1. Water Vapour Imagery and
Potential Vorticity

2. Questions How can you visualize the wind?
How can you see the upper air flow?
What colour is the wind?

3. OUTLINE Some Physics Imagery Characteristics WV Interpretation
NWP Verification
Potential Vorticity – Introduction
PV Anomalies
PV and WV Imagery

4. Visible

5. Infrared

6. Water Vapour

7. Visible imagery IR imagery WV imagery Trop Atmospheric window
Emissions Vis - Albedo IR – temperature WV – emissions of water vapour depends on vapour and its temperature

8. EM Spectrum
Visible 0.8 m
IR 10.8 m
WV 6.2, 7.3 m

9. Remember Stefan-Boltzmann’s law?
The hotter the body, the greater the irradiance
Key Learning points:
Should know:
Above 55 deg N/S image not much use due to curvature, it needs to be processed and projected to be useful for lats up to 65 deg.
MSG geostationary orbit at KM (6 times the Earth radius)
Could Know
Meteosat’s have a reserve of 4 kg fuel to move up into a graveyard orbit. (Often though they are initially moved into the Indian ocean orbit (India did not supply images until recently, due to ‘issues’ with Pakistan using them, but also the quality is not as good a Meteosat – India were out of the cooperating nations until recently, and it may take sometime to catch up.
The NOAA image does degrade East / West and North / South away from the SSP.
Low intensity from cold
High intensity from warm
WV appears white
WV appears dark

10. Distribution of WV Completely moist atmosphere
Emitting water molecules

11. Where is the source of radiation detected at the satellite?
Distribution of WV
Completely moist atmosphere
Emitting water molecules
Where is the source of radiation detected at the satellite?

12. Distribution of WV
Dry upper troposphere

13. Where is the source of radiation detected at the satellite?
Distribution of WV
Dry upper troposphere
Where is the source of radiation detected at the satellite?

14. Moisture profiles and radiation

15. Display converted to temperature
White indicates upper tropospheric moisture
Grey indicates dry upper troposphere and moist middle levels
Black indicates dry air at middle and upper levels

16. Variation of contribution with humidity in water vapour images
Note that moisture here
will not be detected

17. EM Spectrum
Channel 5 (6.2m) strong absorption, centred around 300 hPa
Channel 6 (7.3m) less strong absorption, centred near 500 hPa

18. Variation of contribution with humidity in water vapour images
Ch hPa

19. WV imagery characteristics

20. Water vapour loop 6-8 June, 2000

21. 1. Latitude Effect Whiter at the poles Higher contrast in tropics
Moisture from colder source
Higher contrast in tropics
Can be cold or warm
More moisture variability
Higher tropopause
Moist air appears dark when it is warm

22. 1. Latitude Effect

23. 2. Seasonal Effects Whiter in mid-latitude winter
Lower temperatures for given height
Range reduced
Higher contrast in mid-latitude summer
Higher, colder tropopause
Larger range

24. 2. Seasonal Effects
Winter

25. 2. Seasonal Effects
Summer

26. 3. Crossover effect All radiation detected from 700-200hPa
A given intensity may come from different profiles
It’s been found that …
cloud at mid levels contributes more radiation than higher levels

27. Imagery interpretation
Broadscale upper flow patterns
Jetstreams
Troughs/Ridges
Areas of vertical motion
Short-wave features
Convection

33. Water Vapour and NWP

34. Verification WV can be used to identify upper air features in the flow
Position
Orientation
Shape
Speed of movement
Development with time
Compare these to NWP analyses and forecast frames
Assessment of model performance

35. WV Image MODEL: 5 March 03, 06Z Relative vorticity, 300hPa heights,
MSLP

36. Recapitulation on WV Water vapour imagery …
shows upper level flows and humidity patterns in cloud-free areas
can be directly compared to model fields (height, vorticity, vertical motion)
can show developments before cloud formation is evident on VIS/IR

37. Any Questions (so far)?

38. Potential Vorticity
A refresher!

39. Objectives
to write down the equation for PV and understand the meaning of the terms
to describe the effects of a PV anomaly on atmospheric development
to describe how PV can be related to water vapour imagery and NWP

40. Potential Vorticity
PV is actually quite a simple concept and has been around for years (since the 1930s at least).
It is increasingly used in Ops Centre and Ops Centre Guidance.

41. Potential Vorticity P = 1 a.   z
PV simply combines vorticity and static stability (vertical temperature gradient).
P = 1 a.  z 
density
absolute
vorticity
vertical
potential
temperature
gradient

42. How does PV vary?
Density decreases with height so PV tends to increase slightly upwards.
f, the Coriolis parameter increases with latitude, so PV increases slightly towards the poles.
The major change in PV occurs at the tropopause where the static stability increases very rapidly.

43. How does PV vary?
Typical values of PV in the troposphere are generally less than 1.5 “PV units”.
In the stratosphere PV increases rapidly to in excess of 4 “PV units”.
Therefore there is a large gradient of PV at the tropopause
(1 PV unit = 10-6 m2s-1 K.kg-1)

45. Potential Vorticity PV is a conserved quantity, which changes
only slowly with time.

46. Potential Vorticity
This fits with what we already know about vorticity
If we stretch a column of air it spins more rapidly
If we squash an air column it spins less rapidly

47. Invertibility
PV contains information about both the dynamics (through vorticity) and thermodynamics (through potential temperature) of the atmosphere.
This is enough information to give all the other atmospheric fields if we have a boundary condition and a balance state.

48. Invertibility
So if you know the PV distribution in the atmosphere together with say the MSLP field, you can get all the other fields.
You could write an NWP model using PV and it would be cheaper to run than a conventional model.

49. Field Modification

50. PV Anomalies

51. Potential Vorticity anomaly
A PV anomaly near the tropopause.
The thick line is the
PV = 2 surface.
Thin lines are
isentropes.
The dotted and
solid contours show
circulation (out of and
into the page).
strato-
sphere
tropo-
sphere

52. The effect of a Potential Vorticity anomaly
A column of air
passing beneath the
PV anomaly is
stretched and so
gains some cyclonic
vorticity.
In reality the upper
level features move
faster than low level
air.
strato-
sphere
tropo-
sphere

53. The effect of a Potential Vorticity anomaly
Air flowing relative to the isentropic surface flows up the surface on the forward side of a positive PV anomaly - ISENTROPIC UPGLIDING

54. The effect of a Potential Vorticity anomaly
An upper level PV anomaly induces low level vorticity.
Upper level PV anomalies occur where the tropopause changes height rapidly.
Tropopause height changes rapidly in the vicinity of fronts, developing depressions, upper lows or cold pools.

55. An upper low / cold pool

56. The effect of a Potential Vorticity anomaly (cyclonic development)
A positive PV anomaly over a low level baroclinic zone induces a positive feedback mechanism
(eg depressions)

57. Potential Vorticity anomalies
00Z 2/11/92.
PV (colours). 900 hPa w (white) MSLP (black)

58. Potential Vorticity anomalies
00Z 3/11/92 (24 hours later)
PV (colours). 900 hPa w (white) MSLP (black)

59. PV and WV Imagery

60. PV and water vapour imagery
Stratospheric air has high PV and low humidity.
The upper troposphere in a tropical airmass has low PV and high humidity.
In mid latitudes PV values near the tropopause relate closely to radiances in the water vapour channel.

61. PV and water vapour imagery
In a developing depression, the tropical air in the warm conveyor belt will be white or pale grey in a WV image, and will have low PV.
The dry, cold descending air behind the system will be dark grey or black in a WV image and will have high PV.
Where the tropopause is changing height rapidly, there will be a sharp PV gradient.

62. PV and water vapour imagery

63. PV and water vapour imagery
This means that the PV field from an NWP model is almost like a forecast water vapour image.
If the PV distribution from the model is overlaid on a water vapour image, the quality of the analysis or forecast can be subjectively assessed.

64. PV and water vapour imagery
The model’s PV field at T+0 can be compared with water vapour imagery.
If they do not match well, the model analysis can be adjusted to give a better fit and therefore a better forecast.
This provides a means of evaluating and improving NWP forecasts.

65. Any Questions?