada, N., Poorter, H., Poot, P., Prior, L., Pyankov, V. I., Roumet, C., Thomas, S. C., Tjoelker, M. G., Veneklaas, E. J., and Villar, R: The worldwide leaf economics spectrum, Nature, 428, 821–827, 2004.
Yang, S. and Tyree, M. T.: Hydraulic architecture of Acer saccharum and A. rubrum: comparison of branches to whole trees and the contribution of leaves to hydraulic resistance, J. Exper. Bot., 45, 179–186, 1994.
Zeppel, M., Macinnis-Ng, C., Palmer, A., Taylor, D., Whitley, R., Fuentes, S., Yunusa, I., Williams, M., and Eamus, D: An analysis of the sensitivity of sap flux to soil and plant variables assessed for an Australian woodland using a soil–plant–atmosphere model, Functional Plant Biol., 35, 509–520, 2008.
Zhou, S., Duursma, R. A., Medlyn, B. E., Kelly, J. W. G., and Prentice, I. C.: How should we model plant responses to drought? An analysis of stomatal and non-stomatal responses to water stress, Agr. Forest Meteorol., 182/183, 204–214, 2013.
