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The Reduction of Systematic Temperature Biases in Soil Moisture–Limited Regimes by Stochastic Root Depth Variations

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  • 1 a Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
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Abstract

In soil moisture–limited evapotranspiration regimes, near-surface temperatures are strongly affected by the available soil water amount for evapotranspiration. Its spurious representation in climate models consequently results in an inaccurately simulated turbulent heat flux partitioning and associated temperature biases. Since the physical reasons for soil moisture–induced temperature biases are different in every region and model, a new method is presented to reduce these biases systematically. To achieve this, a stochastic root depth variation is applied, whereby the root depths in each grid box of the model domain are uniformly perturbed. Thus, the soil water supply for evapotranspiration is increased for 50% of the grid boxes in the model domain and reduced for the other 50%. In energy-limited regimes, where soil moisture just slightly affects the near-surface temperatures, the turbulent heat flux partitioning is not affected. In moisture-limited regimes, the method has an asymmetric effect on evapotranspiration. In cases of overestimated supplies, the reduced root depths in 50% of the model domain result in an overall evapotranspiration reduction. In cases of underestimated supplies, the opposite is the case. In cases of correctly simulated supplies, the evapotranspiration reduction in 50% of the model domain and the evapotranspiration increase in the other 50% balance each other on a climatological mean. In this way, the method affects the turbulent heat flux partitioning only if soil moisture is spuriously simulated in the model. The associated biases are then systematically reduced, independently of the underlying physical process, which caused the soil moisture deficiencies.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: M. Breil, marcus.breil@kit.edu

Abstract

In soil moisture–limited evapotranspiration regimes, near-surface temperatures are strongly affected by the available soil water amount for evapotranspiration. Its spurious representation in climate models consequently results in an inaccurately simulated turbulent heat flux partitioning and associated temperature biases. Since the physical reasons for soil moisture–induced temperature biases are different in every region and model, a new method is presented to reduce these biases systematically. To achieve this, a stochastic root depth variation is applied, whereby the root depths in each grid box of the model domain are uniformly perturbed. Thus, the soil water supply for evapotranspiration is increased for 50% of the grid boxes in the model domain and reduced for the other 50%. In energy-limited regimes, where soil moisture just slightly affects the near-surface temperatures, the turbulent heat flux partitioning is not affected. In moisture-limited regimes, the method has an asymmetric effect on evapotranspiration. In cases of overestimated supplies, the reduced root depths in 50% of the model domain result in an overall evapotranspiration reduction. In cases of underestimated supplies, the opposite is the case. In cases of correctly simulated supplies, the evapotranspiration reduction in 50% of the model domain and the evapotranspiration increase in the other 50% balance each other on a climatological mean. In this way, the method affects the turbulent heat flux partitioning only if soil moisture is spuriously simulated in the model. The associated biases are then systematically reduced, independently of the underlying physical process, which caused the soil moisture deficiencies.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: M. Breil, marcus.breil@kit.edu

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