Search NASA⌕ Search

SEARCH · Search NASA

Results for “Cryosphere”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

An Assessment of SNPP and NOAA20 VIIRS RSB Calibration Performance in NASA SIPS Reprocessed Collection-2 L1B Data Products

Two VIIRS sensors onboard the SNPP and NOAA20 satellites have been successfully operating for over 10 and 4 years, respectively, providing the worldwide user community with high-quality imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans. This study provides a temporal radiometric stability and calibration consistency assessment of the SNPP and NOAA20 VIIRS reflective solar bands using the latest NASA SIPS C2 L1B products. Several independent vicarious approaches are used to examine the stability of SNPP VIIRS and consistency of the at-sensor reflectance between the two VIIRS instruments. These approaches include observations from simultaneous nadir overpasses, the Libya-4 desert and Dome C snow/ice sites, and deep convective clouds. The impact of existing band spectral differences on the reflectance measurements is accounted for utilizing scene-specific hyperspectral observations provided by the SCIAMACHY sensor onboard the ENVISAT platform. Results indicate that both SNPP and NOAA20 VIIRS reflectances are stable within 1% over their mission periods for all bands, except for a few bands in the visible range from SNPP VIIRS that show more upward drifts at high radiances. NOAA20 VIIRS reflectances are systematically lower than SNPP by 2 to 4% for most bands, with the exception of few short wavelength bands where it is seen to be up to 7%.

VIIRS↗
NASA NTRS2022

Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters

High-resolution space-based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal-to-noise ratio. Different applications drive divergent instrument designs, so optimization for wide-reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications-agnostic, data-driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high-dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal-to-noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher-level algorithms, products, applications, or disciplines.

Intrinsic dimensionality↗
NASA NTRS2022

Ongoing Progress Toward NASA's Surface Biology and Geology Mission

Pursuant to recommendations by the National Academies of Science, Engineering and Medicine's Earth Science Decadal Survey, the National Aeronautics and Space Administration (NASA) has announced the development of an Earth System Observatory (ESO), a series of missions designed to observe processes across the Earth's interior, surface and atmosphere. A key component of this system is the Surface Biology and Geology (SBG) investigation. SBG will measure the composition and properties of Earth's land, inland waters, and coastal oceans. The notional architecture consists of multiple spacecraft slated for launch in the 2027–2028 timeframe (Figure 1). Target science questions and geophysical variables span diverse disciplines including terrestrial and aquatic ecology, geology, vulcanology, hydrology and cryospheric sciences (Figure 2). Beyond simply measuring geophysical variables for each discipline, SBG will provide information about the links between the different domains, enabling a more comprehensive understanding of the Earth as a connected system. SBG measurements will also benefit a wide range of societal applications including agriculture, terrestrial and aquatic biodiversity, natural hazards, public health, and management of water and other natural resources. SBG will also coordinate measurements, data products, and analyses with other ESO elements to deliver an integrated Earth System perspective of Earth and its changing climate.

David R. Thompson↗
NASA NTRS2023

Pypromice: A Python Package for Processing Automated Weather Station Data

The pypromice Python package is for processing and handling observation datasets from automated weather stations (AWS). It is primarily aimed at users of AWS data from the Geological Survey of Denmark and Greenland (GEUS), which collects and distributes in situ weather station observations to the cryospheric science research community. Functionality in pypromice is primarily handled using two key open-source Python packages, xarray (Hoyer & Hamman, 2017) and pandas (The pandas development team, 2020). A defined processing workflow is included in pypromice for transforming original AWS observations (Level 0, L0) to a usable, CF-convention-compliant dataset (Level 3, L3) (Figure 1). Intermediary processing levels (L1,L2) refer to key stages in the workflow, namely the conversion of variables to physical measurements and variable filtering (L1), cross-variable corrections and user-defined data flagging and fixing (L2), and derived variables (L3). Information regarding the station configuration is needed to perform the processing, such as instrument calibration coefficients and station type (one-boom tripod or two-boom mast station design, for example), which are held in a toml configuration file. Two example configuration files are provided with pypromice , which are also used in the package’s unit tests. More detailed documentation of the AWS design, instrumentation, and processing steps are described in Fausto et al. (2021).

pypromice↗
NASA NTRS2023

Modeling Sea Ice Albedo and Transmittance Measurements With A Fully-Coupled Radiative Transfer Model

A rigorous treatment of the sea ice medium has been incorporated in the advanced Coupled Ocean-Atmosphere Radiative Transfer (COART) model. The inherent optical properties (IOPs) of brine pockets and air bubbles over the 0.25-4.0 μm spectral region are parameterized as a function of the vertical profile of the sea ice physical properties (temperature, salinity and density). We test the model performance using available albedo and transmittance measurements collected during the Impacts of Climate on the Ecosystems and Chemistry of the Arctic Pacific Environment (ICESCAPE) and the Surface Heat Budget of the Arctic Ocean (SHEBA) field campaigns. The observations are adequately simulated when at least three layers are used to represent bare (first-year and multi-year) ice, including a thin top layer characterized by low density and high scattering. Two layers can be sufficient to model isolated cases of multi-year ice, and apply well to ponded ice except for shallow ponds over thick ice. The albedo and transmittance of ponded ice in the visible are mainly determined by the optical properties of the ice underlying the water layer used to model the pond. Sensitivity results indicate that the air volume or ice density has the largest impact on the simulated fluxes. Possible contamination from light-absorbing impurities, such as black carbon or ice algae, is also implemented in the model and is able to effectively reduce the albedo and transmittance in the visible spectrum to further improve the model-observation agreement. The agreement between the observed and modeled spectra validates the parameterization of the sea ice IOPs, and endorses COART as an accurate tool for radiation studies in the cryosphere.

Coupled Ocean-9 Atmosphere Radiative Transfer (COA↗
NASA NTRSDate not supplied

Earth Energy Balance Assessment at the 2022 BIPM-WMO Metrology for Climate Action Workshop

The BIPM and WMO hosted a five-day workshop in Sept. 2022 to assess the state of current metrology and identify future meteorological needs regarding climate change for the upcoming decade. A resulting broad policy-oriented workshop summary report, written by the workshop’s ~70 international organizers and reviewed by meeting attendees, identifies the current issues in each of nine high-level topic areas and provides recommendations to address them, listing specific needs, pathways, timelines, and responsible agencies or organizations for each. One prominent Topic within the workshop, “Earth Energy Balance,” was organized by the authors of this presentation and resulted in a section of the workshop summary report using the contributions from the topic’s several pre-recorded oral and poster presentations and the outcomes of two interactive real-time community-wide discussion sessions. The Earth-energy-balance topic issues centered on three areas: Radiometric energy measurements, including needed accuracies and stabilities and the use of SI-Traceable Satellites (SITSats), such as CLARREO and TRUTHS, to achieve them; improved on-orbit calibration sources, including the Sun and the Moon, thermal-infrared and UV sources, and space-flight blackbodies; and the four primary Earth-heat storage reservoirs of the oceans, land, permafrost, and cryosphere, giving an inventory of where and how much of the Earth’s energy is stored and how much uptake there is of the incoming energy. This presentation will summarize the results of the Earth Energy Balance topic from the 2022 BIPM-WMO Metrology for Climate Action Workshop.

earth↗
NASA NTRS2022

Impact of Clouds and Blowing Snow on Surface and Atmospheric Boundary Layer Properties over Dome C, Antarctica

Clouds and blowing snow (BLSN) occur frequently over Antarctica, where it is critical to understand their feedbacks to surface and atmospheric boundary layer processes. Dome C, an elevated East Antarctic station, dominated by lengthy periods of surface longwave (LW) radiative cooling, is selected to reveal cloud and BLSN impacts within a largely stable environment. The sky condition is classified as clear, cloudy, or BLSN, using 3 years of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite data. Co-located and contemporaneous in situ observations are used to investigate the relationship of sky condition with surface and atmospheric boundary layer thermal structure, focusing on seasonal variability. Results show that increased downwelling LW radiation from clouds abate surface radiative cooling losses, contributing to warming during all seasons. An increase of 3°C in the mean surface air temperature is observed during spring, whereas, a more dramatic rise (around 10°C), due to accompanying large-scale subsidence, is observed during fall and winter in association with clouds. For all seasons, the wind speed and wind speed shear are strongest during BLSN events, and the surface-based inversion is weakened by cooling which peaks in a shallow above-surface turbulent layer. The stronger background stability during fall and winter seasons, restricts turbulence and BLSN depths generally to the lowest tens of meters. The Earth's cryosphere is among the most rapidly evolving yet least well-observed regions, and knowledge of clouds and BLSN interactions with the typical stable atmospheric boundary layer can help further understand energy and moisture exchanges.

CALIPSO↗
NASA NTRSDate not supplied

Overview of Submesoscale-Climate Connections

In this talk, I will present a brief overview of some recent results and current research priorities regarding the significant participation of upper ocean / submesoscale processes in regional to global Earth system dynamics in a warming climate, such as ocean overturning, biogeochemistry, and heat and carbon uptake as well as atmospheric, coastal, and cryospheric dynamics. In addition to reviewing the evidence for these links by topic, I will highlight how advances in both understanding and prediction are derived from the integrated triad of process studies, modeling, and regional and global observing systems. Finally, I will discuss how triadic investments focused on these upper ocean processes might lead to better-informed decision-making for climate change adaptation and mitigation strategies.

Overview↗
NASA NTRSDate not supplied

Reanalysis Activities at the NASA Global Modeling and Assimilation Office

This talk presents an overview of recent reanalysis activities at the NASA Global Modeling and Assimilation Office (GMAO) as part of a multi-faceted strategy towards an Integrated Earth System retrospective analysis, coupling components of the atmosphere, ocean, chemistry, land, and ice. While elements of the atmosphere-ocean coupled Goddard Earth Observing System (GEOS) model and data assimilation are being actively developed, a suite of reanalysis products is designed to provide further understanding of key aspects of Earth system coupling in a reanalysis context: The baseline atmospheric reanalysis, the GEOS Retrospective analysis for the early 21st Century (GEOS-R21C), features recent advances in the GEOS model and data assimilation, and targets the NASA’s Earth Observing System EOS and post-EOS satellite observations; GEOS-IT, a user-tailored low-resolution atmospheric reanalysis, serves as a second baseline to the NASA Instrument Teams for validation and calibration and drives a one-way coupled ocean reanalysis, GEOSIT-Ocean; PolarMERRA, a high-resolution downscaled product for the polar regions, focuses on improving the representation of polar atmospheric processes with an assessment of current cryospheric biases, and targeted improvements to surface sea ice and glacier conditions; Finally, R21C-Chem, an off-line atmospheric chemistry and composition reanalysis, includes both tropospheric and stratospheric trace gases. The diversity of these reanalysis activities presents unique opportunities for collaborations cross-teams/institutions, with new commercial data partners, and with end-user groups. This talk will discuss these opportunities and explore leveraging the lessons learned along the way on key drivers in Earth system interactions as we converge towards the next generation of the Modern-Era Retrospective analysis for Research and Applications (MERRA) suite.

Amal El Akkraoui↗
NASA NTRS2021

Widespread Megaripple Activity Across the North Polar Ergs of Mars

The most expansive dune fields on Mars surround the northern polar cap where various aeolian bedform classes are modified by wind and ice. The morphology and dynamics of these ripples, intermediate-scale bedforms (termed megaripples and transverse aeolian ridges (TARs)), and sand dunes reflect information regarding regional boundary conditions. We found that populations of polar megaripples and larger TARs are distinct in terms of their morphology, spatial distribution, and mobility. Whereas regionally-restricted TARs appeared degraded and static in long-baseline observations, polar megaripples were not only widespread but migrating at relatively high rates (0.13± 0.03 m/Earth year) and possibly more active than other regions on Mars. This high level of activity is somewhat surprising since there is limited seasonality for aeolian transport due to surficial frost and ice during the latter half of the martian year. A comprehensive analysis of an Olympia Cavi dune field estimated that the advancement of megaripples, ripples, and dunes avalanches accounted for ~1%, ~10%, and ~100%, respectively, of the total aeolian system’s sand fluxes. This included dark-toned ripples that migrated the average equivalent of 9.6±6 m/yr over just 22 days in northern summer - unprecedented rates for Mars. While bedform transport rates are some of the highest yet reported on Mars, the sand flux contribution between the different bedforms does not substantially vary from equatorial sites with lower rates. Seasonal off-cap sublimation winds and summer-time polar storms are attributed as the cause for the elevated activity, rather than cryospheric processes. Plain Language Summary “Megaripples” are distinct wind-driven bedforms that occur on the surface of Earth and Mars, often with sizes between that of smaller ripples and larger dunes. Recent work has found the thin martian atmosphere can mobilize some coarse-grained megaripples, overturning prior notions that these were static relic landforms from a past climate. We mapped megaripples and adjacent bedforms across the north polar sand seas, the most expansive collection of dune fields on Mars. Megaripples were found to be widespread across the region and migrating at relatively high rates relative to other sites on Mars that are at lower latitudes. This enhanced activity is likely related to the greater sand fluxes found for neighboring dunes which are driven by summer-time seasonal winds when polar ice is sublimating. In contrast, other megaripples appear to be stabilized, a likely result of inter-granular ice within low wind areas.

Matthew Chojnacki↗
NASA NTRSDate not supplied

NASA EOSDIS 20 Years of Data Usage and User Assessment in Support of Open Science Initiative

NASA EOS Data and Information System (EOSDIS) has been distributing data to world-wide users free with open access. Since the launch of NASA’s Terra satellite in 1999, more than 10,000 distinct EOS data products have been archived and distributed by NASA-funded Earth Science data centers encompassed by the EOSDIS. As of September 30, 2022, more than 90 PB of data archived by EOSDIS have been made available to public users and during FY 2023 over 60 PB have been distributed to public users worldwide. Over these twenty and more years, it has shown significant increase in the distribution of various data products. This has been possible due to free and open access of the data thereby a step towards open science initiative. The purposes of this study are 1) to perform a comprehensive investigation of the archive and distribution patterns of EOSDIS data products for last 20 years, 2) to identify and characterize the global user community for those data, 3) analyze the increased demand for data products, 4) evaluate distribution of higher level products because those are the ones most frequently used in the studies of natural disasters by public users (those data requestors not involved directly in the production or validation of the data products.) and contribute globally to the advance scientific understanding of the Earth-Atmosphere Systems. Funded by the Earth Science Data and Information System (ESDIS) Project, the ESDIS Metrics System (EMS) collects archive, distribution, and user information from EOSDIS data centers. The information (comprising all data products including heritage datasets going back to the 1990s) is stored in a relational database from which it can be analyzed in many ways. We present several metrics analyses that include data distribution patterns for all, as well as the most frequently requested data products; and user characterizations by country, domain, and Earth Science discipline (e.g., Land, Ocean, Cryosphere) of the requested products. Due to the enormous quantity of data handled by EOSDIS data centers and requirements of future data systems to archive increasing amounts of Earth Science data from future and current Earth Science missions effectively, the results of this study can provide insight on how the user communities have accessed the data and provide guidance for open science initiative.

Lalit Wanchoo↗
NASA NTRS2023

Sea Surface Temperature Gradients Estimation Using Top-of-Atmosphere Observations from the ESA Earth Explorer 10 Harmony Mission: Preliminary Studies

The Harmony satellite mission was recently approved as the next European Space Agency (ESA) Earth Explorer 10. The mission science objectives cover several applications related to solid earth, the cryosphere, upper-ocean dynamics and air–sea interactions. The mission consists of a constellation of two satellites, flying with the Copernicus Sentinel 1 (C or D) spacecraft, each hosting a C-band receive-only radar and a thermal infrared (TIR) payload. From an ocean dynamics/air–sea interaction perspective, the mission will provide the unique opportunity to observe simultaneously the signature of submesoscale upper-ocean processes via synthetic aperture radar and TIR imagery. The TIR imager is based on microbolometer technology and its acquisitions will rely on four channels: three narrow-band channels yielding observations at a ≃1 km spatial sampling distance (SSD) and a panchromatic (PAN, 8–12 μm) channel characterized by a ≃300 m SSD. Our study investigates the potential of Harmony in retrieving spatial features related to sea surface temperature (SST) gradients from the high-resolution PAN channel, relying on top-of-atmosphere (TOA) observations. Compared to a standard SST gradient retrieval, our approach does not require atmospheric correction, thus avoiding uncertainties due to inter-channel co-registration and radiometric consistency, with the possibility of exploiting the higher resolution of the PAN channel. The investigations were carried out simulating the future Harmony TOA radiances (TARs), as well as relying on existing state-of-the-art level 1 satellite products. Our approach enables the correct description of SST features at the sea surface avoiding the generation of spurious features due to atmospheric correction and/or instrumental issues. In addition, analyses based on existing satellite products suggest that the clear-sky TOA observations, in a typical mid-latitude scene, allow the reconstruction of up to 85% of the gradient magnitudes found at the sea-surface level. The methodology is less efficient in tropical areas, suffering from smoothing effects due to the high concentrations of water vapor.

sea surface temperature (SST)↗
NASA NTRS2024

Applications of ArcticDEM for measuring volcanic dynamics, landslides, retrogressive thaw slumps, snowdrifts, and vegetation heights

Topographical changes are of fundamental interest to a wide range of Arctic science disciplines faced with the need to anticipate, monitor, and respond to the effects of climate change, including geohazard management, glaciology, hydrology, permafrost, and ecology. This study demonstrates several geomorphological, cryospheric, and biophysical applications of ArcticDEM – a large collection of publicly available, time-dependent digital elevation models (DEMs) of the Arctic. Our study illustrates ArcticDEM's applicability across different disciplines and five orders of magnitude of elevation derivatives, including measuring volcanic lava flows, ice cauldrons, post-failure landslides, retrogressive thaw slumps, snowdrifts, and tundra vegetation heights. We quantified surface elevation changes in different geological settings and conditions using the time series of ArcticDEM. Following the 2014–2015 Bárðarbunga eruption in Iceland, ArcticDEM analysis mapped the lava flow field, and revealed the post-eruptive ice flows and ice cauldron dynamics. The total dense-rock equivalent (DRE) volume of lava flows is estimated to be (1431 ± 2) million m 3 . Then, we present the aftermath of a landslide in Kinnikinnick, Alaska, yielding a total landslide volume of (400 ± 8) × 103 m 3 and a total area of 0.025 km 2 . ArcticDEM is further proven useful for studying retrogressive thaw slumps (RTS). The ArcticDEM-mapped RTS profile is validated by ICESat-2 and drone photogrammetry resulting in a standard deviation of 0.5 m. Volume estimates for lake-side and hillslope RTSs range between 40,000 ± 9000 m 3 and 1,160,000 ± 85,000 m 3 , highlighting applicability across a range of RTS magnitudes. A case study for mapping tundra snow demonstrates ArcticDEM's potential for identifying high-accumulation, late-lying snow areas. The approach proves effective in quantifying relative snow accumulation rather than absolute values (standard deviation of 0.25 m, bias of −0.41 m, and a correlation coefficient of 0.69 with snow depth estimated by unmanned aerial systems photogrammetry). Furthermore, ArcticDEM data show its feasibility for estimating tundra vegetation heights with a standard deviation of 0.3 m (no bias) and a correlation up to 0.8 compared to the light detection and ranging (LiDAR). The demonstrated capabilities of ArcticDEM will pave the way for the broad and pan-Arctic use of this new data source for many disciplines, especially when combined with other imagery products. The wide range of signals embedded in ArcticDEM underscores the potential challenges in deciphering signals in regions affected by various geological processes and environmental influences.

Chunli Dai↗
NASA NTRS2024

Global Sensitivity Analysis of Simulated Remote Sensing Polarimetric Observations Over Snow

This study presents a detailed theoretical assessment of the information content of passive polarimetric observations over snow scenes, using a global sensitivity analysis (GSA) method. Conventional sensitivity studies focus on varying a single parameter while keeping all other parameters fixed. In contrast, the GSA correctly addresses the covariance of state parameters across their entire parameter space, hence favoring a more correct interpretation of inversion algorithms and the optimal design of their state vectors. The forward simulations exploit a vector radiative transfer model to obtain the Stokes vector emerging at the top of the atmosphere for different solar zenith angles, when the bottom boundary consists of a vertically resolved snowpack of non-spherical grains. The presence of light-absorbing particulates (LAPs), either embedded in the snow or aloft in the atmosphere above in the form of aerosols, is also considered. The results are presented for a set of wavelengths spanning the visible (VIS), near-infrared (NIR), and shortwave infrared (SWIR) region of the spectrum. The GSA correctly captures the expected, high sensitivity of the reflectance to LAPs in the VIS–NIR and to grain size at different depths in the snowpack in the NIR–SWIR. With adequate viewing geometries, mono-angle measurements of total reflectance in the VIS–SWIR (akin to those of the Moderate Resolution Imaging Spectroradiometer, MODIS) resolve grain size in the top layer of the snowpack sufficiently well. The addition of multi-angle polarimetric observations in the VIS–NIR provides information on grain shape and microscale roughness. The simultaneous sensitivity in the VIS–NIR to both aerosols and snow-embedded impurities can be disentangled by extending the spectral range to the SWIR, which contains information on aerosol optical depth while remaining essentially unaffected when the same particulates are mixed with the snow. Multi-angle polarimetric observations can therefore (i) effectively partition LAPs between the atmosphere and the surface, which represents a notorious challenge for snow remote sensing based on measurements of total reflectance only and (ii) lead to better estimates of grain shape and roughness and, in turn, the asymmetry parameter, which is critical for the determination of albedo. The retrieval uncertainties are minimized when the degree of linear polarization is used in place of the polarized reflectance. The Sobol indices, which are the main metric for the GSA, were used to select the state parameters in retrievals performed on data simulated for multiple instrument configurations. Improvements in retrieval quality with the addition of measurements of polarization, multi-angle views, and different spectral channels reflect the information content, identified by the Sobol indices, relative to each configuration. The results encourage the development of new remote sensing algorithms that fully leverage multi-angle and polarimetric capabilities of modern remote sensors. They can also aid flight planning activities, since the optimal exploitation of the information content of multi-angle measurements depends on the viewing geometry. The better characterization of surface and atmospheric parameters in snow-covered regions advances research opportunities for scientists of the cryosphere and ultimately benefits albedo estimates in climate models.

remote sensing↗
NASA NTRSDate not supplied

Managing Current Earth Observation Needs through User-Driven Implementation of Upcoming Satellite Needs Working Group (SNWG) Solutions

Since 2016, the Satellite Needs Working Group (SNWG), an initiative of the U.S. Group on Earth Observations (USGEO), has surveyed federal agencies every two years to identify their satellite earth observation needs. For each expressed need, NASA-led assessment teams coordinate with responding agencies to devise remote sensing solutions that benefit multiple partners and span across a number of thematic areas including, but not limited to, Atmospheric Composition, Carbon Cycle and Ecosystems, Earth Surface and Interior, and Oceans and Cryosphere. Solutions can comprise existing or modified data products as well as the construction of new data products and technologies: since 2016, a multitude of SNWG activities have been theorized and developed, reaching a wide range of users in the science community. Due to an increase in survey responses in 2020 and to assure solution delivery to users within five years of budget appropriations, the SNWG Management Office was established to oversee the assessment of agency needs and the implementation and operations of solution development. The SNWG MO’s unique implementation strategy creates multiple touchpoints with agencies during solution development helping fulfill Earth Science to Action priorities (the 2024 NASA Earth Science Division strategic plan) and ensuring solutions are accessible, usable, and support decision-making for their intended audience. This presentation will outline the ways in which SNWG supports complementary goals of the Decadal Survey, with specific attention on the SNWG MO’s renewed user-centric implementation strategy for upcoming SNWG solutions.

Jenny Wood↗
NASA NTRS2014

A Spurious Jump in the Satellite Record: Has Antarctic Sea Ice Expansion Been Overestimated?

Recent estimates indicate that the Antarctic sea ice cover is expanding at a statistically significant rate with a magnitude one-third as large as the rapid rate of sea ice retreat in the Arctic. However, during the mid-2000s, with several fewer years in the observational record, the trend in Antarctic sea ice extent was reported to be considerably smaller and statistically indistinguishable from zero. Here, we show that much of the increase in the reported trend occurred due to the previously undocumented effect of a change in the way the satellite sea ice observations are processed for the widely used Bootstrap algorithm data set, rather than a physical increase in the rate of ice advance. Specifically, we find that a change in the intercalibration across a 1991 sensor transition when the data set was reprocessed in 2007 caused a substantial change in the long-term trend. Although our analysis does not definitively identify whether this change introduced an error or removed one, the resulting difference in the trends suggests that a substantial error exists in either the current data set or the version that was used prior to the mid- 2000s, and numerous studies that have relied on these observations should be reexamined to determine the sensitivity of their results to this change in the data set. Furthermore, a number of recent studies have investigated physical mechanisms for the observed expansion of the Antarctic sea ice cover. The results of this analysis raise the possibility that much of this expansion may be a spurious artifact of an error in the processing of the satellite observations.

Cryosphere↗