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All sourcesNASA NTRSDOE OSTI
NASA NTRS1962

SATELLITES AND WEATHER FORECASTING

Just 2 years ago the first Tiros weather satellite gave meteorologists powerful new eyes with which to view their atmospheric domain. Since that time developments have been rapid. Techniques have been developed for using the satellite observations in day-to-day weather analysis and forecasting. Communications have been improved to increase the availability of the satellite observations throughout the world. Research using the Tiros data is increasing our understanding of the atmosphere and will lead to improved weather observing satellite

Meteorological satellite↗
NASA NTRS1994

REE chemistry and Sm-Nd systematics of late Archean weathering profiles in the Fortescue Group, Western Australia

Two weathering profiles, each consisting of an upper, sericite-rich zone and a lower, chlorite-rich zone, are preserved between flows of the Mt. Roe Basalt in the Fortescue Group, Hamersley Basin, Western Australia. REE concentrations in samples from these two profiles, which originally developed ca 2,760 Ma, show large variations depending on stratigraphic position. LREE abundances and (La/Yb)N are greatest at depths of 3-6 m below the paleosurface of the Mt. Roe #1 profile and are somewhat lower in samples above this level. The LREEs reach concentrations 6-9 times greater than in the underlying basalt, and thus appear to have been mobilized downward in the paleosol and concentrated in its middle part. LREE concentrations in the #2 profile show a similar distribution but with a sharp increase in all REE concentrations within 50 cm of the paleosurface. The distinction between the REE profiles in the two paleosols may be related to the difference in the overlying material. The #1 paleosol is overlain by a few meters of sediments and then by basalt, whereas the #2 paleosol is directly overlain by basalt. The LREEs appear to have been mobilized both during chemical weathering of the parental basalt and during later lower-greenschist-facies metamorphism and metasomatism of the paleosols. Remobilization of the REEs during the regional metamorphism of the Fortescue Group is confirmed by a whole-rock Sm-Nd reference isochron of Mt. Roe #1 samples with an age of 2,151 +/- 360 Ma. Variable initial 143Nd/144Nd values of unweathered basalt samples which may represent the paleosol protolith prevents a confident determination of the magnitude of LREE mobility. Both the initial mobilization of the REEs during weathering and the metasomatic remobilization appear to have taken place under redox conditions where Ce was present dominantly as Ce3+, because Ce anomalies are not developed within the sericite zone samples regardless of concentration. Europium anomalies in the paleoweathering profile are somewhat variable and were probably modified by mobilization of Eu2+ at metamorphic conditions. In all samples, the HREEs appear to have been relatively immobile and correlate with Al, Ti, Cr, V, Zr, and Nb. Sm-Nd systematics and REE patterns of four unweathered basalt samples indicate derivation of the Mt. Roe Basalts from a heterogeneous and enriched source having epsilon Nd between -4.0 and -7.4. Initial 143Nd/144Nd values of these basalts are even lower than those reported by NELSON et al. (1992) for Fortescue Group basalts and indicate a substantial crustal component in the generation of Mt. Roe Basalts.

NASA Discipline Exobiology↗
NASA NTRS2012

Understanding Space Weather: The Sun as a Variable Star

The Sun is a complex system of systems and until recently, less than half of its surface was observable at any given time and then only from afar. New observational techniques and modeling capabilities are giving us a fresh perspective of the solar interior and how our Sun works as a variable star. This revolution in solar observations and modeling provides us with the exciting prospect of being able to use a vastly increased stream of solar data taken simultaneously from several different vantage points to produce more reliable and prompt space weather forecasts. Solar variations that cause identifiable space weather effects do not happen only on solar-cycle timescales from decades to centuries; there are also many shorter-term events that have their own unique space weather effects and a different set of challenges to understand and predict, such as flares, coronal mass ejections, and solar wind variations.

Sun: Corona↗
NASA NTRS2012

A Comparison of Perturbed Initial Conditions and Multiphysics Ensembles in a Severe Weather Episode in Spain

Ensembles of numerical model forecasts are of interest to operational early warning forecasters as the spread of the ensemble provides an indication of the uncertainty of the alerts, and the mean value is deemed to outperform the forecasts of the individual models. This paper explores two ensembles on a severe weather episode in Spain, aiming to ascertain the relative usefulness of each one. One ensemble uses sensible choices of physical parameterizations (precipitation microphysics, land surface physics, and cumulus physics) while the other follows a perturbed initial conditions approach. The results show that, depending on the parameterizations, large differences can be expected in terms of storm location, spatial structure of the precipitation field, and rain intensity. It is also found that the spread of the perturbed initial conditions ensemble is smaller than the dispersion due to physical parameterizations. This confirms that in severe weather situations operational forecasts should address moist physics deficiencies to realize the full benefits of the ensemble approach, in addition to optimizing initial conditions. The results also provide insights into differences in simulations arising from ensembles of weather models using several combinations of different physical parameterizations.

severe weather↗
NASA NTRS2015

Predicting Space Weather Effects on Close Approach Events

The NASA Robotic Conjunction Assessment Risk Analysis (CARA) team sends ephemeris data to the Joint Space Operations Center (JSpOC) for conjunction assessment screening against the JSpOC high accuracy catalog and then assesses risk posed to protected assets from predicted close approaches. Since most spacecraft supported by the CARA team are located in LEO orbits, atmospheric drag is the primary source of state estimate uncertainty. Drag magnitude and uncertainty is directly governed by atmospheric density and thus space weather. At present the actual effect of space weather on atmospheric density cannot be accurately predicted because most atmospheric density models are empirical in nature, which do not perform well in prediction. The Jacchia-Bowman-HASDM 2009 (JBH09) atmospheric density model used at the JSpOC employs a solar storm active compensation feature that predicts storm sizes and arrival times and thus the resulting neutral density alterations. With this feature, estimation errors can occur in either direction (i.e., over- or under-estimation of density and thus drag). Although the exact effect of a solar storm on atmospheric drag cannot be determined, one can explore the effects of JBH09 model error on conjuncting objects' trajectories to determine if a conjunction is likely to become riskier, less risky, or pass unaffected. The CARA team has constructed a Space Weather Trade-Space tool that systematically alters the drag situation for the conjuncting objects and recalculates the probability of collision for each case to determine the range of possible effects on the collision risk. In addition to a review of the theory and the particulars of the tool, the different types of observed output will be explained, along with statistics of their frequency.

Space Weather↗
NASA NTRS2016

A Mathematical Model and Algorithm for Routing Air Traffic Under Weather Uncertainty

A central challenge in managing today's commercial en route air traffic is the task of routing the aircraft in the presence of adverse weather. Such weather can make regions of the airspace unusable, so all affected flights must be re-routed. Today this task is carried out by conference and negotiation between human air traffic controllers (ATC) responsible for the involved sectors of the airspace. One can argue that, in so doing, ATC try to solve an optimization problem without giving it a precise quantitative formulation. Such a formulation gives the mathematical machinery for constructing and verifying algorithms that are aimed at solving the problem. This paper contributes one such formulation and a corresponding algorithm. The algorithm addresses weather uncertainty and has closed form, which allows transparent analysis of correctness, realism, and computational costs.

uncertainty↗
NASA NTRS2015

Forecasting Space Weather Events for a Neighboring World

Shortly after NASA's Mars Atmosphere and Volatile EvolutioN mission (MAVEN) spacecraft entered Mars' orbit on 21 September 2014, scientists glimpsed the Martian atmosphere's response to a front of solar energetic particles (SEPs) and an associated coronal mass ejection (CME). In response to some solar flares and CMEs, streams of SEPs burst from the solar atmosphere and are further accelerated in the interplanetary medium between the Sun and the planets. These particles deposit their energy and momentum into anything in their path, including the Martian atmosphere and MAVEN particle detectors. MAVEN scientists had been alerted to the likely CME-Mars encounter by a space weather prediction system that had its origins in space weather forecasting for Earth but now forecasts space weather for Earth's neighboring planets. The two Solar Terrestrial Relations Observatory spacecraft and Solar Heliospheric Observatory observed a CME on 26 September, with a trajectory that suggested a Mars intercept. A computer model developed for solar wind prediction, the Wang-Sheeley-Arge-Enlil cone model [e.g., Zheng et al., 2013; Parsons et al., 2011], running in real time at the Community Coordinated Modeling Center (CCMC) located at NASA Goddard since 2006, showed the CME propagating in the direction of Mars (Figure 1). According to MAVEN particle detectors, the disturbance and accompanying SEP enhancement at the leading edge of the CME reached Mars at approximately 17 hours Universal Time on 29 September 2014. Such SEPs may have a profound effect on atmospheric escape - they are believed to be a possible means for driving atmospheric loss. SEPs can cause loss of Mars' upper atmosphere through several loss mechanisms including sputtering of the atmosphere. Sputtering occurs when atoms are ejected from the atmosphere due to impacts with energetic particles.

space weather↗
NASA NTRS2017

Extratropical Weather Systems on Mars: Radiatively-Active Water Ice Effects

Extratropical, large-scale weather disturbances, namely transient, synoptic-period,baroclinic barotropic eddies - or - low- (high-) pressure cyclones (anticyclones), are components fundamental to global circulation patterns for rapidly rotating, differentially heated, shallow atmospheres such as Earth and Mars. Such "wave-like" disturbances that arise via (geophysical) fluid shear instability develop, mature and decay, and travel west-to-east in the middle and high latitudes within terrestrial-like planetary atmospheres. These disturbances serve as critical agents in the transport of heat and momentum between low and high latitudes of the planet. Moreover, they transport trace species within the atmosphere (e.g., water vapor/ice, other aerosols (dust), chemical species, etc). Between early autumn through early spring, middle and high latitudes on Mars exhibit strong equator-to-pole mean temperature contrasts (i.e., "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that such strong baroclinicity supports vigorous, large-scale eastward traveling weather systems [Banfield et al., 2004; Barnes et al., 1993]. A good example of traveling weather systems, frontal wave activity and sequestered dust activity from MGS/MOC image analyses is provided in Figure 1 (cf. Wang et al. [2005]). Utilizing an upgraded and evolving version of the NASA Ames Research Center (ARC) Mars global climate model, investigated here are key dynamical and physical aspects of simulated northern hemisphere (NH) large-scale extratropica lweather systems,with and without radiatively-active water ice clouds. Mars Climate Model:

cyclones↗
NASA NTRS2017

UTM Weather Presentation

Presentation highlighting how weather affected UAS operations during the UTM field tests. Research to develop UAS weather translation models with a description of current and future work for UTM weather.

UTM↗
NASA NTRS2015

Integration of Dynamic Weather Routes Automation with Air/Ground Data Communications

The Dynamic Weather Routes (DWR) toolcontinuously and automatically analyzes airborne flights in en route airspace to identify flights where a route correction could save significant flight time and still avoid weather. A partnership between NASA, American Airlines (AA), and the FAA has enabled testing of DWR in real-world air traffic operations. En route Data Communications (Data Comm) could significantly reduce the controller and pilot workload needed to communicate DWR route changes under today’s voice-based operations and thereby enable more timely and frequent high-value corrections to weather avoidance routes. Sample data from the DWR trial at AA illustrate how Data Comm could improve DWR operations. Two operating concepts that integrate DWR with Data Comm are described:(1) route corrections are initiated by air traffic control and implemented using Airborne Reroutes and Data Comm, and (2) route corrections are initiated by the dispatcher and pilot and implemented via Data Comm. Both concepts align with Federal Aviation Administration (FAA) plans for implementation ofData Comm in en route airspace.

weather avoidance↗
NASA NTRS2021

Evaluation of Clouds, Radiation, and Precipitation in CMIP6 Models Using Global Weather States Derived from ISCCP-H Cloud Property Data

A clustering methodology is applied to cloud optical depth cloud top pressure (TAU-PC) histograms from the new, 1-degree resolution, ISCCP-H dataset, to derive an updated global Weather State (WS) dataset. Then, PC-TAU histograms from current-climate CMIP6 model simulations are assigned to the ISCCP-H WSs along with their concurrent radiation and precipitation properties, to evaluate model cloud, radiation, and precipitation properties in the context of the Weather States. The new ISCCP-H analysis produces WSs that are very similar to those previously found in the lower resolution ISCCP-D dataset. The main difference lies in the splitting of the ISCCP-D thin stratocumulus WS between the ISCCP-H shallow cumulus and stratocumulus WSs, which results in the reduction by one of the total WS number. The evaluation of the CMIP6 models against the ISCCP-H Weather States, shows that, in the ensemble mean, the models are producing an adequate representation of the frequency and geographical distribution of the WSs, with measurable improvements compared to the WSs derived for the CMIP5 ensemble. However, the frequency of shallow cumulus clouds continues to be underestimated, and, in some WSs the good agreement of the ensemble mean with observations comes from averaging models that significantly overpredict and underpredict the ISCCP-H WS frequency. In addition, significant biases exist in the internal cloud properties of the model WSs, such as the model underestimation of cloud fraction in middle-top clouds and secondarily in midlatitude storm and stratocumulus clouds, that result in an underestimation of cloud SW cooling in those regimes.

Clouds↗
NASA NTRS2022

CMEs and SEPs During November–December 2020: A Challenge for Real-Time Space Weather Forecasting

Predictions of coronal mass ejections (CMEs) and solar energetic particles (SEPs) are a central issue in space weather forecasting. In recent years, interest in space weather predictions has expanded to include impacts at other planets beyond Earth as well as spacecraft scattered throughout the heliosphere. In this sense, the scope of space weather science now encompasses the whole heliospheric system, and multipoint measurements of solar transients can provide useful insights and validations for prediction models. In this work, we aim to analyze the whole inner heliospheric context between two eruptive flares that took place in late 2020, that is, the M4.4 flare of 29 November and the C7.4 flare of 7 December. This period is especially interesting because the STEREO-A spacecraft was located ∼60° east of the Sun–Earth line, giving us the opportunity to test the capabilities of “predictions at 360°” using remote-sensing observations from the Lagrange L1 and L5 points as input. We simulate the CMEs that were ejected during our period of interest and the SEPs accelerated by their shocks using the WSA–Enlil–SEPMOD modeling chain and four sets of input parameters, forming a “mini-ensemble.” We validate our results using in situ observations at six locations, including Earth and Mars. We find that, despite some limitations arising from the models' architecture and assumptions, CMEs and shock-accelerated SEPs can be reasonably studied and forecast in real time at least out to several tens of degrees away from the eruption site using the prediction tools employed here.

Coronal mass ejections↗
NASA NTRSDate not supplied

Extracting Lessons of Human Performance and Resilience Management from a Study of Weather-Related Safety Risks and Incidents Reported to NASA's Aviation Safety Reporting System (ASRS)

We present a study of weather-related incident reports submitted to NASA’s Aviation Safety Reporting System (ASRS) by air carrier pilots and air traffic controllers in the US. Using specific examples, we examine the weather-related risks reported and the relevant aspects of human performance and resilience management exhibited during these incidents. We describe our methods of lesson extraction to maximize learning, including the use of advance algorithms, and we conclude with a review of the weather-related risks encountered and the resilient practices employed to mitigate them.

resilience↗
DOE OSTI2020

Solar Photovoltaics in Severe Weather: Cost Considerations for Storm Hardening PV Systems for Resilience

Solar photovoltaic (PV) power has many advantages as a resilient power source, including the ability to provide power after a natural disaster. While solar arrays often survive severe weather events, systems are occasionally compromised and left unable to provide power. For PV systems to act as resilient power providers, they must remain operational. Building a system that is more likely to survive a storm comes at a cost, though. Previous efforts have identified various system measures and practices that can increase the likelihood of a PV system surviving a severe weather event. But what is the cost premium for a storm hardened PV system? This report provides initial estimates for the up-front cost premiums for various methods of storm hardening PV systems.

14 SOLAR ENERGY↗
DOE OSTI2022

The RAM-SCB model and its applications to advance space weather forecasting

Energetic particle fluxes that are part of the Earth’s ring current and radiation belts can intensify significantly during space weather events like geomagnetic storms and could cause severe damage to satellite-based technologies. Understanding the physical processes that control their dynamics and improving our capability for their prediction is thus extremely important. In the context of space weather applications and user needs, this paper provides a brief description of our kinetic ring current-atmosphere interactions model with self-consistent magnetic field (RAM-SCB) and its further extension to implement a self-consistent electric (E) field. Specific examples that demonstrate RAM-SCB capabilities and limitations to reproduce the near-Earth space weather environment are given. In this paper, the current status of RAM-SCB is assessed and plans for its further improvement are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

3D Seismic Anatomy of a Watershed Reveals Climate–Topography Coupling That Drives Water Flowpaths and Bedrock Weathering

To investigate how bedrock transforms to soil, we mapped the topography of the interface demarcating onset of weathering under an east-west trending shale watershed in the Valley and Ridge province in the U.S.A. Using wave-equation travel-time tomography from a seismic array of >4000 geophones, we obtained a 3D P-wave velocity (Vp) model that resolves structures ~20 m below land surface (mbls). The depth of mobile soil and the onset of dissolution of chlorite roughly match Vp = 600 m/s and Vp = 2700 m/s, respectively. Chlorite dissolution initiates porosity growth in the shale matrix. Depth to the 2700 m/s contour is greater under the N- as compared to S-facing hillslopes and under sub-planar as compared to concave-up land surfaces. Broadly, the geometries of the ‘soil’ and ‘chlorite’ Vp contours are consistent with the calculated potential for shear fracture opening under weak regional compression. However, this calculated fracture potential does not consistently explain observations related to N- vs. S-facing aspect nor fracture density observed by borehole televiewer. Apparently, regional compression is only a secondary influence on Vp: the primary driver of P-wave slowing in the upper layers of this catchment is topographic control of reactive water flowpaths and their integrated effects on weathering. Here, the Vp result is best explained as the long-term integrated effect of groundwater flow-induced geochemical weathering of shale in response to climate-driven patterns of micro- and macro-topography.

54 ENVIRONMENTAL SCIENCES↗