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.
Quick Review of Remote Sensing Basic Theory Paolo Antonelli CIMSS University of Wisconsin-Madison Ostuni, June 2006

2. Outline IR at High Spectral Resolution Basic Principles
Limits in IR remote sensing

3. High Spectral Resolution
Visible
(Reflective Bands)
Infrared
(Emissive Bands)

4. High Spectral Resolution
High Vertical Resolution

5. Radiative Transfer Equation

6. Transmittance for an off-line Channels
 + a + r = 1 z
close to 1
a close to 0 z3
T(z3)
The molecular species in the
atmosphere are not very active:
most of the photons emitted by the surface make it to the Satellite
if a is close to 0 in the atmosphere then  is close to 0, not much contribution from the atmospheric layers
T(z2) z2
T(z1) z1
Surface emission
Atmospheric emission 1 

7. Trasmittance on an Absorption Linez
Absorption Channel:
 close to 0
a close to 1
T(z4) z4
T(z3) z3
One or more molecular species in the
atmosphere is/are very active:
most of the photons emitted by the surface will not make it to the Satellite (they will be absorbed)
if a is close to 1 in the atmosphere then  is close to 1, most of the observed energy comes from one or more of the uppermost atmospheric layers z2
T(z2)
T(z1) z1 1 

8. Weighting Functions zN zN z2 z2 z1 z1 1 
d/dz

9. What Causes Absorption?
Molecules in the Atmosphere.
For any layer of the atmosphere,
molecular absorption
determines the layer emissivity
and trasmittivity

10. CO2 Lines

11. H2O Lines

12. Vibrational Lines
CO2 O3
H2O
CO2

13. Rotational Lines
CO2 O3
H2O
CO2

14. Weighting Functions A b s o r H p e t I i g h n t Wavenumber
Energy Contribution

15. Broad Band window window Samplig of vibrational bands
Integration over rotational bands
CO2 O3
H2O

16. … in Brightness Temperature

17. High Spectral Resolution
Samplig over rotational bands

18. AIRS and MODIS (mt Etna, Sicily, 28 Oct 2002)

19. Broad Band vs High Spectral

20. Questions
For a given water vapor line what happens to its weighting function
When the amount of upper tropospheric water vapor increases?

21. For a given water vapor spectral channel
Weighting Function
For a given water vapor spectral channel H E I G T
Wet Atm.
Wet
Moderate
Moderate
Dry Atm.
Dry
Tau
100%

22. How does it look the observed spectrum for high thick water
Questions
How does it look the observed spectrum for high thick water
vapor cloud ?

23. Thick Cloud Opacity

24. Questions
Moving deeper and deeper into an absorption line the observed
BT tends do decrease, why?
Is it always true that the BT decreases going
deeper into the absorption band?

25. Temperature Inversions
AIRS (20 July 2002)
calculation
Sub-Arctic Winter
May 2001 S. Pole radiosonde
profile used in calculation
(0.365 mm H2O)

26. Conclusions High Vertical Resolution High Spectral Resolution
Large Volume
of Data
(redundancy)