The Goes-r Series: A New Generation of Geostationary Environmental Satellites

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THE GOES-R
SERIES:

A New Generation of Geostationary
Environmental Satellites
Copyright
Contributors
Preface
Acknowledgments
Abbreviations and Acronyms
1
GOES-R Series Introduction
	References
2
History of Geostationary Weather Satellites
	The Early Days
	Other Nations Join In
	Evolving GOES
		The GOES Sounder
	Advanced Geo Imagers
	High Spectral Resolution Geo Sounders
	The Future
	Acknowledgments
	References
	Further Reading
3
GOES-R Series Spacecraft and Instruments
	GOES-R Mission History and Overview
	GOES-R Series Space Segment Overview
	Advanced Baseline Imager
	Geostationary Lightning Mapper
	Extreme Ultraviolet and X-ray Irradiance Sensors
	Solar Ultraviolet Imager
	Space Environment In Situ Suite
	Magnetometer
	Communications Payloads
	Acknowledgments
	References
4
ABI Imagery from the GOES-R Series
	Introduction
	Imagery
		Visible Spectral Bands
		Near-IR Spectral Bands
		IR Spectral Bands
	Future Enhancements
	Summary
	Acknowledgments
	References
	Further Reading
5
Red-Green-Blue Composites from the GOES-R Series ABI
	Introduction
	Scaling and Simple RGBs
	Advanced RGBs
	Summary
	Acknowledgments
	References
	Further Reading
6
ABI Cloud Products from the GOES-R Series
	Introduction
	Products and Their Physical Basis
		Cloud Detection
		Applications: Radiance Assimilation for NWP
		Cloud Height
		Application: Generation of Target Heights for Cloud-Drift Winds
		Daytime Cloud Optical Properties
		Applications: Solar Energy Estimation
	Future Enhancements
		Use of Native Resolution to Detect Partly Cloudy 2-km Pixels
		Use of Native Resolution for Cloud Detection
	Fog Detection and Characterization
	Summary
	Acknowledgments
	References
	Further Reading
7
ABI Legacy Atmospheric Profiles and Derived Products from the GOES-R Series
	Introduction
	LAP Algorithm
		The Generalized Least Squares Regression
		The Physical Retrieval Algorithm
		Derived Products
	Product Validation
		Legacy Vertical Temperature/Moisture Profiles
		Total Precipitable Water
		Derived Instability Indices
	Applications to Weather Forecasting
		A North Dakota/Minnesota storm case on June 21, 2017
		A Nebraska/Iowa Storm Case on June 29, 2017
		An Illinois Storm Case on July 10, 2017
	Future Enhancements
	Summary
	Acknowledgments
	References
	Further Reading
8
Winds from ABI on the GOES-R Series
	Introduction
	GOES-R ABI Winds Algorithm
		Target Selection
		Feature Tracking
		Height Assignment
		Quality Control
	ABI Winds Product
	Validation and Evaluation of GOES-16 Winds
	Future Enhancements and Applications
	Summary
	Acknowledgments
	References
	Further Reading
9
GOES-R Series Applications to Hurricane Monitoring
	Introduction
	Advanced Applications to TC Monitoring
		Center Fixing
		Intensity Estimation and Rapid Structure Changes
		Environmental Wind Fields
		Lightning Trends
		Sea Surface Temperatures (SSTs)
		The Saharan Air Layer (SAL)
		Other Environmental Analyses
	Summary
	Acknowledgments
	References
	Further Reading
10
Remote Sensing of Volcanic Ash with the GOES-R Series
	Introduction
	Overview of GOES-R Measurement Capabilities
		Advanced Baseline Imager
		Geostationary Lightning Mapper
	Qualitative Applications: GOES-R vs GOES-NOP
	Quantitative Applications: The GOES-R Baseline Product Suite
	Quantitative Applications: The VOLcanic Cloud Analysis Toolkit
	Summary and Conclusions
	Acknowledgments
	References
11
Rainfall Rates from the GOES-R Series
	Introduction
	Rainfall Rate Algorithm Description
	Rainfall Rate Algorithm Performance
	Future Enhancements
	Summary
	Acknowledgments
	References
	Further Reading
12
Land Surface Temperature Product from the GOES-R Series
	Introduction
	GOES-R ABI LST Algorithm
		Mission Requirement
		ABI LST Algorithm
	ABI LST Product
	Validation and Evaluation
		In Situ LST Observations
		Data Matchup and Quality Control Procedures
		Validation Results and Analysis
		LST Inter-Sensor Comparison
	Future Enhancements
	Summary
	Acknowledgments
	References
	Further Reading
13
Monitoring Fires with the GOES-R Series
	Monitoring Fires from Geostationary Orbit
	Physics of Fire Detection
	The Algorithm
	Using ABI L1b Imagery and L2 Fire Detection and Characterization Data for Fire Monitoring
	Validating Satellite Fire Products
	Summary and Looking Ahead
	Acknowledgments
	References
	Further Reading
14
Snow and Ice Products from ABI on the GOES-R Series
	Introduction
	Fractional Snow Cover
	Ice Surface Temperature
	Ice Concentration
	Ice Thickness and Age
	Ice Motion
	Summary
	Acknowledgments
	References
	Further Reading
15
Shortwave Radiation from ABI on the GOES-R Series
	Introduction
	Shortwave Radiation Products
	The GOES-R SRB Algorithm
	Evaluation of GOES-16 DSR and RSR
	Possible Enhancements
	Summary
	Acknowledgments
	References
16
Lightning Detection: GOES-R Series Geostationary Lightning Mapper
	Introduction
	GLM Observations
		GLM Detection Methods
		GLM Data Quality
	GLM Applications
		GLM Distributions
		GLM Gridded Products
	Future Work
	Acknowledgments
	References
	Further Reading
17
Air Quality Applications of ABI Aerosol Products from the GOES-R Series
	Introduction
	Aerosol Detection Product (ADP) Algorithm
	Aerosol Optical Depth (AOD) Algorithm
	Pixel Screening
	GeoColor Imagery
	Dust RGB Imagery
	Validation of GOES-16 Aerosol Products
	Air Quality Applications: A Case Study of Fire/Smoke Event on August 16, 2018
	Future Enhancements
	Summary
	Acknowledgments
	References
18
GOES-R Series Solar Dynamics
	Introduction
		Solar Drivers of Space Weather
		The GOES-R Solar Ultraviolet Imager (SUVI)
	SUVI Imagery and Level 1b Data Products
		SUVI’s View of the Sun
		SUVI Level 1 Data Products
	Level 2 Products
		High Dynamic Range Composite Images
		SUVI Thematic Maps
		Bright Region, Flare Location, and Coronal Hole Reports
		Other Image-Based SUVI L2 Products
		Acknowledgments
	References
19
GOES-R Series Solar X-ray and Ultraviolet Irradiance
	Introduction
	X-ray Measurements and Products
		Irradiances
		Daily Background
		Event Detection
		Flare Location
	EUV Measurements and Products
		EUVS Calibrations and Degradation Tracking
		EUVS Event Detection
		Magnesium II Index
		EUV Proxy Spectrum
	Summary
	Acknowledgments
	References
20
The GOES-R Space Environment In Situ Suite (SEISS): Measurement of Energetic Particles in Geospace
	Introduction
	Magnetospheric Particle Sensor—Low Energy (MPS-LO)
	Magnetospheric Particle Sensor—High Energy (MPS-HI)
	Solar and Galactic Proton Sensor (SGPS)
	Energetic Heavy Ion Sensor
	Level 1b (L1b) Processing and Data Products
	Level 2 (L2) Algorithms and Data Products
	GOES Data in Support of Space Science Research
	Acknowledgments
	References
21
Magnetic Field Observations from the GOES-R Series
	Introduction
	Observing the Geomagnetic Field at GEO
	Data Products
		Processing Levels
		One-Minute Averages
		Geomagnetic Field in Alternative Coordinates
		Quiet-Field Model
		Geosynchronous Magnetopause Crossing Detection
			Algorithm Overview
			Algorithm Outputs
	Conclusions
	Acknowledgments
	References
	Further Reading
22
GOES-R Series Data Access and Dissemination
	Introduction
	Product Generation, Access, and Dissemination Framework
	GOES-R Series Operational Product Dissemination Paths
		GOES Rebroadcast (GRB) to Direct Broadcast (DB) Users
		Product Distribution and Access (PDA)
		High Rate Information Transmission (HRIT)/Emergency Managers Weather Information Network (EMWIN)
		GEONETCast Americas (GNC-A)
		NOAA’s Comprehensive Large Array-Data Stewardship System (CLASS)
		AWIPS SBN/NOAAPort
		GOES Image Viewer is a Public-Facing Website Maintained by STAR
	Other Sources of GOES-R Products
		Websites
		University Corporation for Atmospheric Research (UCAR)/Unidata
		NOAA’s Big Data Project
	The GOES-R Series User Community and User-Based Partnerships
	Summary
	Acknowledgments
	References
	Additional Webpages
	Further Reading
23
GOES-R Series Summary and Look Ahead
	Summary
	A Look Ahead
	Acknowledgments
	References
Index
	A
	B
	C
	D
	E
	F
	G
	H
	I
	J
	K
	L
	M
	N
	O
	P
	Q
	R
	S
	T
	U
	V
	W
	X
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