1. In the past thirty five years NOAA, with help from NASA, has established a remote sensing capability on polar and geostationary platforms that has proven useful in monitoring and predicting severe weather such as tornadic outbreaks, tropical cyclones, and flash floods in the short term, and climate trends indicated by sea surface temperatures, biomass burning, and cloud cover in the longer term. This has become possible first with the visible and infrared window imagery of the 1970s and has been augmented with the temperature and moisture sounding capability of the 1980s. The imagery from the NOAA satellites, especially the time continuous observations from geostationary instruments, dramatically enhanced our ability to understand atmospheric cloud motions and to predict severe thunderstorms. These data were almost immediately incorporated into operational procedures. Use of sounder data in the operational weather systems is more recently coming of age. The polar orbiting sounders are filling important data voids at synoptic scales. Applications include temperature and moisture analyses for weather prediction, analysis of atmospheric stability, estimation of tropical cyclone intensity and position, and global analyses of clouds. The Advanced TIROS Operational Vertical Sounder (ATOVS) includes both infrared and microwave observations with the latter helping considerably to alleviate the influence of clouds for all weather soundings. The Geostationary Operational Environmental Satellite (GOES) Imager and Sounder have been used to develop procedures for retrieving atmospheric temperature, moisture, and wind at hourly intervals in the northern hemisphere. Temporal and spatial changes in atmospheric moisture and stability are improving severe storm warnings. Atmospheric flow fields are helping to improve hurricane trajectory forecasting. Applications of these NOAA data also extend to the climate programs; archives from the last fifteen years offer important information about the effects of aerosols and greenhouse gases and possible trends in global temperature.
This talk will indicate the present capabilities and foreshadow some of the developments anticipated in the next twenty years.
Summary Remote Sensing Seminar Lectures in Maratea Paul Menzel NOAA/NESDIS/ORA May 2003

2. Satellite remote sensing of the Earth-atmosphere
Remote sensing of the earth atmosphere depends on the instruments characteristics (mirror sizes, detector signal to noise performance, spectral coverage and resolution) as well as the scene radiation and transmittance through the atmosphere (day or night, cloudy or clear, moist or dry). The following slides will present some of these concepts briefly.
Observations depend on
telescope characteristics (resolving power, diffraction)
detector characteristics (signal to noise)
communications bandwidth (bit depth)
spectral intervals (window, absorption band)
time of day (daylight visible)
atmospheric state (T, Q, clouds)
earth surface (Ts, vegetation cover)

3. Spectral Characteristics of Energy Sources and Sensing Systems

4. Solar (visible) and Earth emitted (infrared) energy
Incoming solar radiation (mostly visible) drives the earth-atmosphere (which emits infrared).
Over the annual cycle, the incoming solar energy that makes it to the earth surface (about 50 %) is balanced by the outgoing thermal infrared energy emitted through the atmosphere.
The atmosphere transmits, absorbs (by H2O, O2, O3, dust) reflects (by clouds), and scatters (by aerosols) incoming visible; the earth surface absorbs and reflects the transmitted visible. Atmospheric H2O, CO2, and O3 selectively transmit or absorb the outgoing infrared radiation. The outgoing microwave is primarily affected by H2O and O2.

5. Solar Spectrum
The top of the atmosphere incoming solar radiation is characterized by a Planck blackbody of temperature about 6000 K. Of the electromagnetic energy emitted from the sun, approximately 50% lies in wavelengths longer than the visible region, about 40% in the visible region ( m), and about 10% in wavelengths shorter than the visible region.
The radiation sensed at the surface of the earth has been attenuated by atmospheric O3, O2, CO2, and H2O (most of the water vapor sensitive bands occur at wavelengths longer than 0.8 um). The visible remote sensing from geo orbit with GOES has been traditionally covering .5 to .9 um; from leo orbit with AVHRR two spectral bands .58 to .68 um (lower reflection from vegetation) and .72 to 1.00 um (higher vegetation reflection) have been maintained. With the launch of the MODIS, the monitoring in the visible has been expanded to 19 bands.

6. VIIRS, MODIS, FY-1C, AVHRR
CO2 O2
H2O O2
H2O
H2O
H2O O2
H2O
H2O
CO2

7. AVIRIS Movie #2 AVIRIS Image - Porto Nacional, Brazil 20-Aug-1995
224 Spectral Bands: mm
Pixel: 20m x 20m Scene: 10km x 10km
Another sequence from AVIRIS shows the different images as a function of wavelength when viewing a partly cloudy scene. Again how the reflectance changes as one approaches the absorption bands and the surface disappears. The reflection from the vegetated surface increases after 0.72 um and surface features become evident. The heavy higher cloud reveals different details at different wavelengths. It is imperative that the satellite evolution in the next decade introduce this type of remote sensing. The science possibilities are enormous. This image loop is the work of Mike Griffen and his co-workers at MIT/Lincoln Lab. 1 1

8. MODIS IR Spectral Bands
This slide shows an observed infrared spectrum of the earth thermal emission of radiance to space. The earth surface Planck blackbody - like radiation at 295 K is severely attenuated in some spectral regions. Around the absorbing bands of the constituent gases of the atmosphere (CO2 at 4.3 and 15.0 um, H20 at 6.3 um, and O3 at 9.7 um), vertical profiles of atmospheric parameters can be derived. Sampling in the spectral region at the center of the absorption band yields radiation from the upper levels of the atmosphere (e.g. radiation from below has already been absorbed by the atmospheric gas); sampling in spectral regions away from the center of the absorption band yields radiation from successively lower levels of the atmosphere. Away from the absorption band are the windows to the bottom of the atmosphere. Surface temperatures of 296 K are evident in the 11 micron window region of the spectrum and tropopause emissions of 220 K in the 15 micron absorption band. As the spectral region moves toward the center of the CO2 absorption band, the radiation temperature decreases due to the decrease of temperature with altitude in the lower atmosphere.
IR remote sensing (e.g. HIRS and GOES Sounder) currently covers the portion of the spectrum that extends from around 3 microns out to about 15 microns. Each measurement from a given field of view (spatial element) has a continuous spectrum that may be used to analyze the earth surface and atmosphere. Until recently, we have used “chunks” of the spectrum (channels over selected wavelengths) for our analysis. In the near future, we will be able to take advantage of the very high spectral resolution information contained within the 3-15 micron portion of the spectrum. From the polar orbiting satellites, horizontal resolutions on the order of 10 kilometers will be available, and depending on the year, we may see views over the same area as frequently as once every 4 hours (assuming 3 polar satellites with interferometers). With future geostationary interferometers, it may be possible to view at 4 kilometer resolution with a repeat frequency of once every 5 minutes to once an hour, depending on the area scanned and spectral resolution and signal to noise required for given applications.

9. Current GOES Sounder Spectral Bands: 14.7 to 3.7 um and vis
Eighteen infrared sounding bands (channels) ranging from 14.7 (top left) to 3.9 (bottom middle) microns were selected for the GOES sounder; the channels were patterned after those realized for the polar orbiting High resolution Infrared Radiometer Sounder (HIRS). These multispectral observations yield information about the vertical structure of atmospheric temperature and moisture. The concept of profile retrieval is based on the fact that atmospheric absorption and transmittance are highly dependent on the frequency of the radiation and the amount of the absorbing gas. At frequencies close to the centers of absorbing bands, a small amount of gas results in considerable attenuation in the transmission of the radiation; therefore most of the outgoing radiation arises from the upper levels of the atmosphere. At frequencies far from the centers of the band, a relatively large amount of the absorbing gas is required to attenuate transmission; therefore the outgoing radiation arises from the lower levels of the atmosphere. This is evident moving from 14.7 (ch1, op left) to 11 (ch8, 2nd row middle) microns; features in the lower atmosphere emerge as wavelength moves from the center of the CO2 absorption band. The H2O sensitive bands (ch8 - 12) exhibit similar behavior. The shortwave CO2 sensitive bands (ch ) also detect reflected solar radiation (more at shorter wavelengths)

10. GOES Sounder Spectral Bands: 14.7 to 3.7 um and vis
The GOES Sounder spectral bands are indicated along with there sensitivity to a particular atmospheric layer. Blue are the temperature sensitive bands, red are moisture bands, and green are surface bands.
As indicated earlier, sampling in the spectral region at the center of the absorption band yields radiation from the upper levels of the atmosphere (e.g. radiation from below has already been absorbed by the atmospheric gas); sampling in spectral regions away from the center of the absorption band yields radiation from successively lower levels of the atmosphere. Away from the absorption band are the windows to the bottom of the atmosphere. Surface temperatures of 296 K are evident in the 11 micron window region of the spectrum and tropopause emissions of 210 K in the 15 micron absorption band. As the spectral region moves toward the center of the CO2 absorption band, the radiation temperature decreases due to the decrease of temperature with altitude in the lower atmosphere.

11. Radiative Transfer through the Atmosphere
The radiance leaving the earth-atmosphere system which can be sensed by a satellite borne radiometer is the sum of radiation emissions from the earth surface and each atmospheric level that are transmitted to the top of the atmosphere. Considering the earth's surface to be a blackbody emitter (emissivity equal to unity), the upwelling radiance intensity, R, for a cloudless atmosphere is given by the indicated expression. The first term is the surface contribution and the second term is the atmospheric contribution to the radiance to space.
The fundamental principle of atmospheric sounding with meteorological satellites detecting the earth-atmosphere thermal infrared emission is based on the solution of the radiative transfer equation. In this equation, the upwelling radiance arises from the product of the Planck function, the spectral transmittance, and the implied weighting function. The Planck function consists of temperature information, while the transmittance is associated with the absorption coefficient and density profile of the relevant absorbing gases. Obviously, the observed radiance contains the temperature and gaseous profiles of the atmosphere, and therefore, the information content of the observed radiance from satellites must be physically related to the temperature field and absorbing gaseous concentration.

12. II II I |I I ATMS Spectral Regions

14. Radiation is governed by Planck’s Law
c2 /T
B(,T) = c1 /{  5 [e ] }
In microwave region c2 /λT << 1 so that c2 /T
e = 1 + c2 /λT + second order
And classical Rayleigh Jeans radiation equation emerges
Bλ(T)  [c1 / c2 ] [T / λ4]
Radiance is linear function of brightness temperature.

15. On board Terra, MODIS (Moderate Resolution Imaging Spectroradiometer) is beginning to deliver exciting data about the oceans, land , and atmosphere. The following slides explain the spectral channel selection and present a few applications examples in each area. For ocean applications, the MODIS team has selected several spectral bands that are on line and off line absorption features associated with chlorophyll and accessary pigments. The multispectral data will be used to reveal their respective concentrations in the ocean waters.

16. Or land applications, MODIS has several spectral bands that are above and below step function increases or decreases in the reflectivity of vegetation (increases above 0.72 um) or snow/ice (decreases above 1.4 um). The multispectral data will be used to reveal the extent of vegetation and snow/ice in the various regions of the globe.

17. For atmospheric applications, MODIS reflective bands can indicate particle size in clouds. Notice how the spectrum opens with increasing wavelength so that measurements at 2.1 and 0.75 um can be used to discriminate 5 to 30 um particles. Again this is a multispectral application of the MODIS data to reveal cloud and clear sky properties.

18. It is important to note that the atmospheric windows are not transparent (there is some moisture absorption of radiation in the 8 to 12 um region) and that the earth surface does not exhibit blackbody behavior. These characteristics must be accounted for when using remote sensing data over land to infer temperature and moisture profiles. They are also important for mapping land surface properties. MODIS is well situated to make multispectral determinations of land cover type and temperature.

19. The brightness temperatures of the outgoing radiance observed by an airborne interferometer are shown along with the MODIS infrared spectral bands. The brightness temperatures generally decrease as the center of an absorption band is approached. This decrease is associated with the decrease of tropospheric temperature with altitude. Near about 690 cm-1, the temperature shows a minimum which is related to the colder tropopause. On the basis of the sounding principle already discussed, the MODIS team selected a set of sounding wave numbers such that a temperature layers in the troposphere can be described. The arrows indicate the selection. The associated weighting functions are also shown revealing that the radiation is coming from broad overlapping layers, helping to confound the inversion problem from multispectral radiance measurements to temperature profile.

20. Multispectral data reveals improved information about ice / water clouds
A well known application of IR window multispectral is discrimination of water cloud from ice cloud. Because liquid phase water absorbs radiation differently than solid phase water (ice) at different wavelengths, it will be possible to discriminate between the two, as well as to detect clouds with mixed phase. The tri-spectral technique utilizes radiance measurements near 10.0, 11.5, and 13.0 microns; water is indicated when T10~T11 and T11<<T13 and ice is indicated when T10<<T11 and T11~T13.
With geostationary tri-spectral observations it will be possible to watch clouds as they change phase, which is often indicative of where they are in their life cycle.
Knowing cloud type and height (from CO2 slicing) is important for numerous applications - not the least of which is feeding advanced numerical weather prediction models that will soon be available.

21. MODIS

23. Ice reflectance

26.  c13 Using wavenumbers c2/T
Planck’s Law B(,T) = c13 / [e ] (mW/m2/ster/cm-1)
where  = # wavelengths in one centimeter (cm-1)
T = temperature of emitting surface (deg K)
c1 = x 10-5 (mW/m2/ster/cm-4)
c2 = (cm deg K)
Wien's Law dB(max,T) / dT = 0 where (max) = 1.95T
indicates peak of Planck function curve shifts to shorter wavelengths (greater wavenumbers) with temperature increase. 
Stefan-Boltzmann Law E =   B(,T) d = T4, where  = 5.67 x 10-8 W/m2/deg4. o
states that irradiance of a black body (area under Planck curve) is proportional to T4 .
Brightness Temperature
c13
T = c2/[ln(______ + 1)] is determined by inverting Planck function B

27. Radiative Transfer Equation
When reflection from the earth surface is also considered, the RTE for infrared radiation can be written o
I = sfc B(Ts) (ps) +  B(T(p)) F(p) [d(p)/ dp] dp ps
where
F(p) = { 1 + (1 - ) [(ps) / (p)]2 }
The first term is the spectral radiance emitted by the surface and attenuated by the atmosphere, often called the boundary term and the second term is the spectral radiance emitted to space by the atmosphere directly or by reflection from the earth surface.
The atmospheric contribution is the weighted sum of the Planck radiance contribution from each layer, where the weighting function is [ d(p) / dp ]. This weighting function is an indication of where in the atmosphere the majority of the radiation for a given spectral band comes from.

28. RTE in Cloudy Conditions
Iλ = η Icd + (1 - η) Ic where cd = cloud, c = clear, η = cloud fraction
λ λ o
Ic = Bλ(Ts) λ(ps) +  Bλ(T(p)) dλ .
λ ps pc
Icd = (1-ελ) Bλ(Ts) λ(ps) + (1-ελ)  Bλ(T(p)) dλ
λ ps
+ ελ Bλ(T(pc)) λ(pc) +  Bλ(T(p)) dλ
ελ is emittance of cloud. First two terms are from below cloud, third term is cloud contribution, and fourth term is from above cloud. After rearranging
pc dBλ
Iλ - Iλc = ηελ  (p) dp .
ps dp
Techniques for dealing with clouds fall into three categories: (a) searching for cloudless fields of view, (b) specifying cloud top pressure and sounding down to cloud level as in the cloudless case, and (c) employing adjacent fields of view to determine clear sky signal from partly cloudy observations.

29. Cloud Properties
RTE for cloudy conditions indicates dependence of cloud forcing (observed minus clear sky radiance) on cloud amount () and cloud top pressure (pc) pc
(I - Iclr) =    dB . ps
Higher colder cloud or greater cloud amount produces greater cloud forcing; dense low cloud can be confused for high thin cloud. Two unknowns require two equations.
pc can be inferred from radiance measurements in two spectral bands where cloud emissivity is the same.  is derived from the infrared window, once pc is known. This is the essence of the CO2 slicing technique.

30. RCO2 RIRW Cloud Clearing
For a single layer of clouds, radiances in one spectral band vary linearly with those of another as cloud amount varies from one field of view (fov) to another
Clear radiances can be inferred by extrapolating to cloud free conditions.
clear
RCO2 x
partly cloudy xx x
x x x
cloudy x
N=1
N=0
RIRW

31. Moisture
Moisture attenuation in atmospheric windows varies linearly with optical depth.
- k u
 = e = 1 - k u
For same atmosphere, deviation of brightness temperature from surface temperature is a linear function of absorbing power. Thus moisture corrected SST can inferred by using split window measurements and extrapolating to zero k
Moisture content of atmosphere inferred from slope of linear relation.

33. Comparison of geostationary (geo) and low earth orbiting (leo) satellite capabilities
Geo Leo
observes process itself observes effects of process
(motion and targets of opportunity)
repeat coverage in minutes repeat coverage twice daily
(t  30 minutes) (t = 12 hours)
full earth disk only global coverage
best viewing of tropics best viewing of poles
same viewing angle varying viewing angle
differing solar illumination same solar illumination
visible, IR imager visible, IR imager
(1, 4 km resolution) (1, 1 km resolution)
one visible band multispectral in visible
(veggie index)
IR only sounder IR and microwave sounder
(8 km resolution) (17, 50 km resolution)
filter radiometer filter radiometer,
interferometer, and
grating spectrometer
diffraction more than leo diffraction less than geo

34. Email comments on course to Suggestions to improve
Best feature
Worst feature
Suggestions to improve