Field Measurements for Remote Sensing of the Cryosphere

Remote sensing observations of the cryosphere, like any other target of interest, require ground-based measurements for both calibration and validation, as inversion algorithms are usually underdetermined and uncertainties in the retrieval are needed for application. Field-based observations are performed in selected representative locations, and typically involve both direct in situ measurements of the physical properties of interest, as well as ground-based remote sensing techniques. New state-of-the-art modern techniques for measuring physical properties rapidly and at high spatial resolution have recently given us a new view of spatiotemporal variability. These are important, as large variability at scales below the typical footprint of spaceborne sensors often exists. Simulating remote sensing measurements using ground-based sensors provides the ability to perform both in situ and remote sensing measurements at the same scale, providing insight into the dominant physical processes that must be accounted for in inversion models and retrieval schemes. While direct in situ measurements provide the most accurate information about the properties of interest, they are time-consuming and expensive and are, therefore, only practical at relatively few locations, and often with low temporal resolution. Spatial sampling strategies, designed specifically for the remote sensing observation of interest, can reduce uncertainties in comparisons between ground-based and airborne/spaceborne estimates. Intensive remote sensing calibration and validation campaigns, often associated with an upcoming or recent satellite launch, provide unique opportunities for detailed characterization at a wide range of scales, and these are typically large international collaborative efforts. This chapter reviews standard in situmanual field measurements for snow and ice properties, as well as newer high-resolution techniques and instruments used to simulate airborne and spaceborne remote sensing observations. Sampling strategies and example applications from recent international calibration and validation experiments are given. Field measurements are a crucial component of remote sensing of the cryosphere, as they provide both the necessary direct observations of the variables of interest, as well as measurements that simulate the particular remote sensing technique at scales that can be characterized accurately. Ground-based observations provide the information needed to: improve and develop new retrieval algorithms; calibrate algorithms; and validate results to provide accurate uncertainty assessments

Review Article: Global Monitoring of Snow Water Equivalent Using High-Frequency Radar Remote Sensing

Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 × 106 km2 of Earth\u27s surface (31 % of the land area) each year, and is thus an important expression and driver of the Earth\u27s climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (∼ −13 % per decade) as Arctic summer sea ice. More than one-sixth of the world\u27s population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth\u27s cold regions\u27 ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of water stored as snow on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations are not able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high-socio-economic-value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-band synthetic aperture radar (SAR) for global monitoring of SWE. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimeter-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modeling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, density, and layering. We describe radar interactions with snow-covered landscapes, the small but rapidly growing number of field datasets used to evaluate retrieval algorithms, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and application communities on progress made in recent decades and sets the stage for a new era in SWE remote sensing from SAR measurements

Derivation and evaluation of a new extinction coefficient for use with the n-HUT snow emission model

In this study, snow slab data collected from the Arctic Snow Microstructure Experiment were used in conjunction with a six-directional flux coefficient model to calculate individual slab absorption and scattering coefficients. These coefficients formed the basis for a new semiempirical extinction coefficient model, using both frequency and optical diameter as input parameters, along with the complex dielectric constant of snow. Radiometric observations, at 18.7, 21.0, and 36.5 GHz at both horizontal polarization (H-Pol) and vertical polarization (V-Pol), and snowpit data collected as part of the Sodankylä Radiometer Experiment were used to compare and contrast the simulated brightness temperatures produced by the multi-layer Helsinki University of Technology snow emission model, utilizing both the original empirical model and the new semiempirical extinction coefficient model described here. The results show that the V-Pol RMSE and bias values decreased when using the semiempirical extinction coefficient; however, the H-Pol RMSE and bias values increased on two of the lower microwave bands tested. The unbiased RMSE was shown to decrease across all frequencies and polarizations when using the semiempirical extinction coefficient

Modeling of Subsurface Scattering from Ice Sheets for Pol-InSAR Applications

Remote sensing is a fundamental tool to measure the dynamics of ice sheets and provides valuable information for ice sheet projections under a changing climate. There is, however, the potential to further reduce the uncertainties in these projections by developing innovative remote sensing methods. One of these remote sensing techniques, the polarimetric synthetic aperture radar interferometry (Pol-InSAR), is known since decades to have the potential to assess the geophysical properties below the surface of ice sheets, because of the penetration of microwave signals into dry snow, firn, and ice. Despite this, only very few studies have addressed this topic and the development of robust Pol-InSAR applications is at an early stage. Two potential Pol-InSAR applications are identified as the motivation for this thesis. First, the estimation and compensation of the penetration bias in digital elevation models derived with SAR interferometry. This bias can lead to errors of several meters or even tens of meters in surface elevation measurements. Second, the estimation of geophysical properties of the subsurface of glaciers and ice sheets using Pol-InSAR techniques. There is indeed potential to derive information about melt-refreeze processes within the firn, which are related to density and affect the mass balance. Such Pol-InSAR applications can be a valuable information source with the potential for monthly ice sheet wide coverage and high spatial resolution provided by the next generation of SAR satellites. However, the required models to link the Pol-InSAR measurements to the subsurface properties are not yet established. The aim of this thesis is to improve the modeling of the vertical backscattering distribution in the subsurface of ice sheets and its effect on polarimetric interferometric SAR measurements at different frequencies. In order to achieve this, polarimetric interferometric multi-baseline SAR data at different frequencies and from two different test sites on the Greenland ice sheet are investigated. This thesis contributes with three concepts to a better understanding and to a more accurate modeling of the vertical backscattering distribution in the subsurface of ice sheets. First, the integration of scattering from distinct subsurface layers. These are formed by refrozen melt water in the upper percolation zone and cause an interesting coherence undulation pattern, which cannot be explained with previously existing models. This represents a first link between Pol-InSAR data and geophysical subsurface properties. The second step is the improved modeling of the general vertical backscattering distribution of the subsurface volume. The advantages of more flexible volume models are demonstrated, but interestingly, the simple modification of a previously existing model with a vertical shift parameter lead to the best agreement between model and data. The third contribution is the model based compensation of the penetration bias, which is experimentally validated. At the investigated test sites, it becomes evident that the model based estimates of the surface elevations are more accurate than the interferometric phase center locations, which are conventionally used to derive surface elevations of ice sheets. This thesis therefore improves the state of the art of subsurface scattering modeling for Pol-InSAR applications, demonstrates the model-based penetration bias compensation, and makes a further research step towards the retrieval of geophysical subsurface information with Pol-InSAR

The Holy Grail: A road map for unlocking the climate record stored within Mars' polar layered deposits

In its polar layered deposits (PLD), Mars possesses a record of its recent climate, analogous to terrestrial ice sheets containing climate records on Earth. Each PLD is greater than 2 ​km thick and contains thousands of layers, each containing information on the climatic and atmospheric state during its deposition, creating a climate archive. With detailed measurements of layer composition, it may be possible to extract age, accumulation rates, atmospheric conditions, and surface activity at the time of deposition, among other important parameters; gaining the information would allow us to “read” the climate record. Because Mars has fewer complicating factors than Earth (e.g. oceans, biology, and human-modified climate), the planet offers a unique opportunity to study the history of a terrestrial planet’s climate, which in turn can teach us about our own planet and the thousands of terrestrial exoplanets waiting to be discovered. During a two-part workshop, the Keck Institute for Space Studies (KISS) hosted 38 Mars scientists and engineers who focused on determining the measurements needed to extract the climate record contained in the PLD. The group converged on four fundamental questions that must be answered with the goal of interpreting the climate record and finding its history based on the climate drivers. The group then proposed numerous measurements in order to answer these questions and detailed a sequence of missions and architecture to complete the measurements. In all, several missions are required, including an orbiter that can characterize the present climate and volatile reservoirs; a static reconnaissance lander capable of characterizing near surface atmospheric processes, annual accumulation, surface properties, and layer formation mechanism in the upper 50 ​cm of the PLD; a network of SmallSat landers focused on meteorology for ground truth of the low-altitude orbiter data; and finally, a second landed platform to access ~500 ​m of layers to measure layer variability through time. This mission architecture, with two landers, would meet the science goals and is designed to save costs compared to a single very capable landed mission. The rationale for this plan is presented below. In this paper we discuss numerous aspects, including our motivation, background of polar science, the climate science that drives polar layer formation, modeling of the atmosphere and climate to create hypotheses for what the layers mean, and terrestrial analogs to climatological studies. Finally, we present a list of measurements and missions required to answer the four major questions and read the climate record. 1. What are present and past fluxes of volatiles, dust, and other materials into and out of the polar regions? 2. How do orbital forcing and exchange with other reservoirs affect those fluxes? 3. What chemical and physical processes form and modify layers? 4. What is the timespan, completeness, and temporal resolution of the climate history recorded in the PLD

Multi-Channel Ground-Penetrating Radar for the Continuous Quantification of Snow and Firn Density, Depth, and Accumulation

A priority of ice sheet surface mass balance (SMB) prediction is ascertaining the surface density and annual snow accumulation. These forcing data are inputs for firn density models and can be used to inform remotely sensed ice sheet surface processes and to assess Regional Climate Model (RCM) skill. The Greenland Traverse for Accumulation and Climate Studies (GreenTrACS) retrieved 16 shallow firn cores and dug 42 snow pits along the Western percolation zone of the Greenland Ice Sheet (GrIS) during May and June of 2016 and 2017. I deployed and maintained a multi-channel 500 MHz ground-penetrating radar in a multi-offset configuration throughout the two traverse campaigns. The multi-channel radar technique accurately and independently estimates density, depth, and annual snow accumulation -- between the firn core and snow pit sites -- by horizon velocity analysis of common midpoint radar reflections from the snow and shallow firn. I analyzed a 45 km section of the traverse in a high accumulation zone, known as the GreenTrACS Core 15 Western Spur. Deviations in surface density up to +- 15 kg/m3 from the transect mean correlate with surface elevation and surface slope angle. Spatial variation in mean annual accumulation of ~0.175 m w.e. ɑ-1 occurs across a trough in the surface topography ~5 km wide. The reported variability of density and accumulation demonstrates that RCMs must be down-scaled to resolutions within 5 km to assess subtle yet significant contributions to the GrIS SMB

Five decades of radioglaciology

Radar sounding is a powerful geophysical approach for characterizing the subsurface conditions of terrestrial and planetary ice masses at local to global scales. As a result, a wide array of orbital, airborne, ground-based, and in situ instruments, platforms and data analysis approaches for radioglaciology have been developed, applied or proposed. Terrestrially, airborne radar sounding has been used in glaciology to observe ice thickness, basal topography and englacial layers for five decades. More recently, radar sounding data have also been exploited to estimate the extent and configuration of subglacial water, the geometry of subglacial bedforms and the subglacial and englacial thermal states of ice sheets. Planetary radar sounders have observed, or are planned to observe, the subsurfaces and near-surfaces of Mars, Earth's Moon, comets and the icy moons of Jupiter. In this review paper, and the thematic issue of the Annals of Glaciology on ‘Five decades of radioglaciology’ to which it belongs, we present recent advances in the fields of radar systems, missions, signal processing, data analysis, modeling and scientific interpretation. Our review presents progress in these fields since the last radio-glaciological Annals of Glaciology issue of 2014, the context of their history and future prospects

Exploiting the ANN Potential in Estimating Snow Depth and Snow Water Equivalent From the Airborne SnowSAR Data at X- and Ku-Bands

Within the framework of European Space Agency (ESA) activities, several campaigns were carried out in the last decade with the purpose of exploiting the capabilities of multifrequency synthetic aperture radar (SAR) data to retrieve snow information. This article presents the results obtained from the ESA SnowSAR airborne campaigns, carried out between 2011 and 2013 on boreal forest, tundra and alpine environments, selected as representative of different snow regimes. The aim of this study was to assess the capability of X- and Ku-bands SAR in retrieving the snow parameters, namely snow depth (SD) and snow water equivalent (SWE). The retrieval was based on machine learning (ML) techniques and, in particular, of artificial neural networks (ANNs). ANNs have been selected among other ML approaches since they are capable to offer a good compromise between retrieval accuracy and computational cost. Two approaches were evaluated, the first based on the experimental data (data driven) and the second based on data simulated by the dense medium radiative transfer (DMRT). The data driven algorithm was trained on half of the SnowSAR dataset and validated on the remaining half. The validation resulted in a correlation coefficient R ≃ 0.77 between estimated and target SD, a root-mean-square error (RMSE) ≃ 13 cm, and bias = 0.03 cm. ANN algorithms specific for each test site were also implemented, obtaining more accurate results, and the robustness of the data driven approach was evaluated over time and space. The algorithm trained with DMRT simulations and tested on the experimental dataset was able to estimate the target parameter (SWE in this case) with R = 0.74, RMSE = 34.8 mm, and bias = 1.8 mm. The model driven approach had the twofold advantage of reducing the amount of in situ data required for training the algorithm and of extending the algorithm exportability to other test sites

The layering of polar firn - investigations of the climatic impact on polar firn structure using high resolution density measurements and 3D-X-ray-microfocus-computer-tomography

The polar firn structure is investigated in terms of layering using high-resolution density measurements of 19 firn cores and X-ray-microfocus-computer-tomography image analysis of 6 surface firn cores. The impact of local climate conditions such as mean annual temperature and accumulation rate on the generation, structure and evolution of the layering is studied. We find at all sites a high variability in density and microstructure due to the layered character of the firn. The standard deviation of the measured physical properties is used as a proxy to parameterize the layering and to compare the degree of layering at different sites. The results indicate, that the seasonal stratigraphy in ice core records, which is assumed to be formed by a continuous deposition at the surface and yields the basis of paleo-climate studies, is not necessarily formed at the surface by depositional mechanisms, but by densification and snow metamorphism deeper down in the firn column, influenced by impurities. The layering is also displayed in the microstructure, but shows a very complex pattern as the result of the combined effect of initial layering, sintering and short-term changes in local climate conditions. Nevertheless the microstructure from very different sites and very diverse metamorphic states shows some surprisingly well defined relationships: the specific surface area of the firn samples, which can be determined by several methods, can be described bijective from the measured chord length (average intersection of the ice phase with a line). This strengthens the assumption, that optical properties of snow and firn can be described by an effective radius of spheres, showing the same specific surface area as the measured sample. For any applications where the effective ice-air-interface of the firn is important, (air-exchange, chemical interactions, interactions with optical properties, microwaves), the easy-to-measure-specific surface area is sufficient to obtain the effective radius of the firn structure. The results of this study point out, that the stratigraphy, i.e. the amplitude and the frequency of the density variability, is not a constant property of firn, which is continuously buried in the firn column with depth and time. The original surface density and its variability, the original surface grain size and its variability and incorporated impurities as well as the interaction of the frequencies of the density variability and impurity concentration variability configure the dynamic evolution of the layering of the firn with depth. The layering of polar firn shows a random generation at the surface and a very dynamic evolution with depth, which is influenced not only by the microstructure and the local climate conditions but also by impurities incorporated into the firn at the surface

The Holy Grail: A road map for unlocking the climate record stored within Mars' polar layered deposits

In its polar layered deposits (PLD), Mars possesses a record of its recent climate, analogous to terrestrial ice sheets containing climate records on Earth. Each PLD is greater than 2 ​km thick and contains thousands of layers, each containing information on the climatic and atmospheric state during its deposition, creating a climate archive. With detailed measurements of layer composition, it may be possible to extract age, accumulation rates, atmospheric conditions, and surface activity at the time of deposition, among other important parameters; gaining the information would allow us to “read” the climate record. Because Mars has fewer complicating factors than Earth (e.g. oceans, biology, and human-modified climate), the planet offers a unique opportunity to study the history of a terrestrial planet’s climate, which in turn can teach us about our own planet and the thousands of terrestrial exoplanets waiting to be discovered. During a two-part workshop, the Keck Institute for Space Studies (KISS) hosted 38 Mars scientists and engineers who focused on determining the measurements needed to extract the climate record contained in the PLD. The group converged on four fundamental questions that must be answered with the goal of interpreting the climate record and finding its history based on the climate drivers. The group then proposed numerous measurements in order to answer these questions and detailed a sequence of missions and architecture to complete the measurements. In all, several missions are required, including an orbiter that can characterize the present climate and volatile reservoirs; a static reconnaissance lander capable of characterizing near surface atmospheric processes, annual accumulation, surface properties, and layer formation mechanism in the upper 50 ​cm of the PLD; a network of SmallSat landers focused on meteorology for ground truth of the low-altitude orbiter data; and finally, a second landed platform to access ~500 ​m of layers to measure layer variability through time. This mission architecture, with two landers, would meet the science goals and is designed to save costs compared to a single very capable landed mission. The rationale for this plan is presented below. In this paper we discuss numerous aspects, including our motivation, background of polar science, the climate science that drives polar layer formation, modeling of the atmosphere and climate to create hypotheses for what the layers mean, and terrestrial analogs to climatological studies. Finally, we present a list of measurements and missions required to answer the four major questions and read the climate record. 1. What are present and past fluxes of volatiles, dust, and other materials into and out of the polar regions? 2. How do orbital forcing and exchange with other reservoirs affect those fluxes? 3. What chemical and physical processes form and modify layers? 4. What is the timespan, completeness, and temporal resolution of the climate history recorded in the PLD