Satellite passive ocean color instruments have provided an unbroken ∼20-year record of global ocean plankton properties, but this measurement approach has inherent limitations in terms of spatial-temporal sampling and ability to resolve vertical structure within the water column. These limitations can be addressed by coupling ocean color data with measurements from a spaceborne lidar. Airborne lidars have been used for decades to study ocean subsurface properties, but recent breakthroughs have now demonstrated that plankton properties can be measured with a satellite lidar. The satellite lidar era in oceanography has arrived. Here, we present a review of the lidar technique, its applications in marine systems, a perspective on what can be accomplished in the near future with an ocean- and atmosphere-optimized satellite lidar, and a vision for a multiplatform virtual constellation of observational assets that would enable a three-dimensional reconstruction of global ocean ecosystems.

Ammonia measurements from a vehicle‐based, mobile open‐path sensor and those from aircraft were compared with Tropospheric Emission Spectrometer (TES) NH₃ columns at the pixel scale during the NASA Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality field experiment. Spatial and temporal mismatches were reduced by having the mobile laboratory sample in the same areas as the TES footprints. To examine how large heterogeneities in the NH₃ surface mixing ratios may affect validation, a detailed spatial survey was performed within a single TES footprint around the overpass time. The TES total NH₃ column above a single footprint showed excellent agreement with the in situ total column constructed from surface measurements with a difference of 2% (within the combined measurement uncertainties). The comparison was then extended to a TES transect of nine footprints where aircraft data (5–80 ppbv) were available in a narrow spatiotemporal window (<10 km, <1 h). The TES total NH₃ columns above the nine footprints agreed to within 6% of the in situ total columns derived from the aircraft‐based measurements. Finally, to examine how TES captures surface spatial gradients at the interpixel scale, ground‐based, mobile measurements were performed directly underneath a TES transect, covering nine footprints within ±1.5 h of the overpass. The TES total columns were strongly correlated (R² = 0.82) with the median NH₃ mixing ratios measured at the surface. These results provide the first in situ validation of the TES total NH₃ column product, and the methodology is applicable to other satellite observations of short‐lived species at the pixel scale.

Ocean lidar attenuation and scattering parameters were derived from a high-spectral-resolution lidar (HSRL) using two different retrieval techniques. The first used the standard HSRL retrieval, and the second used only the total backscatter channel and a perturbation retrieval (PR). The motivation is to evaluate differences between the two techniques that would affect the decision of whether to use a simple backscatter lidar or a more complex HSRL in future applications. For the data set investigated, the attenuation coefficient from the PR was an average of 11% lower than that from the HSRL. The PR estimate of the scattering parameter decreased with depth relative to the HSRL estimate, although the overall bias was zero as a result of the calibration procedure. Near the surface, the coefficient of variability in both estimates of attenuation and in HSRL estimates of scattering were around 5%, but that in the PR estimate of scattering was over 10%. At greater depths, the variability increases for all of the profile parameters. The correlation between the two estimates of attenuation coefficient was 0.7. The correlation between scattering parameters was > 0.8 near the surface, but decreased to 0.4 at a depth of around 20 m. Overall, the PR performed better relative to the HSRL in offshore waters than in nearshore waters.

Spaceborne lidar observations have great potential to provide accurate global estimates of the aerosol direct radiative effect (DRE) in both clear and cloudy conditions. However, comparisons between observations from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) and multiple years of Atmospheric Radiation Measurement (ARM) program's ground‐based Raman lidars (RL) show that CALIPSO does not detect all radiatively significant aerosol, i.e., aerosol that directly modifies the Earth's radiation budget. We estimated that using CALIPSO observations results in an underestimate of the magnitude of the global mean aerosol DRE by up to 54%. The ARM RL data sets along with NASA Langley airborne high spectral resolution lidar data from multiple field campaigns are used to derive the detection sensitivity required to accurately resolve the aerosol DRE. This shows that a lidar with a backscatter coefficient detection sensitivity of about 1–2 × 10⁻⁴ km⁻¹ sr⁻¹ at 532 nm would resolve all the aerosol needed to derive the DRE to within 1%.

Earth observing systems have proven to be a unique source of long-term synoptic information on numerous physical, chemical and biological parameters on a global scale. Merging this information for integrated studies that peruse key questions about the ocean-atmosphere interface is, however, very challenging. Such studies require interdisciplinary frameworks and novel insights into ways to address the problem. We present here a perspective review on how current and emerging remote sensing technologies could help address two scientific questions within the Surface Ocean-Lower Atmosphere Study (SOLAS) science plan: (1) to what extent does upper-ocean biology affect the composition and radiative properties of the marine boundary layer; and (2) to what extent does upper-ocean turbulence drive fluxes of mass and energy at the air-sea interface. We provide a thorough review of how these questions have been addressed and discuss novel potential avenues using multiplatform space-borne missions, from visible to microwave, active and passive sensors.

The year 2023 marked the tenth anniversary of the first published description of global ocean plankton stocks based on measurements from a satellite lidar. Diverse studies have since been conducted to further refine and validate the lidar retrievals and use them to discover new characteristics of plankton seasonal dynamics and marine animal migrations, as well as evaluate geophysical products from traditional passive ocean color sensors. Surprisingly, all of these developments have been achieved with lidar instruments not designed for ocean applications. Over this same decade, we have witnessed unprecedented changes in ocean ecosystems at unexpected rates and driven by a multitude of environmental stressors, with a dominant factor being climate warming. Understanding, predicting, and responding to these ecosystem changes requires a global ocean observing network linking satellite, in situ, and modeling approaches. Inspired by recent successes, we promote here the creation of a lidar global ocean climate record as a key element in this envisioned advanced observing system. Contributing to this record, we announce the development of a new satellite lidar mission with ocean-observing capabilities and then discuss additional technological advances that can be envisioned for subsequent missions. Finally, we discuss how a potential near-term gap in global ocean lidar data might, at least partially, be filled using on-orbit or soon-to-be-launched lidars designed for other disciplinary purposes, and we identify upcoming needs for in situ support systems and science community development.