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Title: Determining Spatial Scales of Soil Moisture—Cloud Coupling Pathways Using Semi-Idealized Simulations

Journal Article · · Journal of Geophysical Research. Atmospheres
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
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The spatial scales of land-atmosphere interactions over heterogeneous, realistic soil moisture patterns are critical to improve our understanding of land-atmosphere interactions. However, these scales are poorly quantified. We use high-resolution numerical experiments to quantify the spatial scales for a selected day during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign in Oklahoma. A semi-idealized approach (removing background winds and surface topography while retaining the real-world data for other boundary conditions) enables examination of the local influence from the surface. Simulations that apply uniform surface, variable land cover with uniform soil moisture, and variable land cover with variable soil moisture are then compared. Land cover variations, especially water and urban surfaces, create two variance peaks in the surface sensible heat flux in the scales >10 km (meso-β) and <6 km (meso-γ). Both peaks are enhanced by the observation-based soil moisture distribution that has most of its variance in the meso-β scale. Atmospheric response in the meso-β scale is hydrostatic with weak vertical motion. The land cover variations induce secondary circulations in the scales of 2.5–6 km. The additional soil moisture variability intensifies extreme circulations over dry soil patches and sharp sensible heat flux gradients, slightly extending the characteristic scales to 2.5–9 km. While their areal coverage is small, soil moisture variations on such “hotspots” lead to substantially larger convective cloud structure and domain-mean rainfall, calling for a consideration of their non-linear effect in large-scale models.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center; Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER)
Contributing Organization:
Argonne National Laboratory (ANL); Brookhaven National Laboratory (BNL); Oak Ridge National Laboratory (ORNL); Pacific Northwest National Laboratory (PNNL)
Grant/Contract Number:
AC02-05CH11231; AC05-76RL01830
OSTI ID:
1837435
Report Number(s):
PNNL-SA-162397
Journal Information:
Journal of Geophysical Research. Atmospheres, Journal Name: Journal of Geophysical Research. Atmospheres Journal Issue: 2 Vol. 127; ISSN 2169-897X
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English

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