Bias-corrected CMIP6 global dataset for dynamical downscaling of the historical and future climate (1979–2100)

Dynamical downscaling is an important approach to obtaining fine-scale weather and climate information. However, dynamical downscaling simulations are often degraded by biases in the large-scale forcing itself. We constructed a bias-corrected global dataset based on 18 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) dataset. The bias-corrected data have an ERA5-based mean climate and interannual variance, but with a non-linear trend from the ensemble mean of the 18 CMIP6 models. The dataset spans the historical time period 1979–2014 and future scenarios (SSP245 and SSP585) for 2015–2100 with a horizontal grid spacing of (1.25° × 1.25°) at six-hourly intervals. Our evaluation suggests that the bias-corrected data are of better quality than the individual CMIP6 models in terms of the climatological mean, interannual variance and extreme events. This dataset will be useful for dynamical downscaling projections of the Earth’s future climate, atmospheric environment, hydrology, agriculture, wind power, etc.

Persistence and variability of Earth’s inter-hemispheric albedo symmetry in 19 years of CERES EBAF observations

Despite the unequal partitioning of land and aerosol sources between the hemispheres, Earth’s albedo is observed to be persistently symmetric about the equator. This symmetry is determined by the compensation of clouds to the clear-sky albedo. Here, the variability of this inter-hemispheric albedo symmetry is explored by decomposing observed radiative fluxes in the CERES EBAF satellite data record into components reflected by the atmosphere, clouds, and the surface. We find that the degree of inter-hemispheric albedo symmetry has not changed significantly throughout the observational record. The variability of the inter-hemispheric difference in reflected solar radiation (asymmetry) is strongly determined by tropical and subtropical cloud cover, particularly those related to non-neutral phases of the El Niño-Southern Oscillation (ENSO). As the ENSO is the most significant source of interannual variability in reflected radiation on a global scale, this underscores the inter-hemispheric albedo symmetry as a robust feature of Earth’s current annual mean climate. Comparing this feature in observations with simulations from coupled models reveals that the degree of modeled albedo symmetry is mostly dependent on biases in reflected radiation in the midlatitudes, and that models that overestimate its variability the most have larger biases in reflected radiation in the tropics. The degree of model albedo symmetry is improved when driven with historical sea surface temperatures, indicating that the degree of symmetry in Earth’s albedo is dependent on the representation of cloud responses to coupled ocean-atmosphere processes.

Hadley Circulation in the Present and Future Climate Simulations of the K-ACE Model

Hadley circulation (HC) is a planetary-scale overturning circulation in the tropics that transports momentum, heat, and moisture poleward. In this study, we evaluate the strength and extent of the HC in the historical and future climate simulations of the Korean Meteorological Administration (KMA) Advanced Community Earth system model (K-ACE), which was recently developed by the National Institute of Meteorological Sciences of Korea. Compared with a reanalysis product, the overall structure of the HC is reasonably reproduced by the K-ACE. At the same time, it is also found that the Northern Hemisphere HC in the K-ACE is shifted southward by a few degrees, while the strength of the Southern Hemisphere (SH) HC is under-represented by approximately 20%. These biases in the strength and extent of the HC can be explained by biases in the eddy momentum flux and precipitation in the tropics. In the future climate simulations under the Shared Socioeconomic Pathway 5-Representative Concentration Pathway 8.5 scenario, the HCs in the K-ACE show a weakening and widening trend in both hemispheres, which is consistent with the projections of many Coupled Model Intercomparison Project Phase 6 models. A notable feature of the K-ACE is the widening of the SH HC, which takes place at a rate that is about double the multi-model mean. Climate models that share the component models with the K-ACE, such as UKESM, HadGEM3-GC31-LL, and ACCESS-CM2/ESM1, also show enhanced poleward expansion of the HC in the SH. This strong expansion is shown to be dominated by the expansion of the regional HC over the Pacific.

A Global Assessment of Climate Change Adaptation in Marine Protected Area Management Plans

Marine protected area (MPA) efficacy is increasingly challenged by climate change. Experts have identified clear climate change adaptation principles that MPA practitioners can incorporate into MPA management; however, adoption of these principles in MPA management remains largely unquantified. We conducted a text analysis of 647 English-language MPA management plans to assess the frequency with which they included climate change-related terms and terms pertaining to ecological, physical, and sociological components of an MPA system that may be impacted by climate change. Next, we manually searched 223 management plans to quantify the plans’ climate change robustness, which we defined as the degree of incorporation of common climate change adaptation principles. We found that climate change is inadequately considered in MPA management plans. Of all plans published since 2010, only 57% contained at least one of the climate change-related terms, “climate change,” “global warming,” “extreme events,” “natural variability,” or “climate variability.” The mean climate change robustness index of climate-considering management plans was 10.9 or 39% of a total possible score of 28. The United States was the only region that had plans with climate robustness indices of 20 or greater. By contrast, Canada lags behind other temperate jurisdictions in incorporating climate change adaptation analysis, planning, and monitoring into MPA management, with a mean climate change robustness index of 6.8. Climate change robustness scores have generally improved over time within the most common MPA designations in Oceania, the United Kingdom, and the United States, though the opposite is true in Canada. Our results highlight the urgent need for practitioners to incorporate climate change adaptation into MPA management in accordance with well-researched frameworks.

Observational constraints reduce estimates of the global mean climate relevance of black carbon

How emissions of black carbon (BC) aerosols affect the climate is still uncertain, due to incomplete knowledge of its sources, optical properties and atmospheric processes such as transport, removal and impact on clouds. Here we constrain simulations from four climate models with observations of atmospheric BC concentrations and absorption efficiency, and the most recent emission inventories, to show that the current global mean surface temperature change from anthropogenic BC emissions is likely to be weak at +0.03 ±0.02K. Atmospheric rapid adjustment processes are found to reduce the top of atmosphere radiative imbalance relative to instantaneous radiative forcing (direct aerosol effect) by almost 50% as a multi-model mean. Furthermore, constraining the models to reproduce observational estimates of the atmospheric vertical profile reduces BC effective radiative forcing to 0.08 W m-2, a value more than 50% lower than in unconstrained simulations. Our results imply a need to revisit commonly used climate metrics such as the global warming potential of BC. This value (for a 100-year time horizon) reduces from 680 when neglecting rapid adjustments and using an unconstrained BC profile to our best estimate of 160 ±120.

Cost and greenhouse gas emissions of current, healthy, flexitarian and vegan diets in Aotearoa (New Zealand)

ObjectiveTo compare the costs and climate impact (greenhouse gas emissions) associated with current and healthy diets and two healthy and environmentally friendly dietary patterns: flexitarian and vegan.DesignModelling studySettingAotearoa (New Zealand).Main outcome measuresThe distribution of the cost and climate impact (kgCO2e/kg of food per fortnight) of 2 weekly current, healthy, vegan and flexitarian household diets was modelled using a list of commonly consumed foods, a set of quantity/serves constraints for each, and constraints for food group and nutrient intakes based on dietary guidelines (Eating and Activity Guidelines for healthy diets and EAT-Lancet reference diet for vegan and flexitarian diets) or nutrition survey data (current diets).ResultsThe iterative creation of 210–237 household dietary intakes for each dietary scenario was achieved using computer software adapted for the purpose (DIETCOST). There were stepwise differences between diet scenarios (p<0.001) with the current diet having the lowest mean cost in New Zealand Dollars (NZ$584 (95% CI NZ$580 to NZ$588)) per fortnight for a family of four) but highest mean climate impact (597 kgCO2e (95% CI 590 to 604 kgCO2e)), followed by the healthy diet (NZ$637 (95% CI NZ$632 to NZ$642), 452 kgCO2e (95% CI 446 to 458 kgCO2e)), the flexitarian diet (NZ$728 (95% CI NZ$723 to NZ$734), 263 kgCO2e (95% CI 261 to 265 kgCO2e)) and the vegan diet, which had the highest mean cost and lowest mean climate impact (NZ$789, (95% CI NZ$784 to NZ$794), 203 kgCO2e (95% CI 201 to 204 kgCO2e)). There was a negative relationship between cost and climate impact across diets and a positive relationship within diets.ConclusionsMoving from current diets towards sustainable healthy diets (SHDs) will reduce climate impact but generally at a higher cost to households. The results reflect trade-offs, with the larger constraints placed on diets, the greater cost and factors such as nutritional adequacy, variety, cost and low-emissions foods being considered. Further monitoring and policies are needed to support population transitions that are country specific from current diets to SHD.

Extreme melt season ice layers reduce firn permeability across Greenland

Surface meltwater runoff dominates present-day mass loss from the Greenland Ice Sheet. In Greenland’s interior, porous firn can limit runoff by retaining meltwater unless perched low-permeability horizons, such as ice slabs, develop and restrict percolation. Recent observations suggest that such horizons might develop rapidly during extreme melt seasons. Here we present radar sounding evidence that an extensive near surface melt layer formed following the extreme melt season in 2012. This layer was still present in 2017 in regions up to 700 m higher in elevation and 160 km further inland than known ice slabs. We find that melt layer formation is driven by local, short-timescale thermal and hydrologic processes in addition to mean climate state. These melt layers reduce vertical percolation pathways, and, under appropriate firn temperature and surface melt conditions, encourage further ice aggregation at their horizon. Therefore, the frequency of extreme melt seasons relative to the rate at which pore space and cold content regenerates above the most recent melt layer may be a key determinant of the firn’s multi-year response to surface melt.

A bias-corrected CMIP6 global dataset for dynamical downscaling of future climate, 1979–2100

Dynamical downscaling is an important approach to obtaining fine-scale weather and climate information. However, dynamical downscaling simulations are often degraded by biases in the large-scale forcing itself. Here, we construct a set of bias-corrected global dataset based on 18 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5). The bias-corrected data have an ERA5-based mean climate and interannual variance, but with a nonlinear trend from the mean of 18 CMIP6 models. The dataset spans the historical period of 1979–2014 and future scenarios (SSP245 and SSP585) of 2015–2100 with a horizontal resolution of 1.25° × 1.25° and 6-hourly intervals. Our evaluation suggests that the bias-corrected data shows clearly better quality than individual CMIP6 models evaluated in terms of climatological mean, interannual variance and extreme events. The presented dataset will be useful for the dynamical downscaling projections of future climate, atmospheric environment, hydrology, agriculture, wind power, etc.

Investigating the impact of cloud-radiative feedbacks on tropical precipitation extremes

Although societally important, extreme precipitation is difficult to represent in climate models. This study shows one robust aspect of extreme precipitation across models: extreme precipitation over tropical oceans is strengthened through a positive feedback with cloud-radiative effects. This connection is shown for a multi-model ensemble with experiments that make clouds transparent to longwave radiation. In all cases, tropical extreme precipitation reduces without cloud-radiative effects. Qualitatively similar results are presented for one model using the cloud-locking method to remove cloud feedbacks. The reduced extreme precipitation without cloud-radiative feedbacks does not arise from changes in the mean climate. Rather, evidence is presented that cloud-radiative feedbacks enhance organization of convection and most extreme precipitation over tropical oceans occurs within organized systems. This result suggests that climate models must correctly predict cloud structure and properties, as well as capture the essence of organized convection in order to accurately represent extreme rainfall.