Subject
Creator
- Qianlai Zhuang, 0000-0002-4536-9851 7
- Licheng Liu, 0000-0002-9649-1056 4
- Youmi Oh, 0000-0002-4685-0567 2
- Bo Elberling 1
- Chang Liao, 0000-0002-7348-8858 1
- David Medvigy 1
- Edward J. Dlugokencky 1
- Gustaf Hugelius 1
- Hojeong Kang 1
- Jaehyun Lee, 0000-0003-0883-1207 1
Type
- Dataset 7
Date
Total is 7 Results
Code and Model results for Soil organic carbon is a key determinant of CH4 sink in global forest soils
10.4231/8K7W-NF84
Hojeong Kang
,
Jaehyun Lee
,
Qianlai Zhuang
,
Youmi Oh
05/09/2023
This dataset contains code and model results for the paper 'Soil organic carbon is a key determinant of CH4 sink in global forest soils' by Lee et al. (2023).
Biogeochemistry EAPS global forest soils Methane Dynamics Model (MDM) soil methane oxidation
Global CO Dynamics Model Output during 1901-2100
10.4231/XK25-7981
06/10/2020
Global soil CO fluxes during 1901-2013, 2000-2013 and 2014-2100 from model simulations. Together with published paper, figures and tables.
Atmospheric Chemistry Modeling Biogeochemistry Carbon Monoxide Climate Climate Dynamics EAPS Earth and Atmospheric Sciences
Data of global wetland methane emissions from artificial neural network modeling v1.0
10.4231/3YX4-EY30
01/21/2020
Source code of an ANN model, site level data, input data, output data and visualization results, which are presented in the manuscript "Inventorying Global Wetland Methane Emissions Based on In Situ Data and an Artificial Neural Network...
Artificial Neural Network (ANN) Atmospheric Chemistry Modeling Biogeochemistry Earth and Atmospheric Sciences Interactive Data Language (IDL) Machine Learning Matlab Methane Dynamics Model (MDM) Methane Emission
Global CO Dynamics Model Output during 1901-2100
10.4231/JGZ8-9C75
07/05/2019
Global soil CO fluxes during 1901-2013, 2000-2013 and 2014-2100 from model simulations. Together with published paper, figures and tables.
Atmospheric Chemistry Modeling Biogeochemistry Carbon Monoxide Climate Climate Dynamics EAPS Earth and Atmospheric Sciences
Microbial decomposition processes and vulnerable arctic soil organic carbon in the 21st century
10.4231/ANMV-J384
07/25/2019
Various levels of representations of biogeochemical processes in current biogeochemistry models contribute to uncertainty in carbon budget quantification. Detailed microbial mechanisms were incorporated into TEM 5.0 (Terrestrial Ecosystem Model).
Arctic Region Biogeochemistry Carbon Dynamics Climate Change EAPS Earth and Atmospheric Sciences Microbial-Based Model Terrestrial Ecosystem Model (TEM)
Code and Data for Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic
10.4231/Q3R8-SZ17
Bo Elberling
,
David Medvigy
,
Edward J. Dlugokencky
,
Gustaf Hugelius
,
Licheng Liu
,
Lisa R. Welp-Smith
,
Lori Bruhwiler
,
Ludovica D'Imperio
,
Maggie C.Y. Lau
,
Qianlai Zhuang
,
Tullis C. Onstott
,
Youmi Oh
02/04/2020
This publication contains code and data of a biogeochemistry model, XPTEM-XHAM, for paper "Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic" by Oh et al. accepted in Nature Climate Change.
Arctic Region Biogeochemistry EAPS Earth and Atmospheric Sciences Methane Dynamics Model (MDM) Methane Emission Microbial-Based Model soil
Quantifying Dissolved Organic Carbon Dynamics Using a Three-Dimensional Terrestrial Ecosystem Model at High Spatial-Temporal Resolutions
10.4231/7YY6-HQ02
Chang Liao
,
Laodong Guo
,
Qianlai Zhuang
,
Ruby Leung
12/02/2019
Arctic ecosystems are very sensitive to the global climate change. This study provides a modeling framework to adequately quantify the Arctic land ecosystem carbon budget by considering the lateral transport of carbon affected by permafrost...
Alaska Arctic Region Biogeochemistry C Carbon Cycle Climate Change Earth and Atmospheric Sciences ECO3D Ecosystem Hydrology LSM Permafrost TEM
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Results 1 - 7 of 7