Precipitation is a primary input for hydrologic, agricultural, and engineering models, so making accurate estimates of it across the landscape is critically important. While the distribution of in-situ measurements of precipitation can lead to challenges in spatial interpolation, gridded precipitation information is designed to produce a full coverage product. In this study, we compare daily precipitation accumulations from the ERA5 Global Reanalysis (hereafter ERA5) and the US Global Historical Climate Network (hereafter GHCN) across the northeastern United States. We find that both the distance from the Atlantic Coast and elevation difference between ERA5 estimates and GHCN observations affect precipitation relationships between the two datasets. ERA5 has less precipitation along the coast than GHCN observations but more precipitation inland. Elevation differences between ERA5 and GHCN observations are positively correlated with precipitation differences. Isolated GHCN stations on mountain peaks, with elevations well above the ERA5 model grid elevation, have much higher precipitation. Summer months (June, July, and August) have slightly less precipitation in ERA5 than GHCN observations, perhaps due to the ERA5 convective parameterization scheme. The heavy precipitation accumulation above the 90th, 95th, and 99th percentile thresholds are very similar for ERA5 and the GHCN. We find that daily precipitation in the ERA5 dataset is comparable to GHCN observations in the northeastern United States and its gridded spatial continuity has advantages over in-situ point precipitation measurements for regional modeling applications.

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APRIL 2015 AMERICAN METEOROLOGICAL SOCIETY | 537 W ith frequent references in the media to climate change, the public often requests information on climate and its impacts. Local field offices of the National Oceanic and Atmospheric Administration (NOAA)'s National Weather Service (NWS) encounter numerous climate-related questions, such as those related to expected weather in upcoming seasons, the causes of drought and the relationship to climate change, as well as the impacts of El Niño on snowpack. Many industries such as energy, agriculture, agribusiness, transportation, and natural resource management integrate climate information into their planning and operating procedures on a regular basis. In addition, significant changes in national and international policies regulating actions of industrial enterprises require the use of scientifically sound climate information. In the United States, one such driver is the June 2013 President's Climate Action Plan (www.whitehouse.gov/sites/default/files /image/president27sclimateactionplan.pdf), which states that "[t]he Administration will continue to lead in advancing the science of climate measurement and adaptation and the development of tools for climaterelevant decision making by focusing on increasing the availability, accessibility, and utility of relevant scientific tools and information."