Surface energy partitioning over four dominant vegetation types across the United States in a coupled regional climate model (Weather Research and Forecasting Model 3–Community Land Model 3.5)
Surface energy partitioning over four dominant vegetation types across the United States in a coupled regional climate model (Weather Research and Forecasting Model 3–Community Land Model 3.5)
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DOI：
10.1029/2011jd016991
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发表时间：
2012-03
影响因子：
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通讯作者：
Yaqiong Lu;L. Kueppers
中科院分区：
文献类型：
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作者：
Yaqiong Lu;L. Kueppers
[1]准确表征地表能量分配对于利用耦合气候-陆面模式研究地表过程和土地覆盖与土地利用变化的气候影响至关重要。对于这些模型，特别是新耦合的模型来说，一个关键问题是它们能否充分区分不同植被类型之间地表能量分配的差异。通过将模式输出与观测结果（AmeriFlux、云和地球辐射能系统（CERES））进行比较，我们在一个最近耦合的区域气候模式——天气研究与预报模式3-社区土地模式3.5 （WRF3-CLM3.5）中评估了美国4种主要植被类型（农田、草地、针叶常绿林和阔叶落叶林）的3年（2004-2006）地表能量分配和地表气候。以及独立斜坡模型（PRISM）数据上的参数-高程回归)和标准WRF模型输出。研究发现，WRF3-CLM3.5能较好地捕捉针叶常绿林能量分配的季节特征，但在农田、草地和阔叶落叶林中仍需改进。修正耕地和草地的叶面积指数表示可以立即改善潜热通量的模拟，从而改善能量分配。增加灌溉方案对中西部的农田尤其重要，在那里，土壤湿度和降水的强耦合可以形成正反馈，减少潜热通量，增加暖偏。对于阔叶林，叶片出苗前模拟的多余潜热通量主要来自土壤蒸发，土壤蒸发方案有待进一步完善。最后，全域高估的净辐射对感热通量、潜热通量和地热通量以及地表温度都有正偏倚。标准的WRF模拟也有类似的暖偏差，这意味着除陆地表面代码以外的模块存在错误。灵敏度测试表明，改进太阳向下辐射的模拟可以减少能量通量和温度偏差。在加入灌溉过程并对叶面积指数进行校正后，WRF3-CLM3.5在研究天然草地与灌溉农田之间、针叶常绿森林与草地之间的转换上是可靠的。
[1] Accurate representation of surface energy partitioning is crucial for studying land surface processes and the climatic influence of land cover and land use change using coupled climate-land surface models. A critical question for these models, especially for newly coupled ones, is whether they can adequately distinguish differences in surface energy partitioning among different vegetation types. We evaluated 3 years (2004–2006) of surface energy partitioning and surface climate over four dominant vegetation types (cropland, grassland, needleleaf evergreen forest, and broadleaf deciduous forest) across the United States in a recently coupled regional climate model, Weather Research and Forecasting Model 3–Community Land Model 3.5 (WRF3-CLM3.5), by comparing model output to observations (AmeriFlux, Clouds and the Earth’s Radiant Energy System (CERES), and Parameter-elevation Regressions on Independent Slopes Model (PRISM) data) and to standard WRF model output. We found that WRF3-CLM3.5 can capture the seasonal pattern in energy partitioning for needleleaf evergreen forest but needs improvements in cropland, grassland, and broadleaf deciduous forest. Correcting the leaf area index representation for cropland and grassland could immediately improve the simulation of latent heat flux and hence the energy partitioning. Adding an irrigation scheme is especially important for cropland in the Midwest, where the strongly coupled soil moisture and precipitation can form a positive feedback that reduces latent heat flux and increases the warm bias. For deciduous forest, the simulated excess latent heat flux before leaf emergence is mainly from soil evaporation, requiring further improvement in the soil evaporation scheme. Finally, the domain-wide overestimated net radiation contributes to positive biases in sensible, latent, and ground heat flux, as well as surface temperature. The standard WRF simulation has a similar warm bias, implicating errors in modules other than the land surface code. A sensitivity test suggests that improved simulation of downward solar radiation could reduce the energy flux and temperature biases. After adding irrigation process and correcting the leaf area index, WRF3-CLM3.5 appears reliable for studying conversions between natural grassland and irrigated cropland and between needleleaf evergreen forest and grassland.