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A 30+ Year AVHRR Land Surface Reflectance Climate Data Record and Its Application to Wheat Yield Monitoring (2017)

Murphy, Emilie ; Becker-Reshef, Inbal ; Franch, Belen ; [et al.]

In: CASI

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Publication Date: 2019-05-21

Description: The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing dataset that ranges from the 1980's to the present. Over the years, several efforts have been made on the calibration of the different instruments to establish a consistent land surface reflectance time-series and to augment the AVHRR data record with data from other sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS). In this paper, we present a summary of all the corrections applied to the AVHRR Surface Reflectance and NDVI Version 4 Product, developed in the framework of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) program. These corrections result from assessment of the geo-location, improvement of the cloud masking and calibration monitoring. Additionally, we evaluate the performance of the surface reflectance over the AERONET sites by a cross-comparison with MODIS, which is an already validated product, and evaluation of a downstream Leaf Area Index (LAI) product. We demonstrate the utility of this long time-series by estimating the winter wheat yield over the USA. The methods developed by [1] and [2] are applied to both the MODIS and AVHRR data. Comparison of the results from both sensors during the MODIS-era shows the consistency of the dataset with similar errors of 10%. When applying the methods to AVHRR historical data from the 1980's, the results have errors equivalent to those derived from MODIS.

Keywords: Earth Resources and Remote Sensing

Type: GSFC-E-DAA-TN40735 , Remote Sensing (e-ISSN 2072-4292); 9; 3; 296

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Near Real-Time Use of Optical Remote Sensing and Synthetic Aperture Radar for Response to Central U.S. Flooding in Late April-Early May 2017 (2017)

Meyer, Franz J. ; Molthan, Andrew ; Schultz, Lori A. ; [et al.]

In: CASI

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Publication Date: 2019-07-13

Description: No abstract available

Keywords: Earth Resources and Remote Sensing

Type: MSFC-E-DAA-TN50300 , American Geophysical Union (AGU) 2017 Fall Meeting; Dec 11, 2017 - Dec 15, 2017; New Orleans, LA; United States

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Optimal A-Train Data Utilization: A Use Case of Aura OMI L2G and MERRA-2 Aerosol Products (2017)

Meyer, David J. ; Wei, Jennifer ; Shen, Suhung ; [et al.]

In: CASI

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Publication Date: 2019-08-13

Description: Ozone Monitoring Instrument (OMI) aboard NASA's Aura mission measures ozone column and profile, aerosols, clouds, surface UV irradiance, and the trace gases including NO2, SO2, HCHO, BrO, and OClO using UltraViolet electromagnetic spectrum (280 - 400 nm) with a daily global coverage and a pixel spatial resolution of 13 km 24 km at nadir, and it's been one of the key instruments to study the Earth's atmospheric composition and chemistry. The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is NASA's atmospheric reanalysis using an upgraded version of Goddard Earth Observing System Model, version 5 (GEOS-5) data assimilation system. Compared to its predecessor MERRA, MERRA-2 is enhanced with more aspects of the Earth system among which is aerosol assimilation. When comparing between satellite pixel measurements and modeled grid data, how to properly handle counterpart pairing is critical considering their spatial and temporal variations. The comparison between satellite and model data by simply using Level 3 (L3) products may result biases due to lack of detailed temporal information. It has been preferred to inter-compare or implement satellite derived physical quantity (i.e., Level 2 (L2) Swath type) directly with/to model measurements with higher temporal and spatial resolution as possible. However, this has posed a challenge in the community to handle. Rather than directly handling the L2 or L3 data, there is a Level 2G (L2G) product conserving L2 pixel scientific data quality but in Grid type with the global coverage. In this presentation, we would like to demonstrate the optimal utilization of OMI L2G daily aerosol products by comparing with MERRA-2 hourly aerosol simulations matched well in both space and time.

Keywords: Earth Resources and Remote Sensing

Type: GSFC-E-DAA-TN42520 , International A-Train Symposium; Apr 19, 2017 - Apr 21, 2017; Pasadena, CA; United States

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Recovering Nimbus Era Observations at the NASA GES DISC (2017)

Johnson, J. ; Gerasimov, I. ; Esfandiari, A. ; [et al.]

In: CASI

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Publication Date: 2019-07-13

Description: Between 1964 and 1978, NASA launched a series of seven Nimbus meteorological satellites which provided Earth observations for 30 years. These satellites, carrying a total of 33 instruments to observe the Earth at visible, infrared, ultraviolet, and microwave wavelengths, revolutionized weather forecasting, provided early observations of ocean color and atmospheric ozone, and prototyped location-based search and rescue capabilities. The Nimbus series paved the way for a number of currently operational systems such as the EOS (Earth Observation System) Terra, Aqua, and Aura platforms. The original data archive includes both magnetic tapes and film media. These media are well past their expected end of life, placing at risk valuable data that are critical to extending the history of Earth observations back in time. GES DISC (Goddard Earth Sciences Data and Information Services Center) has been incorporating these data into a modern online archive by recovering the digital data files from the tapes, and scanning images of the data from film strips. The digital data products were written on obsolete hardware systems in outdated file formats, and in the absence of metadata standards at that time, were often written in proprietary file structures. Through a tedious and laborious process, oft-corrupted data are recovered, and incomplete metadata and documentation are reconstructed.

Keywords: Earth Resources and Remote Sensing

Type: AGU Paper IN23D-0111 , GSFC-E-DAA-TN50514 , AGU Fall Meeting 2017; Dec 11, 2017 - Dec 15, 2017; New Orleans, LA; United States

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