Search NASA⌕ Search

SEARCH · Search NASA

Results for “Primary Production”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

MODIS Data from the GES DISC DAAC: Moderate-Resolution Imaging Spectroradiometer (MODIS)

The Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) is responsible for the distribution of the Level 1 data, and the higher levels of all Ocean and Atmosphere products (Land products are distributed through the Land Processes (LP) DAAC DAAC, and the Snow and Ice products are distributed though the National Snow and Ice Data Center (NSIDC) DAAC). Ocean products include sea surface temperature (SST), concentrations of chlorophyll, pigment and coccolithophores, fluorescence, absorptions, and primary productivity. Atmosphere products include aerosols, atmospheric water vapor, clouds and cloud masks, and atmospheric profiles from 20 layers. While most MODIS data products are archived in the Hierarchical Data Format-Earth Observing System (HDF-EOS 2.7) format, the ocean binned products and primary productivity products (Level 4) are in the native HDF4 format. MODIS Level 1 and 2 data are of the Swath type and are packaged in files representing five minutes of Files for Level 3 and 4 are global products at daily, weekly, monthly or yearly resolutions. Apart from the ocean binned and Level 4 products, these are in Grid type, and the maps are in the Cylindrical Equidistant projection with rectangular grid. Terra viewing (scenes of approximately 2000 by 2330 km). MODIS data have several levels of maturity. Most products are released with a provisional level of maturity and only announced as validated after rigorous testing by the MODIS Science Teams. MODIS/Terra Level 1, and all MODIS/Terra 11 micron SST products are announced as validated. At the time of this publication, the MODIS Data Support Team (MDST) is working with the Ocean Science Team toward announcing the validated status of the remainder of MODIS/Terra Ocean products. MODIS/Aqua Level 1 and cloud mask products are released with provisional maturity.

Source record↗
NASA NTRS2016

Combining Livestock Production Information in a Process-Based Vegetation Model to Reconstruct the History of Grassland Management

Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5deg by 0.5deg. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 19012012. The grass-biomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, risingCO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6.1 x 10(exp 6) km(exp 2) in 1901 to 12.3 x 10(exp 6) kmI(exp 2) in 2000, although the expansion pathway varies between different regions. ORCHIDEE-GM also simulated augmentation in global mean productivity and herbage-use efficiency over managed grassland during the 20th century, indicating a general intensification of grassland management at global scale but with regional differences. The gridded grassland management intensity maps are model dependent because they depend on modelled productivity. Thus specific attention was given to the evaluation of modelled productivity against a series of observations from site-level net primary productivity (NPP) measurements to two global satellite products of gross primary productivity (GPP) (MODIS-GPP and SIF data). Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle, and inter-annual variability of grassland productivity at global scale well and thus is appropriate for global applications presented here.

Livestock dataset↗
NASA NTRS1995

Seasonal variability of light availability and utilization in the Sargasso Sea

A 2 year time series of optical, biogeochemical, and physical parameters, taken near the island of Bermuda, is used to evaluate the sources of temporal variability in light avaliability and utilization in the Sargasso Sea. Integrated assessments of light availability are made by examining the depth of constant percent incident photosynthetically available radiation (% PAR) isolumes. To first order, changes in the depth %PAR isolumes were caused by physical processes: deep convection mixing in the winter which led to the spring bloom and concurrent shallowing of %PAR depths and the occurrence of anomalous thermohaline water masses during the summer and fall seasons. Spectral light availability variations are assessed using determinations of diffuse attenuation coefficient spectra which illustrates a significant seasonal cycle in colored detrital particulate and/or dissolved materials that is unrelated to changes in chlorophyll pigment concentrations. Temporal variations in the photosynthetic light utilization index Psi are used to assess vertically intergrated light utilization variations. Values of Psi are highly variable and show no apparent seasonal pattern which indicates that Psi is not simply a 'biogeochemical constant.' Determinations of in situ primary production rates and daily mean PAR fluxes are used to diagnose the relative role of light limitation in determining vertically integrated rates of primary production integral PP. The mean depth of the light-saturated zone (the vertical region where the daily mean PAR flux was greater than or equal to the saturation irradiance) is only approximately 40 m, although more than one half of interal PP occurred within this zone. Production model results illustrate that accurate predictions of integral PP are dependent upon rates of light-saturated production rather than upon indices of light limitation. It seems unlikely that significant improvements in simple primary production models will come from the partitioning of the Earth's seas into biogeochemical provinces.

Siegel, David A.↗
NASA NTRS1985

Analysis of Terrestrial Conditions and Dynamics

An ecological model is developed to estimate annual net primary productivity of vegetation in twelve major North American biomes. Three models are adapted and combined, each addressing a different factor known to govern primary productivity, i.e., photosynthesis, respiration, and moisture availability. Measures of intercepted photosynthetically active radiation (1PAR) for input to the photosynthesis model are derived from spectral vegetation index data. Normalized Difference Vegetation Index (NDVI) data are produced from NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) observations for April 1982 through March 1983. NDVI values are sampled from within the biomes at locations for which climatological data are available. Monthly estimates of Net Primary Productivity (NPP) for each sample location are generated and summed over the twelve month period. These monthly estimates are averaged to produce a single annual estimated NPP value for each biomes. Comparison of estimated NPP values with figures reported in the literature produces a correlation coefficient of 85.

Goward, S. N.↗
NASA NTRS2000

The Northeast Monsoon's Impact on Mixing, Phytoplankton Biomass and Nutrient Cycling in the Arabian Sea

In the northern Arabian Sea, atmospheric conditions during the Northeast (winter) Monsoon lead to deep convective mixing. Due to the proximity of the permanent pyncnocline to the sea surface, this mixing does not penetrate below 125 m. However, a strong nitracline is also present and the deep convection results in significant nitrate flux into the surface waters. This leads to nitrate concentrations over the upper 100 m that exceed 4 micrometers toward the end of the Monsoon. During the 1994/1995 US JGOFS/Arabian Sea expedition, the mean areal gross primary production over two successive Northeast Monsoons was determined to be 1.35gC/sq m/d. Thus, despite the deep penetrative convection, high rates of primary productivity were maintained. An interdisciplinary model was developed to elucidate the biogeochemical processes involved in supporting the elevated productivity. This model consists of a 1-D mixed-layer model coupled to a set of equations that tracked phytoplankton growth and the concentration of the two major nutrients (nitrate and ammonium). Zooplankton grazing was parameterized by rate constant determined by shipboard experiments. Model boundary conditions consist of meteorological time-series measured from the surface buoy that was part of the ONR Arabian Sea Experiment's central mooring. Our numerical experiments show that elevated surface evaporation, and the associated salinization of the mixed layer, strongly contributes to the frequency and penetration depth of the observed convective mixing. Cooler surface temperatures, increased nitrate entrainment, reduced water column stratification, and lower near-surface chlorophyll a concentrations all result from this enhanced mixing. The model also captured a dependence on regenerated nitrogen observed in nutrient uptake experiments performed during the Northeast Monsoon. Our numerical experiments also indicate that variability in mean pycnocline depth causes up to a 25% reduction in areal chlorophyll a concentration. We hypothesize that such shifts in pycnocline depth may contribute to the interannual variations in primary production and surface chlorophyll a concentration that have been previously observed in this region.

Wiggert, J. D.↗
NASA NTRS2000

The Turbulent Life of Phytoplankton

Phytoplankton is a generic name for photosynthesizing microscopic organisms that inhabit the upper sunlit layer (euphotic zone) of almost all oceans and bodies of freshwater. They are agents for "primary production," the incorporation of carbon from the environment into living organisms, a process that, sustains the aquatic food web. It is estimated that phytoplankton contribute about half of the global primary production, the other half being due to terrestrial plants. By sustaining the aquatic food web and controlling the biogeochemical cycles through primary production, phytoplankton exert a dominant influence on life on earth. Turbulence influences this process in three very important ways. First, essential mineral nutrients are transported from the deeper layers to the euphotic zone through turbulence. Second, turbulence helps to suspend phytoplankton in the euphotic zone since in still water, the phytoplankton, especially the larger species, tend to settle out of the sunlit layers. Third, turbulence transports phytoplankton from the surface to the dark sterile waters, and this is an important mechanism of loss. Thus, stable phytoplankton populations are maintained through a delicate dynamic balance between the processes of turbulence, reproduction, and sinking. The first quantitative model for this was introduced by Riley, Stommel and Bumpus in 1949. This is an attempt to extend their efforts through a combination of analysis and computer simulation in order to better understand the principal qualitative aspects of the physical/biological coupling of this natural system.

S Ghosal↗
NASA NTRS1982

The Marine Resources Experiment Program (MAREX)

The Satellite Ocean Color Science Working Group was established to consider the scientific utility of repeated satellite measurements of ocean color, especially for measuring global ocean chlorophyll and for studying the fate of global primary productivity in the sea. Results of the group's deliberations are presented. The scientific requirements are given for ocean color data from a CZCS follow on sensor in order to address global primary productivity, fishery, and carbon storage problems. Some specific experiments, called the marine resource experiment and designed to determine critical nutrient fluxes, photosynthetic rates, and primary productivity and biomass, are outlined.

Source record↗
NASA NTRS1993

DataHub sponsored analysis

The primary productivity of phytoplankton in the ocean is largely responsible for the assimilation of carbon into the oceanic environment, and thus in part the removal of carbon from the atmosphere. Because the ocean is thought to be a primary sink for atmospheric carbon, the basin wide and global distribution of oceanic primary productivity is of central importance in the global budget of carbon. To understand the global productivity of the oceans, the interactions between the physical and biological structures must be known. To address the broader context of the primary productivity of the sea, the physical and biological processes and their variability, including changes in water mass, incident irradiance, nutrients, and consequent formation of blooms of different species of marine phytoplankton and bacteria must be studied. In this investigation, we will use time series of the pigment distributions, taken from the Coastal Zone Color Scanner (CZCS), and of the sea-surface temperature, taken from the NOAA Advanced Very High Resolution Radiometer (AVHRR). These time series will be examined to determine the spatial and temporal statistics of productivity, including the interannual variations that occur in productivity caused by variations in the physical environment. For this task we have chosen to use monthly composite global maps created from the satellite imagery.

Tran, An Van↗
NASA NTRS1997

Regional Application of an Ecosystem Production Model for Studies of Biogeochemistry in the...

The degree to which primary production, soil carbon, and trace gas fluxes in tropical forests of the Amazon are limited by moisture availability and other environmental factors was examined using an ecosystem modeling application for the country of Brazil. A regional geographic information system (GIS) serves as the data source of climate drivers, satellite images, land cover, and soil properties for input to the NASA Ames-CASA (Carnegie-Ames-Stanford Approach) model over a 8-km grid resolution. Simulation results supports the hypothesis that net primary production (NPP) is limited by cloud interception of solar radiation over the humid northwestern portion of the region. Peak annual rates for NPP of nearly 1.4 kg C m-2yr -1are localized in the seasonally dry eastern Amazon in areas that we assume are primarily deep-rooted evergreen forest cover. Regional effects of forest conversion on NPP and soil carbon content are indicated in the model results, especially in seasonally dry areas. Comparison of model flux predictions along selected eco-climatic transects reveal moisture, soil, and land use controls on gradients of ecosystem production and soil trace gas emissions (CO2, N2O, and NO). These results are used to formulate a series of research hypotheses for testing in the next phase of regional modeling, which includes recalibration of the light-use efficiency term in CASA using field measurements of NPP, and refinements of vegetation index and soil property (texture and potential rooting depth) maps for the region.

Potter, C. S.↗
NASA NTRS2013

Phenological Versus Meteorological Controls on Land-atmosphere Water and Carbon Fluxes

Phenological dynamics and their related processes strongly constrain land-atmosphere interactions, but their relative importance vis-à-vis meteorological forcing within general circulation models (GCMs) is still uncertain. Using an off-line land surface model, we evaluate leaf area and meteorological controls on gross primary productivity, evapotranspiration, transpiration, and runoff at four North American sites, representing different vegetation types and background climates. Our results demonstrate that compared to meteorological controls, variation in leaf area has a dominant control on gross primary productivity, a comparable but smaller influence on transpiration, a weak influence on total evapotranspiration, and a negligible impact on runoff. Climate regime and characteristic variations in leaf area have important modulating effects on these relative controls, which vary depending on the fluxes and timescales of interest. We find that leaf area in energylimited evaporative regimes tends to exhibit greater control on annual gross primary productivity than in moisture-limited regimes, except when vegetation exhibits little interannual variation in leaf area. For transpiration, leaf area control is somewhat less in energylimited regimes and greater in moisture-limited regimes for maximum pentad and annual fluxes. These modulating effects of climate and leaf area were less clear for other fluxes and at other timescales. Our findings are relevant to land-atmosphere coupling in GCMs, especially considering that leaf area variations are a fundamental element of land use and land cover change simulations.

Puma, Michael J.↗
NASA NTRS1998

A Method to Access Absolute fIPAR fo Vegetation in Spatially Complex Ecosystems

Arid and semi-arid lands compose a large fraction of the earth's terrestrial vegetation, and thereby contribute significantly to global atmospheric-biospheric interactions. The thorny shrubs and small trees in these semi-arid shrub lands have counterparts throughout much of the world's tropical and subtropical zones and have captured substantial areas of the world's former grasslands. The objective of our field and remotely sensed measurements in the semi-arid shrublands of Texas is to monitor interannual variability and directional change in landscape structure, ecosystem processes and atmosphere-biosphere exchanges. To understand the role ecosystems play in controlling the composition of the atmosphere, it is necessary to quantify processes such as photosynthesis and primary production, decomposition and soil carbon storage, and trace gas exchanges. Photosynthesis is the link whereby surface-atmosphere exchanges such as the radiation balance and exchange of heat, moisture, and gas can be inferred. It also describes the efficiency of carbon dioxide exchange and is directly related to the primary production of vegetation. Our efforts in this paper focus on the indirect, quantification of photosynthesis, and thereby carbon flux and net primary production, via remote sensing and direct measurements of intercepted photosynthetically active radiation (IPAR).

Wessman, Carol A.↗
NASA NTRS2014

Natural Ocean Carbon Cycle Sensitivity to Parameterizations of the Recycling in a Climate Model

Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10 %) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34 %, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which eventually resurfaces with the global thermohaline circulation especially in the Southern Ocean. Because of the reduced primary production and carbon export in GISSEH compared to GISSER, the biological pump efficiency, i.e., the ratio of primary production and carbon export at 75 m, is half in the GISSEH of that in GISSER, The Southern Ocean emerges as a key region where the CO2 flux is as sensitive to biological parameterizations as it is to physical parameterizations. The fidelity of ocean mixing in the Southern Ocean compared to observations is shown to be a good indicator of the magnitude of the biological pump efficiency regardless of physical model choice.

Antarctic Ocean↗
NASA NTRS2009

Using LIDAR and Quickbird Data to Model Plant Production and Quantify Uncertainties Associated with Wetland Detection and Land Cover Generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the MOderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

Cook, Bruce D.↗
NASA NTRS2012

Development of Primary Volatile Production in COMET C/20O9 Pl (GARRADD) During its 2011-2O12 Apparition

We quantified primary volatiles in comet C/2009 Pl (Garradd) through pre- and post-perihelion observations acquired during its apparition in 2011-12 [1,2,3]. Detected volatiles include H2O, CO, CH4, C2H2, C2H6, HCN, NH3, H2CO, and CH3OH. We present production rates and chemical abundance ratios (relative to water) for all species, and I-D spatial profiles for multiple primary volatiles. We discuss these findings in the context of an emerging taxonomy based on primary volatiles in comets [4]. We used three spectrometer/telescope combinations. On UT 20ll August 7 (Rh 2.4 AU) and September 17-21 (Rh 2.0 AU), we used CRIRES at ESO's Very Large Telescope (VLT) [1]. On September 8 and 9 (Rh 2.1 AU), we used NIRSPEC at Keck-2 and CSHELL at IRTF [2]. Using NIRSPEC on October 13 and 2012 January 08 (Rh 1.83 and 1.57 AU, respectively), we detected nine primary volatiles pre-perihelion, and six post-perihelion [3]. CO was enriched in Garradd while C2H2 was strongly depleted. C2H6 and CH3OH displayed abundances close to those measured for the majority of Oort cloud comets observed to date. The high fractional abundance of CO identifies comet C12009 P1 as a CO-rich comet. Spatial profiles revealed notable differences among individual primary species. Given the relatively large heliocentric distance of C/2009 Pl, we explored the effect of water not being fully sublimated within our field of view and we identi$, the "missing" water fraction needed to reconcile the retrieved abundance ratios with the mean values found for "organics-normal" comets.

Mumma, M. J.↗
NASA NTRS1989

Monitoring global land surface using Nimbus-7 37 GHz data - Theory and examples

Simplified radiative transfer models for 37 GHz brightness temperatures are developed and applied to observations taken with the Nimbus-7 scanning multichannel microwave radiometer. It is found that, as the vegetation density increases, polarization difference decreases. The polarization difference also decreases with increasing surface roughness. Empirical relations are established between the satellite observations and annual rainfall over Africa and Australia, primary productivity, and actual evaporation. Color-coded maps of primary productivity and evaporation are presented.

Choudhury, Bhaskar J.↗
NASA NTRS2000

BOREAS RSS-8 BIOME-BGC Model Simulations at Tower Flux Sites in 1994

BIOME-BGC is a general ecosystem process model designed to simulate biogeochemical and hydrologic processes across multiple scales (Running and Hunt, 1993). In this investigation, BIOME-BGC was used to estimate daily water and carbon budgets for the BOREAS tower flux sites for 1994. Carbon variables estimated by the model include gross primary production (i.e., net photosynthesis), maintenance and heterotrophic respiration, net primary production, and net ecosystem carbon exchange. Hydrologic variables estimated by the model include snowcover, evaporation, transpiration, evapotranspiration, soil moisture, and outflow. The information provided by the investigation includes input initialization and model output files for various sites in tabular ASCII format.

Hall, Forrest G.↗
NASA NTRS1983

Remote sensing investigations of wetland biomass and productivity for global biosystems research

Monitoring biomass of wetlands ecosystems can provide information on net primary production and on the chemical and physical status of wetland soils relative to anaerobic microbial transformation of key elements. Multispectral remote sensing techniques successfully estimated macrophytic biomass in wetlands systems. Regression models developed from ground spectral data for predicting Spartina alterniflora biomass over an entire growing season include seasonal variations in biomass density and illumination intensity. An independent set of biomass and spectral data were collected and the standing crop biomass and net primary productivity were estimated. The improved spatial, radiometric and spectral resolution of th LANDSAT-4 Thematic Mapper over the LANDSAT MSS can greatly enhance multispectral techniques for estimating wetlands biomass over large areas. These techniques can provide the biomass data necessary for global ecology studies.

Harkisky, M.↗
NASA NTRS2016

Remotely Sensed Northern Vegetation Response to Changing Climate: Growing Season and Productivity Perspective

Vegetation growing season and maximum photosynthetic state determine spatiotemporal variability of seasonal total gross primary productivity of vegetation. Recent warming induced impacts accelerate shifts on growing season and physiological status over Northern vegetated land. Thus, understanding and quantifying these changes are very important. Here, we first investigate how vegetation growing season and maximum photosynthesis state are evolved and how such components contribute on inter-annual variation of seasonal total gross primary productivity. Furthermore, seasonally different response of northern vegetation to changing temperature and water availability is also investigated. We utilized both long-term remotely sensed data to extract larger scale growing season metrics (growing season start, end and duration) and productivity (i.e., growing season summed vegetation index, GSSVI) for answering these questions. We find that regionally diverged growing season shift and maximum photosynthetic state contribute differently characterized productivity inter-annual variability and trend. Also seasonally different response of vegetation gives different view of spatially varying interaction between vegetation and climate. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation to changing climate.

Climate↗