Quantifying the Impact of Excess Moisture From Transpiration From Crops on an...

Souri, A., H. Wang, Gonzalez Abad, X. Liu, and K. Chance (2020), Quantifying the Impact of Excess Moisture From Transpiration From Crops on an Extreme Heat Wave Event in the Midwestern U.S.: A Top‐Down Constraint From Moderate Resolution Imaging Spectroradiometer Water Vapor Retrieval, J. Geophys. Res., 125, e2019JD031941, doi:10.1029/2019JD031941.

The primary focus of this study is to understand the contribution from excess moisture from crop transpiration to the severity of a heat wave episode that hit the Midwestern U.S. from 16 to 20 July 2011. To elucidate this, we first provide an optimal estimate of the transpiration water vapor flux using satellite total column water vapor retrievals whose accuracy and precision are characterized using independent observations. The posterior transpiration flux is estimated using a local ensemble transform Kalman filter that employs a mesoscale weather model as the forward model. The new estimation suggests that the prior values of transpiration flux from crops are biased high by 15%. We further use the constrained flux to examine the sensitivity of meteorology to the contributions from crops. Over the agricultural areas during daytime, elevated moisture (up to 40%) from crops not only increases humidity (thus the heat index) but also provides a positive radiative forcing by increasing downward longwave radiation (13 ± 4 W m−2) that results in even higher surface air temperature (+0.4 °C). Consequently, we find that the elevated moisture generally provides positive feedback to aggravate the heat wave, with daytime enhancements of heat index by as large as 3.3 ± 0.8 °C. Due to a strong diurnal cycle in the transpiration, the feedback tends to be stronger in the afternoon (up to 5 °C) and weaker at night. Results offer a potential basis for designing mitigation strategies for the effect of transpiration from agriculture in the future, in addition to improving the estimation of canopy transpiration.

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Research Program: 
Applied Sciences Program (ASP)
Atmospheric Composition
Atmospheric Composition Modeling and Analysis Program (ACMAP)
Aura Science Team