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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Thermodynamics and Cloud Radiative Effect from the First Year of GoAmazon

Deforestation is an ongoing concern for the Amazon Rainforest of Brazil and associated changes to the land surface have been hypothesized to alter the climate in the region. A comprehensive set of meteorological observations at the surface and within the lower troposphere above Manacapuru, Brazil and data from the Modern Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) are used to evaluate the seasonal cycle of cloudiness, thermodynamics, and the radiation budget. While ample moisture is present in the Amazon Rainforest year round, the northward progression of the Hadley circulation during the dry season contributes to a drying of the middle troposphere and inhibits the formation of deep convection. This results in a reduction in cloudiness and precipitation as well as an increase in the height of the lifting condensation level, which is shown to have a negative correlation to the fraction of low clouds. Frequent cloudiness prevents solar radiation from reaching the surface and clouds are often reflective with high values of shortwave cloud radiative effect at the surface and top of the atmosphere. Cloud radiative effect is reduced during the dry season however the dry season surface shortwave cloud radiative effect is still double what is observed during the wet season in other tropical locations. Within the column, the impact of clouds on the radiation budget is more prevalent in the longwave part of the spectrum, with a net warming in the wet season.

Amazon Rainforest↗
NASA NTRS1992

Low-level nocturnal wind maximum over the Central Amazon Basin

A low-level nocturnal wind maximum is shown to exist over extensive and nearly undisturbed rainforest near the central Amazon city of Manaus. Meteorological data indicate the presence of this nocturnal wind maximum during both the wet and dry seasons of the Central Amazon Basin. Daytime wind speeds which are characteristically 3-7 m/s between 300 and 1000 m increase to 10-15 m/s shortly after sunset. The wind-speed maximum is reached in the early evening, with wind speeds remaining high until several hours after sunrise. The nocturnal wind maximum is closely linked to a strong low-level inversion formed by radiational cooling of the rainforest canopy. Surface and low-level pressure gradients between the undisturbed forest and the large Amazon river system and the city of Manaus are shown to be responsible for much of the nocturnal wind increase. The pressure gradients are interpreted as a function of the thermal differences between undisturbed forest and the river/city. The importance of both the frictional decoupling and the horizontal pressure gradient suggest that the nocturnal wind maximum does not occur uniformly over all Amazonia. Low-level winds are thought to be pervasive under clear skies and strong surface cooling and that, in many places (i.e., near rivers), local pressure gradients enhance the low-level nocturnal winds.

Greco, Steven↗
NASA NTRS1993

AVHRR-LAC estimates of forest area in Madagascar, 1990

Three AVHRR-LAC data sets acquired in September 1990 and January 1991 were used to map the forest resources of Madagascar. The island was partitioned into four strata to include: (1) the western hardwoods, (2) the central grasslands, (3) the eastern rainforest, and (4) spiny forest. Each stratum was classified separately using AVHRR-LAC data in conjunction with 1984-1988 Landsat-MSS photoproducts. The results of AVHRR classification indicate that approximately 11 percent of the island is covered by forest. Estimates of forest area, by stratum, are as follows: western hardwoods, 6697 sq km; central grasslands, 2830 sq km; eastern rainforest 34,167 sq km; and spiny forest, 17,224 sq km. The total forest area on the 587,041 sq km island is estimated to be 60,918 sq km. The AVHRR forest map was compared to a mid-1970s land cover map which was developed using Landsat-MSS photoproducts. The average class agreement between the mid 1970s ground reference map and the 1990 AVHRR-LAC map was 78.2 percent, the overall accuracy was 81.1 percent. Much of the per-pixel disagreement between the ground reference and AVHRR maps involved areas identified as forest in the 1970s and as nonforest in 1990.

Nelson, R.↗
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 NTRS2002

Rationalizing Burned Carbon with Carbon Monoxide Exported from South America

We present several estimates cross-checking the fluxes of carbon to the atmosphere from burning, comparing models that are based on simple land-surface parameterizations and atmospheric transport dynamics. Both estimates made by NASA Ames and USP modeling techniques are quite high compared to some detailed satellite/land-use studies of emissions. The flux of carbon liberated to the atmosphere via biomass burning is important for several reasons. This flux is a fundamental statistic for the parameterization of the large-scale flux of gases controlling the reactive greenhouse gases methane and ozone. Similarly, it is central to the estimation of the translocation of nitrogen and pyrodenitrification in the tropics. Thirdly, CO2 emitted from rainforest clearing contributes directly to carbon lost from the rainforest system as it contributes to greenhouse gas forcing. While CO2 from pasturage, agriculture, etc, is considered to be reabsorbed seasonally, and so "off budget" for the carbon cycle, it must also be accounted. CO2 anomalies related to daily weather and interannual climatic variation are strong enough to perturb our scientific perception of long-term carbon storage trends. We compare fluxes deduced from land-use statistics (originally, W.M. Hao) and from satellite hot pixels (A. Setzer) with atmospheric fluxes determined by the mesoscale/continental scale models RAMS and MM5, and point to some new work with highly resolved global models (the NASA Data Assimilation Office's GEOS4). Our simulations are tied to events, so that measured tracers like CO tie the models directly to the burning and meteorology of a specific period. We point out a particular sensitivity in estimates based on CO, and indicate how analysis of CO2 along with other biomass-burning tracers may lead to an improved multi-species estimator of carbon burned.

Chatfield, R.↗
NASA NTRS2012

Quantifying Uncertainties in Land Surface Microwave Emissivity Retrievals

Uncertainties in the retrievals of microwave land surface emissivities were quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including SSM/I, TMI and AMSR-E, were 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 in the 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 85.0/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are mostly likely caused by rain/cloud contamination, which can lead to random errors up to 10~17 K under the most severe conditions.

Tian, Yudong↗
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 NTRS2012

Net Primary Production of Terrestrial Ecosystems from 2000 to 2009

The CASA (Carnegie-Ames-Stanford) ecosystem model has been used to estimate monthly carbon fluxes in terrestrial ecosystems from 2000 to 2009, with global data inputs from NASA's Terra Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation cover mapping. Net primary production (NPP) flux for atmospheric carbon dioxide has varied slightly from year-to-year, but was predicted to have increased over short multi-year periods in the regions of the high-latitude Northern Hemisphere, South Asia, Central Africa, and the western Amazon since the year 2000. These CASA results for global NPP were found to be in contrast to other recently published modeling trends for terrestrial NPP with high sensitivity to regional drying patterns. Nonetheless, periodic declines in regional NPP were predicted by CASA for the southern and western Untied States, the southern Amazon, and southern and eastern Africa. NPP in tropical forest zones was examined in greater detail to discover lower annual production values than previously reported in many global models across the tropical rainforest zones, likely due to the enhanced detection of lower production ecosystems replacing primary rainforest.

Terrestiral ecosystems↗
NASA NTRSDate not supplied

Detecting Volcanic Co2 Emissions Hidden in Tropical Volcanic Forests Using Fixed-Wing sUAS

CO2 emissions are among the earliest indicators of subsurface state change and reactivation of volcanic systems and these deep signals reflect in faint diffuse emissions variations on volcanic flanks. Monitoring vast areas of rainforests covering tropical volcanoes is challenging, and space-borne sensors like OCO-2 are not sensitive enough. Fortunately, trees exposed to mild enhancements of CO2 may experience fertilization and build excess CO2 into excess biomass (Cawse-Nicholson, et al. 2018, Biogeosciences). They also process excess CO2 through photosynthesis, measurable by fluorescence (Bogue et al., 2019, Biogeosciences). Furthermore, spaceborne remote sensing instruments have demonstrated increasing NDVI months to years before eruptions, unexplained by other factors (e.g., Houlie et al. 2006, EPSL; Seiler et al. 2017, PLoS One). By providing a means to map large areas of above-canopy CO2 variations over tropical rainforest on the flanks of actively degassing volcanoes, we enable to interpret the signals plants provide in response to excess CO2 with airborne and spaceborne hyperspectral remote sensing methods, including a possible future Surface Biology and Geology (SBG) NASA satellite mission.As a critical step to mature and test this concept, we deployed small unmanned aerial systems (sUAS) using a fixed-wing sUAS designed for autonomous operations and long endurance in extreme environments, without causing significant disturbance of the sampled air. We integrated an in-situ sensor to record the CO2 enhancement field above the forest canopy. Test flight results on the flanks of Turrialba volcano in Costa Rica above forest canopies covering known moderate gas seeps demonstrate the sUAS-borne detection and mapping capabilities of above-canopy elevated CO2 gradients. The strong detection capabilities and high detector signal stability resulted from key system design elements including RF shielding, mechanical stabilization, and calibration procedures. This highly robust system is readily applied for diffuse volcanic CO2 emission studies on active volcanoes covered by dense vegetation.

Volcanic↗
DOE OSTI2026

A multi‐variable framework for selecting WRF physics configurations at convection‐permitting scales: An Amazon wet‐season case study

Tropical convection over rainforests modulates atmospheric circulation and the energy and hydrological cycles across multiple scales. However, the scarcity of observations still limits our understanding of these processes. Although numerical models are utilized to investigate atmospheric physical processes, their performance depends on the choice of parameterizations and grid resolution. Here, in this work, we introduce and apply a multi‐variable, multi‐physics framework to evaluate and rank the Advanced Research Weather Research and Forecasting (WRF–ARW) configurations at 1‐km resolution over the central Amazon during the wet season. A 48‐member ensemble combines three land‐surface models (LSMs), four planetary boundary layer (PBL), and four microphysics (MP) schemes. Model performance for seven convection‐related near‐surface and boundary‐layer variables is assessed using Taylor diagrams and the Taylor skill score (TSS), analysis of variance (ANOVA)‐based sensitivity metrics, and non‐parametric rank tests. We then construct a combined, weighted TSS to identify configurations that are comparatively robust across variables. Results showed that most configurations reproduce near‐surface temperature, sensible and latent heat fluxes, and boundary‐layer height reasonably well, whereas humidity and rainfall remain challenging. LSM choice has the strongest impact on the surface fluxes and a secondary influence on near‐surface temperature and humidity, PBL schemes dominate boundary‐layer height, and MP schemes exert the largest control on rainfall. No single configuration is optimal for all variables, but the combination of Noah (LSM), Yonsei University (PBL), and Morrison (MP) emerges as the most robust configuration for this case, with the WRF single‐moment six‐class scheme (WSM6) providing a competitive, computationally cheaper MP alternative. The framework is general and can be applied to other regions, seasons, and convective regimes.

Amazon rainforest↗
DOE OSTI2026

Fungal mat growth and leaf colonization at the TRACE warming experiment, Mar - Aug 2024, Luquillo, Puerto Rico

This data package contains processed measurements on the growth of litter mat-forming fungi and the time to leaf colonization at the Tropical Responses to Altered Climate Experiment (TRACE). Located near the Sabana Field Research Station in Luquillo, Puerto Rico, the TRACE site is located in a mature, closed-canopy tropical rainforest within the Luquillo Experimental Forest (LEF). These data quantify fungal mat growth and the time to leaf colonization of fungi species Gymnopus johnstonii and Marasmius crinis-equi. The experiment was conducted in ambient (control) and experimentally warmed plots (4°C above ambient) during spring and summer periods to assess how litter mat-forming fungi respond to a range of environmental conditions of tropical wet forests. The data files include tables of relative fungal mat growth rates, time to leaf colonization, averages of soil temperature (°C), and number of dry days before leaf attachment. The data are stored in comma-separated values (CSV) format and viewable with any text editor, spreadsheet, or statistical software (e.g., R, Python, Excel). Associated metadata describe plot identifiers, measurement descriptions, and processing steps.

Agaric fungi↗
DOE OSTI2024

Quantifying and Modeling the Impact of Phase State on the Ice Nucleation Abilities of 2-Methyltetrols as a Key Component of Secondary Organic Aerosol Derived from Isoprene Epoxydiols

Organic aerosols (OAs) may serve as ice-nucleating particles (INPs), impacting the formation and properties of cirrus clouds when their phase state and viscosity are in the semisolid to glassy range. However, there is a lack of direct parameterization between aerosol viscosity and their ice nucleation capabilities. In this study, we experimentally measured the ice nucleation rate of 2-methyltetrols (2-MT) aerosols, a key component of isoprene-epoxydiol-derived secondary organic aerosols (IEPOX-SOA), at different viscosities. These results demonstrate that the phase state has a significant impact on the ice nucleation abilities of OA under typical cirrus cloud conditions, with the ice nucleation rate increasing by 2 to 3 orders of magnitude when the phase state changes from liquid to semisolid. An innovative parametric model based on classical nucleation theory was developed to directly quantify the impact of viscosity on the heterogeneous nucleation rate. This model accurately represents our laboratory measurement and can be implemented into climate models due to its simple, equation-based form. Based on data collected from the ACRIDICON-CHUVA field campaign, our model predicts that the INP concentration from IEPOX-SOA can reach the magnitude of 1 to tens per liter in the cirrus cloud region impacted by the Amazon rainforest, consistent with recent field observations and estimations. This novel parameterization framework can also be applied in regional and global climate models to further improve representations of cirrus cloud formation and associated climate impacts.

2-methyltetrol↗
DOE OSTI2025

Factors Controlling Precipitation Onset and Maintenance: Inferences From Large Eddy Simulations of Two Afternoon Deep Convective Regimes Over Amazon

To investigate the environmental factors controlling the onset and maintenance of afternoon precipitation over tropical rainforests, two contrasting cases are created for large eddy simulations (LES) using GoAmazon observations: one features a single-pulse rain dissipating quickly in earlier afternoon, while the other shows double pulses lasting until evening. For these two specific cases under consideration, LES confirms that early-morning relative humidity dominates afternoon rain patterns. The attributed impacts are distinct: moisture determines the rain onset timing while temperature affects the peak rain intensity. Single-pulse day observes one round of strong precipitation and cold pools, which further suppresses convection. On double-pulse day, the first precipitation peak results from an intermediate development of congestus clouds, whose detrainment leads to a gradual moistening of the lower-to-middle troposphere. This behavior of convection favors a second pulse of stronger precipitation with more convective organization, whose development decouples from surface fluxes and sustains until evening.

Amazon↗
DOE OSTI2025

Boundary-Layer-Coupled and Decoupled Clouds in Global Storm-Resolving Models: Comparisons With the ARM Observations

The accurate representation of interactions between clouds and planetary boundary layer (PBL) is a persistent challenge in climate models, critical for simulating surface energy budget. The emergence of kilometer-grid-scale global storm resolving models (GSRMs) offers the potential for enhanced details of PBL processes in these complex interactions. This study evaluates the representation of PBL-coupled and decoupled clouds in nine GSRM simulations against extensive ground-based observations by the Department of Energy Atmospheric Radiation Measurement (ARM) program, across six sites encompassing diverse regimes such as marine and continental environments in tropics and midlatitude. By differentiating coupling based on the relative positions between cloud bases and PBL tops, our analysis focuses on the simulation of PBL height, cloud frequency, position and vertical extent. The GSRMs generally exhibit commendable agreements with observed cloud structures and PBL diurnal cycles across different ARM sites. In contrast to the relatively consistent representation of decoupled clouds, discrepancies exist between the simulated and the observed coupled clouds, particularly in areas of intense convection, for example, over tropical rainforests and mountainous regions. These biases are probably associated with the models' tendency to underestimate the boundary layer humidity and the frequency of coupled clouds within different ranges of PBL heights. This study underscores the importance for continuous improvements in the representation of boundary layer and convection within these global kilometer-grid-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

GPM IMERG V07B and V06B: Evaluation Using Ground-Based Radar Observations and Application in Global Mesoscale Convective System Tracking

This study evaluates the latest Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG V07B) against its predecessor V06B, for studying mesoscale convective systems (MCSs). Both versions are compared using ground-based radar and rain gauge data from five meteorologically diverse regions: the contiguous United States (including eastern coastlines), Amazon rainforest, central Argentina mountains, equatorial Indian Ocean, and northern Australia across multiple temporal (0.5–6 hours) and spatial scales (0.1°–0.25°). An updated global MCS tracking dataset is developed by integrating satellite-observed infrared brightness temperature with IMERG V07B. Comparation of IMERG against radar observations reveals that IMERG demonstrates better performance in capturing the probability distribution and quantitative contributions of rainfall (from no-rain to intense-rain conditions) over tropical oceans than over land, with marked improvements in IMERG V07B for heavy-to-intense rain (> 10 mm h-1). Over land, systematic biases persist: IMERG tends to overestimate light-to-moderate rain (1–10 mm h-1) while underestimating heavy-to-intense rain. Additionally, aggregating IMERG to coarser resolutions (3-hourly or 0.25°) improves consistency with radar observations, outperforming the 1-hourly/0.1° resolution. The new IMERG V07B-based global MCS dataset exhibits consistent statistical characteristics with the V06B-based dataset, despite lower mean rain rates and reduced heavy precipitation contributions. These findings offer valuable insights for utilizing IMERG V07B in global precipitation studies, MCS characterization, and model evaluation.

Zhang, Sihan↗