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NASA NTRS2022

Using commercial high-resolution satellite imagery to monitor a nuisance macroalga in the largest marine protected area in the U.S.A.

Satellite imagery is a useful tool for monitoring and mapping the distribution of invasive or nuisance algal species on coral reefs over the temporal and spatial scales needed for ecosystem management. Visual inspections of high-resolution satellite imagery were used to detect the newly discovered nuisance alga, Chondria tumulosa , at Manawai (Pearl and Hermes Atoll) in combination with ground-truthing surveys. Low-albedo (“dark”) survey sites on spur habitats were associated with mean C. tumulosa cover seven times higher than adjacent high-albedo (“light”) sites. There was an inverse relationship between C. tumulosa percent cover at ground-truthing sites and mean reflectance values. Archival satellite imagery showed that areas of high C. tumulosa cover (i.e., dark patches) were not evident on or before 2015 on the northeast backreef. This case study is the first to apply satellite imagery to target a nuisance red macroalgal bloom on a coral reef. The ability to use satellites for the detection of nuisance or invasive benthic species, such as expansive mats of C. tumulosa , provides managers with a valuable tool, especially in remote regions.

Invasive↗

NASA NTRSDate not supplied

Comparing Low-Cost Sensors with Ground-Based and Airborne In-Situ and Column Observations of NO2 and HCHO during the FRAPPE Field Campaign in Colorado, USA

Even in the presence of more reliable air quality tools, low-cost sensors have the benefit of recording data on highly localized spatial and temporal scales, allowing for multiple measurements within a single satellite pixel and on pixel boundaries. However, they are less accurate than their regulatory-grade counterparts, requiring regular co-locations with accepted instruments to ensure their validity. Thus, the addition of low-cost sensors to a field campaign – where reference-grade air quality instruments are abundant – not only provides ample opportunities for low-cost sensor co-location and calibration, but also allows the low-cost instruments to be used for sub-pixel validation, covering more surface area than the regulatory instruments alone with a network of sensors. During the summer of 2014, our low-cost sensor network was deployed during the Front Range Air Pollution and Photochemistry Experiment (FRAPPÉ) campaign conducted to sample the composition of air at and above ground level in northeastern Colorado, USA. The low-cost sensor platform included a suite of gas-phase sensors, notably NO2 and two generalized volatile organic compound (VOC) sensors, which were leveraged together to quantify speciated hydrocarbons such as formaldehyde. These key pollutants were chosen for their impacts on human health and climate change, as well as their inclusion on the TEMPO satellite launching this year. Airborne campaign measurements included slant column optical observations of formaldehyde (HCHO), nitrogen dioxide (NO2), and ozone (O3). Myriad additional in-situ instruments described chemical composition up to approximately 5 km above surface level. Ground-based instrumentation included both stationary and mobile regulatory-grade instruments, which were used for sensor calibration. Machine learning techniques such as artificial neural networks (ANNs) were used to match the low-cost signals to that of the reference-grade instruments. Here, we compare calibrated low-cost sensor data collected at ground level in a variety of locations along Colorado’s Front Range to various data sources from the FRAPPÉ campaign to better understand how well airborne and regulatory ground-based measurements can be extrapolated to other locations. Further, as the slant column measurements act as satellite simulators, we explore how low-cost instruments can be used for satellite validation purposes. Comparisons among these different data types also have important implications in data fusion.

Kristen Okorn↗

NASA NTRS2022

Dayside Transient Phenomena and Their Impact on the Magnetosphere and Ionosphere

Dayside transients, such as hot flow anomalies, foreshock bubbles, magnetosheath jets, flux transfer events, and surface waves, are frequently observed upstream from the bow shock, in the magnetosheath, and at the magnetopause. They play a significant role in the solar wind-magnetosphere-ionosphere coupling. Foreshock transient phenomena, associated with variations in the solar wind dynamic pressure, deform the magnetopause, and in turn generates field-aligned currents (FACs) connected to the auroral ionosphere. Solar wind dynamic pressure variations and transient phenomena at the dayside magnetopause drive magnetospheric ultra low frequency (ULF) waves, which can play an important role in the dynamics of Earth’s radiation belts. These transient phenomena and their geoeffects have been investigated using coordinated in-situ spacecraft observations, spacecraft-borne imagers, ground-based observations, and numerical simulations. Cluster, THEMIS, Geotail, and MMS multi-mission observations allow us to track the motion and time evolution of transient phenomena at different spatial and temporal scales in detail, whereas ground-based experiments can observe the ionospheric projections of transient magnetopause phenomena such as waves on the magnetopause driven by hot flow anomalies or flux transfer events produced by bursty reconnection across their full longitudinal and latitudinal extent. Magnetohydrodynamics (MHD), hybrid, and particle-in-cell (PIC) simulations are powerful tools to simulate the dayside transient phenomena. This paper provides a comprehensive review of the present understanding of dayside transient phenomena at Earth and other planets, their geoeffects, and outstanding questions.

Bow shock↗

NASA NTRS2023

Ocean Carbon From Space: Current Status and Priorities for the Next Decade

The ocean plays a central role in modulating the Earth’s carbon cycle. Monitoring how the ocean carbon cycle is changing is fundamental to managing climate change. Satellite remote sensing is currently our best tool for viewing the ocean surface globally and systematically, at high spatial and temporal resolutions, and the past few decades have seen an exponential growth in studies utilising satellite data for ocean carbon research. Satellite-based observations must be combined with in-situ observations and models, to obtain a comprehensive view of ocean carbon pools and fluxes. To help prioritise future research in this area, a workshop was organised that assembled leading experts working on the topic, from around the world, including remote-sensing scientists, field scientists and modellers, with the goal to articulate a collective view of the current status of ocean carbon research, identify gaps in knowledge, and formulate a scientific roadmap for the next decade, with an emphasis on evaluating where satellite remote sensing may contribute. A total of 449 scientists and stakeholders participated (with balanced gender representation), from North and South America, Europe, Asia, Africa, and Oceania. Sessions targeted both inorganic and organic pools of carbon in the ocean, in both dissolved and particulate form, as well as major fluxes of carbon between reservoirs (e.g., primary production) and at interfaces (e.g., air-sea and land–ocean). Extreme events, blue carbon and carbon budgeting were also key topics discussed. Emerging priorities identified include: expanding the networks and quality of in-situ observations; improved satellite retrievals; improved uncertainty quantification; improved understanding of vertical distributions; integration with models; improved techniques to bridge spatial and temporal scales of the different data sources; and improved fundamental understanding of the ocean carbon cycle, and of the interactions among pools of carbon and light. We also report on priorities for the specific pools and fluxes studied, and highlight issues and concerns that arose during discussions, such as the need to consider the environmental impact of satellites or space activities; the role satellites can play in monitoring ocean carbon dioxide removal approaches; economic valuation of the satellite based information; to consider how satellites can contribute to monitoring cycles of other important climatically-relevant compounds and elements; to promote diversity and inclusivity in ocean carbon research; to bring together communities working on different aspects of planetary carbon; maximising use of international bodies; to follow an open science approach; to explore new and innovative ways to remotely monitor ocean carbon; and to harness quantum computing. Overall, this paper provides a comprehensive scientific roadmap for the next decade on how satellite remote sensing could help monitor the ocean carbon cycle, and its links to the other domains, such as terrestrial and atmosphere.

oceanography↗

NASA NTRSDate not supplied

Linking Individual Variation in Movement Behavior to Infection Dynamics in Highly Mobile Species

Animal movements are linked to infectious disease dynamics in wildlife through multiple mechanisms across various spatial and temporal scales. For example, infections can impede the movement of infected individuals, but infected hosts can also disperse infectious agents as they move. Individuals inevitably vary in their responses to infections and their roles in determining infection dynamics, which means that considering variation among individuals – whether across species, across time, or within populations – is important for understanding movement-disease relationships and their implications for epidemiology. Here, I draw on studies from multiple systems to examine how variation in movement behavior links to infectious disease epidemiology. For example, a comparative study of habitat selection across multiple waterfowl species highlights that diel behavioral patterns, rather than individual or seasonal variation, is the most important driver of the risk of overlap between waterfowl and poultry farms, and therefore for the risk of avian influenza spillover. Together, these studies show that individual traits interact with the environment to influence the roles of individuals for infectious disease ecology.

Claire Stewart Teitelbaum↗

NASA NTRS2023

PACE Technical Report Series, Volume 11: The PACE Postlaunch Airborne eXperiment (PACE-PAX)

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE; https://pace.gsfc.nasa.gov) mission is NASA's latest and greatest effort to study the ocean-atmosphere system and build upon the legacy of previous satellite missions that have revolutionized our understanding of our home planet. By using advanced radiometric and polarimetric instruments to measure ocean color and key atmospheric variables, PACE aims to provide new insights into the complex interactions between the ocean, atmosphere, and biosphere. This information will be critical for improving our ability to model and predict changes in the Earth's climate, as well as to manage and conserve our planet's valuable natural resources. Performance assessments and science data product validation is a critical process for any Earth Science space-borne mission, as it involves assessing and verifying the quality of the data products generated by the mission while it is in orbit, as well as assigning uncertainties to these retrievals. More specifically, validation efforts are essential for assessing the accuracy of instrument data and the derived science products across varied spatial and temporal scales and ensuring their reliability and consistency with the mission's scientific goals and objectives. The overall plan for validation of PACE data is described in “PACE Science Data Product Validation Plan” (see, e.g., https://pace.gsfc.nasa.gov), and among range of post-launch activities, it describes the need and requirements for a post-launch airborne field campaign in support of PACE validation. This volume outlines the plans and requirements of the PACE Postlaunch Airborne eXperiment (PACE-PAX). The main goal of PACE-PAX is to gather validation and assessment data for the PACE mission, using a variety of airborne and ground-based assets. These assets will be coordinated to obtain complementary measurements of key ocean and atmospheric variables, such as ocean color, aerosols, and clouds. By collecting data from multiple sources, PACE-PAX will help to validate and refine the data products generated by the PACE mission, as well as to identify any potential errors or biases in the measurements. This will be essential for ensuring the accuracy and reliability of the PACE data products, and for maximizing the scientific value of the mission.

Kirk D Knobelspiesse↗

NASA NTRSDate not supplied

The Third Flight of the Marshall Grazing Incidence X-Ray Spectrometer (MaGIXS-3)

The Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) is the first X-ray slitless imaging spectrograph sounding rocket instrument designed to observe spectrally dispersed soft X-ray images of the solar corona over a wide field-of-view. During the first flight of MaGIXS (MaGIXS-1), occurred on 30 July 2021, several emission lines from coronal structures including X-ray bright points were observed. Further, MaGIXS-1 analysis also demonstrated the successful inversion of overlappograms using robust unfolding algorithms. Given the demonstrated success of MaGIXS-1, the second flight of the instrument with a simplified optical design, MaGIXS-2, is scheduled for 2024 to observe high temperature diagnostic emission lines. Results from MaGIXS-1 discovered dominant missing emission lines near 15A, arising from relatively cool plasma that peaks around 2 MK. This wavelength region hosts several closely spaced satellite lines of Fe XVII, Fe XVI and Fe XV ions, which are expected to be enhanced at lower temperatures and are currently unmodeled in the CHIANTI atomic database. This wavelength region offers one of the most unique diagnostics to measure electron temperature, as well as signatures of equilibrium state of the plasma in active regions, which has not been studied so far. The goal of MaGIXS-3 mission is the to determine coronal heating parameters, such as the spatial and temporal properties of coronal heating events, by measuring discriminating observations, such as electron temperature, effective temperature, density, abundance, and departures from thermal equilibrium of the plasma, by observing the Sun in the SXR wavelength range. To meet this goal, the MaGIXS instrument will be upgraded with a new X-ray telescope mirror that will provide higher spatial and spectral resolution and throughput, allowing for spectral lines to be observed at the relevant spatial and temporal scales. In addition, MaGIXS-3 will also carry The Resolving Inversion Context X-ray Spectrometer (TRICXS), a high dispersion Bragg crystal spectrometer to spectrally resolve the lines near 14.9 to 15.9A, critical to unlock the full diagnostic potential of this wavelength range. Here we will present the preliminary concept design of MaGIXS-3 and discuss the potential observations.

X-ray Imaging↗

NASA NTRSDate not supplied

NASA’s Geospace Dynamics Constellation—Providing the first Systematic Measurements of Global Magnetospheric Energy Inputs and Ionosphere-Thermosphere Responses

The Geospace Dynamics Constellation (GDC) is NASA's next strategic Living With a Star mission. GDC's goals are: 1) Understand how the high-latitude ionosphere-thermosphere system responds to variable solar wind/magnetosphere forcing; and 2) Understand how internal processes in the global ionosphere-thermosphere system redistribute mass, momentum, and energy. Planned for launch by the end of the decade, GDC will use six identical observatories, each identically instrumented to fully characterize the magnetospheric drivers of the I-T system as well as the global response of the ionized and neutral gases. GDC will do this with a series of orbital configurations that will enable it to study the widest range of spatial and temporal scales to date, ranging from hundreds of kilometers and several seconds to tens of minutes, and extending through the regional to the global scale. This talk presents GDC's current status, measurement capabilities, sampling scheme, and model development efforts and show how GDC will fit into the larger Heliophysics ecosystem, by 1) obtaining critically needed scientific observations; 2) providing a source for real-time space weather and situational awareness, as well as retrospective studies to further the science of space weather; 3) serving as a "strategic hub" for other space-based and ground-based efforts that want to leverage GDC to perform complementary science. To get the most benefit from GDC’s observations, it will be critical to identify partnerships with other research efforts in the ITM and Geospace arenas, including those utilizing space-based, ground-based, or theoretical investigations. We particularly would like to discuss with groups who are planning or considering observational campaigns during the GDC era, to find ways to leverage GDC observations to do synergistic science that could not be done otherwise.

Douglas E Rowland↗

NASA NTRSDate not supplied

The Next Generation Marshall Grazing Incidence X-Ray Spectrometer (MaGIXS) Sounding Rocket Experiments

The Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) is a sounding rocket experiment that carries an X-ray slitless imaging spectrograph to observe spectrally dispersed soft X-ray (SXR) images of the solar corona over a wide field-of-view. The first flight of MaGIXS occurred on 30 July 2021, during which several emission lines from coronal structures including X-ray bright points were observed. Analysis of MaGIXS-1 data demonstrated the application of new inversion techniques and opened a new arena of inverting complex spectroheliogram data, which has spatial-spectral information overlapped. The second flight of MaGIXS, with a simplified optical design, is scheduled for 2024. The goal of MaGIXS-2 is to observe high temperature diagnostic emission lines within an active region core. MaGIXS-1 discovered dominant missing emission lines near 15Å wavelength region, which hosts several closely spaced satellite lines of Fe XVII, Fe XVI, and Fe XV ions, arising from relatively cool plasma that peaks near 2MK. These lines are expected to be enhanced at lower temperatures and offers one of the most unique diagnostics to measure electron temperature, as well as signatures of equilibrium state of the plasma in active regions, which has not been studied so far. The science goal of the third sounding rocket flight of MaGIXS is to determine coronal heating parameters, such as the spatial and temporal properties of coronal heating events, by measuring discriminating observations, such as electron temperature, effective temperature, density, abundance, and departures from thermal equilibrium of the plasma, by observing the Sun in the SXR wavelength range. For this, the MaGIXS instrument will be upgraded with a new X-ray telescope mirror that will provide higher spatial and spectral resolution and throughput, allowing for spectral lines to be observed at the relevant spatial and temporal scales. In addition, MaGIXS-3 will also carry The Resolving Inversion Context X-ray Spectrometer (TRICXS), a high dispersion Bragg crystal spectrometer to spectrally resolve the lines near 15Å, critical to unlock the full diagnostic potential of this wavelength range. Here we will present the preliminary concept design of MaGIXS-3 and discuss the potential observations.

X-ray Imaging↗

NASA NTRS2024

Northern Brazil Agriculture: Measuring Soybean Yields in Northern Brazil During El Niño-Southern Oscillation Conditions to Evaluate Trends in Agricultural Production and Support Crop Forecasting, 1984 – 2023

As one of the largest agricultural exporters in the world, Brazil’s crop productivity is highly influential to the world’s food supply. Crop productivity across Brazil is heavily influenced by climatic factors, such as the El Niño-Southern Oscillation (ENSO), which drives spatially heterogenous effects on growing conditions. To understand the relationship between ENSO conditions and staple crop productivity, the team used 1984 – 2023 climatic data and vegetation indices for four Brazilian states: Bahia, Mato Grosso, Pará, and Tocantins. The team focused on soybean growing areas in each state derived from annual land use/land cover classifications. Monthly mean Normalized Difference Vegetation Index (NDVI) per state were calculated using multispectral imagery from the Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imagery (OLI) sensors. In addition, the team used crop production indices, ENSO anomalies, temperature, and precipitation data in this study. The team found that although monthly ENSO anomaly did have a positive relationship between temperature and a slight negative relationship with precipitation, ENSO and monthly soy NDVI were not significantly correlated. Results find no association between ENSO conditions and NDVI in the study area at the state level spatial resolution during the study period. Furthermore, the team found that there was no correlation between cumulative growing season soy NDVI and detrended soy production yield for this study region at the spatial and temporal scale of the analysis. Findings from this project will be used by the United States Department of Agriculture’s Foreign Agriculture Service to inform crop productivity forecasting.

remote sensing↗

NASA NTRSDate not supplied

Isolator Shock Train Response to Dual-Mode Scramjet Throttling-Like Forcing

Typical dual-mode scramjet designs employ an isolator component situated between the inlet and combustor. The isolator fluidically buffers the inlet from the combustor via the formation of a shock train, an interconnected series of shock-boundary layer interactions. The isolator is required during ramjet-engine operation and at the lower edges of the scramjet operational envelope. In an operational engine, transient behavior imposes fluidic dynamics due to attitude adjustments, combustor throttling, aberrant resonances within the combustor, etc. To accommodate these transients, the shock train adjusts on both temporal and spatial scales. Sufficiently large downstream pressure increases in the combustor play a critical role during unstart, whereby strong compression waves propagate upstream in the isolator to ultimately force the shock train out the inlet, if it cannot stabilize to the pressure increase. This critically reduces the engine mass flow rate, potentially causing a catastrophic reduction in thrust and loss of the vehicle. A nearly instantaneous unstart can, in principle, be predicted by a ratio of the normal shock pressure jump in an inviscid isolator. However, lower-magnitude perturbations, below this bound, also induce unstarts. Understanding the transient behavior inherent in unsteady isolator operation is critical to reducing safety margin in isolator length and refining engine control algorithms to improve engine performance. The Isolator Dynamics Research Lab (IDRL) is a cold-flow, direct-connect isolator facility ideal for assessing the fundamental fluid dynamics of shock trains. The internal flow of a scramjet isolator is modeled using a 2D, symmetric Mach 2.5 nozzle followed by a 695 mm long, 25.4x50.8 mm rectangular isolator test section. A blockage cone on a high-speed ball screw actuator downstream of the isolator is pulsed to simulate the throttling behavior in an operational combustor. Wall flush high-speed static pressure transducers detect the streamwise shock train within the isolator. Time delays between the onset of the throttling and the response motion of the shock train are analyzed to assess the controlling scales and parameters. From this analysis, the response time of the isolator shock train system is found to depend primarily on the isolator back pressure time-rate-of-change but quickly saturates to a maximum propagation speed along the isolator. These results inform dual-mode scramjet engine designers of the critical parameters and limits of an unstart resistant engine.

scramjet↗

NASA NTRSDate not supplied

Firesense: Supporting Operational Partners Through Co-Development

Fire is a natural disturbance and fundamental to many ecosystems, but, across the United States and many areas globally, fires have become more common, larger and more likely to occur at the same time. This has the potential to challenge resource allocation and response and requires coordinated integration of technology and tools at the spatial and temporal scales required by practitioners who make wildland fire management decisions. In the US wildfire is currently managed across state, federal, and tribal agencies who leverage various datasets to guide management decisions. FireSense, a NASA Science Mission Directorate project, aims to develop and deliver trailblazing technology and tools for use before, during, and after wildland fires by working together with land managers and practitioners. FireSense is focused on turning information into solutions by expanding partnerships and collaborations with operational agencies to inform and deliver data and technology to support decisions for wildland fire management. Through implementation across the US and with campaign activities in a variety of landscapes, coordinated research and development work will build upon adaptive and use-inspired approaches that can be put into operation. By leveraging and complementing partner activities through coordinated investment, we support a more comprehensive and cohesive response that can advance fire science to better understand fire behavior and effects through integrated measurement, monitoring and modeling. We present updates from in-progress technology development and field campaigns within the US which include sampling and application across scales with information from multiple sensors collocated with field measurements and highlighting the importance of cross-scale observations during the fire lifecycle. Coordinated investment in new science and technology for the complete fire lifecycle supports a comprehensive and cohesive fire response that help to overcome barriers and anticipate and manage the new reality of extreme fires in a warming world.

Jacquelyn Shuman↗

NASA NTRS2005

Remote Sensing of Particulate Organic Carbon Pools in the High-Latitude Oceans

The general goal of this project was to characterize spatial distributions at basin scales and variability on monthly to interannual timescales of particulate organic carbon (POC) in the high-latitude oceans. The primary objectives were: (1) To collect in situ data in the north polar waters of the Atlantic and in the Southern Ocean, necessary for the derivation of POC ocean color algorithms for these regions. (2) To derive regional POC algorithms and refine existing regional chlorophyll (Chl) algorithms, to develop understanding of processes that control bio-optical relationships underlying ocean color algorithms for POC and Chl, and to explain bio-optical differentiation between the examined polar regions and within the regions. (3) To determine basin-scale spatial patterns and temporal variability on monthly to interannual scales in satellite-derived estimates of POC and Chl pools in the investigated regions for the period of time covered by SeaWiFS and MODIS missions.

Stramski, Dariusz↗

NASA NTRS2010

Usefulness of AIRS-Derived OLR, Temperature, Water Vapor and Cloudiness Anomaly Trends for GCM Validation

Mainly due to their global nature, satellite observations can provide a very useful basis for GCM validations. In particular, satellite sounders such as AIRS provide 3-D spatial information (most useful for GCMs), so the question arises: can we use AIRS datasets for climate variability assessments? We show that the recent (September 2002 February 2010) CERES-observed negative trend in OLR of approx.-0.1 W/sq m/yr averaged over the globe is found in the AIRS OLR data as well. Most importantly, even minute details (down to 1 x 1 degree GCM-scale resolution) of spatial and temporal anomalies and trends of OLR as observed by CERES and computed based on AIRS-retrieved surface and atmospheric geophysical parameters over this time period are essentially the same. The correspondence can be seen even in the very large spatial variations of these trends with local values ranging from -2.6 W/sq m/yr to +3.0 W/sq m/yr in the tropics, for example. This essentially perfect agreement of OLR anomalies and trends derived from observations by two different instruments, in totally independent and different manners, implies that both sets of results must be highly accurate, and indirectly validates the anomalies and trends of other AIRS derived products as well. These products show that global and regional anomalies and trends of OLR, water vapor and cloud cover over the last 7+ years are strongly influenced by EI-Nino-La Nina cycles . We have created climate parameter anomaly datasets using AIRS retrievals which can be compared directly with coupled GCM climate variability assessments. Moreover, interrelationships of these anomalies and trends should also be similar between the observed and GCM-generated datasets, and, in cases of discrepancies, GCM parameterizations could be improved based on the relationships observed in the data. First, we assess spatial "trends" of variability of climatic parameter anomalies [since anomalies relative to the seasonal cycle are good proxies of climate variability] at the common 1x1 degree GCM grid-scale by creating spatial anomaly "trends" based on the first 7+ years of AIRS Version 5 Leve13 data. We suggest that modelers should compare these with their (coupled) GCM's performance covering the same period. We evaluate temporal variability and interrelations of climatic anomalies on global to regional e.g., deep Tropical Hovmoller diagrams, El-Nino-related variability scales, and show the effects of El-Nino-La Nina activity on tropical anomalies and trends of water vapor cloud cover and OLR. For GCMs to be trusted highly for long-term climate change predictions, they should be able to reproduce findings similar to these. In summary, the AIRS-based climate variability analyses provide high quality, informative and physically plausible interrelationships among OLR, temperature, humidity and cloud cover both on the spatial and temporal scales. GCM validations can use these results even directly, e. g., by creating 1x1 degree trendmaps for the same period in coupled climate simulations.

Molnar, Gyula I.↗

NASA NTRS1986

The intercomparison of ozone measured from the SME and Nimbus-7 satellites on short and long time scales

The spatial and temporal characteristics of ozone density measured from the SBUV (Solar Backscatter Ultraviolet) spectrometer on Nimbus-7 and the UV and the UV and the IR spectrometers on SME (Solar Mesosphere Explorer) are compared in the altitude region near 50 km where the three data sets overlap. Their temporal characteristics, when averaged over the same longitude range, are remarkably similar with respect to seasonal variations and short term fluctuations induced by transient planetary waves. The long term trends in the three data sets, however, differ significantly with each other. Over the three year period after 1982 ozone mixing ratio at 1 mb decreased by about 10 percent based on SEUV measurements but increased by 12 and 30 percent respectively based on SME-IR and SME-UV measurements. None of these estimates are consistent with the predicted decrease of about 2 percent based on solar UV flux and temperature changes during this period.

Chandra, S.↗

NASA NTRS2012

New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.

Ott, L.↗

NASA NTRS2000

Simple and Multiple Endmember Mixture Analysis in the Boreal Forest

Roberts, Dar A.↗

NASA NTRS2001

AVIRIS Land-Surface Mapping in Support of the Boreal Ecosystem-Atmosphere Study (BOREAS)

A key scientific objective of the original Boreal Ecosystem-Atmospheric Study (BOREAS) field campaign (1993-1996) was to obtain the baseline data required for modeling and predicting fluxes of energy, mass, and trace gases in the boreal forest biome. These data sets are necessary to determine the sensitivity of the boreal forest biome to potential climatic changes and potential biophysical feedbacks on climate. A considerable volume of remotely-sensed and supporting field data were acquired by numerous researchers to meet this objective. By design, remote sensing and modeling were considered critical components for scaling efforts, extending point measurements from flux towers and field sites over larger spatial and longer temporal scales. A major focus of the BOREAS follow-on program is concerned with integrating the diverse remotely sensed and ground-based data sets to address specific questions such as carbon dynamics at local to regional scales. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has the potential of contributing to BOREAS through: (1) accurate retrieved apparent surface reflectance; (2) improved landcover classification; and (3) direct assessment of biochemical/biophysical information such as canopy liquid water and chlorophyll concentration through pigment fits. In this paper, we present initial products for major flux tower sites including: (1) surface reflectance of dominant cover types; (2) a land-cover classification developed using spectral mixture analysis (SMA) and Multiple Endmember Spectral Mixture Analysis (MESMA); and (3) liquid water maps. Our goal is to compare these land-cover maps to existing maps and to incorporate AVIRIS image products into models of photosynthetic flux.

Roberts, Dar A.↗