2nd International GPM GV Workshop Taipei, Taiwan, September 27-29, 2005 Characteristics of...

2nd International GPM GV WorkshopTaipei, Taiwan, September 27-29, 2005

Characteristics of Convective Systems Observed During TRMM-LBA

Rob Cifelli, Steve Nesbitt, and Steven A. RutledgeColorado State University


• Amazon one of three primary regions of ascent in the Walker Circulation and an upward branch in the Hadley Circulation

• Copious precipitation/latent heat release, but relatively few detailed studies of deep convection

Motivation for TRMM-LBA


TRMM-LBA• Joint with Large-scale Biosphere Atmosphere experiment (LBA)• Conducted in the State of Rondonia, Brazil (11oS, 62 W; SW corner

of Amazon) during Jan.-Feb. 1999• Goals:

– Validation of TRMM satellite products – Validation of cloud models (e.g., GCEM)– Physics of convection and the processes driving convection

• Instrumentation: – Ground radar: S-pol and TOGA radars (kinematics, microphysics,

rainfall)– Aircraft: ER-2 (TRMM simulator) and UND Citation (microphysics)– Soundings (3-Tethersonde and 4-Radiosonde)– NASA MSFC Brazilian Lightning Detection Network– NOAA dual-frequency wind profiler– Four raingauge networks, 2DVD and JW disdrometers– Other platforms (e.g., CCN, fluxes, flat plate antennas etc.)


Radars and Tethersonde


TRMM-LBA Aircraft


800-1100 m

700 - 800 m

600 - 700 m

500 - 600 m

400 - 500 m

300 - 400 m

200 - 300 m

100 - 200 m

0 - 100 m

Ariquemes

P

-65 -64 -63 -62 -61 -60

-8

-9

-10

-11

-12

-13Vilhena

Porto Velho

TRMM-LBA Instrumentation Network

ST

Jaru

Ji-Parana

150 km

Candeias BasinJamari Basin

Ji Parana Basin

Pimenta Bueno

Basin

Jaru Basin

= ALDF T = TOGA Radar S = S-Pol Radar P = Profiler/Disdrometer

= Sounding/T-sonde/Flux = Gauge Networks #1-2 = Gauge Networks #3-4

800-1100 m

700 - 800 m

600 - 700 m

500 - 600 m

400 - 500 m

300 - 400 m

200 - 300 m

100 - 200 m

0 - 100 m


TRMM-LBA Abracos Hill: 1/14 - 2/28, 1999 Wind direction at 850, Dewpoint 500 mb; Echo intensiy index

0.0

60.0

120.0

180.0

240.0

300.0

360.0

14 19 24 29 34 39 44 49 54 59

Julian Day

Direction (Deg.)

-16

-15

-14

-13

-12

-11

-10

-9

-8

-7

-6

Dewpoint (C

o)

850(smth) Conv. Indx. dp500(smth)

TRMM-LBA: Evidence of Convective Regimes

• West U-wind= Low CI, moist troposphere; monsoon-like convection

• Easterly U-wind= High CI, more dry troposphere; break-like convection


Brazilian Lightning Detection Network (BLDN)

01/99 - 03/99 Lightning Activity - Daily Detections(5 day moving average)

0

5000

10000

15000

20000

25000

30000

12/1/9812/11/9812/21/9812/31/981/10/991/20/991/30/992/9/992/19/993/1/993/11/993/21/993/31/99

Day

Site Detections (~strokes)

• Oscillations apparent

• East (west) anomalies =more (less) lightning.

East Regime


Time series PDFs of TRMM precipitation feature 30 dBZ echo top heights (left) and minimum 85 GHz PCT

DJFM 1998-1999

TRMM-LBA Radar Ops TRMM-LBA Radar Ops

Petersen et al. (2002)

Radar Observed Contrasts in TRMM-LBA Convection: Water Content

• Paucity of ice in mid-upper troposphere

Easterly Convection Westerly Convection

• Active mixed phase microphysics• Copious ice in mid-upper troposphere

• Significant differences in the vertical distribution of hydrometeors

Ice (gm m-3 - thin solid lines), liquid (gm m-3 - color contours), mean drop diameter (mm - heavy solid lines)


Mixed Phase Zone (4 - 8 km) Precipitation Ice and Rain Mass

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E+06

0.1 1.1 2.1 3.1 4.1 5.1 6.1 7.1 8.1

Precipitation Ice Mass (Mi, g m-3)

Frequency

26-Jan-99

25-Feb-99

a.

Westerly

Easterly

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E+06

0.1 2.1 4.1 6.1 8.110.1

Rain Mass (Mw, g m-3)

Frequency

26-Jan-99

25-Feb-99

b.

Westerly

Easterly

ICE RAIN

Frequency Distributions

Polarimetric radar analyses to identify microphysical differencesCourtesy: Dr. Lawrence Carey, Texas A&M


dBZ dBZ

m s-1

m s-1

Distance E-W from S-POL (km)Distance N-S from S-POL (km)

Hei

gh

t (k

m)

Hei

ght (

km)

25 February 1999 2340 UTC Y = 67 km

26 January 1999 2100 UTCX = 6 km

EASTERLY REGIME WESTERLY REGIME

VERTICAL RADAR STRUCTURE


Radar Observed Contrasts in TRMM-LBA Convection: Vertical Mass Transport

• Significant differences in intensity and lifecycle characteristics

Hei

ght (

km)

109 kg s-1

Easterly Convection

Westerly Convection

Time (UTC)

Hei

ght (

km)


• Profiler observations at Ji-Parana, Brazil 15 February 1999 (East)

• Stratiform rain with embedded convective cells

• Updrafts greater than 2 m/s above 6 km altitude

Break period convective system viewed by profiler—C. Williams and K. Gage


Relative Frequency Histograms of S-POL Radar Parameters

16 JAN 99 – 28 FEB 99

0.001

0.01

0.1

1

10

100

<0 5 11 17 23 29 35 41 47 53

Zh Bin (dBZ)

Relative Frequency (%)

EASTERLY

WESTERLY

Zh

0.01

0.1

1

10

100

<=0.5 0.8 1.1 1.4 1.7 2 2.3 2.6 2.9Median Volume Diameter (D0, mm)


EASTERLYWESTERLY

D0

0.001

0.01

0.1

1

10

100

0.15 0.45 0.75 1.05 1.35 1.65 1.95 2.25 2.55 2.85

Kdp Bin (deg km -1)


EASTERLY

WESTERLY

Kdp

0.001

0.01

0.1

1

10

100

0 20 40 60 80 100 120 140 160

Rainfall Rate (mm h-1)

Relative Frequency of Rain

Volume (%)EASTERLY

WESTERLY

R


Composite Q1 Profiles

• ER Convective Q1 is broader due to importance of ice processes• Difference in total Q1’s largely due to WCSF


PDFs of TRMM precipitation feature characteristics as a function of wind regime in Rondônia

DJFM 1997-2000

Petersen et al. (2002)

TMI 85 & 37GHz ice scatteringPCTs

PR echotop heights

Higher optical depths of ice

Higher radar tops


Comparisons of PR, Ground-Based and

Airborne Radar Data in TRMM LBA

Hey

msf

ield

et

al.

(200

0)


Model-Observations Comparison, Tao and Lang, GSFC

Observed CAPPI reflectivity Simulated CAPPI reflectivity

Observed CFAD reflectivity Simulated CFAD reflectivity

Comparisons between model and observations have led to improved microphysical parameterizations and latent heating profiles


• Integrated suite of measurements lead to identification of regimes in LBA

• Dual polarimetric radar is key for characterizing microphysical variability within regimes

• Gauge and disdrometer network important to evaluate errors in polarimetric rainfall measurements

• TRMM-LBA ground network provided a template for GPM GV

• More work is needed to understand the impact of regimes on satellite algorithms

Lessons Learned From TRMM-LBA

2nd International GPM GV Workshop Taipei, Taiwan, September 27-29, 2005 Characteristics of...

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