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Impacts of IOD, ENSO and ENSO Modoki on the Australian Winter Wheat Yields in Recent Decades.

Yuan C, Yamagata T - Sci Rep (2015)

Bottom Line: It is found that IOD plays a dominant role in the recent three decades; the wheat yield is reduced (increased) by -28.4% (12.8%) in the positive (negative) IOD years.In contrast, the ENSO Modoki may have its distinct impacts on the wheat yield variations, but they are much smaller compared to those of IOD.The present study may lead to a possible scheme for predicting wheat yield variations in Australia in advance by use of simple climate mode indices.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Meteorological Disaster of Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science &Technology, Nanjing 210044, China.

ABSTRACT
Impacts of the Indian Ocean Dipole (IOD), two different types of El Niño/Southern Oscillation (ENSO): canonical ENSO and ENSO Modoki, on the year-to-year winter wheat yield variations in Australia have been investigated. It is found that IOD plays a dominant role in the recent three decades; the wheat yield is reduced (increased) by -28.4% (12.8%) in the positive (negative) IOD years. Although the canonical ENSO appears to be responsible for the wheat yield variations, its influences are largely counted by IOD owing to their frequent co-occurrence. In contrast, the ENSO Modoki may have its distinct impacts on the wheat yield variations, but they are much smaller compared to those of IOD. Both the observed April-May and the predicted September-November IOD indices by the SINTEX-F ocean-atmosphere coupled model initialized on April 1st just before the sowing season explain ~15% of the observed year-to-year wheat yield variances. The present study may lead to a possible scheme for predicting wheat yield variations in Australia in advance by use of simple climate mode indices.

No MeSH data available.


Related in: MedlinePlus

(a,b) Correlation coefficients of SON DMI with NDJ Niño3 (solid line) and JJA EMI (dotted line), (c,d) skewness and (e,f) variability of SON DMI (red), NDJ Niño3 (blue) and JJA EMI (gray) based on the 31-year sliding windows with (a,c,e) ERSST and (b,d,f) HadISST. The skewness of JJA EMI in (c,d) has been divided by 2 and the variability of NDJ Niño3 in (e,f) has been divided by 4 for a better comparison. The year in X axis denotes the central year of the 31-year sliding window.
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f4: (a,b) Correlation coefficients of SON DMI with NDJ Niño3 (solid line) and JJA EMI (dotted line), (c,d) skewness and (e,f) variability of SON DMI (red), NDJ Niño3 (blue) and JJA EMI (gray) based on the 31-year sliding windows with (a,c,e) ERSST and (b,d,f) HadISST. The skewness of JJA EMI in (c,d) has been divided by 2 and the variability of NDJ Niño3 in (e,f) has been divided by 4 for a better comparison. The year in X axis denotes the central year of the 31-year sliding window.

Mentions: As shown in Fig. 3, the multi-linear regression coefficients based on the 31-year sliding windows since 1950 further confirm the stronger influences of IOD on the Australian wheat yield in the recent decades. The coefficient related to IOD has a clear increasing trend. In contrast, the coefficient related to the canonical ENSO is approaching zero with time. This does not mean that the potential impacts of the canonical ENSO on the Australian wheat are declining. Rather, they are counted by the frequent co-occurring IOD impacts. As shown in Fig. 4a,b, the correlation coefficient between the DJF Niño3 and SON DMI has been increasing since 1950 and reaches ~0.7 in the last three decades. Cai et al. have shown that the teleconnection of canonical El Niño to extratropical Australia is via the emanated Rossby waves by the eastern tropical Indian Ocean SST anomalies, which can be counted by the positive IOD10. Since the positive skewness of canonical ENSO has been increasing since 1950 (Fig. 4c,d), this may explain why the impacts of canonical ENSO on the Australia wheat yields are more and more counted by IOD. On the other hand, the ENSO Modoki shows a negative skewness. Since there are less co-occurrence between La Niña Modoki and the negative IOD (Supplementary Table 1), the influences of ENSO Modoki on the wheat yields may have some independence from IOD, and they may increase in future with increasing variability (Fig. 4e,f).


Impacts of IOD, ENSO and ENSO Modoki on the Australian Winter Wheat Yields in Recent Decades.

Yuan C, Yamagata T - Sci Rep (2015)

(a,b) Correlation coefficients of SON DMI with NDJ Niño3 (solid line) and JJA EMI (dotted line), (c,d) skewness and (e,f) variability of SON DMI (red), NDJ Niño3 (blue) and JJA EMI (gray) based on the 31-year sliding windows with (a,c,e) ERSST and (b,d,f) HadISST. The skewness of JJA EMI in (c,d) has been divided by 2 and the variability of NDJ Niño3 in (e,f) has been divided by 4 for a better comparison. The year in X axis denotes the central year of the 31-year sliding window.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4663488&req=5

f4: (a,b) Correlation coefficients of SON DMI with NDJ Niño3 (solid line) and JJA EMI (dotted line), (c,d) skewness and (e,f) variability of SON DMI (red), NDJ Niño3 (blue) and JJA EMI (gray) based on the 31-year sliding windows with (a,c,e) ERSST and (b,d,f) HadISST. The skewness of JJA EMI in (c,d) has been divided by 2 and the variability of NDJ Niño3 in (e,f) has been divided by 4 for a better comparison. The year in X axis denotes the central year of the 31-year sliding window.
Mentions: As shown in Fig. 3, the multi-linear regression coefficients based on the 31-year sliding windows since 1950 further confirm the stronger influences of IOD on the Australian wheat yield in the recent decades. The coefficient related to IOD has a clear increasing trend. In contrast, the coefficient related to the canonical ENSO is approaching zero with time. This does not mean that the potential impacts of the canonical ENSO on the Australian wheat are declining. Rather, they are counted by the frequent co-occurring IOD impacts. As shown in Fig. 4a,b, the correlation coefficient between the DJF Niño3 and SON DMI has been increasing since 1950 and reaches ~0.7 in the last three decades. Cai et al. have shown that the teleconnection of canonical El Niño to extratropical Australia is via the emanated Rossby waves by the eastern tropical Indian Ocean SST anomalies, which can be counted by the positive IOD10. Since the positive skewness of canonical ENSO has been increasing since 1950 (Fig. 4c,d), this may explain why the impacts of canonical ENSO on the Australia wheat yields are more and more counted by IOD. On the other hand, the ENSO Modoki shows a negative skewness. Since there are less co-occurrence between La Niña Modoki and the negative IOD (Supplementary Table 1), the influences of ENSO Modoki on the wheat yields may have some independence from IOD, and they may increase in future with increasing variability (Fig. 4e,f).

Bottom Line: It is found that IOD plays a dominant role in the recent three decades; the wheat yield is reduced (increased) by -28.4% (12.8%) in the positive (negative) IOD years.In contrast, the ENSO Modoki may have its distinct impacts on the wheat yield variations, but they are much smaller compared to those of IOD.The present study may lead to a possible scheme for predicting wheat yield variations in Australia in advance by use of simple climate mode indices.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Meteorological Disaster of Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science &Technology, Nanjing 210044, China.

ABSTRACT
Impacts of the Indian Ocean Dipole (IOD), two different types of El Niño/Southern Oscillation (ENSO): canonical ENSO and ENSO Modoki, on the year-to-year winter wheat yield variations in Australia have been investigated. It is found that IOD plays a dominant role in the recent three decades; the wheat yield is reduced (increased) by -28.4% (12.8%) in the positive (negative) IOD years. Although the canonical ENSO appears to be responsible for the wheat yield variations, its influences are largely counted by IOD owing to their frequent co-occurrence. In contrast, the ENSO Modoki may have its distinct impacts on the wheat yield variations, but they are much smaller compared to those of IOD. Both the observed April-May and the predicted September-November IOD indices by the SINTEX-F ocean-atmosphere coupled model initialized on April 1st just before the sowing season explain ~15% of the observed year-to-year wheat yield variances. The present study may lead to a possible scheme for predicting wheat yield variations in Australia in advance by use of simple climate mode indices.

No MeSH data available.


Related in: MedlinePlus