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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #354662
Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Space-borne microwave surface soil moisture observations provide missing link between summertime precipitation and surface temperature biases in CMIP5 simulations over conterminous United States

Author
item AL-YAARI, A. - Collaborator
item DUCHARNE, A. - Sorbonne Universities, Paris
item Crow, Wade
item CHERUY, F. - Pierre And Marie Curie University
item WIGNERON, J. - National Institute For Agricultural Research (INIAP)

Submitted to: Scientific Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/15/2018
Publication Date: 2/1/2019
Citation: Al-Yaari, A., Ducharne, A., Crow, W.T., Cheruy, F., Wigneron, J. 2019. Space-borne microwave surface soil moisture observations provide missing link between summertime precipitation and surface temperature biases in CMIP5 simulations over conterminous United States. Scientific Reports. 9:1657. https://doi.org/10.1038/s41598-018-38309-5.
DOI: https://doi.org/10.1038/s41598-018-38309-5

Interpretive Summary: In agricultural regions, summer heatwaves can significantly reduce agricultural crop yields. Recent research has shown that these events can be intensified by interactions between the land surface and lower atmosphere. This suggests that monitoring land surface conditions (particularly soil moisture) can help us better predict the occurrence and severity of heatwaves. Because large-scale observations of soil moisture are difficult to obtain, past work on this topic has relied heavily on either simulated soil moisture (derived from models) or soil moisture proxies based on observed rainfall. This paper represents the first effort to replicate past studies using direct soil moisture retrievals derived from satellite remote sensing. Results confirm the important role soil moisture plays in determining summertime air temperature variations in the United States and provide new insight into how the role of soil moisture varies regionally. These insights will eventually be used to improve coupled land/atmosphere models that form the basis of climate projections over important agricultural regions of the United States.

Technical Abstract: As demonstrated by several studies based on CMIP5 simulations, a marked dry/warm summer biases can be found in climate projections in the conterminous United States (CONUS) - particularly the central Great Plains (CGP) region. These biases have critical implications for the interpretation of climate change projections; however, the complex overlap of multiple land-atmosphere feedback processes make them difficult to explain (and therefore correct). Even though surface soil moisture (SM) is often cited as a key control variable in these processes, its specific role is still largely unknown. Here, we use recently developed remotely sensed SM products to analyse the link between spatial patterns of summertime SM, precipitation and air temperature biases over CONUS in 20 different CMIP5 simulations. We identify three types of bias combinations: i) a dry/warm bias over the CGP region, with a significant inter-model spatial correlation between SM and air temperature biases (R=-0.65), ii) a wet/cold bias in NW CONUS, and iii) a dry/cold bias in SW CONUS. These results demonstrate the value of large-scale SM observations for resolving the full feed-back loop between precipitation and temperature and therefore bridging an important gap in the study of land-atmosphere coupling.