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Your search keyword '"Santanello, Joseph A."' showing total 113 results
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113 results on '"Santanello, Joseph A."'

102. Introducing the atmospheric thermodynamics lidar in Space: ATLAS

Author

Sodnik, Zoran, Karafolas, Nikos, Cugny, Bruno, Di Girolamo, Paolo, Behrendt, Andreas, Wulfmeyer, Volker, Comerón, Adolfo, Keckhut, Philippe, Hauchecorne, Alain, Richard, Evelyne, Marenco, Franco, Vaughan, Geraint, Rotach, Mathias, Potthast, Roland, Geer, Alan, Demoz, Belay B., Santanello, Joseph, Whiteman, David N., and Turner, David D.

Published
2019
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104. Impact of urbanization on US surface climate

Author

Bounoua, Lahouari, primary, Zhang, Ping, additional, Mostovoy, Georgy, additional, Thome, Kurtis, additional, Masek, Jeffrey, additional, Imhoff, Marc, additional, Shepherd, Marshall, additional, Quattrochi, Dale, additional, Santanello, Joseph, additional, Silva, Julie, additional, Wolfe, Robert, additional, and Toure, Ally Mounirou, additional

Published
2015
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112. Using ARM Observations to Evaluate Climate Model Simulations of Land‐Atmosphere Coupling on the U.S. Southern Great Plains

Author

Phillips, Thomas J., Klein, Stephen A., Ma, Hsi‐Yen, Tang, Qi, Xie, Shaocheng, Williams, Ian N., Santanello, Joseph A., Cook, David R., and Torn, Margaret S.

Abstract

Several independent measurements of warm‐season soil moisture and surface atmospheric variables recorded at the ARM Southern Great Plains (SGP) research facility are used to estimate the terrestrial component of land‐atmosphere coupling (LAC) strength and its regional uncertainty. The observations reveal substantial variation in coupling strength, as estimated from three soil moisture measurements at a single site, as well as across six other sites having varied soil and land cover types. The observational estimates then serve as references for evaluating SGP terrestrial coupling strength in the Community Atmospheric Model coupled to the Community Land Model. These coupled model components are operated in both a free‐running mode and in a controlled configuration, where the atmospheric and land states are reinitialized daily, so that they do not drift very far from observations. Although the controlled simulation deviates less from the observed surface climate than its free‐running counterpart, the terrestrial LAC in both configurations is much stronger and displays less spatial variability than the SGP observational estimates. Preliminary investigation of vegetation leaf area index (LAI) substituted for soil moisture suggests that the overly strong coupling between model soil moisture and surface atmospheric variables is associated with too much evaporation from bare ground and too little from the vegetation cover. These results imply that model surface characteristics such as LAI, as well as the physical parameterizations involved in the coupling of the land and atmospheric components, are likely to be important sources of the problematical LAC behaviors. ARM observational data are used to estimate the terrestrial component of land‐atmosphere coupling strength in the U.S. SGP regionBoth free‐running and constrained climate model simulations of regional atmospheric coupling with soil moisture are too strongSimulated coupling of local vegetation leaf area with surface evaporative fraction is weaker than the observational estimate

Published
2017
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113. Assessment of Irrigation Physics in a Land Surface Modeling Framework using Non-Traditional and Human-Practice Datasets.

Author

Lawston PM, Santanello JA Jr, Franz TE, and Rodell M

Abstract

Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASA's Land Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily time scales. In addition, this study uses point and gridded soil moisture observations from fixed and roving Cosmic Ray Neutron Probes and co-located human practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation for accurate simulation of water and energy states and fluxes over cropland.

Published
2017
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