Articles | Volume 9, issue 3
https://doi.org/10.5194/gmd-9-927-2016
© Author(s) 2016. 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-9-927-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
04 Mar 2016
Development and technical paper |
| 04 Mar 2016
Addressing numerical challenges in introducing a reactive transport code into a land surface model: a biogeochemical modeling proof-of-concept with CLM–PFLOTRAN 1.0
Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
Fengming Yuan
Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
Gautam Bisht
Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
Lawrence Berkeley National Laboratory, Berkeley, California, USA
Glenn E. Hammond
Pacific Northwest National Laboratory, Richland, Washington, USA
Sandia National Laboratories, Albuquerque, New Mexico, USA
Peter C. Lichtner
OFM Research–Southwest, Santa Fe, New Mexico, USA
Jitendra Kumar
Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
Richard T. Mills
Intel Corporation, Hillsboro, Oregon, USA
Xiaofeng Xu
Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
San Diego State University, San Diego, California, USA
Ben Andre
Lawrence Berkeley National Laboratory, Berkeley, California, USA
National Center for Atmospheric Research, Boulder, Colorado, USA
Forrest M. Hoffman
Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
Scott L. Painter
Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
Peter E. Thornton
Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
Viewed
Total article views: 4,916 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Dec 2015)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,663 | 2,088 | 165 | 4,916 | 170 | 192 |
- HTML: 2,663
- PDF: 2,088
- XML: 165
- Total: 4,916
- BibTeX: 170
- EndNote: 192
Total article views: 4,427 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 04 Mar 2016)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,361 | 1,911 | 155 | 4,427 | 163 | 180 |
- HTML: 2,361
- PDF: 1,911
- XML: 155
- Total: 4,427
- BibTeX: 163
- EndNote: 180
Total article views: 489 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Dec 2015)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 302 | 177 | 10 | 489 | 98 | 7 | 12 |
- HTML: 302
- PDF: 177
- XML: 10
- Total: 489
- Supplement: 98
- BibTeX: 7
- EndNote: 12
Cited
10 citations as recorded by crossref.
- Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0) G. Bisht et al. 10.5194/gmd-10-4539-2017
- Considering coasts: Adapting terrestrial models to characterize coastal wetland ecosystems T. O'Meara et al. 10.1016/j.ecolmodel.2021.109561
- Biogeochemical modeling of CO<sub>2</sub> and CH<sub>4</sub> production in anoxic Arctic soil microcosms G. Tang et al. 10.5194/bg-13-5021-2016
- Predicted Land Carbon Dynamics Are Strongly Dependent on the Numerical Coupling of Nitrogen Mobilizing and Immobilizing Processes: A Demonstration with the E3SM Land Model J. Tang & W. Riley 10.1175/EI-D-17-0023.1
- Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets Z. Langford et al. 10.3390/rs8090733
- Arctic Vegetation Mapping Using Unsupervised Training Datasets and Convolutional Neural Networks Z. Langford et al. 10.3390/rs11010069
- Simulated Hydrological Dynamics and Coupled Iron Redox Cycling Impact Methane Production in an Arctic Soil B. Sulman et al. 10.1029/2021JG006662
- Modeling strategies and data needs for representing coastal wetland vegetation in land surface models S. LaFond‐Hudson & B. Sulman 10.1111/nph.18760
- Coupling surface flow with high-performance subsurface reactive flow and transport code PFLOTRAN R. Wu et al. 10.1016/j.envsoft.2021.104959
- Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape J. Kumar et al. 10.5194/tc-10-2241-2016
9 citations as recorded by crossref.
- Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0) G. Bisht et al. 10.5194/gmd-10-4539-2017
- Considering coasts: Adapting terrestrial models to characterize coastal wetland ecosystems T. O'Meara et al. 10.1016/j.ecolmodel.2021.109561
- Biogeochemical modeling of CO<sub>2</sub> and CH<sub>4</sub> production in anoxic Arctic soil microcosms G. Tang et al. 10.5194/bg-13-5021-2016
- Predicted Land Carbon Dynamics Are Strongly Dependent on the Numerical Coupling of Nitrogen Mobilizing and Immobilizing Processes: A Demonstration with the E3SM Land Model J. Tang & W. Riley 10.1175/EI-D-17-0023.1
- Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets Z. Langford et al. 10.3390/rs8090733
- Arctic Vegetation Mapping Using Unsupervised Training Datasets and Convolutional Neural Networks Z. Langford et al. 10.3390/rs11010069
- Simulated Hydrological Dynamics and Coupled Iron Redox Cycling Impact Methane Production in an Arctic Soil B. Sulman et al. 10.1029/2021JG006662
- Modeling strategies and data needs for representing coastal wetland vegetation in land surface models S. LaFond‐Hudson & B. Sulman 10.1111/nph.18760
- Coupling surface flow with high-performance subsurface reactive flow and transport code PFLOTRAN R. Wu et al. 10.1016/j.envsoft.2021.104959
Saved (final revised paper)
Latest update: 06 Dec 2023
Short summary
We demonstrate that CLM-PFLOTRAN predictions are consistent with CLM4.5 for Arctic, temperate, and tropical sites. A tight relative tolerance may be needed to avoid false convergence when scaling, clipping, or log transformation is used to avoid negative concentration in implicit time stepping and Newton-Raphson methods. The log transformation method is accurate and robust while relaxing relative tolerance or using the clipping or scaling method can result in efficient solutions.
We demonstrate that CLM-PFLOTRAN predictions are consistent with CLM4.5 for Arctic, temperate,...
