The vertical structure of vegetation canopies creates micro-climates, which can substantially affect ecosystem responses to climate change. However, the land components of most Earth System Models, including the Energy Exascale Earth System Model (E3SM), typically neglect vertical canopy structure by using a single layer big-leaf representation to simulate water, \cotwo, and energy exchanges between the land and the atmosphere. In this study, we developed a standalone Multi-Layer Canopy Model (MLCMv1) for the E3SM Land Model (ELM) to resolve the micro-climate created by vegetation canopies. The support for the heterogeneous computation architectures is included by using the Portable Extensible Toolkit for Scientific Programming. The numerical implementation of ELM-MLCMv1 was verified against CLM-ml\_v1 for a month-long simulation using data from the Ameriflux US-University of Michigan Biological Station (US-UMB) site. Model structural uncertainty was explored by performing control simulations for five stomatal conductance models (SCMs). All SCMs after calibration were able to accurately match observations of sensible and latent heat flux, though the bias of the three SCMs with plant hydrodynamics (PHD) was slightly lower than that of two SCMs without PHD. Additionally, six idealized simulations were performed to study the impact of environmental variables on canopy processes. All SCMs agreed on the direction of simulated changes in canopy processes due to the changes in these environmental variables. ELM-MLCMv1 achieves a speedup of 25-50 times when comparing performance on a GPU relative to a CPU. This study provides the first necessary model development for including the representation of vertical canopies within ELM.

The long-term net sink of carbon (C), nitrogen (N) and greenhouse gases (GHGs) in the northern permafrost region is projected to weaken or shift under climate change. But large uncertainties remain, even on present-day GHG budgets. We compare bottom-up (data-driven upscaling, process-based models) and top-down budgets (atmospheric inversion models) of the main GHGs (CO2, CH4, and N2O) and lateral fluxes of C and N across the region over 2000-2020. Bottom-up approaches estimate higher land to atmosphere fluxes for all GHGs compared to top-down atmospheric inversions. Both bottom-up and top-down approaches respectively show a net sink of CO2 in natural ecosystems (-31 (-667, 559) and -587 (-862, -312), respectively) but sources of CH4 (38 (23, 53) and 15 (11, 18) Tg CH4-C yr-1) and N2O (0.6 (0.03, 1.2) and 0.09 (-0.19, 0.37) Tg N2O-N yr-1) in natural ecosystems. Assuming equal weight to bottom-up and top-down budgets and including anthropogenic emissions, the combined GHG budget is a source of 147 (-492, 759) Tg CO2-Ceq yr-1 (GWP100). A net CO2 sink in boreal forests and wetlands is offset by CO2 emissions from inland waters and CH4 emissions from wetlands and inland waters, with a smaller additional warming from N2O emissions. Priorities for future research include representation of inland waters in process-based models and compilation of process-model ensembles for CH4 and N2O. Discrepancies between bottom-up and top-down methods call for analyses of how prior flux ensembles impact inversion budgets, more in-situ flux observations and improved resolution in upscaling.

To improve the predictive capability of ecosystem biogeochemical models (EBMs), we discuss the feasibility of formulating biogeochemical processes using physical rules that have underpinned the many successes in computational physics and chemistry. We argue that the currently popular empirically based modeling approaches, such as multiplicative empirical response functions and the law of the minimum, will not lead to EBM formulations that can be continuously refined to incorporate improved mechanistic understanding and empirical observations of biogeochemical processes. As an alternative to these empirical models, we propose to formulate EBMs using established physical rules widely used in computational physics and chemistry. Through several examples, we demonstrate how mathematical representations derived from physical rules can improve understanding of relevant biogeochemical processes and enable more effective communication between modelers, observationalists, and experimentalists regarding essential questions, such as what measurements are needed to meaningfully inform models and how can models generate new process-level hypotheses to test in empirical studies?

We present a representation of nitrogen and phosphorus cycling in the vegetation demography model the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), within the Energy Exascale Earth System (E3SM) land model. This representation is modular, and designed to allow testing of multiple hypothetical approaches for carbon-nutrient coupling in plants. The model tracks nutrient uptake, losses via turnover from both live plants and mortality into soil decomposition, and allocation during tissue growth for a large number of size- and functional-type-resolved plant cohorts within a time-since-disturbance-resolved ecosystem. Root uptake is governed by fine root biomass, and plants vary in their fine root carbon allocation in order to balance carbon and nutrient limitations to growth. We test the sensitivity of the model to a wide range of parameter variations and structural representations, and in the context of observations at Barro Colorado Island, Panama. A key model prediction is that plants in the high-light-availability canopy positions allocate more carbon to fine roots than plants in low-light understory environments, given the widely different carbon versus nutrient constraints of these two niches within a given ecosystem. This model provides a basis for exploring carbon-nutrient coupling with vegetation demography within Earth System Models (ESMs).

Process-based land surface models are important tools for estimating global wetland methane (CH4) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH4 fluxes (FCH4) at different time scales. A Monte Carlo approach has been developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that 1) significant model-observation disagreements are mainly at short- to intermediate time scales (< 15 days); 2) most of the models can capture the CH4 variability at long time scales (> 32 days) for the boreal and Arctic tundra wetland sites but have limited performance for temperate and tropical/subtropical sites; 3) model error approximates pink noise patterns, indicating that biases at short time scales (< 5 days) could contribute to persistent systematic biases on longer time scales; and 4) differences in error pattern are related to model structure (e.g. proxy of CH4 production). Our evaluation suggests the need to accurately replicate FCH4 variability in future wetland CH4 model developments.

In studying problems like plant-soil-microbe interactions in environmental biogeochemistry and ecology, one usually has to quantify and model how substrates control the growth of, and interaction among, biological organisms. To address these substrate-consumer relationships, many substrate kinetics and growth rules have been developed, including the famous Monod kinetics for single substrate-based growth, Liebig’s law of the minimum for multiple-nutrient co-limited growth, etc. However, the mechanistic basis that leads to these various concepts and mathematical formulations and the implications of their parameters are often quite uncertain. Here we show that an analogy based on Ohm’s law in electric circuit theory is able to unify many of these different concepts and mathematical formulations. In this Ohm’s law analogy, a resistor is defined by a combination of consumers’ and substrates’kinetic traits. In particular, the resistance is equal to the mean first passage time that has been used by renewal theory to derive the Michaelis-Menten kinetics under substrate replete conditions for a single substrate as well as the predation rate of individual organisms. We further show that this analogy leads to important insights on various biogeochemical problems, such as (1) multiple-nutrient co-limited biological growth, (2) denitrification, (3) fermentation under aerobic conditions, (4) metabolic temperature sensitivity, and (5) the accuracy of Monod kinetics for describing bacterial growth. We expect our approach will help both modelers and non-modelers to better understand and formulate hypotheses when studying certain aspects of environmental biogeochemistry and ecology.

The relationships and seasonal-to-annual variations among evapotranspiration (ET), precipitation (P), and groundwater dynamics (total water storage anomaly, TWSA) are complex across the Amazon basin, especially the water and energy limitation mechanism for ET. To analyze how ET is controlled by P and TWSA, we used wavelet coherence analysis to investigate the effects of P and TWSA on ET at sub-basin, kilometer, regional, and whole basin scales in the Amazon basin. The Amazon-scale averaged ET has strong correlations with P and TWSA at the annual periodicity. The phase lag between ET and P (ϕ_(ET-P)) is ~1 to ~4 months, and between ET and TWSA (ϕ_(ET-TWSA)) is ~3 to ~7 months. The phase pattern has a south-north divide due to the significant variation in climatic conditions. The correlation between ϕ_(ET-P) and ϕ_(ET-TWSA) is affected by the aridity index, of each sub-basin, as determined using the Budyko framework at the sub-basin level. In the southeast Amazon during a drought year (e.g., 2010), both phases decreased, while in the subsequent years, ϕ_(ET-TWSA) increased. The area of places where ET is limited by water continues to decrease over time in the southern Amazon basin. These results suggest immediate strong groundwater subsidy to ET in the following dry years in the water-limited area of Amazon. The water storage has more control on ET in the southeast but little influence in the north and southwest after a drought. The areas of ET limited by energy or water are switched due to the variability in weather conditions.

The Middle and Lower Reaches of the Yangtze River (MLRYR) region, which has humid subtropical climate conditions and unique plum rain season, is characterized by a simultaneous high-frequency urban flooding and reduction in groundwater levels. Retrofitting the existing buildings into green roofs is a promising approach to combat urban flooding, especially for a densely developed city. Here, the application potential of the Green Roof System (GRS) and the Improved Green Roof System (IGRS) that designed to divert overflowing water from green roofs to recharge groundwater were analyzed in such a densely developed city, Nanchang, China. The performances of the GRS and the IGRS were evaluated using the United States Environmental Protection Agency (USEPA) Storm Water Management Model (SWMM). The simulation results show that in single precipitation events about 41-75% of precipitation could be retained in the GRS depending on precipitation intensity. In 10- and 100-yr precipitation events, the flooding volumes in the GRS region are 82% and 28% less than those of Traditional Roof System (TRS), respectively. For the first time, the influence of GRS on the hydraulic condition of CSS / SWS (Combined Sewage System / Storm Water System) is analyzed, which is a direct reflection of the effect of GRS on alleviating urban flooding. Recognizing the limitation of SWMM, five methods have been used to comprehensively analyze the evapotranspiration process of GRS. The evapotranspiration of the GRS retained water could account for 39% of annual precipitation. Although the IGRS could lead to a higher immediate flood loading (about 20-27%) than the GRS, it could divert more precipitation (more than 10% of the annual precipitation) into the greenbelts, thus significantly increase groundwater recharge. We may conclude that the widespread implementation of both the GRS and the IGRS in Nanchang and other densely developed cities in the MLRYR region could significantly reduce surface and peak runoff rates. In particular, the IGRS can provide more hydrological benefits than the GRS under the same climate conditions.