Surface chlorophyll bloom in the Southeastern Tropical Indian Ocean during boreal summer-fall as reveal in the MODIS dataset

Transcription

1 Surface chlorophyll bloom in the Southeastern Tropical Indian Ocean during boreal summer-fall as reveal in the MODIS dataset Iskhaq Iskandar 1 and Bruce Monger 2 1 Jurusan Fisika, Fakultas MIPA, Universitas Sriwijaya, Inderalaya, Ogan Ilir, Sumatra Selatan, INDONESIA 2 Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA

2 Oceanic circulations in the southeastern tropical Indian Ocean 2/19

3 Atmospheric circulations over the southeastern tropical Indian Ocean (surface wind and SST) 3/19

4 Indian Ocean Dipole (IOD): A brother of El Nino/La Nina Normal condition IOD condition Courtesy of Dr. S.A. Rao ß Normal Condition or Negative IOD High SST, deep thermocline, active atmospheric convection in the eastern Indian Ocean, and westerly winds along the equator ß Positive IOD condition High SST, deep thermocline, active atmospheric convection all shift to the west, and easterly winds along the equator Enhanced southeasterly winds off Sumatra-Java lead to anomalously strong upwelling there.

5 Purpose of this study: Evaluate the dynamics underlying the occurrence of boreal summer-fall surface chlorophyll bloom associated with the Indian Ocean Dipole. Approach: Conduct EOF analysis on MODIS Chl-a, SST and surface winds. Examine the co-occurrence and co-location of each variables in the EOF modes. 5/19

6 Data Monthly Chl-a from MODIS (Jul.2002 Dec.2013). Monthly SST from NOAA (Jan Dec.2012). Monthly winds from ECMWF (Jan.2002 Dec.2012). Methods Seasonal averaged of all variables: DJF, MAM, JJA, SON ß missing data problems (Chl-a). EOF analysis on each seasonally averaged variables. Explain dynamical variability à physical oceanography. 6/19

7 Spatio-temporal variability The coastal area show high variability for all variables. The wind-mixing reveals a very-high variability in the area off west Sumatra-Java. 7/19

8 Spatial Function of EOF-1 Coherent temporal variation in CHL, SST and Ekman pumping in the SETIO region, except the wind mixing. High variability of wind-mixing is observed off west Sumatra-Java, co located with high SST and strong wind during negative IOD. 8/19

9 Temporal Function of EOF-1 Temporal variability is dominated by seasonal variation, though it also reveals interannual modulation. Relatively high weight during 2006 and 2008, and the correlations with DMI time series are significant at 90% confidence level. 9/19

10 Spatial Function of EOF-2 The EOF-2 pattern is a mirror of the EOF-1 pattern. CHL and SST reveal an east-west asymmetry. The positive (negative) weight in Ekman pumping is co-located with the positive (negative) weight in CHL. Strong positive weight of the wind-induce mixing is co-located with strong positive (negative) weight in CHL (SST). 10/19

11 Temporal Function of EOF-2 The second mode mostly captured the interannual variations, in particular strong events in 2006 (piod) and 2010 (niod). Correlations of PC CHL and PC wind curl with DMI time series are significant at 99%, while correlations of PC SST and PC windmixing with DMI are significant at 80%. 11/19

12 Spatial Function of EOF-1 (JJA) a). EOF-1 Chl-a (JJA: 98.2%) c). EOF-1 Wind-curl (JJA: 86.8%) b). EOF-1 SST (JJA: 91.1%) d). EOF-1 Wind-mixing (JJA: 85.9%) The JJA spatial EOF-1 pattern resembles that of EOF-1 pattern for all-season analysis. The SST patterns show 180 out of phase with the CHL pattern. 12/19

13 Temporal Function of EOF-1 (JJA) Only PC SST and wind-curl shows significant correlation with the DMI. JJA is a southeasterly monsoon season (upwelling period) and it is also the development phase of the IOD event. 13/19

14 Spatial Function of EOF-1 (SON) a). EOF-1 Chl-a (SON: 98.1%) c). EOF-1 Wind-curl (SON: 78.3%) b). EOF-1 SST (SON: 82.2%) d). EOF-1 Wind-mixing (SON: 65.9%) The SON spatial EOF-1 pattern resembles that of EOF-2 pattern for all-season analysis. 14/19

15 Temporal Function of EOF-1 (SON) Only PC CHL and SST shows significant correlation with the DMI. The IOD event mostly reaches its peak phase during SON season. During peak IOD event in SON, weak surface winds are observed over the Indonesian region. 15/19

16 Time-series of Dipole Mode Index (July 2002 December 2013) There are two strong IOD events during the study period: positive IOD in 2006 and negative IOD in /19

17 SST and wind anomalies during IOD events SST off Sumatra-Java reached maximum anomaly during SON season. The location of maximum SST and winds during niod shift southward compared to those during piod. Winds over the Indonesian region are relatively weak during IOD event, but there are strong along the western coast of Sumatra. 17/19

18 Summary (1) u Spatial eigenfunctions of the first EOF mode reveal broad areas that exhibit coherent temporal variation in CHL, SST and Ekman pumping in the SETIO region. u The corresponding principal component time series reveals a robust seasonal variation intermitted by a relatively weak interannual variation. u The second EOF mode exhibited a distinct interannual variation with high interannual variation in CHL variation appearing mostly off Sumatra-Java, co-located with high variation in SST, Ekman pumping and wind-induced mixing. 18/19

19 Summary (2) u The 1 st EOF mode for JJA season indicates high variability of the CHL along the southern coast of Indonesia and within the eastern Indonesian seas, and it is 180 out of phase with SST. u The CHL shows strong correlation with the Ekman pumping, but it does not significantly correlate with the DMI, suggesting that the CHL bloom during JJA season (development phase of the IOD event) is mostly associated with the seasonal upwelling favorable winds. u The 1 st EOF mode for SON season reveals high variability of the CHL confined to the southern coast of Java and it is 180 out of phase with SST. u The CHL shows significant correlation with the DMI, but it does not correlate with the Ekman pumping, suggesting that the CHL bloom during the peak phase of the IOD event may be generated by the alongshore upwelling-favorable winds in the preceding season. 19/19

20 THANK YOU Dr. Iskhaq Iskandar Jurusan Fisika, Fakultas MIPA Universitas Sriwijaya South Sumatra, INDONESIA

21 Correlation all season

22 Correlation JJA and SON seasons