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DOE OSTI2021

Impact of Urban Pollution on Organic-Mediated New-Particle Formation and Particle Number Concentration in the Amazon Rainforest

A major challenge in assessing the impact of aerosols on climate change is to understand how human activities change aerosol loading and properties relative to the pristine-preindustrial baseline. Here we combine chemical transport simulation and field measurements to investigate the effect of anthropogenic pollution from an isolated metropolis on particle number concentration over the preindustrial-like Amazon rainforest through various new-particle formation (NPF) mechanisms and primary particle emissions. To represent organic-mediated NPF, we employ a state-of-the-art model that systematically simulates the formation chemistry and thermodynamics of extremely low volatility organic compounds as well as their roles in NPF processes, and further update the model to improve organic NPF simulations under human-influenced conditions. Results show that urban pollution from the metropolis increases particle number concentration by a factor of 5–25 over the downwind region (within 200 km from city center) compared to background conditions. Overall, our model indicates that NPF contributes over 70% of the total particle number in the downwind region except immediately adjacent to the sources. Among different NPF mechanisms, the ternary NPF involving organics and sulfuric acid overwhelmingly dominates. The improved understanding of particle formation mechanisms will help better quantify anthropogenic aerosol forcing from pristine-preindustrial times to present day.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Modeling Volatility-Based Aerosol Phase State Predictions in the Amazon Rainforest

Organic aerosol (OA) is a complex matrix of various constituents—fresh (primary organic aerosols—POA) and aged via oxidation (secondary organic aerosols—SOA), generated from biogenic, anthropogenic, and biomass burning sources. The viscosity of OA can be critical in influencing new particle formation, reactive uptake processes that impact evaporation-growth kinetics, and the lifetime of particles in the atmosphere. We report this work utilizes a well-defined relationship between volatility and viscosity for pure compounds, which we incorporated within the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to simulate the phase state and viscosity of bulk OA during the dry-to-wet transition season (September–October) in the Amazon rainforest during 2014. Our simulations indicate spatial and temporal heterogeneity in aerosol phase state often not captured by global-scale models. We show the strong role of water associated with organic aerosol ($w_s$) as the dominant factor that can be used to quantitatively estimate OA viscosity. Analysis of WRF-Chem simulations across the entire atmospheric column indicates a strong inverse log-linear relationship between $w_s$ and OA viscosity with a correlation coefficient approaching 1, in the background and biomass burning-influenced conditions. At high altitudes where relative humidity (RH) and temperatures are low, our simulations indicate that OA exists in a semisolid-/solid-like phase state, consistent with previous studies. OA hygroscopicity is strongly correlated (ca. –0.8) with OA viscosity at RH ca. 30–50%, but this RH range is found mostly at low OA concentrations and the middle troposphere (ca. 6–10 km altitudes) in our simulated domain. OA hygroscopicity is uncorrelated with viscosity at higher-RH (near surface) and lower-RH (upper troposphere) regimes. At the urban site near surface, where day–night differences in RH are significant, RH is found to drive the phase state. At the background forested site near surface, where day–night RH differences are small, biomass burning-influenced OA is semisolid and a significant OA associated with background conditions is liquid-like. Simulations indicate a long tail of OA viscosity frequency distributions extending in the semisolid/solid regimes over background biogenic-influenced conditions due to the role of low-volatility OA components such as monoterpene oxidation products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Drought re-routes soil microbial carbon metabolism towards emission of volatile metabolites in an artificial tropical rainforest

Drought impacts on microbial activity can alter soil carbon fate and lead to the loss of stored carbon to the atmosphere as CO 2 and volatile organic compounds (VOCs). Here we examined drought impacts on carbon allocation by soil microbes in the Biosphere 2 artificial tropical rainforest by tracking 13 C from position-specific 13 C-pyruvate into CO 2 and VOCs in parallel with multi-omics. During drought, efflux of 13 C-enriched acetate, acetone and C 4 H 6 O 2 (diacetyl) increased. These changes represent increased production and buildup of intermediate metabolites driven by decreased carbon cycling efficiency. Simultaneously, 13 C-CO 2 efflux decreased, driven by a decrease in microbial activity. However, the microbial carbon allocation to energy gain relative to biosynthesis was unchanged, signifying maintained energy demand for biosynthesis of VOCs and other drought-stress-induced pathways. Overall, while carbon loss to the atmosphere via CO 2 decreased during drought, carbon loss via efflux of VOCs increased, indicating microbially induced shifts in soil carbon fate.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Climate-Mediated Changes to Linked Terrestrial and Marine Ecosystems across the Northeast Pacific Coastal Temperate Rainforest Margin

Coastal margins are important areas of materials flux that link terrestrial and marine ecosystems. Consequently, climate-mediated changes to coastal terrestrial ecosystems and hydrologic regimes have high potential to influence nearshore ocean chemistry and food web dynamics. Research from tightly coupled, high-flux coastal ecosystems can advance understanding of terrestrial–marine links and climate sensitivities more generally. In the present article, we use the northeast Pacific coastal temperate rainforest as a model system to evaluate such links. We focus on key above- and belowground production and hydrological transport processes that control the land-to-ocean flow of materials and their influence on nearshore marine ecosystems. We evaluate how these connections may be altered by global climate change and we identify knowledge gaps in our understanding of the source, transport, and fate of terrestrial materials along this coastal margin. Finally, we propose five priority research themes in this region that are relevant for understanding coastal ecosystem links more broadly.

temperate rainforest, coastal margin, climate chan↗

NASA NTRS1996

Mapping Deforestation and Land Use in Amazon Rainforest Using SAR-C Imagery

Land use changes and deforestation in tropical rainforests are among the major factors affecting the overall function of the global environment. To routinely assess the spatial extend and temporal dynamics of these changes has become an important challenge in several scientific disciplines such as climate and environmental studies. In this paper, the feasibility of using polarimetric spaceborne SAR data in mapping land cover types in the Amazon is studied.

SAR-C Imagery Amazon Rainforest Land Use Deforesta↗

DOE OSTI2023

Modeling the Impact of the Organic Aerosol Phase State on Multiphase OH Reactive Uptake Kinetics and the Resultant Heterogeneous Oxidation Timescale of Organic Aerosol in the Amazon Rainforest

Accurate predictions of chemical lifetime, i.e., oxidation timescale and change in the mass of organic aerosols (OAs) in atmospheric models, are critical to quantify the impacts of OA on aerosol–cloud interactions, radiative forcing, and air quality. The heterogeneous oxidation of OA by hydroxyl (OH) radicals is a key process governing OA mass changes during their oxidation. Recently, laboratory observations of the OH uptake coefficient (γ OH ) and heterogeneous reaction rate (k het,OH ) for different OA systems with varying phase states have been combined to develop a new parameterization of γ OH and k het,OH as a function of the OA phase state, i.e., viscosity (η OA ). Here, in this work, we use a recently published viscosity prediction framework to analyze the new γ OH and k het,OH parameterization with a box model. Subsequently, we implement this box model to predict γ OH and k het,OH over the Amazon rainforest in the dry-to-wet transition season with both significant biomass burning and biogenic influences. Relevant parameters within our box model are specified based on detailed regional model simulations over the Amazon using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). η OA is predicted as a function of species volatility, OA composition (including water uptake) along with ambient relative humidity (RH), and temperature. Based on ambient conditions simulated by WRF-Chem over the entire atmospheric column, we use the box model to predict the upper bounds of the heterogeneous oxidation timescale of OA. Based on previous laboratory measurements, we assume that this heterogeneous OH oxidation causes fragmentation (carbon loss) of OA, followed by the evaporation of the fragmented molecules that results in the exponential decay of OA. We predict that the oxidation timescale of OA is ~1 month near the Earth’s surface in the pristine Amazonian background because of low OH concentrations. But OA is oxidized more rapidly within urban and wildfire plumes near the Earth’s surface with an order of magnitude higher OH concentrations compared to the pristine background, causing the simulated oxidation timescale of OA to be much shorter, ~3–4 days. At 3–5 km altitudes where biomass burning OA is predicted to be semisolid, the heterogeneous oxidation timescale is estimated as ~6 days to 3 weeks and decreases with increasing OH concentrations within plumes. We show that the simulated mass loss of OA is strongly size-dependent, where smaller particles oxidize more rapidly compared to larger particles due to their greater per-particle surface area-to-volume ratio. Increasing urbanization and deforestation in the Amazon in the future might increase OH concentrations in the background Amazon, causing faster oxidation of OA. At higher altitudes above liquid clouds, especially in the upper troposphere where temperatures approach ~250 K, future measurements are needed to reduce the uncertainties related to the mass loss of OA at colder temperatures and low relative humidity conditions due to its heterogeneous OH oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Annual Tropical‐Rainforest Productivity Through Two Decades: Complex Responses to Climatic Factors, [CO 2 ] and Storm Damage

Abstract Yearly changes in tropical carbon‐cycling have been a major biotic determinant of the interannual variation in the rise of atmospheric carbon dioxide ([CO 2 ]). The environmental responses underlying these changes remain poorly understood. A 21‐year field study (1997–2018) in a Costa Rican rainforest has produced the first multi‐decade record of landscape‐scale annual aboveground productivity for a tropical ecosystem. While none of the four production components (wood production; leaf‐, twig‐, and reproductive litterfall) increased over two decades, all significantly varied among years. Multi‐factor environmental models explained a large fraction of the inter‐year changes in two production components. Annual changes in three climatic factors and [CO 2 ] jointly accounted for 84% of the variation in annual wood production. While the strongest response of wood production was to decline in years of slightly warmer nights, it also significantly declined in years with more dry‐season hours hotter than 28°C. The yearly changes in reproductive litterfall were largely (52%) determined by the combined effects of increasing [CO 2 ] and declining annual radiation. Twig litterfall declined over the 21 years. Annual leaf litterfall, the largest component of field‐assessed aboveground production, showed no significant environmental responses. An extreme storm in the study's final year disrupted the environmental controls on production that prevailed through the prior 20 years. While important uncertainties are introduced by some of the field methods for assessing aboveground forest production, the findings of this first long‐term field study of annual landscape‐scale productivity raise deep concerns for the future of tropical forests as global warming proceeds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Physics informed deep neural network embedded in a chemical transport model for the Amazon rainforest

Secondary organic aerosols (SOA) are fine particles in the atmosphere, which interact with clouds, radiation and affect the Earth’s energy budget. SOA formation involves chemistry in gas phase, aqueous aerosols, and clouds. Simulating these chemical processes involve solving a stiff set of differential equations, which are computationally expensive steps for three-dimensional chemical transport models. Deep neural networks (DNNs) are universal function approximators that could be used to represent the complex nonlinear changes in aerosol physical and chemical processes; however, key challenges such as generalizability to extended time periods, preservation of mass balance, simulating sparse model outputs, and maintaining physical constraints have limited their use in atmospheric chemistry. Here, we develop an approach of using a physics-informed DNN that overcomes previous such challenges and demonstrates its applicability for the chemical formation processes of isoprene epoxydiol SOA (IEPOX-SOA) over the Amazon rainforest. The DNN is trained with data generated by simulating IEPOX-SOA over the entire atmospheric column, using the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem). The trained DNN is then embedded within WRF-Chem to replace the computationally expensive default solver of IEPOX-SOA formation. The trained DNN predictions generalizes well with the default model simulation of the IEPOX-SOA mass concentrations and its size distribution (20 size bins) over several days of simulations in both dry and wet seasons. The embedded DNN reduces the computational expense of WRF-Chem by a factor of 2. Our approach shows promise in terms of application to other computationally expensive chemistry solvers in climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

The genome of Shorea leprosula (Dipterocarpaceae) highlights the ecological relevance of drought in aseasonal tropical rainforests

Hyperdiverse tropical rainforests, such as the aseasonal forests in Southeast Asia, are supported by high annual rainfall. Its canopy is dominated by the species-rich tree family of Dipterocarpaceae (Asian dipterocarps), which has both ecological (e.g., supports flora and fauna) and economical (e.g., timber production) importance. Recent ecological studies suggested that rare irregular drought events may be an environmental stress and signal for the tropical trees. We assembled the genome of a widespread but near threatened dipterocarp, Shorea leprosula, and analyzed the transcriptome sequences of ten dipterocarp species representing seven genera. Comparative genomic and molecular dating analyses suggested a whole-genome duplication close to the Cretaceous-Paleogene extinction event followed by the diversification of major dipterocarp lineages (i.e. Dipterocarpoideae). Interestingly, the retained duplicated genes were enriched for genes upregulated by no-irrigation treatment. These findings provide molecular support for the relevance of drought for tropical trees despite the lack of an annual dry season.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Saccharomycopsis praedatoria sp. nov., a predacious yeast isolated from soil and rotten wood in an Amazonian rainforest biome

Three yeast isolates were obtained from soil and rotting wood samples collected in an Amazonian rainforest biome in Brazil. Comparison of the intergenic spacer 5.8S region and the D1/D2 domains of the large subunit rRNA gene showed that the isolates represent a novel species of the genus Saccharomycopsis. A tree inferred from the D1/D2 sequences placed the novel species near a subclade containing Saccharomycopsis lassenensis, Saccharomycopsis fermentans, Saccharomycopsis javanensis, Saccharomycopsis babjevae, Saccharomycopsis schoenii and Saccharomycopsis oosterbeekiorum, but with low bootstrap support. In terms of sequence divergence, the novel species had the highest identity in the D1/D2 domains with Saccharomycopsis capsularis, from which it differed by 36 substitutions. In contrast, a phylogenomic analysis based on 1061 single-copy orthologs for a smaller set of Saccharomycopsis species whose whole genome sequences are available indicated that the novel species represented by strain UFMG-CM-Y6991 is phylogenetically closer to Saccharomycopsis fodiens and Saccharomycopsis sp. TF2021a (=Saccharomycopsis phalluae). The novel yeast is homothallic and produces asci with one spheroidal ascospore with an equatorial or subequatorial ledge. The name Saccharomycopsis praedatoria sp. nov. is proposed to accommodate the novel species. The holotype of Saccharomycopsis praedatoria is CBS 16589 T . The MycoBank number is MB849369. S. praedatoria was able to kill cells of Saccharomyces cerevisiae by means of penetration with infection pegs, a trait common to most species of Saccharomycopsis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Community‐Level Metabolic Shifts Following Land Use Change in the Amazon Rainforest Identified by a Supervised Machine Leaning Approach

ABSTRACT The Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. This change in plant cover is known to alter the soil microbiome and the functions it mediates, but the genomic changes underlying this response are still unresolved. In this study, we used a combination of deep shotgun metagenomics complemented by a supervised machine learning approach to compare the metabolic strategies of tropical soil microbial communities in pristine forests and long‐term established pastures in the Amazon. Machine learning‐derived metagenome analysis indicated that microbial community structures (bacteria, archaea and viruses) and the composition of protein‐coding genes were distinct in each plant cover type environment. Forest and pasture soils had different genomic diversities for the above three taxonomic groups, characterised by their protein‐coding genes. These differences in metagenome profiles in soils under forests and pastures suggest that metabolic strategies related to carbohydrate and energy metabolisms were altered at community level. Changes were also consistent with known modifications to the C and N cycles caused by long‐term shifts in aboveground vegetation and were also associated with several soil physicochemical properties known to change with land use, such as the C/N ratio, soil temperature and exchangeable acidity. In addition, our analysis reveals that these alterations in land use can also result in changes to the composition and diversity of the soil DNA virome. Collectively, our study indicates that soil microbial communities shift their overall metabolic strategies, driven by genomic alterations observed in pristine forests and long‐term established pastures with implications for the C and N cycles.

carbon and nitrogen cycles↗

DOE OSTI2020

Amazon rainforest photosynthesis increases in response to atmospheric dryness

Earth system models predict that increases in atmospheric and soil dryness will reduce photosynthesis in the Amazon rainforest, with large implications for the global carbon cycle. Using in situ observations, solar-induced fluorescence, and nonlinear machine learning techniques, we show that, in reality, this is not necessarily the case: In many of the wettest parts of this region, photosynthesis and biomass tend to increase with increased atmospheric dryness, despite the associated reductions in canopy conductance to CO 2 . These results can be largely explained by changes in canopy properties, specifically, new leaves flushed during the dry season have higher photosynthetic capacity than the leaves they replace, compensating for the negative stomatal response to increased dryness. As atmospheric dryness will increase with climate change, our study highlights the importance of reframing how we represent the response of ecosystem photosynthesis to atmospheric dryness in very wet regions, to accurately quantify the land carbon sink.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Rapid growth of anthropogenic organic nanoparticles greatly alters cloud life cycle in the Amazon rainforest

Aerosol-cloud interactions remain uncertain in assessing climate change. While anthropogenic activities produce copious aerosol nanoparticles smaller than 10 nanometers, they are too small to act as efficient cloud condensation nuclei (CCN). The mechanisms responsible for particle growth to CCN-relevant sizes are poorly understood. Here, we present aircraft observations of rapid growth of anthropogenic nanoparticles downwind of an isolated metropolis in the Amazon rainforest. Model analysis reveals that the sustained particle growth to CCN sizes is predominantly caused by particle-phase diffusion-limited partitioning of semivolatile oxidation products of biogenic hydrocarbons. Cloud-resolving numerical simulations show that the enhanced CCN concentrations in the urban plume substantially alter the formation of shallow convective clouds, suppress precipitation, and enhance the transition to deep convective clouds. The proposed nanoparticle growth mechanism, expressly enabled by the abundantly formed semivolatile organics, suggests an appreciable impact of anthropogenic aerosols on cloud life cycle in previously unpolluted forests of the world.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Leaf gas exchange data, Nov 2018 and May 2019, Daintree Rainforest, Australia

This data package contains leaf gas exchange data for 11 canopy tree species in the control and drought treatments at the Daintree Rainforest Observatory in Queensland, Australia (AU-DRO) with the purpose of testing for differences in gas exchange between treatments. Data were collected at the end of the dry season (November 2018) and end of the wet season (May 2019). Using a canopy crane, large branches (>1 m) were collected from the top of the canopy and immediately placed in a bucket of water, upon which the LI-6800 leaf chamber was clamped onto a recently mature leaf with minimal herbivory. Measurements were recorded every 3 seconds for 3 minutes total. The species included in the dataset are: Castanospermum australe, Cleistanthus myrianthus, Cryptocarya mackinnoniana, Dysoxylum papuanum, Elaeocarpus angustifolius (Elaeocarpus grandis), Endiandra microneura, Mallotus paniculatus, Myristica globosa, Rockinghamia angustifolia, Synima cordierorum, Syzygium spp. The two data files included are: 1. LICOR_Data_AU_DRO_2019_GasEx.csv (a compilation of individual LICOR output files, with correction of user input errors such as incorrect species spelling) 2. ESS_DIVE_Data_AU_DRO_2019_GasEx.csv (selected variables and converted units from LICOR_Data_AU_DRO_2019_GasEx.csv to follow the standard gas exchange reporting format from Ely et al. 2021 Ecological Informatics). The metadata files included are: (3) ESS_DIVE_Metadata_AU_DRO_2019_GasEx.xlsx (4) File_Submission_Metadata_AU_DRP_2019_GasEx.xlsx (5) E-Field_Log_AU_DRO_2019_GasEx.xlsx (6) Data_Column_Description_AU_DRO_2019_GasEx.xlsx.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Rapid growth of anthropogenic organic nanoparticles greatly alters cloud lifecycle in the Amazon rainforest

Atmospheric nanoparticles can significantly influence Earth’s climate if they grow to sizes large enough to nucleate cloud droplets. While the contribution of extremely low volatility vapors to nanoparticle growth has been discussed extensively, the role of semivolatile organics has been largely overlooked. Here we examine the growth and impacts of air pollution nanoparticles from an isolated metropolis amidst the Amazon rainforest. Although extremely low volatility organics are necessary for the initial growth of nanoparticles, model analysis suggests that dynamic gas-particle partitioning of semivolatile oxidation products of anthropogenic and natural hydrocarbons is predominantly responsible for the observed rapid growth to 50 nm. Furthermore, cloud-resolving simulations demonstrate that the grown particles appreciably modify shallow cloud droplet size distribution, suppress precipitation, and enhance the transition to deep clouds. With condensable semivolatile organics typically formed in greater proportion, similar nanoparticle growth and impacts on clouds could likely occur in heavily urbanized forested regions globally.

Zaveri, Rahul A↗

DOE OSTI2020

DATASET: Rapid growth of anthropogenic organic nanoparticles greatly alters cloud lifecycle in the Amazon rainforest

Zaveri, Rahul A↗

DOE OSTI2025

Weak influence of anthropogenic emissions on aerosol, cloud, and rain in the wet season of the Amazon rainforest

Anthropogenic emissions have been shown to affect new particle formation, aerosol concentrations, and clouds. Such effects vary with region, environmental conditions, and cloud types. In the wet season of Amazonia, anthropogenic emissions emitted from Manaus, Brazil, can significantly increase the cloud condensation nuclei (CCN) concentrations compared to the background of mainly natural aerosols. However, the regional response of cloud and rain to anthropogenic emissions in Amazonia remains very uncertain. Here, we aim to quantify how aerosol concentration, cloud, and rain respond to changes in anthropogenic emissions through parameterized new particle formation and primary aerosol emission in the Manaus region and to understand the underlying mechanisms. We ran the atmosphere-only configuration of the HadGEM3 climate model with a nested regional domain that covers most of the rainforest region (720 km by 1200 km with 3 km resolution) under scaled regional emissions. The 7 d simulations show that, in the areas that are affected by anthropogenic emissions, when aerosol and precursor gas emissions are doubled from the baseline emission inventories, aerosol number concentrations increase by 13 %. The nucleation rate that involves sulfuric acid and biogenic compounds generally increases with pollution levels. However, nucleation is suppressed very close to the pollution source, resulting in lower nucleation and soluble Aitken mode aerosol number concentrations. We also found that doubling the anthropogenic emission can increase the cloud droplet number concentrations ( N d ) by 9 %, but cloud water and rain mass mixing ratios do not change significantly. Even very strong reductions in aerosol number concentrations by a factor of 4, which is an unrealistic condition, cause only a 4 % increase in rain over the domain. If we assume our simulation has a fine enough grid resolution and an accurate representation of the relevant atmospheric processes, the simulated weak and non-linear response of cloud and rain properties to linearly scaled anthropogenic emissions suggests that the interactions among aerosol, cloud, and precipitation in the Amazonian convective environment are buffered by microphysical processes. It also implies that the convective environment is resilient to the changes in Nd that occur in response to localized anthropogenic aerosol perturbations.

Wang, Xuemei [University of Leeds (United Kingdom)↗

DOE OSTI2020

Modeling land surface processes over a mountainous rainforest in Costa Rica using CLM4.5 and CLM5

This study compares the performance of the Community Land Models (CLM4.5 and CLM5) against tower and ground measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4000 mm of mean annual precipitation and has high daily levels of relative humidity. The measurement tower is equipped with eddy-covariance and vertical profile systems able to measure various micrometeorological variables, particularly in wet and complex terrain. In this work, results from point-scale simulations for both CLM4.5 and its updated version (CLM5) are compared to observed canopy flux and micrometeorological data. Both models failed to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). Overall, CLM5 alleviates some errors in CLM4.5, but CLM5 still cannot precisely simulate a number of canopy processes for this forest. Soil, air, and canopy temperatures, as well as leaf wetness, remain too sensitive to incoming solar radiation rates despite updates to the model. As a result, daytime vapor flux and carbon flux are overestimated, and modeled temperature differences between day and night are higher than those observed. Slope effects appear in the measured average diurnal variations of surface albedo and carbon flux, but CLM5 cannot simulate these features. This study suggests that both CLMs still require further improvements concerning energy partitioning processes, such as leaf wetness process, photosynthesis model, and aerodynamic resistance model for wet and mountainous regions.

58 GEOSCIENCES↗