Duane E. Waliser 1, Baijun Tian 12, and Xianan Jiang 12 1 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 2 Joint Institute.

Duane E. Waliser1, Baijun Tian12, and Xianan Jiang12

1Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA2 Joint Institute for Regional Earth System Science and Engineering,

University of California, Los Angeles, CA

Vertical Structure And Processes Revealed With Recent Satellite Data

Vertical Structure And Processes Revealed With Recent Satellite Data

BIRS, 2009

Figures: E. Maloney, PMEL/TAO, M. Wheeler, J. Lin, D. WaliserFigures: E. Maloney, PMEL/TAO, M. Wheeler, J. Lin, D. Waliser

Kelvin WavesRossby Waves

MJOs

• The MJO is the dominant form of intraseasonal variability in the Tropics, with impacts a wide range of phenomena.

• Our weather & climate models have a relatively poor representation

• Aspects of Vertical Structure – which may be important to initiation/maintenance – have been difficult to evaluate via observations.

• Space-based observations now make it possible to examine aspects of vertical structure of the MJO hydrological cycle.

MotivationMotivation

Question?Question?

Using space-based observations, what can be said about the hydrological cycle of the MJO?

Hydrological DataHydrological Data CMAP Rainfall :

global, 2.5°x2.5° lat-long, pentad, 01/01/1979-02/22/2007. Xie and Arkin (1997)

TRMM 3B42 Rainfall:40S-40N, 0.25° x 0.25°, 3-hourly, 01/01/1998-06/30/2007. Huffman et al. (2007)

AIRS H2OVapMMR & TotH2OVap V4, L3, global, 1.0° x 1.0°, 2Xdaily, 09/01/2002-04/30/2007. Chahine et al. (2006)

QuikSCAT & TMI Moisture Transport 40S-40N, 0.25° x 0.25°, 2Xdaily, 08/1999-12/31/2005. Liu and Tang (2005)

OAFlux Evaporation 65S-65N, 1.0° x 1.0°, daily, 01/01/1981-12/31/2002. Yu and Weller (2007)

SSMI Total Column H2O Vapor & Total Cloud Liquid H2O V6, DMSP F13, global, 0.25° x 0.25°, 2Xdaily, 01/01/1996-06/30/2007. Wentz (1997), Wentz and Spencer (1998)

MLS Ice Water Content 80S-80N, 4° x 8° lat-long, 2Xdaily, 08/26/2004-02/22/2007. Wu et al. (2006)

Spatial-temporal Pattern of the 1st

EEOF Mode of Rainfall Anomaly

Spatial-temporal Pattern of the 1st

EEOF Mode of Rainfall Anomaly

MJO Event Selection

MJO Events in Hydrological Time SeriesMJO Events in Hydrological Time Series

TRMM: 18

CMAP: 57

AIRS:11

QuikSCAT&TMI: 13

OAFlux: 44

SSMI: 23

MLS: 5

Principal Component Time Series of 1st EEOF Mode of Rainfall Anomaly

Rainfall Pattern & Data Sensitivity

Rainfall Pattern & Data Sensitivity

Rainfall & Moisture ConvergenceRainfall & Moisture Convergence

-20 Days

-10 Days

0 Days

+10 Days

+20 Days

Rainfall and Total Column Moisture

Convergence tend to be Correlated throughout Tropics - except maybe

over S. America

-20 Days

-10 Days

0 Days

+10 Days

+20 Days

Rainfall & Surface EvaporationRainfall & Surface Evaporation

Largest Evap anomalies in the subtropics in

association with Rossby grye modulations of tradewind regimes

Near-equatorial Evap anomalies tend to lag

precipitation anomalies

Composite Hydrological CycleComposite Hydrological CycleVertical Structure

Water Vapor Cloud Ice

-0.5 mg/m3

+3 mm/day

600 hPa

900 hPa

300 hPa

-3 mm/day

-0.3 gm/kg

~ 45 days

Surface

Upper Troposphere - See Other Diagram

+0.3 gm/kg

+0.1 gm/kg

+0.5 mg/m3

-3 mm/day +3 mm/day

+2 mm-2 mm

-0.03 mm +0.03 mm

MJO Hydrological Cycle - Troposphere

-0.1 gm/kg

-0.2 mm/day +0.2 mm/day

ColumnIntegrated

Values

+1 mg/m3

+0.1 mg/m3

+3 mm/day

-1 mg/m3

-0.1 mg/m3

~150 hPa

~250 hPa

~100 hPa

-3 mm/day

+100 ppmv

+0.01 ppmv

+1 ppmv

+100 ppmv

+0.01 ppmv

+1 ppmv

~ 45 days

+0.5 K+0.5 K

-0.5 K

Surface

Lower-Middle Troposphere - See Other Diagram

MJO Hydrological Cycle - UTLS

Schwartz, M. J., D. E. Waliser, B. Tian, J. F. Li, D. L. Wu, J. H. Jiang, and W. G. Read, 2008: MJO in EOS MLS cloud ice and water vapor. GRL.

Total-column Moisture BudgetTotal-column Moisture Budget

€

∂W ∂t = −P + MC + E

Surface Rainfall

Surface Evaporation

Moisture Convergence due to large-

scale moisture transport

Total column Moisture change

Moistening (>0)Drying (<0)

€

∂W ∂t + P −MC − E = residual

Summary: ISummary: I

• Satellite Observations are now able to provide an estimate of the chief components of the Hydrological Cycle Associated with the MJO, in some cases with vertical structure information.

• However, calcululations of the Residual Term of the column-integrated values indicates closing the budget with current generation of satellite retrievals is difficult.

• Within the levels of uncertainty, Future plans involve applying the observed Hydrological Cycle of the MJO as a means to diagnose, evaluate and validate GCM simulations of the MJO or Evaluate Theoretical considerations.

Question?Question?

What Physical or Dynamical Mechanism is Responsible for the Lower-tropospheric Moisture

Preconditioning of the MJO?

17

18

19

20

21

22

23

24

25

Summary: IISummary: II significant moisture anomalies are located in the lower troposphere with maxima around 700 hPa during the transition phase; total-column and lower-tropospheric moisture change anomalies are positively correlated.

moisture change anomalies are positively correlated with moisture convergence anomalies but negatively correlated with rainfall and surface evaporation anomalies.

moisture change anomaly is highly & positively correlated with the difference between moisture convergence and rainfall anomalies.

implication: lower-tropospheric moisture preconditioning of the MJO is due to the small difference between moisture convergence and rainfall anomalies instead of surface evaporation anomaly.

Question?Question?

What types of clouds and cloud processes play a role in the moist pre-conditioning?

Considered w.r.t. to boreal summer.

Dataset

Cloudsat (Jun– Sep 2006, 2007)Horizontal resolution: 1x1 degs

Variables:Cloud liquid water content (LWC) Ice water content (IWC)

Cloud typesHigh: CirrusMiddle: Altocumulus (Ac), Altostratus (As)Low: Stratocumulus (Sc), Stratus (St), Nimbostratus (Ns)Vertical: Cumulus (Cu)

GPCP rainfall (1997-2007):horizontal resolution: 1x1 deg., 20-70-day band-pass filtered

Hovmöller diagram of GPCP precipitation (20-70-day filtered; 75-95oE)

Time series of EEOF1 of 1-D 20-70d filtered GPCP rainfall (5oS~25oN, averaged over 75-95oE sector) for MJJAS, 1996-2007.

The EEOF1&2 basically captures northward propagation of the BSISO.

20072006•

•

• • •• •

2006 2007

(mm/day)

-10day

-5

0

5

10

15

20

Time-latitude evolution (75-85oE)

Composite BSISV Evolution (7 events)

GPCP rainfall

(mm/day)

(mm/day)

Northward Propagation

•Vertical Tilting in LWC

•Low-level LWC leading

the convection center

Composite Cloud LWC (85-95oE average)

(no time-filtering, seasonal mean removed)

(mg/m3)

hPa

(mm/day)

Cloud LWC

rainfall

-5d

0d

5d

10d

15d

20d

•IWC generally in phase with convection

Composite

Cloud IWC (mg/m3)

(85-95oE)

-5d

0d

5d

10d

15d

20d

hPa

•LWC variation associated with BSISV mainly related to

non-precipitating and drizzling mid-low clouds;

•Altocumulus cloud are crucial for mid-level LWC

variation;

•Stratocumulus cloud important in the low-level

with contribution from cumulus.

LWC by Cloud Types

Sc+Cu

AC

Total Non-precip Conditions

Total Precipitating Conditions

AC

Sc

80-90 E – Bay of Bengal80-90 E – Bay of Bengal

CloudSat Application: MJO/ISV–driven Monsoon Onset & Breaks

Convective Center Convective Center

Some Drizzling ScMost Non-Precip Ac Some Non-Precip As

Most Precip Deep Conv

Summary: III

• During the northward propagation of the BS MJO, the cloud ice water

content (IWC) in upper troposphere tends to be in phase with

convection.

• A marked vertical tilting is discerned in cloud liquid water content (LWC)

with respect to the convection center. Increased LWC leads the

convection, particularly in the lower troposphere.

• IWC variability is largely associated with deep convective clouds; while

LWC is mainly linked to non-precipitating Altocumulus at mid-level and

drizzling Stratocumulus cloud at low-level; with the latter two appearing

to play a role in pre-conditioning for the northward propagation.

Washington DCUSGS Map

13.5 km AIRS IR; AMSU & HSB m wave

13.5 km AIRS IR; AMSU & HSB m wave

6x7 km POLDER 6x7 km POLDER

5.3 x 8.5 km TES 5.3 x 8.5 km TES

CloudCloud

0.5 km MODIS Band 3-70.5 km MODIS Band 3-7

0.09 km CALIPSO0.09 km CALIPSO

1. 4 km Cloudsat1. 4 km Cloudsat

OCO1x1.5 km

Afternoon Constellation Instrument Footprints

(Source: M. Schoeberl, 2003)

YOTC: A-Train Data Co-Location Possibilities for Studying & Modeling Cloud/ConvectionYOTC: A-Train Data Co-Location Possibilities for Studying & Modeling Cloud/Convection

P(hpa)

qqii(p)(p)

qqll(p)(p)AMSRAMSR

PrecipitationPrecipitationSSTSST

Prec WaterPrec WaterLWPLWP

Surf. Wind SpeedSurf. Wind Speed

AIRSAIRSq(p)q(p)T(p)T(p)

ECMWFECMWF(p)(p)u(p)u(p)

du/dp(p)du/dp(p)divdivHH(p)(p)

qqii(p) & IWP(p) & IWP

qqll(p) & LWP(p) & LWP

Cloud Type (p)Cloud Type (p)~ Particle Size (p)~ Particle Size (p)

Light PrecipLight Precip

Light PrecipLight Precip

CloudSatCloudSat

Aerosol Opt DepthAerosol Opt DepthCloud Top - Cloud Top -

TemperatureTemperature Pressure, Particle Size, Pressure, Particle Size,

etcetc

MODISMODIS

Aerosol (p) Aerosol (p) Cloud (p)Cloud (p)

CALIPSOCALIPSO

< ~3< ~3

UTLS – T(p), q(p), UTLS – T(p), q(p), qqii(p), (p),

CO (p), OCO (p), O33(p), (p),

HNOHNO33(p)(p)

MLSMLS

TOA and SFC radiative TOA and SFC radiative fluxesfluxes

CERESCERES