Change of Dynasty correlated with Climate across the world
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Does climate influence dynastic change over time?
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Change of Dynasty correlated with Climate across the world
- 1. Climate Change & Culture Relationship Abdullah Khan Zehady (Andy) Southeast Asia: Tectonic Puzzles Professor James Ogg
- 2. Human Cultural Stage • Duration of the age of each stage varies depending on the region • Late Paleolithic • Mesolithic • Pre-agricultural material in northwest europe • Material from Levant • Levant: Large area in east mediterranean • Bronze age • Copper mined and alloyed with tin to produce bronze • Far-ranging trade network • Neolithic • New stone age • Progression of behavioral and cultural changes • Iron age • Production of iron based tools and weaponry
- 3. Map of China
- 5. Ancient China • Use of wild and domestic crops, domesticated animals • River Basin valley • Yellow river • Lake area • Concluded with the introduction of metal
- 7. Chinese Imperial Dynasties (2 ~ 3 Ka) • 3000 Yr ago - The Shang dynasty was conquered by the people of Zhou • 2221 Yr ago - Origin of the term “China” • 2250 Yr ago - Qin Shihuangdi extend Chinese rule as far south as Vietnam. • Chinese script • Chinese currency, and system of measurement • Expansion of roads and canals • The Great Wall.
- 8. Chinese Imperial Dynasties (0~2 Ka)
- 9. Causal Link between Climate Change & Human Crisis (Zhang et al. 2011b)
- 10. Pollen records (Northern China) (Li et al 2017) Locations of monsoonal Northern China and Fossil Pollen records from 11 lakes. Assumption Broad-scale pollen datasets from lake sediments can likely represent regional vegetation as well as climatic signals.
- 11. Location of Proxy Samples (Entire China) (Ge et al. 2017)
- 12. Temperature Anomaly for 5 Chinese Regions (Ge et al. 2013)
- 13. Reconstructed Temperature with uncertainties PCR: Principal Component Regression PLS: Projection to Latent Structures (Ge et al. 2017)
- 14. Does North Hemisphere Temperature match with Regional Chinese temperature?
- 15. Temperature Change in China for Past 2000 Years (Ge et al. 2017) Warm Period (AD) 1. 1 ~ 200 2. 550 ~ 760 3. 950 ~ 1300 4. 1900 ~ Cold Period (AD) 1. 210 ~ 350 2. 420 ~ 530 3. 780 ~ 940 4. 1320 ~ 1900
- 16. Dry-Wet Index
- 17. Little Ice age after Medieval Warm Period !! • PANN : Pollen-based Precipitation anomaly • TANN : Pollen-based Temperature anomaly(°C) • 17 Chinese nemrical historical record from the Han to Qing Dynasty • MCA (Medieval Climate Anomaly) / MWP(Medieval Warm Period) • LIA (Little Ice Age) • CWP (Current Warm Period) (Li et al 2017)
- 18. Temperature Anomaly(TANN) Records (Li et al 2017) • 4 Warm Period(-200~120, 640~760, 901~1300, and 1901~2000 AD) • 3 apparent cold periods (121e639, 761e900, and 1301e1900 AD)
- 19. Role of Solar activity – Spectral analysis of TANN Increased Total Solar Irradiance Enhanced thermal contrast between East Asian continent and North Pacific ocean Longer summer monsoon in North China More rainfall to North China where surface temperature is higher. Matches with 100, 50, 23 and 22 yr Cycle for solar activity. (Li et al 2017)
- 20. Precipitation Anomaly(PANN) Records Kiel Climate Model (KCM) (Li et al 2017)
- 21. Role of Solar activity – Spectral analysis of PANN Decreased Total Solar Irradiance Decreased Land temperature Intensified winter monsoon Decreased precipitation and temperature. Matches with 100, 50, 23 and 22 yr Cycle for solar activity. (Li et al 2017)
- 22. Worldwide temperature Proxy for 2000 Years (Horst-Joachim et al 2017)
- 23. ~190 year De Vries/Suess Cycle (Horst-Joachim et al 2017)
- 24. Global temperature reconstruction (Horst-Joachim et al 2017) Grey Curve: Global temperature mean G7 over the last 2000 years. The Fourier spectrum of G7 shows the strongest components as ~1000(Black), ~460 (Blue), and ~190(Green) year period
- 25. What measures to use to correlate with Historical/Cultural Change? Index Abre. Reference Economic level ED Wei et al., 2015 Grain yield grade GY Su et al., 2014 Grain price index GPI Ge et al., 2014 Fiscal grade FG Wei et al., 2014 Agriculturalist policy territory AT Zhang et al., 2014 Extreme flood years EF Hao et al., 2010 Extreme drought years ED Hao et al., 2010 Freeze disaster frequency FD Cai, 2009 Sand-dust event frequency SD ` et al, 1984 Famine index FI Fang et al., 2015 Locust frequency LF Li et al., 2010 Epidemic disaster frequency EPD Gong, 2003 Peasant uprising frequency PUF Fang et al., 2015 Number of wars NW Ge et al., 2014 N. of southward nomadic migrations SNW Pei and Zhang, 2014 Farming-pastoral boundary FPB Zhang et al., 2014 N. of estimated human population HP Li et al., 2009 (Li et al 2017)
- 26. Climate + Economic Variables (Li et al 2017)
- 27. Disaster + War in North China (Li et al 2017)
- 28. Grain Price contrasted with Harmony and crisis in Europe (Zhang et al. 2011b)
- 29. • Precipitation seems likely to be more influential than temperature. • Other Variables: El Nino-Southern Oscillation (ENSO) strength, increased volcanic eruptions and the resulting aerosol, greenhouse gases such as CO2 and CH4. What drives the overall macro-scale agro-ecological, geo-political, and bio-ecological shifts in NC? Precipitation Temperature
- 31. Responses to Climate change in Europe (Zhang et al. 2011b)
- 32. European epidemics and War (Zhang et al. 2011b)
- 33. Causal Link between Climate Change & Human Crisis (Zhang et al. 2011b)
- 34. Paleo-temperature variation and its impact on Europe and China
- 35. Remarks on the response of Climate Change • Climate change determines the fate of agrarian societies via the economy. • Economy interacts with numerous social factors. • Individual, short-term human crises are triggered by social problems. • Although social factors may explain some short- term crises in history, they cannot explain the synchronous occurrence of long-term crises across different climatic zones in the NH.
- 37. Impact on Chinese Dynasty.. • Downturns of most Chinese agroecological dynasties in NC – West Han, East Han, 5D & 10K (the era of Five Dynasties and Ten Kingdoms), Yuan, and Qing Dynasties – Caused by • Armed conflicts with the northern pastoral polities • Large-scale famines and peasant uprisings • Took place at notable dry episodes. The depressions of some agro-ecological dynasties such as the Sui, North Song, and Ming Dynasties – less drier but cold periods • The downfalls of Tang Dynasty – Internal political struggles with climatic change as a minor contributing factor • NC dry-winter monsoon being more influential in arid periods, whilst moist-summer monsoon dominated in wet intervals.
- 39. Territorial and administrative areas in the late Ming (Zheng et al. 2014)
- 40. The Collapse of Ming Dynasty (Zheng et al. 2014) 1580AD 1610AD 1630AD
- 41. Factors behind the Ming Collapse (Zheng et al. 2014)
- 42. Qing Dynasty Warring Period
- 43. Epidemics during Ming and Qing Dynasty (Zheng et al 2014)
- 44. Population during Ming and Qing Dynasty (Zheng et al 2014)
- 45. Influence of Asian Monsoon on Chinese Dynasty LTWMP: Late Tang Weak Monsoon Period NSSMP: N Song Strong Monsoon Period LYWMP: Late Yuan Weak Monsoon Period LMWMP: Late Ming Weak Monsoon Period DACP: Dark Age Cold Period MWP: Medieval Warm Period LIA: Little Ice Age CWP: Current Warm Period (Zhang et al 2008)
- 46. (Zhang et al 2008) Any relationship with Drought/Flood Index, Glacier record and Solar irradiance?
- 47. Solar irradiance more influential than NH Temperature (Zhang et al 2008)
- 48. Wars in Little Ice Age Number of wars in the NH (bright green), Asia (pink), Europe (turquoise) Number of wars worldwide as recorded by Wright (39) (turquoise), Luard (38) (orange), and Brecke (bright green) Twenty-year population growth rate in Europe (turquoise), Asia (pink), and the NH (blue) and the NH 50-year fatality index (bright green)
- 49. Mesopotamian climate and collapse of Akkadian Empire
- 50. Maya Collapse
- 51. Tiwanakku Collapse in Bolivia
- 52. So.. • Climatic shifts may be a trigger to the eco-political changes. • Socio-economic and political response rings in the scales of the changes. • The resilience of societies to changes depends on the strength of their institutional structures, geographical locations, and the technology, leadership and cultural setting. • Hardship brought on by challenging environments can be managed in some circumstances but where this threatens livelihoods and institutional structures then this can be a trigger leading to historical changes, even at dynastic levels.
- 53. The End
Editor's Notes
- Xia Dynasty: First dynasty in traditional chinese history Xia dynasty was established by the legendary Yu the Great after Shun, the last of the Five Emperors gave his throne to him. Yu the great: Moral character, introduction to flood control. Shang Dynasty: Ruled in the yellow river valley Earliest known body of Chinese writing, mostly divinations inscribed on oracle bones – turtle shells, ox scapulae, or other bones Zhou Dynasty: The longest lasting dynasty Shang Dynasty:
- the downturns of most Chinese agro- ecological dynasties in NC such as the West Han, East Han, 5D & 10K (the era of Five Dynasties and Ten Kingdoms), Yuan, and Qing Dynasties, were mostly caused by armed conflicts with the north- ern pastoral polities or large-scale famines and peasant uprisings within these dynasties, which often took place at notable dry epi- sodes that corresponded to low values of GY, HP, GL, and FG, but high values of RPI, EF, ED, FI, LI, PUF, and NW (Fig. 5). In contrast, the depressions of some agro-ecological dynasties such as the Sui, North Song, and Ming Dynasties closely correlated with less drier but cold periods; and whereas the downfalls of other dynasties such as the Tang Dynasty has been suggested to be mainly resulted from internal political struggles with climatic change as a minor contributing factor (Zhang et al., 2007, 2010, 2014). The former is probably due to the NC dry-winter monsoon being more influential in arid periods, whilst moist-summer monsoon dominated in wet intervals, leading to higher terrestrial bio-productivity and land- carrying capacity in this area, since they are more sensitive to the variations in water supply. The steppe ecosystems exploited by the grass-fed nomadic societies (e.g., Hsiung-nu, Hsien-pi, Türk, Khitan, Tangut, Mongol, Oirat, and Jurchen) from Mongolia and its sur- rounding regions indeed surfer most from food shortages in severe droughts, and thus tend to invade the southern agricultural areas and to migrate the peripheral sedentary territories and plunder for subsistence (e.g., Zhang et al., 2014; Büntgen et al., 2016). Such a drought-induced or nomad-triggered demise of the ancient agro- ecological civilizations has also occurred in Middle East (e.g., Mesopotamia and Turkey), North Africa (e.g., Egypt and Tunisia), and North America (e.g., Pueblo and Mississippi) (e.g., Issar, 1995; Weiss and Bradley, 2001; Enzel et al., 2003; Cook et al., 2007; Zhang et al., 2011a,b). In comparison, the effect of water supply may be relatively smaller in tropical or subtropical humid as well as cool humid areas, such as South China and West Europe where the
- PANN and TANN were prepared from eleven fossil pollen stratigraphies from lake sediment cores Northern region of monsoonal China: 80% of the annual rainfall falls during the summer-monsoonal season Sites selected here ideally cover the macro-scale climatic gradients over the entire monsoonal area of northern China.
- ASL – Above Sea Level Tree-ring cores from Tibetan Plateau (TP) Three ice cores from Northern, Central and Southern TP of lengths 170m, 189m, and 110m. Six stalagmites from caves 30 Sediment cores from varved lake 500 m long coral cores from more than 300 massive porite colonies
- Anomaly calculated with 1851-1950 temp average
- The reference period is from 1851 to 1950. The right-hand axis (marked “Sigma Unit”) is for the Yang et al. (2002) series. All color lines have been smoothed using a 100 yr FFT filter. The variations in temperature during the MCA, LIA, and PWP in China are consistent with those in the NH. However, the warming in China during 541–740 was more pronounced than in the NH.
- * 4 warm epochs and 4 cold epochs
- . Ensemble means of dry–wet index spatial patterns for the five cold epochs of AD 440 to AD 540, AD 780 to AD 920, AD 1390 to AD 1460, AD 1600 to AD 1700, and AD 1800 to AD 1900; as well as the four warm epochs of AD 650 to AD 750, AD 1000 to AD 1100, AD 1190 to AD 1290, and AD 1900 to AD 2000. Spatial pattern di↵erences are shown when climate changes from cold to warm (Hao et al., 2016)
- 5D & 10K represents the period of Five Dynasties and Ten Kingdoms in China PANN and TANN : Important bioclimatic variables for plant distribution Pollen- based numerical climatic inferences in northern China
- pollen-inferred TANN record with other related climatic records: 4 Marked warm period the detrended, 15-point smoothed pollen-based TANN anomaly (TA, ±0.3 C) for NC; the composited temperature anomaly (TA) for the entire China (Ge et al., 2013); the winter half-year temperature anomaly (TA) for central eastern (EC) China (Ge et al., 2003); the temperature anomaly (TA) of monsoonal warm-season from May to August from Shihua Cave in NC (Tan et al., 2003); (efg) the three integrated temperature anomaly series (TA-1e3) for northern Hemisphere (NH) (Ljungqvist, 2010; Christiansen and Ljungqvist, 2012; Kobashi et al., 2013); A B the Total Solar Irradiance record (TSI; Vieira et al., 2011); the Asian Pacific Oscillation index (APO; Zhou et al., 2009); the Intertropical Convergence Zone index (ITCZ; Haug et al., 2001); the North Atlantic Oscillation index (NAO; Trouet et al., 2009; Olsen et al., 2012); and the Ice-Rafted Debris record (IRD; Bond et al., 2001) from the North Atlantic Ocean. The pink bands represent warm periods, whereas the gray bands indicate cold periods. , a remarkable warm epoch in NC over the period of about 580e760 AD is not notably reflected in the NH tempera- ture series.
- Correlate well with the 100, 50, 23 and 22 year cycles for the solar activity observed in various solar parameters
- Comparison of pollen-based and KCM-simulated PANN records for monsoonal northern the detrended, 15-point smoothed pollen-based PANN anomaly (±21 mm) for NC; the 15-point smoothed KCM-simulated PANN anomaly (mm) for NC (100e130 E and 35e50 N); the synthesized precipitation index for north-central China (Tan et al., 2011); the d18O records from Wanxiang Cave (Zhang et al., 2008) the d18O records from Huangye (Tan et al., 2010) Cave on the western Loess Plateau; the regional dry-wet index based on historical documents in the northern China Plain (NC) (Zheng et al., 2006); the coupled ECHO-G simulated precipitation for northern China during summertime from May to August (MJJA) (Liu et al., 2011); the drought index based on historical records from Korea (Kim and Choi, 1987); and the d18O record from Fukugaguchi Cave in Japan (Sone et al., 2013). The pink bands depict wet periods, while the gray bands indicate dry periods. KCM Model: KCM model consists of the European Centre for Medium-Range Weather Forecasts (ECMWF) Hamburg atmospheric general circulation model version 5 (ECHAM5; Roeckner et al., 2003) and the Nucleus for European Modeling of the Ocean (NEMO; Madec, 2008) oceanesea ice general circulation model, with the Ocean Atmosphere Sea Ice Soil version 3 (OASIS3; Valcke, 2006). VPDB isotopes are reported in ‰ relative to the standard VPDB (Vienna Pee Dee Belemnite).
- Correlate well with the 100, 50, 23 and 22 year cycles for the solar activity observed in various solar parameters El Nin~o-Southern Oscillation (ENSO) strength (possibly El Nin o-like phases) during drying periods, increased volcanic eruptions and the resulting aerosol load during cooling periods, as well as high volumes of greenhouse gases such as CO2 and CH4 during the recent warming periods, may also play a role in partly affecting the climatic variability in NC
- 5D & 10K represents the period of Five Dynasties and Ten Kingdoms in China PANN and TANN : Important bioclimatic variables for plant distribution Pollen- based numerical climatic inferences in northern China
- 5D & 10K represents the period of Five Dynasties and Ten Kingdoms in China PANN and TANN : Important bioclimatic variables for plant distribution Pollen- based numerical climatic inferences in northern China
- Real grain prices and the alternation of periods of harmony and crisis in Europe, A.D. 1200–1800. (A) European temperature anomaly (σ, orange line), real grain price (Ag/L, bold black line), and the threshold of general crisis (real grain price = 0.2, pink dotted line). (B) Agricultural pro- duction index (orange line) and population size (in millions, green line). European temperature, real grain prices, and agricultural production index were smoothed by 40-y Butterworth low-pass filter. The light gray stripe represents a period of general crisis (real grain price >0.2); the dark gray stripe represents a period of demographic collapse.
- Results of the RDA analysis show that GY, HP, PFB, AT and SD are positively associated with PANN, ED and NW are negatively associated with PANN; GPI, EI, FG, EF, EPD and FI are positively correlated to TANN, whereas FD, SNM and LF are negatively correlated to TANN independently accounting for the total variation in 17 Chinese numerical historical indices, including eco- nomic level (EL), grain yield grade (GY), grain price index (GPI), fiscal grade (FG), agriculturalist policy territory (AT), extreme flood years (EF), extreme drought years (ED), freeze disaster frequency (FD), sand-dust event frequency (SD), famine index (FI), locust frequency (LF), epidemic disaster frequency (EPD), peasant uprising frequency (PUF), number of wars (NW), number of southward nomadic migrations (SNW), farming-pastoral boundary (FPB), and number of estimated human population (HP)
- Responses of different variables in human society to climate change in Europe, A.D. 1500–1800. (A) NH temperature anomaly (8C, red line) and Europe temperature anomaly (σ, black line). (B) Ratio of grain yield to seed (red line) and NH extratropical tree-ring widths (black line). (C) Detrended grain price (Ag/L, red line) and detrended agricultural production index (black line). (D) Detren- ded wage index (σ, red line) and number of famine years per decade (black line). (E) Number of wars (red line) and magnitude of social disturbances (black line). (F ) Detrended human height (in cm, red line) and number of plagues per decade (black line). (G) War fatality index (red line) and number of migrations per quarter century (black line). (H) Detrended population size (in millions, red line)
- Temperature change and the alternation of periods of harmony and crisis in the NH during the past millennium. (A) European temperature anomaly (σ). (B) NH temperature anomaly (8C). (C) NH annual population growth rate (%). (D) Famine years in the NH (number of famine years per decade). (E) Number of deadly epidemic events (malaria, plague, typhus, measles, smallpox, and dysentery) per decade in the NH. (F) Number of wars per year in the NH. All data were smoothed by a 100-y Butterworth low-pass filter. Gray stripes represent periods of crisis in Europe as delimitated by historians
- Paleo-temperature variation and its impact on Europe and China, A.D. 1500 –1800. (A) Temperature anomaly (°C) in the NH (17). (B–E) European data are in green and Chinese data are in red. The data are in normalized units that indicate the relative amplitude of change only. (B) Detrended estimated values of agricultural production (solid lines) and detrended grain yield ratio in Europe (green-dotted curve) (18). The estimated values of agricultural production are calculated by dividing population size by food price. (C) Detrended population size (solid lines) and population growth rate (dotted curves) (22, 24). (D) Detrended wheat price index in Europe and detrended rice price in China (41, 42). (E) Detrended total war frequency ( and ref. 40). All data are smoothed by 40-year Butterworth low pass filter. All of the dotted curves correspond to the right y axis.
- in different countries (in different stages of civilization, culture, economic development, and re- sources) nor can they simulate the alternation of historical golden and dark ages
- NC dry-winter monsoon being more influential in arid periods, whilst moist-summer monsoon dominated in wet intervals, leading to higher terrestrial bio-productivity and land- carrying capacity in this area, since they are more sensitive to the variations in water supply. The steppe ecosystems exploited by the grass-fed nomadic societies (e.g., Hsiung-nu, Hsien-pi, Türk, Khitan, Tangut, Mongol, Oirat, and Jurchen) from Mongolia and its sur- rounding regions indeed surfer most from food shortages in severe droughts, and thus tend to invade the southern agricultural areas and to migrate the peripheral sedentary territories and plunder for subsistence (e.g., Zhang et al., 2014; Büntgen et al., 2016). Such a drought-induced or nomad-triggered demise of the ancient agro- ecological civilizations has also occurred in Middle East (e.g., Mesopotamia and Turkey), North Africa (e.g., Egypt and Tunisia), and North America (e.g., Pueblo and Mississippi) (e.g., Issar, 1995; Weiss and Bradley, 2001; Enzel et al., 2003; Cook et al., 2007; Zhang et al., 2011a,b). In comparison, the effect of water supply may be relatively smaller in tropical or subtropical humid as well as cool humid areas, such as South China and West Europe where the land-carrying productivity is comparatively higher, so that the cooling effect of climate may be more detrimental in driving up- turns and downturns of the pre-industrial agro-ecological civili- zations in these regions (e.g., Zhang et al., 2007, 2011). This suggests that the response of human agro-ecological civilizations to the climatic change varies geographically, because of differences in their food diversity, ecological vulnerability, and adaptive capacity. Such close match-up, rhythmic process, and causal relationship are likely not accidental, but have been suggested as a generalized push-pull phenomenon or a resultant outbreak of Malthusian checks during the pre-industrial era (e.g., Zhang et al., 2007, 2011, 2014; Büntgen et al., 2016). In addition, our findings do not contradict earlier theories with regards to the individuality as well as complexity of the geo-political shifts in human history. In this regard, more detailed case-by-case studies are needed and would thereof further improve our understanding of the past or future climatic as well as environmental circumstances under which the momentous societal events have taken place at the macro- geographical scale on the long-term time series.
- Frequency of wars between the Ming and the Mongols or the Manchu on the northern frontier during 1500–1650.
- Based on the reconstructed temperatures, precipitation changes, and occurrences of extreme climate events, together with historical records on fiscal deterioration, food crises, and the frequencies of popular unrest, rebellions and wars, we identified three principal ways in which climate change contributed to the collapse in the Ming dynasty. Firstly, cooling, aridification, and desertification during a cold period destroyed the military farm system, which was the main supply system for the provisioning of government troops on the northern frontiers; these impacts increased the military expenditure from 64 % of total government expenditure in 1548–1569 to 76 % in 1570–1589 and thus aggravated the national fiscal crisis that occurred during the late Ming dynasty. Secondly, climate deterioration (e.g., cooling, aridification, and an increase in the frequencies of frost- and drought-related disasters, etc.) led to a 20–50 % reduction in the per capita production of raw grain in most areas of China, which resulted in widespread food crises and exacerbated the vulnerability of social structures during the last several decades of the Ming dynasty. Thirdly, the severe droughts occurring in 1627– 1643 were a key trigger to the peasantry uprising. These droughts also played a significant role to promote the peasantry uprising, especially reviving the peasantry troops by recruitment of famine victims when they nearly perished in 1633 and 1638,
- Wanxian Cave – Qinghai Tibetan Plateau and Chinese Loess Plateau 118m long stalagmite Delta-18 O
- Drought Flood Index, Alpine Glacial record (dark blue: Gorner glacier, Light blue: Lower Grindelwald glacier) Solar irradiance
- Paleo-temperature variation, war frequency, and population growth rate, A.D. 1400–1900. (A) Temperature anomaly (°C) in the NH that is smoothed by 40-year Butterworth low pass filter (17). (B) Number of wars in the NH (bright green), Asia (pink), Europe (turquoise), and the arid areas in the NH (orange). (C) Number of wars worldwide as recorded by Wright (39) (turquoise), Luard (38) (orange), and Brecke (bright green). (D) Twenty-year population growth rate in Europe (turquoise), Asia (pink), and the NH (blue) and the NH 50-year fatality index (bright green). Cold phases are shaded as gray stripes. All war time series are in 10-year units, and the data are listed in SI Table 1. The bright green curves correspond to the right y axis.