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Airborne Lidar Measurements of XCO(2) in Synoptically Active Environment and Associated Comparisons With Numerical Simulations
Frontal boundaries have been shown to cause large changes in CO(2) mole‐fractions, but clouds and the complex vertical structure of fronts make these gradients difficult to observe. It remains unclear how the column average CO(2) dry air mole‐fraction (XCO(2)) changes spatially across fronts, and ho...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9786724/ https://www.ncbi.nlm.nih.gov/pubmed/36582815 http://dx.doi.org/10.1029/2021JD035664 |
Sumario: | Frontal boundaries have been shown to cause large changes in CO(2) mole‐fractions, but clouds and the complex vertical structure of fronts make these gradients difficult to observe. It remains unclear how the column average CO(2) dry air mole‐fraction (XCO(2)) changes spatially across fronts, and how well airborne lidar observations, data assimilation systems, and numerical models without assimilation capture XCO(2) frontal contrasts (ΔXCO(2,) i.e., warm minus cold sector average of XCO(2)). We demonstrated the potential of airborne Multifunctional Fiber Laser Lidar (MFLL) measurements in heterogeneous weather conditions (i.e., frontal environment) to investigate the ΔXCO(2) during four seasonal field campaigns of the Atmospheric Carbon and Transport‐America (ACT‐America) mission. Most frontal cases in summer (winter) reveal higher (lower) XCO(2) in the warm (cold) sector than in the cold (warm) sector. During the transitional seasons (spring and fall), no clear signal in ΔXCO(2) was observed. Intercomparison among the MFLL, assimilated fields from NASA's Global Modeling and Assimilation Office (GMAO), and simulations from the Weather Research and Forecasting‐—Chemistry (WRF‐Chem) showed that (a) all products had a similar sign of ΔXCO(2) though with different levels of agreement in ΔXCO(2) magnitudes among seasons; (b) ΔXCO(2) in summer decreases with altitude; and (c) significant challenges remain in observing and simulating XCO(2) frontal contrasts. A linear regression analyses between ΔXCO(2) for MFLL versus GMAO, and MFLL versus WRF‐Chem for summer‐2016 cases yielded a correlation coefficient of 0.95 and 0.88, respectively. The reported ΔXCO(2) variability among four seasons provide guidance to the spatial structures of XCO(2) transport errors in models and satellite measurements of XCO(2) in synoptically‐active weather systems. |
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