During the last four decades, global warming has intensified extreme precipitation events in the Midwestern United States (defined here as the region covering Illinois, Indiana, Ohio and Kentucky), leading to increased risks to human life, property, and infrastructure. To enable climate change adaptation and resilience across various economic and social sectors in this region, updated information about future climate changes, specifically at finer spatial scales, is essential. Leveraging a new 150-year dynamical downscaling dataset at convection-permitting resolution, this study introduces a framework to construct the projected future intensity-duration-frequency (IDF) curves of heavy precipitation, which are prominent tools for infrastructure design and water resources management. This framework generates IDF curves at both sub-daily and multi-day duration utilizing hourly in situ observations as well as quantile-based statistical techniques in bias-correction and return levels selection. The assumption of non-stationarity in the distribution parameter fitting process is also implemented in this workflow. Compared to historical IDF curves for 1980-2022, future projected IDF curves for 2058-2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicate an average intensity increase of approximately 20% and 30%, respectively, across 74 stations and all four seasons of interest. The frequency of future extreme precipitation events in the Midwest region is also projected to double. Furthermore, current results reveal spatial heterogeneity of future trends across stations owing to the high-resolution input dataset.

Feedback control algorithms, an important tool in climate intervention strategy design, are widely used in stratospheric aerosol injection (SAI) simulations but have never been implemented for marine cloud brightening (MCB). Using the Community Earth System Model (CESM2), we present the first simulations of feedback control-regulated MCB. Our controller, which regulates global mean temperature (T0) by varying the area of MCB coverage over time, successfully maintains the desired T0 of 1.5°C above the preindustrial in the SSP2-4.5 global warming scenario comparably to a contemporary SAI controller. After 35 years of intervention, the surface temperature response when MCB has been gradually ramped up over time in this way is similar to a constant intervention with similar global mean temperature (including strong regional heterogeneity), but system memory may cause differences in Arctic sea ice and the Atlantic Meridional Overturning Circulation (AMOC).

Earth System Models (ESMs) are essential tools for understanding the interaction of the human and Earth systems. One key application of these models is studying extreme weather events, such as heat waves or high intensity precipitation events, which have significant socioeconomic consequences. However, the computational demands of running a sufficient number of simulations to robustly characterize expected changes in these hazards, and therefore provide a strong basis to analyze the ensuing risks, are often prohibitive. In this paper we demonstrate that diffusion models – a class of generative deep learning models – can effectively emulate the spatio-temporal trends of ESM daily output. Trained on a handful of runs, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input and is capable of producing daily values of temperature and precipitation that have statistical characteristics close to the ESM output. This approach requires only a small fraction of the computational resources that would be needed to run a large ensemble under any scenario of interest. We evaluate model behavior over a range of scenarios, time horizons and two ESMs, using a number of extreme metrics, including ones that have been long established in the climate modeling and analysis community. Our results show that the samples produced by DiffESM closely matches the spatio-temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.

Previous modeling studies indicate that even though marine cloud brightening under a susceptibility-based strategy is effective in reducing the global average surface temperature, it triggers a La Niña-like sea-surface temperature response with cooling mostly confined within lower latitudes. Here we explore a different cloud seeding strategy involving seeding of regions with low susceptibility. Simulations with the Community Earth System Model, version 2 (CESM2) reveal that because the regional forcing is weaker and more widespread, cooling is more evenly distributed over the globe. This new strategy also does not result in the La Niña-like state seen in the other strategies.

The efficiency of marine cloud brightening in cooling Earth’s surface temperature is investigated by using a medium ensemble of simulations with the Community Earth System Model version 2 (CESM2). Various cloud seeding schemes based on susceptibility are examined to determine what area extent will be required to induce 1oC cooling under SSP2-4.5. The results indicate that cloud seeding over 5% of the ocean area is capable of achieving this goal. Under this seeding scheme, cloud seeding is mainly deployed over lower latitudes where strong surface temperature and precipitation responses are induced. The simulations also reveal that the 5% cloud seeding scheme induces an overall reduction in global precipitation, with an increase over land and a decrease over the ocean.

The specifics of the simulated injection choices in the case of Stratospheric Aerosol Injections (SAI) are part of the crucial context necessary for meaningfully discussing the impacts that a deployment of SAI would have on the planet. One of the main choices is the desired amount of cooling that the injections are aiming to achieve. Previous SAI simulations have usually either simulated a fixed amount of injection, resulting in a fixed amount of warming being offset, or have specified one target temperature, so that the amount of cooling is only dependent on the underlying trajectory of greenhouse gases. Here, we use three sets of SAI simulations achieving different amounts of global mean surface cooling while following a middle-of-the-road greenhouse gas emission trajectory: one SAI scenario maintains temperatures at 1.5ºC above preindustrial levels (PI), and two other scenarios which achieve additional cooling to 1.0ºC and 0.5ºC above PI. We demonstrate that various surface impacts scale proportionally with respect to the amount of cooling, such as global mean precipitation changes, changes to the Atlantic Meridional Overturning Circulation (AMOC) and to the Walker Cell. We also highlight the importance of the choice of the baseline period when comparing the SAI responses to one another and to the greenhouse gas emission pathway. This analysis leads to policy-relevant discussions around the concept of a reference period altogether, and to what constitutes a relevant, or significant, change produced by SAI.

Owing to increasing greenhouse gas emissions, the West Antarctic Ice Sheet as well as a few subglacial basins in East Antarctica are vulnerable to rapid ice loss in the upcoming decades and centuries, respectively. This study examines the effectiveness of using Stratospheric Aerosol Injection (SAI) that minimizes global mean temperature (GMT) change to slow projected 21st century Antarctic ice loss. We use eleven different SAI cases which vary by the latitudinal location(s) and the amount(s) of the injection(s) to examine the climatic response near Antarctica in each case as compared to the reference climate at the turn of the last century. We demonstrate that injecting at a single latitude in the northern hemisphere or at the Equator increases Antarctic shelf ocean temperatures pertinent to ice shelf basal melt, while injecting only in the southern hemisphere minimizes this temperature change. We use these results to analyze the results of more complex multi-latitude injection strategies that maintain GMT at or below 1.5°C above the pre-industrial. All these cases will slow Antarctic ice loss relative to the mid-to-late 21st century SSP2-4.5 emissions pathway. Yet, to avoid a GMT threshold estimated by previous studies pertaining to rapid West Antarctic ice loss (~1.5°C above the pre-industrial), our study suggests SAI would need to cool below this threshold and predominately inject at low southern hemisphere latitudes. These results highlight the complexity of factors impacting the Antarctic response to SAI and the critical role of the injection strategy in preventing future ice loss.

The impacts of Stratospheric Aerosol Injection (SAI) on the atmosphere and surface climate depend on when and where the sulfate aerosol precursors are injected, as well as on how much surface cooling is to be achieved. We use a set of CESM2(WACCM6) SAI simulations achieving three different levels of global mean surface cooling and demonstrate that unlike some direct surface climate impacts driven by the reflection of solar radiation by sulfate aerosols, the SAI-induced changes in the high latitude circulation and ozone are more complex and could be non-linear. This manifests in our simulations by disproportionally larger Antarctic springtime ozone loss, significantly larger intra-ensemble spread of the Arctic stratospheric jet and ozone responses, and non-linear impacts on the extratropical modes of surface climate variability under the strongest-cooling SAI scenario compared to the weakest one. These potential non-linearities may add to uncertainties in projections of regional surface impacts under SAI.

By injecting SO2 into the stratosphere at four latitudes (30°, 15° N/S), it might be possible not only to reduce global mean surface temperature but also to minimize changes in the equator-to-pole and inter-hemispheric gradients of temperature, further reducing some of the impacts arising from climate change relative to equatorial injection. This can happen only if the aerosols are transported to higher latitudes by the stratospheric circulation, ensuring that a greater part of the solar radiation is reflected back to space at higher latitudes, compensating for the reduced sunlight. However, the stratospheric heating produced by these aerosols modifies the circulation and strengthens the stratospheric polar vortex which acts as a barrier to the transport of air toward the poles. We show how the heating results in a feedback where increasing injection rates lead to stronger high-latitudinal transport barriers. This implies a potential limitation in the high-latitude aerosol burden and subsequent cooling.

Stratospheric aerosol injection (SAI) can provide global cooling by adding aerosols to the lower stratosphere, and thus is considered as a possible supplement to emission reduction. Previous studies have shown that injecting aerosols at different latitude(s) and season(s) can lead to differences in regional surface climate, and there are at least three independent degrees of freedom (DOF) that can be used to simultaneously manage three different climate goals. To understand the fundamental limits of how well SAI might compensate for anthropogenic climate change, we need to know the possible surface climate responses to SAI by evaluating the SAI design space. This research work quantifies the number of meaningfully-independent DOFs of the SAI design space. This number of meaningfully-independent DOF depends on both the climate metrics that we care about and the amount of cooling. From the available simulation data of different SAI strategies, we observe that between surface air temperature and precipitation, surface air temperature dominates the change of surface climate. The number of injection choices that produce detectably different surface temperature is more than the number of injection choices that produce detectably different precipitation. At low levels of cooling, only a small set of injection choices yield detectably different surface climate responses. As more cooling is needed, more injection choices produce detectably different surface climate. For a cooling level of 1-2C, we find that there are likely between 6 and 12 DOFs. This reveals new opportunities for exploring alternate SAI designs with different distributions of climate impacts and evaluating the underlying trade-offs between different climate goals.

Deliberately blocking out a small portion of the incoming solar radiation would cool the climate. One such approach would be injecting SO$_2$ into the stratosphere, which would produce sulfate aerosols that would remain in the atmosphere for 1–3 years, reflecting part of the incoming shortwave radiation. This would not affect the climate the same way as increased greenhouse gas (GHG) concentrations, leading to residual differences when a GHG increase is offset by stratospheric sulfate geoengineering. Many climate model simulations of geoengineering have used a uniform reduction of the incoming solar radiation as a proxy for stratospheric aerosols, both because many models are not designed to adequately capture relevant stratospheric aerosol processes, and because a solar reduction has often been assumed to capture the most important differences between how stratospheric aerosols and GHG would affect the climate. Here we show that dimming the sun does not produce the same surface climate effects as simulating aerosols in the stratosphere. By more closely matching the spatial pattern of solar reduction to that of the aerosols, some improvements in this idealized representation are possible, with further improvements if the stratospheric heating produced by the aerosols is included. This is relevant both for our understanding of the physical mechanisms driving the changes observed in stratospheric sulfate geoengineering simulations, and in terms of the relevance of impact assessments that use a uniform solar dimming.

Stratospheric aerosol geoengineering focused on the Arctic could substantially reduce local and worldwide impacts of anthropogenic global warming. Because the Arctic receives little sunlight during the winter, stratospheric aerosols present in the winter at high latitudes have little impact on the climate, whereas stratospheric aerosols present during the summer achieve larger changes in radiative forcing. Injecting SO2 in the spring leads to peak aerosol optical depth (AOD) in the summer. We demonstrate that spring injection produces approximately twice as much summer AOD as year-round injection and restores approximately twice as much September sea ice, resulting in less increase in stratospheric sulfur burden, stratospheric heating, and stratospheric ozone depletion per unit of sea ice restored. We also find that differences in AOD between different seasonal injection strategies are small compared to the difference between annual and spring injection.