|Title||Climate Hazard Assessment for Stakeholder Adaptation Planning in New York City|
|Publication Type||Journal Article|
|Year of Publication||2011|
|Authors||Horton, Radley M., Gornitz Vivien, Bader Daniel A., Ruane Alex C., Goldberg Richard, and Rosenzweig Cynthia|
|Journal||Journal of Applied Meteorology and Climatology|
|Pagination||2247 - 2266|
|Keywords||21st-century, circulation model output, ice sheets, ocean circulation, precipitation, satellite, Sea-level rise, simulations, UNCERTAINTY, VARIABILITY|
This paper describes a time-sensitive approach to climate change projections that was developed as part of New York City’s climate change adaptation process and that has provided decision support to stakeholders from 40 agencies, regional planning associations, and private companies. The approach optimizes production of projections given constraints faced by decision makers as they incorporate climate change into long-term planning and policy. New York City stakeholders, who are well versed in risk management, helped to preselect the climate variables most likely to impact urban infrastructure and requested a projection range rather than a single "most likely" outcome. The climate projections approach is transferable to other regions and is consistent with broader efforts to provide climate services, including impact, vulnerability, and adaptation information. The approach uses 16 GCMs and three emissions scenarios to calculate monthly change factors based on 30-yr average future time slices relative to a 30-yr model baseline. Projecting these model mean changes onto observed station data for New York City yields dramatic changes in the frequency of extreme events such as coastal flooding and dangerous heat events. On the basis of these methods, the current 1-in-10-year coastal flood is projected to occur more than once every 3 years by the end of the century and heat events are projected to approximately triple in frequency. These frequency changes are of sufficient magnitude to merit consideration in long-term adaptation planning, even though the precise changes in extreme-event frequency are highly uncertain.