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

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Shuttle radar images for geologic mapping in tropical rainforest

Images of forested low-relief terrain in the Amazon basin of Brazil, obtained with airborne imaging radar in the Radambrasil project, are compared with SIR-A and Landsat MSS band-7 images to evaluate their usefulness in constructing geologic maps. Sample images are shown, and it is found that Radam images are more useful in distinguishing drainage patterns and mapping the region distribution of stream channels due to their relatively low depression angles (less than 25 deg as opposed to 43-37 deg for SIR-A), but that SIR-A images give superior discrimination of alluvial forest, where trees stand in water, due to the higher reflectivity of branches and water at the SIR-A wavelength (23.5 cm as opposed to 3 cm for Radam). Alluvial forest is also identified by Landsat band 7.

Ford, J. P.↗
NASA NTRS1991

Polarimetric radar measurements of a tropical rainforest

In Mar. 1990, the NASA/JPL DC-8 Airborne Synthetic Aperture Radar (AIRSAR) was flown over an area in northern Belize and the surrounding areas of Guatamala and Mexico. We have extracted the three-frequency polarimetric signatures of a variety of natural areas and have found that many appear to have a unique radar signature, if all polarizations and frequencies are examined.

Durden, S.↗
NASA NTRS1997

The Potential for Collocated AGLP and ERBE data for Fire, Smoke, and Radiation Budget Studies

One month of the Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) Land Pathfinder (AGLP) data from September 1985 are used to examine the spatial and temporal distribution of fires over four major ecosystems in South America. The Earth Radiation Budget Experiment (ERBE) scanner data are used to examine the top of atmosphere (TOA) shortwave and longwave fluxes over smoke generated from biomass burn- ing. The relationship between the AGLP-derived Normalized Difference Vegetation Index (NDVI) and the ERBE-estimated clear sky albedos are also examined as a function of the four ecosystems. This study shows that the grassland areas in South America have the highest number of fires for September 1985, and their corresponding NDVI values are smaller than the tropical rainforest region where the number of fires were comparatively small. Clear sky statistics accumulated during the days when smoke was not present show that clear sky albedos derived from ERBE are higher for grassland areas when compared to the tropical rainforest. The results show that the AGLP can be used to determine the spatial and temporal distribution of fires along with vegetation characteristics, while ERBE data can provide necessary information on broadband albedos and regional top of atmosphere radiative impacts of biomass burning aerosols. Since the AGLP data are available from 1981 to the present day, several climate-related issues can be addressed.

Christropher, S. A.↗
NASA NTRS1997

The Potential for Collocated AGLP and ERBE Data for Fire, Smoke, and Radiation Budget Studies

One month of the Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) Land Pathfinder (AGLP) data from September 1985 are used to examine the spatial and temporal distribution of fires over four major ecosystems in South America. The Earth Radiation Budget Experiment (ERBE) scanner data are used to examine the top of atmosphere (TOA) shortwave and longwave fluxes over smoke generated from biomass burning. The relationship between the AGLP-derived Normalized Difference Vegetation Index (NDVI) and the ERBE-estimated clear sky albedos are also examined as a function of the four ecosystems. This study shows that the grassland areas in South America have the highest number of fires for September 1985. and their corresponding NDVI values are smaller than the tropical rainforest region where the number of fires were comparatively small. Clear sky statistics accumulated during the days when smoke was not present show that clear sky albedos derived from ERBE are higher for grassland areas when compared to the tropical rainforest. The results show that the AGLP can be used to determine the spatial and temporal distribution of fires along with vegetation characteristics, while ERBE data can provide necessary information on broadband albedos and regional top of atmosphere radiative impacts of biomass burning aerosols. Since the AGLP data are available from 1981 to the present day, several climate-related issues can be addressed,

Christopher, S. A.↗
NASA NTRS1997

The Potential for Collocated AGLP and ERBE Data for Fire, Smoke, and Radiation Budget Studies

One month of the Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) Land Pathfinder (AGLP) data from September 1985 are used to examine the spatial and temporal distribution of fires over four major ecosystems in South America. The Earth Radiation Budget Experiment (ERBE) scanner data are used to examine the top of atmosphere (TOA) shortwave and longwave fluxes over smoke generated from biomass burning. The relationship between the AGLP-derived Normalized Difference Vegetation Index (NDVI) and the ERBE-estimated clear sky albedos are also examined as a function of the four ecosystems. This study shows that the grassland areas in South America have the highest number of tires for September 1985, and their corresponding NDVI values are smaller than the tropical rainforest region where the number of fires were comparatively small. Clear sky statistics accumulated during the days when smoke was not present show that clear sky albedos derived from ERBE are higher for grassland areas when compared to the tropical rainforest. The results show that the AGLP can be used to determine the spatial and temporal distribution of fires along with vegetation characteristics, while ERBE data can provide necessary information on broadband albedos and regional top of atmosphere radiative impacts of biomass burning aerosols. Since the AGLP data are available from 1981 to the present day, several climate-related issues can be addressed.

Christopher, S. A.↗
NASA NTRS2019

Widespread Increase of Boreal Summer Dry Season Length Over the Congo Rainforest

Dry season length strongly influences tropical rainforest vegetation and is largely determined by precipitation patterns. Over the Amazon, the dry season length has increased since 1979 and severe short-term droughts have occurred. However, similar changes have not been investigated for the world’s second largest rainforest, the Congo Basin, where long-term drying and large-scale declines in forest greenness and canopy water content were reported. Here we present observational evidence for widespread increases in the boreal summer (June–August) dry season length over the Congo Basin since the 1980s, from both hydrological and ecological perspectives. We analyzed both dry season onset and dry season end via multiple independent precipitation and satellite derived vegetation datasets for the period 1979–2015. The dry season length increased by 6.4–10.4 days per decade in the period 1988–2013, primarily attributed to an earlier dry season onset and a delayed dry season end. The earlier dry season onset was caused by long-term droughts due to decreased rainfall in the pre-dry season (April–June). The delayed dry season end resulted from insufficiently replenished soil moisture, which postpones the start of the next wet season and hinders vegetation regrowth. If such changes continue, the enhanced water stress in a warming climate may affect the carbon cycle and alter the composition and structure of evergreen rainforest.

Congo rainforest growing season NDVI SIF↗
NASA NTRS2018

Understanding Climate-Vegetation Interactions in Global Rainforests Through a GP-Tree Analysis

The tropical rainforests are the largest reserves of terrestrial carbon and, therefore, the future of these rainforests is a question that is of immense importance in the geoscience research community. With the recent severe Amazonian droughts in 2005 and 2010 and on-going drought in the Congo region for more than two decades, there is growing concern that these forests could succumb to precipitation reduction, causing extensive carbon release and feedback to the carbon cycle. However, there is no single ecosystem model that quantifies the relationship between vegetation health in these rainforests and climatic factors. Small scale studies have used statistical correlation measure and simple linear regression to model climate-vegetation interactions, but suffer from the lack of comprehensive data representation as well as simplistic assumptions about dependency of the target on the covariates. In this paper we use genetic programming (GP) based symbolic regression for discovering equations that govern the vegetation climate dynamics in the rainforests. Expecting micro-regions within the rainforests to have unique characteristics compared to the overall general characteristics, we use a modified regression-tree based hierarchical partitioning of the space to build individual models for each partition. The discovery of these equations reveal very interesting characteristics about the Amazon and the Congo rainforests. Our method GP-tree shows that the rainforests exhibit tremendous resiliency in the face of extreme climatic events by adapting to changing conditions.

genetic programming↗
NASA NTRS2002

Evidence of an Intrinsic Intraseasonal Oscillation over Tropical South America During Austral Summer

The intraseasonal variation (ISV) in the 30-60 day band, also known as Madden-Julian oscillation (MJO), has been studied for decades. Madden and Julian showed that the oscillation originated from the western Indian Ocean, propagated eastward, got enhanced over the maritime continent and weakened after passing over the dateline. Composite studies showed evidences of a signal in upper and lower level zonal wind propagating around the globe during an oscillation. Theoretical studies pointed out that the interaction with the warm ocean surface and the coupling with the convective and radiative processes in the atmosphere could manifest the oscillation, which propagates eastward via mutual feedbacks between the wave motions and the cumulus heating. Over tropical South America, no independent 30-60 day oscillation has been reported so far, despite that Amazon is the most distinct tropical convection center over the western hemisphere and the fluxes from its surface of tropical rainforests are close to that from the warm tropical ocean. Liebmann et al. showed a distinct spectral peak of 40-50 day oscillation in outgoing longwave radiation (OLR) over tropical South America and considered that was manifested by the MJO propagation. Nogues-Paegle et al. (2000) focused on a dipole pattern of the OLR anomaly with centers of action over the South Atlantic Convergence Zone (SACZ) and the subtropical plain. They used the regional 10-90 day filtered data and demonstrated this pattern could be represented by the fifth mode of the rotated empirical orthogonal function. Its principal component was further analyzed using the singular spectrum analysis. Their result showed two oscillatory modes with periods of 36-40 days and 22-28 days, of which the former was related to the MJO influence and the latter linked to the remote forcing over southwest of Australia, which produced a wave train propagating southeastward, rounding the southern tip of South America and returning back toward the northeast. The 22-28 day mode has distinct impact on SACZ, responsible for the regional seesaw pattern of alternating dry and wet conditions. In this study we will focus on the 30-60-day spectral band and investigate whether the independent oscillation source over tropical South America is existed. First, we will show the seasonal dependence of the tropical South American ISV in Section 3. Then, the leading principal modes of 30-60 day bandpass filtered 850-hPa velocity potential (VP850) will be computed to distinguish the stationary ISV over tropical South America (SISA) from the propagating MJO in the austral summertime in Section 4. The importance of SISA in representing the regional ISV over South America will be discussed. In Section 5, we will demonstrate the mass oscillation regime of SISA, which is well separated from that of MJO by the Andes, and the convective coupling with rainfall. The dynamical response of SISA and the impact on the South American summer monsoon (SASM) will be presented. Finally, we will give the concluding remarks.

Zhou, Jiayu↗
NASA NTRS1996

Mapping Deforestation and Land Use in Amazon Rainforest Using SAR-C Imagery

Land use changes and deforestation in tropical rainforests are among the major factors affecting the overall function of the global environment. To routinely assess the spatial extend and temporal dynamics of these changes has become an important challenge in several scientific disciplines such as climate and environmental studies. In this paper, the feasibility of using polarimetric spaceborne SAR data in mapping land cover types in the Amazon is studied.

SAR-C Imagery Amazon Rainforest Land Use Deforesta↗
NASA NTRS2013

Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals

Uncertainties in the retrievals of microwaveland-surface emissivities are quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including the Special Sensor Microwave Imager, the Tropical Rainfall Measuring Mission Microwave Imager, and the Advanced Microwave Scanning Radiometer for Earth Observing System, are studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land-surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors inthe retrievals. Generally, these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1%-4% (3-12 K) over desert and 1%-7% (3-20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5%-2% (2-6 K). In particular, at 85.5/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are most likely caused by rain/cloud contamination, which can lead to random errors up to 10-17 K under the most severe conditions.

Land-Surface↗
NASA NTRS1991

Approaches to vegetation mapping and ecophysiological hypothesis testing using combined information from TIMS, AVIRIS, and AIRSAR

The Tropical Rainforest Ecology Experiment (TREE) had two primary objectives: (1) to design a method for mapping vegetation in tropical regions using remote sensing and determine whether the result improves on available vegetation maps; and (2) to test a specific hypothesis on plant/water relations. Both objectives were thought achievable with the combined information from the Thermal Infrared Multispectral Scanner (TIMS), Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and Airborne Synthetic Aperture Radar (AIRSAR). Implicitly, two additional objectives were: (1) to ascertain that the range within each variable potentially measurable with the three instruments is large enough in the site, relative to the sensitivity of the instruments, so that differences between ecological groups may be detectable; and (2) to determine the ability of the three systems to quantify different variables and sensitivities. We found that the ranges in values of foliar nitrogen concentration, water availability, stand structure and species composition, and plant/water relations were large, even within the upland broadleaf vegetation type. The range was larger when other vegetation types were considered. Unfortunately, cloud cover and navigation errors compromised the utility of the TIMS and AVIRIS data. Nevertheless, the AIRSAR data alone appear to have improved on the available vegetation map for the study area. An example from an area converted to a farm is given to demonstrate how the combined information from AIRSAR, TIMS, and AVIRIS can uniquely identify distinct classes of land use. The example alludes to the potential utility of the three instruments for identifying vegetation at an ecological scale finer than vegetation types.

Oren, R.↗
NASA NTRS1984

The Amazon and climate

The climatologies of cloudiness and precipitation for the Amazon, are reviewed and the physical causes of some of the observed features and those which are not well known are explained. The atmospheric circulation over the Amazon is discussed on the large scale tropical circulations forced by deep diabatic heating sources. Weather deforestation which leads to a reduction in evapotranspiration into the atmosphere, and a reduction in precipitation and its implicated for the gobal climate is discussed. It is indicated that a large scale clearing of tropical rainforests there would be a reduction in rainfall which would have global effects on climate and weather both in the tropical and extratropical regions.

Nobre, C. A.↗
NASA NTRS2016

Regional Atmospheric CO2 Inversion Reveals Seasonal and Geographic Differences in Amazon Net Biome Exchange

Understanding tropical rainforest carbon exchange and its response to heat and drought is critical for quantifying the effects of climate change on tropical ecosystems, including global climate carbon feedbacks. Of particular importance for the global carbon budget is net biome exchange of CO2 with the atmosphere (NBE), which represents nonfire carbon fluxes into and out of biomass and soils. Subannual and sub-Basin Amazon NBE estimates have relied heavily on process-based biosphere models, despite lack of model agreement with plot-scale observations. We present a new analysis of airborne measurements that reveals monthly, regional-scale (Approx.1-8 x 10(exp -6) km2) NBE variations. We develop a regional atmospheric CO2 inversion that provides the first analysis of geographic and temporal variability in Amazon biosphere-atmosphere carbon exchange and that is minimally influenced by biosphere model-based first guesses of seasonal and annual mean fluxes. We find little evidence for a clear seasonal cycle in Amazon NBE but do find NBE sensitivity to aberrations from long-term mean climate. In particular, we observe increased NBE (more carbon emitted to the atmosphere) associated with heat and drought in 2010, and correlations between wet season NBE and precipitation (negative correlation) and temperature (positive correlation). In the eastern Amazon, pulses of increased NBE persisted through 2011, suggesting legacy effects of 2010 heat and drought. We also identify regional differences in postdrought NBE that appear related to long-term water availability. We examine satellite proxies and find evidence for higher gross primary productivity (GPP) during a pulse of increased carbon uptake in 2011, and lower GPP during a period of increased NBE in the 2010 dry season drought, but links between GPP and NBE changes are not conclusive. These results provide novel evidence of NBE sensitivity to short-term temperature and moisture extremes in the Amazon, where monthly and sub-Basin estimates have not been previously available.

precipitation↗
NASA NTRS1998

Effects of 1997-1998 El Nino on Tropospheric Ozone and Water Vapor

This paper analyzes the impact of the 1997-1998 El Nino on tropospheric column ozone and tropospheric water vapor derived respectively from the Total Ozone Mapping Spectrometer (TOMS) on Earth Probe and the Microwave Limb Scanning instrument on the Upper Atmosphere Research Satellite. The 1997-1998 El Nino, characterized by an anomalous increase in sea-surface temperature (SST) across the eastern and central tropical Pacific Ocean, is one of the strongest El Nino Southern Oscillation (ENSO) events of the century, comparable in magnitude to the 1982-1983 episode. The major impact of the SST change has been the shift in the convection pattern from the western to the eastern Pacific affecting the response of rain-producing cumulonimbus. As a result, there has been a significant increase in rainfall over the eastern Pacific and a decrease over the western Pacific and Indonesia. The dryness in the Indonesian region has contributed to large-scale burning by uncontrolled wildfires in the tropical rainforests of Sumatra and Borneo. Our study shows that tropospheric column ozone decreased by 4-8 Dobson units (DU) in the eastern Pacific and increased by about 10-20 DU in the western Pacific largely as a result of the eastward shift of the tropical convective activity as inferred from National Oceanic and Atmospheric Administration (NOAA) outgoing longwave radiation (OLR) data. The effect of this shift is also evident in the upper tropospheric water vapor mixing ratio which varies inversely as ozone (O3). These conclusions are qualitatively consistent with the changes in atmospheric circulation derived from zonal and vertical wind data obtained from the Goddard Earth Observing System data assimilation analyses. The changes in tropospheric column O3 during the course of the 1997-1998 El Nino appear to be caused by a combination of large-scale circulation processes associated with the shift in the tropical convection pattern and surface/boundary layer processes associated with forest fires in the Indonesian region.

Chandra, S.↗
NASA NTRS2012

Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased aerosol levels was observed during the dry season, with an inverse dependence of NDVI on aerosol optical thickness (AOT). NDVI observations processed with MAIAC showed highly reproducible and stable inter-annual patterns with little or no dependence on cloud cover, and no significant dependence on AOT (p less than 0.05). In addition to a better detection of cloudy pixels, MAIAC obtained about 20-80 percent more cloud free pixels, depending on season, a considerable amount for land analysis given the very high cloud cover (75-99 percent) observed at any given time in the area. We conclude that a new generation of atmospheric correction algorithms, such as MAIAC, can help to dramatically improve vegetation estimates over tropical rain forest, ultimately leading to reduced uncertainties in satellite-derived vegetation products globally.

tropical ecosystems↗
NASA NTRS1973

Forestry, geology and hydrological investigations from ERTS-1 imagery in two areas of Ecuador, South America

The author has identified the following significant results. In the Oriente area, well-drained forests containing commercially valuable hardwoods can be recognized confidently and delineated quickly on the ERTS imagery. In the tropical rainforest, ERTS can provide an abundance of inferential information about large scale geologic structures. ERTS imagery is better than normal aerial photography for recognizing linears. The imagery is particularly useful for updating maps of the distributary system of the Guagas River Basin and of any other river with a similarly rapid changing channel pattern.

Moreno, N. V.↗
NASA NTRS1991

Global biomass burning - Atmospheric, climatic, and biospheric implications

The present volume discusses the biomass burning (BMB) studies of the International Global Atmospheric Chemistry project, GEO satellite estimation of Amazonian BMB, remote sensing of BMB in West Africa with NOAA-AVHRR, an orbital view of the great Chinese fire of 1987, BMB's role in tropical rainforest reduction, CO and O3 measurements of BMB in the Amazon, effects of vegetation burning on the atmospheric chemistry of the Venezuelan savanna, an assessment of annually-burned biomass in Africa, and light hydrocarbon emissions from African savanna burnings. Also discussed are BMB in India, trace gas and particulate emissions from BMB in temperate ecosystems, ammonia and nitric acid emissions from wetlands and boreal forest fires, combustion emissions and satellite imagery of BMB, BMB in the perspective of the global carbon cycle, modeling trace-gas emissions from BMB, NO(x) emissions from BMB, and cloud-condensation nuclei from BMB.

Levine, Joel S.↗