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Future sea-level rise projections are characterized by both quantifiable uncertainty and unquantifiable structural uncertainty. Thorough scientific assessment of sea-level rise projections requires analysis of both dimensions of uncertainty. Probabilistic sea-level rise projections evaluate the quantifiable dimension of uncertainty; comparison of alternative probabilistic methods provides an indication of structural uncertainty. Here we describe the Framework for Assessing Changes To Sea-level (FACTS), a modular platform for characterizing different probability distributions for the drivers of sea-level change and their consequences for global mean, regional, and extreme sea-level change. We demonstrate its application by generating seven alternative probability distributions under multiple emissions scenarios for both future global mean sea-level change and future relative and extreme sea-level change at New York City. These distributions, closely aligned with those presented in the Intergovernmental Panel on Climate Change Sixth Assessment Report, emphasize the role of the Antarctic and Greenland ice sheets as drivers of structural uncertainty in sea-level change projections.

 

Future sea-level change is characterized by both quantifiable and unquantifiable uncertainties. Effective communication of both types of uncertainty is a key challenge in translating sea-level science to inform long-term coastal planning. Scientific assessments play a key role in the translation process and have taken diverse approaches to communicating sea-level projection uncertainty. Here we review how past IPCC and regional assessments have presented sea-level projection uncertainty, how IPCC presentations have been interpreted by regional assessments and how regional assessments and policy guidance simplify projections for practical use. This information influenced the IPCC Sixth Assessment Report presentation of quantifiable and unquantifiable uncertainty, with the goal of preserving both elements as projections are adapted for regional application. 

Light and soil nitrogen availability can be strong controls of plant nitrogen (N) fixation, but data on how understory N‐fixing plants respond to these drivers are limited despite their important role in ecosystem N cycling. Furthermore, ecosystem N cycling can be altered by the introduction of species with nutrient use patterns that differ from natives. We assessed how N fixation of two exotic, understory species responded to varying light and soil N environments.

We sampled leaf tissue fromMimosa pudicaL.,Desmodium triflorum(L.) DC., and a nonfixing reference plant (Axonopus) growing in control and two N fertilization treatments under either N‐fixing or non‐N‐fixing trees, which may alter local soil nutrient cycling, across a range of light conditions. We measured N fixation with¹⁵N isotope dilution, and ensured that N‐fixing neighbour trees were in fact fixing N. All understory plants were wild‐growing species not native to the study location.

DesmodiumandMimosaacquired 82.6% and 71.6% of their nitrogen from fixation (%N_dfa) in the control, compared to 66.8% and 58.1% in the +10 g N m⁻² year⁻¹treatment and 73.1% and 64.7% in the +15 g N m⁻² year⁻¹treatment. These subtle %N_dfadifferences across fertilization treatments were more apparent at low light availability and disappeared at high light availability. The amount of N fixed by neighbouring trees did not influence %N_dfain the understory species.

Synthesis. Our study shows some differences in N fixation across different nutrient environments at low light for two N‐fixing species, though the changes were small, and both species derived most of their N from fixation. These findings imply that introduced N‐fixing species could exacerbate ecosystem N enrichment, particularly under high soil N conditions.

 

Ocean temperature observations are crucial for a host of climate research and forecasting activities, such as climate monitoring, ocean reanalysis and state estimation, seasonal-to-decadal forecasts, and ocean forecasting. For all of these applications, it is crucial to understand the uncertainty attached to each of the observations, accounting for changes in instrument technology and observing practices over time. Here, we describe the rationale behind the uncertainty specification provided for all in situ ocean temperature observations in the International Quality-controlled Ocean Database (IQuOD) v0.1, a value-added data product served alongside the World Ocean Database (WOD). We collected information from manufacturer specifications and other publications, providing the end user with uncertainty estimates based mainly on instrument type, along with extant auxiliary information such as calibration and collection method. The provision of a consistent set of observation uncertainties will provide a more complete understanding of historical ocean observations used to examine the changing environment. Moving forward, IQuOD will continue to work with the ocean observation, data assimilation and ocean climate communities to further refine uncertainty quantification. We encourage submissions of metadata and information about historical practices to the IQuOD project and WOD. 

Abstract. Human-induced atmospheric composition changes cause a radiative imbalance atthe top of the atmosphere which is driving global warming. This Earth energy imbalance (EEI) is the most critical number defining the prospects for continued global warming and climate change. Understanding the heat gain ofthe Earth system – and particularly how much and where the heat isdistributed – is fundamental to understanding how this affects warmingocean, atmosphere and land; rising surface temperature; sea level; and lossof grounded and floating ice, which are fundamental concerns for society.This study is a Global Climate Observing System (GCOS) concertedinternational effort to update the Earth heat inventory and presents anupdated assessment of ocean warming estimates as well as new and updated estimatesof heat gain in the atmosphere, cryosphere and land over the period1960–2018. The study obtains a consistent long-term Earth system heat gainover the period 1971–2018, with a total heat gain of 358±37 ZJ,which is equivalent to a global heating rate of 0.47±0.1 W m−2.Over the period 1971–2018 (2010–2018), the majority of heat gain is reportedfor the global ocean with 89 % (90 %), with 52 % for both periods inthe upper 700 m depth, 28 % (30 %) for the 700–2000 m depth layer and 9 % (8 %) below 2000 m depth. Heat gain over land amounts to 6 %(5 %) over these periods, 4 % (3 %) is available for the melting ofgrounded and floating ice, and 1 % (2 %) is available for atmospheric warming. Ourresults also show that EEI is not only continuing, but also increasing: the EEIamounts to 0.87±0.12 W m−2 during 2010–2018. Stabilization ofclimate, the goal of the universally agreed United Nations Framework Convention on ClimateChange (UNFCCC) in 1992 and the ParisAgreement in 2015, requires that EEI be reduced to approximately zero toachieve Earth's system quasi-equilibrium. The amount of CO2 in theatmosphere would need to be reduced from 410 to 353 ppm to increase heatradiation to space by 0.87 W m−2, bringing Earth back towards energybalance. This simple number, EEI, is the most fundamental metric that thescientific community and public must be aware of as the measure of how wellthe world is doing in the task of bringing climate change under control, andwe call for an implementation of the EEI into the global stocktake based onbest available science. Continued quantification and reduced uncertaintiesin the Earth heat inventory can be best achieved through the maintenance ofthe current global climate observing system, its extension into areas ofgaps in the sampling, and the establishment of an international framework forconcerted multidisciplinary research of the Earth heat inventory aspresented in this study. This Earth heat inventory is published at the German Climate Computing Centre (DKRZ, https://www.dkrz.de/, last access: 7 August 2020) under the DOIhttps://doi.org/10.26050/WDCC/GCOS_EHI_EXP_v2(von Schuckmann et al., 2020).