Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0

Sea level rise (SLR) is one of the major impacts of global warming; it will threaten coastal populations, infrastructure, and ecosystems around the globe in coming centuries. Well-constrained sea level projections are needed to estimate future losses from SLR and benefits of climate protection and adaptation. Process-based models that are designed to resolve the underlying physics of individual sea level drivers form the basis for state-of-the-art sea level projections. However, associated computational costs allow for only a small number of simulations based on selected scenarios that often vary for different sea level components. This approach does not sufficiently support sea level impact science and climate policy analysis, which require a sea level projection methodology that is flexible with regard to the climate scenario yet comprehensive and bound by the physical constraints provided by process-based models. To fill this gap, we present a sea level model that emulates global-mean long-term process-based model projections for all major sea level components. Thermal expansion estimates are calculated with the hemispheric upwelling-diffusion ocean component of the simple carbon-cycle climate model MAGICC, which has been updated and calibrated against CMIP5 ocean temperature profiles and thermal expansion data. Global glacier contributions are estimated based on a parameterization constrained by transient and equilibrium process-based projections. Sea level contribution estimates for Greenland and Antarctic ice sheets are derived from surface mass balance and solid ice discharge parameterizations reproducing current output from ice-sheet models. The land water storage component replicates recent hydrological modeling results. For 2100, we project 0.35 to 0.56m (66% range) total SLR based on the RCP2.6 scenario, 0.45 to 0.67m for RCP4.5, 0.46 to 0.71m for RCP6.0, and 0.65 to 0.97m for RCP8.5. These projections lie within the range of the latest IPCC SLR estimates. SLR projections for 2300 yield median responses of 1.02m for RCP2.6, 1.76m for RCP4.5, 2.38m for RCP6.0, and 4.73m for RCP8.5. The MAGICC sea level model provides a flexible and efficient platform for the analysis of major scenario, model, and climate uncertainties underlying long-term SLR projections. It can be used as a tool to directly investigate the SLR implications of different mitigation pathways and may also serve as input for regional SLR assessments via component-wise sea level pattern scaling

Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0

Sea level rise (SLR) is one of the major impacts of global warming; it will threaten coastal populations, infrastructure, and ecosystems around the globe in coming centuries. Well-constrained sea level projections are needed to estimate future losses from SLR and benefits of climate protection and adaptation. Process-based models that are designed to resolve the underlying physics of individual sea level drivers form the basis for state-of-the-art sea level projections. However, associated computational costs allow for only a small number of simulations based on selected scenarios that often vary for different sea level components. This approach does not sufficiently support sea level impact science and climate policy analysis, which require a sea level projection methodology that is flexible with regard to the climate scenario yet comprehensive and bound by the physical constraints provided by process-based models. To fill this gap, we present a sea level model that emulates global-mean long-term process-based model projections for all major sea level components. Thermal expansion estimates are calculated with the hemispheric upwelling-diffusion ocean component of the simple carbon-cycle climate model MAGICC, which has been updated and calibrated against CMIP5 ocean temperature profiles and thermal expansion data. Global glacier contributions are estimated based on a parameterization constrained by transient and equilibrium process-based projections. Sea level contribution estimates for Greenland and Antarctic ice sheets are derived from surface mass balance and solid ice discharge parameterizations reproducing current output from ice-sheet models. The land water storage component replicates recent hydrological modeling results. For 2100, we project 0.35 to 0.56m (66% range) total SLR based on the RCP2.6 scenario, 0.45 to 0.67m for RCP4.5, 0.46 to 0.71m for RCP6.0, and 0.65 to 0.97m for RCP8.5. These projections lie within the range of the latest IPCC SLR estimates. SLR projections for 2300 yield median responses of 1.02m for RCP2.6, 1.76m for RCP4.5, 2.38m for RCP6.0, and 4.73m for RCP8.5. The MAGICC sea level model provides a flexible and efficient platform for the analysis of major scenario, model, and climate uncertainties underlying long-term SLR projections. It can be used as a tool to directly investigate the SLR implications of different mitigation pathways and may also serve as input for regional SLR assessments via component-wise sea level pattern scaling

Southern Hemisphere subtropical drying as a transient response to warming

Climate projections1–3 and observations over recent decades4,5 indicate that precipitation in subtropical latitudes declines in response to anthropogenic warming, with significant implications for food production and population sustainability. However, this conclusion is derived from emissions scenarios with rapidly increasing radiative forcing to the year 21001,2, which may represent very different conditions from both past and future ‘equilibrium’ warmer climates. Here, we examine multi-century future climate simulations and show that in the Southern Hemisphere subtropical drying ceases soon after global temperature stabilizes. Our results suggest that twenty-first century Southern Hemisphere subtropical drying is not a feature of warm climates per se, but is primarily a response to rapidly rising forcing and global temperatures, as tropical sea-surface temperatures rise more than southern subtropical sea-surface temperatures under transient warming. Subtropical drying may therefore be a temporary response to rapid warming: as greenhouse gas concentrations and global temperatures stabilize, Southern Hemisphere subtropical regions may experience positive precipitation trends

A practical indicator for surface ocean heat and freshwater buoyancy fluxes and its application to the NCEP reanalysis data

The buoyancy flux at the air/sea interface plays a key role in water mass transformation and mixing as it modifies surface water density and in turn drives overturning and enhances stratification. It is the interplay of these two independent heat and freshwater buoyancy flux components that is of central importance when analysing mechanisms of the ocean/atmosphere interaction. Here, a diagnostic quantity (ΘB) is presented that allows to capture the relative contribution of both components on the buoyancy flux in one single quantity. Using NCEP reanalysis of heat and freshwater fluxes (1948–2009) demonstrates that ΘB is a convenient tool to analyse both the temporal and spatial variability of their corresponding buoyancy fluxes. For the global ocean the areal extent of buoyancy gain and loss regions changed by 10%, with the largest extent of buoyancy gain during the 1970–1990 period. In the subpolar North Atlantic, and likewise in the South Pacific, decadal variability in freshwater flux is pronounced and, for the latter region, takes control over the total buoyancy flux since the 1980s. Some of the areal extent time series show a significant correlation with large-scale climate indices

Supporting data for "Synthesizing long-term sea level rise projections - the MAGICC sea level model v2.0"

This is supporting data and configuration information to reproduce results from the MAGICC sea level model (DOI: 10.5281/zenodo.572395) presented in Nauels et al. (2017), using version 7.0 beta of the simple climate carbon-cycle model MAGICC (Meinshausen et al. 2011). For a compiled or source code version of MAGICC including the sea level model (git hash: c5c4e05518ed99f2bd53e2c6e68d238bbd6f17ec), please contact [email protected]. MAGICC input data and CMIP5 reference datasets are provided as a zip-file. REFERENCE DATASETS For MAGICC version 7.0 beta, the ocean model has been updated to emulate CMIP5 ocean temperatures and thermal expansion. The calibration results shown in Nauels et al. (2017) are based on potential ocean temperature (thetao) and thermal expansion (zostoga) reference datasets that are provided the 'data' directory. Reference datasets for the other sea level components have to be requested from the authors of the corresponding studies (Marzeion et al. 2014, Fettweis et al. 2013, Nick et al. 2013, Ligtenberg 2013, Levermann 2014). All relevant CMIP5 MAGICC input (.IN) is provided in the 'run' directory. MAGICC MODEL CONFIGURATION To customize a MAGICC run, namelist entries have to be modified in the configuration file 'MAGCFG_USER.CFG'. In order to select a CMIP5 model specific MAGICC ocean calibration, the model setup has to be called with the 'FILE_TUNINGMODEL_XX' entry, e.g. 'OCNTUNE_CCSM4' for the CCSM4 model. Automatically, the corresponding initial ocean temperature profile and model specific ocean layer area fractions will be applied. For prescribing the respective surface air temperatures, the namelist flag 'CORE_PRESCRTEMP_APPLY' has to be set to 1, with the model specific temperature dataset defined by 'FILE_PRESCR_SURFACETEMP', e.g. 'CORE_PRESCRTEMP_CMIP5_CCSM4_RCP85.IN'. The following MAGICC namelist entries have to be adapted in order to fully reproduce CMIP5 consistent results presented in Nauels et al. (2017): [...] e.g. FILE_TUNINGMODEL_1 = "OCNTUNE_CCSM4", [...] CORE_SWITCH_TEMPADJUST_OCN2ATM = 1, CORE_SWITCH_OCN_TEMPPROFILE = 2, CORE_SWITCH_OCN_AREAFACTOR = 1, CORE_PRESCRTEMP_APPLY = 1, e.g. FILE_PRESCR_SURFACETEMP = "CORE_PRESCRTEMP_CMIP5_CCSM4_RCP85.IN", [...] OUT_TEMPERATURE = 1, OUT_TEMPOCEANLAYERS = 1, OUT_SEALEVEL = 1, OUT_PARAMETERS = 1, [...] OUT_ASCII_BINARY = "ASCII", [...] MAGICC output is stored in the 'out' directory. Depending on the flag 'OUT_ASCII_BINARY', either ASCII or BINARY files are produced for the output parameters which are set to 1 in the namelist, e.g. 'OUT_SEALEVEL = 1'. MAGICC SEA LEVEL MODEL LICENSE This source code of the MAGICC sea level model is distributed under a Creative Commons Attribution-ShareAlike 4.0 license (https://creativecommons.org/licenses/by-sa/4.0/legalcode). MAGICC PARENT MODEL LICENSES The MAGICC executable is provided under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported license (https://creativecommons.org/licenses/by-nc-sa/3.0/). The MAGICC source code is available under a separate license agreement. Any derivatives have to be fed back to the MAGICC developers, so that users of future MAGICC versions can have the benefit of applying the model alterations, enhancements etc. Furthermore, we would like you to provide feedback, bug reports and development suggestions. REFERENCES Fettweis, X., Franco, B., Tedesco, M., van Angelen, J. H., Lenaerts, J. T. M., van den Broeke, M. R., and Gallée, H.: Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR, The Cryosphere, 7, 469–489, 2013. Levermann, A.,Winkelmann, R., Nowicki, S., Fastook, J. L., Frieler, K., Greve, R., Hellmer, H. H., Martin, M. A., Meinshausen, M., Mengel, M., Payne, A. J., Pollard, D., Sato, T., Timmermann, R., Wang, W. L., and Bindschadler, R. A.: Projecting Antarctic ice discharge using response functions from SeaRISE ice-sheet models, Earth Syst. Dynam., 5, 271–293, 2014. Ligtenberg, S. R. M., van de Berg, W. J., van den Broeke, M. R., Rae, J. G. L., and van Meijgaard, E.: Future surface mass balance of the Antarctic ice sheet and its influence on sea level change, simulated by a regional atmospheric climate model, Climate Dynamics, 41, 867–884, 2013. Meinshausen, M., Raper, S. C. B., and Wigley, T. M. L.: Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration, Atmospheric Chemistry and Physics, 11, 1417–1456, 2011. Nauels, A., Meinshausen, M., Mengel, M., Lorbacher, K., and Wigley, T. M. L.: Synthesizing long-term sea level rise projections – the MAGICC sea level model v2.0, Geosci. Model Dev., 2017. Nick, F. M., Vieli, A., Andersen, M. L., Joughin, I., Payne, A., Edwards, T. L., Pattyn, F., and van de Wal, R. S. W.: Future sea-level rise from Greenland’s main outlet glaciers in a warming climate, Nature, 497, 235–238, 2013