干旱区生态环境知识资源中心(Arid): The surface-boundary layer connection across spatial scales of irrigation-driven thermal heterogeneity: An integrated data and modeling study of the LIAISE field campaign

Arid

DOI	10.1016/j.agrformet.2023.109452
	The surface-boundary layer connection across spatial scales of irrigation-driven thermal heterogeneity: An integrated data and modeling study of the LIAISE field campaign
	Mangan, Mary Rose; Hartogensis, Oscar; Boone, Aaron; Branch, Oliver; Canut, Guylaine; Cuxart, Joan; de Boer, Hugo J.; Le Page, Michel; Martinez-Villagrasa, Daniel; Miro, Josep Ramon; Price, Jeremy; de Arellano, Jordi Vila-Guerau
通讯作者	Mangan, MR
来源期刊	AGRICULTURAL AND FOREST METEOROLOGY
ISSN	0168-1923
EISSN	1873-2240
出版年	2023
卷号	335
英文摘要	Irrigation in semi-arid regions induces thermal heterogeneity across a range of spatial scales that impacts the partitioning of energy at the surface, the development of the atmospheric boundary layer, and the bidirectional interactions between the atmosphere and the surface. In this analysis, we use data from the Land Surface Interactions with the Atmosphere in the Iberian Semi-Arid Environment (LIAISE) experiment combined with a coupled land-atmosphere model to understand the role of the scales of irrigation-induced, thermal heterogeneity on the surface fluxes and consequently, the development of the diurnal convective boundary layer. The surface heterogeneity is characterized by Bowen ratios that range from -0.01 in the irrigated areas to -30 in the non-irrigated areas; however, the observed boundary-layers dynamics in both locations are similar. In this analysis, we address the questions of how the surface fluxes impact the development of the boundary-layer dynamics and how the boundary layer influences the diurnal cycle of surface fluxes. To interpret the observations, we introduce a heterogeneity scaling scheme where length scales range from local scale (-100 m) to regional scale (-10 km) to investigate the role of scale on surface representation in numerical models and to address the discrepancy between surface observations and their representation in weather and climate models.We find that at the surface, both the available energy and its partitioning depend on spatial scale. The observed boundary-layer properties can be explained through the composite of surface fluxes at the regional scale. Surface fluxes at the local scales are unable to replicate the observed boundary layer - even when including large-scale contributions. We find that non-local boundary layer processes like advection are important for partitioning energy at the local scale. We explore the connection between surface fluxes and the development of the boundary layer and the potential non-local effects on boundary-layer development.
英文关键词	Surface heterogeneity Scaling surface fluxes Boundary-layer dynamics Heat & moisture advection
类型	Article
语种	英语
开放获取类型	Green Published, Green Submitted, hybrid
收录类别	SCI-E
WOS记录号	WOS:000982477800001
WOS关键词	PARAMETERIZATION ; INHOMOGENEITIES ; ENTRAINMENT ; INVERSION
WOS类目	Agronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS研究方向	Agriculture ; Forestry ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395003
推荐引用方式 GB/T 7714	Mangan, Mary Rose,Hartogensis, Oscar,Boone, Aaron,et al. The surface-boundary layer connection across spatial scales of irrigation-driven thermal heterogeneity: An integrated data and modeling study of the LIAISE field campaign[J],2023,335.
APA	Mangan, Mary Rose.,Hartogensis, Oscar.,Boone, Aaron.,Branch, Oliver.,Canut, Guylaine.,...&de Arellano, Jordi Vila-Guerau.(2023).The surface-boundary layer connection across spatial scales of irrigation-driven thermal heterogeneity: An integrated data and modeling study of the LIAISE field campaign.AGRICULTURAL AND FOREST METEOROLOGY,335.
MLA	Mangan, Mary Rose,et al."The surface-boundary layer connection across spatial scales of irrigation-driven thermal heterogeneity: An integrated data and modeling study of the LIAISE field campaign".AGRICULTURAL AND FOREST METEOROLOGY 335(2023).