# Introduction 
This is the documentation for the data paper "Surface and bottom in situ, interpolated hydrographic climatologies of the Northwest Atlantic Ocean for 2000-2024"
## Authors 
Haley Synan, Kimberly Hyde, Colleen Mouw, Chris Melrose, Linus Stoltz, Sarah Salois
## Abstract
New in situ, interpolated hydrographic monthly climatologies were created for the Northeast U.S. Continental Shelf (NES) and surrounding boundary waters for the years 2000 - 2024. The climatologies were created at two depth bins: the surface and bottom, where the surface is defined as above the mixed layer depth, and the bottom includes all data within 10 meters of the bathymetric bottom. Multiple point data sources and data collection methods, including data collected from traditional vertical oceanographic profiles, flowthrough systems, buoys, gliders, and others, were aggregated to create the in situ dataset. Barnes objective analysis was performed to create the monthly climatologies for both temperature and salinity at the two depth bins. Root mean squared error (RMSE) and an uncertainty metric were provided with the interpolation. The uncertainty metric highlights regions and seasons that are data-poor and/or highly variable, and where there is lower confidence in the interpolated values. Results were validated using reference climatologies created using satellite and modeled data with the same spatiotemporal bounds. The surface temperature and salinity climatologies both yield significant correlations when compared to the reference climatologies, with the largest biases observed in temperature climatologies in the onshelf region during the summer months (bias<|1.213| °C). Lower correlations in the winter months are observed during validation of bottom temperature climatologies, due to seasonal sampling bias. The products described here were created as input data for a water mass classification model (Synan et al., in prep), but may also be used for other applications, like anomaly detection or other modeling efforts.

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