Visible Infrared Imager Radiometer Suite: A New Operational Cloud Imager

by Hutchison; Keith D.

• ISBN13: 9780415321297
• ISBN10: 0415321298
• Format: Hardcover
• Copyright: 2005-11-14
• Publisher: CRC Press

Summary

The Visible Infrared Imager Radiometer Suite (VIIRS) is the next-generation multispectral imaging instrument to fly on US operational, polar-orbiting meteorological satellites. VIIRS will gather data across 22 spectral bands and be used to create products for a variety of applications including weather forecasting and climate change studies. VIIRS consolidates the best features of heritage instruments, including near-constant resolution and nighttime visible imagery. Visible Infrared Imager Radiometer Suite: A New Operational Cloud Imager provides the first comprehensive guide on the design and exploitation of cloud data collected by the VIIRS.Expert researchers Hutchison and Cracknell discuss the fundamental principles necessary to interpret surface and cloud features in multispectral meteorological satellite imagery. They begin by tracing the evolution of satellite meteorology and detailing previous instruments on which VIIRS is based. Next, they examine the user requirements for VIIRS data products and the studies used to convert these requirements into sensor design parameters. The focus then shifts to the principles and techniques used to exploit VIIRS cloud data. The book ends with a comprehensive discussion of automated processes to retrieve 3-dimensional cloud fields from a variety of algorithms, some of which were developed for the VIIRS.Supplying material for both experienced researchers and those new to the field, Visible Infrared Imager Radiometer Suite is a must-read for anyone interested in evaluating and using the data gathered from the VIIRS project.

Table of Contents

Introduction	1	(20)
Satellite Meteorology	1	(1)
Overview of Numerical Weather Prediction Modeling	1	(1)
Evolution of Observational Data for Numerical Weather Prediction Modeling	2	(6)
Additional Applications of Meteorological Satellite Data	8	(13)
Sea Surface Temperature Analyses	9	(4)
Climate Modeling	13	(3)
Tropical Storm Monitoring	16	(1)
Satellite-Derived Wind Fields	17	(4)
Meteorological Satellite Systems	21	(34)
Evolution of Satellites and Sensors	21	(27)
Polar-orbiting Operational Environmental Satellite Systems	22	(3)
The Advanced TIROS-N Satellite Series	25	(4)
Defense Meteorological Satellite Program	29	(6)
NASA Earth Observing System Program	35	(5)
Other Polar-orbiting Meteorological Satellite Systems	40	(1)
The Proposed EUMETSAT Meteorological Operational Series	41	(2)
Geostationary Meteorological Satellite Systems	43	(5)
The National Polor-orbiting Operational Environmental Satellite System	48	(7)
VIIRS Imagery Design Analysis	55	(12)
VIIRS Environmental Data Record Requirements Overview	55	(1)
VIIRS Imagery Requirements	56	(2)
Cloud Applications-Related Imagery Requirements	58	(4)
Cloud Cover	60	(1)
Cloud Type	60	(2)
Value of Manually Generated Cloud Analyses	62	(5)
Performance Verification of Automated Cloud Models	62	(2)
Quality Control of Automated Cloud Analyses	64	(3)
VIIRS Imagery Requirements Analysis	67	(42)
Theoretical Basis for Manual Cloud Analyses	67	(4)
Overview of Approach to Instrument Design	71	(2)
Cloud Truth Data Sets to Flowdown Sensor Requirements	73	(6)
Cloud Truth from Manual Interpretation of Multispectral Imagery	74	(2)
Cloud Truth in Simulated Imagery	76	(3)
Derivation of Sensing Requirements from Analysis Requirements	79	(7)
Overview of VIIRS Hardware Design	86	(23)
VIIRS Sensor Overview	87	(4)
Detailed VIIRS Design Capabilities	91	(1)
VIIRS Spectral Design Requirements	91	(1)
VIIRS Spatial Capabilities	91	(2)
VIIRS Horizontal Sampling Interval	93	(5)
VIIRS Dynamic Range Capability	98	(1)
VIIRS Sensitivity Capability	99	(1)
VIIRS Sensor Polarization Sensitivity	100	(1)
Detector Performance	101	(1)
Band-to-Band Registration or Coregistration	101	(3)
VIIRS Calibration	104	(5)
Principles in Image Interpretation	109	(42)
Introduction	109	(4)
VIIRS Imagery Data	113	(29)
VIIRS Imagery Band I1 (0.64 ± 0.040-μm)	114	(1)
Theoretical Basis for Band Interpretation	114	(1)
Representative Imagery of the VIIRS I1 Band (0.640- ± 0.040-μm)	115	(1)
VIIRS 12 Band (0.865- ± 0.020-μm)	116	(1)
Theoretical Basis for Band Interpretation	116	(1)
Representative Imagery of the VIIRS I2 Band (0.865- ± 0.020-μm)	117	(1)
VIIRS 13 and M10 Bands (1.61 ± 0.03-μm)	118	(1)
Theoretical Basis for Band Interpretation	118	(1)
Representative Imagery of the VIIRS I3/M10 Band (1.61- ± 0.03-μm)	119	(1)
VIIRS 14 Band (3.74- ± 0.19-μm) and M12 Band (3.7- ± 0.09-μm)	120	(1)
Theoretical Basis for Band Interpretation	120	(3)
Representative Imagery of VIIRS I4 Band (3.74- ± 0.19-μm)	123	(12)
VIIRS 15 Band (11.45- ± 0.95-μm)	135	(1)
Theoretical Basis for Band Interpretation	135	(2)
Representative Imagery of the VIIRS I5 Band (11.45- ± 0.95-μm)	137	(2)
VIIRS Day-Night Band	139	(1)
Theoretical Basis for Band Interpretation	139	(2)
Representative Imagery of the VIIRS DNB (0.7- ± 0.2-μm)	141	(1)
VIIRS Imagery Assist Data	142	(9)
VIIRS M1-M4 Bands (0.412 ± 0.010, 0.445 ± 0.009, 0.488 ± 0.010, 0.555 ± 0.010-μm)	142	(1)
Theoretical Basis for Band Interpretation	142	(2)
Representative Imagery of the VIIRS M1 Band (0.412- ± 0.05-μm)	144	(2)
VIIRS M9 Band (1.378- ± 0.0075-μm)	146	(1)
Theoretical Basis for Band Interpretation	146	(1)
Representative Imagery of the VIIRS M9 Band (1.378- ± 0.075-μm)	147	(4)
Multicolor Composites of Multispectral Imagery	151	(10)
Introduction	151	(2)
Color Composites of (0.64-μm, 0.865-μm, and 12.0-μm) Surface Vegetation and Cloud Classifications	153	(2)
Color Composites (3.7-μm albedo, 0.865-μm, 12.0-μm) for Snow Detection	155	(1)
Color Composites of (0.64-μm, 0.64-μm, 3.7-μm albedo) Snow Mapping Through Thin Cirrus Clouds	156	(2)
Color Composites of (0.412-μm, 0.865-μm, and 0.64-μm) Clouds Over Arid Regions	158	(3)
Case Studies in the Use of Multicolor Composites for Scene Interpretation	161	(20)
Overview	161	(1)
MODIS Airborne Simulation Data Over Alaska	162	(9)
Color Composite 1: Identification of Vegetated Surfaces	162	(1)
Color Composite 2: Identification of Snow and Ice Features	163	(1)
Color Composite 3: Cloud Type Classification Part I	164	(5)
Color Composite 4: Cloud Type Classification Part II	169	(2)
MODIS Airborne Simulation Success Data Collected Over Colorado	171	(10)
Color Composite 1: Identification of Vegetated Surfaces	173	(1)
Color Composite 2: Identification of Snow and Ice Features	174	(1)
Color Composite 3: Cloud Type Classification Part I	174	(3)
Color Composite 4: Cloud Type Classification Part II	177	(4)
Automated 3-D Cloud Analyses from NPOESS	181	(30)
Architecture for 3-D Cloud Analyses	181	(3)
Automated Cloud Detection	184	(5)
Single-Channel Cloud Detection Algorithms	185	(1)
Multispectral Channel Cloud Detection Algorithms	185	(3)
Spatial Cloud Classifier Algorithms	188	(1)
Cloud Top Phase Classifications	189	(3)
Cloud Optical (Thickness and Particle Size) Properties	192	(12)
Retrieval for Water Clouds During Daytime Conditions	194	(5)
Retrieval for Ice Cloud Microphysical Properties	199	(1)
Retrieval of Ice Cloud Properties in Daytime Imagery	200	(1)
Retrieval of Ice Cloud Properties in Nighttime Imagery	201	(3)
Cloud Top (Temperature, Pressure, and Height) Parameters	204	(1)
Cloud Base Heights	205	(6)
Cloud Base Heights Retrieved for Water Clouds	205	(1)
Cloud Base Heights Retrieved for Ice Clouds	206	(1)
Ancillary Data and Products from Other Sensors	207	(1)
Integration of VIIRS, CMIS, and Conventional Cloud Base Observations	208	(3)
References	211	(8)
Index	219