4,565 research outputs found

    NASA GIBS and Worldview: Visualizing NASA's Earth Science Data for All to Explore

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    For more than 20 years, the NASA Earth Observing System (EOS) has operated dozens of remote sensing satellites collecting nearly 15 Petabytes of data that span thousands of science parameters. Within these observations are keys the Earth Scientists have used to unlock many discoveries that we now understand about our planet. Also contained within these observations are a myriad of opportunities for learning and education. The challenge is making them accessible to educators and students in intuitive and simple ways so that effort can be spent on lesson enrichment and not overcoming technical hurdles.The NASA Global Imagery Browse Services (GIBS) system and NASA Worldview interactive mapping site provide a unique view into EOS data through daily full resolution visualizations of hundreds of Earth science parameters. For many of these parameters, visualizations are available within hours of acquisition from the satellite. For others, visualizations are available for the entire mission of the satellite. Accompanying the visualizations are visual aids such as color legends, place names, and orbit tracks. By using these visualizations, educators and students can observe natural phenomena that enrich a scientific education.This presentation will provide an overview of the visualizations available in NASA GIBS and Worldview and how they are accessed. Specific attention will be given to the newer capabilities and accomplishments, including: Support for geostationary sub-daily visualizations, Enhanced support for vector-based visualizations, Improved Worldview tour and snapshot capabilities, New imagery products across a growing set of scientific areas

    Applying the Dark Target Aerosol Algorithm with Advanced Himawari Imager Observations During the KORUS-AQ Field Campaign

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    For nearly 2 decades we have been quantitatively observing the Earth's aerosol system from space at one or two times of the day by applying the Dark Target family of algorithms to polar-orbiting satellite sensors, particularly MODIS and VIIRS. With the launch of the Advanced Himawari Imager (AHI) and the Advanced Baseline Imagers (ABIs) into geosynchronous orbits, we have the new ability to expand temporal coverage of the traditional aerosol optical depth (AOD) to resolve the diurnal signature of aerosol loading during daylight hours. The KoreanUnited States Air Quality (KORUS-AQ) campaign taking place in and around the Korean peninsula during MayJune 2016 initiated a special processing of full-disk AHI observations that allowed us to make a preliminary adoption of Dark Target aerosol algorithms to the wavelengths and resolutions of AHI. Here,we describe the adaptation and show retrieval results from AHI for this 2-month period. The AHI-retrieved AOD is collocated in time and space with existing AErosol RObotic NETwork stations across Asia and with collocated Terra and Aqua MODIS retrievals. The new AHI AOD product matches AERONET, and the standard MODIS product does as well, and the agreement between AHI and MODIS retrieved AOD is excellent, as can be expected by maintaining consistency in algorithm architecture and most algorithm assumptions. Furthermore, we show that the new product approximates the AERONET-observed diurnal signature. Examining the diurnal patterns of the new AHI AOD product we find specific areas over land where the diurnal signal is spatially cohesive. For example, in Bangladesh the AOD in-creases by 0.50 from morning to evening, and in northeast China the AOD decreases by 0.25. However, over open ocean the observed diurnal cycle is driven by two artifacts, one associated with solar zenith angles greater than 70t hat may be caused by a radiative transfer model that does not properly represent the spherical Earth and the other artifact associated with the fringes of the 40 degree glint angle mask. This opportunity during KORUS-AQ provides encouragement to move towards an operational Dark Target algorithm for AHI. Future work will need to re-examine masking including snow mask, reevaluate assumed aerosol models for geosynchronous geometry, address the artifacts over the ocean, and investigate size parameter retrieval from the over-ocean algorithm

    Investigation into the use of satellite remote sensing data products as part of a multi-modal marine environmental monitoring network

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    In this paper it is investigated how conventional in-situ sensor networks can be complemented by the satellite data streams available through numerous platforms orbiting the earth and the combined analyses products available through services such as MyOcean. Despite the numerous benefits associated with the use of satellite remote sensing data products, there are a number of limitations with their use in coastal zones. Here the ability of these data sources to provide contextual awareness, redundancy and increased efficiency to an in-situ sensor network is investigated. The potential use of a variety of chlorophyll and SST data products as additional data sources in the SmartBay monitoring network in Galway Bay, Ireland is analysed. The ultimate goal is to investigate the ability of these products to create a smarter marine monitoring network with increased efficiency. Overall it was found that while care needs to be taken in choosing these products, there was extremely promising performance from a number of these products that would be suitable in the context of a number of applications especially in relation to SST. It was more difficult to come to conclusive results for the chlorophyll analysis

    The Research Unit VolImpact: Revisiting the volcanic impact on atmosphere and climate – preparations for the next big volcanic eruption

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    This paper provides an overview of the scientific background and the research objectives of the Research Unit “VolImpact” (Revisiting the volcanic impact on atmosphere and climate – preparations for the next big volcanic eruption, FOR 2820). VolImpact was recently funded by the Deutsche Forschungsgemeinschaft (DFG) and started in spring 2019. The main goal of the research unit is to improve our understanding of how the climate system responds to volcanic eruptions. Such an ambitious program is well beyond the capabilities of a single research group, as it requires expertise from complementary disciplines including aerosol microphysical modelling, cloud physics, climate modelling, global observations of trace gas species, clouds and stratospheric aerosols. The research goals will be achieved by building on important recent advances in modelling and measurement capabilities. Examples of the advances in the observations include the now daily near-global observations of multi-spectral aerosol extinction from the limb-scatter instruments OSIRIS, SCIAMACHY and OMPS-LP. In addition, the recently launched SAGE III/ISS and upcoming satellite missions EarthCARE and ALTIUS will provide high resolution observations of aerosols and clouds. Recent improvements in modeling capabilities within the framework of the ICON model family now enable simulations at spatial resolutions fine enough to investigate details of the evolution and dynamics of the volcanic eruptive plume using the large-eddy resolving version, up to volcanic impacts on larger-scale circulation systems in the general circulation model version. When combined with state-of-the-art aerosol and cloud microphysical models, these approaches offer the opportunity to link eruptions directly to their climate forcing. These advances will be exploited in VolImpact to study the effects of volcanic eruptions consistently over the full range of spatial and temporal scales involved, addressing the initial development of explosive eruption plumes (project VolPlume), the variation of stratospheric aerosol particle size and radiative forcing caused by volcanic eruptions (VolARC), the response of clouds (VolCloud), the effects of volcanic eruptions on atmospheric dynamics (VolDyn), as well as their climate impact (VolClim)

    MODIS: Moderate-resolution imaging spectrometer. Earth observing system, volume 2B

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    The Moderate-Resolution Imaging Spectrometer (MODIS), as presently conceived, is a system of two imaging spectroradiometer components designed for the widest possible applicability to research tasks that require long-term (5 to 10 years), low-resolution (52 channels between 0.4 and 12.0 micrometers) data sets. The system described is preliminary and subject to scientific and technological review and modification, and it is anticipated that both will occur prior to selection of a final system configuration; however, the basic concept outlined is likely to remain unchanged

    MODIS information, data and control system (MIDACS) level 2 functional requirements

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    The MODIS Information, Data and Control System (MIDACS) Level 2 Functional Requirements Document establishes the functional requirements for MIDACS and provides a basis for the mutual understanding between the users and the designers of the EosDIS, including the requirements, operating environment, external interfaces, and development plan. In defining the requirements and scope of the system, this document describes how MIDACS will operate as an element of the EOS within the EosDIS environment. This version of the Level 2 Requirements Document follows an earlier release of a preliminary draft version. The sections on functional and performance requirements do not yet fully represent the requirements of the data system needed to achieve the scientific objectives of the MODIS instruments and science teams. Indeed, the team members have not yet been selected and the team has not yet been formed; however, it has been possible to identify many relevant requirements based on the present concept of EosDIS and through interviews and meetings with key members of the scientific community. These requirements have been grouped by functional component of the data system, and by function within each component. These requirements have been merged with the complete set of Level 1 and Level 2 context diagrams, data flow diagrams, and data dictionary

    Aqua: AIRS, AMSU, HSB, AMSR-E, CERES, MODIS

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    This brochure provides an overview of the Aqua spacecraft, instruments, science, and data products Aqua, Latin for water, is a NASA Earth Science satellite mission named for the large amount of information that the mission is collecting about the Earth's water cycle, including evaporation from the oceans, water vapor in the atmosphere, clouds, precipitation, soil moisture, sea ice, land ice, and snow cover on the land and ice. Additional variables also measured by Aqua include radiative energy fluxes, aerosols, vegetation cover on the land, phytoplankton and dissolved organic matter in the oceans, and air, land, and water temperatures. Note: this guide was produced before Aqua was launched; for the most recent information on Aqua, go to http://aqua.nasa.gov. Educational levels: Undergraduate lower division, Undergraduate upper division, Graduate or professional, Informal education

    Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations

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    This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are madeIn this study Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua retrievals of aerosol optical thickness (AOT) at 555 nm are compared to Sun photometer measurements from Svalbard for a period of 9 years. For the 642 daily coincident measurements that were obtained, MODIS AOT generally varies within the predicted uncertainty of the retrieval over ocean (ΔAOT=±0.03±0.05·AOT). The results from the remote sensing have been used to examine the accuracy in estimates of aerosol optical properties in the Arctic, generated by global climate models and from in situ measurements at the Zeppelin station, Svalbard. AOT simulated with the Norwegian Earth System Model/Community Atmosphere Model version 4 Oslo global climate model does not reproduce the observed seasonal variability of the Arctic aerosol. The model overestimates clear-sky AOT by nearly a factor of 2 for the background summer season, while tending to underestimate the values in the spring season. Furthermore, large differences in all-sky AOT of up to 1 order of magnitude are found for the Coupled Model Intercomparison Project phase 5 model ensemble for the spring and summer seasons. Large differences between satellite/ground-based remote sensing of AOT and AOT estimated from dry and humidified scattering coefficients are found for the subarctic marine boundary layer in summer.Peer reviewe
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