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NASA NTRS2003

Plant Response to Microwaves at 2.45 GHz

One method of beaming to Earth energy captured by Space Solar Power (SSP) satellites is by using microwaves. Since microwaves are non-ioniz ing and of low energy they probably will have little or no direct eff ect (either long- or short-term) on terrestrial biota. This contentio n must to be proved however, before the public will accept a continuo us beam of microwaves being sent to the ground near populated areas or onto agricultural lands. To begin to address this question, an exper iment has been done that exposed an important agronomic plant speaes (alfalfa, Medicago sativa L.) to a continuous microwave beam at 2.45 GHz and from between 0.5 to 1.2 milli-watts per square centimeter. Th e hypothesis was that plants exposed to microwaves will be no differe nt from those control plants that were not exposed to microwaves. The microwaves were broadcast over a tray of mature, growing plants in the laboratory. The control plants were subjected to the same environme ntal conditions (light, temperature, soil and nutrients) minus the mi crowave exposure. Both populations of plants were watered as needed. As may be seen, the experiment was designed so that the only variable to which the test plants were subjected was microwave exposure. Prec ise, non-destructive measurements were taken of leaf chlorophyll concentration over the period of the experiment. Also measured were gross plant variables such as stem length, internodal distance, and, at the end of the experiment, above-ground biomass, both fresh and dry weig hts. Soil temperatures on bare soil and under the plant canopy were a lso measured. After seven weeks of exposure to microwaves there was n o sigruficant difference between control and test plant populations. A number of other plant/ microwave exposure studies will be discussed in this presentation. However, this experiment is one of the few publ ished examples of organisms being exposed to continuos microwave illu mination at one of the proposed SSP microwave frequencies and intensi ties.

Skiles, J. W.↗

NASA NTRS2012

Discrimination of Biomass Burning Smoke and Clouds in MAIAC Algorithm

The multi-angle implementation of atmospheric correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the smoke test to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 micrometers as compared to 0.47-0.67 micrometers due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.

Lyapustin, A.↗

NASA NTRS2010

Online Simulations of Global Aerosol Distributions in the NASA GEOS-4 Model and Comparisons to Satellite and Ground-Based Aerosol Optical Depth

We have implemented a module for tropospheric aerosols (GO CART) online in the NASA Goddard Earth Observing System version 4 model and simulated global aerosol distributions for the period 2000-2006. The new online system offers several advantages over the previous offline version, providing a platform for aerosol data assimilation, aerosol-chemistry-climate interaction studies, and short-range chemical weather forecasting and climate prediction. We introduce as well a methodology for sampling model output consistently with satellite aerosol optical thickness (AOT) retrievals to facilitate model-satellite comparison. Our results are similar to the offline GOCART model and to the models participating in the AeroCom intercomparison. The simulated AOT has similar seasonal and regional variability and magnitude to Aerosol Robotic Network (AERONET), Moderate Resolution Imaging Spectroradiometer, and Multiangle Imaging Spectroradiometer observations. The model AOT and Angstrom parameter are consistently low relative to AERONET in biomass-burning-dominated regions, where emissions appear to be underestimated, consistent with the results of the offline GOCART model. In contrast, the model AOT is biased high in sulfate-dominated regions of North America and Europe. Our model-satellite comparison methodology shows that diurnal variability in aerosol loading is unimportant compared to sampling the model where the satellite has cloud-free observations, particularly in sulfate-dominated regions. Simulated sea salt burden and optical thickness are high by a factor of 2-3 relative to other models, and agreement between model and satellite over-ocean AOT is improved by reducing the model sea salt burden by a factor of 2. The best agreement in both AOT magnitude and variability occurs immediately downwind of the Saharan dust plume.

Colarco, Peter↗

NASA NTRS2007

Evaluating the Capacity of Global CO2 Flux and Atmospheric Transport Models to Incorporate New Satellite Observations

As we enter the new era of satellite remote sensing for CO2 and other carbon cyclerelated quantities, advanced modeling and analysis capabilities are required to fully capitalize on the new observations. Model estimates of CO2 surface flux and atmospheric transport are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, and ultimately for future projections of carbon-climate interactions. For application to current, planned, and future remotely sensed CO2 data, it is desirable that these models are accurate and unbiased at time scales from less than daily to multi-annual and at spatial scales from several kilometers or finer to global. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 1998 through 2006. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at lxi degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-2), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to in situ observations at sites in Northern mid latitudes and the continental tropics. The influence of key process representations is inferred. We find that the model can resolve much of the hourly to synoptic variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The seasonal cycle and its interannual variations generally respond adequately, but discrepancies in the tropics suggest the need for a refinement of the soil moisture dependence of the respiration flux in CASA. Examples and inferences for interpretation of satellite data will be discussed. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in the terrestrial CO2 sink and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗

NASA NTRS2010

Comparing Global Atmospheric CO2 Flux and Transport Models with Remote Sensing (and Other) Observations

We report recent progress derived from comparison of global CO2 flux and transport models with new remote sensing and other sources of CO2 data including those from satellite. The overall objective of this activity is to improve the process models that represent our understanding of the workings of the atmospheric carbon cycle. Model estimates of CO2 surface flux and atmospheric transport processes are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, to provide the basic framework for carbon data assimilation, and ultimately for future projections of carbon-climate interactions. Models can also be used to test consistency within and between CO2 data sets under varying geophysical states. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 2000 through 2009. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at 1x1 degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-3), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to remote sensing observations from TCCON, GOSAT, and AIRS as well as relevant in situ observations. Examples of the influence of key process representations are shown from both forward and inverse model comparisons. We find that the model can resolve much of the synoptic, seasonal, and interannual variability in the observations, although reasons for persistent discrepancies in northern hemisphere vegetation uptake are examined. At this time, we do not find any serious shortcomings in the model transport representation, but this is still the subject of close scrutiny. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in CO2 fluxes and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗

NASA NTRS2021

Columnar Aerosol Types and Compositions Over Peninsular Southeast Asia Based on Long-Term AERONET Data

Aerosol chemical components such as black carbon (BC) and brown carbon (BrC) regulate aerosol optical properties, which in turn drive the atmospheric radiative forcing estimations due to aerosols. In this study, we used the long-term measurements from AERONET (Aerosol Robotic Network) to better understand the aerosol types and composition with respect to their seasonal and spatial variabilities in peninsular Southeast Asia (PSEA, here defined as Vietnam, Cambodia, Thailand, Laos, and Myanmar). Two methods (i.e., aerosol type cluster and aerosol component retrieval) were applied to determine the aerosol type and chemical composition during the biomass-burning (BB) season. AERONET sites in northern PSEA showed a higher AOD (aerosol optical depth) compared to that of southern PSEA. Differences in land use pattern, geographic location, and weather regime caused much of the aerosol variability over PSEA. Lower single-scattering albedo (SSA) and higher fine-mode fraction (FMF) values were observed in February and March, suggesting the predominance of BB type aerosols with finer and stronger absorbing particles during the dry season. However, we also found that the peak BB month (i.e., March) in northern PSEA may not coincide with the lowest SSA once dust particles have mixed with the other aerosols. Furthermore, we investigated two severe BB events in March of 2014 and 2015, revealing a significant BrC fraction during BB event days. On high AOD days, although the BC fraction was high, the BrC fraction remained low due to lack of aerosol aging. This study highlights the dominance of carbonaceous aerosols in the PSEA atmosphere during the BB season, while also revealing that transported dust particles and BrC aerosol aging may introduce uncertainties into the aerosol radiative forcing calculation.

Sheng-Hsiang Wang↗

NASA NTRS1988

Thermal analysis of wildfires and effects on global ecosystem cycling

Biomass combustion plays an important role in the earth's biogeochemical cycling. The monitoring of wildfires and their associated variables at global scales is feasible and can lead to predictions of the influence of combustion on biogeochemical cycling and tropospheric chemistry. Remote sensing data collected during the 1985 California wildfire season indicate that the information content of key thermal and infrared/thermal wave band channels centered at 11.5 microns, 3.8 microns, and 2.25 microns are invaluable for discriminating and calculating fire related variables. These variables include fire intensity, rate-of-spread, soil cooling recovery behind the fire front, and plume structure. Coinciding Advanced Very High Resolution Radiometer (AVHRR) data provided information regarding temperature estimations and the movement of the smoke plume from one wildfire into the Los Angeles basin.

Ambrosia, Vincent G.↗

NASA NTRS1989

The distribution of middle tropospheric carbon monoxide during early October 1984

The distribution of middle tropospheric carbon monoxide measure by the Measurement of Air Pollution from Satellites (MAPS) instrument carried aboard the space shuttle is reported. The data represent average mixing ratios in the middle troposphere and are presented in the form of maps that show the carbon monoxide mixing ratios averaged for 6 days of the mission. Comparisons with concurrent, direct measurements taken aboard aircraft show that the inferred concentrations are systematically low by from 20 to 40 percent depending upon which direct measurement calibration standard is used. The data show that there are very large CO sources resulting from biomass burning over South America and southern Africa. Measured mixing ratios were high over northeast Asia and were highly variable over Europe.

Reichle, Henry G., Jr.↗

NASA NTRS1990

The distribution of middle tropospheric carbon monoxide during early October 1984

The measurement of Air Pollution from Satellite experiment measured the distribution of middle-tropospheric CO from the Space Shuttle during October 1984. The data represent average mixing ratios between 57 deg N and 57 deg S. Approximately 75,000 individual CO measurements were obtained during the 9-day mission. The data are presented in maps that show the CO mixing ratios averaged over 5 x 5-deg areas for 6 days of the mission. Comparisons with concurrent direct measurements taken aboard aircraft show that the inferred concentrations are systematically low by 20-40 percent, depending upon which direct measurement calibration standard is used. The data show that there are very large CO sources resulting from biomass burning over South America and southern Africa. Measured mixing ratios were high over northeast Asia and were highly variable over Europe.

Reichle, Henry G., Jr.↗

NASA NTRS2002

New Results from Space and Field Observations on the Aerosol Direct and Indirect Radiative Forcing

New space observations from the MODIS instrument on board the Terra satellite and analysis of POLDER data flown on the ADEOS satellite, show in great details the spatial and seasonal variability of the global aerosol system. These spaceborne instruments distinguish fine aerosol from man-made regional pollution and biomass burning from mostly natural coarse dust and sea salt aerosol. E.g. fine regional pollution in and around the Indian sub-continent, Europe and North America; smoke from biomass burning in Southern Africa and Southern America; coarse dust from West Africa and mixed dust pollution and smoke from West and central Africa and East Asia. These regions were also studied extensively in focused field experiments and by the distributed AERONET network. The results generate the first climatologies of the aerosol system, are used to derive the aerosol radiative effects and to estimate the anthropogenic component. The measurements are also used to evaluate each other and constrain aerosol transport models.

Kaufman, Yoram J.↗

NASA NTRS2003

The Global Aerosol System and its Direct Forcing of Climate: Results From MODIS, AERONET and GOCART

Space observations from the MODIS instrument on board the Terra satellite, show in great details the spatial and seasonal variability of the global aerosol system. These spaceborne instruments distinguish fine aerosol from man-made regional pollution and biomass burning from mostly natural coarse dust and sea salt aerosol. E.g. fine regional pollution in and around the Indian sub-continent, Europe and North America; smoke from biomass burning in Southern Africa and Southern America; coarse dust from West Africa and mixed dust pollution and smoke from West and central Africa and East Asia. These regions were also studied extensively in focused field experiments and by the distributed AERONET network. The results generate the first climatology of the aerosol system, are used to derive the aerosol radiative effects and to estimate the anthropogenic component. The measurements are also used to evaluate each other and constrain aerosol transport models.

Kaufman, Y. J.↗

NASA NTRS2012

Influence of Global Vegetation on Mid-Tropospheric CO2 Early Results

AIRS Mid-Tropospheric CO2 shows a high degree of horizontal variability. Ongoing efforts show AIRS data influenced by global circulation patterns including El Nino Southern Oscillation (ENSO) and Madden Julian Oscillation (MJO) What is the influence of global vegetation cycle on CO2 seasonal behavior? (1) Can we correlate mid-trop CO2 seasonal variability with global vegetation for different regions? (2) For now: First look at zonal averages and Land Vegetation (ocean biomass later) (3) Goal: Sanity Check on AIRS Data Seasonal Cycle, Solicit interest by carbon cycle community

climatology↗

NASA NTRS2014

Sensitivity of Mesoscale Modeling of Smoke Direct Radiative Effect to the Emission Inventory: a Case Study in Northern Sub-Saharan African Region

An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of 7 or less are found in the simulated regional (15degW-42degE, 13degS-17degN) and monthly averages of column PM(sub 2.5) loading, surface PM(sub 2.5) concentration, aerosol optical depth (AOD), smoke radiative forcing at the top-of-atmosphere and at the surface, and air temperature at 2 m and at 700 hPa. The smaller differences in these simulated variables may reflect the atmospheric diffusion and deposition effects to dampen the large difference in smoke emissions that are highly concentrated in areas much smaller than the regional domain of the study. Indeed, at the local scale, large differences (up to a factor of 33) persist in simulated smoke-related variables and radiative effects including semi-direct effect. Similar results are also found for November 2010, despite differences in meteorology and fire activity. Hence, biomass burning emission uncertainties have a large influence on the reliability of model simulations of atmospheric aerosol loading, transport, and radiative impacts, and this influence is largest at local and hourly-to-daily scales. Accurate quantification of smoke effects on regional climate and air quality requires further reduction of emission uncertainties, particularly for regions of high fire concentrations such as NSSA.

Sahel and sub-Saharan African region↗

NASA NTRS2007

The Influence of Sea Ice on Primary Production in the Southern Ocean: A Satellite Perspective

Sea ice in the Southern Ocean is a major controlling factor on phytoplankton productivity and growth, but the relationship is modified by regional differences in atmospheric and oceanographic conditions. We used the phytoplankton biomass (binned at 7-day intervals), PAR and cloud cover data from SeaWiFS, ice concentrations data from SSM/I and AMSR-E, and sea-surface temperature data from AVHRR, in combination with a vertically integrated model to estimate primary productivity throughout the Southern Ocean (south of 60"s). We also selected six areas within the Southern Ocean and analyzed the variability of the primary productivity and trends through time, as well as the relationship of sea ice to productivity. We found substantial interannual variability in productivity from 1997 - 2005 in all regions of the Southern Ocean, and this variability appeared to be driven in large part by ice dynamics. The most productive regions of Antarctic waters were the continental shelves, which showed the earliest growth, the maximum biomass, and the greatest areal specific productivity. In contrast, no large, sustained blooms occurred in waters of greater depth (> 1,000 m). We suggest that this is due to the slightly greater mixed layer depths found in waters off the continental shelf, and that the interactive effects of iron and irradiance (that is, increased iron requirements in low irradiance environments) result in the limitation of phytoplankton biomass over large regions of the Southern Ocean.

Smith, Walker O., Jr.↗

NASA NTRS2000

A Simulation Study Comparing Incineration and Composting in a Mars-Based Advanced Life Support System

The objective of this study is to compare incineration and composting in a Mars-based advanced life support (ALS) system. The variables explored include waste pre-processing requirements, reactor sizing and buffer capacities. The study incorporates detailed mathematical models of biomass production and waste processing into an existing dynamic ALS system model. The ALS system and incineration models (written in MATLAB/SIMULINK(c)) were developed at the NASA Ames Research Center. The composting process is modeled using first order kinetics, with different degradation rates for individual waste components (carbohydrates, proteins, fats, cellulose and lignin). The biomass waste streams are generated using modified "Eneray Cascade" crop models, which use light- and dark-cycle temperatures, irradiance, photoperiod, [CO2], planting density, and relative humidity as model inputs. The study also includes an evaluation of equivalent system mass (ESM).

Hogan, John↗

NASA NTRS2011

Daily and Hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We distributed monthly GFED3 emissions during 2003-2009 on a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) active fire observations. We found that patterns of daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of bunting in savannas. On diurnal timescales, our analysis of the GOES active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗

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 NTRS1982

Variation of directional reflectance factors with structural changes of a developing alfalfa canopy

Directional reflectance factors of an alfalfa canopy were determined and related to canopy structure, agronomic variables, and irradiance conditions at four periods during a cutting cycle. Nadir and off-nadir reflectance factors decreased with increasing biomass in Thematic Mapper band 3(0.63-0.69 micrometer) and increased with increasing biomass in band 4(0.76-0.90 micrometer). The sensor view angle had less impact on perceived reflectance as the alfalfa progressed from an erectophile canopy of stems after harvest to a near planophile canopy of leaves at maturity. Studies of directional reflectance are needed for testing and upgrading vegetation canopy models and to aid in the complex interpretation problems presented by aircraft scanners and pointable satellites where illumination and viewing geometries may vary widely. Distinct changes in the patterns of radiance observed by a sensor as structural and biomass changes occur are keys to monitoring the growth and condition of crops.

Kirchner, J. A.↗