Resolving and parameterising the ocean mesoscale in earth system models

Purpose of Review. Assessment of the impact of ocean resolution in Earth System models on the mean state, variability, and future projections and discussion of prospects for improved parameterisations to represent the ocean mesoscale. Recent Findings. The majority of centres participating in CMIP6 employ ocean components with resolutions of about 1 degree in their full Earth Systemmodels (eddy-parameterising models). In contrast, there are alsomodels submitted toCMIP6 (both DECK and HighResMIP) that employ ocean components of approximately 1/4 degree and 1/10 degree (eddy-present and eddy-rich models). Evidence to date suggests that whether the ocean mesoscale is explicitly represented or parameterised affects not only the mean state of the ocean but also the climate variability and the future climate response, particularly in terms of the Atlantic meridional overturning circulation (AMOC) and the Southern Ocean. Recent developments in scale-aware parameterisations of the mesoscale are being developed and will be included in future Earth System models. Summary. Although the choice of ocean resolution in Earth System models will always be limited by computational considerations, for the foreseeable future, this choice is likely to affect projections of climate variability and change as well as other aspects of the Earth System. Future Earth System models will be able to choose increased ocean resolution and/or improved parameterisation of processes to capture physical processes with greater fidelity

Representation of Large-Scale Ocean Circulation in the Atlantic and Southern Ocean in Climate Model Simulations and Projected Changes under Increased Warming

The global ocean acts as a mediator of Earth’s climate due to its role in the storage of heat and carbon. Presently, the ocean accounts for the storage of approximately 93% of the anthropogenic heat on our planet and ~27% of the anthropogenic CO2. Two regions in particular, the Southern Ocean and North Atlantic Ocean (SO, NA), act as gateways for the exchange of CO2 and heat between the atmosphere and the interior ocean. This is due to the unique water mass transformation processes that occur in these regions. Despite their disproportionate role in the climate system, large uncertainty exists with respect to understanding how the ocean circulation patterns and properties are projected to change in these regions throughout the 21st century. One pathway toward reducing projection uncertainty in these regions is to use modern observations and observational products to comprehensively diagnose, quantify, and improve upon mean state biases that exist in the climate simulations used to produce future climate projections. The work presented in this dissertation is a comprehensive analysis of the large-scale ocean circulation and properties in historical and 21st century simulations of large-ensembles of fully-coupled climate and Earth System Models contributed to multiple generations of the Coupled Model Intercomparison Project (CMIP). In the subtropical NA, a key region through which properties from the tropics are advected to the subpolar latitudes, the volume transports of the major flow regimes are reasonably represented in many CMIP5 models relative that observed by the Rapid Climate Change (RAPID) instrumental array at 26.5ºN. As the climate warms, all components of the total flow through the subtropical NA, with the exception of the wind-driven surface Ekman transport, are projected to weaken. Particularly, by applying the dynamical theory of Sverdrup balance, this work highlights the fact that the wind-driven NA subtropical gyre itself is projected to spin-down in response to a reduced wind stress curl over the subtropical latitudes. This spin-down, in conjunction with the reduced overturning at high-latitudes, acts as a source of significant additional weakening to the northward western boundary current flow in the upper ocean. In the SO, despite its dominant role in the oceanic uptake of anthropogenic carbon and heat relative to other basins, the large-scale circulation and properties have been poorly represented in climate models, resulting in low confidence ascribed to 21st century projections of the state of the SO. A comprehensive analysis of the simulation of the large-scale circulation and properties is presented for the Southern Ocean (SO) across thirty-one CMIP5 models. The main focus lies in building a framework to understand the major contributors to a model’s ability to represent the Antarctic Circumpolar Current (ACC) transport. Across the CMIP5 ensemble, the models fall into five different categories: 1) models that produce a reasonable ACC transport for approximately the right reasons, 2) models that accurately simulate key metrics, yet produce a too weak ACC, 3) models that simulate the wind stress forcing at the ocean surface accurately, but have errors in the density gradient, 4) models that simulate an accurate density gradient, but exhibit errors in the wind stress forcing, and 5) models that produce errors in all the metrics. Building on the framework presented in the CMIP5 study, a comprehensive assessment of the large-scale circulation and properties as simulated in the SO is performed across ensembles of models contributed to the past three CMIP generations (CMIP3-CMIP6). The CMIP6 models show improved representation of key observable-metrics in the SO including surface wind stress and wind stress curl, strength of the ACC, and meridional density gradients in the region of the ACC. However, some persistent biases have carried over into CMIP6 including an upper ocean that remains too fresh and too warm, significant warm biases at depth in several simulations, and a poor representation of Antarctic sea ice extent (SIE). These biases in observable metrics need to be considered when interpreting projected trends or biogeochemical properties in this region.Release after 11/05/202

Impact of the Melting of the Greenland Ice Sheet on the Atlantic Meridional Overturning Circulation in 21st Century Model Projections

Contemporary observations show an increase in the melting of the Greenland Ice Sheet (GrIS) since the early 21st century. Located near the critical sites of oceanic deep convection and deep water formation, the melting of the GrIS has the potential to directly impact the Atlantic Meridional Overturning Circulation (AMOC) by freshening ocean surface waters in these regions. The majority of the Coupled Model Intercomparison Project Phase 5 (CMIP5) models project a decline in AMOC strength by 10-50% during the 21st century, in response to the increase in atmospheric greenhouse gas (GHG) concentrations. However, due to the simple treatment of polar ice sheets and the lack of a dynamical ice sheet component in these models, these projections likely underestimated the impacts of the GrIS melt, leading to uncertainty in projecting future AMOC evolution and climate change around Greenland. To better understand the impact of the GrIS melt on the AMOC, we perform a series of 21st century projection runs with a state-of-the-art Earth System Model-GFDL ESM2Mb. We consider a medium and a high Representative Concentration Pathway (RCP) scenario (RCP4.5 and RCP8.5, respectively). Unlike the CMIP5-standard RCP runs which included only radiative forcing, the new model experiments are also forced with additional and potentially more realistic meltwater discharge from the GrIS. This meltwater discharge is estimated based on a model-based relationship between the GrIS surface melt and the 500hPa atmospheric temperature anomalies over Greenland. The model simulations indicate that compared to the RCP4.5-only and RCP8.5-only projections, the additional melt water from the GrIS can further weaken the AMOC, but with a relatively small magnitude. The reason is that radiative forcing already weakens the deep convection and deep water formation in the North Atlantic, therefore limiting the magnitude of further weakening of AMOC due to the additional meltwater. The modeling results suggest that the AMOC's sensitivity to freshwater forcing due to the GrIS melt is highly dependent on the location and strength of oceanic deep convection sites in ESM2Mb as well as the pathways of the meltwater towards these regions. The additional meltwater contributes to the minimum surface warming (so-called "warming hole") south of Greenland. These simulations with ESM2Mb contribute to the Atlantic Meridional Overturning Circulation Model Intercomparison Project (AMOCMIP), a community effort between international modeling centers to investigate the impacts of the melting of the GrIS on the AMOC and quantify the associated uncertainty

Supporting GFDL data for Southern Ocean Freshwater release model experiments Initiative (SOFIA)

Note: This data collection is hosted at the Geophysical Fluid Dynamics Laboratory. Data DOI capability is provided by PUL. Please refer to the README for a detailed description of the dataset. For questions, please contact [email protected], with the subject line including the title of the dataset.See "how_to_access_data.txt" to access data files from GDFL servers.This output was produced in coordination with the Southern Ocean Freshwater release model experiments Initiative (SOFIA) and is the Tier 1 experiment where freshwater is delivered in a spatially and temporally uniform pattern at the surface of the ocean at sea surface temperature in a 1-degree latitude band extending from Antarctica’s coastline. The total additional freshwater flux imposed as a monthly freshwater flux entering the ocean is 0.1 Sv. Users are referred to the methods section of Beadling et al. (2022) for additional details on the meltwater implementation in CM4 and ESM4. The datasets in this collection contain model output from the coupled global climate model, CM4, and Earth System Model, ESM4, both developed at the Geophysical Fluid Dynamics Laboratory (GFDL) of the National Oceanic and Atmospheric Administration (NOAA). The ocean_monthly_z and ocean_annual_z output are provided as z depth levels in meters as opposed to the models native hybrid vertical ocean coordinate which consists of z* (quasi-geopotential) coordinates in the upper ocean through the mixed layer, transitioning to isopycnal (referenced to 2000 dbar) in the ocean interior. Please see README for further details.File list: doc/README data/ cm4_tier1_antwater.agessc.ocean_annual_z.tar.gz cm4_tier1_antwater.bsnk.ice_monthly.tar.gz cm4_tier1_antwater.cld_amt.atmos_level_monthly.tar.gz cm4_tier1_antwater.evap.atmos_level_monthly.tar.gz cm4_tier1_antwater.evs.ocean_monthly.tar.gz cm4_tier1_antwater.ficeberg.ocean_monthly.tar.gz cm4_tier1_antwater.frazil.ice_monthly.tar.gz cm4_tier1_antwater.friver.ocean_monthly.tar.gz cm4_tier1_antwater.heat_content_surfwater.ocean_monthly.tar.gz cm4_tier1_antwater.hfds.ocean_monthly.tar.gz cm4_tier1_antwater.hflso.ocean_monthly.tar.gz cm4_tier1_antwater.hfsifrazil.ocean_monthly.tar.gz cm4_tier1_antwater.hfsso.ocean_monthly.tar.gz cm4_tier1_antwater.lsrc.ice_monthly.tar.gz cm4_tier1_antwater.mlotst.ocean_monthly.tar.gz cm4_tier1_antwater.precip.atmos_level_monthly.tar.gz cm4_tier1_antwater.prlq.ocean_monthly.tar.gz cm4_tier1_antwater.prsn.ocean_monthly.tar.gz cm4_tier1_antwater.rlntds.ocean_monthly.tar.gz cm4_tier1_antwater.rsntds.ocean_monthly.tar.gz cm4_tier1_antwater.sfdsi.ocean_monthly.tar.gz cm4_tier1_antwater.siconc.ice_monthly.tar.gz cm4_tier1_antwater.sithick.ice_monthly.tar.gz cm4_tier1_antwater.siu.ice_monthly.tar.gz cm4_tier1_antwater.siv.ice_monthly.tar.gz cm4_tier1_antwater.slp.atmos_level_monthly.tar.gz cm4_tier1_antwater.snowfl.ice_monthly.tar.gz cm4_tier1_antwater.so.ocean_annual_z.tar.gz cm4_tier1_antwater.so.ocean_monthly_z_complete.tar.gz cm4_tier1_antwater.static_fields.tar.gz cm4_tier1_antwater.tauuo.ocean_monthly.tar.gz cm4_tier1_antwater.tauvo.ocean_monthly.tar.gz cm4_tier1_antwater.temp.atmos_level_monthly.tar.gz cm4_tier1_antwater.thetao.ocean_annual_z.tar.gz cm4_tier1_antwater.thetao.ocean_monthly_z.tar.gz cm4_tier1_antwater.t_ref.atmos_level_monthly.tar.gz cm4_tier1_antwater.ucomp.atmos_level_monthly.tar.gz cm4_tier1_antwater.umo.ocean_annual_z.tar.gz cm4_tier1_antwater.umo.ocean_monthly_z.tar.gz cm4_tier1_antwater.uo.ocean_annual_z.tar.gz cm4_tier1_antwater.uo.ocean_monthly_z.tar.gz cm4_tier1_antwater.u_ref.atmos_level_monthly.tar.gz cm4_tier1_antwater.vcomp.atmos_level_monthly.tar.gz cm4_tier1_antwater.vmo.ocean_annual_z.tar.gz cm4_tier1_antwater.vmo.ocean_monthly_z.tar.gz cm4_tier1_antwater.volcello.ocean_annual_z.tar.gz cm4_tier1_antwater.volcello.ocean_monthly_z.tar.gz cm4_tier1_antwater.vo.ocean_annual_z.tar.gz cm4_tier1_antwater.vo.ocean_monthly_z.tar.gz cm4_tier1_antwater.v_ref.atmos_level_monthly.tar.gz cm4_tier1_antwater.wfo.ocean_monthly.tar.gz cm4_tier1_antwater.zos.ocean_monthly.tar.gz esm4_tier1_antwater.agessc.ocean_annual_z.tar.gz esm4_tier1_antwater.bsnk.ice_monthly.tar.gz esm4_tier1_antwater.cld_amt.atmos_level_monthly.tar.gz esm4_tier1_antwater.evap.atmos_level_monthly.tar.gz esm4_tier1_antwater.evs.ocean_monthly.tar.gz esm4_tier1_antwater.ficeberg.ocean_monthly.tar.gz esm4_tier1_antwater.frazil.ice_monthly.tar.gz esm4_tier1_antwater.friver.ocean_monthly.tar.gz esm4_tier1_antwater.heat_content_surfwater.ocean_monthly.tar.gz esm4_tier1_antwater.hfds.ocean_monthly.tar.gz esm4_tier1_antwater.hflso.ocean_monthly.tar.gz esm4_tier1_antwater.hfsifrazil.ocean_monthly.tar.gz esm4_tier1_antwater.hfsso.ocean_monthly.tar.gz esm4_tier1_antwater.lsrc.ice_monthly.tar.gz esm4_tier1_antwater.mlotst.ocean_monthly.tar.gz esm4_tier1_antwater.precip.atmos_level_monthly.tar.gz esm4_tier1_antwater.prlq.ocean_monthly.tar.gz esm4_tier1_antwater.prsn.ocean_monthly.tar.gz esm4_tier1_antwater.rlntds.ocean_monthly.tar.gz esm4_tier1_antwater.rsntds.ocean_monthly.tar.gz esm4_tier1_antwater.sfdsi.ocean_monthly.tar.gz esm4_tier1_antwater.siconc.ice_monthly.tar.gz esm4_tier1_antwater.sithick.ice_monthly.tar.gz esm4_tier1_antwater.siu.ice_monthly.tar.gz esm4_tier1_antwater.siv.ice_monthly.tar.gz esm4_tier1_antwater.sivol.ice_monthly.tar.gz esm4_tier1_antwater.slp.atmos_level_monthly.tar.gz esm4_tier1_antwater.snowfl.ice_monthly.tar.gz esm4_tier1_antwater.so.ocean_monthly_z.tar.gz esm4_tier1_antwater.static_fields.tar.gz esm4_tier1_antwater.tauuo.ocean_monthly.tar.gz esm4_tier1_antwater.tauvo.ocean_monthly.tar.gz esm4_tier1_antwater.temp.atmos_level_monthly.tar.gz esm4_tier1_antwater.thetao.ocean_monthly_z.tar.gz esm4_tier1_antwater.t_ref.atmos_level_monthly.tar.gz esm4_tier1_antwater.ucomp.atmos_level_monthly.tar.gz esm4_tier1_antwater.umo.ocean_monthly_z.tar.gz esm4_tier1_antwater.uo.ocean_monthly_z.tar.gz esm4_tier1_antwater.u_ref.atmos_level_monthly.tar.gz esm4_tier1_antwater.vcomp.atmos_level_monthly.tar.gz esm4_tier1_antwater.vmo.ocean_monthly_z.tar.gz esm4_tier1_antwater.volcello.ocean_monthly_z.tar.gz esm4_tier1_antwater.vo.ocean_monthly_z.tar.gz esm4_tier1_antwater.v_ref.atmos_level_monthly.tar.gz esm4_tier1_antwater.wfo.ocean_monthly_complete.tar.gz esm4_tier1_antwater.zos.ocean_monthly.tar.g

Representation of Southern Ocean Properties across Coupled Model Intercomparison Project Generations: CMIP3 to CMIP6

International audienceThe air–sea exchange of heat and carbon in the Southern Ocean (SO) plays an important role in mediating the climate state. The dominant role the SO plays in storing anthropogenic heat and carbon is a direct consequence of the unique and complex ocean circulation that exists there. Previous generations of climate models have struggled to accurately represent key SO properties and processes that influence the large-scale ocean circulation. This has resulted in low confidence ascribed to twenty-first-century projections of the state of the SO from previous generations of models. This analysis provides a detailed assessment of the ability of models contributed to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to represent important observationally based SO properties. Additionally, a comprehensive overview of CMIP6 performance relative to CMIP3 and CMIP5 is presented. CMIP6 models show improved performance in the surface wind stress forcing, simulating stronger and less equatorward-biased wind fields, translating into an improved representation of the Ekman upwelling over the Drake Passage latitudes. An increased number of models simulate an Antarctic Circumpolar Current (ACC) transport within observational uncertainty relative to previous generations; however, several models exhibit extremely weak transports. Generally, the upper SO remains biased warm and fresh relative to observations, and Antarctic sea ice extent remains poorly represented. While generational improvement is found in many metrics, persistent systematic biases are highlighted that should be a priority during model development. These biases need to be considered when interpreting projected trends or biogeochemical properties in this region

Novel mutations in neuroendocrine carcinoma of the breast: possible therapeutic targets

Abstract: Primary neuroendocrine carcinoma of the breast is a rare variant, accounting for only 2% to 5% of diagnosed breast cancers, and may have relatively aggressive behavior. Mutational profiling of invasive ductal breast cancers has yielded potential targets for directed cancer therapy, yet most studies have not included neuroendocrine carcinomas. In a tissue microarray screen, we found a 2.4% prevalence (9/372) of neuroendocrine breast carcinoma, including several with lobular morphology. We then screened primary or metastatic neuroendocrine breast carcinomas (excluding papillary and mucinous) for mutations in common cancer genes using polymerase chain reaction-mass spectroscopy (643 hotspot mutations across 53 genes), or semiconductor-based next-generation sequencing analysis (37 genes). Mutations were identified in 5 of 15 tumors, including 3 with PIK3CA exon 9 E542K mutations, 2 of which also harbored point mutations in FGFR family members (FGFR1 P126S, FGFR4 V550M). Single mutations were found in each of KDR (A1065T) and HRAS (G12A). PIK3CA mutations are common in other types of breast carcinoma. However, FGFR and RAS family mutations are exceedingly rare in the breast cancer literature. Likewise, activating mutations in the receptor tyrosine kinase KDR (VEGFR2) have been reported in angiosarcomas and non-small cell lung cancers; the KDR A1065T mutation is reported to be sensitive to VEGFR kinase inhibitors, and fibroblast growth factor receptor inhibitors are in trials. Our findings demonstrate the utility of broad-based genotyping in the study of rare tumors such as neuroendocrine breast cancer