Most instruments on geophysical satellites are passive
rather than active devices. A passive device detects radiances while
an active device is the source of the energy. Active devices have been
less frequently used for geophysical satellites because they require
more power which usually limits instrument lifetime.
The sources of the radiances detected by
passive satellite instruments are reflected solar energy and energy
absorbed and reemitted by the earth/atmosphere system. The portions
of the electromagnetic spectrum which are normally used for
geophysical studies are: the ultraviolet (UV; ~ 0.0001-0.4 um) ,
the visible (VIS; ~ 0.4-0.74 um), the near infrared infrared
(IR; sometimes called outgoing long wave radiation (OLR); ~ 0.74-100
um) and the microwave wavelengths (~ 100 um and longer).
The wavelengths are inversely proportional to the temperature of the
emitting body. Solar energy is contained within the shorter
wavelengths (0.15-4 um) with about 9% in the UV range, 45% in
the VIS range and the
rest at the longer wavelengths. Various geophysical variables and
chemical constituents of the atmosphere-ocean system emit radiation
at the longer wavelengths due to much lower emitting temperatures.
For example, the infrared and microwave wavelengths may be used to
derive atmospheric and thermal information (e.g., the atmosphere's
vertical temperature profile and cloud top temperatures). The visible
wavelength range is mainly used to monitor cloud systems and infer
precipitation.
Satellites may be categorized by their orbits. The
two most common categories are polar-orbiting and geostationary
(Figs. 5.1 and
5.2). Generally, polar-orbiting meteorological
satellites maintain sun-synchronous orbits (an orbit whose plane is
fixed relative to the sun). Sun-synchronous polar orbiters generally
have low orbital altitudes (e.g., 850 km). At these altitudes
it takes about 100 minutes to encircle the globe which yields
14-15 equatorial crossings per day. Sun-synchronous orbits are
designed so that a satellite passes over a particular location at the
equator twice per day at the same time every day. Being in a polar
orbit does not necessarily mean that the satellite passes directly
over the poles. Rather, their orbits are at an angle relative to the
equator. This equator-crossing angle is called the inclination angle
and it is a defined by a mission's objective. Operational
meteorological satellites have large inclination angles (80 degree to
100 degree) while research satellites may have smaller inclination
angles (Fig. 5.3). Operational polar orbiting satellites are
principally used to obtain daily cloud cover, vertical temperature and
water vapor distributions and global sea surface temperature. They
are also used to receive/transmit data from moving platforms (e.g.,
drifting buoys or balloons) and determine their geographic position
based upon the Doppler shift in the frequency received at the
satellite.
Geostationary satellites have high altitudes (e.g.,
36,000 km), maintain a fixed geographic location and orbit at the same
speed that the earth rotates. They make observations at 20-30 minute
intervals throughout each day. This allows continuous monitoring of a
particular area of the earth. The size of the area monitored is a
function of instrument design and satellite altitude. However, a
single geostationary satellite can monitor about 25-30% of the earth's
surface Figure 5.2
illustrates the areas covered by five geostationary satellites.
Spatial resolution varies among the different satellites, ranging from
1 to 5 km (VIS) and from 5 to 8 km (IR). Geostationary satellites
collect full images of VIS and IR each half hour and can do so more
frequently if needed. Use of the IR allows images to be collected
during the day or night. Uses of these data include locating and
tracking tropical storms and deriving wind estimates which are used by
operational weather forecasting models.
Both polar orbiting and
geostationary satellites transmit data back to earth by radio. Polar
orbiters record, and in some cases, preprocess the data prior to
transmitting to earth. Geostationary satellites are always in contact
with a ground station and need not record the data. Geostationary
satellites provide two types of direct broadcast services: (i) a
high-resolution transmission, most often used by researchers, and
(ii) a low resolution transmission often called weather facsimile
(WEFAX). Figures
5.4 and Chapters 3 and 4), which
are site specific, irregularly spaced and of varying quality;
satellite data represent spatial averages, cover wide areas and are of
relatively consistent quality (if the calibration of the detecting
instrument has remained stable). However, the absolute accuracy of the
derived quantities is difficult to establish. Each meteorological
satellite has different spatial sampling resolutions. For orbiting
satellites, horizontal resolution is best along a satellite's track
and is less over areas between tracks. As an example, the UARS, which
is used to study the chemistry, dynamics, and energetics of the
stratosphere, has a 500 km wide latitudinal swath. One
characteristic of raw satellite data is its very large volume.
In general, NASA archives the experimental data and NOAA archives
operational data. These data are available to researchers. However,
the computing and storage requirements generally preclude individual researchers
from doing their own processing. Thus, the research community uses the
processed datasets which are of considerably smaller volume, yet may
still be quite large.
Some sources of error for satellite measurements include: space-time
sampling problems, instrumentation limitations, calibration drift,
aerosol loading after volcanos, difficulty in removing noise,
uncertainties in location, changes in equatorial crossing times and
calibration of results with other observed variables. Sometimes
(e.g., ERBE), the processed data are a combination of inversion
methods and models which can make the data uncertainty estimates
difficult to assess.
One difficult problem is how to assign various estimates to specific
atmospheric altitudes. Simply stated, the problem is that the
satellite instruments detect vertically integrated radiance values.
Complex models exist that estimate how a particular vertical
distribution of a geophysical variable emits radiation. However, there
are a large number of complexities that make interpolation of a
measured radiance value to specific atmospheric levels uncertain. Much
work remains to be done but comparison studies with in situ
data show that significant progress is being made.
NIMBUS: NIMBUS
satellites (1964-78) wre used for cloud mapping and used wide field-of-view and fixed radiometers. However,
the satellites were earth stabilized (as opposed to spin stabilized)
so that the axis is always perpendicular to the surface of the Earth,
and they occupied polar sun-synchronous orbits at approximately 1000
km altitude.
NOAA: NOAA (1970-present) operates a system of operational
weather satellites. The first five were ITOS (Improved TIROS
Operational System) type satellites, carrying three main instruments;
two scanning radiometers (VIS and IR) and a Vertical Temperature
Profile Radiometer (VTPR). These were polar orbiters that provided
information on clouds, vertical temperature profiles, water vapor,
outgoing long-wave radiation (OLR),etc.
TIROS-N: The third generation of operational meteorological
polar-orbiting satellites was started by TIROS-N. The Stratospheric
Sounding Unit (SSU) was provided by the United Kingdom, France
provided the data collection system and it was launched by the U.S. in
1978. The first Microwave Sounding Unit (MSU) and a High Resolution
Infra-Red Sounder (HIRS) were flown on this platform.
GOES: The first Geostationary Observational and Environmental
Satellite (GOES-1) was launched in May 1974. The most recent launches
occurred in March 1987 (GOES-7) and April 1994 (GOES-8). These NOAA
satellites are usually located at 75 degree-west and 135 degree-west
longitudes. The combination allows coverage of almost all of North
America and South America and adjacent oceans (see Fig. 5.2).
Originally, the GOES series provided only VIS and IR images. However,
the instruments have improved in quality over the past 20-years
allowing for more comprehensive examinations of the atmosphere. For
example, the more recent GOES series provide the ability to infer the
vertical profiles of temperature and moisture. This information is
used by operational forecast centers.
Special Purpose Earth-Orbiting Satellites: Skylab demonstrated
the ability to accurately measure the sea surface height (SSHT) from
space. The SSHT is useful for geophysical studies because it is a
proxy for the geoid, a surface of equal gravitational attraction. The
anomalies in the gravitational field provide valuable information
about changes in the density structure of the Earth. It is interesting
to note that "sea level" is not the same over the globe. The SSHT
near Sri-Lanka is more than 180 meters lower than near New Guinea,
6800 km away (granted, these are the extremes). The success of Skylab
experiments spawned the use of radar altimeters on GEOS, Seasat,
Geosat, TOPEX, and ERS-1.
Earth Radiation Budget Experiment: The ERBE satellite system
consisted of an Earth Radiation Budget Satellite (ERBS), NOAA 9, and
NOAA 10. The instrument package includes both scanning and nonscanning
radiometers designed to provide high resolution, regional scale
measurements of numerous radiative quantities. These provided a basis
for long-term continent-scale monitoring of the radiation budget. More
specifically, they measure the amount of solar radiation at the top of
the atmosphere and the radiation emitted by the earth/atmosphere
system. These are of fundamental importance since they determine the
sources and sinks of energy that drive the climate system.
International
Satellite Cloud Climatology Project : The
purpose of ISCCP is to collect and analyze satellite observed
radiances to infer the global distribution of radiative properties of
clouds. The goal is to improve the modeling of cloud effects on
climate. It uses data from the five geostationary satellites and polar
orbiters of the NOAA/TIROS-N type.
European Remote Sensing: The ERS-1 satellite was launched in
July 1991. It is a polar orbiting satellite operating at an altitude
of about 785 km. It carries a number of instruments including an AMI
scatterometer, which measures radar-backscatter from which wind
estimates over the oceans may be derived. A second satellite (ERS-2)
has recently been launched.
Measurements and Orbits
Satellite instruments detect radiances
(i.e., electromagnetic energy over a finite range of wavelengths or,
equivalently, frequencies). These radiances are the result of
scattering, reflection or emission by the earth/atmosphere system.
Although the instruments and computer algorithms are designed to
minimize unwanted information (i.e., noise), the radiances received by
satellite instruments contain both the desired signal and some noise.
(Noise, in this discussion, means not only unwanted
instrument/transmission signals but also unwanted signals from other
geophysical variables.) The detected radiances are transmitted to
centers which process and archive both the raw and processed data.
The processing involves sophisticated `retrieval' algorithms (e.g.,
inversion techniques and/or statistical models) which can be used to
derive estimates for a broad range of geophysical quantities. These
quantities include, but are not limited to: sea surface and
atmospheric temperatures, winds, water vapor, precipitation,
cloud-cover, snow and/or ice cover, elements of the radiation budget,
chemical components (e.g., ozone [o3], carbon
dioxide [co2],...) and other
physical quantities of interest at various space and time
scales. These estimated quantities are used for visual weather
displays, as input to operational weather forecast centers and for
basic scientific research.
Some Satellite Systems and Programs
TIROS and ESSA : The TIROS series (launch dates: 1960-63 for
TIROS I-VIII; 1965 for TIROS IX and X) of satellites were the first to
be launched specifically for atmospheric studies. There were
essentially two sensors on board, an IR radiometer and a television
camera. These satellites were spin-stabilized, meaning that the spin
axis was fixed in space. Consequently, the instruments viewed the
earth perpendicularly only once per orbit. This resulted in the use of
elaborate spherical geometry to determine the latitude and longitude
of the data. The later TIROS series, ESSA (1966-1969), was improved
so that the spin axis was perpendicular to the orbital plane, enabling
perpendicular measurements and easier rectification once per satellite
rotation. The ESSA orbits were sun-synchronous.
Some Representative/Commonly Used NCAR Satellite Datasets
NCAR
IDSatellite/
ExperimentMax.
PeriodDescription ds676.0 TIROS N, NOAA 1974-pres daily gridded VIS and
IR brightnesses, OLR ds684.1 ECT-corrected 1974-1999 Global OLR Datasets ds692.0 NOAA series 1972-1979 vertical temperature
profiles from 8 IR bands ds700.0 NOAA series 1978-1992 raw global radiances
from MSU, SSU, TOVS (sounders) ds701.0 NOAA series 1979-1993 gridded mid-troposphere
temperature from 53.74GHz ds701.5 NOAA series 1979-pres gridded precipitation
from MSU channels (Spencer) ds703.0 NOAA series 1989-1991 Polar
Orbiter Global (GAC) Data ds710.0 NIMBUS-7 1978-1986 along-orbit ozone derived
from backscattered UV ds712.0 1974-1974 reduced gridded dataset Atlantic
brightnesses and IR ds716.0 INSAT 1984-1989 India: IR and VIS VHRR 2x, 8x
daily ds718.5 NOAA series 1974-1994 monthly and
half-monthly OLR ds724.0 Meteosat 1993-pres radiances: 2500x2500
pixels; start July 93; (G. Campbell) ds725.0 ISCCP 1983-1987 geostationary US cloud cover
from radiances ds727.1 GEOSAT 1986-1988 along-orbit global ocean
wind speed, wave height, SSHT ds729.0 SSMI 1987-1991 Chang's 5 degree precip
estimates ds733.0 NIMBUS-7 1978-1987 ERBE matrix of
daily/monthly radiances ds742.0 ISCCP 1983-1994 global equal-area gridded
cloud cover every 3 hours ds744.0 ERS-1 1991-1993 along-track oceanic wind
speeds and directions, SSHT
An Introduction to Atmospheric and Oceanographic Datasets