Michael Oppenheimer

Assessing dangerous climate change through an update of the Intergovernmental Panel on Climate Change (IPCC) “reasons for concern”

Article 2 of the United Nations Framework Convention on Climate Change [United Nations (1992) http://unfccc.int/resource/docs/convkp/conveng.pdf. Accessed February 9, 2009] commits signatory nations to stabilizing greenhouse gas concentrations in the atmosphere at a level that “would prevent dangerous anthropogenic interference (DAI) with the climate system.” In an effort to provide some insight into impacts of climate change that might be considered DAI, authors of the Third Assessment Report (TAR) of the Intergovernmental Panel on Climate Change (IPCC) identified 5 “reasons for concern” (RFCs). Relationships between various impacts reflected in each RFC and increases in global mean temperature (GMT) were portrayed in what has come to be called the “burning embers diagram.” In presenting the “embers” in the TAR, IPCC authors did not assess whether any single RFC was more important than any other; nor did they conclude what level of impacts or what atmospheric concentrations of greenhouse gases would constitute DAI, a value judgment that would be policy prescriptive. Here, we describe revisions of the sensitivities of the RFCs to increases in GMT and a more thorough understanding of the concept of vulnerability that has evolved over the past 8 years. This is based on our expert judgment about new findings in the growing literature since the publication of the TAR in 2001, including literature that was assessed in the IPCC Fourth Assessment Report (AR4), as well as additional research published since AR4. Compared with results reported in the TAR, smaller increases in GMT are now estimated to lead to significant or substantial consequences in the framework of the 5 “reasons for concern.”

Probabilistic assessment of sea level during the last interglacial stage

With polar temperatures ∼3–5 °C warmer than today, the last interglacial stage (∼125 kyr ago) serves as a partial analogue for 1–2 °C global warming scenarios. Geological records from several sites indicate that local sea levels during the last interglacial were higher than today, but because local sea levels differ from global sea level, accurately reconstructing past global sea level requires an integrated analysis of globally distributed data sets. Here we present an extensive compilation of local sea level indicators and a statistical approach for estimating global sea level, local sea levels, ice sheet volumes and their associated uncertainties. We find a 95% probability that global sea level peaked at least 6.6 m higher than today during the last interglacial; it is likely (67% probability) to have exceeded 8.0 m but is unlikely (33% probability) to have exceeded 9.4 m. When global sea level was close to its current level (≥-10 m), the millennial average rate of global sea level rise is very likely to have exceeded 5.6 m kyr-1 but is unlikely to have exceeded 9.2 m kyr-1. Our analysis extends previous last interglacial sea level studies by integrating literature observations within a probabilistic framework that accounts for the physics of sea level change. The results highlight the long-term vulnerability of ice sheets to even relatively low levels of sustained global warming.The Last Interglacial (LIG) stage (ca. 130 115 ka), with polar temperatures likely 3 5◦C warmer than today, serves as a partial analogue for low-end future warming scenarios. Multiple indicators suggest that LIG global sea level (GSL) was higher than at present; based upon a small set of local sea level indicators, the Intergovernmental Panel on Climate Change (IPCC)s Fourth Assessment Report inferred an elevation of approximately 4 6 m. While this estimate may be correct, it is based upon overly simplistic assumptions about the relationship between local sea level and global sea level. Sea level is often viewed as a simple function of changing global ice volume. This perspective neglects local variability, which arises from several factors, including the distortion of the geoid and the elastic and isostatic deformation of the solid Earth by shifting ice masses. Accurate reconstruction of past global and local sea levels, as well as ice sheet volumes, therefore requires integrating globally distributed data sets of local sea level indicators. To assess the robustness of the IPCCs global estimate and search for patterns in local sea level that are diagnostic of meltwater sources, we have compiled a comprehensive database that includes a variety of local sea level indicators from 47 localities, as well as a global sea level record derived from oxygen isotopes. We generate a global synthesis from these data using a novel statistical approach that couples Gaussian process regression to Markov Chain Monte Carlo simulation of geochronological errors. Our analysis strongly supports the hypothesis that global sea level during the Last Interglacial was higher than today, probably peaking between 6 9 m above the present level. This level is close to that expected from the complete melting of the Greenland Ice Sheet, or from major melting of both the Greenland and West Antarctic Ice Sheets. In the period when sea level was within 10 m of the modern value, the fastest rate of sea level rise sustained for a 1 ky period was likely about 80 110 cm per century. Combined with the evidence for mildly higher temperatures during the LIG, our results highlight the vulnerability of ice sheets to even relatively low levels of sustained global warming.

Fixing a critical climate accounting error

Rules for applying the Kyoto Protocol and national cap-and-trade laws contain a major, but fixable, carbon accounting flaw in assessing bioenergy. The accounting now used for assessing compliance with carbon limits in the Kyoto Protocol and in climate legislation contains a far-reaching but fixable flaw that will severely undermine greenhouse gas reduction goals (1). It does not count CO2 emitted from tailpipes and smokestacks when bioenergy is being used, but it also does not count changes in emissions from land use when biomass for energy is harvested or grown. This accounting erroneously treats all bioenergy as carbon neutral regardless of the source of the biomass, which may cause large differences in net emissions. For example, the clearing of long-established forests to burn wood or to grow energy crops is counted as a 100% reduction in energy emissions despite causing large releases of carbon.

Global warming and the stability of the West Antarctic Ice Sheet

Of todays great ice sheets, the West Antarctic Ice Sheet poses the most immediate threat of a large sea-level rise, owing to its potential instability. Complete release of its ice to the ocean would raise global mean sea level by four to six metres, causing major coastal flooding worldwide. Human-induced climate change may play a significant role in controlling the long-term stability of the West Antarctic Ice Sheet and in determining its contribution to sea-level change in the near future.

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.

Linkages among climate change, crop yields and Mexico–US cross-border migration

Climate change is expected to cause mass human migration, including immigration across international borders. This study quantitatively examines the linkages among variations in climate, agricultural yields, and peoples migration responses by using an instrumental variables approach. Our method allows us to identify the relationship between crop yields and migration without explicitly controlling for all other confounding factors. Using state-level data from Mexico, we find a significant effect of climate-driven changes in crop yields on the rate of emigration to the United States. The estimated semielasticity of emigration with respect to crop yields is approximately −0.2, i.e., a 10% reduction in crop yields would lead an additional 2% of the population to emigrate. We then use the estimated semielasticity to explore the potential magnitude of future emigration. Depending on the warming scenarios used and adaptation levels assumed, with other factors held constant, by approximately the year 2080, climate change is estimated to induce 1.4 to 6.7 million adult Mexicans (or 2% to 10% of the current population aged 15–65 y) to emigrate as a result of declines in agricultural productivity alone. Although the results cannot be mechanically extrapolated to other areas and time periods, our findings are significant from a global perspective given that many regions, especially developing countries, are expected to experience significant declines in agricultural yields as a result of projected warming.

Model-based assessment of the role of human-induced climate change in the 2005 Caribbean coral bleaching event

Episodes of mass coral bleaching around the world in recent decades have been attributed to periods of anomalously warm ocean temperatures. In 2005, the sea surface temperature (SST) anomaly in the tropical North Atlantic that may have contributed to the strong hurricane season caused widespread coral bleaching in the Eastern Caribbean. Here, we use two global climate models to evaluate the contribution of natural climate variability and anthropogenic forcing to the thermal stress that caused the 2005 coral bleaching event. Historical temperature data and simulations for the 1870–2000 period show that the observed warming in the region is unlikely to be due to unforced climate variability alone. Simulation of background climate variability suggests that anthropogenic warming may have increased the probability of occurrence of significant thermal stress events for corals in this region by an order of magnitude. Under scenarios of future greenhouse gas emissions, mass coral bleaching in the Eastern Caribbean may become a biannual event in 20–30 years. However, if corals and their symbionts can adapt by 1–1.5°C, such mass bleaching events may not begin to recur at potentially harmful intervals until the latter half of the century. The delay could enable more time to alter the path of greenhouse gas emissions, although long-term “committed warming” even after stabilization of atmospheric CO2 levels may still represent an additional long-term threat to corals.

Climate change increases risk of plant invasion in the Eastern United States

Invasive plant species threaten native ecosystems, natural resources, and managed lands worldwide. Climate change may increase risk from invasive plant species as favorable climate conditions allow invaders to expand into new ranges. Here, we use bioclimatic envelope modeling to assess current climatic habitat, or lands climatically suitable for invasion, for three of the most dominant and aggressive invasive plants in the southeast United States: kudzu (Pueraria lobata), privet (Ligustrum sinense; L. vulgare), and cogongrass (Imperata cylindrica). We define climatic habitat using both the Maxent and Mahalanobis distance methodologies, and we define the best climatic predictors based on variables that best ‘constrain’ species distributions and variables that ‘release’ the most land area if excluded. We then use an ensemble of 12 atmosphere-ocean general circulation models to project changes in climatic habitat for the three invasive species by 2100. The combined methodologies, predictors, and models produce a robust assessment of invasion risk inclusive of many of the approaches typically used individually to assess climate change impacts. Current invasion risk is widespread in southeastern states for all three species, although cogongrass invasion risk is more restricted to the Gulf Coast. Climate change is likely to enable all three species to greatly expand their ranges. Risk from privet and kudzu expands north into Ohio, Pennsylvania, New York, and New England states by 2100. Risk from cogongrass expands as far north as Kentucky and Virginia. Heightened surveillance and prompt eradication of small pockets of invasion in northern states should be a management priority.

The effectiveness of cool and green roofs as urban heat island mitigation strategies

Mitigation of the urban heat island (UHI) effect at the city-scale is investigated using the Weather Research and Forecasting (WRF) model in conjunction with the Princeton Urban Canopy Model (PUCM). Specifically, the cooling impacts of green roof and cool (white/high-albedo) roof strategies over the Baltimore-Washington metropolitan area during a heat wave period (7 June?10 June 2008) are assessed using the optimal set-up of WRF-PUCM described in the companion paper by Li and Bou-Zeid (2014). Results indicate that the surface UHI effect (defined based on the urban?rural surface temperature difference) is reduced significantly more than the near-surface UHI effect (defined based on urban?rural 2 m air temperature difference) when these mitigation strategies are adopted. In addition, as the green and cool roof fractions increase, the surface and near-surface UHIs are reduced almost linearly. Green roofs with relatively abundant soil moisture have comparable effect in reducing the surface and near-surface UHIs to cool roofs with an albedo value of 0.7. Significant indirect effects are also observed for both green and cool roof strategies; mainly, the low-level advection of atmospheric moisture from rural areas into urban terrain is enhanced when the fraction of these roofs increases, thus increasing the humidity in urban areas. The additional benefits or penalties associated with modifications of the main physical determinants of green or cool roof performance are also investigated. For green roofs, when the soil moisture is increased by irrigation, additional cooling effect is obtained, especially when the ?unmanaged? soil moisture is low. The effects of changing the albedo of cool roofs are also substantial. These results also underline the capabilities of the WRF-PUCM framework to support detailed analysis and diagnosis of the UHI phenomenon, and of its different mitigation strategies.

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]