Rune Graversen’s research while affiliated with UiT The Arctic University of Norway and other places

Large volcanic eruptions strongly influence the internal variability of the climate system. Reliable estimates of the volcanic eruption response as simulated by climate models are needed to reconstruct past climate variability. Yet, the ability of models to represent the response to both single‐eruption events and a combination of eruptions remains uncertain. We use the Community Earth System Model version 2 along with the Whole Atmosphere Community Climate Model version 6, known as CESM2(WACCM6), to study the global‐mean surface temperature (GMST) response to idealized single volcano eruptions at the equator, ranging in size from Mt. Pinatubo‐type events to supereruptions. Additionally, we simulate the GMST response to double‐eruption events with eruption separations of a few years. For large idealized eruptions, we demonstrate that double‐eruption events separated by 4 years combine linearly in terms of GMST response. In addition, the temporal development is similar across all single volcanic eruptions injecting at least 400 Tg SO2 $\left({\mathrm{S}\mathrm{O}}_{2}\right)$ into the atmosphere. Because only a few eruptions in the past millennium occurred within 4 years of a previous eruption, we assume that the historical record can be represented as a superposition of single‐eruption events. Hence, we employ a deconvolution method to estimate a nonparametric historical GMST response pulse function for volcanic eruptions, based on climate simulation data from 850 to 1850 taken from a previous study. By applying the estimated GMST response pulse function, we can reconstruct most of the underlying historical GMST signal. Furthermore, the GMST response is significantly perturbed for at least 7 years following eruptions.

Volcanic eruptions cause climate cooling due to the reflection of solar radiation by emitted and subsequently produced aerosols. The climate effect of an eruption may last for about a decade and is nonlinearly tied to the amount of injected SO2 ${\text{SO}}_{2}$ from the eruption. We investigate the climatic effects of volcanic eruptions, ranging from Mt. Pinatubo‐sized events to supereruptions. The study is based on ensemble simulations in the Community Earth System Model Version 2 (CESM2) climate model applying the Whole Atmosphere Community Climate Model Version 6 (WACCM6) atmosphere model, using a coupled ocean and fixed sea surface temperature setting. Our analysis focuses on the impact of different levels of SO2 ${\text{SO}}_{2}$ injections on stratospheric aerosol optical depth (SAOD), effective radiative forcing (ERF), and global mean surface temperature (GMST) anomalies. We uncover a notable time‐dependent decrease in aerosol forcing efficiency (ERF normalized by SAOD) for all eruption SO2 ${\text{SO}}_{2}$ levels during the first posteruption year. In addition, it is revealed that the largest eruptions investigated in this study, including several previous supereruption simulations, provide peak ERF anomalies bounded at −65Wm−2 ${-}65\,\mathrm{W}\,{\mathrm{m}}^{-2}$. Further, a close linear relationship between peak GMST and ERF effectively bounds the GMST anomaly to, at most, approximately −10K ${-}10\,\mathrm{K}$. This is consistent across several previous studies using different climate models.

We investigate the climatic effects of volcanic eruptions spanning from Mt.\ Pinatubo-sized events to super-volcanoes. The study is based on ensemble simulations in the Community Earth System Model Version 2 (CESM2) climate model using the Whole Atmosphere Community Climate Model Version 6 (WACCM6) atmosphere model. Our analysis focuses on the impact of different \ce{SO2}-amount injections on stratospheric aerosol optical depth (AOD), effective radiative forcing (RF), and global temperature anomalies. Unlike the traditional linear models used for smaller eruptions, our results reveal a non-linear relationship between RF and AOD for larger eruptions. We also uncover a notable time-dependent decrease in aerosol forcing efficiency across all eruption magnitudes during the first post-eruption year. In addition, the study reveals that larger as compared to medium-sized eruption events produce a delayed and sharper peak in AOD, and a longer-lasting temperature response while the time evolution of RF remains similar between the two eruption types. When including the results of previous studies, we find that relating \ce{SO2} to any other parameter is inconsistent across models compared to the relationships between AOD, RF, and temperature anomaly. Thus, we expect the largest uncertainty in model codes to relate to the chemistry and physics of \ce{SO2} evolution. Finally, we find that the peak RF approaches a limiting value, and that the peak temperature response follows linearly, effectively bounding the temperature anomaly to at most \sim\SI{-12}{\kelvin}.

Numerical climate model simulations suggest that global warming is enhanced or hampered by the spatial pattern of the warming itself. This phenomenon is known as the “pattern effect” and has in recent years become the most promising explanation for the change over time of climate sensitivity in climate models. Under historical global warming, different patterns of surface-temperature change have emerged, notably a yet unexplained cooling in the Southern Ocean and the East Pacific. Historical climate model simulations notoriously fail to reproduce this cooling, which may contribute to the deviation of the simulated global-mean warming from the observed record. Here we qualitatively investigate the potential impact of historical and other surface-temperature pattern changes by changing the ocean heat transport convergence (Q-flux) in a slab-ocean model. The Q-flux changes are always implemented such that in the global mean they impose no net forcing. Consistent with earlier studies we find that the impact of a negative Q-flux change in the Southern Ocean has a stronger effect than in other regions because of a feedback loop between sea-surface temperatures (SSTs) and clouds in the Southern Ocean and the stably stratified regions in the tropics. The SST-cloud feedback loop facilitates the expansion of the Antarctic sea ice, indeed taking the model into a Snowball-Earth state. The intensity of this effect is found to be model dependent, especially due to differences in the cloud parametrisation. In experiments with deactivated sea ice the impact of the negative Q-flux change is much weaker.

We review how the international modelling community, encompassing Integrated Assessment models, global and regional Earth system and climate models, and impact models, have worked together over the past few decades, to advance understanding of Earth system change and its impacts on society and the environment, and support international climate policy. We then recommend a number of priority research areas for the coming ~6 years (i.e. until ~2030), a timescale that matches a number of newly starting international modelling activities and encompasses the IPCC 7th Assessment Report (AR7) and the 2nd UNFCCC Global Stocktake. Progress in these areas will significantly advance our understanding of Earth system change and its impacts and increase the quality and utility of science support to climate policy. We emphasize the need for continued improvement in our understanding of, and ability to simulate, the coupled Earth system and the impacts of Earth system change. There is an urgent need to investigate plausible pathways and emission scenarios that realize the Paris Climate Targets, including pathways that overshoot the 1.5 °C and 2 °C targets, before later returning to them. Earth System models (ESMs) need to be capable of thoroughly assessing such warming overshoots, in particular, the efficacy of negative CO2 emission actions in reducing atmospheric CO2 and driving global cooling. An improved assessment of the long-term consequences of stabilizing climate at 1.5 °C or 2 °C above pre-industrial temperatures is also required. We recommend ESMs run overshoot scenarios in CO2-emission mode, to more fully represent coupled climate - carbon cycle feedbacks. Regional downscaling and impact models should also use forcing data from these simulations, so impact and regional climate projections are as realistic as possible. An accurate simulation of the observed record remains a key requirement of models, as does accurate simulation of key metrics, such as the Effective Climate Sensitivity. For adaptation, improved guidance on potential changes in climate extremes and the modes of variability these extremes develop in, is a key demand. Such improvements will most likely be realized through a combination of increased model resolution and improvement of key parameterizations. We propose a deeper collaboration across modelling efforts targeting increased process realism and coupling, enhanced model resolution, parameterization improvement, and data-driven Machine Learning methods. With respect to sampling future uncertainty, increased collaboration between approaches that emphasize large model ensembles and those focussed on statistical emulation is required. We recommend increased attention is paid to High Impact Low Likelihood (HILL) outcomes. In particular, the risk and consequences of exceeding critical tipping points during a warming overshoot. For a comprehensive assessment of the impacts of Earth system change, including impacts arising directly from specific mitigation actions, it is important detailed, disaggregated information from the Integrated Assessment Models (IAMs) used to generate future scenarios is available to impact models. Conversely, methods need to be developed to incorporate potential future societal responses to the impacts of Earth system change into scenario development. Finally, the new models, simulations, data, and scientific advances, proposed in this article will not be possible without long-term development and maintenance of a robust, globally connected infrastructure ecosystem. This system must be easily accessible and useable across all modelling communities and across the world, allowing the global research community to be fully engaged in developing and delivering new scientific knowledge to support international climate policy.

Space-borne synthetic aperture radar (SAR) observations provide broad coverage of high-resolution snapshots of the sea surface conditions in polar regions. However, their potential has not yet been fully harnessed for meteorological applications. For instance, standard methods for SAR wind-vector retrieval rely on wind direction inputs from numerical weather prediction models, which hampers the high-resolution capabilities of SAR wind retrievals and the use of these in data assimilation. A recently proposed SAR-only wind-vector retrieval method, that uses SAR information more exhaustively than standard methods do, is compared to in situ ship observations and is found to perform similarly to a standard method under average wind conditions at open sea. However, in coastal regions, at high wind speeds, and in complex meteorological conditions this new application outperforms the standard method. It is concluded here that wind fields obtained from the SAR-only wind-vector retrieval are suitable for data assimilation in high-resolution weather prediction models, since they can provide model-independent, high-quality, and high-resolution observational wind information. In addition, a simple interpolation technique is introduced to substitute land in the calibration procedure of the Doppler centroid anomaly for open-ocean SAR scenes.

Polar warming, ice melt and strong precipitation events are strongly affected by episodic poleward advection of warm and moist air1,2, which, in turn, is linked to variability in poleward moisture transport (PMT)3. However, processes governing regional impacts of PMT as well as long-term trends remain largely unknown. Here we use an ensemble of state-of-the-art global climate models in standardized scenario simulations (1850–2100) to show that both the Arctic and the Antarctic exhibit distinct geographical patterns of PMT-related warming. Specifically, years with high PMT experience considerable warming over subarctic Eurasia and West-Antarctica4, whereas precipitation is distributed more evenly over the polar regions. The warming patterns indicate preferred routes of atmospheric rivers1, which may regionally enhance atmospheric moisture content, cloud cover, and downward longwave radiative heating in years with comparatively high PMT5. Trend-analyses reveal that the link between PMT-variability and regional precipitation patterns will weaken in both polar regions. Even though uncertainties associated with intermodel differences are considerable, the advection of warm and moist air associated with PMT-variability is likely to increasingly cause mild conditions in both polar regions, which in the Arctic will reinforce sea-ice melt. Similarly, the results suggest that warm years in West-Antarctica disproportionally contribute to ice sheet melt6, enhancing the risk of ice-sheet instabilities causing accelerated and sudden sea-level rise.

Numerical climate model simulations suggest that global warming is enhanced or hampered by the spatial pattern of the warming itself. This phenomenon is known as the ``pattern effect'' and has in recent years become the most promising explanation for the change over time of climate sensitivity in climate models. Under historical global warming, different patterns of surface-temperature change have emerged, notably a yet unexplained cooling in the Southern Ocean and the East Pacific. Historical climate model simulations notoriously fail to reproduce this cooling, which may contribute to the deviation of the simulated global-mean warming from the observed record.Here we qualitatively investigate the potential impact of historical and other surface-temperature pattern changes by changing the ocean heat transport convergence (Q-flux) in a slab-ocean model. The Q-flux changes are always implemented such that in the global mean they impose no net forcing. Consistent with earlier studies we find that the impact of a negative Q-flux change in the Southern Ocean has a stronger effect than in other regions because of a feedback loop between sea-surface temperatures (SSTs) and clouds in the Southern Ocean and the stably stratified regions in the tropics. The SST-cloud feedback loop facilitates the expansion of the Antarctic sea ice, indeed taking the model into a Snowball-Earth state. The intensity of this effect is found to be model dependent, especially due to differences in the cloud parametrisation. In experiments with deactivated sea ice the impact of the negative Q-flux change is much weaker.

The climate sensitivity of the Earth and the radiative climate feedback both change over time due to a so-called “pattern effect”, i.e., changing patterns of surface warming. This is suggested by numerical climate model experiments. The Atlantic Meridional Overturning Circulation (AMOC) influences surface warming patterns as it redistributes energy latitudinally. Thus, this ocean circulation may play an important role for climate-feedback change over time. In this study, two groups of members of the Coupled Model Intercomparison Project (CMIP) phases 5 and 6 abrupt4xCO2 experiment are distinguished: one group showing weak and the other strong feedback change over time. It is found that both groups differ significantly in the AMOC response to 4xCO 2 . Therefore, experiments with a slab-ocean model (SOM) with quadrupling of the CO 2 concentration are performed where the AMOC change is mimicked by changing the ocean heat transport. It is found that in the Northern Hemisphere extra-tropics the CMIP model group differences can be qualitatively reproduced by the SOM experiments, indicating that the AMOC plays an important role in setting the surface warming pattern. However, in the tropics and especially in the Southern Hemisphere other explanations are necessary.