The sensitivity of southeast pacific heat distribution to local and remote changes in ocean properties

AbstractThe Southern Ocean features ventilation pathways that transport surface waters into the subsurface thermocline on time scales from decades to centuries, sequestering anomalies of heat and carbon away from the atmosphere and thereby regulating the rate of surface warming. Despite its importance for climate sensitivity, the factors that control the distribution of heat along these pathways are not well understood. In this study, we use an observationally constrained, physically consistent global ocean model to examine the sensitivity of heat distribution in the recently ventilated subsurface Pacific (RVP) sector of the Southern Ocean to changes in ocean temperature and salinity. First, we define the RVP using numerical passive tracer release experiments that highlight the ventilation pathways. Next, we use an ensemble of adjoint sensitivity experiments to quantify the sensitivity of the RVP heat content to changes in ocean temperature and salinity. In terms of sensitivities to surface ocean properties, we find that RVP heat content is most sensitive to anomalies along the Antarctic Circumpolar Current (ACC), upstream of the subduction hotspots. In terms of sensitivities to subsurface ocean properties, we find that RVP heat content is most sensitive to basin-scale changes in the subtropical Pacific Ocean, around the same latitudes as the RVP. Despite the localized nature of mode water subduction hotspots, changes in basin-scale density gradients are an important controlling factor on heat distribution in the southeast Pacific.</jats:p

Seasonal Arctic sea ice forecasting with probabilistic deep learning

Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical benchmarks at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss

Half a degree additional warming, prognosis and projected impacts (HAPPI): Background and experimental design

Abstract. The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and on related global greenhouse-gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the half a degree additional warming, projections, prognosis and impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the present day in worlds that are 1.5 and 2.0 °C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of impact models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments under low-emission scenarios.Large ensembles of simulations (&gt;  50 members) of atmosphere-only models for three time slices are proposed, each a decade in length: the first being the most recent observed 10-year period (2006–2015), the second two being estimates of a similar decade but under 1.5 and 2 °C conditions a century in the future. We use the representative concentration pathway 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5 °C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2 °C scenario. </jats:p

Evidence gaps and biodiversity threats facing the marine environment of the United Kingdom’s Overseas Territories

Understanding the evidence base and identifying threats to the marine environment is critical to ensure cost-effective management and to identify priorities for future research. The United Kingdom (UK) government is responsible for approximately 2% of the world’s oceans, most of which belongs to its 14 Overseas Territories (UKOTs). Containing biodiversity of global significance, and far in excess of the UK mainland’s domestic species, there has recently been a strong desire from many of the UKOTs, the UK Government, and NGOs to improve marine management in these places. Implementing evidence-based marine policy is, however, challenged by the disparate nature of scientific research in the UKOTs and knowledge gaps about the threats they face. Here, we address these issues by systematically searching for scientific literature which has examined UKOT marine biodiversity and by exploring publicly available spatial threat data. We find that UKOT marine biodiversity has received consistent, but largely low, levels of scientific interest, and there is considerable geographical and subject bias in research effort. Of particular concern is the lack of research focus on management or threats to biodiversity. The extent and intensity of threats vary amongst and within the UKOTs but unsurprisingly, climate change associated threats affect them all and direct human stressors are more prevalent in those with higher human populations. To meet global goals for effective conservation and management, there is an urgent need for additional and continued investment in research and management in the Overseas Territories, particularly those that have been of lesser focus