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      Nitrogen cycle impacts on CO 2 fertilisation and climate forcing of land carbon stores

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      Environmental Research Letters
      IOP Publishing

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          Abstract

          Anthropogenic fossil fuel burning increases atmospheric carbon dioxide (CO 2) concentration, which is adjusting the climate system. The direct impact of rising CO 2 levels and climate feedback alters the terrestrial carbon stores. Land stores are presently increasing, offsetting a substantial fraction of CO 2 emissions. Less understood is how this human-induced carbon cycle perturbation interacts with other terrestrial biogeochemical cycles. These connections require quantification, as they may eventually suppress land fertilisation, and so fewer emissions are allowed to follow any prescribed future global warming pathway. Using the new Joint UK Land Environment Simulator-CN large-scale land model, which contributed to Coupled Model Intercomparison Project Phase 6 as the land component of the UK Earth System Model v1 climate model, we focus on how the introduction of the simulated terrestrial nitrogen (N) cycle modulates the expected evolution of vegetation and soil carbon pools. We find that the N-cycle suppresses, by approximately one-third, any future gains by the global soil pool when compared to calculations without that cycle. There is also a decrease in the vegetation carbon gain, although this is much smaller. Factorial simulations illustrate that N suppression tracks direct CO 2 rise rather than climate change. The finding that this CO 2-related effect predominantly influences soil carbon rather than vegetation carbon, we explain by different balances between changing carbon uptake levels and residence times. Finally, we discuss how this new generation of land models may gain further from emerging point knowledge held by the detailed ecological modelling community.

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          An Overview of CMIP5 and the Experiment Design

          The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.
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            Fire in the Earth system.

            Fire is a worldwide phenomenon that appears in the geological record soon after the appearance of terrestrial plants. Fire influences global ecosystem patterns and processes, including vegetation distribution and structure, the carbon cycle, and climate. Although humans and fire have always coexisted, our capacity to manage fire remains imperfect and may become more difficult in the future as climate change alters fire regimes. This risk is difficult to assess, however, because fires are still poorly represented in global models. Here, we discuss some of the most important issues involved in developing a better understanding of the role of fire in the Earth system.
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              Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset

              CRU TS (Climatic Research Unit gridded Time Series) is a widely used climate dataset on a 0.5° latitude by 0.5° longitude grid over all land domains of the world except Antarctica. It is derived by the interpolation of monthly climate anomalies from extensive networks of weather station observations. Here we describe the construction of a major new version, CRU TS v4. It is updated to span 1901–2018 by the inclusion of additional station observations, and it will be updated annually. The interpolation process has been changed to use angular-distance weighting (ADW), and the production of secondary variables has been revised to better suit this approach. This implementation of ADW provides improved traceability between each gridded value and the input observations, and allows more informative diagnostics that dataset users can utilise to assess how dataset quality might vary geographically.
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                Author and article information

                Contributors
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                Journal
                Environmental Research Letters
                Environ. Res. Lett.
                IOP Publishing
                1748-9326
                April 08 2022
                April 01 2022
                April 08 2022
                April 01 2022
                : 17
                : 4
                : 044072
                Article
                10.1088/1748-9326/ac6148
                629ec7a8-7aff-4037-999b-91635520eef7
                © 2022

                http://creativecommons.org/licenses/by/4.0

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