Heinrich Stadials: Globa Climate Impacts and the "Bipolar Seesaw" Phase Relationsip

2020 ◽  
Author(s):  
Richard Peltier ◽  
Jesse velay-Vitow ◽  
Deepak Chandan
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Phase Relationship ◽  
Coupled Model ◽  
Ice Cores ◽  
Climate Impacts ◽  
Coupled Climate Model ◽  
Heinrich Event ◽  
Freshwater Forcing ◽  
Isotopic Records

<p>With the recent demonstration that millennial timescale Dansgaard-Oeschger oscillations of MIS 3 are predictable in a modern coupled climate model following a Heinrich event-like reduction of AMOC strength (eg. Peltier and Vettoretti, 2014), the stage was set for a renewed attack upon the physics of H-events themselves (see Velay-Vitow et al, 2019, JGR-Oceans). This predicts that the freshwater forcing of the AMOC by individual H-events will be on the order of 0.1 Sv and to be maintained for a period between 500 years and 1500 years in accord with data-based inferences (Hemming, 2004). Whereas in the original analysis of H-event induced D-O oscillations the D-O initiating H-event appeared simply as a sharp reduction in AMOC strength in the spin-up of the coupled model, in the work to be reported we transform the pseudo H-event into one that involves explicit freshwater forcing applied at a strength and over a range of times in accord with observational constraints. This has enabled a detailed analysis of the global climate impacts of these events as represented in the coupled climate model that we continue to employ. A critical focus of this analysis is upon the phase relationship between events recorded in the oxygen isotopic records from Greenland and Antarctic ice cores, analyses which demonstrate that this phase relationship is set by the D-O initiating Heinrich event. We also address the expected global climate impacts of stadial-interstadial transitions and provide an initial discussion of these impacts with those recorded in speliothems and other archives.</p>

scholarly journals Effects of Ocean Biology on the Penetrative Radiation in a Coupled Climate Model

2006 ◽  
Vol 19 (16) ◽  
pp. 3973-3987 ◽  
Author(s):  
Patrick Wetzel ◽  
Ernst Maier-Reimer ◽  
Michael Botzet ◽  
Johann Jungclaus ◽  
Noel Keenlyside ◽  
...  
Keyword(s):  
Seasonal Cycle ◽  
Marine Biology ◽  
Climate Model ◽  
Global Climate ◽  
Ocean Model ◽  
Equatorial Pacific ◽  
Shortwave Radiation ◽  
Upper Ocean ◽  
Biogeochemical Model ◽  
Coupled Climate Model

Abstract The influence of phytoplankton on the seasonal cycle and the mean global climate is investigated in a fully coupled climate model. The control experiment uses a fixed attenuation depth for shortwave radiation, while the attenuation depth in the experiment with biology is derived from phytoplankton concentrations simulated with a marine biogeochemical model coupled online to the ocean model. Some of the changes in the upper ocean are similar to the results from previous studies that did not use interactive atmospheres, for example, amplification of the seasonal cycle; warming in upwelling regions, such as the equatorial Pacific and the Arabian Sea; and reduction in sea ice cover in the high latitudes. In addition, positive feedbacks within the climate system cause a global shift of the seasonal cycle. The onset of spring is about 2 weeks earlier, which results in a more realistic representation of the seasons. Feedback mechanisms, such as increased wind stress and changes in the shortwave radiation, lead to significant warming in the midlatitudes in summer and to seasonal modifications of the overall warming in the equatorial Pacific. Temperature changes also occur over land where they are sometimes even larger than over the ocean. In the equatorial Pacific, the strength of interannual SST variability is reduced by about 10%–15% and phase locking to the annual cycle is improved. The ENSO spectral peak is broader than in the experiment without biology and the dominant ENSO period is increased to around 5 yr. Also the skewness of ENSO variability is slightly improved. All of these changes lead to the conclusion that the influence of marine biology on the radiative budget of the upper ocean should be considered in detailed simulations of the earth’s climate.

scholarly journals A simple object-oriented and open source model for scientific and policy analyses of the global carbon cycle – Hector v0.1

2014 ◽  
Vol 7 (5) ◽  
pp. 7075-7119
Author(s):  
C. A. Hartin ◽  
P. Patel ◽  
A. Schwarber ◽  
R. P. Link ◽  
B. P. Bond-Lamberty
Keyword(s):  
Carbon Cycle ◽  
Open Source ◽  
Climate Models ◽  
Modular Design ◽  
Climate Model ◽  
Global Climate ◽  
Coupled Model ◽  
Object Oriented ◽  
Climate Mitigation ◽  
Carbon Cycle Model

Abstract. Simple climate models play an integral role in policy and scientific communities. They are used for climate mitigation scenarios within integrated assessment models, complex climate model emulation, and uncertainty analyses. Here we describe Hector v0.1, an open source, object-oriented, simple global climate carbon-cycle model. This model runs essentially instantaneously while still representing the most critical global scale earth system processes. Hector has three main carbon pools: an atmosphere, land, and ocean. The model's terrestrial carbon cycle includes respiration and primary production, accommodating arbitrary geographic divisions into, e.g., ecological biomes or political units. Hector's actively solves the inorganic carbon system in the surface ocean, directly calculating air–sea fluxes of carbon and ocean pH. Hector reproduces the global historical trends of atmospheric [CO2] and surface temperatures. The model simulates all four Representative Concentration Pathways with high correlations (R>0.7) with current observations, MAGICC (a well-known simple climate model), and the Coupled Model Intercomparison Project version 5. Hector is freely available under an open source license, and its modular design will facilitate a broad range of research in various areas.

Investigation of the Surface and Circulation Impacts of Cloud-Brightening Geoengineering

2012 ◽  
Vol 25 (21) ◽  
pp. 7527-7543 ◽  
Author(s):  
E. Baughman ◽  
A. Gnanadesikan ◽  
A. Degaetano ◽  
A. Adcroft
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Cloud Condensation Nuclei ◽  
Vertical Wind Shear ◽  
Coupled Model ◽  
Walker Circulation ◽  
Cloud Albedo ◽  
Potential Index ◽  
Marine Stratus ◽  
The Impact

Projected increases in greenhouse gases have prompted serious discussion on geoengineering the climate system to counteract global climate change. Cloud albedo enhancement has been proposed as a feasible geoengineering approach, but previous research suggests undesirable consequences of globally uniform cloud brightening. The present study uses GFDL’s Climate Model version 2G (CM2G) global coupled model to simulate cloud albedo enhancement via increases in cloud condensation nuclei (CCN) to 1000 cm−3 targeted at the marine stratus deck of the Pacific Ocean, where persistent low clouds suggest a regional approach to cloud brightening. The impact of this regional geoengineering on global circulation and climate in the presence of a 1% annual increase of CO2 was investigated. Surface temperatures returned to near preindustrial levels over much of the globe with cloud modifications in place. In the first 40 years and over the 140-yr mean, significant cooling over the equatorial Pacific, continued Arctic warming, large precipitation changes over the western Pacific, and a westward compression and intensification of the Walker circulation were observed in response to cloud brightening. The cloud brightening caused a persistent La Niña condition associated with an increase in hurricane maximum potential intensity and genesis potential index, and decreased vertical wind shear between July and November in the tropical Atlantic, South China Sea, and to the east of Japan. Responses were similar with CCN = 500 cm−3.

Reconstructing the distribution of surface mass balance over East Antarctica (DML) from 1850 to present day

2020 ◽  
Author(s):  
Nicolas Ghilain ◽  
Stéphane Vannitsem ◽  
Quentin Dalaiden ◽  
Hugues Goosse
Keyword(s):  
Spatial Distribution ◽  
Mass Balance ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Ice Cores ◽  
Global Climate Models ◽  
East Antarctica ◽  
Surface Mass Balance ◽  
Surface Mass

<p>Over recent decades, the Antarctic Ice Sheet has witnessed large spatial variations at its surface through the surface mass balance (SMB). Since the complex Antarctic topography, working at high resolution is crucial to represent accurately the dynamics of SMB. While ice cores provide a mean to infer the SMB over centuries, the view is very spatially constrained. Global Climate models estimate the spatial distribution of SMB over centuries, but with a too coarse resolution with regards to the large variations due to local orographic effects. We have therefore explored a methodology to statistically downscale the SMB components from the climate model historical simulations (1850-present day). An analogue method is set up over a period of 30 years with the ERA-Interim reanalysis (1979-2010 AD) and associated with SMB components from the Regional Atmospheric Climate Model (RACMO) at 5 km spatial resolution over Dronning Maud in East Antarctica. The same method is then applied to the period from 1850 to present days using an ensemble of 10 simulations from the CESM2 model. This method enables to derive a spatial distribution of SMB. In addition, the changes in precipitation delivery mechanisms can be unveiled.</p>

scholarly journals Decadal Prediction of the Sahelian Precipitation in CMIP5 Simulations

2013 ◽  
Vol 26 (19) ◽  
pp. 7708-7719 ◽  
Author(s):  
Marco Gaetani ◽  
Elsa Mohino
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
System Model ◽  
Low Resolution ◽  
Coupled Models ◽  
Climate System Model ◽  
Model Version ◽  
Coupled Global Climate Model

Abstract In this study the capability of eight state-of-the-art ocean–atmosphere coupled models in predicting the monsoonal precipitation in the Sahel on a decadal time scale is assessed. To estimate the importance of the initialization, the predictive skills of two different CMIP5 experiments are compared, a set of 10 decadal hindcasts initialized every 5 years in the period 1961–2009 and the historical simulations in the period 1961–2005. Results indicate that predictive skills are highly model dependent: the Fourth Generation Canadian Coupled Global Climate Model (CanCM4), Centre National de Recherches Météorologiques Coupled Global Climate Model, version 5 (CNRM-CM5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR) models show improved skill in the decadal hindcasts, while the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) is skillful in both the decadal and historical experiments. The Beijing Climate Center, Climate System Model, version 1.1 (BCC-CSM1.1), Hadley Centre Coupled Model, version 3 (HadCM3), L'Institut Pierre-Simon Laplace Coupled Model, version 5, coupled with NEMO, low resolution (IPSL-CM5A-LR), and Meteorological Research Institute Coupled Atmosphere–Ocean General Circulation Model, version 3 (MRI-CGCM3) models show insignificant or no skill in predicting the Sahelian precipitation. Skillful predictions are produced by models properly describing the SST multidecadal variability and the initialization appears to play an important role in this respect.

scholarly journals Variability of Upper Pacific Ocean Overturning in a Coupled Climate Model

2005 ◽  
Vol 18 (5) ◽  
pp. 666-683 ◽  
Author(s):  
William J. Merryfield ◽  
George J. Boer
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Pacific Ocean ◽  
Climate Model ◽  
Low Frequency ◽  
Heat Content ◽  
Coupled Model ◽  
Tropical Pacific Ocean ◽  
Coupled Climate Model ◽  
Subtropical Cell

Abstract Variability of subtropical cell (STC) overturning in the upper Pacific Ocean is examined in a coupled climate model in light of large observed changes in STC transport. In a 1000-yr control run, modeled STC variations are smaller than observed, but correlate in a similar way with low-frequency ENSO-like variability. In model runs that include anthropogenically forced climate change, STC pycnocline transports decrease progressively under the influence of global warming, attaining reductions of 8% by 2000 and 46% by 2100. Although the former reduction is insufficient to fully account for the apparent observed decline in STC transport over recent decades, it does suggest that global warming may have contributed to the observed changes. Analysis of coupled model results shows that STC transports play a significant role in modulating tropical Pacific Ocean heat content, and that such changes are dominated by anomalous currents advecting mean temperature, rather than by advection of temperature anomalies by mean currents.

Beyond Weather Time-Scale Prediction for Hurricane Sandy and Super Typhoon Haiyan in a Global Climate Model

2015 ◽  
Vol 143 (2) ◽  
pp. 524-535 ◽  
Author(s):  
Baoqiang Xiang ◽  
Shian-Jiann Lin ◽  
Ming Zhao ◽  
Shaoqing Zhang ◽  
Gabriel Vecchi ◽  
...  
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
The Philippines ◽  
Hurricane Sandy ◽  
False Alarms ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Super Typhoon

Abstract While tropical cyclone (TC) prediction, in particular TC genesis, remains very challenging, accurate prediction of TCs is critical for timely preparedness and mitigation. Using a new version of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the authors studied the predictability of two destructive landfall TCs: Hurricane Sandy in 2012 and Super Typhoon Haiyan in 2013. Results demonstrate that the geneses of these two TCs are highly predictable with the maximum prediction lead time reaching 11 days. The “beyond weather time scale” predictability of tropical cyclogenesis is primarily attributed to the model’s skillful prediction of the intraseasonal Madden–Julian oscillation (MJO) and the westward propagation of easterly waves. Meanwhile, the landfall location and time can be predicted one week ahead for Sandy’s U.S landfall, and two weeks ahead for Haiyan’s landing in the Philippines. The success in predicting Sandy and Haiyan, together with low false alarms, indicates the potential of using the GFDL coupled model for extended-range predictions of TCs.

scholarly journals Plant-microbe Symbioses Reveal Underestimation of Modeled Climate Impacts

2018 ◽  
Author(s):  
Mingjie Shi ◽  
Joshua B. Fisher ◽  
Richard P. Phillips ◽  
Edward R. Brzostek
Keyword(s):  
Climate Change ◽  
Nitrogen Limitation ◽  
Climate Models ◽  
Climate Model ◽  
Net Primary Production ◽  
Carbon Sink ◽  
Global Climate ◽  
Terrestrial Ecosystems ◽  
Climate Impacts ◽  
Microbial Symbionts

Abstract. The extent to which terrestrial ecosystems slow climate change by sequestering carbon hinges in part on nutrient limitation. We used a coupled carbon–climate model that accounts for the carbon cost to plants of supporting nitrogen-acquiring microbial symbionts to explore how nitrogen limitation affects global climate. The carbon costs of supporting symbiotic nitrogen uptake reduced net primary production, with the largest absolute effects occurring at low-latitudes and the largest relative changes occurring at high-latitudes. The largest impact occurred in high-latitude ecosystems, where such costs were estimated to increase temperature by 1.0 °C and precipitation by 9 mm yr−1. Globally, our model predicted that nitrogen limitation enhances temperature and decreases precipitation; as such, our results suggest that carbon expenditures to support nitrogen-acquiring microbial symbionts have critical consequences for Earth’s climate, and that carbon–climate models that omit these processes will over-predict the land carbon sink and under-predict climate change.

Volcanic forcing of climate since 1850 in an interactive aerosol-chemistry-climate model

2021 ◽  
Author(s):  
Thomas Aubry ◽  
Anja Schmidt ◽  
Alix Harrow ◽  
Jeremy Walton ◽  
Jane Mulcahy ◽  
...  
Keyword(s):  
Optical Properties ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Ice Cores ◽  
Volcanic Eruptions ◽  
Stratospheric Aerosol ◽  
Aerosol Model ◽  
Volcanic Forcing

<p>Reconstructions of volcanic aerosol forcing and its climatic impacts are undermined by uncertainties in both the models used to build these reconstructions as well as the proxy and observational records used to constrain those models. Reducing these uncertainties has been a priority and in particular, several modelling groups have developed interactive stratospheric aerosol models. Provided with an initial volcanic injection of sulfur dioxide, these models can interactively simulate the life cycle and optical properties of sulfate aerosols, and their effects on climate. In contrast, most climate models that took part in the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP6) directly prescribe perturbations in atmospheric optical properties associated with an eruption. However, before the satellite era, the volcanic forcing dataset used for CMIP6 mostly relies on a relatively simple aerosol model and a volcanic sulfur inventory derived from ice-cores, both of which have substantial associated uncertainties.</p><p>In this study, we produced a new set of historical simulations using the UK Earth System Model UKESM1, with interactive stratospheric aerosol capability (referred to as interactive runs hereafter) instead of directly prescribing the CMIP6 volcanic forcing dataset as was done for CMIP6 (standard runs, hereafter). We used one of the most recent volcanic sulfur inventories as input for the interactive runs, in which aerosol properties are consistent with the model chemistry, microphysics and atmospheric components. We analyzed how the stratospheric aerosol optical depth, the radiative forcing and the climate response to volcanic eruptions differed between interactive and standard runs, and how these compare to observations and proxy records. In particular, we investigate in detail the differences in the response to the large-magnitude Krakatoa 1883 eruption between the two sets of runs. We also discuss differences for the 1979-2015 period where the forcing data in standard runs is directly constrained from satellite observations. Our results shed new light on uncertainties affecting the reconstruction of past volcanic forcing and highlight some of the benefits and disadvantages of using interactive stratospheric aerosol capabilities instead of a unique prescribed volcanic forcing dataset in CMIP’s historical runs.</p>

scholarly journals Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?

2015 ◽  
Vol 28 (17) ◽  
pp. 6938-6959 ◽  
Author(s):  
Alex J. Cannon ◽  
Stephen R. Sobie ◽  
Trevor Q. Murdock
Keyword(s):  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Precipitation Extremes ◽  
Extreme Value Analysis ◽  
Quantile Mapping ◽  
Value Analysis

Abstract Quantile mapping bias correction algorithms are commonly used to correct systematic distributional biases in precipitation outputs from climate models. Although they are effective at removing historical biases relative to observations, it has been found that quantile mapping can artificially corrupt future model-projected trends. Previous studies on the modification of precipitation trends by quantile mapping have focused on mean quantities, with less attention paid to extremes. This article investigates the extent to which quantile mapping algorithms modify global climate model (GCM) trends in mean precipitation and precipitation extremes indices. First, a bias correction algorithm, quantile delta mapping (QDM), that explicitly preserves relative changes in precipitation quantiles is presented. QDM is compared on synthetic data with detrended quantile mapping (DQM), which is designed to preserve trends in the mean, and with standard quantile mapping (QM). Next, methods are applied to phase 5 of the Coupled Model Intercomparison Project (CMIP5) daily precipitation projections over Canada. Performance is assessed based on precipitation extremes indices and results from a generalized extreme value analysis applied to annual precipitation maxima. QM can inflate the magnitude of relative trends in precipitation extremes with respect to the raw GCM, often substantially, as compared to DQM and especially QDM. The degree of corruption in the GCM trends by QM is particularly large for changes in long period return values. By the 2080s, relative changes in excess of +500% with respect to historical conditions are noted at some locations for 20-yr return values, with maximum changes by DQM and QDM nearing +240% and +140%, respectively, whereas raw GCM changes are never projected to exceed +120%.

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