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The National Aeronautics and Space Administration (NASA)’s Operation IceBridge (OIB) was a 13-year (2009–2021) airborne mission to survey land and sea ice across the Arctic, Antarctic, and Alaska. Here, we review OIB’s goals, instruments, campaigns, key scientific results, and implications for future investigations of the cryosphere. OIB’s primary goal was to use airborne laser altimetry to bridge the gap in fine-resolution elevation measurements of ice from space between the conclusion of NASA’s Ice, Cloud, and land Elevation Satellite (ICESat; 2003–2009) and its follow-on, ICESat-2 (launched 2018). Additional scientific requirements were intended to contextualize observed elevation changes using a multisensor suite of radar sounders, gravimeters, magnetometers, and cameras. Using 15 different aircraft, OIB conducted 968 science flights, of which 42% were repeat surveys of land ice, 42% were surveys of previously unmapped terrain across the Greenland and Antarctic ice sheets, Arctic ice caps, and Alaskan glaciers, and 16% were surveys of sea ice. The combination of an expansive instrument suite and breadth of surveys enabled numerous fundamental advances in our understanding of the Earth’s cryosphere. For land ice, OIB dramatically improved knowledge of interannual outlet-glacier variability, ice-sheet, and outlet-glacier thicknesses, snowfall rates on ice sheets, fjord and sub-ice-shelf bathymetry, and ice-sheet hydrology. Unanticipated discoveries included a reliable method for constraining the thickness within difficult-to-sound incised troughs beneath ice sheets, the extent of the firn aquifer within the Greenland Ice Sheet, the vulnerability of many Greenland and Antarctic outlet glaciers to ocean-driven melting at their grounding zones, and the dominance of surface-melt-driven mass loss of Alaskan glaciers. For sea ice, OIB significantly advanced our understanding of spatiotemporal variability in sea ice freeboard and its snow cover, especially through combined analysis of fine-resolution altimetry, visible imagery, and snow radar measurements of the overlying snow thickness. Such analyses led to the unanticipated discovery of an interdecadal decrease in snow thickness on Arctic sea ice and numerous opportunities to validate sea ice freeboards from satellite radar altimetry. While many of its data sets have yet to be fully explored, OIB’s scientific legacy has already demonstrated the value of sustained investment in reliable airborne platforms, airborne instrument development, interagency and international collaboration, and open and rapid data access to advance our understanding of Earth’s remote polar regions and their role in the Earth system.

Data from an IceBridge Arctic campaign on April 20, 2010 with the Airborne Topographic Mapper (ATM) and the Land, Vegetation, and Ice Sensor (LVIS) in operation on the same airplane were used in this study. ATM and LVIS lidar waveforms were fitted with Gaussian curves to calculate pulsewidth, peak location, pulse amplitude, and signal baseline. For each waveform, the centroid, skewness, kurtosis, and pulse area were also calculated. Received waveform parameters, such as pulsewidth, pulse amplitude, pulse area, skewness, and kurtosis, show coherent response to variations of geophysical features along an ATM or LVIS profile. These parameters, combined with elevation, were used to identify leads in sea-ice freeboard calculation. The relationship between these parameters and sea-ice freeboard and surface features were studied by comparing the parameters with ATM and LVIS-derived freeboard and coincident Digital Mapping System images which have been used to classify sea-ice surface types such as leads, thin ice, gray ice, and thick ice. An elevation bias of more than 16 cm (peak-to-peak) as a function of laser scanner azimuth was found in the ATM data, and an empirical correction was applied; this correction will improve the ATM shot-to-shot freeboard significantly. The newly derived ATM freeboard was compared with the current IceBridge IDCSI2 freeboard product at National Snow and Ice Data Center (NSIDC) and the freeboard derived from LVIS data. Over the studied area, the mean freeboard is 0.540 $\pm$ 0.091 m for the IDCSI2 at NSIDC, 0.496 $\pm$ 0.062 m for the ATM after empirical elevation correction, and 0.509 $\pm$ 0.048 m for the LVIS. [ABSTRACT FROM PUBLISHER]

Snow accumulation over an ice sheet is the sole mass input, making it a primary measurement for understanding the past, present, and future mass balance. Near-surface frequency-modulated continuous-wave (FMCW) radars image isochronous firn layers recording accumulation histories. The Semiautomated Multilayer Picking Algorithm (SAMPA) was designed and developed to trace annual accumulation layers in polar firn from both airborne and ground-based radars. The SAMPA algorithm is based on the Radon transform (RT) computed by blocks and angular orientations over a radar echogram. For each echogram's block, the RT maps firn segmented-layer features into peaks, which are picked using amplitude and width threshold parameters of peaks. A backward RT is then computed for each corresponding block, mapping the peaks back into picked segmented-layers. The segmented layers are then connected and smoothed to achieve a final layer pick across the echogram. Once input parameters are trained, SAMPA operates autonomously and can process hundreds of kilometers of radar data picking more than 40 layers. SAMPA final pick results and layer numbering still require a cursory manual adjustment to correct noncontinuous picks, which are likely not annual, and to correct for inconsistency in layer numbering. Despite the manual effort to train and check SAMPA results, it is an efficient tool for picking multiple accumulation layers in polar firn, reducing time over manual digitizing efforts. The trackability of good detected layers is greater than 90%. [ABSTRACT FROM PUBLISHER]