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Evaluation of Surface Fluxes in ERA-Interim Using Flux Tower Data

Chunlüe ZhouCollege of Global Change and Earth System Science, Beijing Normal University, and Joint Center for Global Change Studies, Beijing, China

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Kaicun WangCollege of Global Change and Earth System Science, Beijing Normal University, and Joint Center for Global Change Studies, Beijing, China

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Abstract

Surface air temperature Ta is largely determined by surface net radiation Rn and its partitioning into latent (LE) and sensible heat fluxes (H). Existing model evaluations by comparison of absolute flux values are of limited help because the evaluation results are a blending of inconsistent spatial scales, inaccurate model forcing data, and imperfect parameterizations. This study further evaluates the relationships of LE and H with Rn and environmental parameters, including Ta, relative humidity (RH), and wind speed (WS), using ERA-Interim data at a 0.125° × 0.125° grid with observations at AmeriFlux sites from 1998 to 2012. The results demonstrate ERA-Interim can roughly reproduce the absolute values of environmental parameters, radiation, and turbulent fluxes. The model performs well in simulating the correlation of LE and H with Rn, except for the notable correlation overestimation of H against Rn over high-density vegetation (e.g., deciduous broadleaf forest, grassland, and cropland). The sensitivity of LE to Rn in the model is similar to that observed, but that of H to Rn is overestimated by 24.2%. Over the high-density vegetation, the correlation coefficient between H and Ta is overestimated by over 0.2, whereas that between H and WS is underestimated by over 0.43. The sensitivity of H to Ta is overestimated by 0.72 W m−2 °C−1, whereas that of H to WS in the model is underestimated by 16.15 W m−2 (m s−1)−1 over all of the sites. The model cannot accurately capture the responses of evaporative fraction [EF; EF = LE / (LE + H)] to Rn and environmental parameters. This calls for major research efforts to improve the intrinsic parameterizations of turbulent fluxes, particularly over high-density vegetation.

Denotes Open Access content.

Corresponding author address: Kaicun Wang, College of Global Change and Earth System Science, Beijing Normal University, No. 19 Xinjiekouwai St., Beijing 100875, China. E-mail: kcwang@bnu.edu.cn

Abstract

Surface air temperature Ta is largely determined by surface net radiation Rn and its partitioning into latent (LE) and sensible heat fluxes (H). Existing model evaluations by comparison of absolute flux values are of limited help because the evaluation results are a blending of inconsistent spatial scales, inaccurate model forcing data, and imperfect parameterizations. This study further evaluates the relationships of LE and H with Rn and environmental parameters, including Ta, relative humidity (RH), and wind speed (WS), using ERA-Interim data at a 0.125° × 0.125° grid with observations at AmeriFlux sites from 1998 to 2012. The results demonstrate ERA-Interim can roughly reproduce the absolute values of environmental parameters, radiation, and turbulent fluxes. The model performs well in simulating the correlation of LE and H with Rn, except for the notable correlation overestimation of H against Rn over high-density vegetation (e.g., deciduous broadleaf forest, grassland, and cropland). The sensitivity of LE to Rn in the model is similar to that observed, but that of H to Rn is overestimated by 24.2%. Over the high-density vegetation, the correlation coefficient between H and Ta is overestimated by over 0.2, whereas that between H and WS is underestimated by over 0.43. The sensitivity of H to Ta is overestimated by 0.72 W m−2 °C−1, whereas that of H to WS in the model is underestimated by 16.15 W m−2 (m s−1)−1 over all of the sites. The model cannot accurately capture the responses of evaporative fraction [EF; EF = LE / (LE + H)] to Rn and environmental parameters. This calls for major research efforts to improve the intrinsic parameterizations of turbulent fluxes, particularly over high-density vegetation.

Denotes Open Access content.

Corresponding author address: Kaicun Wang, College of Global Change and Earth System Science, Beijing Normal University, No. 19 Xinjiekouwai St., Beijing 100875, China. E-mail: kcwang@bnu.edu.cn
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