Parameter interactions and sensitivity analysis for modelling carbon heat and water fluxes in a natural peatland, using CoupModel v5

Abstract

Abstract. In contrast to previous peatland carbon dioxide (CO2) model sensitivity analyses, which usually focussed on only one or a few processes, this study investigates interactions between various biotic and abiotic processes and their parameters by comparing CoupModel v5 results with multiple observation variables. Many interactions were found not only within but also between various process categories simulating plant growth, decomposition, radiation interception, soil temperature, aerodynamic resistance, transpiration, soil hydrology and snow. Each measurement variable was sensitive to up to 10 (out of 54) parameters, from up to 7 different process categories. The constrained parameter ranges varied, depending on the variable and performance index chosen as criteria, and on other calibrated parameters (equifinalities). Therefore, transferring parameter ranges between models needs to be done with caution, especially if such ranges were achieved by only considering a few processes. The identified interactions and constrained parameters will be of great interest to use for comparisons with model results and data from similar ecosystems. All of the available measurement variables (net ecosystem exchange, leaf area index, sensible and latent heat fluxes, net radiation, soil temperatures, water table depth and snow depth) improved the model constraint. If hydraulic properties or water content were measured, further parameters could be constrained, resolving several equifinalities and reducing model uncertainty. The presented results highlight the importance of considering biotic and abiotic processes together and can help modellers and experimentalists to design and calibrate models as well as to direct experimental set-ups in peatland ecosystems towards modelling needs.

Sensitivity and Uncertainty of a Long‐Term, High‐Resolution, Global, Terrestrial Sensible Heat Flux Data Set

“…When comparing the magnitude of this sensible heat total uncertainty with uncertainty reported at the local scale, we find similarities between our estimates with Metzger et al () at the local scale. Metzger et al () reports an uncertainty of approximately 3.5 W/m 2 in the sensible heat flux at a natural peatland site in Degerö Stormyr, Sweden, and our sensible heat flux total uncertainty at the pixel over the same location is 5.8 W/m 2 . The difference of 2.3 W/m 2 could result from the discrepancies in the scale of the pixel to the local scale site of Metzger et al ().…”

“…When comparing the magnitude of this sensible heat total uncertainty with uncertainty reported at the local scale, we find similarities between our estimates with Metzger et al (2016) Of all the primary inputs, the largest fraction of the total uncertainty seen in Figure 3 is attributed to the uncertainty in the temperature gradient in most regions. The temperature gradient's dominant impact, relative to other inputs, is consistent with its expected influence as the dominant input in the denominator for sensible heat flux (see equation (7)).…”

“…at the local scale Metzger et al (2016). reports an uncertainty of approximately 3.5 W/m 2 in the sensible heat flux at a natural peatland site in Degerö Stormyr, Sweden, and our sensible heat flux total uncertainty at the pixel over the same location is 5.8 W/m 2 .…”

“…Although the strategies to compute sensitivity and uncertainty in energy fluxes, such as sensible heat flux, differ among studies, many of the studies mentioned above have narrow domains of the local tower or in situ station scale (e.g., Alton et al, ; Cammalleri et al, ; Chehbouni et al, ; Marx et al, ; Sanchez et al, ), catchment scale (e.g., Metzger et al, ; Long et al, ; Wang et al, ), or the regional scale (e.g., (Boisier et al, ; Bounoua et al, ; Hou et al, ; Timmermans et al, ), with only Jung et al () at the global scale. Additionally, several of these studies evaluate a lengthy list of parameters, but the most commonly examined parameters and input data sets for sensible heat flux estimates examined are temperatures (e.g., (Alton et al, ; Chehbouni et al, ; Cammalleri et al, ; Long et al, ; Marx et al, ; Sanchez et al, ; Timmermans et al, ; Xu et al, ; Zhan et al, ), including the temperature gradient between the LST and the air temperature (e.g., Gibson et al, ), wind speed (e.g., (Alton et al, ; Long et al, ; Marx et al, ; Sanchez et al, ; Timmermans et al, ; Zhan et al, ), and the aerodynamic properties of the vegetation such as the roughness length for momentum (e.g., Long et al, ; Marx et al, ; Sanchez et al, ; Timmermans et al, ; Xu et al, ; Zhan et al, ), leaf area index (e.g., Alton et al, ; Sanchez et al, ; Timmermans et al, ; Zhan et al, ), a vegetation index such as normalized difference vegetation index (e.g., Timmermans et al, ; Zhan et al, ) or the enhanced vegetation index (e.g., Xu et al, ), or displacement height and fractional vegetation cover (e.g., Tang et al, ; Tang & Li, ).…”

“…reports an uncertainty of approximately 3.5 W/m 2 in the sensible heat flux at a natural peatland site in Degerö Stormyr, Sweden, and our sensible heat flux total uncertainty at the pixel over the same location is 5.8 W/m 2 . The difference of 2.3 W/m 2 could result from the discrepancies in the scale of the pixel to the local scale site ofMetzger et al (2016).…”