Haughton Ned, Abramowitz Gab, Pitman Andy J, Or Dani, Best Martin J, Johnson Helen R, Balsamo Gianpaolo, Boone Aaron, Cuntz Matthias, Decharme Bertrand, Dirmeyer Paul A, Dong Jairui, Ek Michael, Guo Zichang, Haverd Vanessa, van den Hurk Bart J J, Nearing Grey S, Pak Bernard, Santanello Joe A, Stevens Lauren E, Vuichard Nicolas
ARC Centre of Excellence for Climate Systems Science, Australia.
Department of Environmental Systems Science, Swiss Federal Institute of Technology - ETH Zurich, Switzerland.
J Hydrometeorol. 2016 Jun;17(6):1705-1723. doi: 10.1175/JHM-D-15-0171.1. Epub 2016 May 25.
The PALS Land sUrface Model Benchmarking Evaluation pRoject (PLUMBER) illustrated the value of prescribing performance targets in model intercomparisons. It showed that the performance of turbulent energy flux predictions from different land surface models, at a broad range of flux tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all land surface models were outperformed by a linear regression against downward shortwave radiation. For latent heat flux, all land surface models were outperformed by a regression against downward shortwave, surface air temperature and relative humidity. These results are explored here in greater detail and possible causes are investigated. We examine whether particular metrics or sites unduly influence the collated results, whether results change according to time-scale aggregation and whether a lack of energy conservation in flux tower data gives the empirical models an unfair advantage in the intercomparison. We demonstrate that energy conservation in the observational data is not responsible for these results. We also show that the partitioning between sensible and latent heat fluxes in LSMs, rather than the calculation of available energy, is the cause of the original findings. Finally, we present evidence suggesting that the nature of this partitioning problem is likely shared among all contributing LSMs. While we do not find a single candidate explanation for why land surface models perform poorly relative to empirical benchmarks in PLUMBER, we do exclude multiple possible explanations and provide guidance on where future research should focus.
极地和高山陆地表面模型基准评估项目（PLUMBER）说明了在模型相互比较中设定性能目标的价值。它表明，在广泛的通量塔站点使用通用评估指标时，不同陆地表面模型的湍流通量预测性能平均而言比相对简单的经验模型更差。对于感热通量，所有陆地表面模型都不如基于向下短波辐射的线性回归模型。对于潜热通量，所有陆地表面模型都不如基于向下短波辐射、地表气温和相对湿度的回归模型。本文将更详细地探讨这些结果，并研究可能的原因。我们研究特定指标或站点是否对整理后的结果产生不当影响，结果是否会根据时间尺度聚合而变化，以及通量塔数据中缺乏能量守恒是否会使经验模型在相互比较中获得不公平优势。我们证明观测数据中的能量守恒并非这些结果的原因。我们还表明，陆地表面模型中感热通量和潜热通量的分配，而非可用能量的计算，是最初研究结果的原因。最后，我们提供证据表明，这种分配问题的本质可能在所有参与的陆地表面模型中都存在。虽然我们没有找到一个单一的候选解释来说明为什么陆地表面模型在PLUMBER中相对于经验基准表现不佳，但我们确实排除了多种可能的解释，并为未来研究应关注的方向提供了指导。
