Research Opportunities: SWOP · 1. SWOP data: ATAL, satellite validation, TTL structure,...

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1 Research Opportunities: SWOP —— Sounding Water vapor, Ozone, and Particle during the Asian summer monsoon (2009 ~ 2016 ~ ……) Jianchun Bian (Institute of Atmospheric Physics, Chinese Academy of Sciences) Contributions from: Z. Bai, J. Zhang, Y. Xuan, H. Chen, D. Li, Q. Li, Y. Duan (IAP/CAS); H. Vömel, L. L. Pan (NCAR); F. Weinhold (ETH); D. Hurst, R.-S. Gao, S. Liu, E. Hall, A. Jordan, S. Oltmans (ESRL/NOAA) 2009

Transcript of Research Opportunities: SWOP · 1. SWOP data: ATAL, satellite validation, TTL structure,...

Page 1: Research Opportunities: SWOP · 1. SWOP data: ATAL, satellite validation, TTL structure, supersaturation-cirrus, cirrus-aerosol coupling, dynamical transport, …; Trend and case

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Research Opportunities: SWOP

—— Sounding Water vapor, Ozone, and Particle

during the Asian summer monsoon (2009 ~ 2016 ~ ……)

Jianchun Bian (Institute of Atmospheric Physics, Chinese Academy of Sciences)

Contributions from: Z. Bai, J. Zhang, Y. Xuan, H. Chen, D. Li, Q. Li, Y. Duan (IAP/CAS);

H. Vömel, L. L. Pan (NCAR); F. Weinhold (ETH);

D. Hurst, R.-S. Gao, S. Liu, E. Hall, A. Jordan, S. Oltmans (ESRL/NOAA)

2009

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ASM is a pollutant pathway to stratosphere!

Park et al, JGR, 2009

TTL: Gate to the stratosphere. It’s clean.

ASM: Another gate? But it’s a gate for pollutants!

Randel et al. Science 2010

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Satellite data and models often do not provide sufficiently

resolved details for describing the transport process.

Satellite product lacks of validation over the ASM region. In

situ measurements inside the anticyclone are scarce.

We are planning to conduct coincident in situ measurements

of water vapor, ozone and particle (cirrus and aerosol) in the

UTLS within the ASM anticyclone.

These observations will be significant for quantifying the

moisture and pollutant transport associated with the ASM,

for identifying the transport pathway, and for understanding

microphysical and chemical process in the UTLS. ——

Scientific goals

Scientific Motivation

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LS

KM

2010 Aug 22-2812 CFH/ECC3 Cobald

2013 Aug 3-2622 CFH/ECC18 Cobald

2016 Jul 25-Aug 228 CFH/Cobald6 CFH/POPS

Sounding Locations

2009, Aug 7-1311 CFH/ECC

2011, Sep 12-154 CFH/ECC

2012, Aug 11-Sep 618 CFH/FPH38 ECC , 12 Cobald

2014, Aug 13-2210 CFH/ECC/Cobald

2015, Aug 3-1812 CFH/ECC/Cobald

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Balloon-borne sondes

Compact Optical Backscatter Aerosol Detector (ETH) - particle

NOAA Frost Point Hygrometer (NOAA GMD) – H2O

Cryogenic Frost Point Hygrometer (Vömel-DMT) – H2O

Electrochemical Concentration Cell ozonesonde (DMT) – O3

Radiosonde: P, T, U, winds (u,v) (InterMet)

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CFH measures H2O with high accuracy.,

which is used to understand the

microphysics combined with COBALD

measurements.

Cryogenic Frostpoint Hygrometer

(CFH)

Principle

schematic

Super-

saturation

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COBALD

Principle schematic455 nm

870 nm

1.00 1.05 1.10 1.15 1.20BSR_blue

10

12

14

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18

20

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Altitude (

km

)

KM039

0 40 80 120 16012

13

14

15

16

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181 10 100 1000

-80 -75 -70 -65 -60 -55 -50 -45

KM

21_

dsc

COBALD detects cloud and

aerosol particles by emitting light

at two wavelengths (455nm,

870/940nm), and receiving the

back-scattered signal.

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ECC Ozonesonde

Deep convection signals can be found in ozone profiles.

30 60 90 120 150Ozone mixing ratio (ppbv)

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12

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18

Altitud

e (

km

)

2009080814

2009081014

2009081019

2009081114

2009081119

2009081314

2009081319

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POPS – a newcomer in 2015 & 2016

Printed Optical Particle Spectrometer (POPS): a lightweight,

low-cost detector -- Ru-shan Gao (NOAA)

Measure profiles of aerosol size spectrum

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Sounding information

Period: 2009-2016 (11+12+4+38+22+10+12+14 = 123)

Totally, we have

• ozone: ECC (123)

• water vapor: CFH/FPH (103)

• cloud and aerosol: COBALD (63)

• aerosol size distribution: POPS (9)

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Junge layer

ATAL

Vernier et al. JGR 2015

CALIOP

COBALD

1. COBALD data confirms the ATAL finding from CALIOP

Obs. highlights – ATAL issues

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1. Enhance 14-

19km

2. Extend 2km

above CPT

3. Interstitial

aerosol

2. POPSs see size distribution profile in the ATAL

Ci.

Obs. highlights – ATAL issues

Detect by

COBALD

Yu et al. PNAS AcceptedRu-Shan Gao, talk

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H2O rel. diff. (MLS CFH)

<5% above 68mb

+7% @83mb

7% @100mb

larger bias & dev.

Similar plot Can be found in

Yan et al. AMTD, 2016

316

261

215

178

147

121

100

83

68

56

46

38

Obs. highlights – MLS Validation

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O3 rel. diff. (MLS ECC)

Yan et al. AMTD, 2016

bias abrupt jump

Obs. highlights – MLS Validation

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1. TTL boundaries: bottom top

RESULTS -- Statistics

KMH: 17.300.43

T: 193.71.7

Θ: 384.2 8.4

LHH: 17.540.53 +0.24km

T: 195.2 1.7 +1.5K

Θ: 390.4 10.3 + 6K

TC4

H: 16.6 0.7 km

Θ: 375.1 13 K

Pan et al. JGR, 2014

Level of minimum stability

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2. Interannual variation

of H2O in the UTLS

Decoupled with lower levels

Interannual variation tuned by T?

RESULTS -- Statistics

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ATAL

3. RHi, super-saturation, cirrus

Supersaturation fraction

Cirrus fraction

2-layer

RESULTS -- Statistics

KM

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For Lhasa

KM

LH

Supersaturation fraction Cirrus fraction

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1 10 100 1000Backscatter Ratio; Color Index

4

8

12

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GP

S A

ltitude (

km

)

2010-05-27 0 50 100 150RHi (%)

4

8

12

16

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-80 -60 -40 -20 0Temperature (deg)

870 nm

455 nm

CI

Tair

TfrostRHi

CPT

Case 1:

A deep layer of

supersaturated

air & cloud –

thickness 10km

Some cases

2010-08-27, Lhasa

Cloud

layer

aerosol

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Kunming,

20 Aug’12

Supersaturation @

light cirrus;

Low RHi @ dense

cirrus,

Extra H2O taken

by dense cirrus.

Case 2:

Anti-correlation

between cirrus layer

and supersaturation

Some cases

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2121

0 2 4 6 8 10Water vapor mixing ratio (ppmv)

14

16

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20

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Altitude (

km

)

1 2 3 4BSR

0 20 40 60 80 100RHi (%)

H2O mixing ratioRHiBSR_RedBSR_Blue

Case 3:

Aerosol-cirrus

oupling:

Hygroscopic swollen,

or evaporation?

Some cases

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Case 4:

• Typhoon transport

• Stratospheric intrusion

Some cases

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International collaboration:

Match sounding in 2016 summer

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Summary

1. SWOP data: ATAL, satellite validation, TTL

structure, supersaturation-cirrus, cirrus-aerosol

coupling, dynamical transport, …; Trend and case

study

2. SWOP collaboration: match sounding campaign

(StratoClim); balloon-borne sensors (COBALD,

POPS, …)

Jianchun Bian (IAP/CAS): [email protected]

Thanks for your attention!