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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Environmental drivers of spatial variation in tropical forest canopy height: Insights from NASA’s GEDI spaceborne LiDAR

Forest canopy height is a fundamental ecosystem property—influencing patterns of forest carbon storage and forest ecosystem responses to climate variability and change. Previous studies have analyzed environmental drivers influencing spatial variation in canopy height at landscape-to-regional scales; however, far less is known about the environmental determinants underlying regional and global scale variation in forest canopy height. Using the canopy height metrics products from Global Ecosystem Dynamics Investigation (GEDI), a space-borne Light Detection and Ranging (LiDAR) instrument specifically designed to characterize forest structure, we analyze the environmental correlates of spatial variation of global tropical forest canopy height. Our study demonstrates that climate, topography, and soil properties account for 75% of the variation in tropical forest canopy height. Elevation, dry season length, and solar radiation are the most important drivers in determining canopy height both locally and regionally. These results emphasize the vulnerability of tropical forest structure to ongoing changes in the earth’s climate and provide a valuable empirical baseline for tropical forest management.

Science & Technology - Other Topics↗
DOE OSTI2022

Microbiome assembly in thawing permafrost and its feedbacks to climate

Abstract The physical and chemical changes that accompany permafrost thaw directly influence the microbial communities that mediate the decomposition of formerly frozen organic matter, leading to uncertainty in permafrost–climate feedbacks. Although changes to microbial metabolism and community structure are documented following thaw, the generality of post‐thaw assembly patterns across permafrost soils of the world remains uncertain, limiting our ability to predict biogeochemistry and microbial community responses to climate change. Based on our review of the Arctic microbiome, permafrost microbiology, and community ecology, we propose that Assembly Theory provides a framework to better understand thaw‐mediated microbiome changes and the implications for community function and climate feedbacks. This framework posits that the prevalence of deterministic or stochastic processes indicates whether the community is well‐suited to thrive in changing environmental conditions. We predict that on a short timescale and following high‐disturbance thaw (e.g., thermokarst), stochasticity dominates post‐thaw microbiome assembly, suggesting that functional predictions will be aided by detailed information about the microbiome. At a longer timescale and lower‐intensity disturbance (e.g., active layer deepening), deterministic processes likely dominate, making environmental parameters sufficient for predicting function. We propose that the contribution of stochastic and deterministic processes to post‐thaw microbiome assembly depends on the characteristics of the thaw disturbance, as well as characteristics of the microbial community, such as the ecological and phylogenetic breadth of functional guilds, their functional redundancy, and biotic interactions. These propagate across space and time, potentially providing a means for predicting the microbial forcing of greenhouse gas feedbacks to global climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data Readiness for Scientific AI at Scale

This paper examines how Data Readiness for AI (DRAI) principles apply to leadership-scale scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, bio/health, and materials—to identify common preprocessing patterns and domain-specific constraints. We introduce a two-dimensional readiness framework that combines canonical preprocessing patterns with a five-level operational readiness scale, both tailored to high-performance computing (HPC) environments. This framework helps outline key challenges in transforming large-scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross-domain support for scalable and reproducible AI for science.

Brewer, Wes [ORNL] (ORCID:0000000236393956)↗
DOE OSTI2024

Potential long-term, global effects of enhancing the domestic terrestrial carbon sink in the United States through no-till and cover cropping

Abstract Background Achieving a net zero greenhouse gas United States (US) economy is likely to require both deep sectoral mitigation and additional carbon dioxide removals to offset hard-to-abate emissions. Enhancing the terrestrial carbon sink, through practices such as the adoption of no-till and cover cropping agricultural management, could provide a portion of these required offsets. Changing domestic agricultural practices to optimize carbon content, however, might reduce or shift US agricultural commodity outputs and exports, with potential implications on respective global markets and land use patterns. Here, we use an integrated energy-economy-land-climate model to comprehensively assess the global land, trade, and emissions impacts of an adoption of domestic no-till farming and cover cropping practices based on carbon pricing. Results We find that the adoption of these practices varies depending on which aspects of terrestrial carbon are valued. Valuation of all terrestrial carbon resulted in afforestation at the expense of domestic agricultural production. In contrast, a policy valuing soil carbon in agricultural systems specifically indicates strong adoption of no-till and cover cropping for key crops. Conclusions We conclude that under targeted terrestrial carbon incentives, adoption of no-till and cover cropping practices in the US could increase the terrestrial carbon sink with limited effects on crop availability for food and fodder markets. Future work should consider integrated assessment modeling of non-CO 2 greenhouse gas impacts, above ground carbon storage changes, and capital and operating cost considerations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Changes in the Intensity and Frequency of Atmospheric Blocking and Associated Heat Waves During Northern Summer Over Eurasia in the CMIP5 Model Simulations

The Russia heat wave and wild fires of the summer of 2010 was the most extreme weather event in the history of the country. Studies show that the root cause of the 2010 Russia heat wave/wild fires was an atmospheric blocking event which started to develop at the end of June and peaked around late July and early August. Atmospheric blocking in the summer of 2010 was anomalous in terms of the size, duration, and the location, which shifted to the east from the normal location. This and other similar continental scale severe summertime heat waves and blocking events in recent years have raised the question of whether such events are occurring more frequently and with higher intensity in a warmer climate induced by greenhouse gases. We studied the spatial and temporal distributions of the occurrence and intensity of atmospheric blocking and associated heat waves for northern summer over Eurasia based on CMIPS model simulations. To examine the global warming induced change of atmospheric blocking and heat waves, experiments for a high emissions scenario (RCP8.S) and a medium mitigation scenario (RCP4.S) are compared to the 20th century simulations (historical). Most models simulate the mean distributions of blockings reasonably well, including major blocking centers over Eurasia, northern Pacific, and northern Atlantic. However, the models tend to underestimate the number of blockings compared to MERRA and NCEPIDOE reanalysis, especially in western Siberia. Models also reproduced associated heat waves in terms of the shifting in the probability distribution function of near surface temperature. Seven out of eight models used in this study show that the frequency of atmospheric blocking over the Europe will likely decrease in a warmer climate, but slightly increase over the western Siberia. This spatial pattern resembles the blocking in the summer of 2010, indicating the possibility of more frequent occurrences of heat waves in western Siberia. In this talk, we will also discuss the potential effect of atmosphere-land feedback, particularly how the wetter spring affects the frequency and intensity of atmospheric blocking and heat wave during summer.

Kim, Kyu-Myong↗
NASA NTRS2022

A Synopsis of AIRS Global-Mean Clear-Sky Radiance Trends From 2003 to 2020

Atmospheric Infrared Sounder (AIRS) aboard the National Aeronautics and Space Administration (NASA) Aqua satellite has been operating since September 2002. Its information content, superb instrument performance, and dense sampling pattern make the AIRS radiances an invaluable data set for climate studies. The trends of global-mean, nadir-view, clear-sky AIRS radiances from 2003 to 2020 are studied here, together with the counterparts of synthetic radiances based on two reanalyzes, European Centre for Medium-Range Weather Forecasts Reanalysis V5 (ECMWF ERA5) and NASA Goddard Earth Observing System V5.4.1 (GEOS-5.4.1; a reanalysis product without assimilation of hyperspectral radiances such as AIRS). The AIRS observation shows statistically significant negative trends in most of its CO2 channels, positive but non-significant trends in the channels over the window regions, and statistically significant positive trends in some of its H2O channels. The best agreements between observed and simulated radiance trends are seen over the CO2 tropospheric channels, while the observed and simulated trends over the CO2 stratospheric channels are opposite. ERA5 results largely agree with the AIRS observation over the H2O channels. The comparison in the H2O channels helps reveal a data continuity issue in the GEOS-5.4.1. Contributions from individual variables to the radiance trends are also assessed by performing separate simulations. This study provides the first synopsis of the global-mean trend of AIRS radiances over all its thermal-IR channels.

CO2↗
NASA NTRS2012

The Role of Forcing and Internal Dynamics in explaining the 'Medieval Climate Anomaly'

Proxy reconstructions suggest that peak global temperature during the past warm interval known as the Medieval Climate Anomaly (MCA, roughly 950-1250 AD) has been exceeded only during the most recent decades. To better understand the origin of this warm period, we use model simulations constrained by data assimilation establishing the spatial pattern of temperature changes that is most consistent with forcing estimates, model physics and the empirical information contained in paleoclimate proxy records. These numerical experiments demonstrate that the reconstructed spatial temperature pattern of the MCA can be explained by a simple thermodynamical response of the climate system to relatively weak changes in radiative forcing combined with a modification of the atmospheric circulation, displaying some similarities with the positive phase of the so-called Arctic Oscillation, and with northward shifts in the position of the Gulf Stream and Kuroshio currents. The mechanisms underlying the MCA are thus quite different from anthropogenic mechanisms responsible for modern global warming.

Goossee, Hugues↗
DOE OSTI2021

Evolving CO 2 rather than SST leads to a factor of ten decrease in GCM convergence time

The high computational cost of Global Climate Models (GCMs) is a problem that limits their use in many areas. Recently an inverse climate modeling (InvCM) method, which fixes the global mean sea surface temperature (SST) and evolves the CO 2 mixing ratio to equilibrate climate, has been implemented in a cloud resolving model. In this paper, we apply InvCM to ExoCAM GCM aquaplanet simulations, allowing the SST pattern to evolve while maintaining a fixed global-mean SST. We find that InvCM produces the same climate as normal slab-ocean simulations but converges an order of magnitude faster. We then use InvCM to calculate the equilibrium CO 2 for SSTs ranging from 290 K to 340 K at 1 K intervals and reproduce the large increase in climate sensitivity at an SST of about 315 K at much higher temperature resolution. The speedup provided by InvCM could be used to equilibrate GCMs at higher spatial resolution or to perform broader parameter space exploration in order to gain new insight into the climate system. Additionally, InvCM could be used to find unstable and hidden climate states, and to find climate states close to bifurcations such as the runaway greenhouse transition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Intrinsic Century-Scale Variability in Tropical Pacific Sea Surface Temperatures and Their Influence on Western US Hydroclimate

Hydroclimate variability of the southwest United States (SWUS) is influenced by the tropical Pacific Ocean, particularly through the teleconnection to El Nino/Southern Oscillation (ENSO), which is expected to be altered by climate change. Natural variability in this teleconnection has not been robustly quantified, complicating the detection of anthropogenic climate change. Here, we use a linear inverse model (LIM) to quantify natural variability in the ENSO-SWUS teleconnection. The LIM yields realistic teleconnection patterns with century-scale variability comparable to simulations from the Last Millennium Ensemble project and the Climate Model Intercomparison Project Phases 5 and 6. The variability quantified by the LIM illuminates two aspects of our understanding of ENSO and its impacts: the inherent statistics of the observable system can produce century-long periods with a wide range of correlations to SWUS hydroclimate, including nonsignificant correlations, and thus that detecting changes in ENSO-related hydroclimate variability is challenging in a changing climate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2000

The Evolution of Tropical Precipitation Patterns During ENSO Events Using 21+ Years of GPCP Merged Data

The ENSO phenomenon is characterized by fluctuations in the climate system of the tropical Pacific. Quantifying changes in the precipitation component of this system is important in understanding the distribution of heating in the atmosphere which drives the large-scale circulation and affects the weather patterns in the mid-latitudes. Monitoring precipitation anomalies in the Pacific is also an important component for tracking the evolution of ENSO. The most timely and complete observations of the earth come from satellite instruments. In this study, the state of the art satellite-gauge merged monthly precipitation data set from the Global Precipitation Climatology Project (GPCP) is used to depict tropical rainfall patterns during ENSO events over the past two decades and quantify these patterns using indices. This analysis will be complemented by daily precipitation data which can resolve the Madden-Julian Oscillation and westerly wind burst events. The 1997-98 El Nino and 1998-2000 La Nina were the best observed ENSO cycle in the historic record. Prior to the El Nino (in terms of anomalous warming of the east Pacific) dry anomalies over the Maritime Continent were observed in February 1997 as a westerly wind burst advected convection to the east. The largest SST anomalies occurred around November-December 1997, which were followed by the largest precipitation anomalies in the beginning of 1998. The largest precipitation departures from normal were not colocated with the SST anomalies, but were further west, In the spring of 1998 negative precipitation anomalies to the north of the equator intensified, signaling the mature phase of the El Nino. A rapid increase in the precipitation-based La Nina index from December-January 1998 to March-April 1998 signaled the coming La Nina. The 1982-1983 El Nino was comparable in strength (according to several indices) and the precipitation patterns evolved in a similar fashion. For the 1998-2000 La Nina, the coldest anomalies, were confined to the central equatorial Pacific, while the driest anomalies were found in the west Pacific,

Curtis, Scott↗
NASA NTRS2016

Evaluation of NASA's MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC) U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

MERRA↗
DOE OSTI2024

DAWN: Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate

Abstract Climate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

Arctic Soil Patterns Analogous to Fluid Instabilities: Supporting Data

This dataset characterizes solifluction lobe morphology and spatial patterns using pre-existing LiDAR-derived digital elevation models of 25 sites across Norway with accompanying long term climate data for each site. Data were collected as part of an effort to better understand controls on the formation of solifluction patterns and to test the idea that they are analogous to fluid instabilities. We also provide soil velocity profiles and estimates of effective viscosity from across the world, drawn from literature. They were collected to improve our understanding of the rheology of soliflucting soil. See this article for more information on the theoretical motivation behind this dataset see "Arctic soil patterns analogous to fluid instabilities" (Glade et al., 2021). Data files arranged in a hierarchy and include image files *.tif and *.png, GIS shapefiles and geopackages (*.gpkg), *.csv (with same file as *.xlsx), and *.py (Python scripts readable with a text editor). Files also bundled into *.zip files. Note (2021-10-20): unit corrections made on two files: RR.csv and snowfall.csv. 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impact of climate change on adaptive management decisions in the face of water scarcity

Reoccurring drought through the early 2000s has caused a serious water scarcity issue in the Colorado River Basin. Previous modeling studies have focused on the impact of climate change without considering the adaptive behaviors of farmers and under-utilized Indian water rights. Here, we use a coupled agent-based water resource model (ABM) to investigate how the adaptive decisions of farmers can affect water resource management under both climate change impacts and fully utilized Indian water right conditions. We used five General Circulation Model projections with RCP8.5 scenarios for the study. The results of farm-level decision-making showed different responses in irrigated areas that were changing due to climate change impact. While winter precipitation changes might partially explain the behavior changes, no specific pattern could be concluded based on their location. Also, farmers’ responses about annual water diversion showed more significant inter-year variation compared to irrigated areas. Basin-level metrics showed that climate change impacts will generally worsen water scarcity issues as measured in Navajo Reservoir storage, flow to Lake Powell, and instream flow requirement. But these basin-level water scarcity metrics cannot reflect individual farm-level impacts under climate change, which is why modeling the bottom-up management actions is necessary. When the under-utilized Indian water rights are fully used, it is more likely to trigger the shortage sharing agreement due to the higher tribal water depletion. Evaluation of model uncertainty and a more realistic setup for adaptive actions under drought contingency plans are suggested for future research.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Satellite-based Assessment of Climate Controls on US Burned Area

Climate regulates fire activity through the buildup and drying of fuels and the conditions for fire ignition and spread. Understanding the dynamics of contemporary climate-fire relationships at national and sub-national scales is critical to assess the likelihood of changes in future fire activity and the potential options for mitigation and adaptation. Here, we conducted the first national assessment of climate controls on US fire activity using two satellite-based estimates of monthly burned area (BA), the Global Fire Emissions Database (GFED, 1997 2010) and Monitoring Trends in Burn Severity (MTBS, 1984 2009) BA products. For each US National Climate Assessment (NCA) region, we analyzed the relationships between monthly BA and potential evaporation (PE) derived from reanalysis climate data at 0.5 resolution. US fire activity increased over the past 25 yr, with statistically significant increases in MTBS BA for entire US and the Southeast and Southwest NCA regions. Monthly PE was strongly correlated with US fire activity, yet the climate driver of PE varied regionally. Fire season temperature and shortwave radiation were the primary controls on PE and fire activity in the Alaska, while water deficit (precipitation PE) was strongly correlated with fire activity in the Plains regions and Northwest US. BA and precipitation anomalies were negatively correlated in all regions, although fuel-limited ecosystems in the Southern Plains and Southwest exhibited positive correlations with longer lead times (6 12 months). Fire season PE in creased from the 1980s 2000s, enhancing climate-driven fire risk in the southern and western US where PE-BA correlations were strongest. Spatial and temporal patterns of increasing fire season PE and BA during the 1990s 2000s highlight the potential sensitivity of US fire activity to climate change in coming decades. However, climatefire relationships at the national scale are complex, based on the diversity of fire types, ecosystems, and ignition sources within each NCA region. Changes in the seasonality or magnitude of climate anomalies are therefore unlikely to result in uniform changes in US fire activity.

Morton, D. C.↗
DOE OSTI2025

Subsurface Cooling and Sea Surface Temperature Pattern Formation Over the Equatorial Pacific

Abstract The equatorial cold tongue region has not warmed up in response to historical radiative forcing in the real world, contrary to the strong warming often simulated by climate models. Here we demonstrate that climate models fail to represent one or both of the key processes driving observed sea surface temperature (SST) pattern formation: a realistic surface wind stress pattern shaping subsurface cooling through wind‐driven circulation changes, and effective connectivity between subsurface and surface temperatures via upwelling and mixing. Consequently, none of the models approximate the observed lack of cold tongue SST warming and strengthening of zonal SST gradient across the equatorial Pacific. Furthermore, those that come closest achieve this due to interhemispheric warming differences rather than equatorial dynamics as observed. Addressing different origins of subsurface cooling in observations and simulations, and how they connect to SST, will lead to improved understanding of tropical Pacific SST changes to date and how they will evolve in the future.

Jiang, Feng [Lamont‐Doherty Earth Observatory Colu↗
DOE OSTI2021

Benchmarking performance changes in the simulation of extratropical modes of variability across CMIP generations

In this work, we evaluate extratropical modes of variability in the three most recent phases of the Coupled Model Intercomparison Project (CMIP3, 5, and 6) to gauge improvement of climate models over time. A suite of high-level metrics is employed to objectively evaluate how well climate models simulate the qobserved Northern Annular Mode (NAM), North Atlantic Oscillation (NAO), Pacific North America pattern (PNA), Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO), North Pacific Oscillation (NPO), and North Pacific Gyre Oscillation (NPGO). We apply a Common Basis Function (CBF) approach that projects model anomalies onto observed empirical orthogonal functions (EOFs), together with the traditional EOF approach, to CMIP Historical and AMIP models. We find simulated spatial patterns of those modes have been significantly improved in the newer models, although the skill improvement is sensitive to the mode and season considered. We identify some potential contributions to the pattern improvement of certain modes (e.g., the Southern Hemisphere jet and High-top vertical coordinate), however the performance changes are likely attributed to gradual improvement of the base climate and multiple relevant processes. Less performance improvement is evident in the mode amplitude of these modes and systematic overestimation of the mode amplitude in spring remains in the newer climate models. We find that the post-dominant season amplitude errors in atmospheric modes are not limited to coupled runs but are often already evident in AMIP simulations. This suggests that rectifying the egregious post-dominant season amplitude errors found in many models can be addressed in an atmospheric-only framework making it more tractable to address in the model development process.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Seasonal Patterns and Remote Spectral Estimation of Canopy Chemistry Across the Oregon Transect

We examined seasonal changes in canopy chemical concentrations and content in conifer forests growing along a climate gradient in western Oregon, as part of the Oregon Transect Ecosystem Research (OTTER) study. The chemical variables were related to seasonal patterns of growth and production. Statistical comparisons of chemical variables with data collected from two different airborne remote-sensing platforms were also carried out. Total nitrogen (N) concentrations in foliage varied significantly both seasonally and among sites; when expressed as content in the forest canopy, nitrogen varied to a much greater extent and was significantly related to aboveground net primary production (r = 0.99). Chlorophyll and free amino acid concentrations varied more strongly than did total N and may have reflected changes in physiological demands for N. Large variations in starch concentrations were measured from pre- to post-budbreak in all conifer sites. Examination of remote-sensing data from two different airborne instruments suggests the potential for remote measurement of some canopy chemicals. Multivariate analysis of high-resolution spectral data in the near infrared region indicated significant correlations between spectral signals and N concentration and canopy N content; the correlation with canopy N content was stronger and was probably associated in part with water absorption features of the forest canopy. The spectral bands that were significantly correlated with lignin concentration and content were similar to bands selected in the other laboratory and airborne studies; starch concentrations were not significantly related to spectral reflectance data. Strong relationships between the spectral position of specific reflectance features in the visible region and chlorophyll were also found.

Matson, Pamela↗