Mesoscale variability and drizzle in stratocumulus Kim Comstock General Exam 13 June 2003.
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Transcript of Mesoscale variability and drizzle in stratocumulus Kim Comstock General Exam 13 June 2003.
![Page 1: Mesoscale variability and drizzle in stratocumulus Kim Comstock General Exam 13 June 2003.](https://reader036.fdocuments.net/reader036/viewer/2022070616/5a4d1bf27f8b9ab0599e663e/html5/thumbnails/1.jpg)
Mesoscale variability and drizzle in stratocumulus
Kim Comstock
General Exam13 June 2003
![Page 2: Mesoscale variability and drizzle in stratocumulus Kim Comstock General Exam 13 June 2003.](https://reader036.fdocuments.net/reader036/viewer/2022070616/5a4d1bf27f8b9ab0599e663e/html5/thumbnails/2.jpg)
EPIC 2001 Sc cruise
image courtesyof Rob Wood
x
EPIC 2001 Sc cruise
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Data set• Meteorological measurements on
ship and buoy (T, q, U, LW, SST)• Ceilometer • MMCR and C-band radar• GOES satellite imagery
EPIC 2001 Sc data
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Why are Sc important?• Areal extent and persistence• Effect on radiation budget
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Key parameter: Sc albedo
• mean droplet size– CCN aerosols
• cloud thickness– turbulence, entrainment, drizzle
•diurnal and mesoscale variations• horizontal variability
– mesoscale circulations– drizzle?
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Central QuestionsTo understand the physical processes
that govern variability in Sc albedo, we must answer the following questions:
• What is the structure and life cycle of Sc?
• What is the role of drizzle in mesoscale variability?
• What role does the diurnal cycle play?
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Goals: using EPIC data to address central
questions• Determine drizzle cell properties
from C-band radar.• Obtain and physically interpret
signatures of mesoscale variability from ship and buoy time series.
• Estimate amount of drizzle and relate to mesoscale variability.
• Analyze diurnal cycle and determine how it modulates all of the above.
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MMCR time-height section
-60 -40 -20 0 15 dBZ
hourly cloud top
hourly LCL
hourly cloud base
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Quantifying drizzle• We have reflectivity (Z) over a wide area
around the ship from the C-band radar, but we want to know rain rate (R) information.
• No suitable Z-R relationships exist for drizzle.• We developed Z-R relationships, Z=aRb , from in-situ DSD data at cloud base and at the surface:– aircraft (N Atlantic) and surface (SE Pacific) data– linear least squares regression (log10Z, log10R)
• Ideally, we want to know R at the surface.
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Quantifying drizzle - method
• Evaporation-sedimentation model– assumes truncated exponential drop-size
distribution (DSD) with mean size r – run with various r’s and drop concentrations
• Obtain model reflectivity profiles (Z(z)/ZCB) and compare with MMCR profiles.– infer DSD for each MMCR profile– use model to extrapolate cloud base DSD
characteristics to the surface (get surface R)• Develop “bi-level” Z-R relationship using
cloud base ZCB to predict surface Rs.
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Quantifying drizzle - results
• Apply bi-level Z-R to C-band cloud reflectivity data to obtain area-averaged rain rate at the surface.
• Average drizzle rates for EPIC Sc– 0.93 mm/day at cloud base (range 0.3-3)– 0.13 mm/day at the surface (range 0.02-
0.6)• Uncertainties due to
– C-band calibration (2.5 dBZ)– Z-R fitting procedure
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Diurnal cycle• At night the BL tends to be well
mixed (coupled). • During the day, the BL is less well
mixed (decoupled). • It tends to drizzle most during the
early morning.
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Coupled BL
U
UT
cloud thickness 410 ± 60 mcloud base 930 ± 30 m
~ 30 km
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Decoupled BL
cloud thickness 310 ± 110 mcloud base 930 ± 60 m
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Drizzling BL
cloud thickness 415 ± 150 mcloud base 890 ± 110 m
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Mesoscale variabilityGoes 8 Visible19 October
0545 Local Time
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Summary of previous work
• Though the diurnal signal is dominant, mesoscale structure is an integral part of the dynamics of the Sc BL.
• BL time series classified as coupled, decoupled or drizzling.
• There is a significant amount of drizzle in the SE Pacific BL, and it is associated with increased mesoscale variability
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Future work• Compare Sc mesoscale structure with
previous studies of mesoscale cellular convection (MCC)
• Further examine radar data for 2-D and 3-D information– circulations (also use DYCOMS II and
possibly TEPPS Sc) – compositing/tracking
• Analyze buoy time series for mesoscale variability in relation to “drizzle”.
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MCC comparisons Compare our coupled cell with
closed cell from Rothermel and Agee (1980)
q
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Radial velocities• EPIC C-band volume-scan radial velocities
are probably unusable due to pointing errors associated with these scans.
• Vertical RHI scans appear less susceptible to error, so the radial velocity data (in the RHIs) may be useful for qualitatively looking at 3-D circulations in the BL.
• TEPPS volume scans and DYCOMS II vertically-pointing radar data are other possibilities.
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Example
0
90
180
270
15 km
30 km
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EPIC Sc RHIs 17 October 2001 1058 UTC0
90
180
270
2 km 19 km
dBZ
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EPIC Sc RHIs 17 October 2001 1058 UTC0
90
180
270
2 km 19 km
m/s
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Comparison with DYCOMS II
• Anticipate receiving DYCOMS II aircraft data (vertically-pointing MMCR data and time series)– look for circulations associated with
closed cells and drizzling conditions– look at variability associated with
drizzle (flight RF02)
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C-band compositeCell 1Cell 2
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Compositing/tracking: preliminary results
• Examples from tracked drizzle cells
Time avg PDF of dBZ Average reflectivity
Time (hr UTC)dBZ
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Drizzle’s signature• Air-sea temperature difference
appears to be a good indication of drizzle occurring in the area.
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Drizzle’s signature
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Drizzle climatology• Will apply air-sea T analysis to
year-long buoy time series to determine – frequency and persistence of drizzle – diurnal cycle information– cloud fraction associated with drizzle
•Longwave radiation can be used as a proxy for cloud fraction in the buoy data series.
– relationship to satellite images
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Buoy data• Example of SST-Ta for 15
September 2001 satellite overpasses
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Buoy dataGOES 8 IR 1145 UTC
WHOI BUOY
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Buoy dataGOES 8 Vis 1445 UTC
WHOI BUOY
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Buoy dataGOES 8 Vis 1745 UTC
WHOI BUOY
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Buoy dataGOES 8 Vis 2045 UTC
WHOI BUOY
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ScheduleDate GoalSummer 03 Submit Z-R paperSummer 03 Compositing & sizing of drizzle
cellsSummer-Fall 03 Contribute to broken
cell/drizzle paperFall 03 Submit mesoscale variability
paperWinter-Spring 04 C-band radial velocity analysisSpring-Summer 04 DYCOMS II data analysisSummer-Fall 04 Satellite – time series analysisWinter 05 Finish
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LW as a proxy for cloud fractionLW
-T a4 (
W/m
2 )
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Drizzle and open cellsGOES image (color) and C-band reflectivity (gray
scale)GOES image only
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(Less) drizzle and closed cells
GOES image (color) and C-band reflectivity (gray
scale)GOES image only
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Evaporation-sedimentatio
n model
r (m)
N (#/L)
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C-band Sc Volume Scan
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MCC – closed cell
Moyer&
Young 1994
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Tracking algorithm
Williams and Houze 1987