Mission Data Research Articles

Geographical Distribution of Thundersnow Events and Their Properties From GPM Ku‐Band Radar

AbstractSix‐years (2010–2015) of snow lightning characteristics and climatology, including seasonal, diurnal, and surface temperature distribution, are generated. The World Wide Lightning Location Network (WWLLN) and the National Lightning Detection Network lightning observations are collocated with Modern‐Era Retrospective Analysis for Research and Application (MERRA‐2) temperatures. Cold season lightning events are identified as lightning with the MERRA‐2 two‐meter surface temperature colder than 0 °C and then further classified as snow lightning or thundersnow, when the entire vertical temperature profile is below 2 °C, and as freezing rain lightning when there is a temperature warmer than 2 °C somewhere in the column above the freezing surface. The statistics of snow lightning events from WWLLN and National Lightning Detection Network are well matched and are consistent with the climatology of thundersnow days reported at ground‐based stations over the United States. Using 4 years of observations from the Global Precipitation Measuring Mission Ku band radar, 443 Thunder Snow Features (TSFs) are defined, having a contiguous area of nonzero near surface snow precipitation derived from the Ku band radar and MERRA‐2 data, along with collocated WWLLN lightning flashes. The majority (about 394) are found over high mountainous regions such the Himalayas, Tibet, the Andes, and the Zagros mountain regions. Low‐elevation TSFs (45) are observed over the continental and coastal regions. Though only a small number of TSFs are identified with 4 years of Global Precipitation Mission data, most TSFs have maximum radar reflectivity above 30 dBZ at temperature colder than −10 °C, which indicates the importance of the noninductive charging process in these events.

Discovery and Vetting of Exoplanets. I. Benchmarking K2 Vetting Tools

Abstract We have adapted the algorithmic tools developed during the Kepler mission to vet the quality of transit-like signals for use on the K2 mission data. Using the four sets of publicly available light curves at MAST, we produced a uniformly vetted catalog of 772 transiting planet candidates from K2 as listed at the NASA Exoplanet Archive in the K2 Table of Candidates. Our analysis marks 676 of these as planet candidates and 96 as false positives. All confirmed planets pass our vetting tests. Sixty of our false positives are new identifications, effectively doubling the overall number of astrophysical signals mimicking planetary transits in K2 data. Most of the targets listed as false positives in our catalog show either prominent secondary eclipses, transit depths suggesting a stellar companion instead of a planet, or significant photocenter shifts during transit. We packaged our tools into the open-source, automated vetting pipeline Discovery and Vetting of Exoplanets (DAVE), designed to streamline follow-up efforts by reducing the time and resources wasted observing targets that are likely false positives. DAVE will also be a valuable tool for analyzing planet candidates from NASA’s TESS mission, where several guest-investigator programs will provide independent light-curve sets—and likely many more from the community. We are currently testing DAVE on recently released TESS planet candidates and will present our results in a follow-up paper.

Contribution of a martian atmosphere to laser-induced breakdown spectroscopy (LIBS) data and testing its emission characteristics for normalization applications

For in-situ geochemical analysis of the surface of Mars, laser-induced breakdown spectroscopy (LIBS) is a very useful technique and the first extraterrestrial LIBS instrument ChemCam will soon be followed by others. Appropriate normalization of real mission data that is taken under varying experimental and environmental conditions from diverse geologic samples is an ongoing topic. One approach is the scaling to emission line intensities of carbon and oxygen from the CO2-dominated low-pressure martian atmosphere as an internal standard. Here, we performed several experiments to examine the emission of carbon and oxygen from a simulated martian atmosphere on simple, mostly mono-elemental samples, and to compare the emission characteristics of the elements of both origins. Differences in laser irradiance were found to have the biggest impact on sample emission lines scaled to C and O emission of the atmosphere. The temporal behavior shown in time-resolved LIBS measurements is dominated by the degree of ionization, but the ratio of the neutral emission from the sample to neutral emission from the atmosphere also varies over time. The effect of different grain sizes was minor in comparison to the high intrinsic variation in the LIBS data. Different samples were found to affect the absolute intensity of atmospheric C(I) more than O(I). Furthermore, the C(I) emission was found to be inseparably superimposed by iron if the latter was present in the target. The results indicate limitations of the general suitability of atmospheric carbon and oxygen emission for normalization purposes of martian LIBS data.

NASA’s Early Adopter Program Links Satellite Data to Decision Making

As the cost of satellite missions grow, government agencies are working to increase the relevance and usefulness of the Earth science data that they produce. The US National Aeronautics and Space Administration’s (NASA) early adopter program seeks to formalize partnerships with users of data early within the satellite planning process to ensure the greatest value of the mission. Scientists who are designing the satellite observing system, those who are developing mission data products, and the community who will use them need to work together to determine how satellite data can better inform decision making. NASA is working to initiate engagement with data users much earlier in the satellite program life so that the user needs can be prioritized, continue to engage with users throughout the development cycle, and then include analysis on societal impact after nominal mission life. The Early Adopter Program allows for broad and early engagement with decision makers by encouraging individuals and institutions with clear uses of data to engage with the mission. Early adopters facilitate feedback on mission products during pre-launch and accelerate the utilization of these products post-launch. This paper provides background and detail on how NASA is working to engage with early adopters, describes the partnership between early adopters and NASA missions, and connects the program to improved societal impacts of its satellite missions.

Hierarchical anomalies in drainage network: a case study from Western Ghats, South India

The Chalakudy river, a seventh order tropical drainage system emerging from the Western Ghats is flowing through the Southern Granulite Terrain of Peninsular India. Anomalies in the hierarchical organization of drainage networks reflect the effects of anthropogenic interferences and structural controls in the development of a drainage basin. The anomalies in the drainage composition are determined from bifurcation index, hierarchical parameters and stream gradient index. Computation of drainage indices is carried out with the aid of vectorized data derived from Survey of India (SOI) open series topo maps and Shuttle Radar Topographic Mission (SRTM) data (3Arc resolution) using ArcGIS 10.4 software. Here we discuss the quantitative methodology to determine the hierarchical anomaly index, hierarchical anomaly density and hierarchical anomaly number of drainage basin from geospatial data with an attempt to infer the degree of geomorphic evolution of the sub-basins from the analysis. The sub-basins are in their mature to the late mature stages of geomorphic evolution. It is observed that the tectonically induced diffusive process and anthropogenic interferences in the drainage basin altered the hierarchical organization of drainage network of Chalakudy river basin.

Data Analysis and Results of the Radiation-Tolerant Collaborative Computer On-Board OPTOS CubeSat

The current evolution of the space missions demands to increase the computing capacities of the on-board computer while reducing its power consumption. This requirement evolves faster than the ability of the manufacturers to develop better space-qualified processors. To meet the strong requirements, the National Institute of Aerospace Technology has developed a distributed on-board computer based on commercial off-the-shelf (COTS). This computer, named OPTOS, provides enhanced computational capacities with respect to what computers of other small satellites typically provide. To maintain the reliability needed to perform typical critical activities such as real-time maintenance or current surveillance, authors have conceived a set of collaborative hardening techniques, taking advantage of the distributed architecture of the OPTOS On-Board Computer. The 3-year mission data analysis shows the feasibility of the collaborative hardening techniques implemented, despite using SEU sensitive devices. The authors describe the processes and tools used to analyse the data and clearly expose the functional errors found at unit level, while the system remains unfaulty and reliable thanks to the collaborative techniques.

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing” reflectance (Rrs) for the 412, 443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 × 10−4, 5.49 × 10−4, 4.48 × 10−4, 2.51 × 10−4, 8.83 × 10−5, and 1.36 × 10−4 sr−1, respectively, and 1.09 × 10−2 mg m−3 for the chlorophyll-a concentration (Chl-a), 2.09 × 10−3 m−1 for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (ag (412)), and 3.7 mg m−3 for particulate organic carbon (POC). These Rrs values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

Data driven foreground clustering approach to component separation in multifrequency CMB experiments: a new Planck CMB map

We present a new approach to component separation in multifrequency CMB experiments by formulating the problem as that of partitioning the sky into pixel clusters such that within each pixel cluster the foregrounds have similar spectrum, using only the information available in the data. Only spectral information is used for partitioning, allowing spatially far away pixels to belong to the same cluster if their foreground properties are close. We then apply a modified internal linear combination method to each pixel cluster. Since the foregrounds have similar spectrum within each cluster, the number of components required to describe the foregrounds is smaller compared to all data taken together and simple pixel based ILC algorithm works extremely well. We test our algorithm in the full focal plane simulations provided by the Planck collaboration. We apply our algorithm to the Planck full mission data and compare our CMB maps with the CMB maps released by the Planck collaboration. We show that our CMB maps are clean and unbiased on a larger fraction of the sky, especially at the low Galactic latitudes, compared to publicly available maps released by the Planck collaboration. This is important for constraining beyond the simplest ΛCDM cosmological models and study of anomalies. Our cleaned CMB maps are made publicly available for use by the cosmology community.

Response of Indian monsoon to increase of resolution in NCAR-CAM5

Effects of increase in horizontal resolution (from 2°, to 1° and 0.5°) in simulating Indian summer monsoon (ISM) in Community Atmosphere Model version 5 (CAM5) are reported herein. Various parameters — temperature, rainfall, winds, surface evaporation, precipitable water, specific humidity, and clouds — of the model simulations are examined with respect to observations {India Meteorological Department (IMD) and Tropical Rainfall Measuring Mission (TRMM) data for precipitation and Modern-Era Retrospective analysis for Research and Applications (MERRA) products for rest of the variables}. With increase in horizontal resolution overall improvement in majority of surface driven parameters like surface air temperature, surface specific humidity, and low-level winds is observed that highlights the importance of better representation of orography. Over the Indian subcontinent and surrounding oceans, rainfall is overestimated due to the overestimation of the large-scale precipitation in the model, which significantly gets alleviated with increase in resolution. Overall, seasonal mean features of ISM show significant improvements, which are likely to further improve by representing finer spatial features with increase in resolution. However, some aspects of its temporal variations — seasonal, intraseasonal, and diurnal variations — of monsoon rainfall do not show much improvement with increase in resolution, suggesting that traditional physics parameterizations do not work well at high resolution and hence there is a need for improvement in model physics.

Solar Wind Directional Change Triggering Flapping Motions of the Current Sheet: MMS Observations

AbstractWe report on a flapping motion event near the substorm onset on 17 June 2017 using Magnetospheric Multiscale (MMS) mission data. A strong current density with a maximum value of ~190 nA/m2 is observed during the flapping. The north‐to‐south (south‐to‐north) crossing of the neutral sheet corresponds to an increase (a decrease) of the ZGSM component of the solar wind VZ, SW. The periods (~8 min) of the flapping and variations of VZ, SW are almost equal. In addition, dVZ, SW/dt and dBX/dt observed by MMS exhibit a strong negative correlation. These observations suggest that the flapping motions are triggered by the solar wind directional change via creating a motion of the current sheet in the north‐south direction. The pressure difference between the northern and southern lobes caused by the solar wind is expected to be a possible contribution to the formation of the flapping.

Evaluation of C-Band SAR for Identification of Flooded Vegetation in Emergency Response Products

A synthetic aperture radar (SAR) data set of the Peace Athabasca Delta, Alberta, was used to evaluate approaches to flooded vegetation mapping. A primary objective was to identify how to add a flooded vegetation layer to the Emergency Geomatics Service (EGS) SAR-derived flood products. Field data were used to identify non-flooded and flooded vegetation. A combination of statistical analyses and box plot visual inspection was used to evaluate the magnitude-only images, the polarimetric and compact polarimetric parameters/decompositions, and the coherence products for mapping flooded vegetation. This paper provides some background on the use of SAR for flood mapping, describes the data and processing methods, and presents the results of this comparison. To some degree all polarizations and techniques were effective for mapping flooded vegetation due to the increased backscatter intensity and the phase shift from the double bounce scattering. In particular, all polarization combinations, the HH/HV ratio, Shannon entropy, and the m-chi double bounce produce good separation. The water/vegetation interface remains coherent when flooded, also allowing flooded vegetation to be identified with seasonal coherence. These results demonstrate that the use of multi-mode RADARSAT Constellation Mission data for providing a flooded vegetation layer to EGS flood maps is possible.

Le bilan scientifique de la mission Megha-Tropiques après 8 ans dans l'espace

The Megha-Tropiques mission has been collecting observations of the water and energy cycle in the intertropical atmosphere since 2011. The use of these observations has demonstrated the relevance of its original orbit inclined over the Equator both for the precipitation estimates and for numerical weather prediction. The ongoing scientific exploration of the relationship between water vapor and clouds, the life cycle of tropical convective systems, and hydrometeorology has led to many advances that are briefly presented here. Many operational centres around the world are assimilating available mission data in real time thanks to recent advances in the interpretation of the 183 GHz measurement.

Determination of spatial distribution of topsoil organic carbon stock using geostatistical technique in a karst ecosystem

This study aimed to determine the spatial distribution of total soil organic carbon (TSOC) content in surface soils in the karst ecosystem located in the Mediterranean region of Turkey. Land use types and depression areas were determined using Landsat8 and Shuttle Radar Topography Mission (SRTM) data, respectively. Topsoil samples (0-10 cm) were collected in 108 sites and analysed for soil pH, SOC, bulk density (BD), total nitrogen content (N) and particle size distribution. The exponential model was the best model to describe SOC contents, stable model for BD and circular model for TSOC. The SOC content in different land uses ranked as forest (4.10%) > rangeland (2.60%) > cropland (1.41%) areas. Mean TSOC content was identified as 27.22 MgCha−1 in non-depressed areas and 48.71 MgCha−1 in depressed areas. TSOC dramatically changed from none-depressed areas to depressed areas were identified in cropland (ΔTSOCcropland = 68.05%). Forest areas were more stable in view of the change of carbon sequestration compared to the other areas (ΔTSOCforest3 = 28.24%). Depression areas play very important role in terms of carbon storage capacity in the Karst ecosystem.

VERTICAL ACCURACY ASSESSMENT OF THE PROCESSED SRTM DATA FOR THE BRAZILIAN TERRITORY

Abstract: This research aims to determine the vertical accuracy of the Interferometric Digital Elevation Model (DEM) obtained from the processed Shuttle Radar Topographic Mission (SRTM) data. The research compared the SRTM-GL1 (Shuttle Radar Topographic Mission-Global 1) with 30-meter resolution and the following 90-meter resolution models: (a) EMBRAPA; (b) Hydrological data and maps based on Shuttle Elevation Derivatives at multiple Scales (HydroSHEDS) (HydroSHEDS), provided by the United States Geological Survey (USGS); (c) Consultative Group for International Agricultural Research-Consortium for Spatial Information (CGIAR-CSI); and (d) Jonathan de Ferranti. The accuracy analysis considered the diverse Brazilian regions, adopting 1,087 field points from the Global Navigation Satellite System (GNSS) trackers or topography methods. The Jonathan de Ferranti model achieved the best accuracy with RMSE of 9.61m among the 90-meter resolution models. Most SRTM models at 1:100,000 scale reached Grade A of the Cartographic Accuracy Standard. However, the accuracy at the 1: 50,000 scale did not achieve the same performance. SRTM errors are linearly related to slope and the most significant errors always occur in forest areas. The 30-meter resolution SRTM showed an accuracy of around 10% better (RMSE of 8.52m) than the model of Jonathan de Ferranti with 90-meter resolution (RMSE of 9.61m).

OpenSpace: A System for Astrographics

Human knowledge about the cosmos is rapidly increasing as instruments and simulations are generating new data supporting the formation of theory and understanding of the vastness and complexity of the universe. OpenSpace is a software system that takes on the mission of providing an integrated view of all these sources of data and supports interactive exploration of the known universe from the millimeter scale showing instruments on spacecrafts to billions of light years when visualizing the early universe. The ambition is to support research in astronomy and space exploration, science communication at museums and in planetariums as well as bringing exploratory astrographics to the class room. There is a multitude of challenges that need to be met in reaching this goal such as the data variety, multiple spatio-temporal scales, collaboration capabilities, etc. Furthermore, the system has to be flexible and modular to enable rapid prototyping and inclusion of new research results or space mission data and thereby shorten the time from discovery to dissemination. To support the different use cases the system has to be hardware agnostic and support a range of platforms and interaction paradigms. In this paper we describe how OpenSpace meets these challenges in an open source effort that is paving the path for the next generation of interactive astrographics.

Rainfall monitoring network design using conditioned Latin hypercube sampling and satellite precipitation estimates: An application in the ungauged Ecuadorian Amazon

Rain gauge networks are crucial for enhancing the spatio‐temporal characterization of precipitation. In tropical regions, scarcity of rain gauge data, climatic variability, and variable spatial accessibility make conventional approaches to design rain gauge networks inadequate and impractical. In this study, we propose the use of conditioned Latin hypercube sampling (cLHS) method with multi‐temporal layers of remotely sensed precipitation measurements for capturing the spatio‐temporal precipitation patterns in ungauged areas. The study was conducted in the Amazon region of Ecuador, for which monthly precipitation averages were derived based on a 16‐year period of Tropical Rainfall Measuring Mission (TRMM 3B43 V7) data which were used as prior information to select representative sampling points through cLHS. Two scenarios for the sampling design were considered and evaluated, one without and one with restrictions on accessible sites according to the proximity to roads and settlements. Results showed that both optimized networks captured the variability of precipitation according to the TRMM climatology. Furthermore, evaluation against an independent satellite precipitation data set showed that the optimized networks support mapping precipitation based on ordinary kriging (OK). Comparison with regular and random sampling methods showed that particularly when a practical scenario is considered, the optimized network provided more reliable results over time, highlighting the suitability of the network to capture temporal changes and map precipitation with high accuracy. The proposed approach could be easily adopted in other ungauged and poorly accessible regions for rain gauge network design as well as to the design of multi‐objective monitoring networks.

Partitioning of Terrain Features Based on Roughness

Surface roughness is a key parameter that reflects topographic characteristics and influences surface processes, and characterization of surface roughness is a fundamental problem in geoscience. In recent years, although there have been basic studies on roughness, few studies have compared the concept and quantification of roughness, and there have been few studies that have evaluated the ability of partition terrain features. Based on 1″ resolution Shuttle Radar Topography Mission (SRTM) data and previous studies, we selected the Qinba Mountain region of China and its adjacent areas as our study area, and used 13 different roughness algorithms to extract roughness in this study. Using spatial patterns and statistical distributions, the results were analyzed, and the best algorithm suited to partitioning terrain features was selected. We then evaluated the ability of the algorithm to distinguish the terrain morphology. The results showed the following: (1) The 13 algorithms were able to be classified into four types, that is, gradient (SLOPE), relief (root mean squared height, RMSH), local vector (directional cosine eigenvalue, DCE) and power-spectral (two-dimensional continuous wavelet transform, 2D CWT). (2) The SLOPE and RMSH algorithms were better able to express and distinguish terrain, as they were able to macroscopically distinguish between four types of terrain in the study areas. Based on power-spectral methods, 2D CWT had the same discrimination ability as the first two methods following a normalization transform, whereas the DCE method had a general effect and could only distinguish two types of terrain. (3) Different roughness algorithms had their own applicability for different terrain areas and application directions.

Queueing analysis of DTN protocols in deep-space communications

Delay/disruption tolerant networking (DTN) [1] is proposed as an internetworking architecture for reliable data delivery despite a long propagation delay and/or lengthy link disruptions. DTN targets challenging networking environments where traditional networking protocols such as the terrestrial Transmission Control Protocol/Internet Protocol (TCP/IP) typically do not work effectively. The challenging problem of mission control and data delivery in space communications is a typical application scenario of the DTN technology. Reliable and highly efficient data delivery of DTN relies heavily on the bundle protocol (BP) [2]. BP is intended to establish an overlay network that is able to withstand intermittent data link connectivity in the delivery of DTN data units, termed bundles. BP adopts a store-and-forward mechanism and a custody transfer option for transmission reliability.

Mapping of shadows cast on a protoplanetary disk by a close binary system

For a comprehensive understanding of planetary formation and evolution, we need to investigate the environment in which planets form: circumstellar disks. Here we present high-contrast imaging observations of V4046 Sagittarii, a 20-Myr-old close binary known to host a circumbinary disk. We have discovered the presence of rotating shadows in the disk, caused by mutual occultations of the central binary. Shadow-like features are often observed in disks\cite{garufi,marino15}, but those found thus far have not been due to eclipsing phenomena. We have used the phase difference due to light travel time to measure the flaring of the disk and the geometrical distance of the system. We calculate a distance that is in very good agreement with the value obtained from the Gaia mission's Data Release 2 (DR2), and flaring angles of $\alpha = 6.2 \pm 0.6 $ deg and $\alpha = 8.5 \pm 1.0 $ deg for the inner and outer disk rings, respectively. Our technique opens up a path to explore other binary systems, providing an independent estimate of distance and the flaring angle, a crucial parameter for disk modelling.

Hybrid Wavelet Neural Network Approach for Daily Inflow Forecasting Using Tropical Rainfall Measuring Mission Data

AbstractA novel wavelet-artificial neural network hybrid model (WA-ANN) for short-term daily inflow forecasting is proposed, using for the first time Tropical Rainfall Measuring Mission (TRMM) data...