Leveraging the SPoRT Paradigm and Best Practices for Elevating Severe Weather Responses by the NASA Applied Science Disasters Program
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Testing our understanding of crop yield responses to weather fluctuations at global scale is notoriously hampered by limited information about underlying management conditions, such as cultivar selection or fertilizer application. Here, we demonstrate that accounting for observed spatial variations in growing seasons increases the variance in reported national maize and wheat yield anomalies that can be explained by process-based model simulations from 34 to 58% and 47 to 54% across the 10 most weather-sensitive main producers, respectively. For maize, the increase in explanatory power is similar to the increase achieved by accounting for water stress, as compared to simulations assuming perfect water supply in both rainfed and irrigated agriculture. Representing water availability constraints in irrigation is of second-order importance. We improve the model’s explanatory power by better representing crops’ exposure to observed weather conditions, without modifying the weather response itself. This growing season adjustment now allows for a close reproduction of heat wave and drought impacts on crop yields.
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Changes in ionization production in the lower stratosphere by a few percent during Forbush decreases have been shown to correlate well with changes in winter tropospheric dynamics by a similar relatively small amount. Changes in ionization production by tens of percent on the decadal time scale have been shown to be correlated with changes in winter storm frequencies by tens of percent in the western North Atlantic. Changes in total solar irradiance or solar UV do not have time variations to match the tropospheric variations on the day to day time scales discussed here. Forcing related to magnetic activity is not supported. Thus solar wind/MeV-GeV particle changes appear to be the only viable forcing function for these day to day variations. If solar wind/particle forcing of a few percent amplitude can produce short term weather responses, then observed changes by tens of percent on the decadal and centennial time scale could produce climate changes on these longer time scales. The changes in circulation involved would produce regional climate changes, as observed. At present the relations between stratospheric ionization, electric fields and chemistry and aerosol and cloud microphysics are as poorly known as the relations between the latter and storm feedback processes. However, the capability for investigating these relationships now exists and has recently been most successfully used for elucidating the stratospheric chemistry and cloud microphysics associated with the Antarctic ozone hole. The economic benefits of being able to predict winter severity on an interannual basis, and the extent to which climate change related to solar variability will add to or substract from the greenhouse effect, should be more than adequate to justify support for research in this area.
An intercomparison of analyses of the main PGGE Level IIb data set is presented with three advanced analysis systems. The aims of the work are to estimate the extent and magnitude of the differences between the analyses, to identify the reasons for the differences, and finally to estimate the significance of the differences. Extratropical analyses only are considered. Objective evaluations of analysis quality, such as fit to observations, statistics of analysis differences, and mean fields are discussed. In addition, substantial emphasis is placed on subjective evaluation of a series of case studies that were selected to illustrate the importance of different aspects of the analysis procedures, such as quality control, data selection, resolution, dynamical balance, and the role of the assimilating forecast model. In some cases, the forecast models are used as selective amplifiers of analysis differences to assist in deciding which analysis was more nearly correct in the treatment of particular data.
Neutral-Plasma charge exchange is a fundamental physical process that occurs ubiquitously across the universe. In geospace, charge exchange occurs in the Earth’s topside ionosphere, polar wind, plasmasphere, inner magnetosphere, and magnetosheath. Past and current space missions have profiled plasma and electromagnetic characteristics in various parts of the Earth’s magnetospheric system. However, observations of the exosphere, i.e., neutrals above 500 km altitude, are still sparse and, in some regions, non-existent, which limits our understanding of the neutral contribution to the overall dynamics of the geospace environment. Cold exospheric neutrals (< 10 eV) play an important role in the Sun-Earth interaction. Variability of exospheric density provides key information of the Earth’s atmospheric loss under dynamic space environment conditions. Various neutral species and their density variations in the polar wind can alter ion outflow patterns, modifying global magnetospheric dynamics. Exospheric neutrals also provide an energy sink for the inner magnetosphere by creating Energetic Neutral Atoms (ENAs) through charge exchange with high-energy ring current ions, which subsequently leave our geospace system unimpeded by magnetic fields. Exospheric neutrals also provide a means to observe the global interaction of the solar wind – magnetosphere, through global imaging of the system via ENAs (e.g., the TWINS and IMAGE missions) and soft X-rays (e.g., the upcoming LEXI and SMILE missions), the byproducts of neutral-plasma charge exchange. In the coming decade, we advocate that our community needs to increase our exploration of the neutral populations in the outermost reaches of the Earth’s atmosphere. It is imperative that we improve both in-situ and remote-sensing technologies for measuring key neutral species in our exosphere. We also encourage dedicated exosphere missions and to stimulate model developments of our exosphere and its interaction with the co-located magnetospheric system and neighboring Ionosphere - Thermosphere - Mesosphere system.
The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.
A number of observers claim to have seen thermal anomalies prior to earthquakes, but subsequent analysis by others has failed to produce similar findings. What exactly are these anomalies? Might they be useful for earthquake prediction? It is the purpose of this study to determine if thermal anomalies can be found in association with known earthquakes by systematically co-registering weather satellite images at the sub-pixel level and then determining if statistically significant responses occurred prior to the earthquake event. A new set of automatic co-registration procedures was developed for this task to accommodate all properties particular to weather satellite observations taken at night, and it relies on the general condition that the ground cools after sunset. Using these procedures, we can produce a set of temperature-sensitive satellite images for each of five selected earthquakes (Algeria 2003; Bhuj, India 2001; Izmit, Turkey 2001; Kunlun Shan, Tibet 2001; Turkmenistan 2000) and thus more effectively investigate heating trends close to the epicenters a few hours prior to the earthquake events. This study will lay tracks for further work in earthquake prediction and provoke the question of the exact nature of the thermal anomalies.
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The peak winds near the surface are an important forecast element for space shuttle landings. As defined in the Flight Rules (FR), there are peak wind thresholds that cannot be exceeded in order to ensure the safety of the shuttle during landing operations. The National Weather Service Spaceflight Meteorology Group (SMG) is responsible for weather forecasts for all shuttle landings, and is required to issue surface average and 10-minute peak wind speed forecasts. They indicate peak winds are a challenging parameter to forecast. To alleviate the difficulty in making such wind forecasts, the Applied Meteorology Unit (AMU) developed a PC-based graphical user interface (GUI) for displaying peak wind climatology and probabilities of exceeding peak wind thresholds for the Shuttle Landing Facility (SLF) at Kennedy Space Center (KSC; Lambert 2003). However, the shuttle occasionally may land at Edwards Air Force Base (EAFB) in southern California when weather conditions at KSC in Florida are not acceptable, so SMG forecasters requested a similar tool be developed for EAFB.
The peak winds near the surface are an important forecast element for Space Shuttle landings. As defined in the Shuttle Flight Rules (FRs), there are peak wind thresholds that cannot be exceeded in order to ensure the safety of the shuttle during landing operations. The National Weather Service Spaceflight Meteorology Group (SMG) is responsible for weather forecasts for all shuttle landings. They indicate peak winds are a challenging parameter to forecast. To alleviate the difficulty in making such wind forecasts, the Applied Meteorology Unit (AMTJ) developed a personal computer based graphical user interface (GUI) for displaying peak wind climatology and probabilities of exceeding peak-wind thresholds for the Shuttle Landing Facility (SLF) at Kennedy Space Center. However, the shuttle must land at Edwards Air Force Base (EAFB) in southern California when weather conditions at Kennedy Space Center in Florida are not acceptable, so SMG forecasters requested that a similar tool be developed for EAFB. Marshall Space Flight Center (MSFC) personnel archived and performed quality control of 2-minute average and 10-minute peak wind speeds at each tower adjacent to the main runway at EAFB from 1997- 2004. They calculated wind climatologies and probabilities of average peak wind occurrence based on the average speed. The climatologies were calculated for each tower and month, and were stratified by hour, direction, and direction/hour. For the probabilities of peak wind occurrence, MSFC calculated empirical and modeled probabilities of meeting or exceeding specific 10-minute peak wind speeds using probability density functions. The AMU obtained and reformatted the data into Microsoft Excel PivotTables, which allows users to display different values with point-click-drag techniques. The GUT was then created from the PivotTables using Visual Basic for Applications code. The GUI is run through a macro within Microsoft Excel and allows forecasters to quickly display and interpret peak wind climatology and likelihoods in a fast-paced operational environment. A summary of how the peak wind climatologies and probabilities were created and an overview of the GUT will be presented.
Reviews solar atmospheric tidal forces and modeling challenges and requirements for accurate tidal predictions.
The Integrated Multi-satellitE Retrievals for GPM (IMERG) and the The Global Precipitation Climatology Project (GPCP) are two of the most popular precipitation products. IMERG is a relatively new dataset that targets the needs primarily of the hydrological community by resolving the hydrological cycle of precipitation at fine temporal (30-minutes) and spatial (10-km) scales. IMERG only recently exceeded the user base of the highly successful, but discontinued in 2019, TRMM Multi-satellite Precipitation Analysis (TMPA). GPCP, on the other hand, has traditionally been strong in the climate research community, and recently has been revised under the framework of NASA's Making Earth System Data records for Use in Research Environments (MEaSUREs) program. Both IMERG and GPCP are similar in the underlying approaches to achieve global coverage, in particular using satellite microwave and infrared observations, and adjusting the precipitation retrieval with rain gauge information. While there is a tendency to use both datasets interchangeably, differences remain and some of them limit the usage of IMERG as a climate data record at this point. By applying Principal Component Analysis, we identify the differences and similarities mode-by-mode, and further the guidance on suggested usage of IMERG as a climate data record. As an example in the attached figure, IMERG vs GPSP differences in the explained variance by the two leading seasonal modes can be identified, mainly in the extreme southern latitudes, and over western boundary currents (Gulfstream and Kuroshio). At the preparation time for this presentation, the new version "07"of IMERG was in the works that may resolve the issues presented here. Nevertheless, our analysis can help to gauge the uncertainties of the studies already done using the currently existing IMERG version "06", and evaluate the improvements in the upcoming version "07".
In response to severe weather conditions, traffic management coordinators specify reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options would assist the traffic management coordinators in making more efficient rerouting decisions. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. Essentially, using previous information to inform future decisions. This paper describes the initial steps and methodology used towards this goal. A method to extract relevant features from the large volume of weather data to quantify the convective weather scenario during a particular time range is presented. Similar routes are clustered. A description of the algorithm to identify which cluster of reroute advisories were actually followed by pilots is described. Models built for fifteen of the top twenty most frequently used reroute clusters correctly predict the use of the cluster for over 60 of the test examples. Results are preliminary but indicate that the methodology is worth pursuing with modifications based on insight gained from this analysis.
In response to severe weather conditions, traffic management coordinators (TMCs) reroute air traffic around regions of airspace affected by the severe weather. Presently, acceptable reroutes are specified by issuing reroute advisories. Advisories, based on reroutes published in the National Severe Weather Playbook, consist of several routes describing routing options. These reroutes are selected by TMCs based on their understanding of weather conditions and their previous experience dealing with similar weather conditions. Providing recommendations and analysis of available reroute options could assist the TMCs in making rerouting decisions. While reroute advisories have historically been based on Playbook plays, plays are frequently modified or combined to generate an advisory. Thus, it is natural to present rerouting suggestions to TMCs as modified Playbook plays. The challenge here is to compare advisory subroutes and play subroutes in a meaningful way in order to map advisories back to the Playbook plays upon which they may have been based. In this work, several subroute comparison metrics are presented and discussed. One of these metrics is then used to match advisories to Playbook plays. With the development and implementation of NextGen technologies, there is currently a trend of moving away from the pre-defined Playbook plays (and related advisories) in favor of a more precise specification of trajectories using GPS based navigation tools, such as area navigation (RNAV). Moving towards ubiquitous use of RNAV routes, the objective of rerouting flights will be met with more precisely specified and accurately flown RNAV routes. In the final version of this paper, significant RNAV routes will be identified by finding RNAV routes that are flown frequently. This will require a trajectory comparison technique to compare actually flown flight tracks to specified RNAV routes. The metrics developed here will be used or modified for this task.
The primary responsibilities of the National Weather Service (NWS) are to: provide warnings of severe weather and flooding for the protection of life and property; provide public forecasts for land and adjacent ocean areas for planning and operation; and provide weather support for: production of food and fiber; management of water resources; production, distribution and use of energy; and efficient and safe air operations.
The weathering of planetary surfaces is treated. Both physical and chemical weathering (reactions between minerals or mineraloids and planetary volatiles through oxidation, hydration, carbonation, or solution processes) are discussed. Venus, earth, and Mars all possess permanent atmospheres such that weathering should be expected to significantly affect their respective surfaces. In contrast, Mercury and the moon lack permanent atmospheres but conceivably could experience surface weathering in response to transient atmospheres generated by volcanic or impact cratering events. Weathering processes can be postulated for other rocky objects including Io, Titan, asteroids, and comets.
This study compared pilot situation awareness across three traffic management concepts. The Concepts varied in terms of the allocation of traffic avoidance responsibility between the pilot on the flight deck, the air traffic controllers, and a conflict resolution automation system. In Concept 1, the flight deck was equipped with conflict resolution tools that enable them to fully handle the responsibility of weather avoidance and maintaining separation between ownship and surrounding traffic. In Concept 2, pilots were not responsible for traffic separation, but were provided tools for weather and traffic avoidance. In Concept 3, flight deck tools allowed pilots to deviate for weather, but conflict detection tools were disabled. In this concept pilots were dependent on ground based automation for conflict detection and resolution. Situation awareness of the pilots was measured using online probes. Results showed that individual situation awareness was highest in Concept 1, where the pilots were most engaged, and lowest in Concept 3, where automation was heavily used. These findings suggest that for conflict resolution tasks, situation awareness is improved when pilots remain in the decision-making loop.