CMIP6 Simulations With the CMCC Earth System Model (CMCC‐ESM2)

Lovato, Tomas; Peano, Daniele; Butenschön, Momme; Materia, Stefano; Iovino, Doroteaciro; Scoccimarro, Enrico; Fogli, Pier Giuseppe; Cherchi, Annalisa; Bellucci, Alessio; Gualdi, Silvio; Masina, Simona; Navarra, Antonio

doi:10.1029/2021ms002814

Cited by 164 publications

(53 citation statements)

References 129 publications

(211 reference statements)

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“…Increasing in complexity, MEDUSA2.1 (17), PISCESv2 (18), BFM5.2 (19), and COBALTv2 (20) all include multi-prey response functions, in which prey preferences must be prescribed to determine the partitioning of grazing on different prey options. In MEDUSA2.1 and PISCESv2, two types of zooplankton split their grazing effort between two types of phytoplankton in addition to detritus and smaller zooplankton, but do so with fixed prey preferences.…”

Section: The Representation Of Grazing In Ipcc Cmip6 Modelsmentioning

confidence: 99%

“…On the other hand, models with the highest Grazing Pressure are BFM5.2 (19), CMOC (13) and MARBL (15), all of which assume Grazing Pressure similar or greater than would be expected from an ocean populated exclusively with fast-grazing microzooplankton. In the middle, HAMOCCv2 (11), COBALTv2 (20), PISCESv2 (18), and CanOE (16) all apply moderate Grazing Pressure similar to a mixed-ocean, populated with equal parts meso-and microzooplankton.…”

Section: Grazing Pressure In Cmip6 Modelsmentioning

confidence: 99%

“…Yet marine biogeochemical (BGC) models represent the integrated behavior of all zooplankton using a strictly limited number of zooplankton groups, especially in computationally expensive IPCC coupled-climate models. Within the current generation of BGC models used in Coupled Model Intercomparison Project 6 (CMIP6) (10), most models include one (11)(12)(13)(14)(15) or two (16)(17)(18)(19) zooplankton groups, with few including more (20). Further, while chlorophyll, NPP, and phytoplankton biomass can be estimated from space, global in-situ zooplankton observations cannot (but see (21)), making simulated zooplankton biomass much more difficult to validate against spatially-resolved global data sets (22).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Marine carbon cycling and sequestration is extremely sensitive to zooplankton grazing in biogeochemical models

Rohr

Richardson²,

Lenton

et al. 2022

Preprint

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Zooplankton grazing regulates marine carbon cycling by constraining phytoplankton populations and the subsequent transfer of carbon to depth and higher trophic levels. Yet, without robust in-situ data to constrain them, the grazing formulation in state-of-the-art climate models varies largely. We present a new metric to compare how fast zooplankton are assumed to graze in 10 state-of-the-art (CMIP6) biogeochemical models and find they differ by nearly 2 orders of magnitude, implying an ocean populated exclusively with everything from slow-grazing krill to rapidly-grazing ciliates. We use a global, coupled ocean-biogeochemistry model to test the sensitivity of marine carbon cycling to this uncertainty and find the Net Primary Production (NPP) and export efficiency collapse across the range of plausible values. Even when tuned to identical NPP by increasing phytoplankton growth rates, export and secondary production remain extremely sensitive to grazing, likely biasing predictions of future climate states and food security.

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Section: The Representation Of Grazing In Ipcc Cmip6 Modelsmentioning

confidence: 99%

Section: Grazing Pressure In Cmip6 Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Marine carbon cycling and sequestration is extremely sensitive to zooplankton grazing in biogeochemical models

Rohr

Richardson²,

Lenton

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Developer, country Resolution CMCC-CM2-SR5 [59] Euro-Mediterranean Center on Climate Change, Italy 1.25×0.94 CMCC-ESM2 [60] 1.25×0.94 IPSL-CM6A-LR [61] Institut Pierre Simon Laplace, France 2.5×1.27 MPI-ESM1-2-HR [62] Max Planck Institute for Meteorology, Germany 0.94×0.93 MPI-ESM1-2-LR [63] 1.88×1.85 NorESM2-LM [64] Norwegian Climate Centre, Norway 2.5×1.89 NorESM2-MM [64] 1.25×0.94…”

Section: Modelmentioning

confidence: 99%

Present and future changes of winter cyclonic activity in the Mediterranean-Black Sea region in the 21st century in CMIP6 models’ ensemble

Voskresenskaya¹,

Maslova²,

Lubkov³

et al. 2022

Preprint

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A better understanding of the expected future cyclonic activity, especially in the Mediterranean Basin in winter, is essential for developing scientifically based adaptation and mitigation methods to extreme precipitation and wind anomalies. The aim of this study is to analyze the change of winter cyclonic activity in the Mediterranean-Black Sea region, within the Atlantic–European region, at the beginning (as the recent historical period), middle and end of the 21st century. The projections are based on an ensemble of seven CMIP6 models, which showed the best consistency with NCEP/NCAR and ERA5 reanalysis, under the intermediate SSP2-4.5 and highest-emission SSP5-8.5 scenarios. The results show a consistent increase of the frequency of cyclones over Central Europe and the British Isles associated with the shift of cyclone tracks: norward from the Western Mediterranean region and southward from the Iceland Low. The latter leads to a decrease of the frequency in the north of the Atlantic–European region. At the same time, there is a reduction of the frequency of cyclones over the east of the Mediterranean Sea consistent with the decrease of cyclogenesis events. Area-averaged cyclone numbers in the Western and Eastern Mediterranean and the Black Sea subregions reduce to the end of the century under the highest-emission scenario, but not constantly and with a raise in the middle of the 21st century under both scenarios, which may be linked to the long-term multidecadal variability or regional features. In general, our study shows that the future winter cyclonic activity in the Mediterranean-Black Sea region responds unevenly to global climate changes, because regional and monthly features are important, as well as accounting for the long-term quasiperiodic variability.

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“…Apart from observed data, the simulations of 20 the Coupled Model Intercomparison Project phase 6 (CMIP6) models, with data available at the time of analysis, were used in the analyses of the IPWP expansion in future climate conditions, including ACCESS-CM2 44 , CAMS-CSM1-0 45 , CAS-ESM2-0 46 , CESM2-WACCM 47 , CMCC-CM2-SR5 48 , CMCC-ESM2 49 , EC-Earth3 50 , EC-Earth3-Veg 50 , FGOALS-f3-L 51 , FGOALS-g3 52 , GFDL-ESM4 53 , INM-CM4-8 54 , INM-CM5-0 55 , IPSL-CM6A-LR 56 , MIROC6 57 , MPI-ESM1-2-HR 58 , MPI-ESM1-2-LR 58 , MRI-ESM2-0 59 , NESM3 60 , and TaiESM1 61 (Table 1). The choices of models depend on their availability of both SST and precipitation data of at the time of analysis.…”

Section: Datamentioning

confidence: 99%

On the differential expansion speeds of Indo-Pacific warm pool and deep convection favoring pool under greenhouse warming

Leung

Zhang

Gan

et al. 2022

Preprint

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The Indo-Pacific warm pool (IPWP), which affects the global climate system through supporting tropical convection, has been reported to expand significantly under greenhouse warming. Although early research revealed that the sea surface temperature (SST) threshold for deep convection (σSST_conv) increases with global warming, many latest works on the IPWP expansion were still conducted based on the traditional IPWP definition (e.g., static SST=28°C threshold, and is referred to as the oceanic warm pool, OWPSST=28). Here, using the latest observations and climate model simulations, by considering the long-term variability σSST_conv, we define the deep convection favoring pool (DCFP) over the Indo-Pacific Ocean, which reflects the region where with local SST favors occurrence of deep convections, under past and future climate change. Result based on observations from 1979–2020 shows that because of the increase of σSST_conv under climate change, the DCFP expands at a rate 2.6 times slower than the OWPSST=28, and is more consistent with the change in deep convection area. In the future climate (2015–2100), CMIP6 models projected that the σSST_conv¬ will further increase, with a larger trend under higher emission scenarios. As a result, the increasing trend of the DCFP area is 12–27 times smaller than that of OWPSST=28 under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios. While the OWPSST=28 expands to the eastern Pacific, the DCFP will remain within the Indian Ocean and western Pacific Ocean regardless of the emission levels. The consistency between the area changes of the DCFP and deep convection area implies that the IPWP expansion estimated based on the fixed σSST_conv may not reflect the direct impacts of Indo-Pacific warming on the climate system under greenhouse warming. This study emphasizes the necessity of considering the response of the relationship between deep convection and SST to climate change when studying the long-term variability of the IPWP, and claims that the DCFP serves as a more reasonable reference of IPWP expansion.

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CMIP6 Simulations With the CMCC Earth System Model (CMCC‐ESM2)

Cited by 164 publications

References 129 publications

Marine carbon cycling and sequestration is extremely sensitive to zooplankton grazing in biogeochemical models

Marine carbon cycling and sequestration is extremely sensitive to zooplankton grazing in biogeochemical models

Present and future changes of winter cyclonic activity in the Mediterranean-Black Sea region in the 21st century in CMIP6 models’ ensemble

On the differential expansion speeds of Indo-Pacific warm pool and deep convection favoring pool under greenhouse warming

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