ORCID Profile
0000-0003-4218-6731
Current Organisations
University of Bristol
,
James Cook University
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Publisher: Copernicus GmbH
Date: 24-09-2020
Publisher: Elsevier BV
Date: 06-2021
Publisher: Copernicus GmbH
Date: 03-06-2021
Abstract: Abstract. Drought is predicted to increase in the future due to climate change, bringing with it myriad impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local and regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales and evaluated 10 different representations of soil moisture stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high-latitude (cold-region) sites, while LE was best simulated in temperate and high-latitude (cold) sites. Errors that were not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savanna and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14 and the soil depth from 3.0 to 10.8 m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation (the “soil14_psi” experiments), when the critical threshold value for inducing soil moisture stress was reduced (“soil14_p0”), and when plants were able to access soil moisture in deeper soil layers (“soil14_dr*2”). For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and increased model biases but improved the simulated seasonal cycle and brought the monthly variance closer to the measured variance of LE. Further evaluation of the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES or as a general way to improve land surface carbon and water fluxes in other models. In addition, using soil matric potential presents the opportunity to include plant functional type-specific parameters to further improve modeled fluxes.
Publisher: Copernicus GmbH
Date: 24-09-2020
DOI: 10.5194/GMD-2020-273
Abstract: Abstract. Drought is predicted to increase in the future due to climate change, bringing with it a myriad of impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance, in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local/regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales, and evaluated ten different representations of stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high latitudes/cold region sites, while LE was best simulated in temperate and high latitude/cold sites. Errors not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savannah and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14, and the soil depth from 3m to 10.8m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation, when the onset of stress was delayed, and when roots extended deeper into the soil. For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and made the simulation worse. Further evaluation into the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress.
Publisher: Wiley
Date: 05-10-2022
DOI: 10.1002/GDJ3.180
Abstract: We provide a 1‐year dataset of atmospheric surface CO 2 , CH 4 and H 2 O concentrations and δ 13 C‐CO 2 values from an Australian savanna site. These semi‐arid ecosystems act as carbon sinks in wet years but the persistence of the sink in dry years is uncertain. The dataset can be used to constrain uncertainties in modelling of greenhouse gas budgets, improve algorithms for satellite measurements and characterize the role of vegetation and soil in modulating atmospheric CO 2 concentrations. We found pronounced seasonal variations in daily mean CO 2 concentrations with an increase (by 5–7 ppmv) after the first rainfall of the wet season in early December with peak concentrations maintained until late January. The CO 2 increase reflected the initiation of rapid microbial respiration from soil and vegetation sources upon initial wetting. As the wet season progressed, daily CO 2 concentrations were variable, but generally decreased back to dry season levels as CO 2 assimilation by photosynthesis increased. Mean daily concentrations of CH 4 increased in the wet season by up to 0.2 ppmv relative to dry season levels as the soil profile became waterlogged after heavy rainfall events. During the dry season there was regular cycling between maximum CO 2 /minimum δ 13 C‐CO 2 at night and minimum CO 2 /maximum δ 13 C‐CO 2 during the day. In the wet season diel patterns were less regular in response to variable cloud cover and rainfall. CO 2 isotope data showed that in the wet season, surface CO 2 was predominantly a two‐component mixture influenced by C 3 plant assimilation (day) and soil lant respiration (night), while regional background air from higher altitudes represented an additional CO 2 source in the dry season. Higher wind speeds during the dry season increased vertical mixing compared to the wet season. In addition, night‐time advection of high‐altitude air during low temperature conditions also promoted mixing in the dry season.
Location: United Kingdom of Great Britain and Northern Ireland
Location: Germany
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Thomas Napier.