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While current rates of sea level rise and associated coastal flooding in the New York City region appear to be manageable by stakeholders responsible for communications, energy, transportation, and water infrastructure, projections for sea level rise and associated flooding in the future, especially those associated with rapid icemelt of the Greenland and West Antarctic Icesheets, may be beyond the range of current capacity because an extreme event might cause flooding and inundation beyond the planning and preparedness regimes. This paper describes the comprehensive process, approach, and tools developed by the New York City Panel on Climate Change (NPCC) in conjunction with the region's stakeholders who manage its critical infrastructure, much of which lies near the coast. It presents the adaptation approach and the sealevel rise and storm projections related to coastal risks developed through the stakeholder process. Climate change adaptation planning in New York City is characterized by a multijurisdictional stakeholder-scientist process, state-of-the-art scientific projections and mapping, and development of adaptation strategies based on a risk-management approach.

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Accurate estimates of long-term land surface temperature (T s) and near-surface air temperature (T a) at finer spatio-temporal resolutions are crucial for surface energy budget studies, for environmental applications, for land surface model data assimilation, and for climate change assessment and its associated impacts. The Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Aqua satellite provide a unique opportunity to estimate both temperatures twice daily at the global scale. In this study, differences between T a and T s were assessed locally over regions of North America from 2009 to 2013 using ground-based observations covering a wide range of geographical, topographical, and land cover types. The differences between T a and T s during non-precipitating conditions are generally 2-3 times larger than precipitating conditions. However, these differences show noticeable diurnal and seasonal variations. The differences between T a and T s were also investigated at the global scale using the AIRS estimates under clear-sky conditions for the period 2003-2015. The tropical regions showed about 5-20 C warmer T s than T a during the daytime , whereas opposite characteristics (about 2-5 C cooler T s than T a) are found over most parts of the globe during the night-time. Additionally, T s estimates from the AIRS and the MODIS sensors were inter-compared. Although large-scale features of T s were essentially similar for both sensors, considerable differences in magnitudes were observed (>6 C over mountainous regions). Finally, T a and T s estimates from the AIRS and MODIS sensors were validated against ground-based observations for the period of 2009-2013. The error characteristics notably varied with ground stations and no clear evidence of their dependency on land cover types or elevation was detected. However, the MODIS-derived T s estimates generally showed larger biases and higher errors compared to the AIRS-derived estimates. The biases and errors increased steadily when the spatial resolution of the MODIS estimates changed from finer 3 to coarser. These results suggest that representativeness error should be properly accounted for when validating satellite-based temperature estimates with point observations.