Coupled Model Intercomparison Project 5 (CMIP5) simulations of climate following volcanic eruptions

By S. Driscoll, A. Bozzo, L. Gray, A. Robock, Georgiy L. Stenchikov. 2012

285 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/7d2532729e58d7a4faf3648bb5dad8d61362a578

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Citations in the corpus

Assessing the controllability of Arctic sea ice extent by sulfate aerosol geoengineering (2015, background): “Importantly, persistent climate model errors like the failure to simulate the Northern Hemisphere dynamical response to volcanic eruptions [Driscoll et al., 2012] would be captured by an MPC learning process.”
The predictability of the extratropical stratosphere on monthly time‐scales and its impact on the skill of tropospheric forecasts (2015, methodology): “The experiments are constructed in which forecasts of the same periods are made using high-top and low-top models and the resulting differences in forecast skill are attributed to the presence of the full stratosphere in the high-top model. One difficulty with these experiments is that running two m”
On the lack of stratospheric dynamical variability in low‐top versions of the CMIP5 models (2013, unknown): “MRI-CGCM3 is the only model considered here that interactively simulated the stratospheric aerosol distribution and its radiative properties following volcanic eruptions, unlike the other models in which the aerosol distribution and properties are prescribed from observations [Driscoll et al., 2012]”
A signal-to-noise paradox in climate science (2018, background): “It appears as weak signals in ensemble forecasts(20,23,25,26,28,36) in atmosphere-only simulations forced by prescribed ocean conditions(29,38,39,51,55) and in models subjected to changes in radiative forcing.(59,61,62,74,99) While this review cannot provide absolute proof, it summarises a growing b”
Effects of volcanism on tropical variability (2015, methodology): “…for example, each model has a different resolution in the stratosphere, along with a different implementation of volcanic forcing ranging from a modification of the radiative forcing in the atmosphere to an interactive conversion of sulphur dioxide to stratospheric aerosol [Driscoll et al., 2012].”
The Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) : experimental design and forcing input data for CMIP6 (2016, background): “For instance, the largest uncertainties in radiative forcings (Driscoll et al., 2012) and in lower troposphere temperature trends (Santer et al., 2014) from historical CMIP5 simulations occur during periods of strong volcanic activity.”
Annular mode changes in the CMIP5 simulations (2013, result): “Unlike in the CMIP3 models [Miller et al., 2006], no positive NAM response is seen in the CMIP5 models in DJF (Figure 3a), consistent with previous results based on a smaller subset of CMIP5 models [Driscoll et al., 2012].”
An overview of the Earth system science of solar geoengineering (2016, background): “For example, after large volcanic eruptions a warming at high latitudes in the winter is observed but is not reproduced by many of the current models.(94) Thus, simulations to date of the consequences of SAI have been made with models with a number of significant shortcomings resulting in significan”
The effect of volcanic eruptions on global precipitation (2013, methodology): “In contrast, the model ensemble mean shows a significant drying for years 2–3 in NDJFMA and an insignificant drying for years 0–4 in MJJASO and no visible NAO response consistent with findings for CMIP5 models [e.g., Driscoll et al., 2012].”