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NASA NTRS2007

Aerosol Source Plume Physical Characteristics from Space-based Multiangle Imaging

Models that assess aerosol effects on regional air quality and global climate parameterize aerosol sources in terms of amount, type, and injection height. The multiangle imaging spectroradiometer (MISR) aboard NASA's Terra satellite retrieves total column aerosol optical thickness (AOT), and aerosol type over cloud-free land and water. A stereo-matching algorithm automatically retrieves reflecting-layer altitude wherever clouds or aerosol plumes have discernable spatial contrast, with about 500-m accuracy, at 1.1-km horizontal resolution. Near-source biomass burning smoke, volcanic effluent, and desert dust plumes are observed routinely, providing information about aerosol amount, particle type, and injection height useful for modeling applications. Compared to background aerosols, the plumes sampled have higher AOT, contain particles having expected differences in Angstrom exponent, size, single-scattering albedo, and for volcanic plume and dust cloud cases, particle shape. As basic thermodynamics predicts, thin aerosol plumes lifted only by regional winds or less intense heat sources are confined to the boundary layer. However, when sources have sufficient buoyancy, the representative plumes studied tend to concentrate within discrete, high-elevation layers of local stability; the aerosol is not uniformly distributed up to a peak altitude, as is sometimes assumed in modeling. MISR-derived plume heights, along with meteorological profile data from other sources, make it possible to relate radiant energy flux observed by the moderate resolution imaging spectroradiometer (MODIS), also aboard the Terra spacecraft, to convective heat flux that plays a major role in buoyant plume dynamics. A MISR climatology of plume behavior based on these results is being developed.

aerosol plumes↗
NASA NTRS2021

Scaling photosynthetic function and CO2 dynamics from leaf to canopy level for maize – dataset combining diurnal and seasonal measurements of vegetation fluorescence, reflectance and vegetation indices with canopy gross ecosystem productivity

Recent advances in leaf fluorescence measurements and canopy proximal remote sensing currently enable the non-destructive collection of rich diurnal and seasonal time series, which are required for monitoring vegetation function at the temporal and spatial scales relevant to the natural dynamics of photosynthesis. Remote sensing assessments of vegetation function have traditionally used actively excited foliar chlorophyll fluorescence measurements, canopy optical reflectance data and vegetation indices (VIs), and only recently passive solar induced chlorophyll fluorescence (SIF) measurements. In general, reflectance data are more sensitive to the seasonal variations in canopy chlorophyll content and foliar biomass, while fluorescence observations more closely relate to the dynamic changes in plant photosynthetic function. With this dataset we link leaf level actively excited chlorophyll fluorescence, canopy proximal reflectance and SIF, with eddy covariance measurements of gross ecosystem productivity (GEP). The dataset was collected during the 2017 growing season on maize, using three automated systems (i.e., Monitoring Pulse-Amplitude-Modulation fluorimeter, Moni-PAM; Fluorescence Box, FloX; and from eddy covariance tower). The data were quality checked, filtered and collated to a common 30 minutes timestep. We derived vegetation indices related to canopy functioning (e.g., Photochemical Reflectance Index, PRI; Normalized Difference Vegetation Index, NDVI; Chlorophyll Red-edge, Clre) to investigate how SIF and VIs can be coupled for monitoring vegetation photosynthesis. The raw datasets and the filtered and collated data are provided to enable new processing and analyses.

Petya Campbell↗
NASA NTRS2004

PhyLM: A Mission Design Concept for an Optical/Lidar Instrument to Measure Ocean Productivity and Aerosols from Space

The Physiology Lidar-Multispectral Mission (PhyLM) is intended to explore the complex ecosystems of our global oceans. New "inversion" methods and improved understanding of marine optics have opened the door to quantifying a range of critical ocean properties. This new information could revolutionize our understanding of global ocean processes, such as phytoplankton growth, harmful algal blooms, carbon fluxes between major pools and the productivity equation. The new science requires new measurements not addressed by currently planned space missions. PhyLM will combine active and advanced passive remote sensing technologies to quantify standing stocks and fluxes of climate-critical components of the Ocean carbon cycle to meet these science providing multispectral bands from the far UV through the near infrared (340 - 1250 nm) at a ground resolution of 250 m. Improved detectors, filters, mirrors, digitization and focal plane design will offer an overall higher-quality data product. The unprecedented accuracy and precision of the absolute water-leaving radiances will support inversion- based quantification of an expanded set of ocean carbon cycle components. The dual- wavelength (532 & 1064 nm) Nd:Yag Lidar will enhance the accuracy and precision of the passive data by providing aerosol profiles for atmospheric correction and coincident active measurements of backscattering. The Lidar will also examine dark-side fluorescence as an additional approach to quantifying phytoplankton biomass in highly productive regions.

Gervin, Janette C.↗
NASA NTRS1997

Spectral quality affects disease development of three pathogens on hydroponically grown plants

Plants were grown under light-emitting diode (LED) arrays with various spectra to determine the effects of light quality on the development of diseases caused by tomato mosaic virus (ToMV) on pepper (Capsicum annuum L.), powdery mildew [Sphaerotheca fuliginea (Schlectend:Fr.) Pollaci] on cucumber (Cucumis sativus L.), and bacterial wilt (Pseudomonas solanacearum Smith) on tomato (Lycopersicon esculentum Mill.). One LED (660) array supplied 99% red light at 660 nm (25 nm bandwidth at half-peak height) and 1% far-red light between 700 to 800 nm. A second LED (660/735) array supplied 83% red light at 660 nm and 17% far-red light at 735 nm (25 nm bandwidth at half-peak height). A third LED (660/BF) array supplied 98% red light at 660 nm, 1% blue light (BF) between 350 to 550 nm, and 1% far-red light between 700 to 800 nm. Control plants were grown under broad-spectrum metal halide (MH) lamps. Plants were grown at a mean photon flux (300 to 800 nm) of 330 micromoles m-2 s-1 under a 12-h day/night photoperiod. Spectral quality affected each pathosystem differently. In the ToMV/pepper pathosystem, disease symptoms developed slower and were less severe in plants grown under light sources that contained blue and UV-A wavelengths (MH and 660/BF treatments) compared to plants grown under light sources that lacked blue and UV-A wavelengths (660 and 660/735 LED arrays). In contrast, the number of colonies per leaf was highest and the mean colony diameters of S. fuliginea on cucumber plants were largest on leaves grown under the MH lamp (highest amount of blue and UV-A light) and least on leaves grown under the 660 LED array (no blue or UV-A light). The addition of far-red irradiation to the primary light source in the 660/735 LED array increased the colony counts per leaf in the S. fuliginea/cucumber pathosystem compared to the red-only (660) LED array. In the P. solanacearum/tomato pathosystem, disease symptoms were less severe in plants grown under the 660 LED array, but the effects of spectral quality on disease development when other wavelengths were included in the light source (MH-, 660/BF-, and 660/735-grown plants) were equivocal. These results demonstrate that spectral quality may be useful as a component of an integrated pest management program for future space-based controlled ecological life support systems.

NASA Center KSC↗
NASA NTRSDate not supplied

PyroCbs from Australia Fires and its Impact Using Satellite Observations from CrIS and TROPOMI and Reanalysis Data

Pyrocumulonimbus (pyroCb) clouds are thunder clouds created by intense heat from the Earth’s surface. They are formed similarly to cumulonimbus clouds, but the intense heat that results in the vigorous updraft comes from fire, either large wildfires or volcanic eruptions. Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles to the atmosphere, particularly during the pyroCb outbreak that occurred in southeast Australia between 29 December 2019 and 4 January 2020. It was estimated that at least 18 pyroCbs were generated during this episode, and some of them injected ice, smoke, and biomass burning gases above the local tropopause. An unprecedented abundance of H2O and CO in the stratosphere, and the displacement of background ozone (O3) and N2O from rapid ascent of air from the troposphere and lower stratosphere were found from satellite observations. Some other studies also found that the fire emissions and their long-range transport resulted in stratospheric aerosol, temperature, and O3 anomalies after the 2020 Australian bushfires and altered the Antarctic ozone and vortex, posing great impact to local air quality and climate change. Further study on the atmospheric thermodynamic status of atmosphere associated with these pyroCbs, and the change of the cloud properties and trace gases during this unprecedented Australia fires will be made using a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP). SiFSAP was developed by NASA using the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1, and will soon be available to the public at NASA DAAC. Since this product has a spatial resolution of 15 km at nadir, which is better than most global weather and climate models and other current operational sounding products, a process-oriented analysis of the dynamic transport of CO and fire plumes during this unprecedented fire disasters will be made in this study. Based on a Principal Component Radiative Transfer Model (PCRTM) and an optimized estimation retrieval algorithm, a simultaneously retrieval is made using the whole spectral information measured by CrIS, and the derived SiFSAP include temperature, water vapor, trace gases (such as O3, CO2, CO, CH4 and N2O), cloud properties and surface properties. Use of ATMS together with CrIS allows SiFSAP to get accurate retrieval products under thick pyroCb conditions, and an algorithm to detect pyroCb based on the hyperspectral infrared sounder spectrum from CrIS will be developed and verified. In addition to SiFSAP sounding products, other products like CO, O3, NO2 from TROPOMI, O3 from OMPS will be used for retrospective analysis. The wind fields from the NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize the transport, and the SiFSAP temperature and water vapor profiles within and around pyroCbs will be compared with MERRA-2 and ERA5 products.

Xiaozhen (Shawn) Xiong↗
NASA NTRS2018

GEOS-CF Model Assessment of PM2.5 During Wildfires: Inferring the Impact of PM2.5 Exposure on Adverse Respiratory & Cardiovascular Conditions

Exposure to fine particulate matter (PM2.5) can aggravate pre-existing respiratory and cardiovascular conditions. When PM2.5 is inhaled it can cause damage to the lungs such as reduced lung function and shortness of breath. After being inhaled PM2.5 can enter the bloodstream and cause harm to the heart. One major natural source of PM2.5 exposure is from wildfire smoke. The particulates within the smoke from the wildfires can spread from the initial source region, potentially impacting communities both near and far. During and after wildfire events, PM2.5 levels can exceed the WHO air quality guidelines (10 gm^3 annual mean; 25 gm^3 daily mean), becoming hazardous to an individual's health. Global models can be used to simulate the emission and transport of these particulates and subsequently they can be valuable to air quality forecasting in highly polluted areas. The NASA Goddard Earth Observing System (GEOS) version 5 Composition Forecast (GEOS-CF) system has been used to produce near-real time air quality forecasts of atmospheric composition at a high global resolution of 25 km. The GEOS-CF system utilizes the GEOS weather forecast model coupled with GEOS-Chem (version 11) chemistry module to provide analyses and forecasts of various toxic air pollutants, including PM2.5. The GEOS-CF simulated high levels of PM2.5 (40 gm^3 to 250 gm^3 ), exceeding the WHO guidelines, during multiple recent regional and global wildfire seasons, including the 2017 Seattle, WA and Los Angeles, CA wildfire seasons, and biomass burning events in India. Furthermore, the GEOS-CF simulated PM2.5 applied to a human health assessment model, BenMAP (The Environmental Benefits Mapping and Analysis Program, version 1.3), estimates the impact on adverse respiratory health conditions due to PM2.5 exposure from wildfires. The GEOS-CF predicted PM2.5 during the wildfire season with the corresponding BenMAP results provides an assessment of the human health impact of PM2.5 exposure.

Saunders, Emily↗
NASA NTRSDate not supplied

Observation of Carbon Monoxide and Ozone from 2019-2020 Australia Fires Using Thermal Infrared and Near-Infrared Satellite Sensors

The Single Field-of-view Sounder Atmospheric Products (SiFSAP), including ozone (O3) and carbon monoxide (CO), from CrIS on SNPP have a spatial resolution of about 14 km. Such high-resolution sounder products enable us to make process-oriented analysis of CO emission and transport from biomass burning as well as the O3 production along the transport of fire plumes from large wildfires. An analysis of SiFSAP CO from Australia’s unprecedented wildfires in the end of 2019 to early 2020 and comparison with other satellite products, such as TROPOMI and MOPPIT, demonstrate a good agreement of CO observations among these space-borne sensors. This study also demonstrates the advantage of the SiFSAP CO in capturing the feature of CO transport and O3 production from wildfires, which will benefit air quality study.

Xiaozhen Xiong↗
NASA NTRS2019

Modelling above-ground biomass stock over Norway using national forest inventory data with ArcticDEM and Sentinel-2 data

Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the boreal domain. ArcticDEM is a collection of high-resolution (2 m) space-borne stereogrammetric digital surface models (DSM) covering the entire land area north of 60° of latitude. The free-availability of ArcticDEM data offers new possibilities for aboveground biomass mapping (AGB) across boreal forests, and thus it is necessary to evaluate the potential for these data to map AGB over alternative open-data sources (i.e., Sentinel-2). This study was performed over the entire land area of Norway north of 60° of latitude, and the Norwegian national forest inventory (NFI) was used as a source of field data composed of accurately geolocated field plots (n=7710) systematically distributed across the study area. Separate random forest models were fitted using NFI data, and corresponding remotely sensed data consisting of either: i) a canopy height model (ArcticCHM) obtained by subtracting a high-quality digital terrain model (DTM) from the ArcticDEM DSM height values, ii) Sentinel-2 (S2), or iii) a combination of the two (ArcticCHM+S2). Furthermore, we assessed the effect of the forest- and terrain-specific factors on the models’ predictive accuracy. The best model (,i.e., ArcticCHM+S2) explained nearly 60% of the variance of the training set, which translated in the largest accuracy in terms of root mean square error (RMSE=41.4 t/ha). This result highlights the synergy between 3D and multispectral data in AGB modelling. Furthermore, this study showed that despite the importance of ArcticCHM variables, the S2 model performed slightly better than ArcticCHM model. This finding highlights some of the limitations of ArcticDEM, which, despite the unprecedented spatial resolution, is highly heterogeneous due to the blending of multiple acquisitions across different years and seasons. We found that both forest- and terrain-specific characteristics affected the uncertainty of the ArcticCHM+S2 model and concluded that the combined use of ArcticCHM and Sentinel-2 represents a viable solution for AGB mapping across boreal forests. The synergy between the two data sources allowed for a reduction of the saturation effects typical of multispectral data while ensuring the spatial consistency in the output predictions due to the removal of artifacts and data voids present in ArcticCHM data. While the main contribution of this study is to provide the first evidence of the best-case-scenario (i.e., availability of accurate terrain models) that ArcticDEM data can provide for large-scale AGB modelling, it remains critically important for other studies to investigate how ArcticDEM may be used in areas where no DTMs are available as is the case for large portions of the boreal zone.

space-borne imagery↗
NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here we apply an Ensemble Kalman Filter DA system as part of the Data Assimilation Research Testbed to a variety of land surface simulations. First, we describe the use of remotely sensed biomass observations to provide improved simulations of plant phenology, carbon and water cycling for regions highly sensitive to climate change (Western US, China, and Arctic). We discuss approaches to account for systemic biases between models and observations, including the use of spatially-varying adaptive ensemble inflation as an alternative approach to re-scaling soil moisture observations. Finally, we discuss a strategy to incorporate complementary observations (snow water equivalent, solar-induced fluorescence) to better constrain the representation of carbon and water cycling across complex terrain.

DART↗
NASA NTRS2012

Characteristics and Composition of Atmospheric Aerosols in Phimai, Central Thailand During BASE-ASIA

Popular summary: Atmospheric aerosols play an important role in the Earth's climate system, and can also have adverse effects on air quality and human health. The environmental impacts of aerosols, on the other hand, are highly regional, since their temporal/spatial distribution is inhomogeneous and highly depends on the regional emission sources. To better understand the effects of aerosols, intensive field experiments are necessary to characterize the chemical and physical properties on a region-by-region basis. From late February to early May in 2006, NASA/GSFC's SMARTLabs facility was deployed at a rural site in central Thailand, Southeast Asia, to conduct a field experiment dubbed BASE-ASIA (Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment). The group was joined by scientists from the University of Hawaii and other regional institutes. Comprehensive measurements were made during the experiment, including aerosol chemical composition, optical and microphysical properties, as well as surface energetics and local . meteorology. This study analyzes part of the data from the BASE-ASIA experiment. It was found that, even for the relatively remote rural site, the aerosol loading was still substantial. Besides agricultural burning in the area, industrial pollution near the Bangkok metropolitan area, about 200 km southeast of the site, and even long-range transport from China, also contribute to the area's aerosol loading. The results indicate that aerosol pollution has developed into a regional problem for northern Indochina, and may become more severe as the region's population and economy continue to grow. Abstract: Comprehensive measurements of atmospheric aerosols were made in Phimai, central Thailand (15.l83 N, 102.565 E, elevation: 206 m) during the BASE-ASIA field experiment from late February to early May in 2006. The observed aerosol loading was sizable for this rural site (mean aerosol scattering: 108 +/- 64 Mm(exp -1); absorption: 15 +/- 8 Mm(exp -1); PM(sub 10) concentration: 33 +/- 17 miro-g/ cubic m and dominated by submicron particles. Major aerosol compounds included carbonaceous (OC: 9.5 +/- 3.6miro-g/ cubic m; EC: 2.0 2.3 miro-g/ cubic m and secondary species (SO4(2-): 6.4 +/- 3.7 miro-g/ cubic m, NH4(+): 2.2 +/- 1.3 miro-g/ cubic m). While the site was seldom under the direct influence of large forest fires to its north, agricultural fires were ubiquitous during the experiment, as suggested by the substantial concentration of K+ (0.56 +/- 0.33 micro-g/ cubic m). Besides biomass burning, aerosols in Phimai during the experiment were also strongly influenced by industrial and vehicular emissions from the Bangkok metropolitan region and long-range transport from southern China. High humidity played an important role in determining the aerosol composition and properties in the region. Sulfate was primarily formed via aqueous phase reactions, and hygroscopic growth could enhance the aerosol light scattering by up to 60%, at the typical morning RH level of 85%. The aerosol single scattering albedo demonstrated distinct diurnal variation, ranging from 0.86 +/- 0.04 in the evening to 0.92 +/- 0.02 in the morning. This experiment marks the first time such comprehensive characterization of aerosols was made for rural central Thailand. Our results indicate that aerosol pollution has developed into a regional problem for northern Indochina, and may become more severe as the region's population and economy continue to grow.

Li, Can↗
NASA NTRS2012

Using Pyrolysis and its Bioproducts to Help Close the Loop in Sustainable Life Support Systems

The next step in human exploration of space is beyond low Earth orbit and possibly to sites such as the Moon and Mars. Resupply of critical life support components for missions such as these are difficult or impossible. Life support processes for closing the loop of water, oxygen and carbon have to be identified .. Currently, there are many technologies proposed for terrestrial missions for waste, water, air processing and the creation of consumables. There are a variety of different approaches, but few address all of these issues simultaneously. One candidate is pyrolysis; a method where waste streams can be heated in the absence of oxygen to undergo a thermochemical conversion producing a series of bioproducts. Bioproducts like biochar made from non-edible biomass and human solid waste can possibly provide valuable benefits such as waste reduction, regolith fertilization for increased food production, and become a consumable for water processing and air revitalization systems. Syngas containing hydrogen, carbon monoxide and c~bon dioxide, can be converted to methane and dimethyl ether to create propellants. Bio-oils can be utilized as a heating fuel or fed to bioreactors that utilize oil-eating microbes. Issues such as carbon sequestration and subsequent carbon balance of the closed system and identifying ideal process methods to achieve the highest quality products, whilst being energy friendly, will also be addressed.

McCoy, LaShelle E.↗
NASA NTRS2017

Seasonal Impact of Regional Outdoor Biomass Burning on Air Pollution in Three Indian Cities: Delhi, Bengaluru, and Pune

Air pollution in many of India's cities exceeds national and international standards, and effective pollution control strategies require knowledge of the sources that contribute to air pollution and their spatiotemporal variability. In this study, we examine the influence of a single pollution source, outdoor biomass burning, on particulate matter (PM) concentrations, surface visibility, and aerosol optical depth (AOD) from 2007 to 2013 in three of the most populous Indian cities. We define the upwind regions, or "airsheds," for the cities by using atmospheric back trajectories from the HYSPLIT model. Using satellite fire radiative power (FRP) observations as a measure of fire activity, we target pre-monsoon and post-monsoon fires upwind of the Delhi National Capital Region and pre-monsoon fires surrounding Bengaluru and Pune. We find varying contributions of outdoor fires to different air quality metrics. For the post-monsoon burning season, we find that a subset of local meteorological variables (air temperature, humidity, sea level pressure, wind speed and direction) and FRP as the only pollution source explained 39% of variance in Delhi station PM(sub 10) anomalies, 77% in visibility, and 30% in satellite AOD; additionally, per unit increase in FRP within the daily airshed (1000 MW), PM(sub 10) increases by 16.34 micrograms per cubic meter, visibility decreases by 0.097 km, and satellite AOD increases by 0.07. In contrast, for the pre-monsoon burning season, we find less significant contributions from FRP to air quality in all three cities. Further, we attribute 99% of FRP from post-monsoon outdoor fires within Delhi's average airshed to agricultural burning. Our work suggests that although outdoor fires are not the dominant air pollution source in India throughout the year, post-monsoon fires contribute substantially to regional air pollution and high levels of population exposure around Delhi. During 3-day blocks of extreme PM(sub 2.5) in the 2013 post-monsoon burning season, which coincided with statistically significant high fire activity, concentrations in Delhi averaged 304 micrograms per cubic meter, or more than 1000% above the 24-h PM(sub 2.5) guideline (25 micrograms per cubic meter) of the World Health Organization. These results suggest that providing viable alternatives to agricultural residue burning could help improve post-monsoon air quality for a growing population of 63 million (39% in urban areas) within Delhi's airshed.

Air quality; Outdoor fires; Crop residue burning; ↗
NASA NTRS1990

Algae for controlled ecological life support system diet characterization of cyanobacteria 'spirulina' in batch cultures

Spirulina sp. is a bioregenerative photosynthetic and edible alga for space craft crews in a Closed Ecological Life Support System (CLESS). It was characterized for growth rate and biomass yield in batch cultures, under various environmental conditions. The cell characteristics were identified for one strain of Spirulina: S. maxima. Fast growth rate and high yield were obtained. The partitioning of the assimulatory products (proteins, carbohydrates, lipids) were manipulated by varying the environmental conditions. Experiments with Spirulina demonstrated that under stress conditions carbohydrate increased at the expense of protein. In other experiments, where the growth media were sufficient in nutrients and incubated under optimum growth conditions, the total proteins were increased up to almost 70 percent of the organic weight. In other words, the nutritional quality of the alga could be manipulated by growth conditions. These results support the feasibility of considering Spirulina as a subsystem in CELSS because of the ease with which its nutrient content can be manipulated.

Tadros, M. G.↗
NASA NTRS1999

Tropical Tropospheric Ozone: New Insights from Remote Sensing, Sondes and Field Studies

This talk will summarize our recent research in tropical tropospheric ozone studies in the field and from space. New tropospheric ozone and aerosol products from the TOMS (Total Ozone Mapping Spectrometer) satellite instrument will be highlighted (Hudson and Thompson, 1998; Thompson and Hudson, 1999). These are suitable for studying processes like ozone pollution resulting from biomass fires, seasonal and interannual variations and trends. Archived maps of tropospheric ozone over the tropics, from the Nimbus 7 observing period (1979-1992) are available in digital form at our website: http://metosrv2.umd.edu/-tropo. Real-time processing of TOMS data has produced images of tropical tropospheric ozone (TTO) since early 1997, using Earth-Probe TOMS; these maps are also available on the homepage. The need for validation data for TTO maps has led to establishment of the NASA/NOAA-sponsored SHADOZ (Southern Hemisphere Additional Ozonesondes) network, from which a 2-year record of high-quality ozonesonde data can be obtained: (http://hyperion.gsfc.nasa.gov/Data-services/Shadoz/shadoz-hmpg2.htrnl). Examples will be shown, along with ozonesondes from the January-February 1999 Aerosols-99 cruise of the R/V Ronald H Brown from Virginia to Cape Town, South Africa.

Thompson, Anne M.↗
NASA NTRS2005

NASA's East and Southeast Asia Initiatives: BASE-ASIA and EAST-AIRE

Airborne dust from northern China influences air quality and regional climate in Asia during springtime. However, with the economic growth in China, increased emission of particulate air pollutants from industrial and vehicular sources will not only impact the earth's radiation balance, but also adversely affect human health year round. In addition, both of dust and aerosol pollutants can be transported swiftly across the Pacific affecting North America within a few days. Asian dust and pollutant aerosols can be detected by their colored appearance using current Earth observing satellites (e.g., MODIS, SeaWiFS, TOMS, etc.) and by sunphotometers deployed on the surface of the earth. Biomass burning has been a regular practice for land clearing and conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the climatology of Southeast Asia is very different than that of Africa and South America, such that large-scale biomass burning causes smoke to interact extensively with clouds during the peak-burning season of March to April. Globally significant sources of greenhouse gases (eg., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning. These gases influence the Earth-atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play a role in determining cloud lifetime and precipitation, altering the earth's radiation and water budgets. Biomass burning also affects the biogeochemical cycling of nitrogen and carbon compounds; the hydrological cycle; land surface reflectivity and emissivity; and ecosystem biodiversity and stability. Two NASA initiatives, EAST-AIRE (East Asian Study of Tropospheric Aerosols: an International Regional Experiment) and BASE-ASIA (Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment) will be presented. The objectives of these initiatives is to develop a better understanding of the impacts of aerosols on regional-to-global climate, hydrological and carbon cycles, and tropospheric chemistry.

Tsay, S.↗
NASA NTRS2016

Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of Multiple Satellite Sensors

The Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height and single scattering albedo (SSA) for biomass burning smoke aerosols. By using multiple satellite sensors synergistically, ASHE can provide the height information over much broader areas than lidar observations alone. The complete ASHE algorithm uses aerosol data from MODIS or VIIRS, OMI or OMPS, and CALIOP. A simplified algorithm also exists that does not require CALIOP data as long as the SSA of the aerosol layer is provided by another source. Several updates have recently been made: inclusion of dust layers in the retrieval process, better determination of the input aerosol layer height from CALIOP, improvement in aerosol optical depth (AOD) for nonspherical dust, development of quality assurance (QA) procedure, etc.

satellite remote sensing↗
NASA NTRS2006

A Unique Perspective from Space on our Planet: Science, Technologies and Applications

The study of Planet earth is a very complex problem. It has many non-linear and chaotic systems operating in parallel and have interdependencies. In reality, these systems/phenomena s are not well understood or mathematically modeled because of our lack of knowledge of such intricate processes. However, in order to further the subject of Earth as an integrated system, space provides excellent vantage points to look at these processes in multidimensional framework. For example, we can make strives to understand the global water cycle, carbon cycle, atmospheric chemistry, biomass changes, oceans and solid Earth variations by making multitude of global measurements such as soil moisture, precipitation, tropospheric and stratospheric gases, aerosols, tropospheric winds, ocean salinity, ocean color, vegetation cover, crustal dynamics and many more. Such suites of measurements derive the coupled models so we may predict the changes due to natural and anthropogenic forcing. NASA along with other international space agencies have made tremendous investments in recent years in developing and flying remote sensing space borne sensors to enable these measurements. These science measurements and products are further used to address pressing issues such as coastal zone erosion, air quality, severe weather, water availability and quality, public health, fires, earthquakes, land slides and others for societal benefits. This presentation provides a comprehensive overview of NASA s science investigations, related technologies and satellites/sensors and applications.

Habib, Shaid↗
NASA NTRS2018

Air Quality Modeling Using the NASA GEOS-5 Multispecies Data Assimilation System

The NASA Goddard Earth Observing System (GEOS) data assimilation system (DAS) has been expanded to include chemically reactive tropospheric trace gases including ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). This system combines model analyses from the GEOS-5 model with detailed atmospheric chemistry and observations from MLS (O3), OMI (O3 and NO2), and MOPITT (CO). We show results from a variety of assimilation test experiments, highlighting the improvements in the representation of model species concentrations by up to 50% compared to an assimilation-free control experiment. Taking into account the rapid chemical cycling of NO2 when applying the assimilation increments greatly improves assimilation skills for NO2 and provides large benefits for model concentrations near the surface. Analysis of the geospatial distribution of the assimilation increments suggest that the free-running model overestimates biomass burning emissions but underestimates lightning NOx emissions by 5-20%. We discuss the capability of the chemical data assimilation system to improve atmospheric composition forecasts through improved initial value and boundary condition inputs, particularly during air pollution events. We find that the current assimilation system meaningfully improves short-term forecasts (1-3 day). For longer-term forecasts more emphasis on updating the emissions instead of initial concentration fields is needed.

Keller, Christoph A.↗