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Interferometric synthetic aperture radar (InSAR) has been used to quantify a range of surface and near surface physical properties in permafrost landscapes. Most previous InSAR studies have utilized spaceborne InSAR platforms, but InSAR datasets over permafrost landscapes collected from airborne platforms have been steadily growing in recent years. Most existing algorithms dedicated toward retrieval of permafrost physical properties were originally developed for spaceborne InSAR platforms. In this study, which is the first in a two part series, we introduce a series of calibration techniques developed to apply a novel joint retrieval algorithm for permafrost active layer thickness retrieval to an airborne InSAR dataset acquired in 2017 by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar over Alaska and Western Canada. We demonstrate how InSAR measurement uncertainties are mitigated by these calibration methods and quantify remaining measurement uncertainties with a novel method of modeling interferometric phase uncertainty using a Gaussian mixture model. Finally, we discuss the impact of native SAR resolution on InSAR measurements, the limitation of using few interferograms per retrieval, and the implications of our findings for cross‐comparison of airborne and spaceborne InSAR datasets acquired over Arctic regions underlain by permafrost., Key Points We develop and present several calibration and postprocessing methods for seasonal subsidence estimation from interferometric synthetic aperture radar deformationNovel methods for phase referencing and uncertainty quantification due to nonergodicity within the multilook window are proposedResidual sources of uncertainty in active layer thickness estimation are discussed and quantified

Understanding the complex interrelationships between wildfire and its environmental and anthropogenic controls is crucial for wildfire modeling and management. Although machine learning (ML) models have yielded significant improvements in wildfire predictions, their limited interpretability has been an obstacle for their use in advancing understanding of wildfires. This study builds an ML model incorporating predictors of local meteorology, land‐surface characteristics, and socioeconomic variables to predict monthly burned area at grid cells of 0.25° × 0.25° resolution over the contiguous United States. Besides these predictors, we construct and include predictors representing the large‐scale circulation patterns conducive to wildfires, which largely improves the temporal correlations in several regions by 14%–44%. The Shapley additive explanation is introduced to quantify the contributions of the predictors to burned area. Results show a key role of longitude and latitude in delineating fire regimes with different temporal patterns of burned area. The model captures the physical relationship between burned area and vapor pressure deficit, relative humidity (RH), and energy release component (ERC), in agreement with the prior findings. Aggregating the contribution of predictor variables of all the grids by region, analyses show that ERC is the major contributor accounting for 14%–27% to large burned areas in the western US. In contrast, there is no leading factor contributing to large burned areas in the eastern US, although large‐scale circulation patterns featuring less active upper‐level ridge‐trough and low RH two months earlier in winter contribute relatively more to large burned areas in spring in the southeastern US., Key Points US fire burned areas are well predicted by a machine learning model and SHAP improves interpretation of the contributing factorsIncluding large‐scale circulation patterns conducive to wildfires as predictors improve prediction of burned areas in several regionsFire‐season fuel dryness and dry winters are important contributors to large burned areas in western and southeastern US, respectively

In addition to spaceborne Interferometric Synthetic Aperture Radar (InSAR), airborne data such as those obtained by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) have also been utilized to measure surface subsidence in permafrost areas in recent years. Motivated by the integration of multiplatform InSAR data, we generated two UAVSAR interferograms and one Advanced Land Observing Satellite (ALOS)‐2 L‐band interferogram over a permafrost area near Yellowknife, Canada, then compared the surface subsidence in the thaw seasons of 2017. The correlation coefficient and the root mean square error (RMSE) of subsidence difference are calculated to compare the airborne and spaceborne InSAR measurements. The results demonstrate that the two UAVSAR measurements are self‐consistent, with the correlation coefficient between independent airborne measurements ∼0.7. While the RMSE of the difference between surface subsidence measured by UAVSAR and ALOS2 is ∼2.0 cm, and the correlation coefficients are less than 0.41, that is, a noticeable deviation exists between the UAVSAR and ALOS2 results possibly due to different spatial resolution and the calibration processing of airborne and spaceborne InSAR data. In addition, both UAVSAR and ALOS2 interferograms show larger surface subsidence within taiga needleleaf forest regions than in regions of other biome types (including needleleaf forest, shrubland, and grassland). The results demonstrate that a scheme for the elimination of systematic differences needs to be developed before merging multisource InSAR results. This intercomparison will provide valuable insights for narrowing the gap between radar‐based measurements and planning the integration of airborne and satellite InSAR measurements in permafrost environments., Key Points We compare the seasonal subsidence derived from airborne and satellite InSAR measurementsTwo UAVSAR interferograms are self‐consistent while a significant deviation exists between the UAVSAR and ALOS2 resultsWe discuss the difference and the potential combination use of spaceborne and airborne InSAR to improve subsidence measurements over permafrost regions

We use Ice, Cloud, and land Elevation Satellite 2 (ICESat‐2) laser altimetry crossovers and repeat tracks collected over the North Slope of Alaska to estimate ground surface‐height change due to the seasonal freezing and thawing of the active layer. We compare these measurements to a time series of surface deformation from Sentinel‐1 interferometric synthetic aperture radar (InSAR) and demonstrate agreement between these independent observations of surface deformation at broad spatial scales. We observe a relationship between ICESat‐2‐derived surface subsidence/uplift and changes in normalized accumulated degree days, which is consistent with the thermodynamically driven seasonal freezing and thawing of the active layer. Integrating ICESat‐2 crossover estimates of surface‐height change yields an annual time series of surface‐height change that is sensitive to changes in snow cover during spring and thawing of the active layer throughout spring and summer. Furthermore, this time series exhibits temporal correlation with independent reanalysis datasets of temperature and snow cover, as well as an InSAR‐derived time series. ICESat‐2‐derived surface‐height change estimates can be significantly affected by short length‐scale topographic gradients and changes in snow cover and snow depth. We discuss optimal strategies of post‐processing ICESat‐2 data for permafrost applications, as well as the future potential of joint ICESat‐2 and InSAR investigations of permafrost surface‐dynamics., Key Points ICESat‐2 altimetry can resolve surface subsidence that is related to changes in snow‐cover depth and seasonal thawing of the active layerICESat‐2 measurements of surface‐height change are affected by along‐track topographic gradients and complex surface roughnessComplementary ICESat‐2 and InSAR datasets can be jointly leveraged for future studies in periglacial environments

We describe the capabilities, radiometric stability, and calibration of a custom vacuum environment chamber capable of simulating the near‐surface conditions of airless bodies. Here we demonstrate the collection of spectral measurements of a suite of fine particulate asteroid analogs made using the Planetary Analogue Surface Chamber for Asteroid and Lunar Environments (PASCALE) under conditions like those found on Earth and on airless bodies. The sample suite includes anhydrous and hydrated physical mixtures, and chondritic meteorites (CM, CI, CV, CR, and L5) previously characterized under Earth‐ and asteroid‐like conditions. And for the first time, we measure the terrestrial and extra‐terrestrial mineral end members used in the olivine‐ and phyllosilicate‐dominated physical mixtures under the same conditions as the mixtures and meteorites allowing us better understand how minerals combine spectrally when mixed intimately. Our measurements highlight the sensitivity of thermal infrared emissivity spectra to small amounts of low albedo materials and the composition of the sample materials. As the albedo of the sample decreases, we observe smaller differences between Earth‐ and asteroid‐like spectra, which results from a reduced thermal gradient in the upper hundreds of microns in the sample. These spectral measurements can be compared to thermal infrared emissivity spectra of asteroid (101955) Bennu's surface in regions where similarly fine particulate materials may be observed to infer surface compositions., Key Points Thermal infrared spectra of fine particulate minerals, physical mixtures of those minerals, and meteorites were measured under simulated Bennu conditionsComparisons of mineral, physical mixture, and meteorite spectra highlight the spectral behavior when materials are mixed in increasing complexityAs albedo decreases the spectral effects due to thermal gradients due to the vacuum environment of airless bodies are reduced

Asteroid (101955) Bennu, a near‐Earth object with a primitive carbonaceous chondrite‐like composition, was observed by the Origins, Spectral Interpretation, Resource Identification, and Security‐Regolith Explorer (OSIRIS‐REx) spacecraft to undergo multiple particle ejection events near perihelion between December 2018 and February 2019. The three largest events observed during this period, which all occurred 3.5 to 6 hr after local noon, placed numerous particles, Key Points Meteoroids derived from comets strike Bennu near perihelion once every 2 weeks on average with an impact kinetic energy >7,000 JThey can explain the particle sizes (

While previous cometary missions were only limited to flybys, the groundbreaking ESA/Rosetta mission escorted comet 67P for two years. This enabled for the first time to make in situ measurements of the evolution of a comet's plasma environment. On one hand, low time resolution electron densities are calculated using the plasma frequency extracted from the mutual impedance spectra measured by the RPC-Mutual Impedance Probe (MIP). On the other hand, high time resolution fluctuations of spacecraft potential and ion current are measured by the RPC-Langmuir Probe (LAP). Thus, we perform a MIP-LAP cross-calibration using a spacecraft charging model to retrieve high time resolution electron density fluctuations throughout the entire mission (whenever both the required MIP and LAP operations and data allow). This new dataset will be available to the scientific community on the ESA/PSA around Summer 2019, however it is already available for specific cases of interest. Here, we make use of these data, together with RPC-MAG magnetic field measurements, to investigate in detail the properties of the low-frequency so-called "singing comet" waves observed in the plasma environment of 67P, making use of a change in the wave activity before and during a cometary brightness outburst on February 19, 2016.

International audience; The Rosetta Orbiter Spectrometer for Ion and Neutral Analysis (ROSINA), the mass spectrometer suite on board the European Space Agency's Rosetta mission, was dedicated to the measurement of the volatiles in the coma of comet 67P/Churyumov-Gerasimenko (67P) [1]. Among many other species, ROSINA DFMS, the Double Focusing Mass Spectrometer, detected and quantified the three noble gases argon, krypton, and xenon including their major isotopes [2,3]. Noble gases provide important clues to the physical and chemical conditions during and possibly even before and after the comet's formation in the early solar system. Furthermore, measurements of the isotope ratios provide constraints on the amount of cometary material brought to Earth and its early atmosphere. In this presentation, we will report on the measured coma densities and derived nucleus bulk abundances of these three noble gases and investigate correlations with other volatiles. Furthermore, we will discuss the measured isotope ratios and the implications of these results. AcknowledgementsUoB was funded by the State of Bern, the Swiss National Science Foundation and by the European Space Agency PRODEX Programme. Work at MPS was funded by the Max-Planck Gesellschaft and BMWI (contract 50QP1302), at Southwest Research institute by Jet Propulsion Laboratory (subcontract #1496541 and JPL subcontract to JWH NAS703001TONMO710889), at the University of Michigan by NASA (contract JPL-1266313). This work has been supported through the A*MIDEX project from the French National Research Agency (ANR) (n° ANR-11-IDEX- 0001-02) and by CNES grants at IRAP, LATMOS, LPC2E, LAM, CRPG, by the European Research Council (grant no. 267255 to B. Marty) and at BIRA-IASB by the Belgian Science Policy Office via PRODEX/ROSINA PEA C4000107705. References[1] Balsiger, H., et al., Rosina - Rosetta orbiter spectrometer for ion and neutral analysis. Space Science Reviews. 128, 745-801, 2007. [2] Balsiger, H., et al., Detection of argon in the coma of comet 67P/Churyumov-Gerasimenko. Sci Adv. 1, e1500377, 2015. [3] Marty B., et al., Xenon isotopes in 67P/Churyumov-Gerasimenko show that comets contributed to Earth's atmosphere, Science, 356, 1069 - 1072, 2017.

The magnetometer onboard ESA's Rosetta orbiter detected its highest magnetic field magnitude of 250nT in July 2015, close to perihelion. This magnitude was an enhancement of a factor of five compared to normal values, which makes this the highest interplanetary magnetic field ever measured. We have examined the solar wind conditions at the time and found that a corotating interaction region (CIR), accompanied by a fast flow is the trigger for this unusual event. Because Rosetta does not have solar wind observations during the comet's active phase, we use ENLIL simulations as well as observations at Earth and Mars to constrain the solar wind parameters at the comet. Using a simple model for the magnetic field pile-up we can trace back the field in the coma to corresponding structures in the CIR. The large field is accompanied by a dramatic increase in electron and ion fluxes and energies. However, the electrons and ions in the field of view are not, as expected, increasing at the same time, instead the electrons follow the magnetic field, while the ion density increase is delayed. This is seen as evidence of the kinetic behaviour of the ions as opposed to a magnetized electron fluid. Combining the information on the plasma, we are able to identify at least three different regions in the plasma that have fundamentally different parameters. This allows us to separate the solar wind influence from the comet's effects on the plasma, a problem that is usually not solvable without a spacecraft monitoring the solar wind at the comet.

There are four known sources of dust in the inner solar system: Jupiter Family comets, asteroids, Halley Type comets, and Oort Cloud comets. Here we combine the mass, velocity, and radiant distributions of these cosmic dust populations from an astronomical model with a chemical ablation model to estimate the injection rates of Na and Fe into the Earth's upper atmosphere, as well as the flux of cosmic spherules to the surface. Comparing these parameters to lidar observations of the vertical Na and Fe fluxes above 87.5 km, and the measured cosmic spherule accretion rate at South Pole, shows that Jupiter Family Comets contribute (80 ± 17)% of the total input mass (43 ± 14 t d−1), in good accord with Cosmic Background Explorer and Planck observations of the zodiacal cloud., Key Points Solar system dust sources are fitted to the cosmic spherule accretion rate and the Na and Fe fluxes in the mesosphereJupiter Family Comets provide ~80% of the cosmic dust entering the atmosphere, with 12% from long‐period comets and 8% from asteroidsThe resulting differential ablation of Ca and Fe relative to Na explains the relative abundances of these metal layers in the mesosphere