Modeling the diurnal variability of respiratory fluxes in the Canadian Terrestrial Ecosystem Model (CTEM)

Abstract

The Canadian Terrestrial Ecosystem Model (CTEM) coupled to the Canadian Land Surface Scheme (CLASS) is a dynamic vegetation model that incorporates photosynthesis and respiration submodules among many other physiological processes of the terrestrial biosphere. While the photosynthesis and leaf respiration submodules of CTEM operate at a time step of 30 min, other respiratory fluxes are estimated at a daily time step using the daily-averaged values of canopy and soil temperature, and soil moisture content. Here we modify CTEM to be able to simulate the diurnal variation of ecosystem respiratory fluxes caused by the diurnal variation in the driving climate data. Simulating respiration at a 30 min time step changed the equilibrium states of primary carbon pools and fluxes. This required changes to some of the model's parameters in order to realistically simulate the equilibrium values of carbon pools and fluxes. The resulting estimated daily and annual carbon fluxes from the modified and original CTEM are similar with small relative differences. The similar annual cycles of daily values of primary CO 2 fluxes confirm that modeling the respiratory fluxes at a subdaily time step does not affect the annual cycles of these fluxes. We also demonstrate that the modified version of the model is able to simulate the diurnal cycle of net ecosystem exchange of CO 2 fluxes that are broadly comparable to observation-based estimates at two flux tower sites and exhibit realistic seasonal patterns. Limitations remain in the modeled diurnal patterns of primary landatmosphere CO 2 fluxes which will form the basis of further model improvements.

Bimodal diel pattern in peatland ecosystem respiration rebuts uniform temperature response

“…However, many process-based peatland models [32][33][34] and remote sensing proxies [35][36][37] are developed (i.e., calibrated and validated) with the support of EC-derived ER estimates. Consequently, any bias in these observational data may not only hamper our understanding of processes at (sub-)daily timescales but also directly transfer into modeling estimates of regional and global peatland C budgets 38,39 . We show that the observed bias emanates from the failed assumption of a uniform relationship between ER and temperature 17,29 for both day-and nighttime conditions.…”

Coupling the Canadian Terrestrial Ecosystem Model (CTEM v. 2.0) to Environment and Climate Change Canada's greenhouse gas forecast model (v.107-glb)

“…These deficiencies as well as the different spatial/temporal resolutions among models and observations can explain some of the differences between the datasets. Deficiencies in ERAI and CRU have been investigated in previous studies (Simmons et al, 2010;Balsamo et al, 2010;Szczypta et al, 2011). In summary, the meteorological fields from GEM are similar in quality to those from reanalyses (ERAI) and observation-based (CRU and CRU-NCEP) datasets.…”

“…It is similar in level of complexity to other TEMs (such as CASA from Potter et al, 1993 or SiB from Sellers et al, 1996) which have been used for flux inversions and which have participated in multimodel intercomparisons such as that of Huntzinger et al (2012). In recent studies (Melton and Arora, 2014;Melton et al, 2015;Melton and Arora, 2016;Badawy et al, 2016), CLASS-CTEM was calibrated based on observation-based climate data from the Climate Research Unit (CRU) (Harris et al, 2014) combined with reanalysis fields from the National Centers for Environmental Prediction (NCEP) (Kalnay et al, 1996). By coupling CLASS-CTEM with the atmospheric model, this work helps to pave the way for the coupled meteorological and ecosystem model within the EnKF (e.g., see conclusions of Miller et al, 2015).…”

“…Other terrestrial ecosystem processes, including stem, root, and heterotrophic respiration, are modeled at a daily time step. Recently, Badawy et al (2016) modified CTEM to add the capability to simulate all respiratory fluxes at the same time step as CLASS (i.e., half-hourly) in order to model their diurnal variation caused by subdiurnal signals in the driving climate data. The current version of CTEM does not include the nitrogen cycle and its interactions with the carbon cycle.…”

“…To test the sensitivity of the simulated carbon fluxes to the meteorological forcing, we performed a series of experiments with CLASS-CTEM using two different meteorological inputs from (1) CRU-NCEP (hereafter called CTEM-CRUNCEP), which has been used to drive CLASS-CTEM simulations in previous studies (Melton and Arora, 2014;Melton et al, 2015;Badawy et al, 2016) and (2) GEM-MACH-GHG (hereafter called CTEM-GEM). For the CTEM-CRUNCEP run, the model was first initialized (to represent the pre-industrial period 1861-1900) by running it to equilibrium using repeated 1901-1940 CRU-NCEP climate, a constant globally uniform CO 2 of 286.37 ppm, and a fixed vegetation fractional coverage corresponding to the year 1861 until carbon pools and fluxes were in steady state (zero mean annual net ecosystem exchange -NEE).…”