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At least 1,009 records · Page 56

The Fall and Rise of the Global Climate Model

Abstract Global models are an essential tool for climate projections, but conventional coarse‐resolution atmospheric general circulation models suffer from errors both in their parameterized cloud physics and in their representation of climatically important circulation features. A notable recent study by Terai et al. (2020, https://doi.org/10.1029/2020ms002274) documents a global model capable of reproducing the regime‐based effect of aerosols on cloud liquid water path expected from observational evidence. This may represent a significant advance in cloud process fidelity in global models. Such models can be expected to give a better estimate of the effective radiative forcing of the climate. If this advance in cloud process representation can be matched by advances in the representation of circulation features such as monsoons, then such models may also be able to navigate the complex tangle between spatially heterogeneous aerosol–cloud interactions and regional circulation patterns. This tight link between aerosol and circulation results in anthropogenic perturbations of climate variables of societal importance, such as regional rainfall distributions. Upcoming global models with km‐scale resolution may improve the regional circulation and be able to take advantage of the Terai et al. (2020, https://doi.org/10.1029/2020ms002274) improvement in cloud physics. If so, an era of significantly improved regional climate projection capabilities may soon dawn. If not, then the improvement in cloud physics might spur intensified efforts on problems in model dynamics. Either way, based on the rapid changes in aerosol emissions in the near future, learning to make reliable projections based on biased models is a skill that will not go out of style.

54 ENVIRONMENTAL SCIENCES↗

Ice‐Nucleating Particles That Impact Clouds and Climate: Observational and Modeling Research Needs

Abstract Atmospheric ice‐nucleating particles (INPs) play a critical role in cloud freezing processes, with important implications for precipitation formation and cloud radiative properties, and thus for weather and climate. Additionally, INP emissions respond to changes in the Earth System and climate, for example, desertification, agricultural practices, and fires, and therefore may introduce climate feedbacks that are still poorly understood. As knowledge of the nature and origins of INPs has advanced, regional and global weather, climate, and Earth system models have increasingly begun to link cloud ice processes to model‐simulated aerosol abundance and types. While these recent advances are exciting, coupling cloud processes to simulated aerosol also makes cloud physics simulations increasingly susceptible to uncertainties in simulation of INPs, which are still poorly constrained by observations. Advancing the predictability of INP abundance with reasonable spatiotemporal resolution will require an increased focus on research that bridges the measurement and modeling communities. This review summarizes the current state of knowledge and identifies critical knowledge gaps from both observational and modeling perspectives. In particular, we emphasize needs in two key areas: (a) observational closure between aerosol and INP quantities and (b) skillful simulation of INPs within existing weather and climate models. We discuss the state of knowledge on various INP particle types and briefly discuss the challenges faced in understanding the cloud impacts of INPs with present‐day models. Finally, we identify priority research directions for both observations and models to improve understanding of INPs and their interactions with the Earth System.

54 ENVIRONMENTAL SCIENCES↗

Adjustments to Climate Perturbations—Mechanisms, Implications, Observational Constraints

Since the 5th Assessment Report of the Intergovernmental Panel on Climate Change (AR5) an extended concept of the energetic analysis of climate change including forcings, feedbacks and adjustment processes has become widely adopted. Adjustments are defined as processes that occur in response to the introduction of a climate forcing agent, but that are independent of global-mean surface temperature changes. Most considered are the adjustments that impact the Earth energy budget and strengthen or weaken the instantaneous radiative forcing due to the forcing agent. Some adjustment mechanisms also impact other aspects of climate not related to the Earth radiation budget. Since AR5 and a following description by Sherwood et al., much research on adjustments has been performed and is reviewed here. We classify the adjustment mechanisms into six main categories, and discuss methods of quantifying these adjustments in terms of their potentials, shortcomings and practicality. We furthermore describe aspects of adjustments that act beyond the energetic framework, and we propose new ideas to observe adjustments or to make use of observations to constrain their representation in models. Altogether, the problem of adjustments is now on a robust scientific footing, and better quantification and observational constraint is possible. This allows for improvements in understanding and quantifying climate change.

54 ENVIRONMENTAL SCIENCES↗

Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble

AbstractAssessing uncertainty in future climate projections requires understanding both internal climate variability and external forcing. For this reason, single‐model initial condition large ensembles (SMILEs) run with Earth System Models (ESMs) have recently become popular. Here we present a new 20‐member SMILE with the Energy Exascale Earth System Model version 1 (E3SMv1‐LE), which uses a “macro” initialization strategy choosing coupled atmosphere/ocean states based on inter‐basin contrasts in ocean heat content (OHC). The E3SMv1‐LE simulates tropical climate variability well, albeit with a muted warming trend over the twentieth century due to overly strong aerosol forcing. The E3SMv1‐LE's initial climate spread is comparable to other (larger) SMILEs, suggesting that maximizing inter‐basin ocean heat contrasts may be an efficient method of generating ensemble spread. We also compare different ensemble spread across multiple SMILEs, using surface air temperature and OHC. The Community Earth system Model version 1, the only ensemble which utilizes a “micro” initialization approach perturbing only atmospheric initial conditions, yields lower spread in the first ∼30 years. The E3SMv1‐LE exhibits a relatively large spread, with some evidence for anthropogenic forcing influencing spread in the late twentieth century. However, systematic effects of differing “macro” initialization strategies are difficult to detect, possibly resulting from differing model physics or responses to external forcing. Notably, the method of standardizing results affects ensemble spread: control simulations for most models have either large background trends or multi‐centennial variability in OHC. This spurious disequlibrium behavior is a substantial roadblock to understanding both internal climate variability and its response to forcing.

Stevenson, Samantha↗

Timescale Dependence of the Precipitation Response to CO 2 ‐Induced Warming in Millennial‐Length Climate Simulations

Abstract Previous work has shown that estimates of climate sensitivity vary over time in response to abrupt CO 2 forcing in climate model simulations. The energy fluxes that drive warming in response to increasing CO 2 also influence precipitation, which prompts the question: Does the precipitation response therefore also vary over time? We investigate by examining the response of precipitation to warming forced by greenhouse gases—the hydrological sensitivity—in a set of millennial‐length climate simulations with multiple climate models, Long Run Model Intercomparison Project (LongRunMIP). We compare hydrological sensitivity calculated from three different timescales of the simulations: years 1–20, 21–150, and 151–1000. We show that the hydrological sensitivity lacks a consistent dependence on timescale, in contrast to climate sensitivity. Decomposition of the surface energy budget reveals that the relative muting of the multi‐model mean hydrological sensitivity is driven by surface downwelling shortwave flux.

Him (Kinen) Kao, Wing↗

Application of the AI2 Climate Emulator to E3SMv2's Global Atmosphere Model, With a Focus on Precipitation Fidelity

Abstract Can the current successes of global machine learning‐based weather simulators be generalized beyond 2‐week forecasts to stable and accurate multiyear runs? The recently developed AI2 Climate Emulator (ACE) suggests this is feasible, based upon 10‐year simulations with a network trained on output from a physics‐based global atmosphere model using a grid spacing of approximately 110 km and forced by a repeating annual cycle of sea‐surface temperature. Here we show that ACE, without modification, can be trained to emulate another major atmospheric model, EAMv2, run at a comparable grid spacing for at least 10 years with similarly small climate biases—a prerequisite to wider applicability. With an analysis that combines multiple temporal, spatial, and frequency domain perspectives, we show that ACE faithfully represents the spatiotemporal structure of EAMv2 precipitation and related variables. Finally, we show that a pretrained ACE network is able to adapt to a new global climate model simulation data set with 10 fewer training steps than when starting from random initialization, all while still maintaining low levels of climate bias. Further analysis of these fine‐tuning experiments reveal ACE's intriguing ability to interpolate between distinct global climate models.

Duncan, James P. C.↗

Internal climate variability and projected future regional steric and dynamic sea level rise

Observational evidence points to a warming global climate accompanied by rising sea levels which impose significant impacts on island and coastal communities. Studies suggest that internal climate processes can modulate projected future sea level rise (SLR) regionally. It is not clear whether this modulation depends on the future climate pathways. Here, by analyzing two sets of ensemble simulations from a climate model, we investigate the potential reduction of SLR, as a result of steric and dynamic oceanographic affects alone, achieved by following a lower emission scenario instead of business-as-usual one over the twenty-first century and how it may be modulated regionally by internal climate variability. Results show almost no statistically significant difference in steric and dynamic SLR on both global and regional scales in the near-term between the two scenarios, but statistically significant SLR reduction for the global mean and many regions later in the century (2061–2080). However, there are regions where the reduction is insignificant, such as the Philippines and west of Australia, that are associated with ocean dynamics and intensified internal variability due to external forcing.

54 ENVIRONMENTAL SCIENCES↗

Rice production threatened by coupled stresses of climate and soil arsenic

Projections of global rice yields account for climate change. They do not, however, consider the coupled stresses of impending climate change and arsenic in paddy soils. Here, we show in a greenhouse study that future conditions cause a greater proportion of pore-water arsenite, the more toxic form of arsenic, in the rhizosphere of Californian Oryza sativa L. variety M206, grown on Californian paddy soil. As a result, grain yields decrease by 39% compared to yields at today’s arsenic soil concentrations. In addition, future climatic conditions cause a nearly twofold increase of grain inorganic arsenic concentrations. Our findings indicate that climate-induced changes in soil arsenic behaviour and plant response will lead to currently unforeseen losses in rice grain productivity and quality. Pursuing rice varieties and crop management practices that alleviate the coupled stresses of soil arsenic and change in climatic factors are needed to overcome the currently impending food crisis.

54 ENVIRONMENTAL SCIENCES↗

Advancing research on compound weather and climate events via large ensemble model simulations

Societally relevant weather impacts typically result from compound events, which are rare combinations of weather and climate drivers. Focussing on four event types arising from different combinations of climate variables across space and time, here we illustrate that robust analyses of compound events — such as frequency and uncertainty analysis under present-day and future conditions, event attribution to climate change, and exploration of low-probability-high-impact events — require data with very large sample size. In particular, the required sample is much larger than that needed for analyses of univariate extremes. We demonstrate that Single Model Initial-condition Large Ensemble (SMILE) simulations from multiple climate models, which provide hundreds to thousands of years of weather conditions, are crucial for advancing our assessments of compound events and constructing robust model projections. Combining SMILEs with an improved physical understanding of compound events will ultimately provide practitioners and stakeholders with the best available information on climate risks.

54 ENVIRONMENTAL SCIENCES↗

Muted extratropical low cloud seasonal cycle is closely linked to underestimated climate sensitivity in models

Abstract A large spread in model estimates of the equilibrium climate sensitivity (ECS), defined as the global mean near-surface air-temperature increase following a doubling of atmospheric CO 2 concentration, leaves us greatly disadvantaged in guiding policy-making for climate change adaptation and mitigation. In this study, we show that the projected ECS in the latest generation of climate models is highly related to seasonal variations of extratropical low-cloud fraction (LCF) in historical simulations. Marked reduction of extratropical LCF from winter to summer is found in models with ECS > 4.75 K, in accordance with the significant reduction of extratropical LCF under a warming climate in these models. In contrast, a pronounced seasonal cycle of extratropical LCF, as supported by satellite observations, is largely absent in models with ECS < 3.3 K. The distinct seasonality in extratropical LCF in climate models is ascribed to their different prevailing cloud regimes governing the extratropical LCF variability.

54 ENVIRONMENTAL SCIENCES↗

Expansion of high-latitude deciduous forests driven by interactions between climate warming and fire

High-latitude regions have experienced rapid warming in recent decades, and this trend is projected to continue over the twenty-first century. Fire is also projected to increase with warming. We show here, consistent with changes during the Holocene, that changes in twenty-first century climate and fire are likely to alter the composition of Alaskan boreal forests. We hypothesize that competition for nutrients after fire in early succession and for light in late succession in a warmer climate will cause shifts in plant functional type. Consistent with observations, our ecosystem model predicts evergreen conifers to be the current dominant tree type in Alaska. However, under future climate and fire, our analysis suggests the relative dominance of deciduous broadleaf trees nearly doubles, accounting for 58% of the Alaska ecosystem's net primary productivity by 2100, with commensurate declines in contributions from evergreen conifer trees and herbaceous plants. Post-fire deciduous broadleaf tree growth under a future climate is sustained from enhanced microbial nitrogen mineralization caused by warmer soils and deeper active layers, resulting in taller trees that compete more effectively for light. Finally, the expansion of deciduous broadleaf forests will affect the carbon cycle, surface energy fluxes and ecosystem function, thereby modifying important feedbacks with the climate system.

54 ENVIRONMENTAL SCIENCES↗

Observed changes in dry-season water availability attributed to human-induced climate change

Human-induced climate change impacts the hydrological cycle and thus the availability of water resources. However, previous assessments of observed warming-induced changes in dryness have not excluded natural climate variability and show conflicting results due to uncertainties in our understanding of the response of evapotranspiration. Here in this paper, we employ data-driven and land-surface models to produce observation-based global reconstructions of water availability from 1902 to 2014, a period during which our planet experienced a global warming of approximately 1°C. Our analysis reveals a spatial pattern of changes in average water availability during the driest month of the year over the past three decades compared with the first half of the twentieth century, with some regions experiencing increased and some decreased water availability. The global pattern is consistent with climate model estimates that account for anthropogenic effects, and it is not expected from natural climate variability, supporting human-induced climate change as the cause. There is regional evidence of drier dry seasons predominantly in extratropical latitudes and including Europe, western North America, northern Asia, southern South America, Australia and eastern Africa. We also find that the intensification of the dry season is generally a consequence of increasing evapotranspiration rather than decreasing precipitation.

54 ENVIRONMENTAL SCIENCES↗

Abrupt ice-age shifts in southern westerly winds and Antarctic climate forced from the north

According to the article, the mid-latitude westerly winds of the Southern Hemisphere play a central role in the global climate system via Southern Ocean upwelling, carbon exchange with the deep ocean, Agulhas leakage (transport of Indian Ocean waters into the Atlantic) and possibly Antarctic ice-sheet stability. Meridional shifts of the Southern Hemisphere westerly winds have been hypothesized to occur in parallel with the well-documented shifts of the intertropical convergence zone in response to Dansgaard–Oeschger (DO) events— abrupt North Atlantic climate change events of the last ice age. Shifting moisture pathways to West Antarctica are consistent with this view but may represent a Pacific teleconnection pattern forced from the tropics. The full response of the Southern Hemisphere atmospheric circulation to the DO cycle and its impact on Antarctic temperature remain unclear. Here we use five ice cores synchronized via volcanic markers to show that the Antarctic temperature response to the DO cycle can be understood as the superposition of two modes: a spatially homogeneous oceanic ‘bipolar seesaw’ mode that lags behind Northern Hemisphere climate by about 200 years, and a spatially heterogeneous atmospheric mode that is synchronous with abrupt events in the Northern Hemisphere. Temperature anomalies of the atmospheric mode are similar to those associated with present-day Southern Annular Mode variability, rather than the Pacific–South American pattern. Moreover, deuterium-excess records suggest a zonally coherent migration of the Southern Hemisphere westerly winds over all ocean basins in phase with Northern Hemisphere climate. Our work provides a simple conceptual framework for understanding circum-Antarctic temperature variations forced by abrupt Northern Hemisphere climate change. We provide observational evidence of abrupt shifts in the Southern Hemisphere westerly winds, which have previously documented ramifications for global ocean circulation and atmospheric carbon dioxide. These coupled changes highlight the necessity of a global, rather than a purely North Atlantic, perspective on the DO cycle.

Science & Technology - Other Topics↗

Typical and extreme weather datasets for studying the resilience of buildings to climate change and heatwaves

We present unprecedented datasets of current and future projected weather files for building simulations in 15 major cities distributed across 10 climate zones worldwide. The datasets include ambient air temperature, relative humidity, atmospheric pressure, direct and diffuse solar irradiance, and wind speed at hourly resolution, which are essential climate elements needed to undertake building simulations. The datasets contain typical and extreme weather years in the EnergyPlus weather file (EPW) format and multiyear projections in comma-separated value (CSV) format for three periods: historical (2001–2020), future mid-term (2041–2060), and future long-term (2081–2100). The datasets were generated from projections of one regional climate model, which were bias-corrected using multiyear observational data for each city. The methodology used makes the datasets among the first to incorporate complex changes in the future climate for the frequency, duration, and magnitude of extreme temperatures. These datasets, created within the IEA EBC Annex 80 “Resilient Cooling for Buildings”, are ready to be used for different types of building adaptation and resilience studies to climate change and heatwaves.

54 ENVIRONMENTAL SCIENCES↗

A quantitative method to decompose SWE differences between regional climate models and reanalysis datasets

Abstract The simulation of snow water equivalent (SWE) remains difficult for regional climate models. Accurate SWE simulation depends on complex interacting climate processes such as the intensity and distribution of precipitation, rain-snow partitioning, and radiative fluxes. To identify the driving forces behind SWE difference between model and reanalysis datasets, and guide model improvement, we design a framework to quantitatively decompose the SWE difference contributed from precipitation distribution and magnitude, ablation, temperature and topography biases in regional climate models. We apply this framework within the California Sierra Nevada to four regional climate models from the North American Coordinated Regional Downscaling Experiment (NA-CORDEX) run at three spatial resolutions. Models generally predict less SWE compared to Landsat-Era Sierra Nevada Snow Reanalysis (SNSR) dataset. Unresolved topography associated with model resolution contribute to dry and warm biases in models. Refining resolution from 0.44° to 0.11° improves SWE simulation by 35%. To varying degrees across models, additional difference arises from spatial and elevational distribution of precipitation, cold biases revealed by topographic correction, uncertainties in the rain-snow partitioning threshold, and high ablation biases. This work reveals both positive and negative contributions to snow bias in climate models and provides guidance for future model development to enhance SWE simulation.

54 ENVIRONMENTAL SCIENCES↗

No constraint on long-term tropical land carbon-climate feedback uncertainties from interannual variability

Unraveling drivers of the interannual variability of tropical land carbon cycle is critical for understanding land carbon-climate feedbacks. Here we utilize two generations of factorial model experiments to show that interannual variability of tropical land carbon uptake under both present and future climate is consistently dominated by terrestrial water availability variations in Earth system models. The magnitude of this interannual sensitivity of tropical land carbon uptake to water availability variations under future climate shows a large spread across the latest 16 models (2.3 ± 1.5 PgC/yr/Tt H 2 O), which is constrained to 1.3 ± 0.8 PgC/yr/Tt H 2 O using observations and the emergent constraint methodology. However, the long-term tropical land carbon-climate feedback uncertainties in the latest models can no longer be directly constrained by interannual variability compared with previous models, given that additional important processes are not well reflected in interannual variability but could determine long-term land carbon storage. Our results highlight the limited implication of interannual variability for long-term tropical land carbon-climate feedbacks and help isolate remaining uncertainties with respect to water limitations on tropical land carbon sink in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

Depth dependence of climatic controls on soil microbial community activity and composition

Abstract Subsoil microbiomes play important roles in soil carbon and nutrient cycling, yet our understanding of the controls on subsoil microbial communities is limited. Here, we investigated the direct (mean annual temperature and precipitation) and indirect (soil chemistry) effects of climate on microbiome composition and extracellular enzyme activity throughout the soil profile across two elevation-bioclimatic gradients in central California, USA. We found that microbiome composition changes and activity decreases with depth. Across these sites, the direct influence of climate on microbiome composition and activity was relatively lower at depth. Furthermore, we found that certain microbial taxa change in relative abundance over large temperature and precipitation gradients only in specific soil horizons, highlighting the depth dependence of the climatic controls on microbiome composition. Our finding that the direct impacts of climate are muted at depth suggests that deep soil microbiomes may lag in their acclimation to new temperatures with a changing climate.

16S rRNA↗

Shifting plant species composition in response to climate change stabilizes grassland primary production

The structure and function of alpine grassland ecosystems, including their extensive soil carbon stocks, are largely shaped by temperature. The Tibetan Plateau in particular has experienced significant warming over the past 50 y, and this warming trend is projected to intensify in the future. Such climate change will likely alter plant species composition and net primary production (NPP). Here we combined 32 y of observations and monitoring with a manipulative experiment of temperature and precipitation to explore the effects of changing climate on plant community structure and ecosystem function. First, long-term climate warming from 1983 to 2014, which occurred without systematic changes in precipitation, led to higher grass abundance and lower sedge abundance, but did not affect aboveground NPP. Second, an experimental warming experiment conducted over 4 y had no effects on any aspect of NPP, whereas drought manipulation (reducing precipitation by 50%), shifted NPP allocation belowground without affecting total NPP. Third, both experimental warming and drought treatments, supported by a meta-analysis at nine sites across the plateau, increased grass abundance at the expense of biomass of sedges and forbs. This shift in functional group composition led to deeper root systems, which may have enabled plant communities to acquire more water and thus stabilize ecosystem primary production even with a changing climate. Altogether, our study demonstrates that shifting plant species composition in response to climate change may have stabilized primary production in this high-elevation ecosystem, but it also caused a shift from aboveground to belowground productivity.

54 ENVIRONMENTAL SCIENCES↗