The Beobachtung von Ozean und Wolken–Das Trans ITCZ Experiment (BOWTIE) field campaign investigated how convective storm dynamics interact with the ocean surface to shape the structure of the Atlantic intertropical convergence zone (ITCZ). Conducted aboard the German Research Vessel (R/V) Meteor during August and September 2024, the campaign targeted the full meridional extent of the ITCZ while transiting the tropical Atlantic from east to west. The research was driven by evidence suggesting that storm-scale dynamics is pivotal for shaping the broader structure of the ITCZ and its connection to global circulation patterns and energy transport. BOWTIE featured high-resolution atmospheric and oceanic profiling, with a particular focus on the coupled boundary layers. Observations included cloud and humidity profiles, winds, precipita-tion, sea surface temperature, and upper-ocean physical and biogeochemical properties. A suite of advanced instruments provided vertically resolved cross sections of convective environments and surrounding conditions. BOWTIE was part of the larger international Organized Convection and EarthCARE Studies over the Tropical Atlantic (ORCESTRA) initiative, which coordinated eight campaigns across the Atlantic. During the voyage, the R/V Meteor served as a platform for two additional ORCESTRA campaigns: Soundings and Turbulent eddy measurements in the ITCZ with a Network of Quadcopters (STRINQS), which deployed unmanned aerial vehicles for profiling near-storm environments, and Process Investigation of Clouds and Convective Organization over the Atlantic Ocean (PICCOLO), which brought Colorado State University’s Sea-Pol scanning dual-polarization C-band radar onboard. This article provides an overview of BOWTIE’s scientific goals, campaign design, and observing strategy and presents selected early results from the extensive dataset. The combination of in situ, airborne, and radar measurements offers new insight into how ocean–atmosphere interactions at convective scales shape the ITCZ’s broader structure and behavior. ... Read more

The launch of NASA’s SEASAT satellite in 1978 ushered in the era of radar oceanography. So treasured were the insights provided by this mission that its untimely demise, only three months after launch, did not preclude a legacy of success. In fact, rumors of sabotage sprang up, claiming that the instrument’s remote sensing prowess had jeopardized military assets. Scuttling SEASAT had surely been a matter of national security.

Like plenty of rumors, these, too, were grounded in some truth: SEASAT had shed light on many a mystery, though primarily in the field of physical sciences rather than Cold War conspiracies. Nonetheless, the value of spaceborne oceanography was now clear, and space agencies around the world did not stand idly by. Europe quickly followed suit with its own missions, launching in succession a series of high-resolution imagers, including ERS-1, ERS-2, ENVISAT, and, since 2014, the Sentinel-1 constellation.

Aided by these instruments and many others, the previous decades have been marked by continued scientific advances in the ever-growing field of radar oceanography. Building on that rich heritage, this dissertation aims to advance two distinct (but entwined) subdomains relating to either side of the air-sea interface.

In the first half of this dissertation, Chapters 2 and 3, we investigate the ubiquitous yet often overlooked atmospheric features present in most high-resolution radar images of the ocean. It may seem counterintuitive to study the atmosphere using ocean imagery, but much of the ocean’s surface variability is wind-driven, such that the ocean surface acts as a mirror for the wind field aloft. Till recently, the only systematic use for these atmospheric features had been in studies aiming to relate (an)isotropy to wind directions. But the information content is rich, and much more can be done.

In Chapter 2, we show that significant quantities of atmospheric information remain unexploited. And by using a domain-inspired encoding scheme, we transform high-dimensional radar images into a much lower-dimensional latent space, from which we extract substantially more atmospheric information than preexisting analytical methods.

Then in Chapter 3 we leverage the ever-increasing catalog of Sentinel-1 observations to go one step further. We illustrate that radar-derived atmospheric variables are complementary to state-of-the-art and reference atmospheric estimates. The challenge here is one of persuasion: how to argue that new estimates can complement state-of-the-art estimates when there are insufficient “ground truth” measurements to reconcile discrepancies between them? We aim to address this difficulty through a series of qualitative and quantitative assessments.

In the second half of the dissertation, Chapters 4 and 5, we switch to the other side of the air-sea interface, to investigate different methods of retrieving surface currents—a long-standing challenge in spaceborne oceanography. First, we investigate surface current retrieval for a proposed satellite modification, DopSCA, in Chapter 4. This system could be uniquely capable of retrieving surface current information, but its unorthodox design makes it susceptible to several additional noise sources. One of these noise sources, which we refer to as leakage—the undesired interaction between geometric Doppler, azimuthal backscatter gradients, and the antenna pattern—is investigated to assess its mission-compromising potential. Fortunately, this seems to be a comparatively minor issue.

Then, using a very different instrument in Chapter 5, we consider an alternative surface-current retrieval that incorporates polarimetry. Here we rely on the cross-correlation between wave motion, its radar cross section, and polarization to disentangle the convolved mixture of signals received by the satellite. Simulations and limited real observations illustrate that this approach may be a fruitful avenue towards the long-standing challenge of distinguishing between wave- and current motions. Future systems with additional polarimetric capabilities, such as Harmony or Sentinel-1 Next Generation, stand to gain from this approach in particular.

To summarize, this dissertation investigates radar-based retrieval of heat and momentum transport (from atmospheric convection and surface currents, respectively) by exploiting unique observational properties of a variety of radar satellites. We’ve made progress in both domains: providing the first quantitative and SAR-retrieved air-sea heat-flux estimates, and introducing a new method for surface-current retrieval. But fear not, enough work remains to entertain many radar oceanographers to come ;)
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The interactions between geometrical Doppler, beam pattern, and normalized radar cross section (NRCS) result in the unwanted coupling—leakage—of geometrical Doppler into the perceived geophysical Doppler. Starting from high-resolution synthetic aperture radar (SAR) data we model this leakage for synthesized real aperture radar (RAR) observations of ocean motion. The uncertainty introduced by leakage is ∼1ms−1. Corrections proposed in this work exploit the known interactions between beam pattern and geometric Doppler with NRCS gradients retrieved from simulated low-resolution RAR to estimate and correct for the incurred leakage, reducing the uncertainty to O(0.1ms−1). Further reduction of instantaneous leakage may be achieved through temporal averaging, since the NRCS gradients that cause leakage appear mostly atmosphere induced and decorrelate rapidly. The azimuth resolution and number of independent samples determine a system’s sensitivity to leakage. C-band systems are inherently prone to suffer from greater leakage and worse corrections than their Ku- and Ka-band counterparts. With DopSCA, the propagated effect of leakage is only secondary compared to the pulse-pair uncertainty. In similar systems where pulse-pair uncertainty is suppressed, leakage will dominate instead. ... Read more

Surface velocities measured by Synthetic Aperture Radar (SAR) contain contributions from both mean surface motion—referred to as total surface current (TSC)—and the often more prominent sea-state-induced wave motions. Most modern SAR systems cannot distinguish between these two phenomena, which has stifled TSC retrieval from SAR data for decades. We propose a new framework to separate TSC and wave-motion components by leveraging polarization diversity, exploiting the tendency of each phenomenon to imprint distinct signatures on orthogonal polarizations. Building on a foundational signal model, we derive four source-separation algorithms. To address the model’s theoretical limitations, we introduce empirical extensions via symbolic regression, guided by varying levels of theoretical insight. The developed algorithms are evaluated using simulated C-band SAR data, and benchmarked against a reference geophysical model function (GMF) implementation. Our methods demonstrate comparable overall performance, with errors on the order of O(0.1ms⁻¹), and notably outperform the GMF in resolving kilometer-scale spatial features—a domain where traditional GMFs generally struggle. Preliminary results obtained on TanDEM-X observations confirm the generalizability of our approach. These findings highlight the potential of future SAR missions with polarimetric capabilities, such as Harmony, to achieve high-resolution separation of surface-motion sources using polarization diversity. ... Read more