Ground-truth of a 1-km downscaled NLDAS air temperature product using the New York City Community Air Survey

摘要

Ground-truthing results are presented for a new 1-km air temperature product down-scaled for New York City (NYC) from similar to 12 km North American Land Data Assimilation System (NLDAS) air temperature data using 1 km moderate resolution imaging spectroradiometer surface temperature data. The downscaled product was compared against a unique highly spatially resolved ground-level ambient air temperature dataset collected through the New York City Community Air Survey (NYCCAS), a neighborhood level air pollution and temperature monitoring network, for the years 2009 and 2010. This work focuses on the spatial variation in daily minimum temperatures within the five counties that comprise NYC (similar to 784 km(2)). Overall, the downscaled daily minimum temperature was well correlated with ground station data, with NYCCAS minimum temperatures being slightly higher. Minimum temperature R-2 values were 0.9 and 0.92, and mean absolute errors were 0.69 degrees C and 0.86 degrees C for years 2009 and 2010, respectively. The smallest differences between NYCCAS and the downscaled data were seen at lower temperatures, in less densely urbanized areas, and in areas with higher vegetative cover, suggesting systematic bias in the downscaled data related to land-use. The 1-km dataset discerned neighborhood level temperature differences in high-density urban situations with heterogeneous land cover. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.