Land use and land cover change (LULCC) represents a key process of human-Earth system interaction and has profound impacts on ecosystem carbon cycling. As a key input for ecosystem models, future gridded LULCC data is typically spatially downscaled from regionally LULCC projections by integrated assessment models. The uncertainty associated with different spatial downscaling methods and its impacts on subsequent model projections have been historically ignored and rarely examined. This study investigated this problem using two representative spatial downscaling methods and focused on the impacts on the carbon cycle over ABoVE domain. Specifically, we used the Future Land Use Simulation model (FLUS) and Demeter model to generate 0.25-degree gridded LULCC data with the same input of regional LULCC projections from Global Change Analysis Model, under SSP126 and SSP585. The two sets of downscaled LULCC were used to drive CLM5 to prognostically simulate terrestrial carbon cycle dynamics over the 21st century. The results suggest large spatial-temporal differences between two LULCC datasets under both SSP126 and SSP585. The LULCC differences further lead to large discrepancies in the spatial patterns of projected carbon cycle variables, which are more than 79% of the contributions of LULCC in 2100. Besides, the difference for LULCC and carbon flux under SSP126 is generally larger than those under SSP585. This study highlights the importance of considering the uncertainties induced by spatial downscaling process in future LULCC projections and carbon cycle simulations.

Radiation-topography interaction plays an important role in the surface energy balance over the Tibetan Plateau (TP). However, the impacts of such interaction over the TP on climate locally and in the Asian regions remain unclear. This study uses the Energy Exascale Earth System Model (E3SM) to evaluate the regional and teleconnected impacts of radiation-topography interaction over the TP. Land-atmosphere coupled experiments show that topography regulates the surface energy balance, snow processes, and surface climate over the TP across seasons. Accounting for radiation-topography interaction overall improves E3SM’s performance in simulating surface climate. The winter cold bias in air temperature decreases from -4.48 K to -3.70 K, and the wet bias in summer precipitation is mitigated in southern TP. The TP’s radiation-topography interaction further reduces the South and East Asian summer precipitation biases. Our results demonstrate the topographic roles in regional climate over the TP and highlight its teleconnected climate impacts.

Anthropogenic land use and land cover change (LULCC), is projected to continue in the future. However, the influence of forest management on forest productivity change and subsequent LULCC projections remain under-investigated. This study explored the impacts of forest management-induced change in forest productivity on LULCC throughout the 21st century. Specifically, we developed a framework to softly couple the Global Change Analysis Model and Global Timber Model to consider forest management-induced forest productivity change, and projected future LULCC across the five Shared Socioeconomic Pathways (SSPs). We found future increases in forest management intensity overall drive the increase of forest productivity. The forest management-induced forest productivity change shows diverse responses across all SSPs, with a global increase from 2015 to 2100 ranging from 3.9% (SSP3) to 8.8% (SSP1). This further leads to an overall decrease in the total area with change of land use types, with the largest decrease under SSP1 (-7.5%) and smallest decrease under SSP3 (-0.7%) in 2100. Among land use types, considering forest management-induced change significantly reduces the expansion of managed forest, and also reduces the loss in natural land in 2100 across SSPs. This suggests that ignoring forest management-induced forest productivity change underestimates the efficiency of wood production, overestimates the managed forest expansion required to meet the future demand, and consequently, potentially introduces uncertainties into relevant analyses, e.g., carbon cycle and biodiversity. Thus, we advocate to better account for the impacts of forest management in future LULCC projections.

Wildfire frequency, intensity, and severity are increasing across the Western U.S. Significant tree mortality can occur years after fire events, but this has received little attention compared to the immediate tree loss during a fire. We overlapped forest cover loss data with burn severity maps in the U.S. Pacific Northwest and quantified the total and delayed forest canopy loss after fires. We found that wildfires resulted in total canopy losses of 89%, 67%, and 31% within three years in areas burned at high, moderate, and low severity, respectively. The delayed canopy loss accounted for approximately 1/3, 1/2, and 2/3 of the total canopy loss for high, moderate, and low severity burns. Delayed canopy loss was greater in moist and cool areas than in dry and warm areas, possibly because tree species in the wetter areas are less adapted to tolerate fires with traits such as bark thickness and crown height. Across all forests, delayed canopy loss was greater in dry and warm years. These results suggest greater canopy losses will occur as wildfires expand into areas that historically experienced infrequent fires.

Sub-grid topographic heterogeneity has large impacts on surface energy balance and land-atmosphere interactions. However, the impacts of representing sub-grid topographic effects in land surface models (LSMs) on surface energy balance and boundary conditions remain unclear. This study analyzed and evaluated the impacts of sub-grid topographic representations on surface energy balance, turbulent heat flux and scalar (co-)variances in the Energy Exascale Earth System Model (E3SM) land model (ELM). Three sub-grid topographic representations in ELM were compared: (1) the default sub-grid structure (D), (2) the recently developed sub-grid topographic structure (T), and (3) high spatial resolution (1KM). Additionally, two different solar radiation schemes in ELM were compared: (1) the default plane-parallel radiative transfer scheme (PP) and (2) the parameterization scheme (TOP) that accounts for sub-grid topographic effects on solar radiation. A series of simulations with the three grid structures (D, T and 1KM) and two treatments of solar radiation (TOP and PP) were carried out in the Sierra Nevada, California. There are significant differences between TOP and PP in the 1-km simulated surface energy balance, but the differences in the mean values and standard deviations become small when aggregated to the grid-scale (i.e., 0.5°). The T configuration better mimics the 1KM simulations than the D configuration, and better captures the sub-grid topographic effects on surface energy balance as well as surface boundary conditions. These results underline the importance of representing sub-grid topographic heterogeneities in LSMs and motivate future research to understand the sub-grid topographic effects on land-atmosphere interactions over mountain areas.