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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 ASM [17].For the upper-left graph, 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 graph, the dotted lines represent phase difference; the red line represents the phase of ASM; and the blue lines represent the phase of IRPV. For the lower-right graph, the distribution of the phase difference of the two considered time-series is shown.
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pone.0131693.g007: Wavelet coherency between the IRPV index and ASM [17].For the upper-left graph, 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 graph, the dotted lines represent phase difference; the red line represents the phase of ASM; and the blue lines represent the phase of IRPV. For the lower-right graph, the distribution of the phase difference of the two considered time-series is shown.

Mentions: Our study area covers both the Westerlies-dominated and ASM-dominated regions (i.e., Regions A and B). As the variation of monsoon precipitation is generally regarded one of the most important factors in driving the precipitation disparity between the two regions [25, 59], we compare the IRPV index with the strength of ASM, which is the major determinant of monsoon precipitation. The employed ASM reconstruction is derived from the stalagmite oxygen isotope in Wanxiang Cave in Gansu and spanned AD192–2003 [17]. The result shows that there are significant 160+ year periodicities in the ASM–IRPV coherency (Fig 7). However, the periodicities are intermittent, which are relatively weak in the MWP and the warm 20th century. The above findings indicate that in general, the IRPV in NW China is driven by the fluctuation of monsoon precipitation. Yet, subject to the intermittence of the periodicities in the ASM–IRPV coherency (Fig 7), together with the fact that the monsoon precipitation in NW China is simultaneously modulated by, or interacts with, various ocean-atmospheric modes [6–9, 11, 18, 24, 32, 33, 40], it is necessary to examine whether the variability of IRPV index is also determined by the ocean-atmospheric modes.


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 ASM [17].For the upper-left graph, 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 graph, the dotted lines represent phase difference; the red line represents the phase of ASM; and the blue lines represent the phase of IRPV. For the lower-right graph, the distribution of the phase difference of the two considered time-series is shown.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4495927&req=5

pone.0131693.g007: Wavelet coherency between the IRPV index and ASM [17].For the upper-left graph, 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 graph, the dotted lines represent phase difference; the red line represents the phase of ASM; and the blue lines represent the phase of IRPV. For the lower-right graph, the distribution of the phase difference of the two considered time-series is shown.
Mentions: Our study area covers both the Westerlies-dominated and ASM-dominated regions (i.e., Regions A and B). As the variation of monsoon precipitation is generally regarded one of the most important factors in driving the precipitation disparity between the two regions [25, 59], we compare the IRPV index with the strength of ASM, which is the major determinant of monsoon precipitation. The employed ASM reconstruction is derived from the stalagmite oxygen isotope in Wanxiang Cave in Gansu and spanned AD192–2003 [17]. The result shows that there are significant 160+ year periodicities in the ASM–IRPV coherency (Fig 7). However, the periodicities are intermittent, which are relatively weak in the MWP and the warm 20th century. The above findings indicate that in general, the IRPV in NW China is driven by the fluctuation of monsoon precipitation. Yet, subject to the intermittence of the periodicities in the ASM–IRPV coherency (Fig 7), together with the fact that the monsoon precipitation in NW China is simultaneously modulated by, or interacts with, various ocean-atmospheric modes [6–9, 11, 18, 24, 32, 33, 40], it is necessary to examine whether the variability of IRPV index is also determined by the ocean-atmospheric modes.

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