Abstract
Abstract. The Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) is an open-source community model designed to address research questions that explore the role of the land surface in the global climate system. Here, we evaluate how well CLASSIC reproduces the energy, water, and carbon cycle when forced with quasi-observed meteorological data. Model skill scores summarize how well model output agrees with observation-based reference data across multiple statistical metrics. A lack of agreement may be due to deficiencies in the model, its forcing data, and/or reference data. To address uncertainties in the forcing, we evaluate an ensemble of CLASSIC runs that is based on three meteorological data sets. To account for observational uncertainty, we compute benchmark skill scores that quantify the level of agreement among independent reference data sets. The benchmark scores demonstrate what score values a model may realistically achieve given the uncertainties in the observations. Our results show that uncertainties associated with the forcing and observations are considerably large. For instance, for 10 out of 19 variables assessed in this study, the sign of the bias changes depending on what forcing and reference data are used. Benchmark scores are much lower than expected, implying large observational uncertainties. Model and benchmark score values are mostly similar, indicating that CLASSIC performs well when considering observational uncertainty. Future model development should address (i) a positive albedo bias and resulting shortwave radiation bias in parts of the Northern Hemisphere (NH) extratropics and Tibetan Plateau, (ii) an out-of-phase seasonal gross primary productivity cycle in the humid tropics of South America and Africa, (iii) a lacking spatial correlation of annual mean net ecosystem exchange with site-level measurements, (iv) an underestimation of fractional area burned and corresponding emissions in the boreal forests, (v) a negative soil organic carbon bias in high latitudes, and (vi) a time lag in seasonal leaf area index maxima in parts of the NH extratropics. Our results will serve as a baseline for guiding and monitoring future CLASSIC development.
Highlights
The land surface interacts with the atmosphere through fluxes of momentum, radiation, heat, and mass, the latter including water, trace gases, and aerosols
Assuming that global values are reasonably accurate if (i) the sign of the bias varies depending on the choice of forcing and/or reference, or (ii) the global mean bias is reasonably small (≤ 5 %), we can divide our variables into four groups
Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) shows a systematic negative SW radiation bias in the Northern Hemisphere (NH) extratropics from December to May (Fig. A4), which is consistent with a surface albedo bias as discussed further below
Summary
The land surface interacts with the atmosphere through fluxes of momentum, radiation, heat, and mass, the latter including water, trace gases, and aerosols. Land surface models (LSMs) have been developed to simulate these fluxes in global climate models. Major advancements in LSM development have occurred since including the incorporation of (i) vegetation effects on the surface energy balance (Dickinson, 1984), (ii) vegetation phenology (Sellers et al, 1996), (iii) ecological processes (Foley et al, 1996), and (iv) nutrient cycles (Goll et al, 2012). The Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC; v1.0; Melton et al, 2020) is a state-of-the-art land surface model primarily developed by Environment and Climate Change Canada. CLASSIC is the open-source community model successor to the CLASSCTEM modeling framework, which consists of the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM). CLASS and CTEM simulate physical and biogeochemical land surface processes, respectively, and together they form the land component of the Canadian Earth System Model (Swart et al, 2019)
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