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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2018-267
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2018-267
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model evaluation paper 30 Nov 2018

Model evaluation paper | 30 Nov 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

Evaluating the Met Office Unified Model Global Atmosphere/Land 3.1 (GA/L3.1) and Global Atmosphere/Land 6.1 (GA/L6.1) land surface temperature. Outcomes of the SALSTICE campaign

Jennifer K. Brooke1, R. Chawn Harlow1, Russel L. Scott2, Martin J. Best1, John M. Edwards1, and Mark Weeks1 Jennifer K. Brooke et al.
  • 1Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
  • 2Southwest Watershed Research Center, USDA-ARS, 2000 E. Allen Road, Tucson, AZ 85719, USA

Abstract. A limitation of the Met Office operational data assimilation scheme is that surface-sensitive infrared satellite sounding channels cannot be used during daytime periods where Numerical Weather Prediction (NWP) model background land surface temperature (LST) biases are greater than 2K. The Met Office Unified Model (UM) has a significant cold LST bias in semi-arid regions when compared with satellite observations. UM LST biases were evaluated at global resolution and in a Limited Area Models (LAM) at 2.2km resolution over the SALSTICE (Semi-Arid Land Surface Temperature and IASI Calibration Experiment) experimental domain in southeastern Arizona. This validation is in conjunction with eddy-covariance flux tower measurements. LST biases in the Global Atmosphere/Land 3.1 (GA/L3.1) configuration were largest in the mid-morning with respect to Terra (−13.6±2.8K at the Kendall Grassland site). The diurnal cycle of LST in Global Atmosphere/Land 6.1 (GA/L6.1) showed a significant improvement relative to GA/L3.1. The higher resolution LAM showed added value over the global configurations.

The spatial distribution of the LST biases relative to Moderate Resolution Imaging Spectroradiometer (MODIS) and the modelled bare soil cover fraction were found to be moderately correlated (0.61±0.08) during the daytime, which suggests that regions of cold LST bias are associated with low bare soil cover fraction. Coefficients of correlation with the shrub surface fractions followed the same trend as the bare soil cover fraction although with a less significant correlation (0.36±0.09), and indicate that the sparse vegetation canopies in southeastern Arizona are not well represented in UM ancillary datasets. The x-component of the orographic slope was positively correlated with the LST bias (0.35±0.06) and identified that regions of cold model LST bias are found on easterly slopes and regions of warm model LST bias are found on westerly slopes. An overestimate in the modelled turbulent heat and moisture fluxes at the eddy-covariance flux sites was found to be coincident with an underestimate in the ground heat flux.

Jennifer K. Brooke et al.
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Jennifer K. Brooke et al.
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Short summary
This paper evaluates a significant cold land surface temperature bias in semi-arid regions in the Met Office Unified Model when compared with satellite observations. Sparse vegetation canopies are not well represented in ancillary datasets, in particular regions of cold bias are correlated with low bare soil cover fractions. The study demonstrates the difficulties in modelling land-surface temperatures that match state-of-the-art satellite retrievals required for operational data assimilation.
This paper evaluates a significant cold land surface temperature bias in semi-arid regions in...
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