Attribution of Forced and internal Chinese climate variability in the Common era (Afiche)
Final Report Abstract
We generated a gridded temperature reconstruction for East Asia using selected 61 multi-proxy evidences. We extend available reconstructions to 2000 years and also assess uncertainties by applying a stochastic model for a multi-proxy network over a larger area. Results suggest warmth until the 3rd century CE, followed by cooling until the 10th century. Warm conditions are found ca. 900-1200 CE, in the early 14th century and at the turn of the 15th century. The period 1450-1850 CE was cooler than today. From the 1850s, temperatures increased with the 1990s being likely the warmest decade. The reconstruction agrees well with climate model simulations for the past 1250 years. Changes of solar irradiance and clusters of volcanic eruptions were the major drivers during the preindustrial period, anthropogenic forcing was responsible for the recent warming. We generated a gridded reconstruction of warm season precipitation for China spanning the past half millennium (paper in preparation). It compares well to existed sub-regional climate reconstructions and is consistent with documented historical information and nature evidences from various resources. Together with GCM simulations, the product can be then used to analyze the influences of natural forcing and anthropogenic forcing on East Asia monsoon systems. We more precisely calculated the strength of long-term persistence (long term memory, LTM) in world-wide tree ring width chronologies using detrended fluctuation analysis (DFA), and found the value (0.8) is larger than the value in observed temperature/rainfall (0.6/0.5) data over inland continent. Furthermore, we found the LTM in proxy chronologies propagates into the reconstructed regional climate and may be intensified while spatial correlations may lead to enforcing the low-frequencies, no matter whether based on TRW-only proxies or multi-proxies. One main characteristic of data with LTM is that the successive increments are positively correlated, and this could cause several effects which need special cautions: i) A “significant” trend in the whole data length and too strong local trends in certain periods; ii) Intensified low-frequency variations or say overestimated mean state of climate anomalies in certain time periods; iii) Unrealistic cluster of extreme events.
Publications
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2015: Detrended partial-cross-correlation analysis: a new method for analyzing correlations in complex systems. Nature Sci. Rep., 5, 8143
Yuan, N., Z. Fu, H. Zhang, L. Piao, E. Xoplaki, and J. Luterbacher
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2015: Modified climate with long term memory in tree ring proxies. Environmental research letters, 10, 084020
Zhang, H., N. Yuan, E. Xoplaki, J. Werner, U. Büntgen, J. Esper, K. Treydte, and J. Luterbacher
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2016: A novel way to detect correlations on multi-time scales, with temporal evolution and for multi-variables. Nature Sci. Reports, 6, 27707
Yuan, N., Luterbacher, J., C. Zu, and Xoplaki, E.
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2016: Eurasian cooling and societal change during the Late Antique Little Ice Age (536 to ~660 CE). Nature Geosci., 9, 231–236
Büntgen, U., Myglan, V., Ljungqvist, F.C., McCormick, M., Di Cosmo, N., Sigl, M., Jungclaus, J., Wagner, S., Krusic, P.J., Esper, J., Kaplan, J.O., de Vaan, M.A.C., Luterbacher, J., Wacker, L., Tegel, W., and Kirdyanov, A.V.
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2016: European summer temperatures since Roman times. Environ. Res. Lett., 11, 024001
Luterbacher, J. et al.
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2016: Review of treering based temperature reconstructions of the past millennium. Quat. Sci. Rev., 145, 134-151
Esper, J., Krusic, P.J., Ljungqvist, F.C., Luterbacher, J., Carrer, M., Cook, E.R., Davi, N.K., Hartl-Meier, C., Kirdyanov, A., Konter, O., Myglan, V., Timonen, M., Treydte, K., Trouet, V., Villalba, R., Wilson, R.S., Yang, B., and Büntgen, U.
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2017: Biome changes in Asia since the mid-Holocene – an analysis of different transient Earth system model simulations, Clim. Past 13. 107-134
Dallmeyer, A., Claussen, M., Ni, J., Cao, X., Wang, Y., Fischer, N., Pfeiffer, M., Jin, L., Khon, V., Wagner, S., Haberkorn, K., and Herzschuh, U.
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2017: Comparing data and model estimates of hydroclimate variability and change over the Common Era. Clim Past. 13, 1851–1900
Hydro2k Consortium: Smerdon, J.E., Luterbacher, J., et al.
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2017: Internal and external forcing of multidecadal Atlantic climate variability over the past 1200 years. Nature Geosci., 10, 512-517
Wang, J., Yang, B., Ljungqvist, F.C., Luterbacher, J., Osborn, T.J., Briffa, K.R., and Zorita, E.
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2017: The PMIP4 simulations of the last millennium (PMIP past1000). Geosci. Model Dev., 10, 4005–4033
Jungclaus, J.H., Bard, E., Baroni, M., Braconnot, P., Cao, J., Chini, L.P., Egorova, T., Evans, M., González-Rouco, J.F., Goosse, H., Hurtt, G.C., Joos, F., Kaplan, J.O., Khodri, M., Klein Goldewijk, K., Krivova, N., LeGrande, A.N., Lorenz, S.J., Luterbacher, J., Maycock, A.C., Man, W., Meinshausen, M., Moberg, A., Muscheler, R., Nehrbass-Ahles, C., Ottera, O.H., Otto-Bliesner, B.I, Phipps, S.J., Pongratz, J., Rozanov, E., Schmidt, G.A., Schmidt, H., Schmutz, W., Schurer, A., Shapiro, A.I., Sigl, M., Smerdon, J.E., Solanki, S.K., Toohey, M., Timmreck, C., Usoskin, I.G., Wagner, S., Wu, C.-J., Yeo, K.L., Zanchettin, D., Zhang, Q., and Zorita, E.
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2017: Weakening of annual temperature cycle over the Tibetan Plateau since the 1870s. Nature Comm., 8:14008
Duan, J., Esper, J., Büntgen, U., Li, L., Xoplaki, E., Zhang, H., Wang, L., Fang, Y., and Luterbacher, J.
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2018: East Asian warm season temperature variations over the past two millennia. Nat. Sci. Reports, 8, 7702
Zhang, H., Werner, J.P., García-Bustamante, E., González-Rouco, F.J., Wagner, S., Zorita, E., Fraedrich, K., Jungclaus, J., Zhu, X., Xoplaki, E., Chen, F., Duan, J., Ge, Q., Hao, Z., Ivanov, M., Talento, S., Schneider, L., Wang, J., Yang, B., and Luterbacher, J.
