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  • 2020-2023  (29)
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  • 1
    Publication Date: 2022-05-16
    Description: Remote imaging spectroscopy, also known as hyperspectral imaging, uses Radiative Transfer Models (RTMs) to predict the measured radiance spectrum for a specific surface and atmospheric state. Discrepancies between RTM assumptions and physical reality can cause systematic errors in surface property estimates. We present a statistical method to quantify these model errors without invoking ground reference data. Our approach exploits scene invariants — properties of the environment which are stable over space or time — to estimate RTM discrepancies. We describe techniques for discovering these features opportunistically in flight data. We then demonstrate data-driven methods that estimate the aggregate errors due to model discrepancies without having to explicitly identify the underlying physical mechanisms. The resulting distributions can improve posterior uncertainty predictions in operational retrievals.
    Type: info:eu-repo/semantics/article
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  • 2
    Publication Date: 2022-01-10
    Description: Changes in electron flux in Earth's outer radiation belt can be modeled using a diffusion‐based framework. Diffusion coefficients D for such models are often constructed from statistical averages of observed inputs. Here, we use stochastic parameterization to investigate the consequences of temporal variability in D. Variability time scales are constrained using Van Allen Probe observations. Results from stochastic parameterization experiments are compared with experiments using D constructed from averaged inputs and an average of observation‐specific D. We find that the evolution and final state of the numerical experiment depends upon the variability time scale of D; experiments with longer variability time scales differ from those with shorter time scales, even when the time‐integrated diffusion is the same. Short variability time scale experiments converge with solutions obtained using an averaged observation‐specific D, and both exhibit greater diffusion than experiments using the averaged‐input D. These experiments reveal the importance of temporal variability in radiation belt diffusion.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 3
    Publication Date: 2022-07-25
    Description: Future global Visible Shortwave Infrared Imaging Spectrometers, such as the Surface Biology and Geology (SBG) mission, will regularly cover the Earth's entire terrestrial land area. These missions need high fidelity atmospheric correction to produce consistent maps of terrestrial and aquatic ecosystem traits. However, estimation of surface reflectance and atmospheric state is computationally challenging, and the terabyte data volumes of global missions will exceed available processing capacity. This article describes how missions can overcome this bottleneck using the spatial continuity of atmospheric fields. Contemporary imaging spectrometers oversample atmospheric spatial variability, so it is not necessary to invert every pixel. Spatially sparse solutions can train local linear emulators that provide fast, exact inversions in their vicinity. We find that estimating the atmosphere at 200 m scales can outperform traditional atmospheric correction, improving speed by one to two orders of magnitude with no measurable penalty to accuracy. We validate performance with an airborne field campaign, showing reflectance accuracies with RMSE of 1.1% or better compared to ground measurements of diverse targets. These errors are statistically consistent with retrieval uncertainty budgets. Local emulators can close the efficiency gap and make rigorous model inversion algorithms feasible for global missions such as SBG.
    Type: info:eu-repo/semantics/article
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  • 4
    Publication Date: 2022-03-10
    Description: Snow and ice melt processes on the Greenland Ice Sheet are a key in Earth’s energy balance and are acutely sensitive to climate change. Melting dynamics are directly related to a decrease in surface albedo, amongst others caused by the accumulation of light-absorbing particles (LAPs). Featuring unique spectral patterns, these accumulations can be mapped and quantified by imaging spectroscopy. We present first results for the retrieval of glacier ice properties from the spaceborne PRISMA imaging spectrometer by applying a recently developed simultaneous inversion of atmospheric and surface state using optimal estimation. The image analyzed in this study was acquired over the South-West margin of the Greenland Ice Sheet in late August 2020. The area is characterized by patterns of both clean and dark ice associated with a high amount of LAPs deposited on the surface. We present retrieval maps and uncertainties for grain size, liquid water, and algae concentration, as well as estimated reflectance spectra for different surface properties. We then show the feasibility of using imaging spectroscopy to interpret multiband sensor data to achieve high accuracy, frequently repeated observations of changing snow and ice conditions. For example, the impurity index calculated from multiband Sentinel-3 OLCI measurements is dependent on dust particles, but we show that algae concentration alone can be predicted from this data with less than 20 % uncertainty. Our study evidence that present and upcoming orbital imaging spectroscopy missions such as PRISMA, EnMAP, CHIME, and the SBG designated observable, can significantly support research of melting ice sheets.
    Type: info:eu-repo/semantics/article
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  • 5
    Publication Date: 2022-08-05
    Description: Snow and ice melt processes are a key in Earth's energy-balance and hydrological cycle. Their quantification facilitates predictions of meltwater runoff as well as distribution and availability of fresh water. They control the balance of the Earth's ice sheets and are acutely sensitive to climate change. These processes decrease the surface reflectance with unique spectral patterns due to the accumulation of liquid water and light absorbing particles (LAP), that require imaging spectroscopy to map and measure. Here we present a new method to retrieve snow grain size, liquid water fraction, and LAP mass mixing ratio from airborne and spaceborne imaging spectroscopy acquisitions. This methodology is based on a simultaneous retrieval of atmospheric and surface parameters using optimal estimation (OE), a retrieval technique which leverages prior knowledge and measurement noise in an inversion that also produces uncertainty estimates. We exploit statistical relationships between surface reflectance spectra and snow and ice properties to estimate their most probable quantities given the reflectance. To test this new algorithm we conducted a sensitivity analysis based on simulated top-of-atmosphere radiance spectra using the upcoming EnMAP orbital imaging spectroscopy mission, demonstrating an accurate estimation performance of snow and ice surface properties. A validation experiment using in-situ measurements of glacier algae mass mixing ratio and surface reflectance from the Greenland Ice Sheet gave uncertainties of ±16.4 μg/gice and less than 3%, respectively. Finally, we evaluated the retrieval capacity for all snow and ice properties with an AVIRIS-NG acquisition from the Greenland Ice Sheet demonstrating this approach's potential and suitability for upcoming orbital imaging spectroscopy missions.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 6
    Publication Date: 2022-05-25
    Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Jacox, M. G., Alexander, M. A., Siedlecki, S., Chen, K., Kwon, Y., Brodie, S., Ortiz, I., Tommasi, D., Widlansky, M. J., Barrie, D., Capotondi, A., Cheng, W., Di Lorenzo, E., Edwards, C., Fiechter, J., Fratantoni, P., Hazen, E. L., Hermann, A. J., Kumar, A., Miller, A. J., Pirhalla, D., Buil, M. P., Ray, S., Sheridan, S. C., Subramanian, A., Thompson, P., Thorne, L., Annamalai, H., Aydin, K., Bograd, S. J., Griffis, R. B., Kearney, K., Kim, H., Mariotti, A., Merrifield, M., & Rykaczewski, R. Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments. Progress in Oceanography, 183, (2020): 102307, doi:10.1016/j.pocean.2020.102307.
    Description: Marine ecosystem forecasting is an area of active research and rapid development. Promise has been shown for skillful prediction of physical, biogeochemical, and ecological variables on a range of timescales, suggesting potential for forecasts to aid in the management of living marine resources and coastal communities. However, the mechanisms underlying forecast skill in marine ecosystems are often poorly understood, and many forecasts, especially for biological variables, rely on empirical statistical relationships developed from historical observations. Here, we review statistical and dynamical marine ecosystem forecasting methods and highlight examples of their application along U.S. coastlines for seasonal-to-interannual (1–24 month) prediction of properties ranging from coastal sea level to marine top predator distributions. We then describe known mechanisms governing marine ecosystem predictability and how they have been used in forecasts to date. These mechanisms include physical atmospheric and oceanic processes, biogeochemical and ecological responses to physical forcing, and intrinsic characteristics of species themselves. In reviewing the state of the knowledge on forecasting techniques and mechanisms underlying marine ecosystem predictability, we aim to facilitate forecast development and uptake by (i) identifying methods and processes that can be exploited for development of skillful regional forecasts, (ii) informing priorities for forecast development and verification, and (iii) improving understanding of conditional forecast skill (i.e., a priori knowledge of whether a forecast is likely to be skillful). While we focus primarily on coastal marine ecosystems surrounding North America (and the U.S. in particular), we detail forecast methods, physical and biological mechanisms, and priority developments that are globally relevant.
    Description: This study was supported by the NOAA Climate Program Office’s Modeling, Analysis, Predictions, and Projections (MAPP) program through grants NA17OAR4310108, NA17OAR4310112, NA17OAR4310111, NA17OAR4310110, NA17OAR4310109, NA17OAR4310104, NA17OAR4310106, and NA17OAR4310113. This paper is a product of the NOAA/MAPP Marine Prediction Task Force.
    Keywords: Prediction ; Predictability ; Forecast ; Ecological forecast ; Mechanism ; Seasonal ; Interannual ; Large marine ecosystem
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 7
    Publication Date: 2022-02-16
    Description: Muography uses muons naturally produced in the interactions between cosmic rays and atmosphere for imaging and characterization of density differences and time-sequential changes in solid (e.g. rocks) and liquid (e.g. melts±dissolved gases) materials in scales from tens of metres to up to a few kilometres. In addition to being useful in discovering the secrets of the pyramids, ore prospecting and surveillance of nuclear sites, muography successfully images the internal structure of volcanoes. Several field campaigns have demonstrated that muography can image density changes relating to magma ascent and descent, magma flow rate, magma degassing, the shape of the magma body, an empty conduit diameter, hydrothermal activity and major fault lines. In addition, muography is applied for longterm volcano monitoring in a few selected volcanoes around the world. We propose using muography in volcanomonitoring in conjunction with other existing techniques for predicting volcanic hazards. This approach can provide an early indication of a possible future eruption and potentially the first estimate of its scale by producing direct evidence of magma ascent through its conduit in real time. Knowing these issues as early as possible buy critically important time for those responsible for the local alarm and evacuation protocols.
    Description: Published
    Description: 20210320
    Description: 2V. Struttura e sistema di alimentazione dei vulcani
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 8
    Publication Date: 2022-02-24
    Description: In the last 10 yr, the International Atomic Energy Agency (IAEA) revised its safety standards for site evaluations of nuclear installations in response to emerging fault displacement hazard evaluation practices developed in Member States. New amendments in the revised safety guidance (DS507) explicitly recommend fault displacement hazard assessment, including separate approaches for candidate new sites versus existing sites. If there is insufficient basis to conclusively determine that a fault is not capable of surface displace- ment at an existing site, then a probabilistic fault displacement hazard analysis (PFDHA) is recommended to better characterize the hazard. This new recommendation has generated the need for the IAEA to provide its Member States with guidance on performing PFDHA, including its formulation and implementation. This article provides an overview of current PFDHA state-of-practice for nuclear installations that is consistent with the new IAEA safety standards. We also summarize progress in an ongoing international PFDHA bench- mark project that will ultimately provide technical guidance to Member States for con- ducting site-specific fault displacement hazard assessments.
    Description: Published
    Description: 2661–2672
    Description: 6T. Studi di pericolosità sismica e da maremoto
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 9
    Publication Date: 2022-10-26
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Clayton, S., Alexander, H., Graff, J. R., Poulton, N. J., Thompson, L. R., Benway, H., Boss, E., & Martiny, A. Bio-GO-SHIP: the time is right to establish global repeat sections of ocean biology. Frontiers in Marine Science, 8, (2022): 767443, https://doi.org/10.3389/fmars.2021.767443.
    Description: In this article, we present Bio-GO-SHIP, a new ocean observing program that will incorporate sustained and consistent global biological ocean observations into the Global Ocean Ship-based Hydrographic Investigations Program (GO-SHIP). The goal of Bio-GO-SHIP is to produce systematic and consistent biological observations during global ocean repeat hydrographic surveys, with a particular focus on the planktonic ecosystem. Ocean plankton are an essential component of the earth climate system, form the base of the oceanic food web and thereby play an important role in influencing food security and contributing to the Blue Economy. Despite its importance, ocean biology is largely under-sampled in time and space compared to physical and chemical properties. This lack of information hampers our ability to understand the role of plankton in regulating biogeochemical processes and fueling higher trophic levels, now and in future ocean conditions. Traditionally, many of the methods used to quantify biological and ecosystem essential ocean variables (EOVs), measures that provide valuable information on the ecosystem, have been expensive and labor- and time-intensive, limiting their large-scale deployment. In the last two decades, new technologies have been developed and matured, making it possible to greatly expand our biological ocean observing capacity. These technologies, including cell imaging, bio-optical sensors and 'omic tools, can be combined to provide overlapping measurements of key biological and ecosystem EOVs. New developments in data management and open sharing can facilitate meaningful synthesis and integration with concurrent physical and chemical data. Here we outline how Bio-GO-SHIP leverages these technological advances to greatly expand our knowledge and understanding of the constituents and function of the global ocean plankton ecosystem.
    Description: The Bio-GO-SHIP pilot program was funded under the National Oceanographic Partnership Program as an inter-agency partnership between NOAA and NASA, with the US Integrated Ocean Observing System and NOAA's Global Ocean Monitoring and Observing program (HA, SC, JG, AM, and NP). HA was supported by a WHOI Independent Research and Development award. AM was supported by funding from NSF OCE-1848576 and 1948842 and NASA 80NSSC21K1654. JG was funded by NASA from grants 80NSSC17K0568 and NNX15AAF30G. LT was supported by award NA06OAR4320264 06111039 to the Northern Gulf Institute by NOAA's Office of Oceanic and Atmospheric Research, U.S. Department of Commerce.
    Keywords: Biological oceanography ; Plankton ecosystems ; Ocean observing ; Repeat hydrography ; GO-SHIP program
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 10
    Publication Date: 2022-10-27
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Rastetter, E., Kwiatkowski, B., Kicklighter, D., Plotkin, A., Genet, H., Nippert, J., O’Keefe, K., Perakis, S., Porder, S., Roley, S., Ruess, R., Thompson, J., Wieder, W., Wilcox, K., & Yanai, R. N and P constrain C in ecosystems under climate change: role of nutrient redistribution, accumulation, and stoichiometry. Ecological Applications, (2022): e2684, https://doi.org/10.1002/eap.2684.
    Description: We use the Multiple Element Limitation (MEL) model to examine responses of 12 ecosystems to elevated carbon dioxide (CO2), warming, and 20% decreases or increases in precipitation. Ecosystems respond synergistically to elevated CO2, warming, and decreased precipitation combined because higher water-use efficiency with elevated CO2 and higher fertility with warming compensate for responses to drought. Response to elevated CO2, warming, and increased precipitation combined is additive. We analyze changes in ecosystem carbon (C) based on four nitrogen (N) and four phosphorus (P) attribution factors: (1) changes in total ecosystem N and P, (2) changes in N and P distribution between vegetation and soil, (3) changes in vegetation C:N and C:P ratios, and (4) changes in soil C:N and C:P ratios. In the combined CO2 and climate change simulations, all ecosystems gain C. The contributions of these four attribution factors to changes in ecosystem C storage varies among ecosystems because of differences in the initial distributions of N and P between vegetation and soil and the openness of the ecosystem N and P cycles. The net transfer of N and P from soil to vegetation dominates the C response of forests. For tundra and grasslands, the C gain is also associated with increased soil C:N and C:P. In ecosystems with symbiotic N fixation, C gains resulted from N accumulation. Because of differences in N versus P cycle openness and the distribution of organic matter between vegetation and soil, changes in the N and P attribution factors do not always parallel one another. Differences among ecosystems in C-nutrient interactions and the amount of woody biomass interact to shape ecosystem C sequestration under simulated global change. We suggest that future studies quantify the openness of the N and P cycles and changes in the distribution of C, N, and P among ecosystem components, which currently limit understanding of nutrient effects on C sequestration and responses to elevated CO2 and climate change.
    Description: This material is based on work supported by the National Science Foundation under Grant No. 1651722 as well through the NSF LTER Program 1637459, 2220863 (ARC), 1637686 (NWT), 1832042 (KBS), 2025849 (KNZ), 1636476 (BNZ), 1637685 (HBR), 1832210 (HFR), 2025755 (AND). We also acknowledge NSF grants 1637653 and 1754126 (INCyTE RCN), and DOE grant DESC0019037. We also acknowledge support through the USDA Forest Service Hubbard Brook Experimental Forest, North Woodstock, New Hampshie (USDA NIFA 2019-67019-29464) and Pacific Northwest Research Station, Corvallis, Oregon.
    Keywords: Carbon dioxide fertilization ; Carbon sequestration ; Carbon-nitrogen interactions ; Carbon-phosphorus interactions ; Climate change ; Long-term ecological research (LTER) ; Nitrogen cycle ; Phosphorus cycle ; Terrestrial ecosystem stoichiometry
    Repository Name: Woods Hole Open Access Server
    Type: Article
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