Data-model comparison of the Younger Dryas event: Discussion

2001 ◽  
Vol 38 (3) ◽  
pp. 477-478 ◽  
Author(s):  
H Renssen ◽  
R FB Isarin
Keyword(s):  
Data Model ◽  
Model Comparison ◽  
Younger Dryas ◽  
Younger Dryas Event

The chronology of the last Deglaciation: Implications to the cause of the Younger Dryas Event

1988 ◽  
Vol 3 (1) ◽  
pp. 1-19 ◽  
Author(s):  
W. S. Broecker ◽  
M. Andree ◽  
W. Wolfli ◽  
H. Oeschger ◽  
G. Bonani ◽  
...  
Keyword(s):  
Younger Dryas ◽  
Last Deglaciation ◽  
The Last Deglaciation ◽  
Younger Dryas Event

Data-model Comparison for the mid-Pliocene Warm Period

2021 ◽  
Author(s):  
Julia Tindall ◽  
Alan Haywood ◽  
Ulrich Salzmann ◽  
Aisling Dolan
Keyword(s):  
Data Model ◽  
Model Comparison ◽  
Surface Air Temperature ◽  
High Latitudes ◽  
Orbital Forcing ◽  
Local Site ◽  
Modern Analogue ◽  
Intercomparison Project ◽  
Global Mean ◽  
Good Agreement

<p>Modelling results from PlioMIP2 (the Pliocene Model Intercomparison Project Phase 2) focussing on MIS KM5c; ~3.205Ma, suggest that global mean surface air temperature was 1.7 – 5.2 °C higher than the preindustrial.  This warming was amplified at the poles and over land.  The results are in reasonable agreement with paleodata over the ocean.   </p><p>Over the land the situation is more complicated.  Model and data are in very good agreement at lower latitudes, however at high latitudes an initial data-model comparison shows much warmer mPWP temperatures from data than from models.   </p><p>Here we consider possible reasons for this data-model discord at high latitudes.  These include uncertainties in model boundary conditions (such as CO<sub>2 </sub>and orbital forcing), and whether there are local site-specific conditions which need to be accounted for.  We also show that the seasonal cycle in mPWP temperatures at these high latitude sites has no modern analogue.  This could lead to inaccuracies when comparing model derived mean annual temperatures with quantitative climatic estimates from palaeobotanical data using Nearest Living Relative methods.</p>

scholarly journals Mid-Holocene climate change in Europe: a data-model comparison

2007 ◽  
Vol 3 (3) ◽  
pp. 499-512 ◽  
Author(s):  
S. Brewer ◽  
J. Guiot ◽  
F. Torre
Keyword(s):  
Climate Change ◽  
Data Model ◽  
General Circulation ◽  
Model Comparison ◽  
General Circulation Models ◽  
Growing Degree Days ◽  
Degree Days ◽  
European Continent ◽  
Holocene Climate Change ◽  
Correct Location

Abstract. We present here a comparison between the outputs of 25 General Circulation Models run for the mid-Holocene period (6 ka BP) with a set of palaeoclimate reconstructions based on over 400 fossil pollen sequences distributed across the European continent. Three climate parameters were available (moisture availability, temperature of the coldest month and growing degree days), which were grouped together using cluster analysis to provide regions of homogenous climate change. Each model was then investigated to see if it reproduced 1) similar patterns of change and 2) the correct location of these regions. A fuzzy logic distance was used to compare the output of the model with the data, which allowed uncertainties from both the model and data to be taken into account. The models were compared by the magnitude and direction of climate change within the region as well as the spatial pattern of these changes. The majority of the models are grouped together, suggesting that they are becoming more consistent. A test against a set of zero anomalies (no climate change) shows that, although the models are unable to reproduce the exact patterns of change, they all produce the correct signs of change observed for the mid-Holocene.

scholarly journals The Warm Winter Paradox in the Pliocene High Latitudes

2022 ◽  
Author(s):  
Julia C. Tindall ◽  
Alan M. Haywood ◽  
Ulrich Salzmann ◽  
Aisling M. Dolan ◽  
Tamara Fletcher
Keyword(s):  
High Latitude ◽  
Data Model ◽  
Model Comparison ◽  
Co2 Concentration ◽  
High Latitudes ◽  
Warm Winter ◽  
Reconstruction Methods ◽  
Number Of Factors ◽  
Modern Analogue ◽  
Winter Temperatures

Abstract. Reconciling palaeodata with model simulations of the Pliocene climate is essential for understanding a world with atmospheric CO2 concentration near 400 parts per million by volume. Both models and data indicate an amplified warming of the high latitudes during the Pliocene, however terrestrial data suggests Pliocene high latitude temperatures were much higher than can be simulated by models. Here we show that understanding the Pliocene high latitude terrestrial temperatures is particularly difficult for the coldest months, where the temperatures obtained from models and different proxies can vary by more than 20 °C. We refer to this mismatch as the ‘warm winter paradox’. Analysis suggests the warm winter paradox could be due to a number of factors including: model structural uncertainty, proxy data not being strongly constrained by winter temperatures, uncertainties on data reconstruction methods and also that the Pliocene high latitude climate does not have a modern analogue. Refinements to model boundary conditions or proxy dating are unlikely to contribute significantly to the resolution of the warm winter paradox. For the Pliocene, high latitude, terrestrial, summer temperatures, models and different proxies are in good agreement. Those factors which cause uncertainty on winter temperatures are shown to be much less important for the summer. Until some of the uncertainties on winter, high latitude, Pliocene temperatures can be reduced, we suggest a data-model comparison should focus on the summer. This is expected to give more meaningful and accurate results than a data-model comparison which focuses on the annual mean.

scholarly journals Large-scale features of Pliocene climate: results from the Pliocene Model Intercomparison Project

2012 ◽  
Vol 8 (4) ◽  
pp. 2969-3013 ◽  
Author(s):  
A. M. Haywood ◽  
D. J. Hill ◽  
A. M. Dolan ◽  
B. Otto-Bliesner ◽  
F. Bragg ◽  
...  
Keyword(s):  
Data Model ◽  
Large Scale ◽  
Model Comparison ◽  
Numerical Models ◽  
Model Intercomparison ◽  
System Sensitivity ◽  
Sensitivity Tests ◽  
Intercomparison Project ◽  
Known Unknowns ◽  
Shed Light

Abstract. Climate and environments of the mid-Pliocene Warm Period (3.264 to 3.025 Ma) have been extensively studied. Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a co-ordinated multi-model and multi-model/data intercomparison. Whilst commonalities in model outputs for the Pliocene are evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data/model comparison highlights the potential for models to underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Sensitivity tests exploring the "known unknowns" in modelling Pliocene climate specifically relevant to the high-latitudes are also essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses). Estimates of longer-term sensitivity to CO2 (also known as Earth System Sensitivity; ESS), suggest that ESS is greater than Climate Sensitivity (CS), and that the ratio of ESS to CS is between 1 and 2, with a best estimate of 1.5.

scholarly journals 3D Simulator for Wind Interferometer Data-Model Comparison

2020 ◽  
Author(s):  
Md. Nurul Huda ◽  
Scott L. England ◽  
Gustavo Gargioni
Keyword(s):  
Data Model ◽  
Model Comparison

scholarly journals Quantifying the effect of seasonal and vertical habitat tracking on planktonic foraminifera proxies

2017 ◽  
Vol 13 (6) ◽  
pp. 573-586 ◽  
Author(s):  
Lukas Jonkers ◽  
Michal Kučera
Keyword(s):  
Environmental Change ◽  
Data Model ◽  
Model Comparison ◽  
Planktonic Foraminifera ◽  
Temporal Trends ◽  
Global Scale ◽  
Individual Species ◽  
Near Surface ◽  
Proxy Records ◽  
Habitat Tracking

Abstract. The composition of planktonic foraminiferal (PF) calcite is routinely used to reconstruct climate variability. However, PF ecology leaves a large imprint on the proxy signal: seasonal and vertical habitats of PF species vary spatially, causing variable offsets from annual mean surface conditions recorded by sedimentary assemblages. PF seasonality changes with temperature in a way that minimises the environmental change that individual species experience and it is not unlikely that changes in depth habitat also result from such habitat tracking. While this behaviour could lead to an underestimation of spatial or temporal trends as well as of variability in proxy records, most palaeoceanographic studies are (implicitly) based on the assumption of a constant habitat. Up to now, the effect of habitat tracking on foraminifera proxy records has not yet been formally quantified on a global scale. Here we attempt to characterise this effect on the amplitude of environmental change recorded in sedimentary PF using core top δ18O data from six species. We find that the offset from mean annual near-surface δ18O values varies with temperature, with PF δ18O indicating warmer than mean conditions in colder waters (on average by −0.1 ‰ (equivalent to 0.4 °C) per °C), thus providing a first-order quantification of the degree of underestimation due to habitat tracking. We use an empirical model to estimate the contribution of seasonality to the observed difference between PF and annual mean δ18O and use the residual Δδ18O to assess trends in calcification depth. Our analysis indicates that given an observation-based model parametrisation calcification depth increases with temperature in all species and sensitivity analysis suggests that a temperature-related seasonal habitat adjustment is essential to explain the observed isotope signal. Habitat tracking can thus lead to a significant reduction in the amplitude of recorded environmental change. However, we show that this behaviour is predictable. This allows accounting for habitat tracking, enabling more meaningful reconstructions and improved data–model comparison.

scholarly journals Large-scale features of Pliocene climate: results from the Pliocene Model Intercomparison Project

2013 ◽  
Vol 9 (1) ◽  
pp. 191-209 ◽  
Author(s):  
A. M. Haywood ◽  
D. J. Hill ◽  
A. M. Dolan ◽  
B. L. Otto-Bliesner ◽  
F. Bragg ◽  
...  
Keyword(s):  
Data Model ◽  
Large Scale ◽  
Model Comparison ◽  
Numerical Models ◽  
Model Intercomparison ◽  
System Sensitivity ◽  
Sensitivity Tests ◽  
Intercomparison Project ◽  
Known Unknowns ◽  
Shed Light

Abstract. Climate and environments of the mid-Pliocene warm period (3.264 to 3.025 Ma) have been extensively studied. Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a coordinated multi-model and multi-model/data intercomparison. Whilst commonalities in model outputs for the Pliocene are clearly evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data/model comparison highlights that models potentially underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Furthermore, sensitivity tests exploring the known unknowns in modelling Pliocene climate specifically relevant to the high latitudes are essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses). Estimates of longer-term sensitivity to CO2 (also known as Earth System Sensitivity; ESS), support previous work suggesting that ESS is greater than Climate Sensitivity (CS), and suggest that the ratio of ESS to CS is between 1 and 2, with a "best" estimate of 1.5.

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