An Investigation of a Subseasonal Forecast Model’s Ability to Represent Land-Atmosphere Interactions
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Benson, David O
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Abstract
A reanalysis of atmospheric and land-surface states is investigated to understand the water cycle, energy cycle and the role of the planetary boundary layer (PBL) in land-atmosphere interactions, and is used as validation for model forecast data. Subseasonal to seasonal (S2S) forecasts from an operational forecast model are examined to determine if they can replicate the relationships observed when using the reanalysis data. The ability of the S2S models to properly show relationships that indicate land-atmosphere interactions are crucial for forecasting extreme events, and understanding the conditions that allow for the intensification and persistence of these events. Daily noontime values of temperature, humidity, and surface fluxes were taken from the reanalysis dataset, as well as morning values of soil moisture over the contiguous United States. Potential evaporation and boundary layer properties are calculated and correlation analyses are carried out to determine the significance of these relationships to one another and to state variables. A similar investigation is carried out using daily averaged data from the S2S forecast model. The reanalysis reinforces previous knowledge on the role of soil moisture and the boundary layer in land-atmosphere interaction over the continental US. Correlations (or anticorrelations) among terms involved in land-atmosphere interactions are strong in the summer months (June, July, and August) with gradients from either north to south, or west to east. The western US typically show that soil moisture and evaporation plays a role in the land-atmosphere interactions. The forecast model was inconclusive, with values of surface fluxes over the western and north-central US showing the possibility of issues in the way this model behaves. Overall, further studies need to be carried out on the forecast model to determine better ways to determine these relationships, or improve on the data products from the model.
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Subseasonal to seasonal forecast, NCEP model, Extremes, Land-atmosphere interactions, Priestley-Tayloer Coefficient