Jump to content

New NASA Software Simulates Science Missions for Observing Terrestrial Freshwater


NASA

Recommended Posts

  • Publishers

4 min read

New NASA Software Simulates Science Missions for Observing Terrestrial Freshwater

Global map; different colored areas on each continent show the varying levels of freshwater
A map describing freshwater accumulation (blue) and loss (red), using data from NASA’s Gravity Recovery and Climate Experiment (GRACE) satellites. A new Observational System Simulation Experiment (OSSE) will help researchers design science missions dedicated to monitoring terrestrial freshwater storage. Image Credit: NASA
Image Credit: NASA

From radar instruments smaller than a shoebox to radiometers the size of a milk carton, there are more tools available to scientists today for observing complex Earth systems than ever before. But this abundance of available sensors creates its own unique challenge: how can researchers organize these diverse instruments in the most efficient way for field campaigns and science missions?

To help researchers maximize the value of science missions, Bart Forman, an Associate Professor in Civil and Environmental Engineering at the University of Maryland, and a team of researchers from the Stevens Institute of Technology and NASA’s Goddard Space Flight Center, prototyped an Observational System Simulation Experiment (OSSE) for designing science missions dedicated to monitoring terrestrial freshwater storage.

“You have different sensor types. You have radars, you have radiometers, you have lidars – each is measuring different components of the electromagnetic spectrum,” said Bart Forman, an Associate Professor in Civil and Environmental Engineering at the University of Maryland. “Different observations have different strengths.”

Terrestrial freshwater storage describes the integrated sum of freshwater spread across Earth’s snow, soil moisture, vegetation canopy, surface water impoundments, and groundwater. It’s a dynamic system, one that defies traditional, static systems of scientific observation.

Forman’s project builds on prior technology advancements he achieved during an earlier Earth Science Technology Office (ESTO) project, in which he developed an observation system simulation experiment for mapping terrestrial snow. 

It also relies heavily on innovations pioneered by NASA’s Land Information System (LIS) and NASA’s Trade-space Analysis Tool for Designing Constellations (TAT-C), two modeling tools that began as ESTO investments and quickly became staples within the Earth science community.

Forman’s tool incorporates these modeling programs into a new system that provides researchers with a customizable platform for planning dynamic observation missions that include a diverse collection of spaceborne data sets.

In addition, Forman’s tool also includes a “dollars-to-science” cost estimate tool that allows researchers to assess the financial risks associated with a proposed mission.

Together, all of these features provide scientists with the ability to link observations, data assimilation, uncertainty estimation, and physical models within a single, integrated framework.

“We were taking a land surface model and trying to merge it with different space-based measurements of snow, soil moisture, and groundwater to see if there was an optimal combination to give us the most bang for our scientific buck,” explained Forman.

While Forman’s tool isn’t the first information system dedicated to science mission design, it does include a number of novel features. In particular, its ability to integrate observations from spaceborne passive optical radiometers, passive microwave radiometers, and radar sources marks a significant technology advancement.

Forman explained that while these indirect observations of freshwater include valuable information for quantifying freshwater, they also each contain their own unique error characteristics that must be carefully integrated with a land surface model in order to provide estimates of geophysical variables that scientists care most about.

Forman’s software also combines LIS and TAT-C within a single software framework, extending the capabilities of both systems to create superior descriptions of global terrestrial hydrology.

Indeed, Forman stressed the importance of having a large, diverse team that features experts from across the Earth science and modeling communities.

“It’s nice to be part of a big team because these are big problems, and I don’t know the answers myself. I need to find a lot of people that know a lot more than I do and get them to sort of jump in and roll their sleeves up and help us. And they did,” said Forman.

Having created an observation system simulation experiment capable of incorporating dynamic, space-based observations into mission planning models, Forman and his team hope that future researchers will build on their work to create an even better mission modeling program.

For example, while Forman and his team focused on generating mission plans for existing sensors, an expanded version of their software could help researchers determine how they might use future sensors to gather new data.

“With the kinds of things that TAT-C can do, we can create hypothetical sensors. What if we double the swath width? If it could see twice as much space, does that give us more information? Simultaneously, we can ask questions about the impact of different error characteristics for each of these hypothetical sensors and explore the corresponding tradeoff.” said Forman.

PROJECT LEAD

Barton Forman, University of Maryland, Baltimore County

SPONSORING ORGANIZATION

NASA’s Advanced Information Systems Technology (AIST) program, a part of NASA’s Earth Science Technology Office (ESTO), funded this project

View the full article

Link to comment
Share on other sites

Join the conversation

You can post now and register later. If you have an account, sign in now to post with your account.
Note: Your post will require moderator approval before it will be visible.

Guest
Reply to this topic...

×   Pasted as rich text.   Paste as plain text instead

  Only 75 emoji are allowed.

×   Your link has been automatically embedded.   Display as a link instead

×   Your previous content has been restored.   Clear editor

×   You cannot paste images directly. Upload or insert images from URL.

  • Similar Topics

    • By NASA
      10 min read
      Preparations for Next Moonwalk Simulations Underway (and Underwater)
      Return to 2024 SARP Closeout Faculty Advisors:
      Dr. Guanyu Huang, Stony Brook University
      Graduate Mentor:
      Ryan Schmedding, McGill University

      Ryan Schmedding, Graduate Mentor
      Ryan Schmedding, graduate mentor for the 2024 SARP Atmospheric Science group, provides an introduction for each of the group members and shares behind-the scenes moments from the internship.
      Danielle Jones
      Remote sensing of poor air quality in mountains: A case study in Kathmandu, Nepal
      Danielle Jones
      Urban activity produces particulate matter in the atmosphere known as aerosol particles. These aerosols can negatively affect human health and cause changes to the climate system. Measures for aerosols include surface level PM2.5 concentration and aerosol optical depth (AOD). Kathmandu, Nepal is an urban area that rests in a valley on the edge of the Himalayas and is home to over three million people. Despite the prevailing easterly winds, local aerosols are mostly concentrated in the valley from the residential burning of coal followed by industry. Exposure to PM2.5 has caused an estimated ≥8.6% of deaths annually in Nepal. We paired NASA satellite AOD and elevation data, model  meteorological data, and local AirNow PM2.5 and air quality index (AQI) data to determine causes of variation in pollutant measurement during 2023, with increased emphasis on the post-monsoon season (Oct. 1 – Dec. 31). We see the seasonality of meteorological data related to PM2.5 and AQI. During periods of low temperature, low wind speed, and high pressure, PM2.5 and AQI data slightly diverge. This may indicate that temperature inversions increase surface level concentrations of aerosols but have little effect on the total air column. The individual measurements of surface pressure, surface temperature, and wind speed had no observable correlation to AOD (which was less variable than PM2.5 and AQI over the entire year). Elevation was found to have no observable effect on AOD during the period of study. Future research should focus on the relative contributions of different pollutants to the AQI to test if little atmospheric mixing causes the formation of low-altitude secondary pollutants in addition to PM2.5 leading to the observed divergence in AQI and PM2.5.

      Madison Holland
      Analyzing the Transport and Impact of June 2023 Canadian Wildfire Smoke on Surface PM2.5 Levels in Allentown, Pennsylvania
      Madison Holland
      The 2023 wildfire season in Canada was unparalleled in its severity. Over 17 million hectares burned, the largest area ever burned in a single season. The smoke from these wildfires spread thousands of kilometers, causing a large population to be exposed to air pollution. Wildfires can release a variety of air pollutants, including fine particulate matter (PM2.5). PM2.5 directly affects human health – exposure to wildfire-related PM2.5 has been associated with respiratory issues such as the exacerbation of asthma and chronic obstructive pulmonary disease. In June 2023, smoke from the Canadian wildfires drifted southward into the United States. The northeastern United States reported unhealthy levels of air quality due to the transportation of the smoke. In particular, Pennsylvania reported that Canadian wildfires caused portions of the state to have “Hazardous” air quality. Our research focused on how Allentown, PA experienced hazardous levels of air quality from this event. To analyze the concentrations of PM2.5 at the surface level, NASA’s Hazardous Air Quality Ensemble System (HAQES) and the EPA’s Air Quality System (AQS) ground-based site data were utilized. By comparing HAQES’s forecast of hazardous air quality events with recorded daily average PM2.5 with the EPA’s AQS, we were able to compare how well the ensemble system was at predicting total PM2.5 during unhealthy air quality days. NOAA’s Hybrid Single-Particle Lagrangian Integrated Trajectory model, pyrsig, and the Canadian National Fire Database were used. These datasets revealed the trajectory of aerosols from the wildfires to Allentown, Pennsylvania, identified the densest regions of the smoke plumes, and provided a map of wildfire locations in southeastern Canada. By integrating these datasets, we traced how wildfire smoke transported aerosols from the source at the ground level.

      Michele Iraci
      Trends and Transport of Tropospheric Ozone From New York City to Connecticut in the Summer of 2023
      Michele Iraci
      Tropospheric Ozone, or O₃, is a criteria pollutant contributing to most of Connecticut and New York City’s poor air quality days. It has adverse effects on human health, particularly for high-risk individuals. Ozone is produced by nitrogen oxides and volatile organic compounds from fuel combustion reacting with sunlight. The Ozone Transport Region (OTR) is a collection of states in the Northeast and Mid-Atlantic United States that experience cross-state pollution of O₃. Connecticut has multiple days a year where O₃ values exceed the National Ambient Air Quality Standards requiring the implementation of additional monitoring and standards because it falls in the OTR. Partially due to upstream transport from New York City, Connecticut experiences increases in O₃ concentrations in the summer months. Connecticut has seen declines in poor air quality days from O₃ every year due to the regulations on ozone and its precursors. We use ground-based Lidar, Air Quality System data, and a back-trajectory model to examine a case of ozone enhancement in Connecticut caused by air pollutants from New York between June and August 2023. In this time period, Connecticut’s ozone enhancement was caused by air pollutants from New York City. As a result, New York City and Connecticut saw similar O₃ spikes and decline trends. High-temperature days increase O₃ in both places, and wind out of the southwest may transport O₃ to Connecticut. Production and transport of O₃ from New York City help contribute to Connecticut’s poor air quality days, resulting in the need for interstate agreements on pollution management.

      Stefan Sundin
      Correlations Between the Planetary Boundary Layer Height and the Lifting Condensation Level
      Stefan Sundin
      The Planetary Boundary Layer (PBL) characterizes the lowest layer in the atmosphere that is coupled with diurnal heating at the surface. The PBL grows during the day as solar heating causes pockets of air near the surface to rise and mix with cooler air above. Depending on the type of terrain and surface albedo that receives solar heating, the depth of the PBL can vary to a great extent. This makes PBL height (PBLH) a difficult variable to quantify spatially and temporally. While several methods have been used to obtain the PBLH such as wind profilers and lidar techniques, there is still a level of uncertainty associated with PBLH. One method of predicting seasonal PBLH fluctuation and potentially lessening uncertainty that will be discussed in this study is recognizing a correlation in PBLH with the lifting condensation level (LCL). Like the PBL, the LCL is used as a convective parameter when analyzing upper air data, and classifies the height in the atmosphere at which a parcel becomes saturated when lifted by a forcing mechanism, such as a frontal boundary, localized convergence, or orographic lifting. A reason to believe that PBLH and LCL are interconnected is their dependency on both the amount of surface heating and moisture that is present in the environment. These thermodynamic properties are of interest in heavily populated metropolitan areas within the Great Plains, as they are more susceptible to severe weather outbreaks and associated economic losses. Correlations between PBLH and LCL over the Minneapolis-St. Paul metropolitan statistical area during the summer months of 2019-2023 will be discussed.

      Angelica Kusen
      Coupling of Chlorophyll-a Concentrations and Aerosol Optical Depth in the Subantarctic Southern Ocean and South China Sea (2019-2021)
      Angelica Kusen
      Air-sea interactions form a complex feedback mechanism, whereby aerosols impact physical and biogeochemical processes in marine environments, which, in turn, alter aerosol properties. One key indicator of these interactions is chlorophyll-a (Chl-a), a pigment common to all phytoplankton and a widely used proxy for primary productivity in marine ecosystems. Phytoplankton require soluble nutrients and trace metals for growth, which typically come from oceanic processes such as upwelling. These nutrients can also be supplied via wet and dry deposition, where atmospheric aerosols are removed from the atmosphere and deposited into the ocean. To explore this interaction, we analyze the spatial and temporal variations of satellite-derived chl-a and AOD, their correlations, and their relationship with wind patterns in the Subantarctic Southern Ocean and the South China Sea from 2019 to 2021, two regions with contrasting environmental conditions.
      In the Subantarctic Southern Ocean, a positive correlation (r²= 0.26) between AOD and Chl-a was found, likely due to dust storms following Austrian wildfires. Winds deposit dust aerosols rich in nutrients, such as iron, to the iron-limited ocean, enhancing phytoplankton photosynthesis and increasing chl-a. In contrast, the South China Sea showed no notable correlation (r² = -0.02) between AOD and chl-a. Decreased emissions due to COVID-19 and stricter pollution controls likely reduced the total AOD load and shifted the composition of aerosols from anthropogenic to more natural sources.
      These findings highlight the complex interrelationship between oceanic biological activity and the chemical composition of the atmosphere, emphasizing that atmospheric delivery of essential nutrients, such as iron and phosphorus, promotes phytoplankton growth. Finally, NASA’s recently launched PACE mission will contribute observations of phytoplankton community composition at unprecedented scale, possibly enabling attribution of AOD levels to particular groups of phytoplankton.

      Chris Hautman
      Estimating CO₂ Emission from Rocket Plumes Using in Situ Data from Low Earth Atmosphere
      Chris Hautman
      Rocket emissions in the lower atmosphere are becoming an increasing environmental concern as space exploration and commercial satellite launches have increased exponentially in recent years. Rocket plumes are one of the few known sources of anthropogenic emissions directly into the upper atmosphere. Emissions in the lower atmosphere may also be of interest due to their impacts on human health and the environment, in particular, ground level pollutants transported over wildlife protected zones, such as the Everglades, or population centers near launch sites. While rockets are a known source of atmospheric pollution, the study of rocket exhaust is an ongoing task. Rocket exhaust can have a variety of compositions depending on the type of engine, the propellants used, including fuels, oxidizers, and monopropellants, the stoichiometry of the combustion itself also plays a role. In addition, there has been increasing research into compounds being vaporized in atmospheric reentry. These emissions, while relatively minimal compared to other methods of travel, pose an increasing threat to atmospheric stability and environmental health with the increase in human space activity. This study attempts to create a method for estimating the total amount of carbon dioxide released by the first stage of a rocket launch relative to the mass flow of RP-1, a highly refined kerosene (C₁₂H₂₆)), and liquid oxygen (LOX) propellants. Particularly, this study will focus on relating in situ CO₂ emission data from a Delta II rocket launch from Vandenberg Air Force Base on April 15, 1999, to CO₂ emissions from popular modern rockets, such as the Falcon 9 (SpaceX) and Soyuz variants (Russia). The findings indicate that the CO₂ density of any RP-1/LOX rocket is 6.9E-7 times the mass flow of the sum of all engines on the first stage. The total mass of CO₂ emitted can be further estimated by modeling the volume of the plume as cylindrical. Therefore, the total mass can be calculated as a function of mass flow and first stage main engine cutoff. Future CO₂ emissions on an annual basis are calculated based on these estimations and anticipated increases in launch frequency.


      Return to 2024 SARP Closeout Share
      Details
      Last Updated Nov 22, 2024 Related Terms
      General Explore More
      8 min read SARP East 2024 Ocean Remote Sensing Group
      Article 21 mins ago 10 min read SARP East 2024 Hydroecology Group
      Article 21 mins ago 11 min read SARP East 2024 Terrestrial Fluxes Group
      Article 22 mins ago View the full article
    • By NASA
      11 min read
      Preparations for Next Moonwalk Simulations Underway (and Underwater)
      Return to 2024 SARP Closeout Faculty Advisors:
      Dr. Lisa Haber, Virginia Commonwealth University
      Dr. Brandon Alveshere, Virginia Commonwealth University
      Dr. Chris Gough, Virginia Commonwealth University
      Graduate Mentor:
      Mindy Priddy, Virginia Commonwealth University

      Mindy Priddy, Graduate Mentor
      Mindy Priddy, graduate mentor for the 2024 SARP Terrestrial Fluxes group, provides an introduction for each of the group members and shares behind-the scenes moments from the internship.

      Angelina De La Torre
      Using NDVI as a Proxy for GPP to Predict Carbon Dioxide Fluxes
      Angelina De La Torre
      Climate change, driven primarily by greenhouse gases, poses a threat to the future of our planet. Among these gases is carbon dioxide (CO₂), which has a much longer atmospheric residence time compared to other greenhouse gases. One potential factor in reducing atmospheric CO₂ enrichment is plant productivity. Gross Primary Productivity (GPP) estimates the amount of CO₂ fixed during photosynthesis. The Normalized Difference Vegetation Index (NDVI) provides insight into the health of an ecosystem by measuring the density and greenness of vegetation. Therefore, it can be inferred that there is a relationship between NDVI and GPP, as greener plants are likely more productive. In this study, we used NDVI as a proxy for GPP and analyzed the effect NDVI had on CO₂ fluxes during California’s wet season between January and March 2023 in a restored tidal freshwater wetland. GPP and CO₂ flux data were obtained from the Dutch Slough AmeriFlux tower in Oakley, California. Landsat data were used to calculate the average NDVI. The influence of NDVI on GPP was assessed using linear regression. A second linear regression was then performed using NDVI and CO₂ flux, of which GPP is one component. We anticipate that wetlands with greater vegetation density will have lower CO₂ emissions.

      Because Landsat data scans in 16-day intervals, daily variation in NDVI could not be observed. This translates to a frequency discrepancy between the Landsat and AmeriFlux data, as AmeriFlux towers measure in half-hour intervals. Additionally, the wet season represented was limited by data availability, as the data before 2023 were unavailable. Despite data limitations in this study, the outlined process could be repeated in various wetland and climate classifications for further analysis of a larger sample size. This study could assist in developing strategies to increase CO₂ sequestration in an attempt to slow the effects of climate change.

      Samarth Jayadev
      Using Machine Learning to Assess Relationships between NDVI and Net Carbon Exchange During the COVID-19 Pandemic
      Samarth Jayadev
      Understanding the movement of carbon between Earth’s land surface and atmosphere is essential for ecosystem monitoring, creating climate change mitigation strategies, and assessing the carbon budget on national to global scales. Measures of greenness serve as indicators of processes such as photosynthesis that control carbon exchange and are vital in modeling of carbon fluxes. NASA’s Orbiting Carbon Observatory (OCO-2) provides high quality measurements of column-averaged CO₂ concentrations that can be used to derive net carbon exchange (NCE), a measure of CO₂ flux between terrestrial ecosystems and the atmosphere.
      From OCO-2, NCE data collected at the land nadir, land glint satellite position combined with in situ sampling can provide accurate measurements on a 1°x1° scale suitable for carbon flux characterization across the contiguous United States (CONUS). Normalized difference vegetation index (NDVI), which ranges from -1 to +1, measures the greenness of vegetation, serving as an indicator of plant density and health. This can help to understand ecosystem to carbon-cycle interactions and be leveraged for determining patterns with NCE. We examined the relationship between NDVI and NCE across CONUS during 2020 using Gradient Boosting Decision Trees (GBDT) which specialize in classifying and predicting non-linear relationships. This algorithm takes multiple weak learners (decision trees) and combines their predictions in an iterative ensemble method to improve prediction accuracy. Feature and permutation importance tests found that January and August (trough and peak NDVI, respectively) were the highest weighted predictor variables related to NCE. The dataset was split in a 90% training 10% test ratio across latitude/longitude grid cells to assess and verify model performance. Using the mean squared error loss function and hyperparameters with optimal estimators, tree depth, sample split, and learning rate the algorithm was able to converge the test predictions to match the deviance of the training data. The gradient boosting model can be applied to different months and years of NDVI/NCE to further explore these relationships or a multitude of research questions. Further studies should consider integrating land use and land cover change variables such as bare land and urbanization to improve predictions of NCE.

      Makai Ogoshi
      Deep-learning Derived Spaceborne Canopy Structural Metrics Predict Forest Carbon Fluxes
      Makai Ogoshi
      Terrestrial and airborne lidar data products describing canopy structure are potent predictors of forest carbon fluxes, but whether satellite data products produce similarly robust indicators of canopy structure is not known. The assessment of contemporary spaceborne lidar and other remote sensing data products as predictors of carbon fluxes is crucial to next generation instrument and data product design and large-spatial scale modeling. We investigated relationships between deciduous broadleaf forest canopy structure, derived from deep-learning models created with lidar data from GEDI and optical imagery from Sentinel-2, and forest carbon exchange. These included comparisons to in-situ continuous net ecosystem exchange (NEE), gross primary production (GPP), and net primary production (NPP). We find that the mean  canopy height from the gridded spaceborne product has a strong correlation with forest NPP, similar to prior analysis with ground-based lidar (portable canopy lidar; PCL). For comparison to NPP, heights taken from the gridded spaceborne product were compared by overlapping the product with nine terrestrial forest sites from the National Ecological Observatory Network (NEON). We used standard deviation of canopy height as a measure of canopy structural complexity. Complexity derived from the gridded spaceborne product does not show the same strong correlation with NPP as found when using PCL. Mean annual GPP and NEE across five years were compared to the gridded spaceborne product at six Fluxnet2015-tower sites with continuous, gap-filled carbon flux data. When compared to in-situ flux tower data, neither mean canopy height nor structural complexity strongly correlate to annual NEE or GPP. Primarily, the finding that derived spaceborne products exhibit a strong correlation between forest canopy height and NPP will advance global-scale application of forest-carbon flux predictions. Secondarily, a variety of limitations highlight shortcomings in the current terrestrial flux data network. A small number of available study sites, both spatially and temporally, and lack of resolution in vertical complexity of canopy structure both contribute to uncertainty in assessing the relationships to NEE and GPP.

      Sebastian Reed
      Porewater Methane Concentrations Vary Significantly Across A Freshwater Tidal Wetland
      Sebastian Reed
      Methane is a potent greenhouse gas that is over 80 times more powerful than CO₂ at trapping heat and accounts for an estimated 30% of global temperature rise associated with climate change. The largest natural source of methane worldwide is wetlands. Despite the role of methane in driving climate change, the magnitude of global annual wetland methane flux remains highly uncertain. This study analyzes the effects of greenness (assessed using Normalized Difference Vegetation Index; NDVI), plant species composition, rooting depth, atmospheric methane concentration, and plant longevity on porewater methane concentration at the Kimages Rice Rivers Center tidal freshwater wetland. Samples for atmospheric and porewater concentrations were conducted in situ in June 2024. For each sampling location (n = 23) we collected whole air samples (WAS) 2m above the marsh surface and porewater samples 5cm below the marsh surface. We visually assessed species composition at each sample location, with 12 species of wetland plants present overall. We used the TRY plant database to find the rooting depth, leaf nitrogen content, and lifespan of each species. Drone multispectral data from 2023 was used to estimate NDVI values. These variables were compared to the pore water methane concentration via stepwise linear regression. Leaf N content, NDVI, plant species, and WAS sampling did not show statistically significant correlation to porewater methane concentration. Rooting depth showed a slight positive correlation with porewater methane (alpha = 0.1, p = 0.08, R^2 = 0.1). Samples with only perennial plants (as opposed to annual plants) had a higher mean value of porewater methane (p = 0.1). Analyzing porewater methane provides insight as to what wetland components affect methanogenesis and methane release, which aids in assessing which plant functional traits are most responsible for driving or mitigating climate change. Results from this study and future research in this area has the potential to more accurately assess how methane cycles through wetlands to the atmosphere.

      Nohemi Rodarte
      Understanding the vertical profile of CO₂ concentration: How carbon dioxide levels change with altitude
      Nohemi Rodarte
      Carbon dioxide (CO₂) is one of the main greenhouse gasses that contribute to global warming.While the relationship between CO₂ concentrations and land cover types, such as forests and urban areas, is well documented, there is limited knowledge of how CO₂ concentrations vary with altitude at fine spatial scales. Guided by our hypothesis that CO₂ levels vary with altitude and increase with elevation, we used airborne data collected from the B200 aircraft, which flew at different altitudes (400 to 1200 feet) above the urban area of Hopewell, Virginia, between 9:40 AM and 10:40 AM. We analyzed the CO₂ concentrations recorded by the flight to obtain the median and range for each 100 feet of altitude. Our results reveal that carbon dioxide concentrations varied significantly across the range of altitudes investigated. Within the area studied, CO₂ concentrations were found to range between 410 and 470 ppm. The distribution of these concentrations along the altitude gradient shows a bimodal pattern, with notable peaks at altitudes of 700 to 800 feet and 1100 to 1200 feet. Although CO₂ levels were present at all measured altitudes, there was a noticeable drop in the mean concentration at 800 feet,which then stabilized until reaching 1,000 feet before rising again. This pattern indicates that the concentrations of this greenhouse gas are not uniformly distributed with altitude, but rather vary significantly, showing higher concentrations at certain elevations and lower concentrations at others. The CO₂ distribution fluctuates with altitude, showing higher or lower levels at specific heights rather than a smooth gradient, indicating that altitude impacts CO₂ concentrations. While we did not identify the drivers of this change, future studies could evaluate how factors such as surface emissions, atmospheric mixing, and local conditions may contribute to vertical CO₂ profiles, since the altitudes we considered in this research are within the troposphere.

      Camille Shaw
      Linking NDVI with CO₂ and CH₄ Fluxes: Insights into Vegetation and Urban Source-Sink Dynamics in the Great Dismal Swamp
      Camille Shaw
      In recent years, carbon dioxide, methane, and other greenhouse gases have gained attention because of their contribution to the rise in Earth’s global mean temperature. Methane and carbon dioxide have various sources and sinks, but an expanding array of sources have created a need to assess ongoing change in carbon balance. This study aims to quantify the relationship between Normalized Difference Vegetation Index, or NDVI, and methane and carbon dioxide fluxes. We measured carbon dioxide and methane concentrations within the boundary layer using the PICARRO instrument, focusing on the Great Dismal Swamp, a forested wetland, and surrounding areas in the Eastern Mid-Atlantic Region. Data collection occurred at various times of day and along different flight paths in 2016, 2017, and 2024, with each year representing data from a single season, either spring or fall, for temporal analysis. We calculated methane and carbon dioxide fluxes along the flight paths using airborne eddy covariance, a method for capturing accurate flux measurements while accounting for the mixing of gases in the boundary layer caused by heat. Additionally, we calculated NDVI for this area using NASA’s Landsat 8 and 9 satellite imagery. Analysis of the afternoon flight data revealed a negative linear correlation between NDVI and carbon dioxide flux. Urban areas, characterized by low NDVI, exhibit a positive carbon dioxide flux as a consequence of emissions from vehicles, while forested areas, with high NDVI, show a negative carbon dioxide flux because of photosynthesis. In contrast, methane flux shows minimal correlation with NDVI. The lack of correlation arises because forested wetlands, with high NDVI, emit substantial amounts of methane, while urban areas, despite having low NDVI, still produce significant methane emissions from landfills and industrial activities. Future research could further investigate how seasonal and diurnal variations influence the correlations between NDVI and greenhouse gases by collecting comprehensive data across all seasons within a given year and at various times of the day.

      Return to 2024 SARP Closeout Share
      Details
      Last Updated Nov 22, 2024 Related Terms
      General Explore More
      8 min read SARP East 2024 Ocean Remote Sensing Group
      Article 21 mins ago 10 min read SARP East 2024 Atmospheric Science Group
      Article 21 mins ago 10 min read SARP East 2024 Hydroecology Group
      Article 21 mins ago View the full article
    • By NASA
      NASA has awarded Bastion Technologies Inc., of Houston, the Center Occupational Safety, Health, Medical, System Safety and Mission Assurance Contract (COSMC) at the agency’s Ames Research Center in California’s Silicon Valley.
      The COSMC contract is a hybrid cost-plus-fixed-fee and firm-fixed-price contract, with an indefinite-delivery/indefinite-quantity component and maximum potential value of $53 million. The contract phase-in begins Thursday, Jan. 2, 2025, followed by a one-year base period that begins Feb. 14, 2025, and options to extend performance through Aug. 13, 2030.
      Under this contract, the company will provide support for occupational safety, industrial hygiene, health physics, safety and health training, emergency response, safety culture, medical, wellness, fitness, and employee assistance. The contractor also will provide subject matter expertise in several areas including system safety, software safety and assurance, quality assurance, pressure system safety, procurement quality assurance, and range safety. Work will primarily be performed at NASA Ames and NASA’s Armstrong Flight Research Center in Edwards, California, as needed.
      For information about NASA and agency programs, visit:
      https://www.nasa.gov
      -end-
      Tiernan Doyle
      NASA Headquarters, Washington
      202-358-1600
      tiernan.p.doyle@nasa.gov
      Rachel Hoover
      Ames Research Center, Silicon Valley, Calif.
      650-604-4789
      rachel.hoover@nasa.gov
      View the full article
    • By NASA
      2 Min Read Why NASA Is a Great Place to Launch Your Career 
      Students at NASA's Jet Propulsion Laboratory pose for photos around the laboratory wearing their eclipse glasses. Credits: NASA/JPL-Caltech  Recently recognized as the most prestigious internship program by Vault.com, NASA has empowered countless students and early-career professionals to launch careers in science, technology, engineering, and mathematics (STEM) fields. NASA interns make real contributions to space and science missions, making it one of the best places to start your career. 
      “NASA internships give students the chance to work on groundbreaking projects alongside experts, providing impactful opportunities for professional growth,” said Mike Kincaid, associate administrator for NASA’s Office of STEM Engagement. “Since starting my career as an intern at NASA’s Johnson Space Center in Houston, I’ve experienced firsthand how NASA creates lasting connections and open doors—not just for me, but for former interns who are now colleagues across the agency. These internships build STEM skills, confidence, and networks, preparing the next generation of innovators and leaders.” 
      NASA interns achieve impressive feats, from discovering new exoplanets to becoming astronauts and even winning Webby Awards for their science communication efforts. These valuable contributors play a crucial role in NASA’s mission to explore the unknown for the benefit of all. Many NASA employees start their careers as interns, a testament to the program’s lasting impact. 
      Students congratulate the 23rd astronaut class at NASA’s Johnson Space Center in Houston on March 5, 2024.NASA/Josh Valcarcel Additionally, NASA is recognized as one of America’s Best Employers for Women and one of America’s Best Employers for New Graduates by Forbes, reflecting the agency’s commitment to fostering a diverse and inclusive environment. NASA encourages people from underrepresented groups to apply, creating a diverse cohort of interns who bring a wide range of perspectives and ideas to the agency.  
      “My internship experience has been incredible. I have felt welcomed by everyone I’ve worked with, which has been so helpful as a Navajo woman as I’ve often felt like an outsider in male-dominated STEM spaces,” said Tara Roanhorse, an intern for NASA’s Office of STEM Engagement. 
      If you’re passionate about space, technology, and making a difference in the world, NASA’s internship program is the perfect place to begin your journey toward a fulfilling and impactful career.  
      To learn more about NASA’s internship programs, visit: https://www.intern.nasa.gov/ 
      Keep Exploring Discover More STEM Topics From NASA
      For Colleges and Universities
      For Students Grades 9-12
      Join Artemis
      Learning Resources
      View the full article
    • By Space Force
      SSC and USC partnered up to pair USC Trojans with SSC Guardians to work within real USSF programs. This partnership team acted as a “living laboratory” to identify strategies for implementing agile development into complex defense projects.

      View the full article
  • Check out these Videos

×
×
  • Create New...