Articles | Volume 7, issue 6
https://doi.org/10.5194/gmd-7-3089-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-3089-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
18 Dec 2014
Model description paper |
| 18 Dec 2014
DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Department of Life Sciences, Imperial College London, Silwood Park, Ascot, SL5 7PY, UK
R. Spahni
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
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60 citations as recorded by crossref.
- Review and Future Research Directions about Major Monitoring Method of Soil Erosion Y. LI et al. 10.1088/1755-1315/63/1/012042
- Evaluation of wetland CH4in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations R. Parker et al. 10.5194/bg-19-5779-2022
- Modeling spatiotemporal dynamics of global wetlands: comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties Z. Zhang et al. 10.5194/bg-13-1387-2016
- Global peatland area and carbon dynamics from the Last Glacial Maximum to the present – a process-based model investigation J. Müller & F. Joos 10.5194/bg-17-5285-2020
- CH4 exchanges of the natural ecosystems in China during the past three decades: The role of wetland extent and its dynamics D. Wei & X. Wang 10.1002/2016JG003418
- Impacts of climate and reclamation on temporal variations in CH<sub>4</sub> emissions from different wetlands in China: from 1950 to 2010 T. Li et al. 10.5194/bg-12-6853-2015
- Plant Regrowth as a Driver of Recent Enhancement of Terrestrial CO2 Uptake M. Kondo et al. 10.1029/2018GL077633
- Towards a microbial process-based understanding of the resilience of peatland ecosystem service provisioning – A research agenda J. Ritson et al. 10.1016/j.scitotenv.2020.143467
- Carbon uptake in Eurasian boreal forests dominates the high‐latitude net ecosystem carbon budget J. Watts et al. 10.1111/gcb.16553
- PALADYN v1.0, a comprehensive land surface–vegetation–carbon cycle model of intermediate complexity M. Willeit & A. Ganopolski 10.5194/gmd-9-3817-2016
- Future impacts of climate change on inland Ramsar wetlands Y. Xi et al. 10.1038/s41558-020-00942-2
- Wetlands of North Africa During the Mid‐Holocene Were at Least Five Times the Area Today W. Chen et al. 10.1029/2021GL094194
- ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO<sub>2</sub>, water, and energy fluxes on daily to annual scales C. Qiu et al. 10.5194/gmd-11-497-2018
- Accounting for forest age in the tile-based dynamic global vegetation model JSBACH4 (4.20p7; git feature/forests) – a land surface model for the ICON-ESM J. Nabel et al. 10.5194/gmd-13-185-2020
- Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations O. Peltola et al. 10.5194/essd-11-1263-2019
- A strong mitigation scenario maintains climate neutrality of northern peatlands C. Qiu et al. 10.1016/j.oneear.2021.12.008
- Exploring constraints on a wetland methane emission ensemble (WetCHARTs) using GOSAT observations R. Parker et al. 10.5194/bg-17-5669-2020
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- Holocene peatland and ice-core data constraints on the timing and magnitude of CO 2 emissions from past land use B. Stocker et al. 10.1073/pnas.1613889114
- N<sub>2</sub>O changes from the Last Glacial Maximum to the preindustrial – Part 2: terrestrial N<sub>2</sub>O emissions and carbon–nitrogen cycle interactions F. Joos et al. 10.5194/bg-17-3511-2020
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- Modelling northern peatland area and carbon dynamics since the Holocene with the ORCHIDEE-PEAT land surface model (SVN r5488) C. Qiu et al. 10.5194/gmd-12-2961-2019
- Development of the global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M) Z. Zhang et al. 10.5194/essd-13-2001-2021
- The Global Methane Budget 2000–2017 M. Saunois et al. 10.5194/essd-12-1561-2020
- The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2017 A. Petrescu et al. 10.5194/essd-13-2307-2021
- WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia T. Bohn et al. 10.5194/bg-12-3321-2015
- Including hydrological self-regulating processes in peatland models: Effects on peatmoss drought projections J. Nijp et al. 10.1016/j.scitotenv.2016.12.104
- Committed and projected future changes in global peatlands – continued transient model simulations since the Last Glacial Maximum J. Müller & F. Joos 10.5194/bg-18-3657-2021
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- Effects of extreme meteorological conditions in 2018 on European methane emissions estimated using atmospheric inversions R. Thompson et al. 10.1098/rsta.2020.0443
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- Terrestrial methane emissions from the Last Glacial Maximum to the preindustrial period T. Kleinen et al. 10.5194/cp-16-575-2020
- Blanket Peat Restoration: Numerical Study of the Underlying Processes Delivering Natural Flood Management Benefits S. Goudarzi et al. 10.1029/2020WR029209
- Large historical carbon emissions from cultivated northern peatlands C. Qiu et al. 10.1126/sciadv.abf1332
- Natural and anthropogenic methane fluxes in Eurasia: a mesoscale quantification by generalized atmospheric inversion A. Berchet et al. 10.5194/bg-12-5393-2015
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- Utilizing Earth Observations of Soil Freeze/Thaw Data and Atmospheric Concentrations to Estimate Cold Season Methane Emissions in the Northern High Latitudes M. Tenkanen et al. 10.3390/rs13245059
- The role of northern peatlands in the global carbon cycle for the 21st century C. Qiu et al. 10.1111/geb.13081
- Using Atmospheric Inverse Modelling of Methane Budgets with Copernicus Land Water and Wetness Data to Detect Land Use-Related Emissions M. Tenkanen et al. 10.3390/rs16010124
- Methane fluxes in the high northern latitudes for 2005–2013 estimated using a Bayesian atmospheric inversion R. Thompson et al. 10.5194/acp-17-3553-2017
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- Modelling past and future peatland carbon dynamics across the pan‐Arctic N. Chaudhary et al. 10.1111/gcb.15099
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- The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2019 A. Petrescu et al. 10.5194/essd-15-1197-2023
- The global methane budget 2000–2012 M. Saunois et al. 10.5194/essd-8-697-2016
- Modeling Carbon Accumulation and Permafrost Dynamics of Northern Peatlands Since the Holocene B. Zhao et al. 10.1029/2022JG007009
- Gridded maps of wetlands dynamics over mid-low latitudes for 1980–2020 based on TOPMODEL Y. Xi et al. 10.1038/s41597-022-01460-w
- Methane budget estimates in Finland from the CarbonTracker Europe-CH<sub>4</sub> data assimilation system A. Tsuruta et al. 10.1080/16000889.2018.1565030
- Methane at Svalbard and over the European Arctic Ocean S. Platt et al. 10.5194/acp-18-17207-2018
- Past and future evolution of Abies alba forests in Europe – comparison of a dynamic vegetation model with palaeo data and observations M. Ruosch et al. 10.1111/gcb.13075
- Constraints on oceanic methane emissions west of Svalbard from atmospheric in situ measurements and Lagrangian transport modeling I. Pisso et al. 10.1002/2016JD025590
- Modelling past, present and future peatland carbon accumulation across the pan-Arctic region N. Chaudhary et al. 10.5194/bg-14-4023-2017
- Modelling Holocene peatland dynamics with an individual-based dynamic vegetation model N. Chaudhary et al. 10.5194/bg-14-2571-2017
- A predictive algorithm for wetlands in deep time paleoclimate models D. Wilton et al. 10.5194/gmd-12-1351-2019
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Latest update: 20 Apr 2024
Short summary
Simulating the spatio-temporal dynamics of inundation is key to understanding the role of wetlands under past and future climate change. Here, we describe and assess the DYPTOP model that predicts the extent of inundation and the global spatial distribution of peatlands. DYPTOP makes use of high-resolution topography information and uses ecosystem water balance and peatland soil C balance criteria to simulate peatland spatial dynamics and carbon accumulation.
Simulating the spatio-temporal dynamics of inundation is key to understanding the role of...
