Marine Climate Archives Across the Medieval Climate Anomaly-Little Ice Age Transition from Viking and Medieval Age Shells, Orkney, Scotland

2014 ◽  
Vol 13 ◽  
pp. 40-40
Author(s):  
Donna Surge ◽  
James H. Barrett
Keyword(s):  
Little Ice Age ◽  
Ice Age ◽  
Medieval Climate Anomaly ◽  
Climate Anomaly ◽  
Marine Climate

Characterization of the Medieval Climate Anomaly, Little Ice Age and recent warming in northern Lapland

2017 ◽  
Vol 37 ◽  
pp. 1257-1266 ◽  
Author(s):  
Tomi P. Luoto ◽  
E. Henriikka Kivilä ◽  
Marttiina V. Rantala ◽  
Liisa Nevalainen
Keyword(s):  
Little Ice Age ◽  
Ice Age ◽  
Medieval Climate Anomaly ◽  
Climate Anomaly ◽  
Recent Warming

Lacustrine stable isotope record of precipitation changes in Nicaragua during the Little Ice Age and Medieval Climate Anomaly

Geology ◽  
2013 ◽  
Vol 41 (2) ◽  
pp. 151-154 ◽  
Author(s):  
Nathan D. Stansell ◽  
Byron A. Steinman ◽  
Mark B. Abbott ◽  
Michael Rubinov ◽  
Manuel Roman-Lacayo
Keyword(s):  
Stable Isotope ◽  
Little Ice Age ◽  
Ice Age ◽  
Medieval Climate Anomaly ◽  
Climate Anomaly ◽  
Isotope Record ◽  
Precipitation Changes ◽  
Stable Isotope Record

The medieval climate anomaly and the little Ice Age in coastal Syria inferred from pollen-derived palaeoclimatic patterns

2011 ◽  
Vol 78 (3-4) ◽  
pp. 178-187 ◽  
Author(s):  
D. Kaniewski ◽  
E. Van Campo ◽  
E. Paulissen ◽  
H. Weiss ◽  
J. Bakker ◽  
...  
Keyword(s):  
Little Ice Age ◽  
Ice Age ◽  
Medieval Climate Anomaly ◽  
Climate Anomaly

scholarly journals Was the Little Ice Age more or less El Niño-like than the Medieval Climate Anomaly? Evidence from hydrological and temperature proxy data

2017 ◽  
Vol 13 (3) ◽  
pp. 267-301 ◽  
Author(s):  
Lilo M. K. Henke ◽  
F. Hugo Lambert ◽  
Dan J. Charman
Keyword(s):  
Little Ice Age ◽  
Large Scale ◽  
Global Climate ◽  
Ice Age ◽  
Medieval Climate Anomaly ◽  
Climate Anomaly ◽  
Proxy Data ◽  
The Past ◽  
Proxy Records

Abstract. The El Niño–Southern Oscillation (ENSO) is the most important source of global climate variability on interannual timescales and has substantial environmental and socio-economic consequences. However, it is unclear how it interacts with large-scale climate states over longer (decadal to centennial) timescales. The instrumental ENSO record is too short for analysing long-term trends and variability and climate models are unable to accurately simulate past ENSO states. Proxy data are used to extend the record, but different proxy sources have produced dissimilar reconstructions of long-term ENSO-like climate change, with some evidence for a temperature–precipitation divergence in ENSO-like climate over the past millennium, in particular during the Medieval Climate Anomaly (MCA; AD  ∼  800–1300) and the Little Ice Age (LIA; AD  ∼  1400–1850). This throws into question the stability of the modern ENSO system and its links to the global climate, which has implications for future projections. Here we use a new statistical approach using weighting based on empirical orthogonal function (EOF) to create two new large-scale reconstructions of ENSO-like climate change derived independently from precipitation proxies and temperature proxies. The method is developed and validated using model-derived pseudo-proxy experiments that address the effects of proxy dating error, resolution, and noise to improve uncertainty estimations. We find no evidence that temperature and precipitation disagree over the ENSO-like state over the past millennium, but neither do they agree strongly. There is no statistically significant difference between the MCA and the LIA in either reconstruction. However, the temperature reconstruction suffers from a lack of high-quality proxy records located in ENSO-sensitive regions, which limits its ability to capture the large-scale ENSO signal. Further expansion of the palaeo-database and improvements to instrumental, satellite, and model representations of ENSO are needed to fully resolve the discrepancies found among proxy records and establish the long-term stability of this important mode of climatic variability.

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