Assessing the potential for crop albedo enhancement in reducing heatwave frequency, duration, and intensity under future climate change

Adapting to the impacts of future warming, and in particular the impacts of heatwaves, is an increasingly important challenge. One proposed strategy is land-surface radiation management via crop albedo enhancement. This has been argued to be an effective method of reducing daily hot temperature extremes regionally. However, the influence of crop albedo enhancement on heatwave events, which last three or more days, is yet to be explored and this remains an important knowledge gap. Using a fully coupled earth system model with 10 ensemble members, we show that crop albedo enhancement by up to ＋0.1 reduces the frequency of heatwave days over Europe and North America by 10 to 20 days; with a larger reduction over Europe under a future climate driven by SSP2-4.5. The average temperature anomaly during heatwaves (the magnitude of the event), is reduced by 0.8 °C to 1.2 °C where the albedo was enhanced, but reductions in mean heatwave duration are limited. There was a marked reduction in the mean annual cumulative heatwave intensity across most of Eurasia and North America, ranging from 32 °C to as high as 80 °C in parts of southern Europe. These changes were largely driven by a reduction in net radiation, decreasing the sensible heat flux, which reduces the maximum temperature, and therefore, heatwave frequency and intensity. These changes were largely localised to where the albedo enhancement was applied with no significant changes in atmospheric circulation or precipitation, which presents advantages for implementation. While our albedo perturbation of up to ＋0.1 is large and represents the likely upper limit of what is possible with more reflective crops, and we assume that more reflective crops are grown everywhere and instantly, these results provide useful guidance to policy makers and farmers on the maximum possible benefits of using more reflective crops in limiting the impacts of heatwaves under future climate

The Treatment of Uncertainties in Reactive Pollution Dispersion Models at Urban Scales

The ability to predict NO2 concentrations ([NO¬2]) within urban street networks is important for the evaluation of strategies to reduce exposure to NO2. However, models aiming to make such predictions involve the coupling of several complex processes: traffic emissions under different levels of congestion; dispersion via turbulent mixing; chemical processes of relevance at the street-scale. Parameterisations of these processes are challenging to quantify with precision. Predictions are therefore subject to uncertainties which should be taken into account when using models within decision making. This paper presents an analysis of mean [NO¬2] predictions from such a complex modelling system applied to a street canyon within the city of York, UK including the treatment of model uncertainties and their causes. The model system consists of a micro-scale traffic simulation and emissions model, a Reynolds Averaged turbulent flow model coupled to a reactive Lagrangian particle dispersion model. The analysis focuses on the sensitivity of predicted in-street increments of [NO¬2] at different locations in the street to uncertainties in the model inputs. These include physical characteristics such as background wind direction, temperature and background ozone concentrations; traffic parameters such as overall demand and primary NO2 fraction; as well as model parameterisations such as roughness lengths, turbulent time- and length-scales and chemical reaction rate coefficients. Predicted [NO¬2] is shown to be relatively robust with respect to model parameterisations, although there are significant sensitivities to the activation energy for the reaction NO+O3 as well as the canyon wall roughness length. Under off-peak traffic conditions, demand is the key traffic parameter. Under peak conditions where the network saturates, road-side [NO¬2] is relatively insensitive to changes in demand and more sensitive to the primary NO2 fraction. The most important physical parameter was found to be the background wind direction. The study highlights the key parameters required for reliable [NO¬2] estimations suggesting that accurate reference measurements for wind direction should be a critical part of air quality assessments for in-street locations. It also highlights the importance of street scale chemical processes in forming road-side [NO¬2], particularly for regions of high NOx emissions such as close to traffic queues

Compatible fossil fuel CO2 emissions in the CMIP6 earth system models' historical and shared socioeconomic pathway experiments of the twenty-first century

We present the compatible CO2 emissions from fossil fuel (FF) burning and industry, calculated from the historical and Shared Socioeconomic Pathway (SSP) experiments of nine Earth system models (ESMs) participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The multimodel mean FF emissions match the historical record well and are close to the data-based estimate of cumulative emissions (394 6 59 GtC vs 400 6 20 GtC, respectively). Only two models fall inside the observed uncertainty range; while two exceed the upper bound, five fall slightly below the lower bound, due primarily to the plateau in CO2 concentration in the 1940s. The ESMs' diagnosed FF emission rates are consistent with those generated by the integrated assessment models (IAMs) from which the SSPs' CO2 concentration pathways were constructed; the simpler IAMs' emissions lie within the ESMs' spread for seven of the eight SSP experiments, the other being only marginally lower, providing confidence in the relationship between the IAMs' FF emission rates and concentration pathways. The ESMs require fossil fuel emissions to reduce to zero and subsequently become negative in SSP1-1.9, SSP1-2.6, SSP4-3.4, and SSP5-3.4over. We also present the ocean and land carbon cycle responses of the ESMs in the historical and SSP scenarios. The models' ocean carbon cycle responses are in close agreement, but there is considerable spread in their land carbon cycle responses. Land-use and land-cover change emissions have a strong influence over the magnitude of diagnosed fossil fuel emissions, with the suggestion of an inverse relationship between the two. © 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses)

Top-down assessment of the Asian carbon budget since the mid 1990s

Increasing atmospheric carbon dioxide (CO2) is the principal driver of anthropogenic climate change. Asia is an important region for the global carbon budget, with 4 of the world’s 10 largest national emitters of CO2. Using an ensemble of seven atmospheric inverse systems, we estimated land biosphere fluxes (natural, land-use change and fires) based on atmospheric observations of CO2 concentration. The Asian land biosphere was a net sink of −0.46 (−0.70–0.24) PgC per year (median and range) for 1996–2012 and was mostly located in East Asia, while in South and Southeast Asia the land biosphere was close to carbon neutral. In East Asia, the annual CO2 sink increased between 1996–2001 and 2008–2012 by 0.56 (0.30–0.81) PgC, accounting for ∼35% of the increase in the global land biosphere sink. Uncertainty in the fossil fuel emissions contributes significantly (32%) to the uncertainty in land biosphere sink change

Top-down assessment of the Asian carbon budget since the mid 1990s

Increasing atmospheric carbon dioxide (CO2) is the principal driver of anthropogenic climate change. Asia is an important region for the global carbon budget, with 4 of the world’s 10 largest national emitters of CO2. Using an ensemble of seven atmospheric inverse systems, we estimated land biosphere fluxes (natural, land-use change and fires) based on atmospheric observations of CO2 concentration. The Asian land biosphere was a net sink of -0.46 (-0.70-0.24) PgC per year (median and range) for 1996-2012 and was mostly located in East Asia, while in South and Southeast Asia the land biosphere was close to carbon neutral. In East Asia, the annual CO2 sink increased between 1996-2001 and 2008-2012 by 0.56 (0.30-0.81) PgC, accounting for ~35% of the increase in the global land biosphere sink. Uncertainty in the fossil fuel emissions contributes significantly (32%) to the uncertainty in land biosphere sink change

RECCAP2 Future Component: Consistency and Potential for Regional Assessment to Constrain Global Projections

This is the final version. Available from Wiley via the DOI in this record. Data Availability Statement: All CMIP6 model output datasets analyzed during this study are available online at https://esgf-node.llnl.gov/search/cmip6/ and code required to reproduce figures is available at https://github.com/ChrisJones-MOHC/RECCAP2Future_2023 (ChrisJones-MOHC, 2023) and Zenodo at https://doi.org/10.5281/zenodo.8420250.Projections of future carbon sinks and stocks are important because they show how the world's ecosystems will respond to elevated CO2 and changes in climate. Moreover, they are crucial to inform policy decisions around emissions reductions to stay within the global warming levels identified by the Paris Agreement. However, Earth System Models from the 6th Coupled Model Intercomparison Project (CMIP6) show substantial spread in future projections—especially of the terrestrial carbon cycle, leading to a large uncertainty in our knowledge of any remaining carbon budget (RCB). Here we evaluate the global terrestrial carbon cycle projections on a region‐by‐region basis and compare the global models with regional assessments made by the REgional Carbon Cycle Assessment and Processes, Phase 2 activity. Results show that for each region, the CMIP6 multi‐model mean is generally consistent with the regional assessment, but substantial cross‐model spread exists. Nonetheless, all models perform well in some regions and no region is without some well performing models. This gives confidence that the CMIP6 models can be used to look at future changes in carbon stocks on a regional basis with appropriate model assessment and benchmarking. We find that most regions of the world remain cumulative net sources of CO2 between now and 2100 when considering the balance of fossil‐fuels and natural sinks, even under aggressive mitigation scenarios. This paper identifies strengths and weaknesses for each model in terms of its performance over a particular region including how process representation might impact those results and sets the agenda for applying stricter constraints at regional scales to reduce the uncertainty in global projections.European Union’s Horizon 2020European Union’s Horizon 2020European Union’s Horizon 2020Joint UK BEIS/Defra Met Office Hadley Centre Climate ProgrammeCarbonWatch-NZ Endeavour Research ProgrammeSão Paulo Research FoundationSão Paulo Research FoundationSão Paulo Research FoundationNational Science FoundationAndrew Carnegie Fellow ProgramCNPqKorea Ministry of EnvironmentNatural Environment Research Council (NERC)Natural Environment Research Council (NERC)National Environmental Science Progra

Attribution of multi-annual to decadal changes in the climate system: The Large Ensemble Single Forcing Model Intercomparison Project (LESFMIP)

Multi-annual to decadal changes in climate are accompanied by changes in extreme events that cause major impacts on society and severe challenges for adaptation. Early warnings of such changes are now potentially possible through operational decadal predictions. However, improved understanding of the causes of regional changes in climate on these timescales is needed both to attribute recent events and to gain further confidence in forecasts. Here we document the Large Ensemble Single Forcing Model Intercomparison Project that will address this need through coordinated model experiments enabling the impacts of different external drivers to be isolated. We highlight the need to account for model errors and propose an attribution approach that exploits differences between models to diagnose the real-world situation and overcomes potential errors in atmospheric circulation changes. The experiments and analysis proposed here will provide substantial improvements to our ability to understand near-term changes in climate and will support the World Climate Research Program Lighthouse Activity on Explaining and Predicting Earth System Change.publishedVersio

Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0

The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text-based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non-specialists to access CMIP data in a new, user-friendly way

Microglial activation and chronic neurodegeneration

Microglia, the resident innate immune cells in the brain, have long been implicated in the pathology of neurode-generative diseases. Accumulating evidence points to activated microglia as a chronic source of multiple neurotoxic factors, including tumor necrosis factor-α, nitric oxide, interleukin-1β, and reactive oxygen species (ROS), driving progressive neuron damage. Microglia can become chronically activated by either a single stimulus (e.g., lipopolysaccharide or neuron damage) or multiple stimuli exposures to result in cumulative neuronal loss with time. Although the mechanisms driving these phenomena are just beginning to be understood, reactive microgliosis (the microglial response to neuron damage) and ROS have been implicated as key mechanisms of chronic and neurotoxic microglial activation, particularly in the case of Parkinson’s disease. We review the mechanisms of neurotoxicity associated with chronic microglial activation and discuss the role of neuronal death and microglial ROS driving the chronic and toxic microglial phenotype