Low-Level Wind Variability over the Indochina Peninsula during Boreal Winter

Low-Level Wind Variability over the Indochina Peninsula during Boreal Winter

2012 1st Journal Conference on Environmental Science and Development (2012 1st JCESD)

Sirapong Sooktawee, Usa Humphries, Atsamon Limsakul, and Prungchan Wongwises

Introduction

� The flooding in southern Thailand probably resulted from the Asian Winter Monsoon (S. Limjirakan and A. Limsakul, 2011).

� Winter monsoon is a one of major climate features influencing the Indochina peninsula, but less of studies than studies focussing on summer monsoon.

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than studies focussing on summer monsoon.

� During winter season, East Asian Winter Monsoon (EAWM) is important climate feature.

� Low-level wind (850 hPa) can be used to represent winter monsoon (He J., et al., 2007)

The 2012 1st Journal Conference on Environmental Science and Development

Study Domain

� The study area representing Indochina peninsula (IDP) is a domain of 5-30°N, 90-110°E

� The domain consists of Cambodia, Laos,

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Cambodia, Laos, Myanmar, Thailand,

Viet Nam, and some territory of Malaysia.


KH: Cambodia, LA: Laos, MM: Myanmar, MY: Malaysia, TH: Thailand, and VN: Viet Nam

Data of the Study� Monthly Japanese 25-year reanalysis (JRA-25) data (Dec-Jan-Feb) with 1.25°×

1.25° horizontal resolution of 32 years (1979-2010) at 850 hPa level was used for analysis of the study.

� National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data with 2.5°× 2.5°horizontal resolution (1957-2010) was used to ensure representativeness of JRA-25 data set.

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JRA-25 NCEP/NCAR

Boreal winter climatology of low-level wind (850 hPa wind)

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Methodology

� Vector Empirical Orthogonal Function (VEOF)

is used to decompose orthogonal modes in

terms of time and space.

Hardy et al. (1978) succeeded to decompose surface wind

from observation representing mesoscale region.

Wu et al. (2006), (2008) apply the method to distinct modes

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Wu et al. (2006), (2008) apply the method to distinct modes

of monsoon.

� Pearson correlation was used to investigate

relation of temporal variation to East Asian

winter monsoon (EAWM) indices.


Procedure of Analysis

Construct a data matrix

Determine anomalies of zonal ( ) and meridional ( )winds

Form a complex number from and

u′ v′

u′ v′

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Analyze by VEOF

Eigenvectors(Spatial pattern)

Principal components (PCs)(Temporal variation)

Real part Imaginary part Real part Imaginary part

Modes of Low-Level Wind

• The first eigenvector (VEOF1) and the second eigenvector (VEOF2) accounting for 46.58% and 13.77% of variance, respectively, that is 60.35% of the total.

Real part (zonal) of PC1

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Imaginary part (meridional) of PC1

Positive phase Negative phase

Mean Low-Level Wind Fields

The circulation during boreal winter in 1998 (negative phases) exhibits stronger southwesterlies over northern part of Thailand, Laos, and Viet Nam than the circulation (positive phases) in 1999

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a positive phase year (1999)a negative phase year (1998)

Composite Analysis for Anomalies

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positive phase negative phase

Relation between PC1 and EAWM

Correlation coefficients show weak correlations to EAWM indices

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Conclusions

� VEOF can use to decompose variability of winter monsoon over the

IDP.

� From composite analysis, positive (negative) phase of anomalous

zonal and meridional wind show strengthening on northeasterlies

(southwesterlies) perhaps related to more (less) influence of EAWM

on the Indochina peninsular.

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� The variability of winter monsoon over the IDP shows interannual

variation.

� The correlation coefficients of PC1s to TII and TAI indices are weak.

� Influences of other climate modes on the Indochina peninsula and mechanism are required to investigate further.

Acknowledgements

� The Japan Meteorological Agency (JMA) and the Central Research Institute of

Electric Power Industry (CRIEPI)

� Assoc. Prof. Dr. Lin Wang, Institute of Atmospheric Physics, Chinese Academy of

Sciences and his group

� The Physical Sciences Division (PSD) of the Earth System Research Laboratory

(ESRL), the National Oceanic and Atmospheric Administration (NOAA)

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� The National Center for Atmospheric Research (NCAR)

� The Joint Graduate School of Energy and Environment (JGSEE) and the Center of

Excellence on Energy Technology and Environment (CEE)

Thank You for Your Attention