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Modelling paleoclimate states and the transitions between them represents a challenge for models of all complexities. At the same time, the past offers a unique possibility to thoroughly test and evaluate models that are used to simulate the present and make future climate projections.
We invite papers on paleoclimate model simulations, including time-slice (as in the Paleoclimate Modelling Intercomparison Project - PMIP) and transient simulations of climate variations on timescales ranging from millennial to glacial cycles and beyond. Presentations about results from the latest phase of PMIP4-CMIP6 are particularly encouraged. However, comparisons of different models (comprehensive GCMs, EMICs and/or conceptual models), between different periods, and between models and data, including an analysis of the underlying mechanisms, are all within the scope of the session.

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Convener: Masa Kageyama | Co-conveners: André Paul, Julia Hargreaves, Michal Kucera
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| Attendance Wed, 06 May, 16:15–18:00 (CEST)

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Chat time: Wednesday, 6 May 2020, 16:15–18:00

D3482 |
EGU2020-8911<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Chris Brierley, Anni Zhao, Sandy Harrison, and Pascale Braconnot and the PMIP4 Community

The mid-Holocene (6,000 years ago) is a standard experiment for the evaluation of the simulated response of global climate models using paleoclimate reconstructions. The latest mid-Holocene simulations are a contribution by the Palaeoclimate Model Intercomparison Project (PMIP4) to the current phase of the Coupled Model Intercomparison Project (CMIP6). Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the northern hemisphere and associated shifts in tropical rainfall.  Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of -0.3 K, which is -0.2 K cooler that the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Neither this difference nor the improvement in model complexity and resolution seems to improve the realism of the simulations. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on climate sensitivity and feedback strength.

How to cite: Brierley, C., Zhao, A., Harrison, S., and Braconnot, P. and the PMIP4 Community: Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8911, https://doi.org/10.5194/egusphere-egu2020-8911, 2020

D3483 |
EGU2020-21624<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Emmanuele Russo, Bijan Fallah, and Christoph Raible
In this study the COSMO-CLM sensitivity to parameters perturbation is investigated under different climate forcings. The main aim is to understand
how the uncertainty of the model propagates in different climate regimes and whether the model presents structural stability when different forcings are considered. For this purpose, two Physically Perturbed Ensembles (PPEs) are produced, each composed of 35 realizations, at two different periods of the past: the Mid-Holocene, 6000 years ago, and the Pre-industrial period. The two periods present significant differences in the seasonal values of incoming insolation due to changes in the Earth’s orbital configuration. The effects of these changes on the Earth’s radiative balance, at least when considering seasonal values, are of the same magnitude of the changes due to GHGs emissions of the worst case Representative Concentration Pathway scenario (RCP8.5). Two additional ensembles, but with a lower number of components, are produced in order to determine the role of the boundaries with respect to the one of changes in the climate forcings.
Preliminary analyses show that the model presents a structurally stable behavior in the two periods for several variables, in particular when considering climate mean statistics. Some parameters do not produce sensible changes in the model behavior in both periods. This confirms that conducting a calibration of the model only on a restricted set of parameters is a good praxis when willing to simulate future or past climate change. On the other hand, some parameters show remarkable changes with respect to a reference simulation: these differences are maintained in the two different regimes, pointing again to a relatively good model stability, but also to a very similar sensitivity of the model to the different forcings. Finally, when considering the ensembles with the same forcings but different boundaries, the effect of the boundaries seems to play a major role. This is particularly important for climate projections using the COSMO-CLM: a model PPE would probably not be particularly relevant in order to characterize the model uncertainty, but more attention should instead be paid to consider a wide ensemble of independent boundary realizations with different GCMs

How to cite: Russo, E., Fallah, B., and Raible, C.: A Climate Model Structural Behavior Under Different Forcing, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21624, https://doi.org/10.5194/egusphere-egu2020-21624, 2020

D3484 |
EGU2020-9387<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Pierre Sepulchre and Julia Bres

Driven by plate tectonics and geodynamics, Earth surface has been reshaped during the Cenozoic, with the uplift of numerous mountain ranges. Climate modellers have been tackling the direct impact of these changes on climate for decades, essentially thanks to sensitivity experiments to topography, aiming at quantifying the impact of mountains on atmospheric and ocean dynamics. An indirect consequence of mountain uplift is changes in the continental river routing system, that can be relocated and provide the ocean with freshwater fluxes very different from the present. Here we focus on the Amazon and the Congo river, which routing are known to have been altered by the uplifts of the Andes and the East African Rift System, respectively. We carried out numerical simulations with the IPSL-CM5A2 earth system model in which we alternatively relocated or cut the runoff of these two rivers, and compared the results to simulations where topography only has been changed. We analyze the consequences of the changes in routing in terms of ITCZ position, precipitation spatial patterns, and salinity budgets and associated AMOC strength over the oceans. We show that depending on the region considered, the direct (mechanical) and indirect (hydrology) consequences of uplift on climate can either add up or counteract each other.

 

How to cite: Sepulchre, P. and Bres, J.: Did the evolution of tropical river systems impact the Cenozoic climate system ? A preliminary study with the IPSL-CM5A2 earth system model., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9387, https://doi.org/10.5194/egusphere-egu2020-9387, 2020

D3485 |
EGU2020-11028<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Bette L. Otto-Bliesner, Esther C. Brady, Anni Zhao, and Chris Brierley and the PMIP4 and QUIGS team

The modeling of paleoclimate, using physically based tools, is increasingly seen as a strong out-of-sample test of the models that are used for the projection of future climate changes. New to CMIP6 is the Tier 1 lig127k experiment, designed to address the climate responses to stronger orbital forcing than the midHolocene experiment, using the same state-of-the-art models and following a common experimental protocol. We present a multi-model ensemble of 17 climate models, all of which (except for two) have also completed the CMIP6 DECK experiments. The Equilibrium Climate Sensitivity (ECS) of these models varies from 2.1 to 5.3°C. The seasonal character of the insolation anomalies results in strong warming over the Northern Hemisphere (NH) continents in the lig127k ensemble as compared to the piControl in June-July-August and a much-reduced minimum (August-September) summer sea ice extent in the Arctic. The multi-model results indicate enhanced summer monsoonal precipitation and areal extent in the Northern Hemisphere and reductions in the Southern Hemisphere. These responses are greater in the lig127k than midHolocene simulations as expected from the larger insolation anomalies at 127 ka than 6 ka.

New syntheses for surface temperature and precipitation, targeted for 127ka, have been developed for comparison to the multi-model ensemble. The lig127k model ensemble and data reconstructions are in good agreement for summer temperature anomalies over Canada, Scandinavia, and the North Atlantic and precipitation over the Northern Hemisphere continents. The model-data comparisons and mismatches point to further study of the sensitivity of the simulations to uncertainties in the specified boundary conditions and of the uncertainties and sparse coverage in current proxy reconstructions.

The CMIP6-PMIP4 lig127k simulations, in combination with the proxy record, have potential implications for confidence in future projections of monsoons, surface temperature, Arctic sea ice, and the stability of the Greenland ice sheet.

How to cite: Otto-Bliesner, B. L., Brady, E. C., Zhao, A., and Brierley, C. and the PMIP4 and QUIGS team: Large-scale features of Last Interglacial climate: Results from evaluating the lig127k simulations for CMIP6-PMIP4, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11028, https://doi.org/10.5194/egusphere-egu2020-11028, 2020

D3486 |
EGU2020-8628<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Louise Sime, Masa Kageyama, Marie Sicard, Maria-Vittoria Guarino, Anne de Vernal, David Schroeder, Ruediger Stein, and Irene Malmierca-Vallet and the Ayako Abe-Ouchi6, Cecilia Bitz7, Pascale Braconnot1, Esther Brady8, Matthew A. Chamberlain9, Danny Feltham4, Chuncheng Guo10, Gerrit Lohmann5, Katrin Meissner11, Laurie Menviel11, Polina Morozova12, Kerim H. Nisancioglu13,14, Bette Otto-Bliesner8, Ryouta

The Last interglacial (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models’ representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 12 climate models in terms of Arctic sea ice. The mean pre-industrial to LIG reduction in minimum sea ice area (SIA) reaches 59% (multi-model mean LIG area is 2.21 mill. km2, compared to 5.85 mill. km2 for the PI), and the range of model results for LIG minimum sea ice area (from 0.02 to 5.65 mill. km2) is larger than for PI (from 4.10 to 8.30 mill. km2). On the other hand there is little change for the maximum sea ice area (which is 12 mill. km2 for both the PI and the LIG, with a standard deviation of 1.04 mill. km2 for PI and 1.21 mill. km2 for LIG). To evaluate the model results we synthesize LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. South of 78oN, in the Atlantic and Nordic seas, the LIG was seasonally ice-free. North of 78oN there are some discrepancies between sea ice reconstructions based on dinocysts/foraminifers/ostracods and IP25: some sites have both seasonal and perennial interpretations based on the same core, but different indicators. Because of the conflicting interpretations it is not possible for any one model to match every data point in our data synthesis, or say whether the Arctic was seasonally ice-free. Drivers for the inter-model differences are: different phasing of the up and down short-wave anomalies over the Arctic ocean, associated with differences in model albedo; possible cloud property differences, in terms of optical depth; LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally we note that inter-comparisons between the LIG simulations, and simulations with moderate CO2 increase (during the transition to high CO2 levels), may yield insight into likely 21C Arctic sea ice changes using these LIG simulations.

How to cite: Sime, L., Kageyama, M., Sicard, M., Guarino, M.-V., de Vernal, A., Schroeder, D., Stein, R., and Malmierca-Vallet, I. and the Ayako Abe-Ouchi6, Cecilia Bitz7, Pascale Braconnot1, Esther Brady8, Matthew A. Chamberlain9, Danny Feltham4, Chuncheng Guo10, Gerrit Lohmann5, Katrin Meissner11, Laurie Menviel11, Polina Morozova12, Kerim H. Nisancioglu13,14, Bette Otto-Bliesner8, Ryouta : A multi-model CMIP6 study of Arctic sea ice at 127 ka: Sea ice data compilation and model differences, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8628, https://doi.org/10.5194/egusphere-egu2020-8628, 2020

D3487 |
EGU2020-22296<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Zhaoyang Song, Mojib Latif, Wonsun Park, and Yuming Zhang

Stable oxygen isotope records from northern Greenland suggest that the local multidecadal surface-temperature variability exhibited a large reduction from the last glaciation to the Holocene. The origin of the reduced variability is thought to be perturbations in the mean atmospheric circulation due to Northern Hemisphere ice sheet variability. We reassess the factors driving the large multidecadal Greenland surface temperature (T2m) variability during the Last Glacial Maximum. The Kiel Climate Model has been integrated under preindustrial and glacial boundary conditions. We find that both atmospheric teleconnections from the Interdecadal Pacific Oscillation (IPO) and North Atlantic/Arctic sea ice variations strongly intensify under glacial boundary conditions, driving enhanced surface wind and in turn heat flux variability over Greenland. Additional simulations that restore the Pacific sea-surface temperature (SST) to its climatology confirm the important role of the IPO.

To investigate the relative contributions of atmospheric teleconnection from the IPO and sea-ice on the Greenland T2m, we force the atmospheric component of the coupled model in stand-alone mode by SSTs and sea ice concentrations simulated in coupled mode. The influence of atmospheric teleconnection is three times larger than that of sea ice. We conclude that the enhanced multidecadal Greenland surface-temperature variability during the LGM can largely be attributed to stronger atmospheric teleconnection from the IPO.

How to cite: Song, Z., Latif, M., Park, W., and Zhang, Y.: Enhanced multidecadal Greenland surface temperature variability during the Last Glacial Maximum linked to the Interdecadal Pacific Oscillation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22296, https://doi.org/10.5194/egusphere-egu2020-22296, 2020

D3488 |
EGU2020-9264<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Fanny Lhardy, Nathaëlle Bouttes, Didier Roche, and Xavier Crosta

At the interface of the atmosphere and the oceans, sea ice is a thin and reactive layer which depends on the surface temperatures of the two and with significant impact on both. In this vein, sea ice affects the regional energy budget due to its high albedo, modulates the transfer of gas and energy at the ocean-atmosphere by its simple presence and modifies the water column vertical structure through brine rejection during freezing and freshwater input during melting. As the densification of surface waters can lead to deep water formation, sea ice has an impact on deep ocean circulation (Ferrari et al. [2014], Marzocchi et al. [2019]).

Around 21,000 years ago, the glacial period called the LGM was marked by extensive ice sheets in the Northern Hemisphere, a consequent lower sea-level, and lower atmospheric CO2 concentrations than today’s. However, the processes driving these lower atmospheric CO2 concentrations are still not fully understood. Paleotracer data (Curry and Oppo [2005]) suggest that the Antarctic Bottom Water was a poorly ventilated and voluminous water mass, therefore efficiently trapping carbon. Proxies also allow for the reconstruction of LGM sea ice (de Vernal et al. [2013]), and their studies have indicated both an extended Southern Ocean sea ice and an enhanced seasonality (Gersonde et al. [2005], Allen et al. [2011], Benz et al. [2016]).

Models are very helpful to investigate the potentially complex response of the climate system to any perturbation. The Paleoclimate Modelling Intercomparison Project (now in phase 4) has proposed standardized LGM boundary conditions which notably allows for an evaluation of the model performance under cold conditions. During past PMIP phases, the simulation of the LGM deep ocean circulation has proven to be challenging (Otto-Bliesner et al. [2007], Muglia and Schmittner [2015]), which could be linked – at least partially – to the limitations in modelling past sea-ice changes (Goosse et al. [2013], Roche et al. [2012]).

In this study, the iLOVECLIM model – of intermediate complexity – (Goosse et al. [2010]) is used under the PMIP4 experimental design with both the ICE-6G-C and GLAC-1D topographies. The simulated sea ice is compared with a recent compilation of proxy data (Crosta, pers. com.). We look for potential sources of the observed model-data discrepancies using different model configurations. We examine in particular the simulated SSTs compared to MARGO [2009] data and show a regional and seasonal model-data disagreement that is quite consistent with the sea-ice model-data comparison.

How to cite: Lhardy, F., Bouttes, N., Roche, D., and Crosta, X.: Integrating model and data over the Southern Ocean at the Last Glacial Maximum to better understand the sea-ice cover, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9264, https://doi.org/10.5194/egusphere-egu2020-9264, 2020

D3489 |
EGU2020-10622<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
André Paul, Martin Werner, Alexandre Cauquoin, Javier García-Pintado, Ute Merkel, and Thejna Tharammal

The evaluation of a specific component of a comprehensive climate model is often hindered by biases in the coupled system, in simulations of the present as well as of past climate conditions. To assess different implementations of water isotopes as part of the hydrological cycle, we carried out atmosphere-only runs using different atmospheric general circulation models (AGCMs, here: CAM and ECHAM) but the same pre-industrial and Last Glacial Maximum (LGM, ~19,000 to ~23,000 a before present) boundary conditions, especially with respect to the monthly sea-surface temperature (SST) and sea-ice fraction fields. For the LGM, we used a new global climatology of the ocean surface during the Last Glacial Maximum mapped on a regular grid (GLOMAP), which is an extension of the Glacial Atlantic Ocean Mapping (GLAMAP) reconstruction of the Atlantic SST based on the results of the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) project and several recent estimates of the LGM sea-ice extent. This way, we can, on the one hand, avoid the propagation of the SST bias in coupled climate models. On the other hand, by comparing to fully-coupled simulations, we can isolate the impact of the ocean feedback on the simulated distributions of water isotopes over land, ice and ocean. To analyze the results, we calculated the anomalies between the LGM and pre-industrial climate states and compared them between the different models and to data. It turned out that the model response was affected by the amount of global cooling as well as the structure of the SST anomalies. The patterns in the simulated isotopic composition of precipitation for the LGM tended to follow the patterns in the SST boundary condition; a more zonal structure in the SST led to a more zonal response. Our results show the advantage of using water isotopes as a diagnostic tool for an AGCM through direct model-data comparison.

How to cite: Paul, A., Werner, M., Cauquoin, A., García-Pintado, J., Merkel, U., and Tharammal, T.: Sensitivity of isotopes in the hydrological cycle to simulated vs. reconstructed Last Glacial Maximum surface conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10622, https://doi.org/10.5194/egusphere-egu2020-10622, 2020

D3490 |
EGU2020-18159<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Patricio Velasquez and Christoph C. Raible

To understand the processes that govern the climate response and feedbacks, modelling paleoclimate states offers a unique possibility to have insights into the mechanisms that convert a modified forcing into climate changes. In spite of the benefit of using global climate models (GCMs) for reproducing other climate states, their spatial resolution insufficiently represents regional and local climates, especially over complex topography. In this study, we bridge this scale gap by using a dynamical downscaling with the regional climate model Weather Forecast Research Model version 3.8.1. that is driven by the fully coupled Community Climate System Model version 4. Focussing on the Alpine region, we obtain climate information at 2 km resolution at present-day (perpetual 1990 AD conditions), the Last Glacial Maximum (LGM, 21 kya) and Marine Isotope Stage 4 (MIS4, 65 kya). The benefit of the dynamical downscaling approach is illustrated by analysing the PD and LGM simulations with the proxy evidences. The orbital forcing response is assessed by the comparing MIS4 to LGM simulations. Since the height of the Laurentide and Scandinavian ice sheets may still have some uncertainties, we carry out two additional dynamically downscaled simulations where the thickness of the ice-sheets is modified to 66% and 125% of the LGM level.

Focusing on temperature and precipitation, we observe that the dynamical downscaling approach improves the representation of the Alpine climate agreeing the proxy evidences better than the GCM, especially during colder months. Furthermore, the MIS4 orbital forcing shows an increase of temperature over the Alpine region, in particular at low levels and during colder months. In addition, the precipitation is slightly increased over low-altitude areas, but strongly over the mountains, in particular in the western Alps during colder months. This increase of precipitation is the result of an increment of water content due to the temperature rise. The outcome of using different ice-sheet thicknesses shows that temperature remains almost unchanged but the precipitation patterns is modified showing differences over southwestern and northeastern Alps, especially during colder months. This change in the precipitation pattern is explained by the modification of the atmospheric dynamics over the North Atlantic and Europe, in particular by the orientation and the shift of the larger-scale wind patterns, i.e., wind stream and storm tracks.

In conclusion, we demonstrate that the regional dynamical downscaling is a valuable method for representing paleoclimates at a finer scale. Moreover, a different orbital forcing mostly impacts on temperature, especially during colder months. Whereas a modified thickness of the Laurentide and Scandinavian ice-sheets mainly impacts on precipitation pattern, in particular the southwestern and northeastern regions during colder months.

How to cite: Velasquez, P. and Raible, C. C.: High resolution climate information over Europe during glacial times using a dynamical downscaling approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18159, https://doi.org/10.5194/egusphere-egu2020-18159, 2020

D3491 |
EGU2020-20896<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Lucía A. Azibeiro, Michal Kucera, Lukas Jonkers, Francisco J. Sierro, and Angela Cloke-Hayes

La reconstrucción de la temperatura de la superficie del mar (TSM) ha estado durante mucho tiempo en el centro de la investigación paleoceanográfica. Los estudios en el Mediterráneo no han sido una excepción, ya que la reconstrucción cuantitativa de TSM en esta cuenca semicerrada es crucial para comprender el cambio climático pasado en la región. Muchos de estos métodos se basaron en foraminíferos planctónicos, tanto en su geoquímica de caparazón como en la composición de los ensamblajes (por ejemplo, funciones de transferencia). Comprender y modelar las relaciones entre el censo actual y las variables ambientales es la base para transformar los datos fósiles en estimaciones cuantitativas de estas variables. Aunque globalmente, los conjuntos de foraminíferos parecen estar determinados principalmente por la temperatura, en cuencas marginales como el Mediterráneo, 

In this study we attempt to determine which environmental parameters may control the variability of planktonic foraminifer assemblages in the modern Mediterranean. For this purpose, census counts of planktonic foraminifera assemblages from Mediterranean coretops (ForCenS data base) have been integrated with monthly estimates of SST, chlorophyll concentration, and vertical gradients of various parameters as proxies for water column stratification/mixing (WOA 1998).  Redundancy Analysis (RDA) was used to evaluating the explanatory power and the collinearity among tested environmental parameters and a forward selection of variables was carried out to identify those explaining independently the largest share of the variance in the composition of planktonic foraminifera assemblages.

Se identificaron nueve variables significativas. Tres de ellos corresponden a TSM, mientras que los otros seis se distribuyen entre las concentraciones de clorofila superficial (2) y los gradientes térmicos verticales (4). Las variables más explicativas son la TSM de junio (R 2 0.43) y el gradiente térmico vertical de diciembre (R 2 0.15).

How to cite: Azibeiro, L. A., Kucera, M., Jonkers, L., Sierro, F. J., and Cloke-Hayes, A.: Environmental parameters affecting composition of modern Mediterranean planktonic foraminifera assemblages, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20896, https://doi.org/10.5194/egusphere-egu2020-20896, 2020

D3492 |
EGU2020-5553<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Julia Hargreaves and James Annan

Paleoclimate simulations are widely used as a test of the ability of climate models to simulate climate states that are substantially different to the present day, and quantitative reconstructions of these climate states is an essential component of model evaluation.  With there being no large network of instrumental observations from these periods, we must rely on inferences from a relatively modest number of unevenly distributed proxy records which are believed to be quantitatively indicative of the climate state.  In order to robustly establish climatic conditions over global scales, we require methods for smoothing and interpolating between these sparse and imperfect estimates.  In recent years, we have worked on this problem and created a global reconstruction of the Last Glacial Maximum [Annan and Hargreaves, 2013, Climate of the Past] using the data and models which were available at that time.  The method uses scaled patterns from the PMIP ensemble of structurally diverse climate simulations, combined with sparse sets of proxy data, to produce spatially coherent and complete  data  fields  for  surface  air  and  sea  temperatures  (potentially  including  the  seasonal cycle)  along  with  uncertainty  estimates  over  the  whole  field.   This  approach  is  more  robust than alternative methods, which either perform a purely statistical interpolation of the data or at best combine the data with a single climate model. Here, we aim to improve the method, update the inputs, and apply the same technique to both Last Glacial Maximum and mid Pliocene climate intervals. As well as generating spatially complete and coherent maps of climate variables, our approach also generates well-calibrated uncertainty estimates.

How to cite: Hargreaves, J. and Annan, J.: Global reconstruction of surface temperature fields for past equilibrium climates, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5553, https://doi.org/10.5194/egusphere-egu2020-5553, 2020

D3493 |
EGU2020-11153<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Masa Kageyama and the PMIP4 LGM group

The Last Glacial Maximum (LGM, ~21,000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models have been used to generate LGM simulations as part of the Palaeoclimate Modelling Intercomparison Project (PMIP) contributionto CMIP6. Here we provide a preliminary analysis and evaluation of the results of these LGM experiments and compare them with the previous generation of simulations (PMIP3-CMIP5). We show that the PMIP4-CMIP6 are globally less cold and less dry than the PMIP3-CMIP5 simulations, most probably because of the use of a more realistic specification of the northern hemisphere ice sheets in the latest simulations although changes in model configuration may also contribute to this. There are important differences in both atmospheric and ocean circulation between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large so, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land-sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the palaeoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. The spatial patterns of increased precipitation associated with changes in the jet streams are also poorly captured. However, changes in the tropics are more realistic, particularly the changes in tropical temperatures over the oceans. Although these results are preliminary in nature, because of the limited number of LGM simulations currently available, they nevertheless point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.

How to cite: Kageyama, M. and the PMIP4 LGM group: The PMIP4-CMIP6 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3-CMIP5 simulations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11153, https://doi.org/10.5194/egusphere-egu2020-11153, 2020

D3494 |
EGU2020-12398<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received their highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Takashi Obase and Ayako Abe-Ouchi

During the last deglaciation, a major global warming trend was punctuated by abrupt climate changes, likely related to Atlantic meridional overturning circulation (AMOC). One problem is that an abrupt increase in the AMOC during the Bølling‐Allerød (BA) transition occurred when the melting of Northern Hemisphere ice sheets was significant, which tended to weaken the AMOC. Here, from transient simulations of the last deglaciation using an atmosphere‐ocean general circulation model, we show that an abrupt increase in the AMOC during the BA transition could occur without reduction in glacial meltwater. The abrupt increase in the AMOC accompanied abrupt warming in Greenland and sea ice retreat in the North Atlantic, consistent with proxies and previous modeling studies. The results imply that abrupt BA warming during the middle stage of the last deglaciation was a response to gradual warming under the presence of meltwater from continental ice sheets.

How to cite: Obase, T. and Abe-Ouchi, A.: Abrupt Bølling‐Allerød Warming Simulated under Gradual Forcing of the Last Deglaciation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12398, https://doi.org/10.5194/egusphere-egu2020-12398, 2020

D3495 |
EGU2020-22222<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Ayako Abe-Ouchi, Wing-Le Chan, Sam Sherriff-Tadano, Takashi Obase, Takahito Mitsui, Kenji Kawamura, Akira Oka, Masakazu Yoshimori, and Rumi Ohgaito

The glacial period was punctuated by abrupt millennial scale climate changes, such as Dansgaard Oeschger events, Boeling-Allerod and Younger Dryas. Although abrupt climate changes were shown to have a strong link to the shift between the (quasi) multiple equilibria of Atlantic Meridional Overturning Circulation (AMOC), modeling both together the stability of AMOC under different climate condition and observed glacial-deglacial climate change with fully coupled ocean-atmosphere GCM have been challenging. Here we present a series of long transient experiments (> 10, 000 years) with steadyforcing under different glacial condition summarized as a phase diagram and compared them with simulation under transient forcing experiments following PMIP4 using a coupled ocean-atmosphere model, MIROC4m AOGCM. The simulated LGM AMOC is weaker and shallower than the modern AMOC under Pre-Industrial condition. Conventional stability diagram for varied freshwater flux as well as phase diagram showing the response of the AMOC and climate to steady forcing is first obtained. It is shown that (quasi-) multiple equilibria exist indeed under a certain range of climate condition. When a steady forcing under glacial condition is applied even without freshwater perturbation, however, the whole climate-ocean system shows self-sustained oscillation with bipolar seesaw pattern and changes between interstadials and stadials, whose periodicity or the return time ranges from 1000 years to nearly 10000 years depending on the background forcing, e.g. Greenhouse Gas levels. We show that the Southern Ocean plays important role in determining the condition of oscillations. It implies that the abrupt climate change during the glacial climate and deglaciation can be induced much more frequently when the coupled climate system enters the region of the AMOC oscillatory mode than outside of the region. Implication on the mechanism and the conditions of the millennial scale climate changes for the past time period is discussed.

 

How to cite: Abe-Ouchi, A., Chan, W.-L., Sherriff-Tadano, S., Obase, T., Mitsui, T., Kawamura, K., Oka, A., Yoshimori, M., and Ohgaito, R.: Unforced oscillations of climate and AMOC under Glacial climate in MIROC 4m AOGCM, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22222, https://doi.org/10.5194/egusphere-egu2020-22222, 2020

D3496 |
EGU2020-5645<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Thomas Kleinen, Sergey Gromov, Benedikt Steil, and Victor Brovkin

The time between the last glacial maximum (LGM) and the present is highly interesting with regard to atmospheric methane. Between the LGM and 10 ka BP atmospheric CH4, as reconstructed from ice cores, nearly doubled, with very rapid concentration changes of about 200 ppb occurring during the Bølling Allerød (BA) and Younger Dryas (YD) transitions. During the Holocene, atmospheric CH4 is very similar for 10 ka BP and PI, but CH4 is about 15% lower in between at 5 ka BP.

We use a methane-enabled version of MPI-ESM, the Max Planck Institute Earth System Model, to investigate changes in methane cycling in a transient ESM experiment from the LGM to the present. The model is driven by prescribed orbit, greenhouse gases and ice sheets, with all other changes to the climate system determined internally. Methane cycling is modelled by modules representing the atmospheric transport and sink of methane, as well as terrestrial sources and sinks from soils, termites, and fires. Thus, the full natural methane cycle – with the exception of geological and animal emissions – is represented in the model.

Model results are compared to methane concentrations from ice cores, and key periods in climate/methane evolution are highlighted by detailed analyses. Methane concentrations can mainly be explained by emission changes, with LGM emissions substantially reduced in comparison to the early Holocene and preindustrial states due to lower temperature, CO2, and soil carbon. For the large transitions during the deglaciation, such as the transitions from Older Dryas to BA, BA to YD, and YD to Holocene, ocean circulation changes are required to obtain atmospheric methane changes of sufficient magnitude and rapidity.

How to cite: Kleinen, T., Gromov, S., Steil, B., and Brovkin, V.: Methane from the LGM to the present: The Natural methane cycle, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5645, https://doi.org/10.5194/egusphere-egu2020-5645, 2020