scholarly journals Global warming-induced Asian hydrological climate transition across the Miocene–Pliocene boundary

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hong Ao ◽  
Eelco J. Rohling ◽  
Ran Zhang ◽  
Andrew P. Roberts ◽  
Ann E. Holbourn ◽  
...  
Keyword(s):  
Summer Monsoon ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Chinese Loess Plateau ◽  
Red Clay ◽  
Chinese Loess ◽  
Climate Model Simulations ◽  
Climate Transition ◽  
Climate Responses

AbstractAcross the Miocene–Pliocene boundary (MPB; 5.3 million years ago, Ma), late Miocene cooling gave way to the early-to-middle Pliocene Warm Period. This transition, across which atmospheric CO2 concentrations increased to levels similar to present, holds potential for deciphering regional climate responses in Asia—currently home to more than half of the world’s population— to global climate change. Here we find that CO2-induced MPB warming both increased summer monsoon moisture transport over East Asia, and enhanced aridification over large parts of Central Asia by increasing evaporation, based on integration of our ~1–2-thousand-year (kyr) resolution summer monsoon records from the Chinese Loess Plateau aeolian red clay with existing terrestrial records, land-sea correlations, and climate model simulations. Our results offer palaeoclimate-based support for ‘wet-gets-wetter and dry-gets-drier’ projections of future regional hydroclimate responses to sustained anthropogenic forcing. Moreover, our high-resolution monsoon records reveal a dynamic response to eccentricity modulation of solar insolation, with predominant 405-kyr and ~100-kyr periodicities between 8.1 and 3.4 Ma.

Mineral magnetic record of the Miocene-Pliocene climate transition on the Chinese Loess Plateau, North China

2017 ◽  
Vol 89 (3) ◽  
pp. 619-628 ◽  
Author(s):  
Hong Ao ◽  
Mark J. Dekkers ◽  
Andrew P. Roberts ◽  
Eelco J. Rohling ◽  
Zhisheng An ◽  
...  
Keyword(s):  
Climate Variability ◽  
East Asia ◽  
Loess Plateau ◽  
Single Domain ◽  
Chinese Loess Plateau ◽  
Red Clay ◽  
Chinese Loess ◽  
Mineral Magnetic ◽  
Climate Transition ◽  
The Chinese Loess Plateau

AbstractPre-Quaternary terrestrial climate variability is less well understood than that during the Quaternary. The continuous eolian Red Clay sequence underlying the well-known Quaternary loess-paleosol sequence on the Chinese Loess Plateau (CLP) provides an opportunity to study pre-Quaternary terrestrial climate variability in East Asia. Here, we present new mineral magnetic records for a recently found Red Clay succession from Shilou area on the eastern CLP, and demonstrate a marked East Asian climate shift across the Miocene-Pliocene boundary (MPB). Pedogenic fine-grained magnetite populations, ranging from superparamagnetic (SP)/single domain (SD) up to small pseudo-single domain (PSD) sizes (i.e., from <30 nm up to ~1000 nm), dominate the magnetic properties. Importantly, our mineral magnetic results indicate that both pedogenic formation of SP grains and transformation of SP grains to SD and small PSD grains accelerated across the MPB in the Shilou Red Clay, which are indicative of enhanced pedogenesis. We relate this enhanced pedogenesis to increased soil moisture availability on the CLP, associated with stronger Asian Summer Monsoon precipitation during an overall period of global cooling. Our study thus provides new insights into the Miocene-Pliocene climate transition in East Asia.

scholarly journals Global climate disruption and regional climate shelters after the Toba supereruption

2021 ◽  
Vol 118 (29) ◽  
pp. e2013046118
Author(s):  
Benjamin A. Black ◽  
Jean-François Lamarque ◽  
Daniel R. Marsh ◽  
Anja Schmidt ◽  
Charles G. Bardeen
Keyword(s):  
High Resolution ◽  
Human Evolution ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Test Case ◽  
Sulfur Emission ◽  
Community Earth System Model ◽  
Climate Model Simulations ◽  
Paleoclimate Records

The Toba eruption ∼74,000 y ago was the largest volcanic eruption since the start of the Pleistocene and represents an important test case for understanding the effects of large explosive eruptions on climate and ecosystems. However, the magnitude and repercussions of climatic changes driven by the eruption are strongly debated. High-resolution paleoclimate and archaeological records from Africa find little evidence for the disruption of climate or human activity in the wake of the eruption in contrast with a controversial link with a bottleneck in human evolution and climate model simulations predicting strong volcanic cooling for up to a decade after a Toba-scale eruption. Here, we use a large ensemble of high-resolution Community Earth System Model (CESM1.3) simulations to reconcile climate model predictions with paleoclimate records, accounting for uncertainties in the magnitude of Toba sulfur emissions with high and low emission scenarios. We find a near-zero probability of annual mean surface temperature anomalies exceeding 4 °C in most of Africa in contrast with near 100% probabilities of cooling this severe in Asia and North America for the high sulfur emission case. The likelihood of strong decreases in precipitation is low in most of Africa. Therefore, even Toba sulfur release at the upper range of plausible estimates remains consistent with the muted response in Africa indicated by paleoclimate proxies. Our results provide a probabilistic view of the uneven patterns of volcanic climate disruption during a crucial interval in human evolution, with implications for understanding the range of environmental impacts from past and future supereruptions.

scholarly journals Filling the matrix: an ANOVA-based method to emulate regional climate model simulations for equally-weighted properties of ensembles of opportunity

2021 ◽  
Author(s):  
Ole B. Christensen ◽  
Erik Kjellström
Keyword(s):  
Regional Climate Model ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Surface Wind ◽  
Climate Data ◽  
Large Ensembles ◽  
Climate Model Simulations

AbstractCollections of large ensembles of regional climate model (RCM) downscaled climate data for particular regions and scenarios can be organized in a usually incomplete matrix consisting of GCM (global climate model) x RCM combinations. When simple ensemble averages are calculated, each GCM will effectively be weighted by the number of times it has been downscaled. In order to facilitate more equal and less arbitrary weighting among downscaled GCM results, we present a method to emulate the missing combinations in such a matrix, enabling equal weighting among participating GCMs and hence among regional consequences of large-scale climate change simulated by each GCM. This method is based on a traditional Analysis of Variance (ANOVA) approach. The method is applied and studied for fields of seasonal average temperature, precipitation and surface wind and for the 10-year return value of daily precipitation and of 10-m wind speed for a completely filled matrix consisting of 5 GCMs and 4 RCMs. We quantify the skill of the two averaging methods for different numbers of missing simulations and show that ensembles where lacking members have been emulated by the ANOVA technique are better at representing the full ensemble than corresponding simple ensemble averages, particularly in cases where only a few model combinations are absent. The technique breaks down when the number of missing simulations reaches the sum of the numbers of GCMs and RCMs. Also, the method is only useful when inter-simulation variability is limited. This is the case for the average fields that have been studied, but not for the extremes. We have developed analytical expressions for the degree of improvement obtained with the present method, which quantify this conclusion.

scholarly journals Filling the Matrix: An ANOVA-Based Method to Emulate Regional Climate Model Simulations for Equally-Weighted Properties of Ensembles of Opportunity

2021 ◽  
Author(s):  
Ole Bøssing Christensen ◽  
Erik Kjellström
Keyword(s):  
Regional Climate Model ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Surface Wind ◽  
Climate Data ◽  
Large Ensembles ◽  
Climate Model Simulations

Abstract Collections of large ensembles of regional climate model (RCM) downscaled climate data for particular regions and scenarios can be organized in a usually incomplete matrix consisting of GCM (global climate model) x RCM combinations. When simple ensemble averages are calculated, each GCM will effectively be weighted by the number of times it has been downscaled. In order to facilitate more equal and less random weighting among downscaled GCM results, we present a method to emulate the missing combinations in such a matrix, enabling equal weighting among participating GCMs and hence among regional consequences of large-scale climate change simulated by each GCM. This method is based on a traditional Analysis of Variance (ANOVA) approach. The method is applied and studied for fields of seasonal average temperature, precipitation and surface wind and for the 10-year return value of daily precipitation and of 10-m wind speed for a completely filled matrix consisting of 5 GCMs and 4 RCMs. We quantify the skill of the two averaging methods for different numbers of missing simulations and show that ensembles where lacking members have been emulated by the ANOVA technique are better at representing the full ensemble than corresponding simple ensemble averages, particularly in cases where only a few model combinations are absent. The technique breaks down when the number of missing simulations reaches the sum of the numbers of GCMs and RCMs.

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