Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019JD032255 |
Modeling Spatial Heterogeneity in Surface Turbulent Heat Flux in the US Southern Great Plains | |
Williams, Ian N.1; Lee, Jungmin M.2; Tadic, Jovan1; Zhang, Yunyan2; Chu, Housen1 | |
2020-07-16 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES |
ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2020 |
卷号 | 125期号:13 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Advances in numerical modeling of cloud dynamics are driving a need for improved land model prediction at convective storm scales. In this study, satellite and ground-based vegetation remote sensing data were combined with land model experiments to more accurately characterize land surface spatial heterogeneity in the Community Land Model (CLM4.0). The new subgrid classification of plant functional types (PFT) and leaf area index (LAI) enables consistent comparison between models and ground-based flux measurements in the U.S. southern Great Plains. Errors in vegetation data sets (inferred from comparison between 250 m satellite and ground-based LAI), while large, had less impact on the simulated characteristics of spatial heterogeneity compared to errors in model representation of surface energy partitioning (between latent and sensible heat flux) and its relationship to LAI. Predicted spatial heterogeneity in surface energy partitioning was enhanced after replacing soil and stomatal resistance parameters with a new set that better predicts the observed relationship to LAI. These modifications increase the number of smaller (mesoscale) dry land patches having higher sensible heat flux. The parameter experiments suggest that vegetation state and processes (transpiration) act to broaden the size spectrum of surface heat flux heterogeneity, which can influence clouds and convective initiation. Moreover, improvements in vegetation input data and model parameters had partially compensating effects on surface flux heterogeneity, indicating the importance of evaluating input data and parameterizations together to improve prediction at higher spatial resolutions. |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000551484700015 |
WOS关键词 | LAND-ATMOSPHERE INTERACTIONS ; SOIL-MOISTURE ; MESOSCALE ; SCALE ; CLOUDS ; IMPACT ; COVER ; TRANSPIRATION ; VARIABILITY ; EVAPORATION |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/289484 |
专题 | 气候变化 |
作者单位 | 1.Lawrence Berkeley Natl Lab, Climate & Ecosyst Sci Div, Berkeley, CA 94720 USA; 2.Lawrence Livermore Natl Lab, Livermore, CA 94550 USA |
推荐引用方式 GB/T 7714 | Williams, Ian N.,Lee, Jungmin M.,Tadic, Jovan,et al. Modeling Spatial Heterogeneity in Surface Turbulent Heat Flux in the US Southern Great Plains[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2020,125(13). |
APA | Williams, Ian N.,Lee, Jungmin M.,Tadic, Jovan,Zhang, Yunyan,&Chu, Housen.(2020).Modeling Spatial Heterogeneity in Surface Turbulent Heat Flux in the US Southern Great Plains.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,125(13). |
MLA | Williams, Ian N.,et al."Modeling Spatial Heterogeneity in Surface Turbulent Heat Flux in the US Southern Great Plains".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 125.13(2020). |
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