Coastlines globally are increasingly being illuminated with Artificial Light At Night (ALAN) from various urban infrastructures such as houses, offices, piers, roads, ports and dockyards. Artificial sky glow can now be detected above 22% of the world's coasts nightly and will dramatically increase as coastal human populations more than double by the year 2060. One of the clearest demonstrations that we have entered another epoch, the urbanocene, is the prevalence of ALAN visible from space. Photobiological life history adaptations to the moon and sun are near ubiquitous in the surface ocean (0-200m), such that cycles and gradients of light intensity and spectra are major structuring factors in marine ecosystems. The potential for ALAN to reshape the ecology of coastal habitats by interfering with natural light cycles and the biological processes they inform is increasingly recognized and is an emergent focus for research.This dataset is derived from two primary satellite data sources: an artificial night sky brightness world atlas (Falchi et al., 2016) and an in-water Inherent Optical Property (Lee et al., 2002) dataset derived from ESA's Ocean Colour Climate Change Initiative (OC-CCI https://www.oceancolour.org/).These primary datasets are both used in conjunction with in-situ derived measurements and radiative transfer modelling in order to quantify the critical depth (Zc) to which biologically relevant ALAN penetrates throughout the global ocean's estuarine, coastal and near shore regions, in particular the area defined by an individual country's Exclusive Economic Zone.The critical depth is defined as the depth at which the modelled light level in the water column, illuminated by ALAN, drops below 0.102 µWm-2, the minimum irradiance of white light that elicits diel vertical migration in adult female Calanus copepods (Batnes et al., 2015). This is function of incident ALAN irradiance at the surface as well as the in-water transparency (governed by in-water optically active constituents).This dataset is an updated version of https://doi.pangaea.de/10.1594/PANGAEA.929749 and has improved geolocation, land masking, spectral thresholding and spatial coverage.

Filenaming conventions:(1) In-water_clear-sky_ALAN_Zc_Month-MM_aaS_bbN_ccW_ddE_AAA.ncwhere MM is month of the year (01 - January)aa, bb, cc, dd define the regional box of interest where:aa is the minimum latitudebb is the maximum latitudecc is the minimum longitudedd is the maximum longitudeAAA is a free-form descriptor of the geographical region of interest(2)Derived dataset from the primary data by Lee et al., 2002 publication algorithm using the primary dataset of Sathyendranath et al., 2019 (the CCI dataset):ESACCI-OC-MAPPED-CLIMATOLOGY-1M_MONTHLY_4km_GEO_PML_OCx_QAA-Kd-mm-fv4.0.ncwhere mm is the month of the year (01 - January).They contain the diffuse attenuation coefficient Kd at three broadband wavelengths, global, at 4 km resolution in geometric projection.