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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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NASA NTRS2003

Satellites as Sentinels for Climate and Health

Remotely-sensed data and observations are providing powerful new tools for addressing climate and environment-related human health problems through increased capabilities for monitoring, risk mapping, and surveillance of parameters useful to such problems as vector- borne and infectious diseases, air and water quality,. harmful algal blooms, W radiation, contaminant and pathogen transport in air and water, and thermal stress. Remote sensing, geographic information systems (GIs), global positioning systems (GPS), improved computation capabilities, and interdisciplinary research between the Earth and health science communities, together with local knowledge, are being combined in rich collaborative efforts resulting in more rapid problem-solving, early warning, and prevention in global climate and health issues. These collaborative efforts are enabling increased understanding of the relationships among changes in temperature, rainfall, wind, soil moisture, solar radiation, vegetation, and the patterns of extreme weather events and health issues. This increased understanding and improved information and data sharing, in turn, empowers local health and environmental decision-makers to better predict climate-related health problems, decrease vulnerability, take preventive measures, and improve response actions. This paper provides a number of recent examples of how satellites - from their unique vantage point in space - can serve as sentinels for climate and health.

Maynard, Nancy G.↗
NASA NTRS2021

Ecosystem age-class dynamics and distribution in the LPJ-wsl v2.0 global ecosystem model

Forest ecosystem processes follow classic responses with age, peaking production around canopy closure and declining thereafter. Although age dynamics might be more dominant in certain regions over others, demographic effects on net primary production (NPP) and heterotrophic respiration (Rh) are bound to exist. Yet, explicit representation of ecosystem demography is notably absent in many global ecosystem models. This is concerning because the global community relies on these models to regularly update our collective understanding of the global carbon cycle. This paper aims to present the technical developments of a computationally efficient approach for representing age-class dynamics within a global ecosystem model, the Lund–Potsdam–Jena – Wald, Schnee, Landschaft version 2.0 (LPJ-wsl v2.0) dynamic global vegetation model and to determine if explicit representation of demography influenced ecosystem stocks and fluxes at global scales or at the level of a grid cell. The modeled age classes are initially created by simulated fire and prescribed wood harvesting or abandonment of managed land, otherwise aging naturally until an additional disturbance is simulated or prescribed. In this paper, we show that the age module can capture classic demographic patterns in stem density and tree height compared to inventory data, and that simulated patterns of ecosystem function follow classic responses with age. We also present two scientific applications of the model to assess the modeled age-class distribution over time and to determine the demographic effect on ecosystem fluxes relative to climate. Simulations show that, between 1860 and 2016, zonal age distribution on Earth was driven predominately by fire, causing a 45- to 60-year difference in ages between older boreal (50–90° N) and younger tropical (23° S–23° N) ecosystems. Between simulation years 1860 and 2016, land-use change and land management were responsible for a decrease in zonal age by −6 years in boreal and by −21 years in both temperate (23–50° N) and tropical latitudes, with the anthropogenic effect on zonal age distribution increasing over time. A statistical model helped to reduce LPJ-wsl v2.0 complexity by predicting per-grid-cell annual NPP and Rh fluxes by three terms: precipitation, temperature, and age class; at global scales, R2 was between 0.95 and 0.98. As determined by the statistical model, the demographic effect on ecosystem function was often less than 0.10 kg C/sq. myr but as high as 0.60 kg C/sq. myr where the effect was greatest. In the eastern forests of North America, the simulated demographic effect was of similar magnitude, or greater than, the effects of climate; simulated demographic effects were similarly important in large regions of every vegetated continent. Simulated spatial datasets are provided for global ecosystem ages and the estimated coefficients for effects of precipitation, temperature and demography on ecosystem function. The discussion focuses on our finding of an increasing role of demography in the global carbon cycle, the effect of demography on relaxation times (resilience) following a disturbance event and its implications at global scales, and a finding of a 40 Pg C increase in biomass turnover when including age dynamics at global scales. Whereas time is the only mechanism that increases ecosystem age, any additional disturbance not explicitly modeled will decrease age. The LPJ-wsl v2.0 age module represents another step forward towards understanding the role of demography in global ecosystems.

LPJ-wsl↗
NASA NTRS1986

COVER Project and Earth resources research transition

Results of research in the remote sensing of natural boreal forest vegetation (the COVER project) are summarized. The study objectives were to establish a baseline forest test site; develop transforms of LANDSAT MSS and TM data for forest composition, biomass, leaf area index, and net primary productivity; and perform tasks required for testing hypotheses regarding observed spectral responses to changes in leaf area index in aspen. In addition, the transfer and documentation of data collected in the COVER project (removed from the Johnson Space Center following the discontinuation of Earth resources research at that facility) is described.

Botkin, D. B.↗
NASA NTRS1994

Yield and seed oil content response of dwarf, rapid-cycling Brassica to nitrogen treatments, planting density, and carbon dioxide enrichment

Effects of N level (15 to 30 mM), time of N increase (14 to 28 days after planting), and planting density (1163 to 2093 plants/m2) were determined for crop yield responses of dwarf, rapid-cycling brassica (Brassica napus L., CrGC 5-2, Genome: ACaacc). Crops were grown in solid-matrix hydroponic systems and under controlled-environment conditions, including nonsupplemented (ambient) or elevated CO2 concentrations (998 +/- 12 micromoles mol-1). The highest seed yield rate obtained (4.4 g m-2 day-1) occurred with the lowest N level (15 mM) applied at the latest treatment time (day 28). In all trials, CO2 enrichment reduced seed yield rate and harvest index by delaying the onset of flowering and senescence and stimulating vegetative shoot growth. The highest shoot biomass accumulation rate (55.5 g m-2 day-1) occurred with the highest N level (30 mM) applied at the earliest time (day 14). Seed oil content was not significantly affected by CO2 enrichment. Maximum seed oil content (30% to 34%, dry weight basis) was obtained using the lowest N level (15 mM) initiated at the latest treatment time (day 28). In general, an increase in seed oil content was accompanied by a decrease in seed protein. Seed carbohydrate, moisture, and ash contents did not vary significantly in response to experimental treatments. Effects of N level and time of N increase were consistently significant for most crop responses. Planting density was significant only under elevated CO2 conditions.

Non-NASA Center↗
NASA NTRS2016

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Landsat-8 snow albedo↗
NASA NTRS2024

Effects of Water Limitation and Competition on Tree Carbon Allocation in an Earth System Modeling Framework

Earth system models (ESMs) have a limited capacity to represent plant functional diversity and shifts in trait distributions. Approaches to improving the representation of this complexity in ESMs include (i) optimality-based approaches that predict trait–environment responses and (ii) explicitly modelling coexistence and community assembly. These approaches are expected to converge only when optimality-based approaches identify competitively dominant strategies, which often differ from strategies that maximize ecosystem functioning or fitness components in monoculture. We used two models, LM3-PPA (a vegetation demographic model designed as an ESM component) and BiomeE (a computationally efficient analog for LM3-PPA), to explore how water limitation affects carbon allocation strategies of canopy trees. We compared competitive allocation strategies and those that maximize biomass or productivity in monoculture. We did not explicitly model coexistence or community assembly. Rather, we used model experiments to identify competitive and maximizing strategies in a two-dimensional trait space under different precipitation and mortality scenarios. At 10 eastern US locations, we simulated historical, wet and dry climate scenarios, novel drought and three different mortality scenarios (low, medium or high sensitivity to water deficit). For each site and scenario, we identified the competitive strategy and three maximizing strategies (maximum biomass, productivity or drought-tolerance). Root: leaf ratios tended to increase and leaf area tended to decrease with increasing water stress (increasing water limitation and its effects on mortality). However, relative to maximizing strategies, competitive strategies shifted towards greater allocation to roots and leaves with increasing water stress. Competitive overinvestments (greater allocation to roots and leaves by competitive strategies compared with maximizing strategies) were robust across different modelling contexts, including vegetation parameter sets (Acer vs. Populus), models (LM3-PPA vs. BiomeE) and uncalibrated vs. calibrated BiomeE versions. Synthesis: The theoretical prediction that competitive and maximizing allocation strategies differ under water limitation is confirmed for a demographic model designed as an ESM component. Optimality-based trait predictions can simplify representing trait diversity in ESMs but do not always correspond to competitive outcomes. Explicitly modelling coexistence and community assembly in ESMs is challenging but is likely the most general approach to representing trait diversity.

vegetation demographic model↗
NASA NTRS1997

The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity

Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain failing in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearitv in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

White, Cary B.↗
NASA NTRSDate not supplied

Flight Test Exploration of Integrated Wildfire Response Operations with Crewed and Uncrewed Air Assets

Since 2016, Japan Aerospace Exploration Agency (JAXA) and NASA have partnered to investigate the safe and efficient integration of uncrewed aircraft systems (UAS) in disaster relief operations. Current disaster response operations would benefit from the use of UAS but are limited by the need for safe airspace integration technologies and enabling regulations. The work presented in this paper focuses on the safe integration of UAS and helicopters in active wildfire disaster response operations. The authors propose the use of mission planning and traffic management technologies, including onboard pilot situation awareness support technologies, to coordinate airspace operations between crewed and uncrewed aircraft (e.g., UAS). A representative wildfire scenario including a helicopter and UAS was developed. The helicopter mission included a flight path that mimicked the siphoning of water from a natural water reservoir (lake) and a subsequent water drop over vegetation along the progressing edge of a fire perimeter. Simulated UAS were assumed to conduct aerial ignition flights in the vicinity as part of a controlled burn of the vegetation ahead of the fire front to create a natural barrier between the fire and a nearby populated area. A situation awareness tool was developed and used to support the helicopter pilots’ task to stay clear of the volume of airspace where the UAS was conducting its operation while efficiently conducting the fire suppression mission. A flight test using JAXA’s experimental helicopter was conducted in August 2022 to validate the developed technology. The advantages of the developed technology were demonstrated, and pilot feedback confirmed that real-time awareness of the UAS operation airspace helped the flight planning and execution of a safe mission that minimized the flight time loss due to the potential interference with the UAS. Post-flight interviews with the pilots indicated no sufficient increase in the pilots’ workload and provided ideas for future technology development. Future research will provide recommendations to standards development organizations to support considerations for crewed-uncrewed interactions in disaster-response operations.

disaster response↗
NASA NTRS1988

The prospects for detecting spectral shifts due to satellite sensor aging

Along with responsivity changes due to sensor aging, there may be concurrent spectral changes. A field-measurement approach for detecting postlaunch spectral changes is described. For illustration, one hypothetical model of change (spectral band shift) is explored through simulation for five satellite sensors. Two different types of natural terrain - vegetation and bare soil - are used as test targets.

Suits, G.↗
NASA NTRS1992

An overview of surface radiance and biology studies in FIFE

The use of satellite data to study and to understand energy and mass exchanges between the land surface and the atmosphere requires information about various biological processes and how various reflected or emitted spectral radiances are influenced by or manifested in these processes. To obtain such information, studies were conducted by the First ISLSCP Field Experiment (FIFE) surface radiances and biology (SRB) group using surface, near-surface, helicopter, and aircraft measurements. The two primary objectives of this group were to relate radiative fluxes to biophysical parameters and physiological processes and to assess how various management treatments affect important biological processes. This overview paper summarizes the results obtained by various SRB teams working in nine different areas: (1) measurements of bidirectional reflectance and estimation of hemispherical albedo; (2) evaluation of spatial and seasonal variability reflectance and vegetation indices; (3) determination of surface and radiational factors and their effects on vegetation indices and photosynthetically active radiation relationships; (4) use of surface temperatures to estimate sensible heat flux; (5) controls over photosynthesis and respiration at small scales; (6) soil surface CO2 fluxes and grassland carbon budget; (7) landscape variations in controls over gas exchange and energy partitioning; (8) radiometric response of prairie to management and topography; and (9) determination of nitrogen gas exchanges in a tallgrass prairie.

Blad, B. L.↗
NASA NTRS2016

Cross Correlation versus Normalized Mutual Information on Image Registration

This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.

band-to-band↗
NASA NTRS1993

The use of a vegetation index for assessment of the urban heat island effect

A vegetation index and radiative surface temperature were derived from NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) data for the Seattle, WA region from 28 June through 4 July 1991. The vegetation index and surface temperature values were computed for locations of weather observation stations within the region and compared to observed minimum air temperatures. These comparisons were used to evaluate the use of AVHRR data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). AVHRR derived normalized difference vegetation index (NDVI) and radiant surface temperature data from a one week composite product were both related significantly to observed minimum temperatures, however, the vegetation index accounted for a greater amount of the spatial variation observed in mean minimum temperatures. The difference in the NDVI between urban and rural regions appears to be an indicator of the difference in surface properties (i.e., evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures.

Gallo, K. P.↗
NASA NTRS2014

Temperature and Snow-Mediated Moisture Controls of Summer Photosynthetic Activity in Northern Terrestrial Ecosystems Between 1982 and 2011

Recent warming has stimulated the productivity of boreal and Arctic vegetation by reducing temperature limitations. However, several studies have hypothesized that warming may have also increased moisture limitations because of intensified summer drought severity. Establishing the connections between warming and drought stress has been difficult because soil moisture observations are scarce. Here we use recently developed gridded datasets of moisture variability to investigate the links between warming and changes in available soil moisture and summer vegetation photosynthetic activity at northern latitudes (greater than 45N) based on the Normalized Difference Vegetation Index (NDVI) since 1982. Moisture and temperature exert a significant influence on the inter-annual variability of summer NDVI over about 29% (mean r(sup 2) = 0.29 +/ 0.16) and 43% (mean r(sup 2 = 0.25 +/- 0.12) of the northern vegetated land, respectively. Rapid summer warming since the late 1980s (approximately 0.7deg C) has increased evapotranspiration demand and consequently summer drought severity, but contrary to earlier suggestions it has not changed the dominant climate controls of NDVI over time. Furthermore, changes in snow dynamics (accumulation and melting) appear to be more important than increased evaporative demand in controlling changes in summer soil moisture availability and NDVI in moisture-sensitive regions of the boreal forest. In boreal North America, forest NDVI declines are more consistent with reduced snowpack rather than with temperature-induced increases in evaporative demand as suggested in earlier studies. Moreover, summer NDVI variability over about 28% of the northern vegetated land is not significantly associated with moisture or temperature variability, yet most of this land shows increasing NDVI trends. These results suggest that changes in snow accumulation and melt, together with other possibly non-climatic factors are likely to play a significant role in modulating regional ecosystem responses to the projected warming and increase in evapotranspiration demand during the coming decades.

Snowpack↗
NASA NTRS2024

Evaluation of a Combined Drought Indicator Against Crop Yield Estimations and Simulations Over the Argentine Humid Pampas

Droughts pose serious threats to the agricultural sector, especially in rainfed-dominated agricultural regions like those in Argentina’s Humid Pampas. This region was recently impacted by slow-evolving and long-lasting droughts as well as by flash droughts, resulting in losses reaching thousands of millions of US dollars. Improvements of drought early warning systems are essential, particularly given the projected increase in drought frequency and severity over southern South America. The spatial and temporal relationship between precipitation deficits, soil moisture and vegetation health anomalies are crucial for better understanding and representation of the agricultural droughts and their impacts. In this context, the Combined Drought Indicator (CDI) considers the causal and time-lagged relationship of these three variables. The study’s objective is twofold: (1) Analyze the time-lagged response between precipitation deficits, soil moisture and satellite fAPAR anomalies; and (2) Evaluate the CDI’s capability to characterize the severity of drought events on the Humid Pampas against agricultural yield estimations and simulations, as well as agricultural emergency declarations. The correlation among the variables shows strong spatial variability. The highest Pearson correlation values (r > 0.42) are observed over parts of the Humid Pampas for time lags of 0, 10, and 20 days between the variables. Although the CDI has limitations, such as its coarse spatial resolution and monthly temporal resolution of precipitation data, it effectively tracks the progression of major drought events in the region. The CDI’s performance aligns well with estimations and simulations of soybean and corn yields, as well as official declarations of agricultural emergencies. Insights from this study also provide a basis for discussing potential improvements to the CDI. This study highlights the global and regional significance of evaluating and enhancing the CDI for effective drought monitoring, emphasizing the role of collaborative efforts for future advancements in drought early warning systems.

Combined Drought Indicator↗
NASA NTRS2012

The Influence of Ozone Precursor Emissions from Four World Regions on Tropospheric Composition and Radiative Climate Forcing

Ozone (O3) precursor emissions influence regional and global climate and air quality through changes in tropospheric O3 and oxidants, which also influence methane (CH4) and sulfate aerosols (SO4 (sup 2-)). We examine changes in the tropospheric composition of O3, CH4, SO4 (sup 2-) and global net radiative forcing (RF) for 20% reductions in global CH4 burden and in anthropogenic O3 precursor emissions (NOx, NMVOC, and CO) from four regions (East Asia, Europe and Northern Africa, North America, and South Asia) using the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model (CTM) simulations, assessing uncertainty (mean plus or minus 1 standard deviation) across multiple CTMs. We evaluate steady state O3 responses, including long-term feedbacks via CH4. With a radiative transfer model that includes greenhouse gases and the aerosol direct effect, we find that regional NOx reductions produce global, annually averaged positive net RFs (0.2 plus or minus 0.6 to 1.7 2 mWm(sup -2)/Tg N yr(sup -1), with some variation among models. Negative net RFs result from reductions in global CH4 (-162.6 plus or minus 2 mWm(sup -2) for a change from 1760 to 1408 ppbv CH4) and regional NMVOC (-0.4 plus or minus 0.2 to 0.7 plus or minus 0.2 mWm(sup -2)/Tg C yr(sup -1) and CO emissions (-0.13 plus or minus 0.02 to -0.15 plus or minus 0.02 mWm(sup-2)/Tg CO yr(sup-1). Including the effect of O3 on CO2 uptake by vegetation likely makes these net RFs more negative by -1.9 to- 5.2 mWm(sup -2)/Tg N yr(sup -1), -0.2 to -0.7 mWm(sup -2)/Tg C yr(sup -1), and -0.02 to -0.05 mWm(sup -2)/ Tg CO yr(sup -1). Net RF impacts reflect the distribution of concentration changes, where RF is affected locally by changes in SO4 (sup -2), regionally to hemispherically by O3, and globally by CH4. Global annual average SO4 2 responses to oxidant changes range from 0.4 plus or minus 2.6 to -1.9 plus or minus 1.3 Gg for NOx reductions, 0.1 plus or minus 1.2 to -0.9 plus or minus 0.8 Gg for NMVOC reductions, and -0.09 plus or minus 0.5 to -0.9 plus or minus 0.8 Gg for CO reductions, suggesting additional research is needed. The 100-year global warming potentials (GWP(sub 100)) are calculated for the global CH4 reduction (20.9 plus or minus 3.7 without stratospheric O3 or water vapor, 24.2 plus or minus 4.2 including those components), and for the regional NOx, NMVOC, and CO reductions (18.7 plus or minus 25.9 to 1.9 plus or minus 8.7 for NOx, 4.8 plus or minus 1.7 to 8.3 plus or minus 1.9 for NMVOC, and 1.5 plus or minus 0.4 to 1.7 plus or minus 0.5 for CO). Variation in GWP(sub 100) for NOx, NMVOC, and CO suggests that regionally specific GWPs may be necessary and could support the inclusion of O3 precursors in future policies that address air quality and climate change simultaneously. Both global net RF and GWP100 are more sensitive to NOx and NMVOC reductions from South Asia than the other three regions.

ozone↗
NASA NTRS2023

A Multi-Satellite Framework to Rapidly Evaluate Extreme Biosphere Cascades: The Western US 2021 Drought and Heatwave

The increasing frequency and intensity of climate extremes and complex ecosystem responses motivate the need for integrated observational studies at low-latency to determine biosphere responses and carbon-climate feedbacks. Here, we develop a satellite-based rapid attribution workflow and demonstrate its use at a 1–2-month latency to attribute drivers of the carbon cycle feedbacks during the 2020-2021 Western US drought and heatwave. In the first half of 2021, concurrent negative photosynthesis anomalies and large positive column CO 2 anomalies were detected with satellites. Using a simple atmospheric mass balance approach, we estimate a surface carbon efflux anomaly of 132 TgC in June 2021, a magnitude corroborated 28 independently with a dynamic global vegetation model. Integrated satellite observations of hydrologic processes, representing the soil-plant-atmosphere continuum (SPAC), show that these surface carbon flux anomalies are largely due to substantial reductions in photosynthesis because of a spatially widespread moisture-deficit propagation through the SPAC between 2020 and 2021. A causal model indicates deep soil moisture stores partially drove photosynthesis, maintaining its values in 2020 and driving its declines throughout 2021. The causal model also suggests legacy effects may have amplified photosynthesis deficits in 2021 beyond the direct effects of environmental forcing. The integrated, observation framework presented here provides a valuable first assessment of a biosphere extreme response and an independent testbed for improving drought propagation and mechanisms in models. The rapid identification of extreme carbon anomalies and hotspots can also aid mitigation and adaptation decisions.

Causal model↗
NASA NTRS1998

Detecting a Terrestrial Biosphere Sink for Carbon Dioxide: Interannual Ecosystem Modeling for the Mid-1980s

There is considerable uncertainty as to whether interannual variability in climate and terrestrial ecosystem production is sufficient to explain observed variation in atmospheric carbon content over the past 20-30 years. In this paper, we investigated the response of net CO2 exchange in terrestrial ecosystems to interannual climate variability (1983 to 1988) using global satellite observations as drivers for the NASA-CASA (Carnegie-Ames-Stanford Approach) simulation model. This computer model of net ecosystem production (NEP) is calibrated for interannual simulations driven by monthly satellite vegetation index data (NDVI) from the NOAA Advanced Very High Resolution Radiometer (AVHRR) at 1 degree spatial resolution. Major results from NASA-CASA simulations suggest that from 1985 to 1988, the northern middle-latitude zone (between 30 and 60 degrees N) was the principal region driving progressive annual increases in global net primary production (NPP; i.e., the terrestrial biosphere sink for carbon). The average annual increase in NPP over this predominantly northern forest zone was on the order of +0.4 Pg (10 (exp 15) g) C per year. This increase resulted mainly from notable expansion of the growing season for plant carbon fixation toward the zonal latitude extremes, a pattern uniquely demonstrated in our regional visualization results. A net biosphere source flux of CO2 in 1983-1984, coinciding with an El Nino event, was followed by a major recovery of global NEP in 1985 which lasted through 1987 as a net carbon sink of between 0.4 and 2.6 Avg C per year. Analysis of model controls on NPP and soil heterotrophic CO2 fluxes (Rh) suggests that regional warming in northern forests can enhance ecosystem production significantly. In seasonally dry tropical zones, periodic drought and temperature drying effects may carry over with at least a two-year lag time to adversely impact ecosystem production. These yearly patterns in our model-predicted NEP are consistent in magnitude with the estimated exchange of CO2 by the terrestrial biosphere with the atmosphere, as determined by previous isotopic (delta (sup 13 C) convolution analysis. Ecosystem simulation results can help further target locations where net carbon sink fluxes have occurred in the past or may be verified in subsequent field studies.

Potter, Christopher S.↗
NASA NTRS2020

Great Basin Ecological Forecasting II: Assessing and Forecasting Live Fuel Moisture Content of Wildfire Fuels for the Eastern Great Basin to Improve Wildfire Timing and Severity Predictions

The eastern Great Basin (EGB) extends throughout the states of Arizona, Colorado,Idaho, Utah, and Wyoming, covering approximately 411,000 km2. In recent years, wildfires in the EGB have increased in frequency and size, representing a growing concern for our partners at the Bureau of Land Management (BLM), the National Weather Service (NWS), and the Great Basin Coordination Center (GBCC). Live fuel moisture (LFM) is an important factor in predicting wildfire risk, as dry vegetation requires less energy to combust than wet vegetation. Land managers currently derive LFM levels from just 165 in situ sites in the EGB. In order to provide partners with a more accurate assessment of LFM, the team used data from the National Elevation Dataset, Aqua and Terra Moderate Resolution Imaging Spectroradiometer, and Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite. These datasets include vegetation indices, evapotranspiration, and topographic variables, which were used to create biweekly forecasts of LFM throughout the EGB. An accuracy assessment was conducted using historical in situ data from our partners at the BLM and the GBCC. This model allowed our partners to make informed decisions regarding resource allocation in response to the predicted timing and severity of wildfires in the EGB.

Ecological Forecasting↗