Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements
Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements
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DOI：
10.5194/gmd-14-3269-2021
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发表时间：
2020-09
影响因子：
5.1
通讯作者：
A. Harper;Karina E. Williams;Karina E. Williams;P. McGuire;M. Rojas;D. Hemming;D. Hemming;A. Verhoef
中科院分区：
文献类型：
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作者：
A. Harper;Karina E. Williams;Karina E. Williams;P. McGuire;M. Rojas;D. Hemming;D. Hemming;A. Verhoef
抽象的。由于气候变化，预计未来干旱将会增加，给生态系统带来无数的影响。植物对干旱土壤的反应是降低气孔导度，以保持水分，避免水力破坏。尽管植物干旱响应对全球碳循环和局部和区域气候反馈具有重要意义，但陆地表面模型无法捕捉到观测到的植物对土壤水分胁迫的响应。我们在季节和年度时间尺度上评估了土壤水分胁迫对英国联合陆地环境模拟器(Jules)vn4.9中模拟的总初级生产力(GPP)和潜在能通量(LE)的影响，并评估了模型中10种不同的土壤水分胁迫表示。对于默认配置，GPP在温带生物群地点比在热带或高纬度(寒冷地区)地点更接近实际，而LE在温带和高纬度(寒冷地区)地点模拟得最好。不是由于土壤水分胁迫造成的误差，可能与物候学有关，导致了热带稀树草原和落叶林地的GPP模型偏差。我们发现，对于大多数生物群落和气候，计算土壤水分压力的三种替代方法产生的结果比默认的参数化法更现实。所有这些措施都涉及将土壤层数从4层增加到14层，土壤深度从3.0米增加到10.8米。此外，我们还发现，当土壤基质势取代应力方程中的体积含水率时(“soil14_psi”实验)，当诱导土壤水分胁迫的临界阈值降低(“soil14_P0”)时，以及当植物能够获得更深土壤层的土壤水分时(“soil14_dr*2”)，土壤质量都得到了改善。对于LE，在温带混交林的默认配置下偏差最大，一年中的大部分时间都出现了高估。在这些地点，减少土壤水分胁迫(使用上述新的参数化)增加了LE，增加了模型偏差，但改善了模拟的季节循环，使月变化更接近LE的实测值。进一步评估许多地点LE偏高的原因将有助于通过新的土壤水分胁迫参数来改善碳通量和能量通量。增加土壤深度和植物获得深层土壤水分的机会改善了模拟的许多方面，我们建议在未来的工作中使用Jules进行这些设置，或者作为在其他模型中改善陆地表面碳和水通量的一般方法。此外，使用土壤基质势提供了包括植物功能类型特定参数的机会，以进一步改进模拟的通量。
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.