Christopher M. Little

Probabilistic 21st and 22nd Century Sea-Level Projections at a Global Network of Tide-Gauge Sites

Sea-level rise due to both climate change and non-climatic factors threatens coastal settlements, infrastructure, and ecosystems. Projections of mean global sea-level (GSL) rise provide insufficient information to plan adaptive responses; local decisions require local projections that accommodate different risk tolerances and time frames and that can be linked to storm surge projections. Here we present a global set of local sea-level (LSL) projections to inform decisions on timescales ranging from the coming decades through the 22nd century. We provide complete probability distributions, informed by a combination of expert community assessment, expert elicitation, and process modeling. Between the years 2000 and 2100, we project a very likely (90% probability) GSL rise of 0.5–1.2 m under representative concentration pathway (RCP) 8.5, 0.4–0.9 m under RCP 4.5, and 0.3–0.8 m under RCP 2.6. Site-to-site differences in LSL projections are due to varying non-climatic background uplift or subsidence, oceanographic effects, and spatially variable responses of the geoid and the lithosphere to shrinking land ice. The Antarctic ice sheet (AIS) constitutes a growing share of variance in GSL and LSL projections. In the global average and at many locations, it is the dominant source of variance in late 21st century projections, though at some sites oceanographic processes contribute the largest share throughout the century. LSL rise dramatically reshapes flood risk, greatly increasing the expected number of “1-in-10” and “1-in-100” year events.

Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Climate Change: New Dimensions in Disaster Risk, Exposure, Vulnerability, and Resilience

Executive Summary Disaster signifies extreme impacts suffered when hazardous physical events interact with vulnerable social conditions to severely alter the normal functioning of a community or a society (high confidence) . Social vulnerability and exposure are key determinants of disaster risk and help explain why non-extreme physical events and chronic hazards can also lead to extreme impacts and disasters, while some extreme events do not. Extreme impacts on human, ecological, or physical systems derive from individual extreme or non-extreme events, or a compounding of events or their impacts (for example, drought creating the conditions for wildfire, followed by heavy rain leading to landslides and soil erosion). [1.1.2.1, 1.1.2.3, 1.2.3.1, 1.3] Management strategies based on the reduction of everyday or chronic risk factors and on the reduction of risk associated with non-extreme events, as opposed to strategies based solely on the exceptional or extreme, provide a mechanism that facilitates the reduction of disaster risk and the preparation for and response to extremes and disasters (high confidence) . Effective adaptation to climate change requires an understanding of the diverse ways in which social processes and development pathways shape disaster risk. Disaster risk is often causally related to ongoing, chronic, or persistent environmental, economic, or social risk factors. [1.1.2.2, 1.1.3, 1.1.4.1, 1.3.2] Development practice, policy, and outcomes are critical to shaping disaster risk (high confidence) . Disaster risk may be increased by shortcomings in development. Reductions in the rate of depletion of ecosystem services, improvements in urban land use and territorial organization processes, the strengthening of rural livelihoods, and general and specific advances in urban and rural governance advance the composite agenda of poverty reduction, disaster risk reduction, and adaptation to climate change. [1.1.2.1, 1.1.2.2, 1.1.3, 1.3.2, 1.3.3]

Geographic Variability of Sea-Level Change

Local sea-level changes differ significantly from global-mean sea-level change as a result of (1) non-climatic, geological background processes; (2) atmosphere/ocean dynamics; and (3) the gravitational, elastic, and rotational “fingerprint” effects of ice and ocean mass redistribution. Though the research communities working on these different effects each have a long history, the integration of all these different processes into interpretations of past changes and projections of future change is an active area of research. Fully characterizing the past contributions of these processes requires information from sources covering a range of timescales, including geological proxies, tide-gauge observations from the last ~3 centuries, and satellite-altimetry data from the last ~2 decades. Local sea-level rise projections must account for the different spatial patterns of different processes, as well as potential correlations between different drivers.

New York City Panel on Climate Change 2015 Report. Chapter 2: Sea level rise and coastal storms.

New York City’s low-lying areas are home to a large population, critical infrastructure, and iconic natural, economic and cultural resources. These areas are currently exposed to coastal flooding by warmseason tropical storms such as Hurricane Sandya (Box 2.1) and cold-season nor’easters. Sea level rise increases the frequency and intensity of coastal flooding. For example, the 12 inches of sea level rise in New York City since 1900 may have expanded Hurricane Sandy’s flood area by approximately 25 square miles, flooding the homes of more than 80,000 additional peopleb in New York and New Jersey alone (Climate Central 2013, as reported in Miller et al., 2013; see also Chapter 3, NPCC, 2015). This chapter presents an overview of observed sea level rise and coastal storms for the New York metropolitan region, sea level rise projection methods and results, coastal storm projections, and recommendations for future research.

Toward a new generation of ice sheet models

Large ice sheets, such as those presently covering Greenland and Antarctica, are important in driving changes of global climate and sea level. Yet numerical models developed to predict climate change and ice sheet-driven sea level fluctuations have substantial limitations: Poorly represented physical processes in the ice sheet component likely lead to an underestimation of sea level rise forced by a warming climate. The resultant uncertainty in sea level projections, and the implications for climate policy, have been widely discussed since the publication of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) [IPCC, 2007]. The assessment report notes that current models do not include “the full effects of changes in ice sheet flow, because a basis in published literature is lacking.” The report also notes that the understanding of rapid dynamical changes in ice flow “is too limited to assess their likelihood or provide a best estimate or an upper bound for sea level rise.”

Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections

The representative concentration pathway (RCP) simulations included in phase 5 of the Coupled Model Intercomparison Project (CMIP5) quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ because of 1) forcing, 2) the representation of the climatesystemin atmosphere‐ocean generalcirculation models (AOGCMs), and 3)the presence of unforced (internal) variability. Global and local sea level rise projections derived from these simulations, and the emergence of distinct responses to the four RCPs depend on the relative magnitude of these sources of uncertainty at different lead times. Here, the uncertainty in CMIP5 projections of sea level is partitioned at globalandlocal scales,using a164-member ensembleof twenty-first-centurysimulations. Local projectionsat New York City (NYSL) are highlighted. The partition between model uncertainty, scenario uncertainty, and internal variability in global mean sea level (GMSL) is qualitatively consistent with that of surface air temperature, with model uncertainty dominant for most of the twenty-first century. Locally, model uncertainty is dominant through 2100, with maxima in the North Atlantic and the Arctic Ocean. The model spread is driven largely by 4 of the 16 AOGCMs in the ensemble; these models exhibit outlying behavior in all RCPs and in both GMSL and NYSL. The magnitude of internal variability varies widely by location and across models, leading to differences of several decades in the local emergence of RCPs. The AOGCM spread, and its sensitivity to model exclusion and/or weighting, has important implications for sea level assessments, especially if a local risk management approach is utilized.

New York City Panel on Climate Change 2015 Report Chapter 4: Dynamic Coastal Flood Modeling

Philip Orton,1,a Sergey Vinogradov,2,a Nickitas Georgas,1,a Alan Blumberg,1,a Ning Lin,3 Vivien Gornitz,4 Christopher Little,5 Klaus Jacob,6 and Radley Horton4 1Stevens Institute of Technology, Hoboken, NJ. 2Earth Resources Technology/National Atmospheric and Oceanic Administration, Silver Spring, MD. 3Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ. 4Columbia University Center for Climate Systems Research, New York, NY. 5Atmospheric and Environmental Research, Lexington, MA. 6Lamont-Doherty Earth Observatory, Palisades, NY.

Probabilistic framework for assessing the ice sheet contribution to sea level change

Previous sea level rise (SLR) assessments have excluded the potential for dynamic ice loss over much of Greenland and Antarctica, and recently proposed “upper bounds” on Antarctica’s 21st-century SLR contribution are derived principally from regions where present-day mass loss is concentrated (basin 15, or B15, drained largely by Pine Island, Thwaites, and Smith glaciers). Here, we present a probabilistic framework for assessing the ice sheet contribution to sea level change that explicitly accounts for mass balance uncertainty over an entire ice sheet. Applying this framework to Antarctica, we find that ongoing mass imbalances in non-B15 basins give an SLR contribution by 2100 that: (i) is comparable to projected changes in B15 discharge and Antarctica’s surface mass balance, and (ii) varies widely depending on the subset of basins and observational dataset used in projections. Increases in discharge uncertainty, or decreases in the exceedance probability used to define an upper bound, increase the fractional contribution of non-B15 basins; even weak spatial correlations in future discharge growth rates markedly enhance this sensitivity. Although these projections rely on poorly constrained statistical parameters, they may be updated with observations and/or models at many spatial scales, facilitating a more comprehensive account of uncertainty that, if implemented, will improve future assessments.

Large-Scale Oceanographic Constraints on the Distribution of Melting and Freezing under Ice Shelves

Previous studies suggest that ice shelves experience asymmetric melting and freezing. Topography may constrain oceanic circulation (and thus basal melt–freeze patterns) through its influence on the potential vorticity (PV) field. However, melting and freezing induce a local circulation that may modify locations of heat transport to the ice shelf. This paper investigates the influence of buoyancy fluxes on locations of melting and freezing under different bathymetric conditions. An idealized set of numerical simulations (the “decoupled” simulations) employs spatially and temporally fixed diapycnal fluxes. These experiments, in combination with scaling considerations, indicate that while flow in the interior is governed by large-scale topographic gradients, recirculation plumes dominate near buoyancy fluxes. Thermodynamically decoupled models are then compared to those in which ice–ocean heat and freshwater fluxes are driven by the interior flow (the “coupled” simulations). Near the southern boundary, strong cyclonic flow forced by melt-induced upwelling drives inflow and melting to the east. Recirculation is less evident in the upper water column, as shoaling of meltwater-freshened layers dissipates the dynamic influence of buoyancy forcing, yet freezing remains intensified in the west. In coupled simulations, the flow throughout the cavity is relatively insensitive to bathymetry; stratification, the slope of the ice shelf, and strong, meridionally distributed buoyancy fluxes weaken its influence.

New York City Panel on Climate Change 2015 ReportChapter 1: Climate Observations and Projections

Radley Horton,1,a Daniel Bader,1,a Yochanan Kushnir,2 Christopher Little,3 Reginald Blake,4 and Cynthia Rosenzweig5 1Columbia University Center for Climate Systems Research, New York, NY. 2Ocean and Climate Physics Department, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY. 3Atmospheric and Environmental Research, Lexington, MA. 4Physics Department, New York City College of Technology, CUNY, Brooklyn, NY. 5Climate Impacts Group, NASA Goddard Institute for Space Studies; Center for Climate Systems Research, Columbia University Earth Institute, New York, NY