Numerical Evaluation of JULES Surface Tiling Scheme with High-Resolution Atmospheric Forcing and Land Cover Data

Park, Juhan; Lee, Seung-Jae; Ha, Tae Yong

doi:10.2151/sola.2018-004

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…For example, Melton et al (2017) used two linked algorithms to provide tiles of representative soil textures for subgrids in a terrestrial ecosystem model and found that the model is relatively insensitive to subgrid soil textures compared to a simple grid-mean soil texture at a global scale. However, the treatment without soil subgrid structure in JULES resulted in soil-moisture-dependent anomalies in simulated carbon flux (Park et al, 2018). Further research is necessary to investigate the upscaling effect on models.…”

Section: Model Use Of Soil Data Derived By the Linkage Methodsmentioning

confidence: 99%

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Shangguan¹

2019

Preprint

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Soil is an important regulator of Earth system processes, but remains one of the least well-described data layers in Earth system models (ESMs). We reviewed global soil property maps from the perspective of ESMs, including soil physical and chemical and biological properties, which can also offer insights to soil data developers and users. These soil datasets provide model inputs, initial variables, and benchmark datasets. For modelling use, the dataset should be geographically continuous and scalable and have uncertainty estimates. The popular soil datasets used in ESMs are often based on limited soil profiles and coarse-resolution soil-type maps with various uncertainty sources. Updated and comprehensive soil information needs to be incorporated into ESMs. New generation soil datasets derived through digital soil mapping with abundant, harmonized, and quality-controlled soil observations and environmental covariates are preferred to those derived through the linkage method (i.e. taxotransfer rule-based method) for ESMs. SoilGrids has the highest accuracy and resolution among the global soil datasets, while other recently developed datasets offer useful compensation. Because there is no universal pedotransfer function, an ensemble of them may be more suitable for providing derived soil properties to ESMs. Aggregation and upscaling of soil data are needed for model use, but can be avoided by using a subgrid method in ESMs at the expense of increases in model complexity. Producing soil property maps in a time series still remains challenging. The uncertainties in soil data need to be estimated and incorporated into ESMs.

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Section: Model Use Of Soil Data Derived By the Linkage Methodsmentioning

confidence: 99%

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Shangguan¹

2019

Preprint

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“…This dataset was implemented in CLM4.5, and there were significant influences on the water and energy simulations compared to the default constant depth (Brunke et al, 2016). Shangguan et al (2017) developed a global DTB by digital soil mapping based on about 1.7 million observations from soil profiles and water wells, which has a much higher accuracy than the dataset by Pelletier et al (2016). Vrettas and Fung (2016) showed that weathered bedrock stores a significant fraction (more than 30 %) of the total water despite its low porosity.…”

Section: Soil Dataset Incorporated Into Esmsmentioning

confidence: 99%

A review of the global soil property maps for Earth system models

Dai

Shangguan

Wei

et al. 2019

SOIL

122

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Abstract. Soil is an important regulator of Earth system processes, but remains one of the least well-described data layers in Earth system models (ESMs). We reviewed global soil property maps from the perspective of ESMs, including soil physical and chemical and biological properties, which can also offer insights to soil data developers and users. These soil datasets provide model inputs, initial variables, and benchmark datasets. For modelling use, the dataset should be geographically continuous and scalable and have uncertainty estimates. The popular soil datasets used in ESMs are often based on limited soil profiles and coarse-resolution soil-type maps with various uncertainty sources. Updated and comprehensive soil information needs to be incorporated into ESMs. New generation soil datasets derived through digital soil mapping with abundant, harmonized, and quality-controlled soil observations and environmental covariates are preferred to those derived through the linkage method (i.e. taxotransfer rule-based method) for ESMs. SoilGrids has the highest accuracy and resolution among the global soil datasets, while other recently developed datasets offer useful compensation. Because there is no universal pedotransfer function, an ensemble of them may be more suitable for providing derived soil properties to ESMs. Aggregation and upscaling of soil data are needed for model use, but can be avoided by using a subgrid method in ESMs at the expense of increases in model complexity. Producing soil property maps in a time series still remains challenging. The uncertainties in soil data need to be estimated and incorporated into ESMs.

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Impact of leaf area index from various sources on estimating gross primary production in temperate forests using the JULES land surface model

Lee

Park

Cho

et al. 2019

Agricultural and Forest Meteorology

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Numerical Evaluation of JULES Surface Tiling Scheme with High-Resolution Atmospheric Forcing and Land Cover Data

Cited by 3 publications

References 42 publications

Reply to Anonymous Referee #1's first comment (same as the previous reply to this comment)

Reply to Anonymous Referee #1's first comment (same as the previous reply to this comment)

A review of the global soil property maps for Earth system models

Impact of leaf area index from various sources on estimating gross primary production in temperate forests using the JULES land surface model

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