Climate variations during 20th Climate variations during 20th century in the Northwest Pacific century in the Northwest Pacific

Region.Region.Dmitry D. KaplunenkoDmitry D. Kaplunenko**,,****, Vladimir I. Ponomarev , Vladimir I. Ponomarev **, Young J. Ro , Young J. Ro ****, ,

Olga O. TrusenkovaOlga O. Trusenkova** and Serge T. Trusenkov and Serge T. Trusenkov**

** – V.I. Il’ichev Pacific Oceanological Institute, Vladivostok, Russia; – V.I. Il’ichev Pacific Oceanological Institute, Vladivostok, Russia;

**** – Chungnam National University, Daejeon, Republic of Korea. – Chungnam National University, Daejeon, Republic of Korea.

E-mail: dimkap@poi.dvo.ruE-mail: dimkap@poi.dvo.ru

Introduction

This work provides:- Study of climate variability by the datasets based

on different methods of data augmentation (instrumental and reanalysis based)

- Analysis on climate variability by the data on monthly air temperature for Northeast Asia and SST for North Pacific region for centennial (correlations, wavelets) and semicentennial period (correlations, wavelets, trends)

Used data sources

• Instrumental:

Air Temperature: Global History Climatic Network:http://lwf.ncdc.noaa.gov/oa/pub/data/ghcn/v2/ghcnftp.html SST: GLBSST (Japan Meteorological Agency) ftp://ddb.kishou.go.jp/pub/Climate/SeaSurfaceTemp

• Reanalysis based:

Air Temperature: NCEP/NCAR Reanalysis project data: http://www.cdc.noaa.gov/cdc/data.ncep.reanalysis.htmlSST: Hadley Centre for Climate Prediction and Research:http://badc.nerc.ac.uk/data/hadisst/

Data coverage (Tair)

Data coverage for meteorological data:

Contribution (GHCN stns.):

NCEP: 2.5°x2.5°

Russia 60

Korea 9

Japan 46

China 32

Mongolia 8

Total 155 80 100 120 140 160 180

20

40

60

Data coverage (SST)Sea surface temperature.

• GLBSST (Japan Meteorological Agency) (North Pacific, period 1946-2002, 2°x2° )

• Hadley Centre for Climate Prediction and Research (North Pacific,1946-2002,1870-2002,1°x1° )

Data coverage:

Assessing of climate changes by prepared Assessing of climate changes by prepared datasets using known statistical methodsdatasets using known statistical methods

Assessing methods:• Principal Component Analysis (EOF,CEOF)• Correlation and spectral analysis (wavelet)• Linear trend estimation

Object of interest:• Northeast Asia• North Pacific

Data for assessing:• Sea Surface Temperature, Air temperature mean values

for 1946-2002 (GHCN, NCEP/NCAR, JMA GLBSST, Hedley SST) and 1870-2002 (Hedley SST)

EOF-decomposition instrumental dataAir temperature SST

CEOF-decomposition instrumental data Air temperature SST

EOF-decomposition reanalysis data Air temperature SST

NCEP

CEOF-decomposition reanalysis dataAir temperature SST

Wavelet derived oscillations for instr. data (Tair)Amlitude Phase Scalar EOF

Scale-averaged wavelet power over the 3–7-yr, 8-20-yr and 21-50-yr band for the GHCN dataset for winter

Wavelet derived oscillations for instr. data (SST)Amlitude Phase Scalar EOF

Scale-averaged wavelet power over the 3–7-yr, 8-20-yr and 21-50-yr band for the JMA dataset for winter

Wavelet derived oscillations for reanal. Data (Tair)

Scale-averaged wavelet power over the 3–7-yr, 8-20-yr and 21-50-yr band for the NCEP dataset for winter

Amlitude Phase Scalar EOF

Wavelet derived oscillations for reanal. data (SST57)Amlitude Phase Scalar EOF

Scale-averaged wavelet power over the 3–7-yr, 8-20-yr and 21-50-yr band for the Hedley (56 years) dataset for winter

Wavelet derived oscillations for reanal. Data (SST133)Amlitude Phase Scalar EOF

Scale-averaged wavelet power over the 3–7-yr, 8-20-yr and 21-50-yr band for the Hedley (132 years) dataset for winter

PDO-correlations with instr. dataAmplitude-winter Phase-winter Scalar EOF-winter

temporal modes and PDO for GHCN data on period 1946-2002. Amplitude-winter Phase-winter Scalar EOF-winter

modes and PDO for GLBSST (JMA) data on period 1946-2002

PDO-correlations with reanal. dataAmplitude-winter Phase-winter Scalar EOF-winter

Amplitude-winter Phase-winter Scalar EOF-winter

temporal modes and PDO for NCEP data on period 1948-2002

temporal modes and PDO for HEDLEY data on period 1946-2002

PDO-correlations with reanal. Data (Hedley SST 1900-2002)

Amplitude-winter Phase-winter Scalar EOF-winter

Amplitude-summer Phase-summer Scalar EOF-summer

Correlation analysis on temporal modes and PDO for Hedley SST data on period 1900-2002.

Linear trends estimation resultsInstrumental Data:

Reanalysis Data

Conclusions• Both types of used dataset (instrumental and

reanalysis) is could be used for study climatic variability at the decadal and multidecadal scales and shows its relations to the climatic processes at ocean-atmosphere system observed by the other data.

• Scale averaged oscillations show the similar tendencies for the spectral analysis for correspondent data sets (air temperature/SST).

• The correlation analysis on the propagating signals influence for these dataset is rather complicated, but SST is highly correlated with the PDO in all cases

• Long-term tendencies analysis shows better agreement for instrumental data observations (more real) than for reanalysis data

Thank you for Thank you for your attention!your attention!