1. New uses of remote sensing to understand boundary layer clouds
Rob Wood
Jan 22, 2004
Contributions from Kim Comstock, Chris Bretherton,
Peter Caldwell, Martin Köhler, Rene Garreaud, and Ricardo Muñoz

2. Estimating MBL properties from combined satellite/reanalysis
Outline
What is remote sensing?
Recent work at UW:
Pockets of open cells
Estimating MBL properties from combined satellite/reanalysis
Other new technology
What’s next?

3. What is remote sensing?
Definition: The science, technology and art of obtaining information about objects or phenomena from a distance (i.e., without being in physical contact with them).
Examples: Radar, lidar, all satellite observations
Ms. Evelyn Pruitt of the United States Office of Naval Research coined the term “remote sensing” in 1958 to include aerial photography, satellite-based imaging, and other forms of remote data collection.

4. Recent work at UW The mystery of open cell pockets
Inferring MBL structure by combining knowledge from satellites and reanalysis

5. Scanning radars used to observe drizzle from shallow MBL cloud
Scanning C-band (5 cm) radar employed during TEPPS (NE Pacific) and EPIC 2001 (SE Pacific).
Distinct cellular nature of drizzle imaged for the first time
Allows investigation of links between cloud and drizzle structure

6. C-band radar movie from EPIC
40 km
Wind

7. Structure and evolution of drizzle cells
60 km
30 dBZ 20 10
-10
0235
0250
0305
0320
0335
Structure and evolution of drizzle cells
We just saw a number of drizzle cells advecting by the ship. I have identified individual cells in the C-band images and ‘cut them out’ of each image in the sequence. Here’s an example C-band image, in which a cell is selected and cut out. You can see it at the bottom at other points during the cell’s life cycle. I then take time series of these cells and average their properties over time and space.
C-band
example
October 21
0305 LT

8. Lifetime of drizzle cells/events
Typical cell lifetimes 1-2 hours Mean cloud base rain rates of mm hr-1 Cloud liquid water depletion rates do not exceed 0.2 mm hr-1 zi(u.qT) ~ 1 mm hr-1 Mesoscale gradients in qT are ~1 g kg-1 over 5-10 km  Typical mesoscale u variations must be 1-2 m s-1

9. C-band reflectivity and radial velocity
Mesoscale wind fluctuations related to drizzle cells
Radial velocity fluctuations
Radar reflectivity

10. The “POCS” mystery
Pockets Of Open Cells (POCS) are frequently observed in otherwise unbroken Sc. Their cause is unknown
POCS

11. The first satellite remote sensor - Tiros 1
TV Camera
in space
Mesoscale cellular
convection

12. MODIS 250m visible imagery
100 km

13. POCS associated with clean clouds
m brightness temperature difference
Low Tb indicative of low re
0 Tb 5
Figure courtesy
Bjorn Stevens, UCLA

14. POCS regions drizzle more
Figure by Kim Comstock/Rob Wood

15. More vigorous drizzle in POCS
MODIS brightness temperature difference, GOES thermal IR, scanning C-band radar
Figure by Sandra Yuter/Rob Wood

16. DYCOMS II aircraft mm radar
Figure by Bjorn Stevens

17. Climatology of open and closed cellular regions

18. POCS and drizzle – summary
POCS are often associated with small cloud effective radius and enhanced drizzle (no counter examples found to date)
Differences in LWP pdf shape are not expected to strongly modulate mean drizzle rate (LWP more skewed in POCS, but with lower cloud fraction)
Drizzle much more heterogeneous in POCS which may cause large horizontal temperature gradients through evaporative cooling – this in turn leads to density currents (“mini cold pools”) that enhance mesoscale fluxes of moisture and energy

19. MBL depth, entrainment and decoupling
Integrative approach to derive MBL and cloud properties in regions of low cloud
Combines observations from MODIS and TMI with reanalysis from NCEP and climatology from COADS
Results in estimates of MBL depth and decoupling (and climatology of entrainment)

20. MBL depth, entrainment, and decoupling

21. Methodology Independent observables: LWP, Ttop, SST
Unknowns: zi, q (= )
Use COADS climatological surface RH and air-sea temperature difference
Use NCEP reanalysis free-tropospheric temperature and moisture
Iterative solution employed to resulting non-linear equation for zi

22. Mean MBL depth (Sep/Oct 2000)
NE Pacific SE Pacific

23. Mean decoupling parameter q
Decoupling scales well with MBL depth

24. q vs zi-zLCL

25. Deriving mean entrainment rates
Use equation: we=uzi+ws
Estimate ws from NCEP reanalysis
Estimate uzi from NCEP winds and two month mean zi

26. Mean entrainment rates
Entrainment rate [mm/s] ◄ NE Pacific SE Pacific ► Subsidence rate [mm/s]

27. Summary of MBL depth work
Scene-by-scene estimation of MBL depth and decoupling
Climatology of entrainment rates over the subtropical cloud regions derived using MBL depth and subsidence from reanalysis
Decoupling strong function of MBL depth
Next step: deriving links between turbulence, inversion strength and entrainment by coupling to simple model forced with realistic boundary conditions

28. New technology: Multi-angle imaging (MISR)
On Terra (launched late 1999) 9 cameras in fore and aft direction (-70 to +70) Unprecedented 3D examination of cloud structure

29. Example of MISR’s potential
Movie

30. What’s next for MBL cloud remote sensing?
SPACEBORNE
millimeter RADAR in space: CLOUDSAT [launch 2004]; EARTHCARE [ESA, launch 2008]
 first spaceborne drizzle measurements
Cloud/aerosol LIDAR: CALIPSO [launch 2004]; +EARTHCARE
 MBL aerosol characteristic in clear regions;
first direct measurements of MBL depth at high spatial resolution from space
GROUND BASED
Scanning MM radars – 3D cloud structure
Scanning LIDAR on aircraft – cloud top mapping and entrainment processes

31. Diurnal cycle –The view from space
From Wood et al. (2002)
SE Pacific has similar mean LWP, but much stronger diurnal cycle, than NE Pacific…. …Why? A=LWP amplitude /LWP mean

32. EPIC 2001 [85W, 20S] Diurnal cycle of subsidence ws, entrainment we, and zi/t
zi/t + u•zi = we - ws
 0.05 cm s-1
NIGHT DAY NIGHT DAY ws we
dzi/dt
swe=0.24 cm s-1
sws=0.26 cm s-1
szi/t=0.44 cm s-1
Conclusion: Subsidence and entrainment contribute equally to diurnal cycle of MBL depth

33. Quikscat mean and diurnal divergence
Mean divergence observed over most of SE Pacific Coastal SE Peru
Diurnal difference (6L-18L) anomaly off Peruvian/Chilean coast (cf with other coasts)
Anomaly consistent with reduced subsidence (upsidence) in coastal regions at 18L
Mean divergence Diurnal difference (6L-18L)

34. Cross section through SE Pacific stratocumulus sheet

35. Diurnal subsidence wave - ECMWF
Daytime dry heating leads to ascent over S American continent • Diurnal wave of large-scale ascent propagates westwards over the SE Pacific at m s-1 • Amplitude cm s-1 • Reaches over 1000 km from the coast, reaching 90W around 15 hr after leaving coast

36. Subsidence wave in MM5 runs (Garreaud & Muñoz 2003, Universidad de Chile)
Vertical large scale wind at 800 hPa (from 15-day regional MM5 simulation, October 2001) Subsidence prevails over much of the SE Pacific during morning and afternoon (10-18 UTC) A narrow band of strong ascending motion originates along the continental coast after local noon (18 UTC) and propagates oceanward over the following 12 hours, reaching as far west as the IMET buoy (85W, 20S) by local midnight.

37. Vertical-local time contours (MM5)
17S-73W S-71W S-76W
Height [m]
Vertical wind as a function of height and local time of day – contours every 0.5 cm/s, with negative values as dashed lines Vertical extent of propagating wave limited to < 5-6 km Ascent peaks later further out into the SE Pacific

38. Diurnal vs. synoptic variability (MM5)
Diurnal amplitude equal to or exceeds synoptic variability (here demonstrated using 800 hPa potential temperature variability) over much of the SE Pacific, making the diurnal cycle of subsidence a particularly important mode of variability
Diurnal vs. synoptic variability (MM5)

39. Seasonal cycle of subsidence wave (MM5)
Wave amplitude greatest during austral summer when surface heating over S America is strongest. Effect present all year round, consistent with dry heating rather than having a deep convective origin MM5 simulations broadly consistent with ECMWF reanalysis data
22-18S, 78-74W

40. Effect of subsidence diurnal cycle upon cloud properties and radiation
Use mixed layer model (MLM) to attempt to simulate diurnal cycle during EPIC 2001 using:
(a) diurnally varying forcings including subsidence rate
(b) diurnally varying forcings but constant (mean) subsidence
Compare results to quantify effect of the “subsidence wave” upon clouds, MBL properties, and radiative budgets

41. MLM results
Entrainment closure from Nicholls and Turton – results agree favourably with observationally-estimated values Cloud thickness and LWP from both MLM runs higher than observed – stronger diurnal cycle in varying subsidence run. Marked difference in MLM TOA shortwave flux during daytime (up to 10 W m-2, with mean difference of 2.3 W m-2) Longwave fluxes only slightly different (due to slightly different cloud top temperature) Results probably underestimate climatological effect of diurnally- varying subsidence because MLM cannot simulate daytime decoupling SW LW

42. Conclusions
Reanalysis data and MM5 model runs show a diurnally-modulated 5-6 km deep gravity wave propagating over the SE Pacific Ocean at m s-1. The wave is generated by dry heating over the Andean S America and is present year-round. Data are consistent with Quikscat anomaly.
MM5 simulations show the wave to be characterized by a long, but narrow (few hundred kilometers wide) region of upward motion (“upsidence”) passing through a region largely dominated by subsidence.
The wave causes remarkable diurnal modulation in the subsidence rate atop the MBL even at distances of over 1000 km from the coast.
At 85W, 20S, the wave is almost in phase with the diurnal cycle of entrainment rate, leading to an accentuated diurnal cycle of MBL depth, which mixed layer model results show will lead to a stronger diurnal cycle of cloud thickness and LWP.
The wave may be partly responsible for the enhanced diurnal cycle of cloud LWP in the SE Pacific (seen in satellite studies).

43. Acknowledgements References
We thank Chris Fairall, Taneil Uttal, and other NOAA staff for the collection of the EPIC 2001 observational data on the RV Ronald H Brown. The work was funded by NSF grant ATM and NASA grant NAG5S
References
Bretherton, C. S., Uttal, T., Fairall, C. W., Yuter, S. E., Weller, R. A., Baumgardner, D., Comstock, K., Wood, R., 2003: The EPIC 2001 Stratocumulus Study, Bull. Am. Meteorol. Soc., submitted 1/03.
Garreaud, R. D., and Muñoz, R., 2003: The dirnal cycle in circulation and cloudiness over the subtropical Southeast Pacific, submitted to J. Clim., 7/03.
Wood, R., Bretherton, C. S., and Hartmann, D. L., 2002: Diurnal cycle of liquid water path over the subtropical and tropical oceans. Geophys. Res. Lett /2002GL015371, 2002

44. Ground based radar Developed during WWII for aircraft detection
Operators surprised by unusual signals that turned out to be caused by rain
Post-WWII: A remote sensing industry is born

45. Lidar