East Asian Monsoon Signals Reflected in Temperature and Precipitation Changes over the Past 300 Years in the Middle and Lower Reaches of the Yangtze River

<div><p>Based on observational data and Asian monsoon intensity datasets from China, the relationships between the East Asian winter monsoon index and winter temperature, the East Asian summer monsoon index and Meiyu precipitation over the middle and lower reaches of the Yangtze River, were analyzed. We found that the monsoon signals were reflected in the temperature and Meiyu precipitation variations. Thus, we used the reconstructed Meiyu precipitation and winter temperature series for the past 300 years and detected the summer/winter monsoon intensity signals using multi-taper spectral estimation method and wavelet analysis. The main periodicities of Meiyu precipitation and winter temperature, such as interannual cycle with 2–7-year, interdecadal-centennial cycles with 30–40-year and 50–100-year, were found. The good relationships between the East Asian summer and winter monsoons suggested that they were in phase at 31-year cycle, while out of phase at 100-year cycle, but with 20-year phase difference. In addition, the winter monsoon intensity may be regulated by the North Atlantic Oscillation, the Arctic Oscillation and the Atlantic Multidecadal Oscillation, and the summer monsoon is closely related to the signal intensities of the Pacific Decadal Oscillation.</p></div

Study area and locations of the proxy data used for the annual temperature reconstruction in Xinjiang.

<p>Bottom right: subregions categorized by climate regionalization and the coherence of the temperature change in China (reproduced from Ref. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144210#pone.0144210.ref014" target="_blank">14</a>]).</p

Relationship between EAWM, NAO, AO and AMO at 50–100-year cycles, AO and AMO use the green and red color axes (a), and EASM and PDO at 30–40-year cycles (b).

<p>Relationship between EAWM, NAO, AO and AMO at 50–100-year cycles, AO and AMO use the green and red color axes (a), and EASM and PDO at 30–40-year cycles (b).</p

Reconstruction of annual temperature anomalies (with a reference period of 1901–2000; the same for the other series) in Xinjiang during 1850–2001 and comparison with other data.

<p>(a) Comparison of the reconstruction and observation for 1951–2001. (b) Annual temperature anomalies with a 95% confidence interval reconstructed by the signal decomposition and synthesis method. (c) Annual temperature anomalies with a 95% confidence interval reconstructed by traditional method. (d) Observed temperature anomalies at Fergana (40.37°N, 71.75°E), Republic of Uzbekistan for 1881–2001 (data from <a href="http://climexp.knmi.nl/" target="_blank">http://climexp.knmi.nl/</a>). (e) NH land air temperature anomalies for 1850–2001 from the Climatic Research Unit, University of East Anglia (<a href="http://www.cru.uea.ac.uk/cru/data/temperature/CRUTEM4v-nh.dat" target="_blank">http://www.cru.uea.ac.uk/cru/data/temperature/CRUTEM4v-nh.dat</a>). The box between panel (b) and (c) shows the approximate time intervals for glacial activity in the Tianshan Mountains and the other western China highlands during the 20th century [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144210#pone.0144210.ref041" target="_blank">41</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144210#pone.0144210.ref043" target="_blank">43</a>].</p

Standardized climate reconstructions and spectra analysis.

<p>(a) winter temperature and (b) Meiyu precipitation over the MLRYR. (1) Standardized climate reconstructions; (2) wavelet spectra analysis; region circled by black contours passing the 90% confidence level; cross-hatched areas represent the cone of influence calculated by the standard program from <a href="http://ion.researchsystems.com/" target="_blank">http://ion.researchsystems.com/</a> [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131159#pone.0131159.ref041" target="_blank">41</a>]; (3) multi-taper method analysis with 90% and 95% confidence levels [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131159#pone.0131159.ref042" target="_blank">42</a>].</p

Correlations between East Asian monsoon indices and temperature/precipitation during the observed period.

<p>(a) winter monsoon index and winter temperature and (b) summer monsoon index and June–July precipitation. The shaded areas from red to yellow passed negative correlation at 99%, 95%, 90% confidence levels, and green color indicates positive correlated regions.</p

Comparison of IMFs at different scales derived by EEMD (red line for reconstruction by the new method, blue line for that by the traditional method).

<p>Comparison of IMFs at different scales derived by EEMD (red line for reconstruction by the new method, blue line for that by the traditional method).</p

Variations of EAWM and EASM over the interdecadal–centennial scale: (a) EAWM and (b) EASM.

<p>Variations of EAWM and EASM over the interdecadal–centennial scale: (a) EAWM and (b) EASM.</p

Global and regional climate responses to national-committed emission reductions under the Paris agreement

<p>To stabilize global mean temperature change within the range of 1.5–2.0°C in accordance with the Paris Agreement, countries worldwide submitted their Intended Nationally Determined Contributions with their proposed emission reductions. However, it remains unclear what the resulting climate change in terms of temperature and precipitation would be in response to the Intended Nationally Determined Contribution emission efforts. This study quantifies the global and regional temperature and precipitation changes in response to the updated Intended Nationally Determined Contribution scenarios, using simulations of 14 Fifth Coupled Climate Model Intercomparison Project models. Our results show that Intended Nationally Determined Contribution emissions would lead to a global mean warming of 1.4°C (1.3–1.7°C) in 2030 and 3.2°C (2.6–4.3°C) in 2100, above the preindustrial level (the 1850–1900 average). Spatially, the Arctic is projected to have the largest warming, 2.5 and 3 times the global average for 2030 and 2100, respectively, with strongest positive trends at 70–85°N over Asia, Europe and North America (6.5–9.0°C). The excessive warming under Intended Nationally Determined Contribution scenarios is substantially above the 1.5°C or 2.0°C long-term stabilization level. Global mean precipitation is projected to be similar to preindustrial levels in 2030, and an increase of 6% (4–9%) by 2100 compared with the preindustrial level. Regional precipitation changes will be heterogeneous, with significant increases over the equatorial Pacific (about +120%) and strong decreases over the Mediterranean, North Africa and Central America (−15% – −30%). These results clearly show that it is necessary to adjust and strengthen national mitigation efforts on current Intended Nationally Determined Contributions to meet the long-term temperature target.</p

Estimated effects of sodium reduction strategy for 60 intervention compared to 59 control villages.

<p>Estimated effects of sodium reduction strategy for 60 intervention compared to 59 control villages.</p