
Three modes of climate change since the Last Glacial Maximum in arid and semi-arid regions of the Asian continent
地理学报(英文版) ›› 2022, Vol. 32 ›› Issue (2) : 195-213.
Three modes of climate change since the Last Glacial Maximum in arid and semi-arid regions of the Asian continent
The westerly winds and East Asian summer monsoon play a leading role in climate change of southwestern North America and eastern Asia since the Last Glacial Maximum (LGM), respectively. Their convergence in arid and semi-arid regions of the Asian continent (AAC) makes the regional climate change more complicated on the millennial-scale. There are still limitations in applying paleoclimate records and climate simulations of characteristic periods to investigate climate change patterns since the LGM in this region. In this study, we adopt two indexes indicating effective moisture and rely on a continuous simulation, a time slice simulation, and numerous paleoclimate records to comprehensively investigate the climate change modes and their driving mechanisms since the LGM in AAC. Results demonstrate a millennial-scale climate differentiation phenomenon and three climate change modes possibly occurring in AAC since the LGM. The western AAC largely controlled by the westerly winds is featured as wet climates during the LGM but relatively dry climates during the mid-Holocene (MH), coinciding with the climate change mode in southwestern North America. Conversely, dry conditions during the LGM and relatively wet conditions during the MH are reflected in eastern AAC governed by the East Asian summer monsoon, which leans to the climate change mode in eastern Asia. If climate change in central AAC is forced by the interaction of two circulations, it expresses wet conditions in both the LGM and MH, tending to a combination of the southwestern North American and eastern Asian modes. Precipitation and evaporation exert different intensities in influencing three climate modes of different periods. Furthermore, we identify the significant driving effects of greenhouse gases and ice sheets on westerly-dominated zones of AAC, while orbit-driven insolation on monsoon-dominated zones of AAC.
arid and semi-arid regions / Asian continent / climate change mode / Last Glacial Maximum / paleoclimate simulation {{custom_keyword}} /
Table 1 Boundary conditions for PMIP 3 models at the LGM and MH |
Boundary conditions | Last Glacial Maximum | Mid-Holocene |
---|---|---|
Eccentricity | 0.018994 | 0.018682 |
Obliquity (°) | 22.949° | 24.105° |
Longitude of perihelion (°) | 114.42° | 0.87° |
CO2 (ppm) | 185 | 280 |
CH4 (ppb) | 350 | 650 |
N2O (ppb) | 200 | 270 |
Ice sheet | Peltier (2004) 21 ka | Peltier (2004) 0 ka |
Vegetation | Present-day | Present-day |
Table 2 Details of used PMIP 3 models |
Model name | Grid number (lon×lat) | Levels | Resolution (lon °) | Resolution (lat °) |
---|---|---|---|---|
CNRM-CM5 | 256×128 | 17 | 1.40625 | 1.40625 |
CCSM4 | 288×192 | 17 | 1.25 | 0.9375 |
MIROC-ESM | 128×64 | 35 | 2.8125 | 2.8125 |
GISS-E2-R | 144×90 | 17 | 2.5 | 2 |
MPI-ESM-P | 192×96 | 25 | 1.875 | 1.875 |
MRI-CGCM3 | 320×160 | 23 | 1.125 | 1.125 |
Table 3 Wet/dry climate status of LGM relative to MH |
Records name | Latitude | Longitude | Record status | Proxies used | References |
---|---|---|---|---|---|
Hajar mountains | 22.83 | 59 | Dry | Sedimentation rates | Fuchs et al., 2008 |
Huguang Maar Lake | 21.15 | 110.28 | Dry | Water content | Mingram et al., 2004 |
Gutian peat | 26.09 | 110.37 | Dry | δ13Corg | Man et al., 2016 |
Lake Caohai | 27 | 104.67 | Dry | δ13C | Lin and Wei, 2000 |
Qilu Hu | 24.18 | 102.75 | Dry | CaCO3 | Hodell et al., 1999 |
Lake Tianchi | 25.87 | 99.27 | Dry | C/N | Jiang et al., 2019 |
Lake Ximencuo | 33.38 | 101.1 | Dry | Pollen | Herzschuh et al., 2014 |
Lake Kuhai | 35.3 | 99.2 | Dry | Pollen | Wischnewski et al., 2011 |
Qinghai Lake | 36.53 | 99.6 | Dry | Carbonate | Madsen et al., 2008 |
Sanjiaocheng | 38.2 | 103.34 | Dry | TOC | Zhang et al., 2004 |
Xiaogou | 36 | 105 | Dry | TOC | Wu et al., 2009 |
Xunyi Loess | 35.72 | 109.42 | Dry | δ13C | Lu et al., 2013 |
Luochuan loess deposits | 35.03 | 108.22 | Dry | δ13C | Lu et al., 2013 |
Hala Lake | 38.2 | 97.4 | Dry | OM | Yan and Wünnemann, 2014 |
Hovsgol Lake | 50.54 | 101.16 | Dry | Lake level | Murakami et al., 2010 |
Achit Nuur | 49.42 | 90.52 | Wet | MAP | Sun et al., 2013 |
Karakul Lake | 39.02 | 73.53 | Dry | Sediments | Heinecke et al., 2017 |
Zabuye Lake | 31.35 | 84.07 | Wet | δ18OCarb | Wang et al., 2002 |
Van Lake | 38.5 | 43 | Dry | TIC | Öğretmen, 2012 |
Yitang Lake | 40.3 | 94.97 | Dry | δ13C | Zhao et al., 2015 |
Luanhaizi | 37.59 | 101.35 | Dry | Pollen | Herzschuh et al., 2005 |
Lop Nur | 40.78 | 91.05 | Wet | Grain size | Luo et al., 2009 |
Aydin | 42.53 | 89.17 | Wet | Sediments | Li et al., 1989 |
Lake Manas | 45.75 | 86 | Dry | Pollen | Rhodes et al., 1996 |
Balikun Lake | 43.7 | 92.8 | Dry | / | GLSDB |
Bangge Lake | 31.75 | 89.57 | Wet | / | GLSDB |
Beysehir | 37.75 | 31.5 | Wet | / | GLSDB |
Dachaidan-Xiaochaidan salt lakes | 37.5 | 95.37 | Wet | / | GLSDB |
Erhai | 25.84 | 99.98 | Wet | / | GLSDB |
Ioannina | 39.66 | 20.88 | Wet | / | GLSDB |
Konya | 37.5 | 33 | Wet | / | GLSDB |
Manxing Lake | 22 | 100.6 | Dry | / | GLSDB |
Zeribar | 35.53 | 46.12 | Wet | / | GLSDB |
Zhacang Caka | 32.6 | 82.38 | Wet | / | GLSDB |
Figure 2 Variation of interannual precipitation in AAC during 1901-2018: (a) trend analysis of annual precipitation from 1901 to 2018; (b) trend analysis of summer precipitation from 1901 to 2018; (c) EOF1 spatial distribution of summer precipitation from 1901 to 2018; (d) time series of the principal components related to EOF1. Red (blue) colors in trend analysis represent the upward (downward) trend and the shadow areas are where the trends are statistically significant at 5% level. |
Figure 3 Spatio-temporal difference of effective moisture simulation in AAC since the LGM: (a) trend analysis of effective moisture change since the LGM; (b) EOF1 spatial distribution based on effective moisture since the LGM; (c) time series of the principal components related to EOF1; (d-f) time series of effective moisture (purple), precipitation (blue) and evaporation (orange) extracted from the westerly-dominated zones (black slant lines), monsoon-dominated zones (blue slant lines) and their intersection zones (red crosshatches), respectively. The gray line represents the calculated original values and the colored lines represent the 210-year average running series; red (blue) colors in trend analysis represent the upward (downward) trend and the dot areas are where the trends are statistically significant at 5% level. |
Figure 5 Trend analysis of effective moisture change under only orbitally-driven insolation forcing, only greenhouse gas forcing, only ice sheets forcing and only Northern Hemisphere meltwater fluxes forcing since the LGM. Red (blue) colors represent the upward (downward) trend and the dot areas are where the trends are statistically significant at 5% level. |
Figure 6 Spatial correlation analysis of effective moisture between full forcings and only orbitally-driven insolation forcing (a), only greenhouse gas forcing (b), only ice sheets forcing (c) and only Northern Hemisphere meltwater fluxes forcing (d). Red (blue) colors represent the positive correlation (negative correlation) and the crosshatches represent the regions with significant correlation, and dot areas are where the correlations are statistically significant at 5% level. |
Figure 7 Global paleoclimate records: (a) The summer insolation at 30°N since the LGM (Berger and Loutre, 1991); (b) The N2O records in GISP2 and Taylor Dome ice core (Sowers et al., 2003); (c) the CO2 records in Antarctic ice cores (Bereiter et al., 2015); (d) lake level records from Lake Lahontan (Briggs et al., 2005; Broecker et al., 2009); (e) lake level records from Lake Surprise (Ibarra et al., 2014); (f) lake level records from Lake Owens (Bacon et al., 2006); (g) reconstruction of annual precipitation based on pollen data in Dalianhai and Qinghai lakes (Li et al., 2017); (h) reconstruction of mean effective moisture from monsoonal Central Asia (Herzschuh, 2006); (i) the carbonate δ18O records from the QL section (Li et al., 2020). |
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CRU TS (Climatic Research Unit gridded Time Series) is a widely used climate dataset on a 0.5° latitude by 0.5° longitude grid over all land domains of the world except Antarctica. It is derived by the interpolation of monthly climate anomalies from extensive networks of weather station observations. Here we describe the construction of a major new version, CRU TS v4. It is updated to span 1901-2018 by the inclusion of additional station observations, and it will be updated annually. The interpolation process has been changed to use angular-distance weighting (ADW), and the production of secondary variables has been revised to better suit this approach. This implementation of ADW provides improved traceability between each gridded value and the input observations, and allows more informative diagnostics that dataset users can utilise to assess how dataset quality might vary geographically.
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Values for the precession and obliquity of the earth 9000 years ago indicate that the global average solar radiation for July 9000 years ago was 7 percent greater than at present. When the estimated solar radiation values are used in a low-resulation climate model, the model simulates an intensified continent-scale monsoon circulation. This result agrees with paleoclimatic evidence from Africa, Arabia, and India that monsoon rains were stronger between 10,000 and 5000 years ago than they are today.
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Paleoatmospheric records of trace-gas concentrations recovered from ice cores provide important sources of information on many biogeochemical cycles involving carbon, nitrogen, and oxygen. Here, we present a 106,000-year record of atmospheric nitrous oxide (N2O) along with corresponding isotopic records spanning the last 30,000 years, which together suggest minimal changes in the ratio of marine to terrestrial N2O production. During the last glacial termination, both marine and oceanic N2O emissions increased by 40 +/- 8%. We speculate that our records do not support those hypotheses that invoke enhanced export production to explain low carbon dioxide values during glacial periods.
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