subject: EAPS creator: Qianlai Zhuang, 0000-0002-4536-9851
10.4231/FYFN-1Z68
Mingyang Guo , Narasinha Shurpali , Pertti Martikainen , Pirkko Kortelainen , Qianlai Zhuang , Sari Juutinen , Zeli Tan
03/30/2020
This publication includes model output of a lake biogeochemistry model ALBM, and data analysis codes which were used for paper 'Rising methane emissions from boreal lakes due to increasing ice-free days' by Guo et al. in Environmental Research...
10.4231/6647-C769
Bailu Zhao , Qianlai Zhuang , Steve Frolking
05/26/2022
This dataset is used to reproduce the results in Modeling carbon accumulation and greenhouse gas emissions of northern peatlands since the Holocene. The dataset includes simulated pan-Arctic peat thickness, soil C stock and historical permafrost...
basal date EAPS Holocene P-TEM pan-Arctic peatland Permafrost
10.4231/QP7V-V527
09/20/2022
This study simulates the C dynamics of northern peatlands during1990-2300. Before 2100, northern peatlands are a C source under all climate scenarios except for the mildest one. Afterwards, northern peatlands under all scenarios are C sources.
10.4231/FV42-TZ12
Bailu Zhao , Qianlai Zhuang , Steve Frolking
10/24/2022
This dataset is used to reproduce the results in Modeling carbon accumulation and greenhouse gas emissions of northern peatlands since the Holocene. The dataset includes simulated pan-Arctic peat thickness, soil C stock and historical permafrost...
EAPS Holocence norhtern peatlands P-TEM Permafrost Python Code
10.4231/E1AD-DB33
10/04/2022
This data contains model output of net primary production (NPP), heterotrophic respiration (RH), foliage projection cover (FPC) and soil temperature.
10.4231/SJC1-9F83
11/15/2022
This data contains the processed model output of methane emission from the ALBM and TEM-MDM models.
10.4231/ZJM7-A207
05/02/2024
It contains simulation results of TEM in Eurasia during 2003-2016.
Carbon Dynamics EAPS Terrestrial Ecosystem Model (TEM) Wildfire
10.4231/NR0B-EJ07
Qianlai Zhuang , Xinyu Liu , Xuan Xi
05/24/2024
This dataset contains the main materials for predicting site-level surface soil moisture based on a developed hybrid physics-guided deep learning modeling framework.
EAPS Long short-term memory (LSTM) Physics-Guided Deep Learning Soil Moisture Terrestrial Ecosystem Model (TEM)
10.4231/SBB0-V865
Qianlai Zhuang , Xinyu Liu , Xuan Xi
08/21/2024
This dataset contains the main materials for predicting site-level surface soil moisture based on a developed hybrid physics-guided deep learning modeling framework.
EAPS Long short-term memory (LSTM) Physics-Guided Deep Learning Soil Moisture Terrestrial Ecosystem Model (TEM)
10.4231/JZ10-FH54
John Melack , L. Ruby Leung , Mingyang Guo , Qianlai Zhuang , Xin Lan , Youmi Oh , Zeli Tan
11/12/2021
Model output of methane diffusive, ebullitive, and total fluxes.
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