The Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) is a NASA Earth Ventures Suborbital Investigation designed to test the hypothesis that oceanic frontogenesis and the kilometer-scale ("submesoscale") instabilities that accompany it make important contributions to vertical exchange of climate and biological variables in the upper ocean. These processes have been difficult to resolve in observations and models. A necessary step toward testing the hypothesis was to make accurate measurements of upper-ocean velocity fields over a broad range of scales and to relate them to the observed variability of vertical transport and surface forcing. To achieve that, we used aircraft-based remote sensing, satellite remote sensing, ships, drifter deployments, and a fleet of autonomous vehicles. This paper will provide a brief overview of the S-MODE measurements, with a special focus on surface current measurements.

The Surface Water and Ocean Topography (SWOT) mission was recommended by the 2007 National Research Council Decadal Survey to expand on previous altimetry missions like TOPEX/Poseidon. Utilizing wide-swath altimetry technology, SWOT aims to achieve complete coverage of the world’s oceans and freshwater bodies through high-resolution elevation measurements. SWOT received approval for implementation in 2016, it was ultimately launched in December 2022, and it is currently delivering preliminary data to the public. The primary instrument in SWOT is the Ka-band Radar Interferometer (KaRIn) which utilizes JPL-developed radar interferometry technology to measure ocean and surface water levels with unprecedented accuracy. This paper focuses on the challenges in designing, testing, and finally commissioning in flight a complex instrument like KaRIn. We also present preliminary flight performance and compare it with ground measurements and simulations. Our analysis indicates that KaRIn meets or exceeds all its requirements, but it has also revealed several interesting and unexpected observations, offering just a glimpse of future scientific discoveries that KaRIn will enable.

The Ka-band wind scatterometry is a relatively new methodology to retrieve ocean surface winds. Modeling the Ka-band ocean surface backscatter is challenging, especially because of the lack of in-situ measurements. In the framework of the NASA Earth Ventures Suborbital-3 Submesoscale Ocean Dynamics Experiment (S-MODE) mission, a new data set of ocean surface backscatter has been collected. These measurements were obtained from a Ka-band Doppler scatterometer (KaBODS) located on the Woods Hole Oceanographic Institution (WHOI) Air-Sea Interaction Tower (ASIT). In this work we present our analysis and findings on the KaBODS backscatter measurements based on the development of a wind empirical backscatter model. We show that the data are characterized by a large variability, which is mainly due to intrinsic geophysical effects. The source of this geophysical variability is currently under investigation.

The Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) is a NASA Earth Ventures Suborbital Investigation designed to test the hypothesis that kilometer-scale (“submesoscale”) ocean eddies make important contributions to vertical exchange of climate and biological variables in the upper ocean. To test this hypothesis, S-MODE will employ a combination of aircraft-based remote sensing measurements of the ocean surface, measurements from ships, measurements from a variety of autonomous oceanographic platforms, and numerical modeling. The field campaign will consist of two month-long intensive operating periods (IOPs) that will be preceded by a smaller-scale pilot experiment to test and improve operational readiness and to compare measurements made from different platforms. The pilot experiment was delayed because of the 2020 coronavirus pandemic, and it is currently planned for October-November 2020.

DopplerScatt is a Ka-band pencil-beam Doppler scatterometer developed under NASA's ESTO Instrument Incubator Program (IIP) to serve as a demonstrator for future spaceborne instruments to measure ocean surface currents and winds simultaneously. We review the capabilities of the Doppler-Scatt instrument, and present results from multiple airborne campaigns. One of our primary results will be the development of Ka-band Geophysical Model Functions (GMFs) to translate backscatter and Doppler measurements into surface winds and currents.

Remote sensing techniques for estimation of high-resolution (sub-mesoscale) ocean surface currents have been of interest to science community for many years. Different radar techniques have been tried, with the most popular being along track interferometry and direct Doppler analysis measurements. Jet Propulsion laboratory (JPL) has recently developed a new airborne Ka-band Doppler scatterometer (DopplerScatt), designed to simultaneously measure ocean surface vector currents and winds. The first validation of DopplerScatt's surface current measurements was performed by the Applied Physics Laboratory (APL) at University of Washington using the C-band airborne ATI SAR collocated measurements during a joint campaign in September 2016. In this paper, we compare the two radial velocity measurements and use a numerical scattering model to aid in understanding the differences.

The motivation for a satellite mission to measure surface winds (stress) and surface currents is described. The mission concept is explained, and a successful example is shown based on simulated satellite sampling of the output a high-resolution ocean model with and without anticipated measurement noise.

Recent evidence suggests that the tropics have expanded over the last few decades by a very rough 10per decade. Until now, understanding the mechanisms of that expansion has been confined to models and proxies because of the unavailability of systematic observations of the large-scale circulation. Scatterometer-derived ocean surface vector winds, provide for the first time, an accurate depiction of the large-scale circulation and allow the study of the Hadley cell evolution through analysis of its surface branch. In this study we determine the extent of the Hadley cell as defined by the subtropical zero-crossing of the zonally-averaged zonal wind component. We use scatterometer observations from a number of missions, covering ~13 years. Our analyses reveal seasonal and interannual variability, as well as a long-term trend for expansion of the Hadley cell width. More interestingly, our results show an apparent discontinuity in the signal when the data source changes from one observing system to another. This raises the question about the significance of the unresolved diurnal signal. Indeed, analyses of observations from tandem missions support this notion. Fortunately, the RapidScat mission makes it possible to resolve, for the first time, the details of the diurnal signal. Our preliminary analyses of the RapidScat observations show the presence of a clear semidiurnal signal in the width of the Hadley cell. This helps explain previously found discrepancies. More importantly, this points to a clear need to understand and resolve the diurnal signal before merging wind observations from different missions to form a consistent climate record.

In this paper, we introduce a reprocessing of the entire SeaWinds on QuikSCAT mission. The goal of the reprocessing is to create a climate data record suitable for climate studies and to incorporate recent algorithm improvements. Three different levels of QuikSCAT data are produced at the Jet Propulsion Laboratory: L1B, geolocated, calibrated, backscatter measurements in chronological order by acquisition time; L2A, backscatter measurements binned into a geographical grid; and L2B, gridded ocean surface wind vectors. This reprocessing only changes the L2A and L2B data; we have not changed the L1B processing at all. We introduce new algorithms used in the L1B to L2A processing and in the L2A to L2B processing. After introducing our new algorithms, we show the validation studies performed to date, which include comparisons to numerical weather products, comparisons to buoy data sets, comparisons to other remote sensing instruments, and spectral considerations.

This article summarizes the data processing of the proposed wide-swath altimetry mission Surface Water and Ocean Topography (SWOT), and more specifically the processing steps up to level 2 for the Ka-band Radar Interferometer (KaRIn), which is a near-nadir viewing bistatic SAR system. A general overview of the proposed processing chains and data products is given, and some particularly challenging processing steps are commented on.

River bathymetry plays a key role in estimating river discharge as well as improving our modeling capabilities of fluvial geomorphology. Genetic algorithm techniques can be used to derive river bed topography using only water surface elevations and the corresponding temporal and spatial rates of change. Each river bathymetric estimate, also referred to as a solution, is modeled as a successive collection of cross-sections, also referred to as genes. An initial population of potential solutions is created from solutions comprised of random cross-sections with depths ranging as deep as the surface height to no depth at all. The population is successively evolved by randomly mutating the depths at a random number of cross-sections. The solutions are selected for the next generation by evaluating their individual fitness. Three varieties of fitness tests are applied to each potential solution: Saint-Venant's 1-D flow equation, flow continuity, and the statistical power-law relationships suggested by Leapold & Maddock[1]. In this manner, an ideal solution is derived.

To better prepare data processing system of the Ka-band Radar Interferometer (KaRIn) for the Surface Water and Ocean Topography (SWOT) [1] mission, we opportunistically collected data over several diverse fresh-water targets in the Van Hook Arm areas of North Dakota, USA, using a Ka-band interferometric radar [2] developed at JPL. To make the collection relevant to SWOT, the aircraft was rolled to direct the antenna boresight toward nadir to mimic the SWOT geometry. Using a modified airborne interferometric SAR processor [3] developed at JPL, we were able to process the collected Ka-band airborne data and produced the height and magnitude image products. These results are the first of the kind for Ka-band interferometric synthethic aperture radar over water surfaces with near nadir looking geometry. These initial results will help to characterize the power returns from water surface and land, and provide guidance for the design of post-processing algorithms including methods for water and land classification. The height accuracy we get from the water surface height images can be used to project the water surface height accuracy we would get from SWOT mission. This airborne experiment will help us verify the SWOT data processing chain and make us better prepared for SWOT data processing task.

We performed airborne experiments using 150- and 450-MHz radars to measure ice thickness on the Greenland ice sheet. Our objectives were to investigate to what degree surface clutter obscures the basal echo when airborne measurements are made at different elevations and at different frequencies. We also explored interferometric techniques for processing the data to form swath measurements of ice thickness. We found that surface clutter was minimal for either frequency when operated at low aircraft elevations (500 m above the ice sheet surface) or over benign regions of the ice sheet. Because signal-to-clutter ratios were favorable, we found that we could retrieve the swath measurements of ice thickness at both frequencies using an interferometric technique. At high elevation, surface clutter degraded the 150-MHz signal, but the nadir ice thickness was still retrievable. The basal return in high-elevation 450-MHz data was detectable only after additional beam-steering techniques were applied to the data to reduce the surface clutter signal. Results suggest that interferometric cross-track ice-thickness measurements can be successfully made given a sufficient number of antenna elements driven at either 150 or 450 MHz and flown at both high and low elevations over the interior ice sheet.

We develop and then demonstrate a 3-D tomographic ice sounding method applied to very high frequency (VHF) radar data that produces swath measurements of ice sheet surface topography, ice thickness, and radar reflectivity of both the surface and bed of the ice sheet. First, we formulate the ice sheet imaging problem as a problem of estimating signal arrival angles and illustrate how the method resolves ambiguous echoes arriving simultaneously from the left and right sides of the aircraft, as well as from the surface and base of the ice sheet. We then discuss why we chose the time-domain subaperture method for 2-D image formation for ice sounding. We apply the tomographic technique to the data that we collected in May 2006 and again in July 2008 from a multiple-phase-center VHF radar system. We present 3-D images of the upper and lower surfaces of the ice sheet and compare the estimated surface topography with Ice, Cloud, and land Elevation Satellite altimeter nadir track measurements and the measured swath ice thickness with independent nadir depth sounder tracks. We achieved a 5-m surface topography accuracy and a 14-m ice thickness accuracy.

The primary objective of the National Research Council (NRC) Decadal Survey recommended SWOT (Surface Water and Ocean Topography) Mission is to measure the water elevation of the global oceans, as well as terrestrial water bodies (such as rivers, lakes, reservoirs, and wetlands), to answer key scientific questions on the kinetic energy of ocean circulation, the spatial and temporal variability of the world's surface freshwater storage and discharge, and to provide societal benefits on predicting climate change, coastal zone management, flood prediction, and water resources management. In this paper, we present the overall concept of the SWOT mission, as well as the scientific rational, objectives and development status of the technology items currently under development.

The elevation of the ocean surface has been measured for over two decades from spaceborne altimeters. However, existing altimeter measurements are not adequate to characterize the dynamic variations of most inland water bodies, nor of ocean eddies at scales of less than about 100 km, notwithstanding that such eddies play a key role in ocean circulation and climate change. For terrestrial hydrology, in situ and spaceborne measurements of water surface elevation form the basis for estimates of water storage change in lakes, reservoirs, and wetlands, and of river discharge. However, storage in most inland water bodies, e.g., millions of Arctic lakes, is not readily measured using existing technologies. A solution to the needs of both surface water hydrology and physical oceanography communities is the measurement of water elevations along rivers, lakes, streams, and wetlands and over the ocean surface using swath altimetry. The proposed surface water and ocean topography (SWOT) mission will make such measurements. The core technology for SWOT is the Ka-band radar interferometer (KaRIN), which would achieve spatial resolution on the order of tens of meters and centimetric vertical precision when averaged over targets of interest. Average revisit times will depend upon latitude, with two to four revisits at low to mid latitudes and up to ten revisits at high latitudes per$\sim$20-day orbit repeat period.

We describe a method for retrieving winds from colocated Ku- and C-band ocean wind scatterometers. The method utilizes an artificial neural network technique to optimize the weighting of the information from the two frequencies and to use the extra degrees of freedom to account for rain contamination in the measurements. A high-fidelity scatterometer simulation is used to evaluate the efficacy of the technique for retrieving hurricane force winds in the presence of heavy precipitation. Realistic hurricane wind and precipitation fields were simulated for three Atlantic hurricanes, Katrina and Rita in 2005 and Helene in 2006, using the Weather Research and Forecasting model. These fields were then input into a radar simulation previously used to evaluate the Extreme Ocean Vector Wind Mission dual-frequency scatterometer mission concept. The simulation produced high-resolution dual-frequency normalized radar cross-section (NRCS) measurements. The simulated NRCS measurements were binned into 5 x 5 km wind cells. Wind speeds in each cell were estimated using an artificial neural network technique. The method was shown to retrieve accurate winds up to 50 m/s even in intense rain.

The Water Elevation Recovery satellite mission is dedicated to the determination of land surface water extent, elevation, and slope using a Ka-band radar interferometer (KaRIn) as its primary instrument. Determining these parameters to the accuracy desired for hydrologic applications is challenging. The scientific objectives of the mission have been set up to 10 cm for the height budget and 10 murad (1 cm/1 km) for the slope budget. In this paper, we implement a Virtual Mission simulation and use it to examine the measurement performances for three case studies in Europe: a relatively small river such as the Meuse in Northern Western Europe, the Lena river in Russia, one of the major Siberian rivers, and Lake Leman in Western Europe. We simulate KaRIn data with the associated instrument and geophysical error sources and implement ground processing techniques to go from the original raw data to science data. We examine the impact of external errors in detail and implement calibration techniques that rely on the use of ancillary topographic data, such as the Shuttle Radar Topography Mission digital elevation model (DEM). We find that the impact of external errors can be reduced to a few centimeters. The random error budget can also be reduced below 10 cm by means of appropriate processing. The scientific requirements of the mission are shown to be met for all cases.

In this paper, spaceborne radar altimeters are shown to have the potential for monitoring the height of large rivers with accuracies of approximately 1 m. However, the need for a better height accuracy and the observations of smaller continental basins have led to studies on how to improve and extend the use of nadir-altimeter data. Conventional retracking techniques over land are limited to the examination of altimeter waveforms on a case-by-case basis. Due to the arbitrary geometry which may be present at altimeter river crossings, this approach may be limited to large rivers, which approximate ocean crossings. To overcome this limitation, we introduce a waveform-fitting method which uses the entire set of waveforms associated with a water crossing, rather than individual waveforms. By using ancillary data, such as digital elevation model (obtained from Shuttle Radar Topography Mission and Gtopo30) and classification maps (obtained from Landsat and MODIS), it is possible to recast the retracking problems as a maximum-likelihood-estimation problem. Theoretical power returns based on the a priori knowledge of the observed scenes are generated, resulting in a parametric library of waveform histories, which is then used to constrain the estimation. For demonstration, we concentrate on the river Meuse in northern western Europe and on the river Lena in Russia. The Meuse has important social impact, since it has flooded in the past and better real-time predictions of its changing stage may improve flood-forecasting skill. Furthermore, it presents a challenge to conventional nadir-altimeter waveform retracking. We will present both theoretical performance results and demonstrate the feasibility based on real altimeter data.

The Water Elevation Recovery (WatER) satellite mission was recently proposed and supported by a large international scientific community. It is dedicated to the determination of land surface water extent, elevation and slope, and also ocean mesoscale and submesoscale phenomena, using a Ka band Radar Interferometer (KaRIN) as its primary instrument. This instrument is able to provide the appropriate space-time sampling required to observe full signatures of the parameters characterizing these phenomena. However, determining these parameters to the accuracy desired for hydrologic applications is challenging.

The Microwave Observatory of Subcanopy and Subsurface (MOSS) is a mission concept for a spaceborne synthetic aperture radar (SAR) system that provides global observations of soil moisture under substantial vegetation cover (exceeding 20 kg/m2) and at useful depths (1-5 m). The concept was developed and a number of new required technologies were demonstrated through a National Aeronautics and Space Administration Earth Science Technology Office Instrument Incubator Program project. This very high frequency (VHF)/ultrahigh frequency (UHF) polarimetric SAR is designed to provide 7-10-day observations of soil moisture at 1-km resolution. The rapid repeat cycle mandates swath widths in the range of 300-400 km, which must be realized by a 30-m-long antenna. Conventional array implementations would result in a mass of more than 4000 kg, whereas with the technology proposed and demonstrated in this project, the total antenna mass is less than 500 kg. The antenna concept is a dual-stacked patch array feed illuminating a 30-m mesh reflector to synthesize the long apertures and achieve the wide swath. The feed system prototype was fabricated and its performance demonstrated. Other major project components were: (1) system-level SAR and mission design; (2) demonstration of science data and products, using a tower-based VHF/UHF radar; (3) spacecraft and mesh reflector antenna mechanical design; (4) developing mitigation strategies for ionospheric effects; and (5) assessing frequency interference effects. Experimental science data were generated from the tower radar for soil moisture profiling in Arizona and for forest penetration in Oregon. The soil moisture products were demonstrated through an integrated inversion-processing algorithm. This paper summarizes the results from the MOSS project and demonstrates the feasibility of the spaceborne mission.

We describe a real-time radar processing algorithm for radar interferometry of Ocean surface with a Wide Swath Ocean Altimeter: a real aperture radar interferometer concept to measure Ocean surface topography on a 200km swath. The algorithm compresses the input data by a factor of over 7000 and improves interferometric correlation by approximating the viewing geometry. It takes into account continuous changes in the viewing geometry due to the Earth's Geoid modeled as a table of n th order polynomials called the viewing scenario table. Each polynomial models a segment of the orbit and approximates how the distance between the platform and the ground varies as a function of time. Various algorithm parameters are updated regularly to compensate for the changes in the viewing geometry. These updates are implemented as time shifts to coregister successive data rangelines and frequency shifts to correct effects related to geometric decorrelation.

Measurements of deep and subcanopy soil moisture are critical in understanding the global water and energy cycle, as well as the interaction of the carbon and water cycles, but are presently not available on a synoptic basis. In this paper, a low-frequency UHF/VHF radar mission concept is presented and technology challenges to implement it are discussed. This mission concept is currently being studies under a NASA/ESTO instrument incubator program (IIP) project. The progresses of several aspects of the project are discussed.

In this paper, we present error sources and predicted performance of the Wide-Swath Ocean altimeter, an instrument which has been proposed as an experiment for the NASA/CNES Ocean Surface Topography Mission. The data obtained by this instrument will allow the detailed study of ocean mesoscale phenomena, with a space-time resolution which cannot be achieved by a single conventional nadir altimeter.

Synthetic aperture radar interferometry is an imaging technique for measuring the topography of a surface, its changes over time, and other changes in the detailed characteristic of the surface. By exploiting the phase of the coherent radar signal, interferometry has transformed radar remote sensing from a largely interpretive science to a quantitative tool, with applications in cartography, geodesy, land cover characterization, and natural hazards. This paper reviews the techniques of interferometry, systems and limitations, and applications in a rapidly growing area of science and engineering.

The correlation properties of altimeter returns are useful in the optimal design of altimeter systems. They are also necessary for implementing maximum likelihood estimation algorithms for altimeter waveform parameter estimation. The authors derive a simple expression for the bin-to-bin and pulse-to-pulse correlation of altimeter waveforms. This expression is a triple convolution of the specular point probability density function, a product of altimeter point target responses, and a generalized surface impulse response. This result is analogous to the usual expression for the mean altimeter waveform. The authors compare these theoretical predictions against real data, using measurements from the Skylab and Geosat altimeters. Finally, they present a simple application of the results to altimeter system design.>

The authors consider whether the unified perturbation method (UPM), which converges faster over a wider domain of surface roughness than other perturbations and intrinsically possesses characteristics similar to the two-scale expansion without requiring a free parameter, can be improved by applying the two-scale concept. To do so, they expand the unknown source current in a two-scale approximation. It is shown that the UPM performs best without two-scale expansions. The optimum spectral split of the various two-scale theories considered is presented.>