Daytime measurements of reflected sunlight in the visible spectrum have been a staple of Earth-viewing radiometers since the advent of the environmental satellite platform. At night, these same optical-spectrum sensors have traditionally been limited to thermal infrared emission, which contains relatively poor information content for many important weather and climate parameters. These deficiencies have limited our ability to characterize the full diurnal behavior and processes of parameters relevant to improved monitoring, understanding and modeling of weather and climate processes. Visible-spectrum light information does exist during the nighttime hours, originating from a wide variety of sources, but its detection requires specialized technology. Such measurements have existed, in a limited way, on USA Department of Defense satellites, but the Suomi National Polar-orbiting Partnership (NPP) satellite, which carries a new Day/Night Band (DNB) radiometer, offers the first quantitative measurements of nocturnal visible and near-infrared light. Here, we demonstrate the expanded potential for nocturnal low-light visible applications enabled by the DNB. Via a combination of terrestrial and extraterrestrial light sources, such observations are always available—expanding many current existing applications while enabling entirely new capabilities. These novel low-light measurements open doors to a wealth of new interdisciplinary research topics while lighting a pathway toward the optimized design of follow-on satellite based low light visible sensors.

Most environmental satellite radiometers use solar reflectance information when it is available during the day but must resort at night to emission signals from infrared bands, which offer poor sensitivity to low-level clouds and surface features. A few sensors can take advantage of moonlight, but the inconsistent availability of the lunar source limits measurement utility. Here we show that the Day/Night Band (DNB) low-light visible sensor on the recently launched Suomi National Polar-orbiting Partnership (NPP) satellite has the unique ability to image cloud and surface features by way of reflected airglow, starlight, and zodiacal light illumination. Examples collected during new moon reveal not only meteorological and surface features, but also the direct emission of airglow structures in the mesosphere, including expansive regions of diffuse glow and wave patterns forced by tropospheric convection. The ability to leverage diffuse illumination sources for nocturnal environmental sensing applications extends the advantages of visible-light information to moonless nights.

Significance: As an unforeseen windfall of its high sensitivity, the Day/Night Band (DNB) low-light visible sensor carried on the Suomi satellite enables global detection of gravity waves in the upper atmosphere at unprecedented subkilometric detail. On moonless nights, the observations provide all-weather viewing of waves as they modulate the nightglow layer located near the mesopause. These waves are launched by a variety of mechanisms ranging from orography to convection, intensifying fronts, and seismic and volcanic events. Wave energy is recognized as the principal driver of upper atmospheric circulation, which in turn influences tropospheric weather patterns. For lack of global observations, information about upper atmospheric wave distribution and character is limited. Here, the DNB begins to fill a critical gap.

This study compared the detection capabilities of the Geostationary Lightning Mapper (GLM) and ground‐based Earth Networks Total Lightning Network (ENL) over the contiguous United States (CONUS) from 25 April 2017 to 5 May 2018. GLM detection efficiency (DE) relative to ENL varied spatially with greater DE in the southeastern United States and lower DE in the Northern Plains. Regions with greater DE were often regions where most intracloud flashes had normal positive polarity, while lower DE regions frequently had inverted negative intracloud. According to the tripolar noninductive charging model, inverted intracloud flashes are lower altitude than normal intracloud flashes. This lower altitude flash may result in greater cloud scattering of the optical lightning signal, which at cloud top is less than the GLM detection limits. DE was generally also greater for greater absolute peak current flashes, which serves as a proxy for optical energy. Additionally, GLM observed flashes to be generally greater in area and duration in the eastern relative to the western CONUS, which may result in the greater DE. GLM DE was also varied with the solar zenith angle as greatest DE occurred at night. ENL DE relative to GLM was varied spatially over CONUS with greater DE over eastern CONUS. ENL DE was greater for flashes of greater GLM flash radiant energy, area, and duration.

The launch of the NASA CloudSat in April 2006 enabled the first satellite-based global observation of vertically resolved cloud information. However, CloudSat’s nonscanning W-band (94 GHz) Cloud Profiling Radar (CPR) provides only a nadir cross section, or “curtain,” of the atmosphere along the satellite ground track, precluding a full three-dimensional (3D) characterization and thus limiting its utility for certain model verification and cloud-process studies. This paper details an algorithm for extending a limited set of vertically resolved cloud observations to form regional 3D cloud structure. Predicated on the assumption that clouds of the same type (e.g., cirrus, cumulus, and stratocumulus) often share geometric and microphysical properties as well, the algorithm identifies cloud-type-dependent correlations and uses them to estimate cloud-base height and liquid/ice water content vertical structure. These estimates, when combined with conventional retrievals of cloud-top height, result in a 3D structure for the topmost cloud layer. The technique was developed on multiyear CloudSat data and applied to Moderate Resolution Imaging Spectroradiometer (MODIS) swath data from the NASA Aqua satellite. Data-exclusion experiments along the CloudSat ground track show improved predictive skill over both climatology and type-independent nearest-neighbor estimates. More important, the statistical methods, which employ a dynamic range-dependent weighting scheme, were also found to outperform type-dependent near-neighbor estimates. Application to the 3D cloud rendering of a tropical cyclone is demonstrated.