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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Interannual variability in phytoplankton blooms observed in the northwestern Arabian Sea during the southwest monsoon

Interannual changes in the strength and seasonal evolution of the 1979 through 1982 surface-level southwest monsoon winds are related to variations in the summer phytoplankton bloom of the northwestern Arabian Sea by synthesis of satellite ocean-color remote sensing with analysis of in-situ hydrographic and meteorological data sets. The 1979-1981 southwest monsoon phytoplankton blooms in the northwest Arabian Sea peaked during August-September, extended from the Omani coast to about 6 E, and appeared to lag the development of open-sea upwelling by at least 1 month. In all 3 years the bloom was driven by spatially distinct upward nutrient fluxes to the euphotic zone forced by the physical processes of coastal upwelling and offshore Ekman pumping. Coastal upwelling was evident from May through September, yielded the most extreme concentrations of phytoplankton biomass, and along the Omani coast was limited in its impact on upper ocean biological variability to the continental shelf. Ekman pumping stimulated the development of a broad open-ocean component of the southwest monsoon phytoplankton bloom oceanward of the Omani shelf. Phytoplankton biomass on the Omani continental shelf was increased during both the early and late phases of the 1980 southwest monsoon due to stronger coastal upwelling under the most intense southwesterly winds of the four summers investigated. Diminished coastal upwelling during the early phase of the weak 1982 southwest monsoon resulted in a coastal bloom that reached a mean phytoplankton-pigment concentration that was 28 percent of that seen in 1980. The lack of a strong regional northwestern Arabian Sea bloom in late summer 1982 is attributed to the development of persistent, shallow temperature stratification that rendered Ekman pumping less effective in driving upward nutrient fluxes.

Brock, John C.↗
NASA NTRS2008

Ground-based SMART-COMMIT Measurements for Studying Aerosol and Cloud Properties

From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations cover large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite data sets. The development and deployment of SMARTCOMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile facilities are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instruments fall into three categories: flux radiometer, radiance sensor and in-situ probe. In this paper, we will demonstrate the capability of SMART-COMMIT in recent field campaigns (e.g., CRYSTAL-FACE, UAE 2, BASEASIA, NAMMA) that were designed and executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., biomass-burning smoke, airborne dust) and cirrus clouds. We envision robust approaches in which well-collocated ground-based measurements and space-borne observations will greatly advance our knowledge of extensive aerosols and clouds.

Tsay, Si-Chee↗
NASA NTRS2010

Evaluation of an ATP Assay to Quantify Bacterial Attachment to Surfaces in Reduced Gravity

Aim: To develop an assay to quantify the biomass of attached cells and biofilm formed on wetted surfaces in variable-gravity environments. Methods and Results: Liquid cultures of Pseudomonas aeruginosa were exposed to 30-35 brief cycles of hypergravity (< 2-g) followed by free fall (i.e., reduced gravity) equivalent to either lunar-g (i.e., 0.17 normal Earth gravity) or micro-g (i.e., < 0.001 normal Earth gravity) in an aircraft flying a series of parabolas. Over the course of two days of parabolic flight testing, 504 polymer or metal coupons were exposed to a stationary-phase population of P. aeruginosa strain ERC1 at a concentration of 1.0 x 10(exp 5) cells per milliliter. After the final parabola on each flight test day, half of the material coupon samples were treated with either 400 micro-g/L ionic silver fluoride (microgravity-exposed cultures) or 1% formalin (lunar-gravity-exposed cultures). The remaining sample coupons from each flight test day were not treated with a fixative. All samples were returned to the laboratory for analysis within 2 hours of landing, and all biochemical assays were completed within 8 hours of exposure to variable gravity. The intracellular ATP luminescent assay accurately reflected cell physiology compared to both cultivation-based and direct-count microscopy analyses. Cells exposed to variable gravity had more than twice as much intracellular ATP as control cells exposed only to normal Earth gravity.

Birmele, Michele N.↗
NASA NTRS2018

Seasonal and Interannual Assessment of Cloud Cover and Atmospheric Constituents Across the Amazon (2000 - 2015): Insights for Remote Sensing and Climate Analysis

The quantitative assessment of cloud cover and atmospheric constituents improves our ability to exploit the climate feedback into the Amazon basin. In the 21st century, three droughts have already occurred in the Amazonia (e.g. 2005, 2010, 2015), inducing regional changes in the seasonal patterns of atmospheric constituents. In addition to climate, the atmospheric dynamic and attenuation properties are long-term challenges for satellite-based remote sensing of this ecosystem: high cloudiness, abundant water vapor content and biomass burning season. Therefore, while climatology analysis supports the understanding of atmospheric variability and trends, it also offers valuable insights for remote sensing applications. In this study, we evaluate the seasonal and interannual variability of cloud cover and atmospheric constituents (aerosol loading, water vapor and ozone content) over the Amazon basin, with focus on both climate analysis and remote sensing implications. We take the advantage of new atmosphere daily products at 1 km resolution derived from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data. An intercomparison of Aerosol Robotic Network (AERONET) and MAIAC aerosol optical depth (AOD) and columnar water vapor (CWV) showed quantitative information with a correlation coefficient higher than 0.81. Our results show distinct regional patterns of cloud cover across the Amazon basin: northwestern region presets a persistent cloud cover (> 80%) throughout the year, while low cloud cover (0-20%) occurs in the southern Amazon during the dry season. The cloud-free period in the southern Amazon is followed by an increase in the atmospheric burden due to fire emissions. Our results reveal that AOD records are changing in terms of area and intensity. During the 2005 and 2010 droughts, the positive AOD anomalies (δ > 0.1) occurred over 39.03% (240.3 million ha) and 27.14% (165.99 million ha) of total basin in the SON season, respectively. In contrast, the recent 2015 drought occurred towards the end of year (October through December) and these anomalies were observed over 23.72% (145 million ha) affecting areas in the central and eastern Amazon unlike previous droughts. The water vapor presents high concentration values (4.0-5.0 g/sq.cm) in the wet season (DJF), while we observed a strong spatial gradient from northwestern to southeastern of the basin during the dry season. In addition, we also found a positive trend of water vapor content ( ∼0.3 g/sq.cm) between 2000 and 2015. The total ozone typically varies between 220 and 270 DU, and it has a seasonal change of ∼25-35 DU from wet season to dry season caused by large emissions of ozone precursors and long-range transport. Finally, while this study contributes to climatological analysis of atmospheric constituents, the remote sensing users can also understand the regional constraints caused by atmospheric attenuation, such as high aerosol loading and cloud obstacles for surface observations.

ozone↗
NASA NTRS2020

How Long Is Too Long? Variogram Analysis of AERONET Data to Aid Aerosol Validation and Intercomparison Studies

Geophysical data sets derived from satellite sensors, ground/airborne instrumentation, and computational models are often compared against each other. A common example is the validation of satellite aerosol optical depth (AOD) retrievals against measurements from Aerosol Robotic Network (AERONET) Sun photometers. Spatiotemporal mismatch between data set sampling means that uncaptured variation in the underlying geophysical field introduces apparent disagreement into such comparisons, known as representation or collocation matchup uncertainty. This study uses variogram analysis of AERONET data to estimate temporal mismatch uncertainties and decorrelation time scales for the global AERONET record. As well as total AOD, the fine‐ and coarse‐mode AODs, Ångström Exponent (AE), and fine‐mode fraction (FMF) of AOD are analyzed. Globally, a time difference of 30 min typically induces from 0.011–0.035 variation in AOD. For total, fine, and coarse AODs the typical time to decorrelation is around 2–10 days. For AE and FMF it is 3–33 days; that is, aerosol systems often persist significantly longer than individual events in them. Biomass burning regions tend to show the largest and fastest subdaily AOD variability and also longest times to decorrelation. Some sites show significant season‐to‐season variations in behavior. These results can be used to inform site‐specific time collocation thresholds for aerosol validation analyses and account for temporal variation when estimating data set uncertainty. They also have implications for comparisons between different satellite products or models, data aggregation, and time series analyses. Results are provided on a site‐by‐site basis to facilitate use by other researchers.

satellite↗
NASA NTRS2012

Variability of Black Carbon Deposition to the East Antarctic Plateau, 1800-2000 AD

Refractory black carbon aerosols (rBC) from biomass burning and fossil fuel combustion are deposited to the Antarctic ice sheet and preserve a history of emissions and long-range transport from low- and mid-latitudes. Antarctic ice core rBC records may thus provide information with respect to past combustion aerosol emissions and atmospheric circulation. Here, we present six East Antarctic ice core records of rBC concentrations and fluxes covering the last two centuries with approximately annual resolution (cal. yr. 1800 to 2000). The ice cores were drilled in disparate regions of the high East Antarctic ice sheet, at different elevations and net snow accumulation rates. Annual rBC concentrations were log-normally distributed and geometric means of annual concentrations ranged from 0.10 to 0.18 m cro-g/kg. Average rBC fluxes were determined over the time periods 1800 to 2000 and 1963 to 2000 and ranged from 3.4 to 15.5 m /a and 3.6 to 21.8 micro-g/sq m/a, respectively. Geometric mean concentrations spanning 1800 to 2000 increased linearly with elevation at a rate of 0.025 micro-g/kg/500 m. Spectral analysis of the records revealed significant decadal-scale variability, which at several sites was comparable to decadal ENSO variability.

Bisiaux, M. M.↗
NASA NTRS2020

Interannual Variability and Trends of Combustion Aerosol and Dust in Major Continental Outflows Revealed by MODIS Retrievals and CAM5 Simulations During 2003-2017

Emissions and long-range transport of mineral dust and combustion-related aerosol from burning fossil fuels and biomass vary from year to year, driven by the evolution of the economy and changes in meteorological conditions and environmental regulations. This study offers both satellite and model perspectives of interannual variability and possible trend of combustion aerosol and dust in major continental outflow regions over the past 15 years (2003-2017). The decade-long record of aerosol optical depth (AOD, denoted as t), separately for combustion aerosol (τ(sub c)) and dust (τ(sub d)), over global oceans is derived from the Collection 6 aerosol products of the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard both Terra and Aqua. These MODIS/Aqua datasets, complemented by aerosol source-tagged simulations using the Community Atmospheric Model Version 5 (CAM5), are then analyzed to understand the interannual variability and potential trend of τ(sub c) and τ(sub d) in the major continental outflows. Both MODIS and CAM5 consistently yield a similar decreasing trend of -0.017 to - 0.020 decade(exp -1) for τ(sub c) over the North Atlantic Ocean and the Mediterranean Sea that is attributable to reduced emissions from North America and Europe, respectively. On the contrary, both MODIS and CAM5 display an increasing trend of +0.017 to +0.036 decade(exp -1) for τ(sub c) over the tropical Indian Ocean, the Bay of Bengal, and the Arabian Sea, which reflects the influence of increased anthropogenic emissions from South Asia and Middle East in the last two decades. Over the northwestern Pacific Ocean that is often affected by East Asian emissions of pollution and dust, the MODIS retrievals show a decreasing trend of - 0.021 decade(exp -1) for τ(sub c) and -0.012 decade(exp -1) for τ(sub d), which is however not reproduced by the CAM5 model. In other outflow regions strongly influenced by biomass burning smoke or dust, both MODIS retrievals and CAM5 simulations show no statistically significant trends; and the MODIS observed interannual variability is usually larger than that of the CAM5 simulation.

Hongbin Yu↗
NASA NTRS2022

Emission Factors and Evolution of SO2 Measured From Biomass Burning in Wildfires and Agricultural Fires

Fires emit sufficient sulfur to affect local and regional air quality and climate. This study analyzes SO2 emission factors and variability in smoke plumes from US wildfires and agricultural fires, as well as their relationship to sulfate and hydroxymethanesulfonate (HMS) formation. Observed SO2 emission factors for various fuel types show good agreement with the latest reviews of biomass burning emission factors, producing an emission factor range of 0.47–1.2 g SO2 kg^(−1) C. These emission factors vary with geographic location in a way that suggests that deposition of coal burning emissions and application of sulfur-containing fertilizers likely play a role in the larger observed values, which are primarily associated with agricultural burning. A 0-D box model generally reproduces the observed trends of SO2 and total sulfate (inorganic + organic) in aging wildfire plumes. In many cases, modeled HMS is consistent with the observed organosulfur concentrations. However, a comparison of observed organosulfur and modeled HMS suggests that multiple organosulfur compounds are likely responsible for the observations but that the chemistry of these compounds yields similar production and loss rates as that of HMS, resulting in good agreement with the modeled results. We provide suggestions for constraining the organosulfur compounds observed during these flights, and we show that the chemistry of HMS can allow organosulfur to act as an S(IV) reservoir under conditions of pH > 6 and liquid water content >10^(−7) g sm^(−3). This can facilitate long-range transport of sulfur emissions, resulting in increased SO2 and eventually sulfate in transported smoke.

Sulfur↗
NASA NTRS2002

Dust, Pollution, and Biomass Burning Aerosols in Asian Pacific: A Column Surface/Satellite Perspective

Many recent field experiments are designed to study the compelling variability in spatial and temporal scale of both pollution-derived and naturally occurring aerosols, which often exist in high concentrations over eastern/southeastern Asia and along the rim of the western Pacific. For example, the phase-I of ACE-Asia was conducted from March-May 2001 in the vicinity of the Gobi desert, East Coast of China, Yellow Sea, Korea, and Japan, along the pathway of Kosa (severe events that blanket East Asia with yellow desert dust, peaked in the Spring season). Asian dust typically originates in desert areas far from polluted urban regions. During transport, dust layers can interact with anthropogenic sulfate and soot aerosols from heavily polluted urban areas. Springtime is also the peak season for biomass burning in southeastern Asia. Added to the complex effects of clouds and natural marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from the source. Thus, understanding the unique temporal and spatial variations of Asian aerosols is of special importance in regional-to-global climate issues such as radiative forcing, the hydrological cycle, and primary biological productivity in the mid-Pacific Ocean. During ACE-Asia we have measured continuously aerosol physical/optical/radiative properties, column precipitable water amount, and surface reflectivity over homogeneous areas from surface. The inclusion of flux measurements permits the determination of aerosol radiative flux in addition to measurements of loading and optical depth. At the time of the Terra/MODIS (Moderate Resolution Imaging Spectroradiometer), SeaWiFS (Sea-viewing Wide Field-of-view Sensor), TOMS (Total Ozone Mapping Spectrometer) and other satellite overpasses, these ground-based observations can provide valuable data to compare with satellite retrievals over land. A column satellite-surface perspective of Asian aerosols will be presented and will discuss their implications in regional-to-global effects on climate, fresh water redistribution, and health issues. (to be presented in Hawaii, April 28 - May 3, and Beijing, China, May 6 - 10, 2002)

Tsay, Si-Chee↗
NASA NTRS2020

Spatial validation reveals poor predictive performance of large-scale ecological mapping models

Mapping aboveground forest biomass is central for assessing the global carbon balance. However, current large-scale maps show strong disparities, despite good validation statistics of their underlying models. Here, we attribute this contradiction to a flaw in the validation methods, which ignore spatial autocorrelation (SAC) in data, leading to overoptimistic assessment of model predictive power. To illustrate this issue, we reproduce the approach of large-scale mapping studies using a massive forest inventory dataset of 11.8 million trees in central Africa to train and validate a random forest model based on multispectral and environmental variables. A standard nonspatial validation method suggests that the model predicts more than half of the forest biomass variation, while spatial validation methods accounting for SAC reveal quasi-null predictive power. This study underscores how a common practice in big data mapping studies shows an apparent high predictive power, even when predictors have poor relationships with the ecological variable of interest, thus possibly leading to erroneous maps and interpretations.

biomass↗
NASA NTRS2002

Tropospheric Ozone during the TRACE-P Mission: Comparison between TOMS Satellite Retrievals and Aircraft Lidar Data, March 2001

Over the past several years, we have developed two new tropospheric ozone retrievals from the TOMS (Total Ozone Mapping Spectrometer) satellite instrument that are of sufficient resolution to follow pollution episodes. The modified-residual technique uses v. 7 TOMS total ozone and is applicable to tropical regimes in which the wave-one pattern in total ozone is observed. The TOMS-direct method ('TDOT' = TOMS Direct Ozone in the Troposphere) represents a new algorithm that uses TOMS radiances directly to extract tropospheric ozone in regions of constant stratospheric ozone. It is not geographically restricted, using meteorological regimes as the basis for classifying TOMS radiances and for selecting appropriate comparison data. TDOT is useful where tropospheric ozone displays high mixing ratios and variability characteristic of pollution. Some of these episodes were observed downwind of Asian biomass burning during the TRACE-P (Transport and Atmospheric Chemical Evolution-Pacific) field experiment in March 2001. This paper features comparisons among TDOT tropospheric ozone column depth, integrated uv-DIAL measurements made from NASA's DC-8, and ozonesonde data.

Frolov, A. D.↗
NASA NTRS2009

Estimating Volume, Biomass, and Carbon in Hedmark County, Norway Using a Profiling LiDAR

A profiling airborne LiDAR is used to estimate the forest resources of Hedmark County, Norway, a 27390 square kilometer area in southeastern Norway on the Swedish border. One hundred five profiling flight lines totaling 9166 km were flown over the entire county; east-west. The lines, spaced 3 km apart north-south, duplicate the systematic pattern of the Norwegian Forest Inventory (NFI) ground plot arrangement, enabling the profiler to transit 1290 circular, 250 square meter fixed-area NFI ground plots while collecting the systematic LiDAR sample. Seven hundred sixty-three plots of the 1290 plots were overflown within 17.8 m of plot center. Laser measurements of canopy height and crown density are extracted along fixed-length, 17.8 m segments closest to the center of the ground plot and related to basal area, timber volume and above- and belowground dry biomass. Linear, nonstratified equations that estimate ground-measured total aboveground dry biomass report an R(sup 2) = 0.63, with an regression RMSE = 35.2 t/ha. Nonstratified model results for the other biomass components, volume, and basal area are similar, with R(sup 2) values for all models ranging from 0.58 (belowground biomass, RMSE = 8.6 t/ha) to 0.63. Consistently, the most useful single profiling LiDAR variable is quadratic mean canopy height, h (sup bar)(sub qa). Two-variable models typically include h (sup bar)(sub qa) or mean canopy height, h(sup bar)(sub a), with a canopy density or a canopy height standard deviation measure. Stratification by productivity class did not improve the nonstratified models, nor did stratification by pine/spruce/hardwood. County-wide profiling LiDAR estimates are reported, by land cover type, and compared to NFI estimates.

Nelson, Ross↗
NASA NTRS2018

Remote Sensing of CDOM, CDOM Spectral Slope, and Dissolved Organic Carbon in the Global Ocean

A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromophoric Dissolved Organic Matter (CDOM) absorption coefficients from 245–715 nm, CDOM spectral slopes in eight visible and ultraviolet wavebands, dissolved and particulate organic carbon (DOC and POC, respectively), and inherent optical, physical, and biogeochemical properties. From field optical and radiometric data and satellite measurements, several semi-analytical, empirical, and machine learning algorithms for retrieving global DOC, CDOM, and CDOM slope were developed, optimized for global retrieval, and validated. Global climatologies of satellite-retrieved CDOM absorption coefficient and spectral slope based on the most robust of these algorithms lag seasonal patterns of phytoplankton biomass belying Case 1 assumptions, and track terrestrial runoff on ocean basin scales. Variability in satellite retrievals of CDOM absorption and spectral slope anomalies are tightly coupled to changes in atmospheric and oceanographic conditions associated with El Niño Southern Oscillation (ENSO), strongly covary with the multivariate ENSO index in a large region of the tropical Pacific, and provide insights into the potential evolution and feedbacks related to sea surface dissolved carbon in a warming climate. Further validation of the DOC algorithm developed here is warranted to better characterize its limitations, particularly in mid-ocean gyres and the southern oceans.

Dissolved organic carbon↗
NASA NTRS2017

Biomass Retrieval from L-Band Polarimetric UAVSAR Backscatter and PRISM Stereo Imagery

The forest above-ground biomass (AGB) and spatial distribution of vegetation elements have profound effects on the productivity and biodiversity of terrestrial ecosystems. In this paper, we evaluated biomass estimation from L-band Synthetic Aperture Radar (SAR) data acquired by National Aeronautics and Space Administration (NASA) Uninhabited Aerial Vehicle SAR (UAVSAR) and the improvement of accuracy by adding canopy height information derived from stereo imagery acquired by Japan Aerospace Exploration Agency (JAXA) Panchromatic Remote Sensing Instrument for Stereo Mapping (PRISM) on-board the Advanced Land Observing Satellite (ALOS). Various models for prediction of forest biomass from UAVSAR data were investigated at pixel sizes of 1/4 ha (50 m x 50 m) and 1 ha. The variance inflation factor (VIF) was calculated for each of the explanatory variables in multivariable regression models to assess the multi-collinearity between explanatory variables. In addition, the t-and p-values were used to interpret the significance of the coefficients of each explanatory variables. The R(exp. 2), Root Mean Square Error (RMSE), bias and Akaike information criterion (AIC), and leave-one-out cross-validation (LOOCV) and bootstrapping were used to validate models. At 1/4-ha scale, the R(exp. 2) and RMSE of biomass estimation from a model using a single track of polarimetric UAVSAR data were 0.59 and 52.08 Mg/ha. With canopy height from PRISM as additional independent variable, R(exp. 2) increased to 0.76 and RMSE decreased to 39.74 Mg/ha (28.24%). At 1-ha scale, the RMSE of biomass estimation based on UAVSAR data of a single track was 39.42 Mg/ha with a R(exp. 2) of 0.77. With the canopy height from PRISM, R(exp. 2) increased to 0.86 and RMSE decreased to 29.47 Mg/ha (20.18%). The models using UAVSAR data alone underestimated biomass at levels above approximately 150 Mg/ha showing the saturation phenomenon. Adding canopy height from PRISM stereo imagery significantly improved the biomass estimation and elevated the saturation level in estimating biomass. Combined use of UAVSAR data acquired from opposite directions (odd and even tracks) slightly improved the biomass estimation.Combined use of UAVSAR data acquired from opposite directions (odd and even tracks) slightly improved the biomass estimation at 1/4-ha scale, R(exp. 2) increased from 0.59 to 0.66 and RMSE reduced from 52.08 to 48.57 Mg/ha. Averaging multiple acquisitions of UAVSAR data from the same look azimuth direction did not improve biomass estimation. A biomass map derived from NASA's LVIS (Laser Vegetation Imaging System) wave-form data was used as a reference for evaluation of the biomass maps from these models. The study has also shown that the errors decreased when deciduous, evergreen, and mixed forests were modeled separately but the improvement was not significant

Zhang, Zhiyu↗
NASA NTRS1992

Seasonal Distribution of African Savanna Fires

Savannas consist of a continuous layer of grass interspersed with scattered trees or shrubs, and cover approx. 10 million square kilometers of tropical Africa. African savanna fires, almost all resulting from human activities, may produce as much as a third of the total global emissions from biomass burning. Little is known, however, about the frequency and location of these fires, and the area burned each year. Emissions from African savanna burning are known to be transported over the mid-Atlantic, south Pacific and Indian oceans; but to study fully the transport of regional savanna burning and the seasonality of the atmospheric circulation must be considered simultaneously. Here we describe the temporal and spatial distribution of savanna fires over the entire African continent, as determined from night-time satellite imagery. We find that, contrary to expectations, most fires are left to burn uncontrolled, so that there is no strong diurnal cycle in the fire frequency. The knowledge gained from this study regarding the distribution and variability of fires will aid monitoring of the climatically important trace gases emitted from burning biomass.

Cahoon, Donald R.↗
NASA NTRS1991

Applications of the EOS SAR to monitoring global change

The SAR employed by NASA's Earth Observing System (EOS) is a multifrequency multipolarization radar which can conduct global monitoring of geophysical and biophysical parameters. The present discussion of the EOS SAR's role in global monitoring emphasizes geophysical product variables applicable to global hydrologic, biogeochemical, and energy cycle models. EOS SAR products encompass biomass, wetland areas, and phenologic and environmental states, in the field of ecosystem dynamics; soil moisture, snow moisture and extent, and glacier and ice sheet extent and velocity, in hydrologic cycle studies; surface-wave fields and sea ice properties, in ocean/atmosphere circulation; and the topography, erosion, and land forms of the solid earth.

Schier, Marguerite↗
NASA NTRS2000

BOREAS RSS-8 BIOME-BGC SSA Simulation of Annual Water and Carbon Fluxes

The BOREAS RSS-8 team performed research to evaluate the effect of seasonal weather and landcover heterogeneity on boreal forest regional water and carbon fluxes using a process-level ecosystem model, BIOME-BGC, coupled with remote sensing-derived parameter maps of key state variables. This data set contains derived maps of landcover type and crown and stem biomass as model inputs to determine annual evapotranspiration, gross primary production, autotrophic respiration, and net primary productivity within the BOREAS SSA-MSA, at a 30-m spatial resolution. Model runs were conducted over a 3-year period from 1994-1996; images are provided for each of those years. The data are stored in binary image format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2019

Satellite-Detected Ocean Ecosystem Response to Volcanic Eruption in the Subarctic Northeast Pacific Ocean

Volcanic eruptions in the Aleutian archipelago during the summer of 2008 deposited large quantities of iron-laden ash to the Subarctic North Pacific Ocean. The surface ocean ecosystem response has been previously characterized using limited in situ and autonomous field measurements and numerical modeling, but basin-scale satellite remote sensing has been limited to a simple description of chlorophyll variability. Here, we show that the ecosystem response is a complex combination of phytoplankton biomass and physiology that can be described with satellite ocean color diagnostics such as the chlorophyll to carbon biomass ratio (Chl:Cphyto) and chlorophyll fluorescence yield. Together, these quantities outline a more complete picture of ecological response spanning unique signals of iron stress (and relief from), photo acclimation, changes in phytoplankton growth rate, increases in biomass, and timescales of decay for these processes.

Ocean Ecosystem↗