The CCSM4 Ocean Component

Danabasoglu, Gökhan; Bates, S. C.; Briegleb, Bruce P.; Jayne, Steven R.; Jochum, Markus; Large, William G.; Peacock, Synte; Yeager, Stephen

doi:10.1175/jcli-d-11-00091.1

Cited by 552 publications

(430 citation statements)

References 68 publications

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“…2(d)) is similar to the results from other contemporary models (e.g. Danabasoglu et al 2012, Delworth et al 2012. The main point to be seen from the trends in Fig.…”

Section: Model and Experimentssupporting

confidence: 88%

Ocean circulation response to anthropogenic aerosol and greenhouse gas forcing in the CSIRO-Mk3.6 climate model

Collier¹,

Rotstayn²,

Kim³

et al. 2013

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“…2(d)) is similar to the results from other contemporary models (e.g. Danabasoglu et al 2012, Delworth et al 2012. The main point to be seen from the trends in Fig.…”

Section: Model and Experimentssupporting

confidence: 88%

Ocean circulation response to anthropogenic aerosol and greenhouse gas forcing in the CSIRO-Mk3.6 climate model

Collier¹,

Rotstayn²,

Kim³

et al. 2013

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“…Both CAM4 and CLM4 are explained separately in following sections. The ocean component of CESM is the Parallel Ocean Program version 2 (POP2), which is a hydrostatic, free-surface, primitive-equation model formulated on a curvilinear orthogonal grid 31 . The nominal 1 • horizontal resolution version of the ocean component is used with 60 vertical levels.…”

Section: Methodsmentioning

confidence: 99%

Fate of water pumped from underground and contributions to sea-level rise

et al. 2016

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The contributions from terrestrial water sources to sea-level rise, other than ice caps and glaciers, are highly uncertain and heavily debated 1-5 . Recent assessments indicate that groundwater depletion (GWD) may become the most important positive terrestrial contribution 6-10 over the next 50 years, probably equal in magnitude to the current contributions from glaciers and ice caps 6 . However, the existing estimates assume that nearly 100% of groundwater extracted eventually ends up in the oceans. Owing to limited knowledge of the pathways and mechanisms governing the ultimate fate of pumped groundwater, the relative fraction of global GWD that contributes to sea-level rise remains unknown. Here, using a coupled climate-hydrological model 11,12 simulation, we show that only 80% of GWD ends up in the ocean. An increase in runo to the ocean accounts for roughly two-thirds, whereas the remainder results from the enhanced net flux of precipitation minus evaporation over the ocean, due to increased atmospheric vapour transport from the land to the ocean. The contribution of GWD to global sea-level rise amounted to 0.02 (±0.004) mm yr −1 in 1900 and increased to 0.27 (±0.04) mm yr −1 in 2000. This indicates that existing studies have substantially overestimated the contribution of GWD to global sea-level rise by a cumulative amount of at least 10 mm during the twentieth century and early twenty-first century. With other terrestrial water contributions included, we estimate the net terrestrial water contribution during the period 1993-2010 to be +0.12 (±0.04) mm yr −1 , suggesting that the net terrestrial water contribution reported in the IPCC Fifth Assessment Report report is probably overestimated by a factor of three.Sea-level rise (SLR) is a direct effect of climate change, through the thermal expansion of ocean waters and the contribution of melt water from ice sheets, ice caps and glaciers. In an initial assessment 13 , the net contribution of sub-polar terrestrial water storage change to global sea-level variation was highly uncertain and heavily debated [14][15][16][17][18]

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“…As discussed by Kay et al [16], CAM5 has a better representation of Arctic cloud properties than earlier model versions. The ocean component [17] is based on the Parallel Ocean Program 2 (POP2; [18]). It uses a nominal 1 • resolution displaced-pole grid with 60 vertical levels.…”

Section: Climate Model Experiments (A) Cesm-cam5 Large Ensemblementioning

confidence: 99%

Factors affecting projected Arctic surface shortwave heating and albedo change in coupled climate models

Holland

Landrum

2015

Phil. Trans. R. Soc. A.

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One contribution of 9 to a discussion meeting issue 'Arctic sea ice reduction: the evidence, models and impacts (part 1)' . We use a large ensemble of simulations from the Community Earth System Model to quantify simulated changes in the twentieth and twenty-first century Arctic surface shortwave heating associated with changing incoming solar radiation and changing ice conditions. For increases in shortwave absorption associated with albedo reductions, the relative influence of changing sea ice surface properties and changing sea ice areal coverage is assessed. Changes in the surface sea ice properties are associated with an earlier melt season onset, a longer snow-free season and enhanced surface ponding. Because many of these changes occur during peak solar insolation, they have a considerable influence on Arctic surface shortwave heating that is comparable to the influence of ice area loss in the early twenty-first century. As ice area loss continues through the twenty-first century, it overwhelms the influence of changes in the sea ice surface state, and is responsible for a majority of the net shortwave increases by the mid-twenty-first century. A comparison with the Arctic surface albedo and shortwave heating in CMIP5 models indicates a large spread in projected twenty-first century change. This is in part related to different ice loss rates among the models and different representations of the late twentieth century ice albedo and associated sea ice surface state.

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The CCSM4 Ocean Component

Cited by 552 publications

References 68 publications

Ocean circulation response to anthropogenic aerosol and greenhouse gas forcing in the CSIRO-Mk3.6 climate model

Ocean circulation response to anthropogenic aerosol and greenhouse gas forcing in the CSIRO-Mk3.6 climate model

Fate of water pumped from underground and contributions to sea-level rise

Factors affecting projected Arctic surface shortwave heating and albedo change in coupled climate models

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