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<p>Water vapour flows in the atmosphere are fundamental to the hydrological cycle, linking evaporation sources to precipitation sinks. Recent atmospheric tracking models have provided valuable insights, allowing one to trace the sources of precipitation and determine where evaporated water from specific regions will eventually precipitate. Despite improvements in model accuracy, there remain significant discrepancies between reconstructed and observed evaporation and precipitation data from reanalysis. To address these discrepancies and enhance the reliability of tracking models’ estimates, we propose a procedure based on Iterative Proportional Fitting (IPF). Using this approach, we reconcile atmospheric moisture flows reconstructed by the Lagrangian model UTrack with ERA5 reanalysis data. This ensures that the traced atmospheric water matches the total evaporation and the precipitation annually. The reconciled bilateral connections provide a new dataset (RECON) centred on the period 2008-2017 that facilitates the exploration of atmospheric vapour flows between evaporation and precipitation basins at the global scale with a spatial resolution of 0.5°. Further, the proposed framework applies to any cell-scale dataset of atmospheric moisture tracking.</p>

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Cell-scale atmospheric moisture flows dataset reconciled with ERA5 reanalysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月15日

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  • Elena De Petrillo,
  • Luca Monaco,
  • Marta Tuninetti,
  • Arie Staal,
  • Francesco Laio

摘要

Water vapour flows in the atmosphere are fundamental to the hydrological cycle, linking evaporation sources to precipitation sinks. Recent atmospheric tracking models have provided valuable insights, allowing one to trace the sources of precipitation and determine where evaporated water from specific regions will eventually precipitate. Despite improvements in model accuracy, there remain significant discrepancies between reconstructed and observed evaporation and precipitation data from reanalysis. To address these discrepancies and enhance the reliability of tracking models’ estimates, we propose a procedure based on Iterative Proportional Fitting (IPF). Using this approach, we reconcile atmospheric moisture flows reconstructed by the Lagrangian model UTrack with ERA5 reanalysis data. This ensures that the traced atmospheric water matches the total evaporation and the precipitation annually. The reconciled bilateral connections provide a new dataset (RECON) centred on the period 2008-2017 that facilitates the exploration of atmospheric vapour flows between evaporation and precipitation basins at the global scale with a spatial resolution of 0.5°. Further, the proposed framework applies to any cell-scale dataset of atmospheric moisture tracking.