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All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Characterization of vegetation by microwave and optical remote sensing

Two series of carefully controlled experiments were conducted. First, plots of important crops (corn, soybeans, and sorghum), prairie grasses (big bluestem, switchgrass, tal fescue, orchardgrass, bromegrass), and forage legumes (alfalfa, red clover, and crown vetch) were manipulated to produce wide ranges of phytomass, leaf area index, and canopy architecture. Second, coniferous forest canopies were simulated using small balsam fir trees grown in large pots of soil and arranged systematically on a large (5 m) platform. Rotating the platform produced many new canopies for frequency and spatial averaging of the backscatter signal. In both series of experiments, backscatter of 5.0 GHz (C-Band) was measured as a function of view angle and polarization. Biophysical measurements included leaf area index, fresh and dry phytomass, water content of canopy elements, canopy height, and soil roughness and moisture content. For a subset of the above plots, additional measurements were acquired to exercise microwave backscatter models. These measurements included size and shape of leaves, stems, and fruit and the probability density function of leaf and stem angles. The relationships of the backscattering coefficients and the biophysical properties of the canopies were evaluated using statistical correlations, analysis of variance, and regression analysis. Results from the corn density and balsam fir experiments are discussed and analyses of data from the other experiments are summarized.

Daughtry, C. S. T.↗
NASA NTRS1981

Spectral-agronomic relationships of corn, soybean and wheat canopies

During the past six years several thousand reflectance spectra of corn, soybean, and wheat canopies were acquired and analyzed. The relationships of biophysical variables, including leaf area index, percent soil cover, chlorophyll and water content, to the visible and infrared reflectance of canopies are described. The effects on reflectance of cultural, environmental, and stress factors such as planting data, seeding rate, row spacing, cultivar, soil type and nitrogen fertilization are also examined. The conclusions are that several key agronomic variables including leaf area index, development stage and degree of stress are strongly related to spectral reflectance and that it should be possible to estimate these descriptions of crop condition from satellite acquired multispectral data.

Bauer, M. E.↗
NASA NTRS1998

Photosynthetic capacity and dry mass partitioning in dwarf and semi-dwarf wheat (Triticum aestivum L.)

Efficient use of space and high yields are critical for long-term food production aboard the International Space Station. The selection of a full dwarf wheat (less than 30 cm tall) with high photosynthetic and yield potential is a necessary prerequisite for growing wheat in the controlled, volume-limited environments available aboard long-term spaceflight missions. This study evaluated the photosynthetic capacity and carbon partitioning of a full-dwarf wheat cultivar, Super Dwarf, which is routinely used in spaceflight studies aboard U.S. space shuttle and NASA/Mir missions and made comparisons with other dwarf and semi-dwarf wheat cultivars utilized in other ground-based studies in plant space biology. Photosynthetic capacity of the flag leaf in two dwarf (Super Dwarf, BB-19), and three semi-dwarf (Veery-10, Yecora Rojo, IBWSN 199) wheat cultivars (Triticum aestivum L.) was assessed by measuring: net maximum photosynthetic rate, RuBP carboxylation efficiency, chlorophyll concentration and flag leaf area. Dry mass partitioning of carbohydrates to the leaves, sheaths, stems and ear was also assessed. Plants were grown under controlled environmental conditions in three replicate studies: slightly enriched CO2 (370 micromoles mol-1), high photosynthetic photon flux (1000 micromoles m-2 s-1; 58 mol m-2 d-1) for a 16 h photoperiod, 22/15 degrees C day/night temperatures, ample nutrients and water provided by one-half strength Hoagland's nutrient solution (Hoagland and Arnon, 1950). Photosynthetic capacity of the flag leaf was determined at anthesis using net CO2 exchange rate versus internal CO2 concentration curves measured under saturating light (2000 micromoles m-2 s-1) and CO2 (1000 micromoles mol-1). Dwarf wheat cultivars had greater photosynthetic capacities than the taller semi-dwarfs, they averaged 20% higher maximum net photosynthetic rates compared to the taller semi-dwarfs, but these higher rates occurred only at anthesis, had slightly greater carboxylation efficiencies and significantly increased chlorophyll concentrations per unit leaf area. The reduced-height wheat had significantly less dry mass fraction in the stem but greater dry mass partitioned to the ear than the taller semi-dwarfs (Yecora rojo, IBWSN-199). Studies with detached heads confirm that the head is a significant sink in the shorter wheat cultivars.

Non-NASA Center↗
NASA NTRS2019

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbonfluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle,we must also be able to understand and model its effects on dryland vegetation. Dynamic Global VegetationModels (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduceseasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to bothtotal productivity and competitive interactions with other plants, errors in how process-based models representphenology hinder our ability to predict climate change impacts. This may be particularly problematic in drylandecosystems where many species have developed a complex phenology in response to seasonal variability in bothmoisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure ofexisting phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) andgross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized modelparameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, wemodified the model to include a semi-deciduous phenology type and added flexibility to the representation ofgrass phenology. While optimizing parameters reduced model bias, the largest gains in model performance wereassociated with the development of our new representation of phenology. This modified model was able to bettercapture seasonal patterns of both leaf area index (R2=0.75) and gross primary productivity (R2=0.84), thoughits ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new modelalso resulted in a more realistic outcome of modeled competition between grass and shrubs. These findingsdemonstrate the importance of improving how DGVMs represent phenology in order to accurately forecastclimate change impacts in dryland ecosystems.

Ecosystem model Phenology Parameter optimization E↗
DOE OSTI2022

Decoupling of greenness and gross primary productivity as aridity decreases

Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity to evaluate how ecosystems respond to climate variability. However, to what degree inter-annual variations in productivity are consistent with greenness and how this relationship varies spatially remains unclear. Here we investigated the strength of the coupling between inter-annual variations in leaf area index (LAI, a measure of greenness) and ecosystem gross primary productivity (GPP) derived from eddy covariance towers, i.e., the r2 of the LAI-GPP relationship. Overall, inter-annual GPP and LAI were highly coupled (i.e., high r2) in arid grasslands, but were fully decoupled in mesic evergreen broadleaf forests, indicating that this relationship varies strongly along aridity gradients. A possible mechanism of the spatial variation in the LAI-GPP relationship is that the tradeoff between ecosystem structure (LAI) and physiology (photosynthesis per unit leaf area) becomes stronger in more humid climates. Land models overestimated the r2 of LAI-GPP correlation for most ecosystem types and failed to capture the spatial pattern along aridity gradients. We conclude that relying on greenness products for evaluating inter-annual changes in vegetation productivity may bias assessments, especially in tropical rainforest ecosystems. Our findings may also reconcile observed disparities between responses in greenness and GPP during drought in Amazon forests.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbon fluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle, we must also be able to understand and model its effects on dryland vegetation. Dynamic Global Vegetation Models (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduce seasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to both total productivity and competitive interactions with other plants, errors in how process-based models represent phenology hinder our ability to predict climate change impacts. This may be particularly problematic in dryland ecosystems where many species have developed a complex phenology in response to seasonal variability in both moisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure of existing phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) and gross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized model parameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, we modified the model to include a semi-deciduous phenology type and added flexibility to the representation of grass phenology. While optimizing parameters reduced model bias, the largest gains in model performance were associated with the development of our new representation of phenology. This modified model was able to better capture seasonal patterns of both leaf area index (R(exp 2) = 0.75) and gross primary productivity (R(exp 2) = 0.84), though its ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new model also resulted in a more realistic outcome of modeled competition between grass and shrubs. These findings demonstrate the importance of improving how DGVMs represent phenology in order to accurately forecast climate change impacts in dryland ecosystems.

Ecosystem model↗
NASA NTRS1984

Mechanical regulation of plant growth and development

Soybean and eggplant grown and shaken in a greenhouse exhibited decreased internode length, internode diameter, leaf area, and fresh and dry weight of roots and shoots in much the same way as outdoor-exposed plants. Perhaps more important than decreased dimensions of plant parts resulting from periodic seismic treatment is the inhibition of photosynthetic productivity that accompanies this stress. Soybeam plants briefly shaken or rubbed twice daily experienced a decrease in relative as well as absolute growth rate compared to that of undisturbed controls. Growth dynamics analysis revealed that virtually all of the decline in relative growth rate (RGR) was due to a decline in net assimilation rate (NAR), but not in leaf area ratio (LAR). Lower NAR suggests that the stress-induced decrease in dry weight gain is due to a decline in photosynthetic efficiency. Possible effects on stomatal aperture was investigated by measuring rates of whole plant transpiration as a function of seismo-stress, and a transitory decrease followed by a gradual, partial recovery was detected.

Mitchell, C. A.↗
NASA NTRS1985

Evaluation of AIS Data for Agronomic and Rangeland Vegetation: Preliminary Results for August 1984 Flight over Nebraska Sandhills Agricultural Laboratory

Since 1978 scientists from the Center for Agricultural Meteorology and Climatology at the University of Nebraska have been conducting research at the Sandhills Agricultural Laboratory on the effects of water stress on crop growth, development and yield using remote sensing techniques. We have been working to develop techniques, both remote and ground-based, to monitor water stress, phenological development, leaf area, phytomass production and grain yields of corn, soybeans and sorghum. Because of the sandy soils and relatively low rainfall at the site it is an excellent location to study water stress without the necessity of installing expensive rainout shelters. The primary objectives of research with the airborne imaging spectrometer (AIS) data collected during an August 1984 flight over the Sandhills Agricultural Laboratory are to evaluate the potential of using AIS to: (1) discriminate crop type; (2) to detect subtle architectural differences that exist among different cultivars or hybrids of agronomic crops; (3) to detect and quantify, if possible, the level of water stress imposed on the crops; and (4) to evaluate leaf area and biomass differences for different crops.

Blad, B. L.↗
NASA NTRS2000

Dependence of Photosynthetic Capacity, Photosynthetic Pigment Allocation, and Carbon Storage on Nitrogen Levels in Foliage of Aspen Stands

The role of foliar nitrogen (N) in the seasonal dynamics and vertical canopy distribution of photosynthetic pigments, photosynthetic capacity, and carbon (C) storage was investigated in boreal broadleaved species. The study was conducted at two different aged stands (60 y and 15 y) in 1994 and 1996 in Saskatchewan, Canada as part of the Boreal Ecosystem-Atmosphere Study (BOREAS). Foliage in upper and lower strata was examined for aspen (Populus tremuloides Michx.) and its associated hazelnut shrub (Corylus americana Walt.). We determined that C accumulation, expressed as dry mass per unit leaf area (mg C cm (exp -2)), was linearly dependent on N content (approximately 0.3- 3.5 mg N cm (exp -2))(r (exp 2) = 0.93, n=383, P less than 0.001) when eleven foliage groups were defined according to species, site, and developmental stage. C assembly was greatest in the upper aspen strata of both sites (seasonal average, 40.1 plus or minus 0.6 mg C cm (exp -2)), intermediate in the lower aspen strata (32.7 plus or minus 0.6), and considerably lower, and similar, in the hazelnut shrub layers (23.7 plus or minus 0.6) and in expanding aspen leaves (23.8 plus or minus 0.5); the lowest C assembly per unit N occurred in the two youngest, emerging leaf groups (17.1 plus or minus 0.6). Other relationships among physiological and biochemical variables were typically non-linear and were confounded by inclusion of the three groups of young (i.e., emerging or expanding) leaves, unless these were separately identified. Net C uptake, measured as photosynthetic capacity (A (sub max), micromole CO2 m (exp -2) s (exp -1)), was greater in aspen throughout the season, and optimal in mid-summer at a C:N ratio of approximately 18 (approximately 2.3 %N). When young leaves were excluded and logarithms of both variables were used, A (sub max) was approximately linearly dependent on N (mg N cm (exp-2) (r (exp 2) = 0.85, n= 193, P less than 0.001), attributed to incorporation of N into photosynthetic complexes and enzymes. In mature leaves, differences in pigment content vs. N among canopy strata were accentuated when N was expressed per unit leaf area (Mg cm (exp -2)) . However, the simplest log-linear relationship between a pigment variable and N was obtained for a ratio describing the relative allocation of photosynthetic pigment to Chl a (Chl a/[Chl b + carotenoids], microgram cm (exp -2)/ microgram cm-2) vs. %N (r (exp 2) = 0.90, n=343, P less than 0.001). Attainment of comparable A (sub max) Chl a content and relative Chl a allocation per unit N (mg cm (exp -2)) was achieved at different foliar N levels per canopy group: the lowest N requirement was for hazelnut leaves in the lowest, shaded stratum at the older, closed canopy site; the highest N requirement was in aspen leaves of the upper-most stratum at the younger, more open canopy site. These results highlight the differences in physiological responses between young and fully expanded leaves and show that sustaining those foliar constituents and processes important to C balance may require higher foliar N levels in leaves of establishing vs. mature aspen stands. There may be implications for remote-sensing assessments made for carbon balance in springtime, or over a landscape mosaic comprised of different aged stands.

Middleton, Elizabeth M.↗
NASA NTRS1980

Effects of management practices on reflectance of spring wheat canopies

The effects of available soil moisture, planting date, nitrogen fertilization, and cultivar on reflectance of spring wheat (Triticum aestivum L.) canopies were investigated. Spectral measurements were acquired on eight dates throughout the growing season, along with measurements of crop maturity stage, leaf area index, biomass, plant height, percent soil cover, and soil moisture. Planting date and available soil moisture were the primary agronomic factors which affected reflectance of spring wheat canopies from tillering to maturity. Comparisons of treatments indicated that during the seedling and tillering stages planting date was associated with 36 percent and 85 percent of variation in red and near infrared reflectances, respectively. As the wheat headed and matured, less of the variation in reflectance was associated with planting date and more with available soil moisture. By mid July, soil moisture accounted for 73 percent and 69 percent of the variation in reflectance in red and near infrared bands, respectively. Differences in spectral reflectance among treatments were attributed to changes in leaf area index, biomass, and percent soil cover. Cultivar and N fertilization rate were associated with very little of the variation in the reflectance of these canopies.

Daughtry, C. S. T.↗
DOE OSTI2023

Structural complexity biases vegetation greenness measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. In conclusion, our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2023

Structural Complexity Biases Vegetation Greenness Measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. Our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

Vegetation indices↗
DOE OSTI2022

LAI, EVI, NDVI, and kNDVI in 23 pantropical forests affected by 21 cyclones

Statement of purpose: Cyclones alter the function and composition of tropical forests, making effects of intensifying cyclones on carbon-rich forests a critical topic of study. Here, we quantified cyclone-induced damage and recovery of 21 cyclone disturbances affecting 23 pantropical forest sites between 1988-2017 utilizing leaf area index (LAI), enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and transformed NDVI (kNDVI) values from Google Earth Engine. Field observations collected in a meta-analysis (Bomfim et al., 2022, in review) were used to ground-truth and test effects of soil resource availability and disturbance factors on damage and recovery. This meta-analysis also served as the basis to begin vegetation index extraction, utilizing unique site and date combinations, from tropical forests effect by cyclone disturbances. We began collecting NDVI (5km resolution) from the NOAA Climate Data Record (CDR) of AVHRR Normalized Difference Vegetation Index (NDVI), Version 5 data product (Vermote, 2019) for all case studies included, 42. Next, we began extracting Landsat data from Landsat 4, 5, and 8, courtesy of the U.S. Geological Survey, in search of higher resolution data. We selected a 3 by 3 Landsat pixel area, leading to a 90m resolution data extraction. The specific imagery used includes Landsat 4 USGS Landsat 4 TM Collection 1 Tier 1 TOA (top of atmosphere) Reflectance, Landsat 5 USGS Landsat 5 TM (thematic mapper) Collection 1 Tier 1 TOA Reflectance, and Landsat 8 USGS Landsat 8 Collection 1 Tier 1 TOA Reflectance. Within Google Earth Engine, we selected the date and location (latitude and longitude), calculated NDVI, kNDVI, and EVI utilizing Landsat bands (see metadata_NGEE-tropics_cyclones), and extracted post- and pre-cyclone values for each case study to calculate cyclone-induced change in the vegetative index. Due to limited spatial resolution of Landsat remote sensing data, MODIS products were investigated next. First, the MOD13Q1.006 Terra Vegetation Indices 16-Day Global 250m product was used to extract 250m EVI and NDVI (Didan, 2015) and then the MCD15A3H.006 MODIS Leaf Area Index/FPAR 4-Day Global 500m product product was used to extract LAI 500m (Myneni et al., 2015). Pre- and post-cyclone values, change in the vegetative index, and standard deviation for all values are included in the main csv (see case_study_data.csv) for all vegetative indices collected, including LAI 500m, EVI 250m, NDVI 250m, NDVI 90m, kNDVI 90m, EVI 90m, and NDVI 5km. Lastly, recovery values were calculated utilizing a standardization method (see metadata_NGEE-tropics_cyclones) and recovery values for MODIS (see MODIS_recovery.csv) and Landsat (Landsat_recovery.csv) data are included.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Effects of root-zone acidity on utilization of nitrate and ammonium in tobacco plants

Tobacco (Nicotiana tabacum L., cv. 'Coker 319') plants were grown for 28 days in flowing nutrient culture containing either 1.0 mM NO3- or 1.0 mM NH4+ as the nitrogen source in a complete nutrient solution. Acidities of the solutions were controlled at pH 6.0 or 4.0 for each nitrogen source. Plants were sampled at intervals of 6 to 8 days for determination of dry matter and nitrogen accumulation. Specific rates of NO3- or NH4+ uptake (rate of uptake per unit root mass) were calculated from these data. Net photosynthetic rates per unit leaf area were measured on attached leaves by infrared gas analysis. When NO3- [correction of NO-] was the sole nitrogen source, root growth and nitrogen uptake rate were unaffected by pH of the solution, and photosynthetic activity of leaves and accumulation of dry matter and nitrogen in the whole plant were similar. When NH4+ was the nitrogen source, photosynthetic rate of leaves and accumulation of dry matter and nitrogen in the whole plant were not statistically different from NO3(-) -fed plants when acidity of the solution was controlled at pH 6.0. When acidity for NH4(+) -fed plants was increased to pH 4.0, however, specific rate of NH4+ uptake decreased by about 50% within the first 6 days of treatment. The effect of acidity on root function was associated with a decreased rate of accumulation of nitrogen in shoots that was accompanied by a rapid cessation of leaf development between days 6 and 13. The decline in leaf growth rate of NH4(+) -fed plants at pH 4.0 was followed by reductions in photosynthetic rate per unit leaf area. These responses of NH4(+) -fed plants to increased root-zone acidity are characteristic of the sequence of responses that occur during onset of nitrogen stress.

NASA Discipline Life Support Systems↗
NASA NTRS1984

Spectral estimators of absorbed photosynthetically active radiation in corn canopies

Most models of crop growth and yield require an estimate of canopy leaf area index (LAI) or absorption of radiation. Relationships between photosynthetically active radiation (PAR) absorbed by corn canopies and the spectral reflectance of the canopies were investigated. Reflectance factor data were acquired with a LANDSAT MSS band radiometer. From planting to silking, the three spectrally predicted vegetation indices examined were associated with more than 95% of the variability in absorbed PAR. The relationships developed between absorbed PAR and the three indices were evaluated with reflectance factor data acquired from corn canopies planted in 1979 through 1982. Seasonal cumulations of measured LAI and each of the three indices were associated with greater than 50% of the variation in final grain yields from the test years. Seasonal cumulations of daily absorbed PAR were associated with up to 73% of the variation in final grain yields. Absorbed PAR, cumulated through the growing season, is a better indicator of yield than cumulated leaf area index. Absorbed PAR may be estimated reliably from spectral reflectance data of crop canopies.

Gallo, K. P.↗
NASA NTRS1985

Spectral estimators of absorbed photosynthetically active radiation in corn canopies

Most models of crop growth and yield require an estimate of canopy leaf area index (LAI) or absorption of radiation. Relationships between photosynthetically active radiation (PAR) absorbed by corn canopies and the spectral reflectance of the canopies were investigated. Reflectance factor data were acquired with a Landsat MSS band radiometer. From planting to silking, the three spectrally predicted vegetation indices examined were associated with more than 95 percent of the variability in absorbed PAR. The relationships developed between absorbed PAR and the three indices were evaluated with reflectance factor data acquired from corn canopies planted in 1979 through 1982. Seasonal cumulations of measured LAI and each of the three indices were associated with greater than 50 percent of the variation in final grain yields from the test years. Seasonal cumulations of daily absorbed PAR were associated with up to 73 percent of the variation in final grain yields. Absorbed PAR, cumulated through the growing season, is a better indicator of yield than cumulated leaf area index. Absorbed PAR may be estimated reliably from spectral reflectance data of crop canopies.

Gallo, K. P.↗
DOE OSTI2026

NGEE Arctic Integrated Modeling (IM3): Improved snow-vegetation interaction

This data product represents the integration of new code capability for arctic tundra snow-vegetation-terrain interactions into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The NGEE Arctic project developed a total of six Integrated Modeling (IM) modules informed by observations and experiments. New ELM capability represented by this data product (IM3) falls into three categories: 1) Downscaling from gridcell to topographic unit level when working through the existing coupler bypass code. 2) Four new parameters (taper, stocking, bendresist, and vegshape) have been added to ELM to allow for flexible definition of snow-vegetation interactions. 3) Vegshape and bendresist parameters are used to calculate the fraction of leaf area and/or stem area buried by snow for a given snow depth. This data record consists of a single document (pdf format) that describes the theoretical basis for the snow-vegetation-terrain interactions added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗
DOE OSTI2026

Data and Scripts Associated with "Modeling Ecohydrological Responses of Vegetation to Urban Microclimates Using the E3SM Land Model"

This dataset supports the study of vegetation ecohydrological responses to urban microclimates using the land component of the Energy Exascale Earth System Model (ELM) at four urban sites in Knoxville, Tennessee, USA. It includes the model inputs, simulation outputs, and associated scripts for running ELM simulations and analyzing the resulting data. The Model_Inputs folder includes static surface data, satellite-derived phenology (i.e., leaf area index), and atmospheric forcing data used to drive ELM simulations. Detailed descriptions of these datasets are provided in Section 2.3.2 of the associated manuscript. The Model_Outputs folder contains simulation results for the baseline, treatment, and ensemble experiments. Outputs from the baseline and treatment simulations are provided as raw ELM NetCDF files. Because the raw outputs from the 4,000-member ensemble are prohibitively large, the ensemble results are provided as summarized CSV files, which also serve as the source data for Figure 5 of the associated manuscript. The Scripts folder contains three components: E3SM, the core codebase of the Energy Exascale Earth System Model (E3SM); elm-olmt, the Offline Land Model Testbed (OLMT) used to perform the simulations; and knoxville_elm, which contains the analysis scripts used to process model outputs and generate the figures and results presented in the associated manuscript. Additional information is provided in Scripts_readme.txt within the Scripts directory.

Lu, Xiaoman [ORNL] (ORCID:0000000306698780)↗