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At least 271 records · Page 15
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NASA NTRS2020

Influence of Synoptic-Dynamic Meteorology on the Long-Range Transport of Indochina Biomass Burning Aerosols

Impacts of long-range transported biomass burning aerosols from northern Indochina on regional air quality, atmospheric visibility, and climate effects have been discussed extensively in the literature over the past decade. However, the mechanism between aerosol transport and the low-level jet (LLJ) in synoptic meteorology dynamics (e.g., the frontal system) is still not fully understood. In this study, we present results of aerosol-LLJ interaction based on the National Aeronautics and Space Administration/Modern Era Retrospective-analysis for Research and Application version 2 (NASA/MERRA-2) dataset simultaneous to field campaigns in spring 2013–2015 over Southeast Asia. For linking the atmospheric circulation to aerosol transport, a general meteorological condition favorable for aerosol transport is demonstrated. Biomass burning aerosol accumulation over the source region (i.e., northern Indochina) coincided with weak westerly system over the northern South China Sea, and as the synoptic weather system evolved, the aerosols were transported to downwind regions (i.e., Taiwan and West Pacific) by a cold front and LLJ dynamics. The MERRA-2 reanalysis data show the postcold front accompanied a LLJ stream at approximately 700 hPa (3 km) and accelerated the haze plume transport eastward with a life cycle of approximately 3–5 days, an event that reoccurred multiple times from March to April. Our results indicate that coexistence of LLJ and a South China Sea anticyclone at 700 hPa, which primarily could drive the mechanism behind these transport events. Furthermore, more observational data from Southeast Asia would greatly benefit studies of aerosol-meteorology interactions in the region.

Hsiang-Yu Huang↗
NASA NTRS2020

Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels

We introduce a multiscale superpixel approach that leverages repeat-pass interferometric coherence and sparse AGB estimates from a simulated spaceborne lidar in order to extend the NISAR mission’s applicable range of aboveground biomass (AGB) in tropical forests. Airborne and spaceborne L-band radar and full-waveform airborne lidar data are used to simulate the NISAR and GEDI mission, respectively. In addition to UAVSAR data, we use spaceborneALOS-2/PALSAR-2 imagery with 14-day temporal baseline, which is comparable to NISAR’s 12-daybaseline. Our reference AGB maps are derived from the airborne LVIS data during the AfriSAR campaign for three sites (Mondah, Ogooue, and Lope). Each tropical site has mean AGB of at least 125 Mg/ha in addition to areas with AGB exceeding 700 Mg/ha. Spatially sampling from these LVIS-derived AGB reference maps, we approximate GEDI AGB estimates. To evaluate our methodology, we perform several different analyses. First, we partition each study site into low(≤100 Mg/ha) and high (>100 Mg/ha) AGB areas, in conformity with the NISAR mission requirement to provide AGB estimates for forests between 0 and 100 Mg/ha with a RMSE below 20 Mg/ha. In the low AGB areas, this RMSE requirement is satisfied in Lope and Mondah and it fell short of the requirement in Ogooue by less 3 Mg/ha with UAVSAR and 6 Mg/ha with PALSAR-2. We note that our maps have finer spatial resolution (50 m) than NISAR requires (1 hectare). In the high AGB areas, the normalized RMSE increases to 51% (i.e.,<90 Mg/ha), but with negligible bias for all three sites. Second, we train a single model to estimate AGB across both high and low AGB regimes simultaneously and obtain a normalized RMSE that is<60% (or<100 Mg/ha). Lastly, we show the use of both (a) multiscale superpixels and (b) interferometric coherence significantly improves the accuracy of the AGB estimates. The InSAR coherence improved the RMSE by approximately 8% at Mondah with both sensors, lowering the RMSE from 59 Mg/ha to 47.4 Mg/h with UAVSAR and from 57.1 Mg/ha to 46 Mg/ha. This work illustrates one of the numerous synergistic relationships between the spaceborne lidars, such as GEDI, with L-band SAR, such as PALSAR-2 and NISAR, in order to produce robust regional AGB in high biomass tropical regions.

NISAR↗
NASA NTRSDate not supplied

Biomass Burning Smoke and Coincident Water Vapor Over the Southeast Atlantic Stratocumulus Region: Results from Observations and Models

In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the Southeast Atlantic (SEA) Ocean. We present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA. Using multiple airborne datasets, we observe a strongly linear correlation between biomass burning indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. This relationship was particularly strong in the 2016 observations, but was also present in the 2017 and 2018 deployments. Using ECMWF and MERRA-2 reanalyses and specialized WRF-Chem simulations, we trace the plume-vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper-tropospheric air and then is subjected to conditions of strong westward advection, namely the South African Easterly Jet (AEJ-S). Our analysis indicates that airmasses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ~5-6km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. The smoky, humid mixed air is then subjected to strong zonal winds and advected over the SEA following largely isentropic trajectories. HYSPLIT back trajectories support this interpretation. With better understanding of this relationship, and its spatial and temporal variations, we are working towards accurately quantifying the radiative and dynamical effects of both aerosol and water vapor over this region.

Kristina Pistone↗
NASA NTRS2020

Assessment Of Polsar And Insar Time-Series From The 2019 Nasa Am-Pm Campaign For Above-Ground Biomass Estimation

The forthcoming launch of the NASA-ISRO Synthetic ApertureRadar (NISAR) mission will open the path to a new typeof L-band measurements constituted by dense time-series ofpolarimetric backscatter and interferometric coherence withunprecedented spatial and temporal sampling. Here, we startthe development of a theoretical framework that links L-bandbackscatter time-series with interferometric coherence measurements.The water-cloud-model (WCM) and an extendedversion of the random-motion-over-ground (RMoG) modelare adopted to express radar measurements in terms of forestabove-ground biomass and tree height. Time-series datacollected during the 2019 UAVSAR AM-PM campaign inSoutheastern United States are used to evaluate the correlationof various PolSAR- and InSAR-derived parameters withfield-measured above-ground biomass.

Lavalle, Marco↗
NASA NTRS2020

A Regional L-band High Biomass Estimation Framework Leveraging Spaceborne Lidar and Interferometric Data to Overcome Backscatter Saturation

We propose a framework to estimate high above ground biomass (AGB) from L-band SAR imagery leveraging spaceborne lidars such as GEDI or ICESat-2 and repeat-pass coherence. Our results indicate we are able to overcome model saturation typically associated with purely backscatter methodologies. We validate our approach using lidar-derived AGB maps from the AfriSAR datasets at Mondah, Ogooue, and Lope. We apply our framework to UAVSAR and ALOS- 2 imagery to obtain 50 meter resolution biomass maps. We obtain < 60% nRMSE (in some cases much better) with negligible relative bias using a multiscale random forest model. We illustrate that the inclusion of coherence can significantly improve high AGB estimation particularly at the coastal site Mondah.

Liao, Tien-hao↗
NASA NTRS2022

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Laura Duncanson↗
NASA NTRSDate not supplied

Excessive Subsidence of the Southeast Atlantic Biomass Burning Aerosol Plume in the NASA Goddard Earth Observing System (GEOS) Model

Global models struggle to accurately represent the meteorological environment over the Southeast Atlantic Ocean, as evidenced by the poor representation of persistent marine stratocumulus decks off the west coast of southern Africa. This complex regime also experiences significant seasonal biomass burning aerosol plumes that are transported from southern Africa over the Atlantic Ocean, which gradually descend via large scale subsidence and interact radiatively and microphysically with the cloudy environment of the region. In comparisons to space borne lidar and aircraft observations we find that the NASA Goddard Earth Observing System (GEOS) model’s MERRA-2 aerosol and meteorology reanalysis shows that the aerosol plume descends too rapidly due to exaggerated large-scale downward vertical motion. This complicates the evaluation of aerosol properties utilizing aircraft observations collected throughout the ORACLES campaign as well as the model’s representation of the heating rate profiles due to the aerosol itself and its radiative interaction with the semi-permanent cloud deck typically located lower in altitude than the smoke. Two types of modeling experiments using GEOS will be presented to diagnose deficiencies in the model related to the excessive subsidence. Ensembles of free-running model simulations with and without radiatively active biomass burning aerosol will be used to quantify the impact of smoke on the atmospheric circulation. It will be demonstrated that heating within the aerosol layer results in self lofting through a reduction of the subsidence but did not alter the vertical placement or speed of the African Easterly jet. The amount of aerosol absorption required to eliminate the bias in the height of the aerosol plume through self-lofting will then be quantified. Finally, a second type of modeling experiment will be discussed in which the meteorology is constrained to observations. This will allow for biases in the height of the aerosol plume due to the general circulation model to be distinguished from biases that may be induced through the data assimilation process.

Allison Collow↗
NASA NTRSDate not supplied

Sampling of Space-Based Observations of XCO2 Associated With Biomass Burning Events

- The OCO-2 Level 3 assimilation product fills in gaps where OCO-2 does not have observations. - Although the Level 3 clearly shows the increased CO2 over the Amazon associated with the September 2017 biomass burning event, the total amount of CO2 may be underestimated because of a sampling bias. - The TCCON observations match fairly well with the OCO-2 observations and can be used to estimate the accuracy of the OCO observations and the temporal sampling bias. However, since it is a remotely sensed product, it may suffer the same sampling biases associated with biomass burning events as OCO-2. - Although aircraft data show that there is a significant variation in xCO2 with altitude, they suggest the OCO-2 fused products created by kriging may be better than the assimilated product at detecting large deviations from the average state on daily and regional scales.

Thomas J. Hearty, III↗
NASA NTRSDate not supplied

Sampling Biases of Space-Based Observations of XCO2 Associated With South American Biomass Burning Events During 2017-2020

- We examine time series of OCO-2 xCO 2 observations coincident with other remotely sensed and in-situ observations to better understand external sampling effects. - The OCO-2 Level 3 assimilation product fills in gaps where OCO-2 does not have observations. - Although the Level 3 clearly shows the increased CO 2 over the Amazon associated with the September 2017 biomass burning event, the total amount of CO 2 may be underestimated because of a sampling bias. - Since TCCON is also a remotely sensed product, it may suffer the same sampling biases associated with biomass burning events as OCO-2. - Aircraft data show that there is significant variation in xCO 2 with altitude. - The OCO-2 fused products created by kriging may be better than the assimilated product at detecting deviations from the average state.

OCO↗
NASA NTRS1996

Estimation of Biomass Fire Temperature and Areal Extent from Calibrated AVIRIS Spectra

This paper describes an approach to derive a range of biomass fire parameters from spectra measured by NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS measures images of the upwelling spectral radiance from 400 to 2500 nm at 10nm intervals. Images are measured of 11 by up to 100 km with 20 by 20 m spatial resolution.

Biomass AVRIS biomass fire smoke cloud aerosol and↗
NASA NTRS1997

Density and composition of microorganisms during long-term (418 day) growth of potato using biologically reclaimed nutrients from inedible plant biomass

A study evaluating alternative methods for long term operation of biomass production systems was recently completed at the Kennedy Space Center (KSC). The 418-day study evaluated repeated batch versus mixed-aged production of potato grown on either standard 1/2-strength Hoagland's nutrient solution or solutions including nutrients recycled from inedible plant material. The long term effects of closure and recycling on microbial dynamics were evaluated by monitoring the microbial communities associated with various habitats within the plant growth system (i.e., plant roots, nutrient solution, biofilms within the hydroponic systems, atmosphere, and atmospheric condensate). Plate count methods were used to enumerate and characterize microorganisms. Microscopic staining methods were used to estunate total cell densities. The primary finding was that the density and composition of microbial communities associated with controlled environmental plant growth systems are stable during long term operation. Continuous production resulted in slightly greater stability. Nutrient recycling, despite the addition of soluble organic material from the waste processing system, did not significantly increase microbial density in any of the habitats.

NASA Center KSC↗
NASA NTRS1996

Biological degradation and composition of inedible sweetpotato biomass

Many challenges are presented by biological degradation in a bioregenerative Controlled Ecological Life Support System (CELSS) as envisioned by the U.S. National Aeronautics and Space Administration (NASA). In the studies conducted with biodegradative microorganism indigenous to sweetpotato fields, it was determined that a particle size of 75 microns and incubation temperature of 30 degrees C were optimal for degradation. The composition of the inedible biomass and characterization of plant nutrient solution indicated the presence of potential energy sources to drive microbial transformations of plant waste. Selected indigenous soil isolates with ligno-cellulolytic or sulfate-reducing ability were utilized in biological studies and demonstrated diversity in ability to reduce sulfate in solution and to utilize alternative carbon sources: a lignin analog--4-hydroxy, 3-methoxy cinnamic acid, cellulose, arabinose, glucose, sucrose, mannitol, galactose, ascorbic acid.

Vegetables/chemistry/metabolism↗
NASA NTRS1996

An Idealized Direct-Contact Biomass Pyrolysis Reactor Model

A numerical study is performed in order to assess the performance of biomass pyrolysis reactors which utilize direct particle-wall thermal conduction heating. An idealized reactor configuration consisting of a flat-plate turbulent boundary layer flow with particle convection along the heated wall and incorporating particle re-entrainment is considered.

biomass boundary layer modeling pyrolysis tar vort↗
NASA NTRS2013

From BASE-ASIA Toward 7-SEAS: A Satellite-Surface Perspective of Boreal Spring Biomass-Burning Aerosols and Clouds in Southeast Asia

In this paper, we present recent field studies conducted by NASA's SMART-COMMIT (and ACHIEVE, to be operated in 2013) mobile laboratories, jointly with distributed ground-based networks (e.g., AERONET, http://aeronet.gsfc.nasa.gov/ and MPLNET, http://mplnet.gsfc.nasa.gov/) and other contributing instruments over northern Southeast Asia. These three mobile laboratories, collectively called SMARTLabs (cf. http://smartlabs.gsfc.nasa.gov/, Surface-based Mobile Atmospheric Research & Testbed Laboratories) comprise a suite of surface remote sensing and in-situ instruments that are pivotal in providing high spectral and temporal measurements, complementing the collocated spatial observations from various Earth Observing System (EOS) satellites. A satellite-surface perspective and scientific findings, drawn from the BASE-ASIA (2006) field deployment as well as a series of ongoing 7-SEAS (2010-13) field activities over northern Southeast Asia are summarized, concerning (i) regional properties of aerosols from satellite and in situ measurements, (ii) cloud properties from remote sensing and surface observations, (iii) vertical distribution of aerosols and clouds, and (iv) regional aerosol radiative effects and impact assessment. The aerosol burden over Southeast Asia in boreal spring, attributed to biomass burning, exhibits highly consistent spatial and temporal distribution patterns, with major variability arising from changes in the magnitude of the aerosol loading mediated by processes ranging from large-scale climate factors to diurnal meteorological events. Downwind from the source regions, the tightly coupled-aerosolecloud system provides a unique, natural laboratory for further exploring the micro- and macro-scale relationships of the complex interactions. The climatic significance is presented through large-scale anti-correlations between aerosol and precipitation anomalies, showing spatial and seasonal variability, but their precise cause-and-effect relationships remain an open-ended question. To facilitate an improved understanding of the regional aerosol radiative effects, which continue to be one of the largest uncertainties in climate forcing, a joint international effort is required and anticipated to commence in springtime 2013 in northern Southeast Asia.

biomass burning aerosols↗
NASA NTRS2013

Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI plots being grouped in clusters) against corresponding estimates assuming two-stage sampling with the LiDAR and employing model-assisted estimators. For each of the two comparisons, the standard errors of the AGB estimates were consistently lower for the LiDAR-assisted designs. The overall reduction of the standard errors in the LiDAR-assisted estimation was around 40-60% compared to the pure field survey. We conclude that the previously proposed two-stage model-assisted estimators are inappropriate for surveys with unequal lengths of the LiDAR flight-lines and new estimators are needed. Some options for design of LiDAR-assisted sample surveys under REDD are also discussed, which capitalize on the flexibility offered when the field survey is designed as an integrated part of the overall survey design as opposed to previous LiDAR-assisted sample surveys in the boreal and temperate zones which have been restricted by the current design of an existing NFI.

Comparison↗
NASA NTRS2012

Characterization of Aerosols over the Indochina Peninsula from Satellite-Surface Observations During Biomass Burning Pre-Monsoon Season

This paper presents characterization of aerosols over the Indochina peninsular regions of Southeast Asia during pre-monsoon season from satellite and ground-based radiometric observations. Our analysis focuses on the seasonal peak period in aerosol loading and biomass burning, prior to the onset of the Asian summer monsoon, as observed in the inter-annual variations of Aerosol Optical Depth (AOD) and fire count data from MODIS. Multi-year (2007-2011) analysis of spaceborne lidar measurements, from CALIOP, indicates presence of aerosols mostly within boundary layer, however extending to elevated altitudes to approx. 4 km over northern regions of Indochina, encompassing Myanmar, northern Thailand and southern China. In addition, a strong gradient in aerosol loading and vertical distribution is observed from the relatively clean equatorial conditions to heavy smoke-laden northern regions (greater aerosol extinction and smaller depolarization ratio). Based on column-integrated ground-based measurements from four AERONET locations distributed over Thailand, the regional aerosol loading is found to be significantly absorbing with spectral single scattering albedo (SSA) below 0.91+/-0.02 in the 440-1020 nm range, with lowest seasonal mean SSA (most absorbing aerosol) over the northern location of Chiang Mai (SSA approx. 0.85) during pre-monsoon season. The smoke-laden aerosol loading is found to exhibit a significant diurnal pattern with higher AOD departures during early morning observations relative to late afternoon conditions (peak difference of more than 15% amplitude). Finally, satellite-based aerosol radiative impact is assessed using CERES shortwave Top-of-Atmosphere flux, in conjunction with MODIS AOD. Overall, a consistency in the aerosol-induced solar absorption characteristic is found among selected regions from ground-based sunphotometer-derived spectral SSA retrievals and satellite-based radiative forcing analysis.

Indochina↗