Published May 3, 2021 | Version v1
Dataset Open

Analyzing coastal fog effects on carbon and water fluxes in a California agricultural system using approaches in biometeorology, remote sensing, and plant physiology

  • 1. San Francisco State University
  • 2. Scripps Institution of Oceanography
  • 3. University of California, Santa Cruz

Description

In coastal California, the peak growing season of economically important crops is concurrent with fog events, which buffer drought stress during the dry season. Coastal fog patterns are changing, so we quantified its effects on the energy, water, and carbon fluxes of an economically important cropland at multiple spatial and temporal scales. Our study site was a strawberry farm located in the fog-belt of the Salinas Valley, California. We used GOES-satellite total albedo to detect and quantify large scale patterns of coastal fog. We used eddy covariance (EC) to quantify actual evapotranspiration and gross primary productivity (GPP) at the field scale from July-September 2016. We measured canopy-scale strawberry physiology on foggy and non-foggy days within the measurement footprint of the EC tower. Downwelling longwave radiation (L↓), observed by a surface-mounted pyrgeometer, was consistently higher on foggy compared to clear-sky days (regardless of fog-drip), indicating that emission of longwave radiation was derived almost entirely from the cloud base. L↓ and total GOES albedo were positively and strongly correlated (R2=0.68, P<0.01). For both field- and canopy-levels, water-use and light-use efficiency increased by as much as 50% and 70%, respectively, during foggy compared to non-foggy conditions. The initial slope of the curvilinear relationship fit between GPP and photosynthetically active radiation was twice as steep during foggy (α=0.0395) than non-foggy (α=0.0210) conditions, suggesting that the scattering of light during fog events enhances photosynthetic output of whole-plants. Our results suggest that irrigation for these fields could be rescheduled during foggy periods without sacrificing plant productivity.

Notes

Datafile 'Eddy-Covariance-with-GOESalbedo-Data' is the eddy covariance data with the GOES-derived albedo values at our study site. Combining these datasets is more useful for generating relationships between field and satellite observations.

Datafile 'Plant-Canopy-Data' is the CO2 and water vapor fluxes at the plant-canopy scale. These instantaneous measurements were made within the footprint of the eddy flux tower.

Datafile 'Irrigation-Soilmoisture-Data' is irrigation flow rates and soil moisture at multiple depths.

Funding provided by: U.S. Department of Agriculture
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000199
Award Number: 2015-67012-22769: NIFA Postdoctoral Fellowship

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Eddy-Covariance-with-GOESalbedo.csv

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