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At least 379 records · Page 21

Brief Communication: Mapping Greenland’s Perennial Firn Aquifers Using Enhanced-Resolution L-Band Brightness Temperature Image Time Series

Enhanced-resolution L-band brightness temperature (TB) image time series generated from observations collected over the Greenland Ice Sheet by NASA’s Soil Moisture Active Passive (SMAP) satellite are used to map Greenland’s perennial firn aquifers from space. Exponentially decreasing L-band T(sub B) signatures are correlated with perennial firn aquifer areas identified via the Center for Remote Sensing of Ice Sheets (CReSIS) Multi-Channel Coherent Radar Depth Sounder (MCoRDS) that was flown by NASA’s Operation IceBridge (OIB) campaign. An empirical algorithm to map extent is developed by fitting these signatures to a set of sigmoidal curves. During the spring of 2016, perennial firn aquifer areas are found to extend over ~ 66 000 km(exp 2).

Julie Z Miller↗

Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding

As spacecraft send back increasing amounts of telemetry data, improved anomaly detection systems are needed to lessen the monitoring burden placed on operations engineers and reduce operational risk. Current spacecraft monitoring systems only target a subset of anomaly types and often require costly expert knowledge to develop and maintain due to challenges involving scale and complexity. We demonstrate the effectiveness of Long Short-Term Memory (LSTMs) networks, a type of Recurrent Neural Network (RNN), in overcoming these issues using expert-labeled telemetry anomaly data from the Soil Moisture Active Passive (SMAP) satellite and the Mars Science Laboratory (MSL) rover, Curiosity. We also propose a complementary unsupervised and nonparametric anomaly thresholding approach developed during a pilot implementation of an anomaly detection system for SMAP, and offer false positive mitigation strategies along with other key improvements and lessons learned during development.

Soderstrom, Tom↗

Improving SMAP freeze-thaw retrievals for pavements using effective soil temperature from GEOS-5: Evaluation against in situ road temperature data over the U.S

Seasonal freeze-thaw (FT) affects over half the northern hemisphere and impacts many key processes of the Earth System such as energy exchange, hydrology and vegetation. Nearly all past studies using spaceborne FT retrievals have focused on characterizing FT specifically for natural environments. FT in the built environment is also routinely studied and a topic of great interest, especially with regards to transportation infrastructure. Whereas natural FT process are frequently investigated using spaceborne observations, FT studies of roads are often limited to local scales, using in situ or nearby weather station data only. Comparisons between FT retrievals obtained from NASA's Soil Moisture Active Passive (SMAP) satellite and roads in Alaska (AK) and the Contiguous United States (CONUS) showed that spaceborne FT retrievals had good agreement with road data. But those results also indicated that NASA FT retrievals in CONUS were relatively too warm compared to road data. If SMAP FT retrievals were to be used for identifying FT transition timing for applications by the transportation community, it is also important for frozen conditions to be identified more accurately. This work is primarily concerned with improving frozen retrievals made in CONUS by calculating new Normalized Polarization Ratio (NPR) thresholds as compared to those currently used in SMAP FT. We found that focusing on a temporal subset of October through May for comparisons greatly improved the correlation between NPR and effective soil temperature (Teff, one of SMAP's ancillary datasets), often from about zero to 0.6. We then applied linear regression between NPR and Teff to obtain new NPR thresholds resulting in the FT-Roads (FT-R) product. NASA FT and FT-R were evaluated against road data at about 1000 locations in CONUS and a battery of different tests indicated that FT-R performed better under nearly all conditions compared to NASA FT. Overall, NASA FT accuracies were 69% and 80% for 6 am and 6 pm SMAP retrievals, while FT-R achieved accuracies of 79% and 82%. We also investigated the potential for using Teff for road FT (6 am, only) and found that those comparisons were even more accurate (84%). We've also quantified inter- and intraregional differences of SMAP FT performance and found that accuracy metrics vary over twice as much between geographic subdivisions (9%) as compared to between the states within a subdivision (4%). Most importantly, the main goal of improving the detection of in situ frozen conditions in CONUS was realized, with FT-R accurately detecting frozen conditions >50% more frequently than NASA FT.

Passive microwave↗

An Observationally-Based Determination of the Arctic Sea Ice-Cloud Feedback Since 2000: Isolating the Arctic Cloud Response to Sea Ice Loss

Arctic sea ice responds to and drives Arctic climate change. The interactions between Arctic sea ice and clouds represent a mechanism through which sea ice can drive climate change. We composite active remote sensing satellite cloud properties for ice-free, marginal ice zone (MIZ), and ice-covered surfaces during MIZ crossing events to investigate the influence of the transition from an ice-covered to an ice-free surface on low-level clouds. We demonstrate that the event-based methodology controls for large-scale meteorological factors and isolates the sea ice effect on clouds. We find larger cloud fraction and total water content below ~1.5 km over ice-free relative to ice-covered surfaces during non-summer months, indicating a low-level cloud sensitivity to Arctic sea ice decline. During summer, results show larger cloud fraction and water content over ice-free surfaces, however the differences are statistically indistinguishable. Evidence is provided that atmospheric thermodynamic profile differences cause the cloud property differences, namely that ice-free footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their ice-covered counterparts. Ice-free and ice-covered surface cloud property differences scale with surface temperature differences such that cloud property differences are only found in the presence of a surface temperature difference. We conclude that surface temperature differences modulate the cloud response to sea ice loss through influences on surface turbulent fluxes and lower tropospheric stability. The results imply a positive non-summer sea ice-cloud feedback and that up to a 0.02 cloud fraction and 0.05 g m 3 total water content increase in fall are due to the observed sea ice decline.

Patrick C Taylor↗

Effect of Assimilating SMAP Soil Moisture on CO2 and CH4 Fluxes through Direct Insertion in a Land Surface Model

Soil moisture impacts the biosphere–atmosphere exchange of CO2 and CH4 and plays an important role in the terrestrial carbon cycle. A better representation of soil moisture would improve coupled carbon–water dynamics in terrestrial ecosystem models and could potentially improve model estimates of large-scale carbon fluxes and climate feedbacks. Here, we investigate using soil moisture observations from the Soil Moisture Active Passive (SMAP) satellite mission to inform simulated carbon fluxes in the global terrestrial ecosystem model LPJ-wsl. Results suggest that the direct insertion of SMAP reduces the bias in simulated soil moisture at in situ measurement sites by 40%, with a greater improvement at temperate sites. A wavelet analysis between the model and measurements from 26 FLUXNET sites suggests that the assimilated run modestly reduces the bias of simulated carbon fluxes for boreal and subtropical sites at 1–2-month time scales. At regional scales, SMAP soil moisture can improve the estimated responses of CO2 and CH4 fluxes to extreme events such as the 2018 European drought and the 2019 rainfall event in the Sudd (Southern Sudan) wetlands. The simulated improvements to land–surface carbon fluxes using the direct insertion of SMAP are shown across a variety of timescales, which suggests the potential of SMAP soil moisture in improving the model representation of carbon–water coupling.

SMAP↗

Estimating the Arctic Cloud-Sea Ice Feedback With Observations during the EOS Period

Arctic sea ice responds to and drives Arctic climate change. The interactions between Arctic sea ice and clouds represent a mechanism through which sea ice can drive climate change. We composite active remote sensing satellite cloud properties for ice-free, marginal ice zone (MIZ), and ice-covered surfaces during MIZ crossing events to investigate the influence of the transition from an ice-covered to an ice-free surface on low-level clouds. We demonstrate that the event-based methodology controls for large-scale meteorological factors and isolates the sea ice effect on clouds. We find larger cloud fraction and total water content below ~1.5 km over ice-free relative to ice-covered surfaces during non-summer months, indicating a low-level cloud sensitivity to Arctic sea ice decline. During summer, results show larger cloud fraction and water content over ice-free surfaces, however the differences are statistically indistinguishable. Evidence is provided that atmospheric thermodynamic profile differences cause the cloud property differences, namely that ice-free footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their ice-covered counterparts. Ice-free and ice-covered surface cloud property differences scale with surface temperature differences such that cloud property differences are only found in the presence of a surface temperature difference. We conclude that surface temperature differences modulate the cloud response to sea ice loss through influences on surface turbulent fluxes and lower tropospheric stability. The results imply a positive non-summer sea ice-cloud feedback and that up to a 0.02 cloud fraction and 0.05 g m 3 total water content increase in fall are due to the observed sea ice decline.

Patrick C. Taylor↗

SMAP Science and Application Results

Science and application results appearing in peer-reviewed journal papers in 2021 are highlighted in this paper. With over six years of science data acquisition, science data products of the NASA Soil Moisture Active Passive (SMAP)satellite project are now being applied in diverse subdisciplines in Earth System science. In 2021, there were close to two-hundred papers appearing in peer-reviewed disciplinary journals. In this paper we highlight a few of the research and applications findings that were reported in the calendar year.

Dara Entekhabi↗

Ice Sheet Melt Water Profile Mapping Using Multi-frequency Microwave Radiometry

For understanding englacial hydrology and its impact on ice sheet mass balance, observations of the liquid water content (LWC) within the ice sheets are needed. Earlier studies have shown the complementary nature of multi-frequency microwave radiometer measurements to detect subsurface LWC distribution in addition to surface LWC, which is critical for understanding the seasonal melt dynamics of ice sheets. In this study, we used 1.4 GHz brightness temperature (TB) measurements from the NASA Soil Moisture Active Passive (SMAP) satellite, and 6.9, 10.7, 18.9, and 36.5 GHz TB measurements from the JAXA Global Change Observation Mission-Water Shizuku (GCOM-W) satellite to investigate the multi-frequency response at pan-Greenland scale. The melt indications derived at different frequencies show trends consistent with persistent seasonal subsurface melt water and delayed subsurface refreezing of the seasonal melt water. The result suggests that the seasonal subsurface persistent melt water occurrences that are not captured by the high-frequency retrievals are both temporally and spatially very significant.

Burgin, Mariko↗

Validating Salinity from SMAP and HYCOM Data with Saildrone Data during EUREC4A-OA/ATOMIC

The 2020 ‘Elucidating the role of clouds-circulation coupling in climate-Ocean-Atmosphere’ (EUREC4A-OA) and the ‘Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign’ (ATOMIC) campaigns focused on improving our understanding of the interaction between clouds, convection and circulation and their function in our changing climate. The campaign utilized many data collection technologies, some of which are relatively new. In this study, we used saildrone uncrewed surface vehicles, one of the newer cutting edge technologies available for marine data collection, to validate Level 2 and Level 3 Soil Moisture Active Passive (SMAP) satellite and Hybrid Coordinate Ocean Model (HYCOM) sea surface salinity (SSS) products in the Western Tropical Atlantic. The saildrones observed fine-scale salinity variability not present in the lower-spatial resolution satellite and model products. In regions that lacked significant small-scale salinity variability, the satellite and model salinities performed well. However, SMAP Remote Sensing Systems (RSS) 70 km generally outperformed its counterparts outside of areas with submesoscale SSS variation, whereas RSS 40 km performed better within freshening events such as a fresh tongue. HYCOM failed to detect the fresh tongue. These results will allow researchers to make informed decisions regarding the most ideal product and its drawbacks for their applications in this region and aid in the improvement of mesoscale and submesoscale SSS products, which can lead to the refinement of numerical weather prediction (NWP) and climate models.

Kashawn Hall↗

Basic research and data analysis for the national geodetic satellite program and for the earth and ocean physics applications program

Activities related to the National Geodetic Satellite Program are reported and include a discussion of Ohio State University's OSU275 set of tracking station coordinates and transformation parameters, determination of network distortions, and plans for data acquisition and processing. The problems encountered in the development of the LAGEOS satellite are reported in an account of activities related to the Earth and Ocean Physics Applications Program. The LAGEOS problem involves transmission and reception of the laser pulse designed to make accurate determinations of the earth's crustal and rotational motions. Pulse motion, ephemeris, arc range measurements, and accuracy estimates are discussed in view of the problem. Personnel involved in the two programs are also listed, along with travel activities and reports published to date.

Source record↗

Coordinated ATS 5 electron flux and simultaneous auroral observations

An attempt is made to correlate ATS 5 plasma data with all-sky photographic data taken at Thompson and Gillam, Manitoba. The fields of view of the Canadian stations cover the projected field line position of the satellite. Trapped electron fluxes at the satellite and the simultaneously measured auroral activity near the projected foot of the satellite field line were compared for several days of varying substorm activity with all-sky camera data, which was in the form of time-varying luminosity plots. The observed auroral intensification coincident with plasma injection shows that on a broad scale the auroras are correlated well with the magnetospheric trapped plasma; however, there is a lack of detailed correlation between the fine structure of the trapped plasma fluxes and the small scale auroral features.

Mende, S. B.↗

Major Characteristics of Southern Ocean Cloud Regimes and Their Effects on the Energy Budget

Clouds over the Southern Ocean are often poorly represented by climate models, but they make a significant contribution to the top-of-atmosphere (TOA) radiation balance, particularly in the shortwave portion of the energy spectrum. This study seeks to better quantify the organization and structure of Southern Hemisphere midlatitude clouds by combining measurements from active and passive satellite-based datasets. Geostationary and polar-orbiter satellite data from the International Satellite Cloud Climatology Project (ISCCP) are used to quantify large-scale, recurring modes of cloudiness, and active observations from CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are used to examine vertical structure, radiative heating rates, and precipitation associated with these clouds. It is found that cloud systems are organized into eight distinct regimes and that ISCCP overestimates the midlevel cloudiness of these regimes. All regimes contain a relatively high occurrence of low cloud, with 79%of all cloud layers observed having tops below 3 km, but multiple-layered clouds systems are present in approximately 34% of observed cloud profiles. The spatial distribution of regimes varies according to season, with cloud systems being geometrically thicker, on average, during the austral winter. Those regimes found to be most closely associated with midlatitude cyclones produce precipitation the most frequently, although drizzle is extremely common in low-cloud regimes. The regimes associated with cyclones have the highest in-regime shortwave cloud radiative effect at the TOA, but the low-cloud regimes, by virtue of their high frequency of occurrence over the oceans, dominate both TOA and surface shortwave effects in this region as a whole.

Haynes, John M.↗

Comparison of ground and satellite based measurements of the fraction of photosynthetically active radiation intercepted by tall-grass prairie

The fraction, of photosynthetically active radiation absorbed by vegetation, F sub ipar, is an important requirement for estimating vegetation biomass productivity and related quantities. This was an integral part of a large international effort; the First ISLSCP Field Experiment (FIFE). The main objective of FIFE was to study the effects of vegetation on the land atmosphere interactions and to determine if these interactions can be assessed from satellite spectral measurements. The specific purpose of this experiment was to find out how well measurements of F sub ipar relate to ground, helicopter, and satellite based spectral reflectance measurements. Concurrent measurements of F sub ipar and ground, helicopter, and satellite based measurements were taken at 13 tall grass prairie sites in Kansas. The sites were subjected to various combinations of burning and grazing managements.

Demetriades-Shah, T. H.↗

Comparison of ground and satellite based measurements of the fraction of photosynthetically active radiation intercepted by tall-grass prairie

The fraction, of photosynthetically active radiation intercepted by vegetation, F(sub ipar) is an important parameter for modeling the interactions between the land-surface and atmosphere and for estimating vegetation biomass productivity. This study was; therefore, an integral part of FIFE. The specific purpose of this experiment was to find out how well definitive measurements of F(sub ipar) on the ground relate to near-ground and satellite based spectral reflectance measurements. Concurrent measurements of F(sub ipar) and ground, helicopter, and satellite based reflectance measurements were taken at thirteen tall-grass prairie sites within the FIFE experimental area. The sites were subjected to various combinations of burning and grazing managements. The ground and helicopter based reflectance measurements were taken on the same day or few days from the time of the overpass of LANDSAT and SPOT satellites. Ground-based reflectance measurements and sun photometer readings taken at the times of the satellite overpasses were used to correct for atmospheric attenuation. Hand-held radiometer spectral indices were strongly correlated with helicopter and satellite based values (r=0.94 for helicopter, 0.93 for LANDSAT Thematic Mapper, and 0.86 for SPOT). However, the ground, helicopter, and satellite based normalized difference spectral vegetation indices showed low sensitivity to changes in F(sub ipar). Reflectance measurements were only moderately well correlated with measurements of F(sub ipar) (r=0.82 for hand-held radiometer, 0.84 for helicopter measurements, and 0.75 for the LANDSAT Thematic Mapper and SPOT). Improved spectral indices which can compensate for site differences are needed in order to monitor F(sub ipar) more reliably.

Demetriades-Shah, T. H.↗

Comparison of ground and satellite based measurements of the fraction of photosynthetically active radiation intercepted by tall-grass prairie

The fraction of photosynthetically active radiation intercepted by vegetation, F(sub ipar) is an important parameter for modeling the interactions between the land-surface and atmosphere and for estimating vegetation biomass productivity. This study was, therefore, an integral part of FIFE. The specific purpose of this experiment was to find out how well definitive measurements of F(sub ipar) on the ground relate to near-ground and satellite based spectral reflectance measurements. Concurrent measurements of F(sub ipar) and ground, helicopter, and satellite based reflectance measurements were taken at thirteen tall-grass prairie sites within the FIFE experimental area. The sites were subjected to various combinations of burning and grazing managements. The ground and helicopter based reflectance measurements were taken on the same day or few days from the time of the overpass of LANDSAT and SPOT satellites. Ground-based reflectance measurements and sun photometer readings taken at the times of the satellite overpasses were used to correct for atmospheric attenuation. Hand-held radiometer spectral indices were strongly correlated with helicopter and satellite based values (r = 0.94 for helicopter, 0.93 for LANDSAT Thematic Mapper, and 0.86 for SPOT). However, the ground, helicopter, and satellite based normalized difference spectral vegetation indices showed low sensitivity to changes in F(sub ipar). Reflectance measurements were only moderately well correlated with measurements of F(sub ipar) (r = 0.82 for hand-held radiometer, 0.84 for helicopter measurements, and 0.75 for the LANDSAT Thematic Mapper and SPOT). Improved spectral indices which can compensate for site differences are needed in order to monitor F(sub ipar) more reliably.

Demetriades-Shah, T. H.↗

Evaluation and Validation of a High Spatial Resolution Satellite Soil Moisture Product over the Continental United States

The soil moisture (SM) data retrieved from the Soil Moisture Active and Passive (SMAP) satellite are available at a 9 km grid spacing since April 2015. This product can provide valuable information for research and applications in hydrology and other related fields. However, the resolution may be too coarse for applications at catchment or field scale. In this study, an established downscaling methodology, which had a major modification regarding its application on the SMAP 33 km domain, was implemented to develop a 1 km soil moisture product based on the SMAP 9 km data. The algorithm proposed here is based on the thermal inertia principle and developed by modeling the relationship between surface temperature difference and SM for different Normalized Difference Vegetation Index (NDVI) classes. The model functions were established and tuned using data from the NASA’s Land Information System (LIS) North America Land Data Assimilation System (NLDAS) and remotely sensed VISible/InfRared (VIS/IR) reflectance data from Long Term Data Record (LTDR) AVHRR (Advanced Very High Resolution Radiometer) for the growing season months of April-September 1981–2018. These were then implemented using the MODIS (Moderate Resolution Imaging Spectroradiometer) data over the Continental United States (CONUS) domain. Validation activities were carried out using in situ measurements distributed through the International Soil Moisture Network (ISMN). The validation results computed using the 1 km SM data showed that the R2, unbiased RMSE (root mean square error) and bias were improved relative to the 9 km SMAP product by 0.045, 0.018m3/m3 and 0.001m3/m3, respectively. The 1 km SM also exhibited a strong time-series autocorrelation. Further accuracy assessment analyses indicated that precipitation might contribute to the uncertainties in both the 9 km SMAP and 1 km downscaled SMAP SM products.

SMAP↗

Air Quality Study Using Satellites - Current Capability and Future Plans

Satellite instruments have had great success in monitoring the stratospheric ozone and in understanding the processes that control its daily to decadal scale variations. This field is now reaching its zenith with a number of satellite instruments from the US, Europe and Canada capping several decades of active research in this field. The primary public policy imperative of this research was to make reliable prediction of increases in biologically active surface UV radiation due to human activity. By contrast retrieval from satellite data of atmospheric constituents and photo-chemically active radiation that affect air quality is a new and growing field that is presenting us with unique challenges in measurement and data interpretation. A key distinction compared to stratospheric sensors is the greatly enhanced role of clouds, aerosols, and surfaces (CAS) in determining the quality and quantity of useful data that is available for air quality research. In our presentation we will use data from several sensors that are currently flying on the A-train satellite constellation, including OMI, MODIS, CLOUDSAT, and CALIPSO, to highlight that CAS can have both positive and negative effects on the information content of satellite measurements. This is in sharp contrast to other fields of remote sensing where CAS are usually considered an interference except in those cases when they are the primary subject of study. Our analysis has revealed that in the reflected wavelengths one often sees much further down into the atmosphere, through most cirrus, than one does in the emitted wavelengths. The lower level clouds provide a nice background against which one can track long-range transport of trace gases and aerosols. In addition, differences in trace gas columns estimated over cloudy and adjacent clear pixels can be used to measure boundary layer trace gases. However, in order to take full advantage of these features it will be necessary to greatly advance our understanding of how CAS affect the radiation at wavelengths that are used to derive the atmospheric constituents that affect air quality as well as the radiation that controls the photolysis of chemically active trace gases. We will discuss how we are using these new insights to design future satellite missions to study air quality.

Bhartia, Pawan K.↗