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Quantifying the Intra-Regional Precipitation Variability in Northwestern China over the Past 1,400 Years.

Lee HF, Pei Q, Zhang DD, Choi KP - PLoS ONE (2015)

Bottom Line: Also, we offer statistical evidence of El Niño Southern Oscillation (Indo-Pacific warm pool sea surface temperature and China-wide land surface temperature) as the prominent multi-decadal to centennial (centennial to multi-centennial) determinant of the IRPV in NW China.The present study contributes to the quantitative validation of the long-term IRPV in NW China and its driving forces, covering the periods with and without instrumental records.It may help to comprehend the complex hydro-climatic regimes in the region.

View Article: PubMed Central - PubMed

Affiliation: Department of Geography, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China; International Centre of China Development Studies, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.

ABSTRACT
There has been a surge of paleo-climatic/environmental studies of Northwestern China (NW China), a region characterized by a diverse assortment of hydro-climatic systems. Their common approach, however, focuses on "deducing regional resemblance" rather than "exploring regional variance." To date, efforts to produce a quantitative assessment of long-term intra-regional precipitation variability (IRPV) in NW China has been inadequate. In the present study, we base on historical flood/drought records to compile a decadal IRPV index for NW China spanned AD580-1979 and to find its major determinants via wavelet analysis. Results show that our IRPV index captures the footprints of internal hydro-climatic disparity in NW China. In addition, we find distinct ~120-200 year periodicities in the IRPV index over the Little Ice Age, which are attributable to the change of hydro-climatic influence of ocean-atmospheric modes during the period. Also, we offer statistical evidence of El Niño Southern Oscillation (Indo-Pacific warm pool sea surface temperature and China-wide land surface temperature) as the prominent multi-decadal to centennial (centennial to multi-centennial) determinant of the IRPV in NW China. The present study contributes to the quantitative validation of the long-term IRPV in NW China and its driving forces, covering the periods with and without instrumental records. It may help to comprehend the complex hydro-climatic regimes in the region.

No MeSH data available.


Related in: MedlinePlus

Wavelet coherency between the IRPV index and Equatorial Pacific SST/China-wide land surface temperature.(A) Eastern Tropical Pacific Ocean SST [68] and the IRPV. (B) Indo-Pacific warm pool SST [69] and the IRPV. (C) China-wide land surface temperature [48] and the IRPV. For the upper-left graphs of A–C, the color code for coherence values varies from dark blue (low values) to dark red (high values). The black curve indicates the cone of influence that delimits the region not influenced by edge effects and the dashed line show the α = 10% significance levels computed based on 1,000 Markov bootstrapped series. For the lower-left graphs of A–C, the dotted lines represent phase difference; the red line represents the phase of the SST/land surface temperature considered; and the blue lines represent the phase of IRPV. For the lower-right graph of A–C, the distribution of the phase difference of the two considered time-series is shown.
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pone.0131693.g009: Wavelet coherency between the IRPV index and Equatorial Pacific SST/China-wide land surface temperature.(A) Eastern Tropical Pacific Ocean SST [68] and the IRPV. (B) Indo-Pacific warm pool SST [69] and the IRPV. (C) China-wide land surface temperature [48] and the IRPV. For the upper-left graphs of A–C, the color code for coherence values varies from dark blue (low values) to dark red (high values). The black curve indicates the cone of influence that delimits the region not influenced by edge effects and the dashed line show the α = 10% significance levels computed based on 1,000 Markov bootstrapped series. For the lower-left graphs of A–C, the dotted lines represent phase difference; the red line represents the phase of the SST/land surface temperature considered; and the blue lines represent the phase of IRPV. For the lower-right graph of A–C, the distribution of the phase difference of the two considered time-series is shown.

Mentions: We calculate the wavelet coherency between the Eastern Tropical Pacific Ocean SST (derived from diatom records in El Junco Lake, Galápagos and spanned AD731–2004) [68] and the IRPV index. Only intermittent 160+ year bands are found (Fig 9A). In parallel, we calculate the wavelet coherency between the Indo-Pacific warm pool SST (derived from sediment cores in Makassar Strait, Indonesia and spanned AD20–1959) [69] and the IRPV index (Fig 9B), and identify a significant ~160–200 year band. The band is relatively stable, except its periodicities weaken in the MWP–LIA transition as well as the transition between the LIA and the warm 20th century. Interestingly, during the above transitions, the 160+ year periodicities in the wavelet coherency between the Eastern Tropical Pacific Ocean SST and IRPV are relatively strong. This suggests that although the Eastern Tropical Pacific Ocean SST itself may not be a very important factor, it supplements the Indo-Pacific warm pool SST in driving the IRPV in NW China. As the periodicities in our wavelet coherency results seem to be modulated by the alternation of climatic episodes, we also compare the IRPV index with China-wide land surface temperature (derived from multi-proxies via Partial Least Square regression method and spanned AD1–1999) [48]. Relatively continuous ~250 year periodicities are found in their coherency (Fig 9C). Briefly, the Indo-Pacific warm pool SST and China-wide land surface temperature is revealed to be the prominent driver of IRPV in NW China at the centennial to multi-centennial time-scale.


Quantifying the Intra-Regional Precipitation Variability in Northwestern China over the Past 1,400 Years.

Lee HF, Pei Q, Zhang DD, Choi KP - PLoS ONE (2015)

Wavelet coherency between the IRPV index and Equatorial Pacific SST/China-wide land surface temperature.(A) Eastern Tropical Pacific Ocean SST [68] and the IRPV. (B) Indo-Pacific warm pool SST [69] and the IRPV. (C) China-wide land surface temperature [48] and the IRPV. For the upper-left graphs of A–C, the color code for coherence values varies from dark blue (low values) to dark red (high values). The black curve indicates the cone of influence that delimits the region not influenced by edge effects and the dashed line show the α = 10% significance levels computed based on 1,000 Markov bootstrapped series. For the lower-left graphs of A–C, the dotted lines represent phase difference; the red line represents the phase of the SST/land surface temperature considered; and the blue lines represent the phase of IRPV. For the lower-right graph of A–C, the distribution of the phase difference of the two considered time-series is shown.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4495927&req=5

pone.0131693.g009: Wavelet coherency between the IRPV index and Equatorial Pacific SST/China-wide land surface temperature.(A) Eastern Tropical Pacific Ocean SST [68] and the IRPV. (B) Indo-Pacific warm pool SST [69] and the IRPV. (C) China-wide land surface temperature [48] and the IRPV. For the upper-left graphs of A–C, the color code for coherence values varies from dark blue (low values) to dark red (high values). The black curve indicates the cone of influence that delimits the region not influenced by edge effects and the dashed line show the α = 10% significance levels computed based on 1,000 Markov bootstrapped series. For the lower-left graphs of A–C, the dotted lines represent phase difference; the red line represents the phase of the SST/land surface temperature considered; and the blue lines represent the phase of IRPV. For the lower-right graph of A–C, the distribution of the phase difference of the two considered time-series is shown.
Mentions: We calculate the wavelet coherency between the Eastern Tropical Pacific Ocean SST (derived from diatom records in El Junco Lake, Galápagos and spanned AD731–2004) [68] and the IRPV index. Only intermittent 160+ year bands are found (Fig 9A). In parallel, we calculate the wavelet coherency between the Indo-Pacific warm pool SST (derived from sediment cores in Makassar Strait, Indonesia and spanned AD20–1959) [69] and the IRPV index (Fig 9B), and identify a significant ~160–200 year band. The band is relatively stable, except its periodicities weaken in the MWP–LIA transition as well as the transition between the LIA and the warm 20th century. Interestingly, during the above transitions, the 160+ year periodicities in the wavelet coherency between the Eastern Tropical Pacific Ocean SST and IRPV are relatively strong. This suggests that although the Eastern Tropical Pacific Ocean SST itself may not be a very important factor, it supplements the Indo-Pacific warm pool SST in driving the IRPV in NW China. As the periodicities in our wavelet coherency results seem to be modulated by the alternation of climatic episodes, we also compare the IRPV index with China-wide land surface temperature (derived from multi-proxies via Partial Least Square regression method and spanned AD1–1999) [48]. Relatively continuous ~250 year periodicities are found in their coherency (Fig 9C). Briefly, the Indo-Pacific warm pool SST and China-wide land surface temperature is revealed to be the prominent driver of IRPV in NW China at the centennial to multi-centennial time-scale.

Bottom Line: Also, we offer statistical evidence of El Niño Southern Oscillation (Indo-Pacific warm pool sea surface temperature and China-wide land surface temperature) as the prominent multi-decadal to centennial (centennial to multi-centennial) determinant of the IRPV in NW China.The present study contributes to the quantitative validation of the long-term IRPV in NW China and its driving forces, covering the periods with and without instrumental records.It may help to comprehend the complex hydro-climatic regimes in the region.

View Article: PubMed Central - PubMed

Affiliation: Department of Geography, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China; International Centre of China Development Studies, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.

ABSTRACT
There has been a surge of paleo-climatic/environmental studies of Northwestern China (NW China), a region characterized by a diverse assortment of hydro-climatic systems. Their common approach, however, focuses on "deducing regional resemblance" rather than "exploring regional variance." To date, efforts to produce a quantitative assessment of long-term intra-regional precipitation variability (IRPV) in NW China has been inadequate. In the present study, we base on historical flood/drought records to compile a decadal IRPV index for NW China spanned AD580-1979 and to find its major determinants via wavelet analysis. Results show that our IRPV index captures the footprints of internal hydro-climatic disparity in NW China. In addition, we find distinct ~120-200 year periodicities in the IRPV index over the Little Ice Age, which are attributable to the change of hydro-climatic influence of ocean-atmospheric modes during the period. Also, we offer statistical evidence of El Niño Southern Oscillation (Indo-Pacific warm pool sea surface temperature and China-wide land surface temperature) as the prominent multi-decadal to centennial (centennial to multi-centennial) determinant of the IRPV in NW China. The present study contributes to the quantitative validation of the long-term IRPV in NW China and its driving forces, covering the periods with and without instrumental records. It may help to comprehend the complex hydro-climatic regimes in the region.

No MeSH data available.


Related in: MedlinePlus