SIFTing through satellite imagery with the Satellite Information Familiarization Tool

Gerth, Jordan J.; Garcia, Raymond K.; Hoese, David J.; Lindstrom, Scott S.; Schmit, Timothy J.

doi:10.15191/nwajom.2020.0810

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SIFTing through satellite imagery with the Satellite Information Familiarization Tool

2020
By Gerth, Jordan J. ; Garcia, Raymond K. ; Hoese, David J. ; ...
Source: Journal of Operational Meteorology, 8(10)

[PDF-2.86 MB]

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Details:

Journal Title:

Journal of Operational Meteorology
Personal Author:

Gerth, Jordan J. ; Garcia, Raymond K. ; Hoese, David J. ; Lindstrom, Scott S. ; Schmit, Timothy J.

Gerth, Jordan J. ; Garcia, Raymond K. ; Hoese, David J. ; Lindstrom, Scott S. ; Schmit, Timothy J. Less -
NOAA Program & Office:

CIMSS (Cooperative Institute for Meteorological Satellite Studies) ; NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research) ; NWS (National Weather Service) ; OBS (Office of Observations)

CIMSS (Cooperative Institute for Meteorological Satellite Studies) ; NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research) ; NWS (National Weather Service) ; OBS (Office of Observations) Less -
Description:

The Satellite Information Familiarization Tool (SIFT) is an open-source, multi-platform graphical user

interface designed to easily display spectral and temporal sequences of geostationary satellite imagery.

The Advanced Baseline Imager (ABI) and Advanced Himawari Imager (AHI) on the “new generation” of

geostationary satellites collect imagery with a spatial resolution four times greater than previously available.

Combined with the increased number of spectral bands and more frequent imaging, the new series imagers

collect approximately 60 times more data. Given the resulting large file sizes, the development of SIFT is a multiyear effort to make those satellite imagery data files accessible to the broad community of students, scientists,

and operational meteorologists. To achieve the objective of releasing software that provides an intuitive user

experience to complement optimum performance on consumer-grade computers, SIFT was built to leverage

modern graphics processing units (GPUs) through existing open-source Python packages, and runs on the three

major operating systems: Windows, Mac, and Linux. The United States National Weather Service funded the

development of SIFT to help enhance the satellite meteorology acumen of their operational meteorologists.

SIFT has basic image visualization capabilities and enables the fluid animation and interrogation of satellite

images, creation of Red-Green-Blue (RGB) composites and algebraic combinations of multiple spectral bands,

and comparison of imagery with numerical weather prediction output. Open for community development, SIFT

users and features continue to grow. SIFT is freely available with short tutorials and a user guide online. The

mandate for the software, its development, realized applications, and envisioned role in science and training

are explained.
Keywords:

[+]

Geostationary Satellites Satellite Meteorology
Source:

Journal of Operational Meteorology, 8(10)
DOI:

https://doi.org/10.15191/nwajom.2020.0810
Document Type:

Journal Article
Rights Information:

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Submitted
Main Document Checksum:

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urn:sha256:71033ddf10d6f3640f2f4f2ac271bd7db042eb4bfe383639fbf7840fa0527dc8
Download URL:

https://repository.library.noaa.gov/view/noaa/27700/noaa_27700_DS1.pdf
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SIFTing through satellite imagery with the Satellite Information Familiarization Tool

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