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NASA NTRS2013

Comet C2012 S1 (ISON): Observations of the Dust Grains From SOFIA and of the Atomic Gas From NSO Dunn and Mcmath-Pierce Solar Telescopes

Comet C/2012 S1 (ISON) is unique in that it is a dynamically new comet derived from the Oort cloud reservoir of comets with a sun-grazing orbit. Infrared (IR) and visible wavelength observing campaigns were planned on NASA's Stratospheric Observatory For Infrared Astronomy (SOFIA) and on National Solar Observatory Dunn (DST) and McMath-Pierce Solar Telescopes, respectively. We highlight our SOFIA (+FORCAST) mid- to far-IR images and spectroscopy (approx. 5-35 microns) of the dust in the coma of ISON are to be obtained by the ISON-SOFIA Team during a flight window 2013 Oct 21-23 UT (r_h approx. = 1.18 AU). Dust characteristics, identified through the 10 micron silicate emission feature and its strength, as well as spectral features from cometary crystalline silicates (Forsterite) at 11.05-11.2 microns, and near 16, 19, 23.5, 27.5, and 33 microns are compared with other Oort cloud comets that span the range of small and/or highly porous grains (e.g., C/1995 O1 (Hale-Bopp) and C/2001 Q4 (NEAT) to large and/or compact grains (e.g., C/2007 N4 (Lulin) and C/2006 P1 (McNaught)). Measurement of the crystalline peaks in contrast to the broad 10 and 20 micron amorphous silicate features yields the cometary silicate crystalline mass fraction, which is a benchmark for radial transport in our protoplanetary disk. The central wavelength positions, relative intensities, and feature asymmetries for the crystalline peaks may constrain the shapes of the crystals. Only SOFIA can look for cometary organics in the 5-8 micron region. Spatially resolved measurements of atoms and simple molecules from when comet ISON is near the Sun (r_h< 0.4 AU, near Nov-20-Dec-03 UT) were proposed for by the ISON-DST Team. Comet ISON is the first comet since comet Ikeya-Seki (1965f) suitable for studying the alkalai metals Na and K and the atoms specifically attributed to dust grains including Mg, Si, Fe, as well as Ca. DST's Horizontal Grating Spectrometer (HGS) measures 4 settings: Na I, K, C2 to sample cometary organics (along with Mg I), and [OI] as a proxy for activity from water (along with Si I and Fe I). State-of-the-art instruments that will also be employed include IBIS, which is a Fabry-Perot spectral imaging system that concurrently measures lines of Na, K, Ca II, or Fe, and ROSA (CSUN/QUB), which is a rapid imager that simultaneously monitors Ca II or CN. From McMath-Pierce, the Solar-Stellar Spectrograph also will target ISON (320-900 nm, R approx. 21,000, r_h<0.3 AU). Assuming survival, the intent is to target ISON over r_h<0.4 AU, characteristic of prior Na detections.

Oort cloud comets↗

NASA NTRS2015

Comparisons of Characteristics of Magnetic Clouds and Cloud-Like Structures During 1995-2012

Using eighteen years (1995 - 2012) of solar wind plasma and magnetic field data (observed by the Wind spacecraft), solar activity (e.g. sunspot number: SSN), and the geomagnetic activity index (Dst), we have identified 168 magnetic clouds (MCs) and 197 magnetic cloud - like structures (MCLs), and we have made relevant comparisons. The following features are found during seven different periods (TP: Total period during 1995 - 2012, P1 and P2: first and second half period during 1995 - 2003 and 2004 - 2012, Q1 and Q2: quiet periods during 1995 - 1997 and 2007 - 2009, A1 and A2: active periods during 1998 - 2006 and 2010 - 2012). (1) During the total period the yearly occurrence frequency is 9.3 for MCs and 10.9 for MCLs. (2) In the quiet periods Q1 > Q1 and Q2 > Q2, but in the active periods A1 < A1 and A2 < A2. (3) The minimum Bz (Bzmin) inside of a MC is well correlated with the intensity of geomagnetic activity, Dstmin (minimum Dst found within a storm event) for MCs (with a Pearson correlation coefficient, c.c. = 0.75, and the fitting function is Dstmin = 0.90+7.78Bzmin), but Bzmin for MCLs is not well correlated with the Dst index (c.c. = 0.56, and the fitting function is Dstmin = -9.40+ 4.58 Bzmin). (4) MCs play a major role in producing geomagnetic storms: the absolute value of the average Dstmin ( MC = -70 nT) for MCs associated geomagnetic storms is two times stronger than that for MCLs ( MCL = -35 nT), due to the difference in the IMF (interplanetary magnetic field) strength. (5) The SSN is not correlated with MCs ( TP, c.c. = 0.27), but is well associated with MCLs ( TP, c.c. = 0.85). Note that the c.c. for SSN vs. P2 is higher than that for SSN vs. P2. (6) Averages of IMF, solar wind speed, and density inside of the MCs are higher than those inside of the MCLs. (7) The average of MC duration (approx. = 18.82 hours) is approx. = 20 % longer than the average of MCL duration (approx. = 15.69 hours). (8) There are more MCs than MCLs in the quiet solar period, and more MCLs than MCs in the active solar period, probably due to the interaction between a MC and another significant interplanetary disturbance (including another MC) which could obviously change the character of a MC, but we speculate that some MCLs are no doubt due to other factors such as complex birth conditions at the Sun.

CME↗

NASA NTRS2018

Evaluation of Usability and Workload with Paper Strips as Compared to Virtual Flight Strips Used for Ramp Operations

This paper describes an experiment designed to compare the use of paper strips with the use of a new user interface, the Ramp Traffic Console (RTC), designed for use by ramp controllers to be used in place of paper strips. A Human-In-the-Loop (HITL) experiment was performed as the fifth study in a series of six HITL simulation experiments designed to evaluate a concept that provided advisories to the users. The RTC was designed to be used as a Decision Support Tool (DST) that provided advisories to ramp controllers regarding metering or pushback such that most of the delay was taken at the gate to save fuel and emissions. In addition to being a DST, an added benefit of the RTC is that it can provide real-time updates of flight data, airport and airspace status to the controller including Traffic Management Initiatives (TMI). The RTC was designed as new user interface that displays virtual strips on a terminal map drawn on a 27-inch touch screen monitor. The RTC was used in some conditions of the experiment by ramp controllers in place of paper strips and paper maps in the HITL environment. In other conditions the controllers were given paper strips and paper maps similar to what they currently use at Charlotte Douglas International Airport (CLT). The study described here, evaluated the use of the virtual strips displayed on the RTC as compared to the use of paper strips and paper map, using current ramp tower controllers at CLT as participants. The research question being asked was - How does management of ramp traffic affect user workload and usability ratings while using RTC to manage traffic in the ramp verses using paper strips? Workload for our purposes is defined by four components of the NASA-TLX (Task Load Index). Usability was assessed with two sets of usability questions - One set of usability questions addressed traffic management performance and the other set addressed issues of resources and efficiency. Both Post Run and Post Study questionnaire responses were gathered and the results were analyzed to assess controller workload and usability ratings under both conditions, virtual strips shown on RTC and Paper Strips. The results indicate that controllers perceived lower workload while using virtual strips displayed on RTC to manage ramp traffic. Usability ratings for Traffic management performance questions are lower in the virtual strip/RTC condition than in the paper strip condition showing a preference for RTC over Paper. Usability ratings for Resources and efficiency questions show mixed results. Additionally, the Post Study Questions show preference for RTC over paper strips. Results of this data analysis will be presented in this paper. This DST evaluation was an important step in researching and improving the tool, which was planned to be deployed in the field.

Aviation Decision Support Tools↗

NASA NTRSDate not supplied

An At-Home Evaluation of a Light Intervention to Mitigate Sleep Inertia Symptoms

Introduction: Sleep inertia symptoms typically occur after waking from nocturnal sleep. Under laboratory settings, light exposure upon waking has been shown to improve alertness, mood, and vigilant attention. We investigated whether a field-deployable light-emitting device would help to improve alertness and working memory in a real-world setting. Methods: Thirty-five participants (18 female; 26.4 ± 6.0 y) completed an at-home, within-subject, randomized crossover study. Participants wore actiwatches during their normal sleep-wake schedule for five nights ahead of the adaptation and experimental nights. On the experimental night, participants performed baseline testing before their self-selected bedtime. Forty-five minutes after bedtime, participants received a phone call and were instructed to perform test bouts while wearing light-emitting glasses with the light either on (light condition) or off (control). A 3-minute descending subtraction task (DST) and the Karolinska Sleepiness Scale (KSS) were performed at +7, +17, +27, and +37 minutes after the call. Participants were then instructed to go back to sleep and were called 45 minutes after lights out to repeat the test bouts in the opposite condition. A series of mixed-effects models were performed with fixed effects of condition, test bout, and their interaction, and a random effect of participant. Condition order, sex, and baseline were included as covariates. Results: There was a significant effect of test bout for DST total responses (χ2 [3] = 17.42; p < .001) and total correct (χ2 [3] = 21.29; p < .001) with improved performance at +27 and +37 minutes compared to +7 minutes. Sex was a significant predictor for KSS (F1,30 = 10.26; p = .003), with females (8.20 ± 0.23) rating higher sleepiness than males (7.10 ± 0.25). There were no other significant effects for DST or KSS outcomes (p > .05). Conclusion: These results suggest that the intervention was not able to improve working memory or alertness under naturalistic at-home settings. Further analysis is needed to determine whether these results are applicable to other cognitive performance domains.

light↗

NASA NTRSDate not supplied

Light as a Reactive Countermeasure to Sleep Inertia: Translating Laboratory Findings to the Field

Sleep inertia describes the brief period of impaired alertness, mood, and cognitive performance experienced after waking. Under laboratory settings, light exposure upon waking during a habitual sleep period has been shown to improve sleep inertia symptoms. We investigated whether a field-deployable light-emitting device would help to mitigate sleep inertia in a real-world setting. Thirty-six participants (18 female; 26.6 years ± 6.1) completed an at-home, within-subject, randomized crossover study. Participants followed their habitual sleep-wake schedule for five nights before an adaptation and experimental night. Forty-five minutes after bedtime on the experimental night, participants received a phone call and were instructed to wear light-emitting glasses with the light either on (light condition) or off (control). A 5-minute psychomotor vigilance task (PVT), the Karolinska Sleepiness Scale (KSS), visual analog scales of mood (VASmood), and a 3-minute descending subtraction task (DST) were performed starting at +2, +12, +22, and +32 minutes after the call. Participants then went back to sleep and were called 45 minutes after lights out for the opposite condition. A series of mixed-effects models were performed with fixed effects of test bout, condition, test bout × condition, and a random effect of participant. Covariates included pre-sleep baseline scores, randomization order, sex, and sleep history. Participants rated themselves as more alert and energetic in the light condition compared to the control condition (VASalert-sleepy p = .01; VASlethargic-energetic p = .001). There was no effect of condition for DST outcomes, but there was a significant improvement in DST total responses in the light condition in a subset of participants waking from N3 (p = .03). There was a significant effect of condition for PVT outcomes, with faster responses (p < .001) and fewer lapses (p < .001) in the control condition. Our results under naturalistic at-home settings suggest that, similar to the in-laboratory study findings, the light intervention improved subjective alertness and mood, while working memory improved after waking from N3. Future studies of light interventions should include measures of visual acuity and comfort to assess the full feasibility and efficacy of interventions in real-world environments.

sleep inertia↗

NASA NTRSDate not supplied

Light as a Reactive Countermeasure to Sleep Inertia: Translating Laboratory Findings to the Field

Sleep inertia describes the brief period of impaired alertness, mood, and cognitive performance experienced after waking. Under laboratory settings, light exposure upon waking during a habitual sleep period has been shown to improve sleep inertia symptoms. We investigated whether a field-deployable light-emitting device would help to mitigate sleep inertia in a real-world setting.\ Thirty-six participants (18 female; 26.6 years ± 6.1) completed an at-home, within-subject, randomized crossover study. Participants followed their habitual sleep-wake schedule for five nights before an adaptation and experimental night. Forty-five minutes after bedtime on the experimental night, participants received a phone call and were instructed to wear light-emitting glasses with the light either on (light condition) or off (control). A 5-minute psychomotor vigilance task (PVT), the Karolinska Sleepiness Scale (KSS), visual analog scales of mood (VASmood), and a 3-minute descending subtraction task (DST) were performed starting at +2, +12, +22, and +32 minutes after the call. Participants then went back to sleep and were called 45 minutes after lights out for the opposite condition. A series of mixed-effects models were performed with fixed effects of test bout, condition, test bout × condition, and a random effect of participant. Covariates included pre-sleep baseline scores, randomization order, sex, and sleep history. Participants rated themselves as more alert and energetic in the light condition compared to the control condition (VASalert-sleepy p = .01; VASlethargic-energetic p = .001). There was no effect of condition for DST outcomes, but there was a significant improvement in DST total responses in the light condition in a subset of participants waking from N3 (p = .03). There was a significant effect of condition for PVT outcomes, with faster responses (p < .001) and fewer lapses (p < .001) in the control condition. Our results under naturalistic at-home settings suggest that, similar to the in-laboratory study findings, the light intervention improved subjective alertness and mood, while working memory improved after waking from N3. Future studies of light interventions should include measures of visual acuity and comfort to assess the full feasibility and efficacy of interventions in real-world environments.

sleep inertia↗

NASA NTRS2023

An Updated Geomagnetic Index-Based Model for Determining the Latitudinal Extent of Energetic Electron Precipitation

Energetic Electron Precipitation (EEP) from the Earth's plasma sheet and the radiation belts is an important feature of atmospheric dynamics through their destruction of ozone in the lower thermosphere and mesosphere. Therefore, understanding the magnitude of the atmospheric impact of the Sun-Earth interaction requires a comprehensive understanding of the intensity and location of EEP. This study improves the accuracy of a previous pressure-corrected Dst model that predicts the equatorward extent of >43, >114, and >292 keV EEP using the measurements from the Medium Energy Proton Electron Detector detector of six National Oceanic and Atmospheric Administration/Polar Orbiting Environmental Satellites and EUMETSAT/METOP satellites. The improvement is achieved through multiple linear regression of pressure-corrected Dst and pressure-corrected Ring Current (RC) indices. The RC index mitigates the baseline variation of the Dst index that created an inherent solar cycle bias in the previous model. The new model is then extended to the Southern Hemisphere (SH) after removing the South Atlantic Anomaly longitudes from the data. More than 80% of the residuals lie within ±1.8° Corrected Geomagnetic Latitude (CGMLat) in the Northern Hemisphere and within ±1.98° CGMLat in the SH.

E. M. Babu↗

NASA NTRSDate not supplied

Light as a Reactive Countermeasure to Sleep Inertia: Translating Laboratory Findings to the Field

sleep inertia↗

NASA NTRSDate not supplied

Multiclass Flight Anomaly Detection Using Sensor Fusion Based on Dempster-Shafer Theory

As aviation systems in commercial operations continue to grow in complexity, the anomalies exhibited by these systems become more elaborate and difficult to detect. To address the challenge of detecting these complex anomalies, deep learning models have been used extensively in aviation anomaly detection studies, at the expense of end-user interpretability. Aiming to maintain the same level of interpretability as traditional threshold-exceedance methods, we continue our development of prediction models using ordinal patterns and their distributions throughout the flight. Specifically, this study extends our work into multiclass anomaly detection using sensor fusion based on Dempster-Shafer theory (DST), a second-order probability theory used to combine information from different sources of evidence. Our approach uses DST to reduce the uncertainty in the class predictions of an ensemble of classifiers. These classifiers rely on the similarity between flight data and class templates to make a prediction of the state of the aircraft. Our approach aims to take advantage of simple models trained on interpretable features (ordinal patterns) to correctly predict an anomaly and identify the flight dynamics linked to the anomaly. Our results show an improvement when using DST-based sensor fusion over simple majority voting. Additionally, our results provide insight into aircraft states linked to rare high-risk anomalies.

Risk detection↗

NASA NTRSDate not supplied

Multiclass Flight Anomaly Detection Using Sensor Fusion Based on Dempster-Shafer Theory

As aviation systems in commercial operations continue to grow in complexity, the anomalies exhibited by these systems become more elaborate and difficult to detect. To address the challenge of detecting these complex anomalies, deep learning models have been used extensively in aviation anomaly detection studies, at the expense of end-user interpretability. Aiming to maintain the same level of interpretability as traditional threshold-exceedance methods, we continue our development of prediction models using ordinal patterns and their distributions throughout the flight. Specifically, this study extends our work into multiclass anomaly detection using sensor fusion based on Dempster-Shafer theory (DST), a second-order probability theory used to combine information from different sources of evidence. Our approach uses DST toreduce the uncertainty in the class predictions of an ensemble of classifiers. These classifiers rely on the similarity between flight data and class templates to make a prediction of the state of the aircraft. Our approach aims to take advantage of simple models trained on interpretable features (ordinal patterns) to correctly predict an anomaly and identify the flight dynamics linked to the anomaly. Our results show an improvement when using DST-based sensor fusion over simple majority voting. Additionally, our results provide insight into aircraft states linked to rare high-risk anomalies.

Risk detection↗

DOE OSTI2026

Update on Integrity Monitoring, Prediction and Assessment, Corrosion Control, and Repair of the Hanford Storage Tanks

DOE has launched a multi-year research program with the focus of preserving and increasing available volume for waste storage at Hanford. The long-term availability and operability of the Hanford Double Shell Tanks (DST) is critical to the completion of the Hanford mission. Maintaining the integrity of the tank will involve having a technology for repair or refurbishment of a DST should the tank function be compromised by degradation, monitoring the tank for indications of accelerated degradation, developing a means for mitigating accelerated degradation, and evaluating options for increasing the storage capacity in the tank farm without constructing new tanks. The project work was started in the middle of 2024; significant progress has been made in the following four areas: (i) tank refurbishment using a high performance grout and an epoxy sealant layer system, (ii) developing a chemically and radiologically stable reference electrode, (iii) designing and implementing a cathodic protection system to mitigate underside corrosion of DST secondary shells, and (iv) exploring evaporation to increase waste storage capacity.

Shukla, Pavan [Savannah River National Laboratory ↗

DOE OSTI2026

Drive Cycles, Battery Pack Scaling, and Usage Considerations for Long-Haul and Regional-Haul Electric Trucks

Electrifying Class-8 heavy-duty trucks presents a promising opportunity to enhance energy efficiency and reduce freight transport costs. Battery electric trucks (BETs), once considered niche, are gaining traction due to advancements in battery technology and cost reductions. However, accurately predicting battery lifespan under realistic usage conditions remains a key challenge. Understanding battery failure mechanisms and their links to design, operation, and management is essential for developers and fleet operators. This study introduces a method to develop simplified, lab-testable dynamic stress test (DST) cycles for regional and long-haul Class-8 BETs, derived from real-world diesel truck usage. These DSTs enable benchmarking of battery technologies, identification of aging stressors, and optimization of battery design, life, and cost. The approach supports evaluation of key metrics such as levelized cost of driving and total cost of ownership, aiding fair comparisons and adoption decisions. We also propose feasible battery pack sizes that meet current driving demands with strategic charging, and a method to scale pack-level DSTs to cell-level cycles for lab-based testing. These tools facilitate tradeoff analysis across battery chemistries, pack sizing, and charging strategies, while offering means to get insights into battery aging under realistic conditions-ultimately supporting informed BET deployment decisions.

25 ENERGY STORAGE↗

DOE OSTI2026

Formulation and Performance Evaluation of Epoxy Sealant Systems for Double-Shell Tank Bottom Refurbishment

The performance of epoxy sealants used in the refurbishment of double-shell tank (DST) systems requires balancing processability, thermomechanical stability, and adhesion to cementitious substrates. This study incorporates Heloxy 8 as a reactive diluent into Westlake 862 epoxy to tailor workability and cured-state properties. Rheological time-sweep analysis demonstrates that increasing the diluent content significantly reduces complex viscosity and extends workability, thereby improving pumpability and flow for large-area applications. However, the targeted 2-hour processing window is not fully achieved. Differential scanning calorimetry (DSC) confirms that all formulations cure at room temperature to glass transition temperatures ( T g ) at least 20 °C above the maximum DST operating temperature (27 °C), thereby ensuring service in the glassy regime. Dynamic mechanical analysis (DMA) reveals formulation-dependent reductions in tan delta and increases in storage modulus, indicating increasingly elastic and mechanically stable networks with diluent incorporation. Pull-off adhesion testing shows that modified formulations (70–90% Westlake epoxy) exhibit significantly higher adhesion strengths than the unmodified system. Grout cohesive failure indicates that interfacial bonding exceeds substrate strength. Collectively, these results demonstrate that controlled reactive diluent incorporation enables optimization of processing behavior, interfacial adhesion, and thermomechanical performance, supporting the suitability of the modified epoxy systems as durable sealant layers for cementitious barrier applications in hazardous waste containment infrastructure.

Differential scanning calorimetry↗

DOE OSTI2025

Heterogeneous Dynamics in Shear Thickening Colloids Revealed by Intrinsic Heterodyne Correlation Spectroscopy

Shear induced frictional networks have been proposed to be responsible for the emergence of discontinuous shear thickening (DST) in complex fluids. However, little experimental evidence exists to support this model directly. Here, in this study, using x-ray photon correlation spectroscopy (XPCS), we show the existence of an intrinsic heterodyne feature during shear cessation, which originates from the relative motion of mobile particles against an aggregated or jammed network induced by shear thickening. Upon removing the shear, the shear stress dissipates rather quickly in a two-step fashion, whereas the heterogeneous particle dynamics persist much longer with the relative velocity decaying slowly with time as 𝑡 −1 . More importantly, both continuous shear thickening (CST) and DST show similar heterodyne features, indicating the intrinsic mechanisms causing shear thickening are similar in nature

Complex fluid↗

DOE OSTI2025

NLR HPC Eagle Jobs Data and Additional Energy Metrics

Overview: Anonymized job-level records from the Eagle high-performance computing (HPC) system at the National Laboratory of the Rockies (NLR). Each record represents a Slurm batch job with scheduling metadata, resource requests, resource utilization, CPU/GPU energy consumption, and efficiency metrics. Sensitive fields (user, account, job name) are replaced with cryptographic hashes. System & Timeframe: Eagle was a 2,000-node, 8-petaflop system operated at NLR from 2019–2024. Data covers the full operational lifetime of the system. Slurm data was processed nightly; timestamps are in Mountain Time. Funding provided by the U.S. Department of Energy, EERE. Files: esif.hpc.eagle.job-anon.zip — Core anonymized job records (Hive-partitioned Parquet) esif.hpc.eagle.job-anon-energy-metrics.zip — Same records with additional iLO and Ganglia energy metrics datacard.md — Full dataset documentation ~13.8 million rows, 62 variables. Readable with PyArrow, pandas, DuckDB, Apache Spark, or any Parquet-compatible tool. Data Collection: Jobs collected via sacct through a pipeline: Eagle Jobs API → Redpanda → StreamSets → HPCMON API → PostgreSQL. Node-level power from iLO (HP Integrated Lights-Out); GPU power from Ganglia monitoring, joined to jobs via node lists and time ranges. Preprocessing: Anonymization of name, user, and account fields via cryptographic hashing Derived columns: queue_wait, cpu_eff, max_mem_eff Simplified job state mapping (e.g., "CANCELLED BY 12345" → "CANCELLED") QoS accounting rules (buy-in, standby, or Slurm QoS value) CPU energy estimated from TDP (200W, Intel Xeon Gold 6154, 18 cores) Timezone-aware columns (_tz) sourced from LEX accounting database to correctly handle DST transitions Key Variables: Scheduling: job_id, partition, state_simple, submit_time_tz, start_time_tz, end_time_tz, queue_waitResources: nodes_req/used, processors_req/used, memory_req, wallclock_req/used, gpus_requested Efficiency: cpu_eff, max_mem_eff Energy: cpu_energy_tdp_estimated_max/used_watt_hours, node_energy_total_watt_hours (iLO), gpu0/1_energy_total_watt_hours (Ganglia) Partitions: bigmem, bigmem-8600, bigscratch, csc, dav, ddn, debug, gpu, haswell, long, mono, short, standard Job States: CANCELLED, COMPLETED, FAILED, NODE_FAIL, OUT_OF_MEMORY, PENDING, RUNNING, TIMEOUT QoS Levels: Unknown, normal, buy-in, debug, penalty, high, standby Important Notes: Non-_tz timestamp columns may be off by one hour across DST boundaries; use _tz columns for time difference calculations Energy fields are null for jobs without monitoring coverage Job step records and raw Slurm JSONB fields are excluded from this extract Do not attempt to re-identify individuals from hashed fields

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1978

The GISS sounding temperature impact test

The impact of DST 5 and DST 6 satellite sounding data on mid-range forecasting was studied. The GISS temperature sounding technique, the GISS time-continuous four-dimensional assimilation procedure based on optimal statistical analysis, the GISS forecast model, and the verification techniques developed, including impact on local precipitation forecasts are described. It is found that the impact of sounding data was substantial and beneficial for the winter test period, Jan. 29 - Feb. 21. 1976. Forecasts started from initial state obtained with the aid of satellite data showed a mean improvement of about 4 points in the 48 and 772 hours Sub 1 scores as verified over North America and Europe. This corresponds to an 8 to 12 hour forecast improvement in the forecast range at 48 hours. An automated local precipitation forecast model applied to 128 cities in the United States showed on an average 15% improvement when satellite data was used for numerical forecasts. The improvement was 75% in the midwest.

Halem, M.↗

NASA NTRS1979

The data systems tests - The final phase

The U.S.A. has conducted a series of data systems tests (DSTs) as a precursor to its participation in FGGE, the Global Weather Experiment. The paper briefly describes the impact those tests have had on the FGGE observing system and on the data management plans. In particular, the final phase of the DST programs is described, wherein a number of investigators have been selected to work with the DST data sets in research studies directed toward the GARP objectives. Thus, an important first step has been taken in providing feedback to the potential FGGE research community.

Greaves, J. R.↗

NASA NTRS1980

Initial geomagnetic field model from Magsat vector data

Magsat data from the magnetically quiet days of November 5-6, 1979, were used to derive a thirteenth degree and order spherical harmonic geomagnetic field model, MGST(6/80). The model utilized both scalar and high-accuracy vector data and fit that data with root-mean-square deviations of 8.2, 6.9, 7.6 and 7.4 nT for the scalar magnitude, B(r), B(theta), and B(phi), respectively. The model includes the three first-order coefficients of the external field. Comparison with averaged Dst indicates that zero Dst corresponds with 25 nT of horizontal field from external sources. When compared with earlier models, the earth's dipole moment continues to decrease at a rate of about 26 nT/yr. Evaluation of earlier models with Magsat data shows that the scalar field at the Magsat epoch is best predicted by the POGO(2/72) model but that the WC80, AWC/75 and IGS/75 are better for predicting vector fields.

Langel, R. A.↗