Biomineralization plasticity and environmental heterogeneity predict geographical resilience patterns of foundation species to future change.

Although geographical patterns of species' sensitivity to environmental changes are defined by interacting multiple stressors, little is known about compensatory processes shaping regional differences in organismal vulnerability. Here, we examine large-scale spatial variations in biomineralization under heterogeneous environmental gradients of temperature, salinity and food availability across a 30° latitudinal range (3,334 km), to test whether plasticity in calcareous shell production and composition, from juveniles to large adults, mediates geographical patterns of resilience to climate change in critical foundation species, the mussels Mytilus edulis and M. trossulus. We find shell calcification decreased towards high latitude, with mussels producing thinner shells with a higher organic content in polar than temperate regions. Salinity was the best predictor of within-region differences in mussel shell deposition, mineral and organic composition. In polar, subpolar, and Baltic low-salinity environments, mussels produced thin shells with a thicker external organic layer (periostracum), and an increased proportion of calcite (prismatic layer, as opposed to aragonite) and organic matrix, providing potentially higher resistance against dissolution in more corrosive waters. Conversely, in temperate, higher salinity regimes, thicker, more calcified shells with a higher aragonite (nacreous layer) proportion were deposited, which suggests enhanced protection under increased predation pressure. Interacting effects of salinity and food availability on mussel shell composition predict the deposition of a thicker periostracum and organic-enriched prismatic layer under forecasted future environmental conditions, suggesting a capacity for increased protection of high-latitude populations from ocean acidification. These findings support biomineralization plasticity as a potentially advantageous compensatory mechanism conferring Mytilus species a protective capacity for quantitative and qualitative trade-offs in shell deposition as a response to regional alterations of abiotic and biotic conditions in future environments. Our work illustrates that compensatory mechanisms, driving plastic responses to the spatial structure of multiple stressors, can define geographical patterns of unanticipated species resilience to global environmental change

Counteracting the climate effects of volcanic eruptions using short-lived greenhouse gases

A large volcanic eruption might constitute a climate emergency, significantly altering global temperature and precipitation for several years. Major future eruptions will occur, but their size or timing cannot be predicted. We show, for the first time, that it may be possible to counteract these climate effects through deliberate emissions of short-lived greenhouse gases, dampening the abrupt impact of an eruption. We estimate an emission pathway countering a hypothetical eruption 3 times the size of Mount Pinatubo in 1991. We use a global climate model to evaluate global and regional responses to the eruption, with and without counteremissions. We then raise practical, financial, and ethical questions related to such a strategy. Unlike the more commonly discussed geoengineering to mitigate warming from long-lived greenhouse gases, designed emissions to counter temporary cooling would not have the disadvantage of needing to be sustained over long periods. Nevertheless, implementation would still face significant challenges

Enhanced Australian carbon sink despite increased wildfire during the 21st century

Climate projections show Australia becoming significantly warmer during the 21st century, and precipitation decreasing over much of the continent. Such changes are conventionally considered to increase wildfire risk. Nevertheless, we show that burnt area increases in southern Australia, but decreases in northern Australia. Overall the projected increase in fire is small (0.72–1.31% of land area, depending on the climate scenario used), and does not cause a decrease in carbon storage. In fact, carbon storage increases by 3.7–5.6 Pg C (depending on the climate scenario used). Using a process-based model of vegetation dynamics, vegetation–fire interactions and carbon cycling, we show increased fire promotes a shift to more fire-adapted trees in wooded areas and their encroachment into grasslands, with an overall increase in forested area of 3.9–11.9%. Both changes increase carbon uptake and storage. The increase in woody vegetation increases the amount of coarse litter, which decays more slowly than fine litter hence leading to a relative reduction in overall heterotrophic respiration, further reducing carbon losses. Direct CO2 effects increase woody cover, water-use efficiency and productivity, such that carbon storage is increased by 8.5–14.8 Pg C compared to simulations in which CO2 is held constant at modern values. CO2 effects tend to increase burnt area, fire fluxes and therefore carbon losses in arid areas, but increase vegetation density and reduce burnt area in wooded areas

What have we learnt from palaeoclimate simulations?

There has been a gradual evolution in the way that palaeoclimate modelling and palaeoenvironmental data are used together to understand how the Earth System works, from an initial and largely descriptive phase through explicit hypothesis testing to diagnosis of underlying mechanisms. Analyses of past climate states are now regarded as integral to the evaluation of climate models, and have become part of the toolkit used to assess the likely realism of future projections. Palaeoclimate assessment has demonstrated that changes in large-scale features of climate that are governed by the energy and water balance show consistent responses to changes in forcing in different climate states, and these consistent responses are reproduced by climate models. However, state-of-the-art models are still largely unable to reproduce observed changes in climate at a regional scale reliably. While palaeoclimate analyses of state-of-the-art climate models suggest an urgent need for model improvement, much work is also needed on extending and improving palaeoclimate reconstructions and quantifying and reducing both numerical and interpretative uncertainties

Assessing the value of seasonal climate forecasts for decision‐making

Seasonal climate forecasts (SCF) can support decision‐making and thus help society cope with and prepare for climate variability and change. The demand for understanding the value and benefits of using SCF in decision‐making processes can be associated with different logics. Two of these would be the need to justify public and private investment in the provision of SCF and demonstrating the gains and benefits of using SCF in specific decision‐making contexts. This paper reviews the main factors influencing how SCF is (or can be) valued in supporting decision‐making and the main methods and metrics currently used to perform such valuations. Our review results in four key findings: (a) there is a current emphasis on economic ex ante studies and the quantification of SCF value; (b) there are fundamental differences in how the value of SCF is defined and estimated across methods and approaches; (c) most valuation methods are unable to capture the differential benefits and risks of using SCF across spatiotemporal scales and groups; and (d) there is limited involvement of the decision‐makers in the valuation process. The paper concludes by providing some guiding principles towards more effective valuations of SCF, notably the need for a wider diversity and integration of methodological approaches. These should particularly embrace ex‐post, qualitative, and participatory approaches which allow co‐evaluation with decision‐makers so that more comprehensive and equitable SCF valuations can be developed in future

Downscaling ECMWF seasonal precipitation forecasts in Europe using the RCA model

The operational performance and usefulness of regional climate models at seasonal time scales are assessed by downscaling an ensemble of global seasonal forecasts. The Rossby Centre RCA regional model was applied to downscale a five-member ensemble from the ECMWF System3 global model in the European Atlantic domain for the period 1981–2001. One month lead time global and regional precipitation predictions were compared over Europe—and particularly over Spain—focusing the study in SON (autumn) dry events. A robust tercile-based probabilistic validation approach was applied to compare the forecasts from global and regional models, obtaining significant skill in both cases, but over a wider area for the later. Finally, we also analyse the performance of a mixed ensemble combining both forecasts

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users.The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model

A verification framework for interannual-to-decadal predictions experiments

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty