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Extreme Air Pollution Events in Hokkaido, Japan Traced Back to Early Snowmelt and Large-Scale Wildfires Over East Eurasia: Case Studies

To identify the unusual climate conditions and their connections to air pollutions in a remote area due to wildfires, we examine three anomalous large-scale wildfires in May 2003, April 2008, and July 2014 over East Eurasia, as well as how products of those wildfires reached an urban city, Sapporo, in the northern part of Japan (Hokkaido), significantly affecting the air quality. NASA's MERRA-2 (the Modern-Era Retrospective analysis for Research and Applications, Version 2) aerosol re-analysis data closely reproduced the PM2.5 variations in Sapporo for the case of smoke arrival inJuly 2014. Results show that all three cases featured unusually early snowmelt in East Eurasia, accompanied by warmer and drier surface conditions in the months leading to the fires, inducing long-lasting soil dryness and producing environmental conditions conductive to active wildfires. Due to prevailing anomalous synoptic-scale atmospheric motions, smoke from those fires eventually reached a remote area, Hokkaido, and worsened the air quality in Sapporo. In futurestudies, continuous monitoring of the timing of Eurasian snowmelt and the air quality from the source regions to remote regions, coupled with the analysis of atmospheric and surface conditions, may be essential in more accurately predicting the effects of wildfires on air quality.

MERRA-2↗

Importance of Trade Dependencies for Agricultural Inputs: A Case Study of Finland

Approximately 80% of the world's population lives in countries that are dependent on food imports to sustain an adequate food supply. Besides these food imports, further dependencies also arise due to the requirements for agricultural inputs, including energy, fertilisers, feed and agricultural machinery. While the trade of agricultural inputs is relatively well represented in economic analysis, the quantification is often in terms of monetary values, and thus the assessments of the actual input quantities are very limited. In this paper, we develop a framework for analysis of the traded input quantities at the country-level and demonstrate its utility through an in-depth analysis of Finland's dependency on agricultural inputs. Further, we assess the importance of these inputs for domestic food production from a resilience perspective. We find that Finland, a country with relatively high food self-sufficiency but also a great dependency on imported agricultural inputs, experienced an increase in its dependency over the period 1996-2016. In case of trading partners, the story is more mixed: while trading partners for soybeans increased, those decreased in case of electricity while no significant change was observed in other commodities. In Finland, the rapeseed dependency on imports (ratio of net imports and consumption) grew from around 0% to almost 50% between the years 1987-2013. Changes for electricity remained substantially smaller, with dependency only slightly growing during the study period. Crude oil and soybean supplies are totally dependent on imports as neither is produced in Finland. Interestingly, the highest dependencies for agricultural inputs were on different countries than that for foodstuff imports. Thus, when identifying and assessing approaches to increase resilience to trade-related shocks, it is essential to understand both foodstuff and agricultural input dependencies within the global food system.

trade dependencies↗

A Blockchain Case Study for Urban Air Mobility Operational Intent

To realize the potential of Urban Air Mobility (UAM), an assurance of cybersecurity is critical for public acceptance. UAM is a concept that proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical takeoff and landing (VTOL) aircraft to overcome increasing surface congestion. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. The intent of this work is to leverage a permissioned blockchain to simulate secure data exchange and storage for the UAM operational intent use case.

UAM↗

A Blockchain Case Study for Urban Air Mobility Operational Intent

To realize the potential of Urban Air Mobility (UAM), an assurance of cybersecurity is critical for public acceptance. UAM is a concept that proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical takeoff and landing (VTOL) aircraft to overcome increasing surface congestion. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. The intent of this work is to leverage a permissioned blockchain to simulate secure data exchange and storage for the UAM operational intent use case.

UAM↗

Sensitivities in Satellite Lidar‐Derived Estimates of Daytime Top‐of‐the‐Atmosphere Optically Thin Cirrus Cloud Radiative Forcing: A Case Study

An optically thin cirrus cloud was profiled concurrently with nadir‐pointing 1,064 nm lidars on 11 August 2017 over eastern Texas, including NASA's airborne Cloud Physics Lidar (CPL) and space‐borne Clouds and Aerosol Transport System (CATS) instruments. Despite resolving fewer (37% vs. 94%) and denser (i.e., more emissive) clouds (average cloud optical depth of 0.10 vs. 0.03, respectively), CATS data render a near‐equal estimate of the top‐of‐atmosphere (TOA) net cloud radiative forcing (CRF) versus CPL. The sample‐relative TOA net CRF solved from CPL is 1.39 W/m2, which becomes 1.32 W/m2 after normalizing by occurrence frequency. Since CATS overestimates extinction for this case, the sample‐relative TOA net forcing is ~3.0 W/m2 larger than CPL, with the absolute value reduced to within 0.3 W/m2 of CPL due its underestimation of cloud occurrence. We discuss the ramifications of thin cirrus cloud detectability from satellite and its impact on attempts at TOA CRF closure.

Erica K. Dolinar↗

Changes in the Magnetic Field Topology and the Dayside/Nightside Reconnection Rates in Response to a Solar Wind Dynamic Pressure Front A Case Study

One of the most significant observations associated with a sharp enhancement in solar wind dynamic pressure, SWP, is the poleward expansion of the auroral oval and the closing of the polar cap. The polar cap shrinking over a wide range of magnetic local times (MLTs), in connection with an observed increase in ionospheric convection and the transpolar potential, led to the conclusion that the nightside reconnection rate is significantly enhanced after a pressure front impact. However, this enhanced tail reconnection has never been directly measured. We demonstrate the effect of a solar wind dynamic pressure front on the polar cap closure, and for the first time, measure the enhanced reconnection rate in the magnetotail, for a case occurring during southward background Interplanetary Magnetic Field (IMF) conditions. We use Polar Ultra-Violet Imager (UVI) measurements to detect the location of the open-closed field line boundary, and combine them with Assimilative Mapping of Ionospheric Electrodynamics (AMIE) potentials to calculate the ionospheric electric field along the polar cap boundary, and thus evaluate the variation of the dayside/nightside reconnection rates. We find a strong response of the polar cap boundary at all available MLTs, exhibiting a significant reduction of the open flux content. We also observe an immediate response of the dayside reconnection rate, plus a phased response, delayed by 15–20min, of the nightside reconnection rate. Finally, we provide comparison of the observations with the results of the Open Geospace General Circulation Model (OpenGGCM), elucidating significant agreements and disagreements

A Boudouridis↗

Assimilation of GPM Retrieved Surface Meteorology Variables with ICE-POP Case Studies

Built upon Tropical Rainfall Measuring Mission (TRMM) legacy for next-generation global observation of rain and snow. The GPM has a broad global coverage ~70°S – 70°N with a swath of 245/125-km for the Ka (35.5 GHz)/Ku (13.6 GHz) band radar, and 850-km for the 13-channel GMI. GPM also features better retrievals for heavy, moderate, and light rain and snowfall.

GPM retrieval product↗

Correlated Topics in a Scalable Multidimensional Text Cube: Algorithms and Aviation Safety Case Study

As world-wide air traffic continues to grow even at a modest pace, the overall complexity of the system will increase significantly. This increased complexity can lead to a larger number of fatalities per year even if the extremely low fatality rate that we currently enjoy is maintained. One important source of information about the safety of the aviation system is in Aviation Safety Text Reports which are written by members of the flight crew, air traffic controllers, and other parties involved with the aviation system. These anonymized narrative reports contain fixed-field contextual information about the flight but also contain free-form narratives that describe, in the author s own words, the nature of the safety incident and, in many cases, the contributing factors that led to the safety incident. Several thousand such reports are filed each month, each of which is read and analyzed by highly trained experts. However, it is possible that there are emerging safety issues due to the fact that they may be reported very infrequently and in different contexts with different descriptions. The goal of this research paper is to develop correlated topic models which uncover correlations in the subspaces defined by the intersection of numerous fixed fields and discovered correlated topics. This task requires the discovery of latent topics in the text reports and the creation of a topic cube. Furthermore, because the number of potential cells in the topic cube is very large, we discuss novel methods of pruning the search space in the topic cells, thereby making the analysis feasible. We demonstrate the new algorithms on an analysis of pilot fatigue and its contributing factors, as well as the safety incidents that are correlated with this phenomenon.

Zhao, Bo↗

Issues in knowledge representation to support maintainability: A case study in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and runtime estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks. Because the scientific data processing modules (called fittings) evolve to match scientists' needs, issues regarding maintainability are of prime importance in PIPE. This paper describes the PIPE system and describes how issues in maintainability affected the knowledge representation used in PIPE to capture knowledge about the behavior of fittings.

Chien, Steve↗

The 27-28 October 1986 FIRE cirrus case study: Meteorology and clouds

Detailed descriptions of the rawinsonde resolved meteorological conditions (3 hourly soundings) associated with a succession of five distinct mesoscale cirrus cloud regimes, that were intensively observed over a 36 hour period, are given. The synoptic scale systems in which these features were embedded are described and a brief overview of the experiment is given. Regional analyses of the static stability structure and vertical motion are presented and interpreted with respect to the characteristics of the corresponding cloud fields as deduced from satellite and lidar observations. The cloud fields exhibited a high degree of persistent mesoscale organization on scales of 20 to 500 km reflecting corresponding scales of dynamic and thermodynamic structure/variability as on the synoptic scale. Cloud generation was usually confined to layers less than 1 km deep (typically 0.5 km in depth) and cellular organization was evident in most cases irrespective of the thermal stratification. Multilayered development was prevalent (2 to 3 layers) and was associated with vertical structure of the temperature and moisture fields resulting primarily from vertical gradients in horizontal advection.

Starr, David↗

The Geometric Factor of Electrostatic Plasma Analyzers: A Case Study from the Fast Plasma Investigation for the Magnetospheric Multiscale mission

We report our findings comparing the geometric factor (GF) as determined from simulations and laboratory measurements of the new Dual Electron Spectrometer (DES) being developed at NASA Goddard Space Flight Center as part of the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission. Particle simulations are increasingly playing an essential role in the design and calibration of electrostatic analyzers, facilitating the identification and mitigation of the many sources of systematic error present in laboratory calibration. While equations for laboratory measurement of the Geometric Factpr (GF) have been described in the literature, these are not directly applicable to simulation since the two are carried out under substantially different assumptions and conditions, making direct comparison very challenging. Starting from first principles, we derive generalized expressions for the determination of the GF in simulation and laboratory, and discuss how we have estimated errors in both cases. Finally, we apply these equations to the new DES instrument and show that the results agree within errors. Thus we show that the techniques presented here will produce consistent results between laboratory and simulation, and present the first description of the performance of the new DES instrument in the literature.

Magnetospheric Multiscale Mission↗

Design-Filter Selection for H2 Control of Microgravity Isolation Systems: A Single-Degree-of-Freedom Case Study

Many microgravity space-science experiments require active vibration isolation, to attain suitably low levels of background acceleration for useful experimental results. The design of state-space controllers by optimal control methods requires judicious choices of frequency-weighting design filters. Kinematic coupling among states greatly clouds designer intuition in the choices of these filters, and the masking effects of the state observations cloud the process further. Recent research into the practical application of H2 synthesis methods to such problems, indicates that certain steps can lead to state frequency-weighting design-filter choices with substantially improved promise of usefulness, even in the face of these difficulties. In choosing these filters on the states, one considers their relationships to corresponding design filters on appropriate pseudo-sensitivity- and pseudo-complementary-sensitivity functions. This paper investigates the application of these considerations to a single-degree-of-freedom microgravity vibration-isolation test case. Significant observations that were noted during the design process are presented. along with explanations based on the existent theory for such problems.

Hampton, R. David↗

What Multilevel Parallel Programs do when you are not Watching: A Performance Analysis Case Study Comparing MPI/OpenMP, MLP, and Nested OpenMP

With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors, parallel programming techniques have evolved that support parallelism beyond a single level. When comparing the performance of applications based on different programming paradigms, it is important to differentiate between the influence of the programming model itself and other factors, such as implementation specific behavior of the operating system (OS) or architectural issues. Rewriting-a large scientific application in order to employ a new programming paradigms is usually a time consuming and error prone task. Before embarking on such an endeavor it is important to determine that there is really a gain that would not be possible with the current implementation. A detailed performance analysis is crucial to clarify these issues. The multilevel programming paradigms considered in this study are hybrid MPI/OpenMP, MLP, and nested OpenMP. The hybrid MPI/OpenMP approach is based on using MPI [7] for the coarse grained parallelization and OpenMP [9] for fine grained loop level parallelism. The MPI programming paradigm assumes a private address space for each process. Data is transferred by explicitly exchanging messages via calls to the MPI library. This model was originally designed for distributed memory architectures but is also suitable for shared memory systems. The second paradigm under consideration is MLP which was developed by Taft. The approach is similar to MPi/OpenMP, using a mix of coarse grain process level parallelization and loop level OpenMP parallelization. As it is the case with MPI, a private address space is assumed for each process. The MLP approach was developed for ccNUMA architectures and explicitly takes advantage of the availability of shared memory. A shared memory arena which is accessible by all processes is required. Communication is done by reading from and writing to the shared memory.

Jost, Gabriele↗

Dragonfly: A Case Study in Dynamic Stability Characterization

Next decade, the Dragonfly probe will enter Titan’s atmosphere on a mission to explore and characterize its unique and complex organic chemistry. In contrast to Mars entry missions, where the challenge is to slow down in its tenuous atmosphere before impacting the surface, Titan’s thick atmosphere provides generous drag. However, Titan has its own unique EDL challenges. Among these challenges is the long time (on the order of 90 minutes!) the vehicle will need to descend unguided through flow regimes where blunt-body entry probes are known to be dynamically unstable. This elongated timeline, both prior to drogue parachute deployment, and during the ensuing descent, has the potential to allow adverse dynamic instability properties to produce large amplitude oscillations in angle-of-attack. This, in-turn may lead to non-compliance in vehicle attitude requirements for EDL events such as parachute deployment, and lander release, or in the most extreme case, tumbling of the aeroshell and near-assured loss of mission.

EDL↗

Dragonfly: A Case Study in Dynamic Stability Characterization

Next decade, the Dragonfly probe will enter Titan’s atmosphere on a mission to explore and characterize its unique and complex organic chemistry. In contrast to Mars entry missions, where the challenge is to slow down in its tenuous atmosphere before impacting the surface, Titan’s thick atmosphere provides generous drag. However, Titan has its own unique EDL challenges. Among these challenges is the long time (on the order of 90 minutes!) the vehicle will need to descend unguided through flow regimes where blunt-body entry probes are known to be dynamically unstable. This elongated timeline, both prior to drogue parachute deployment, and during the ensuing descent, has the potential to allow adverse dynamic instability properties to produce large amplitude oscillations in angle-of-attack. This, in-turn may lead to non-compliance in vehicle attitude requirements for EDL events such as parachute deployment, and lander release, or in the most extreme case, tumbling of the aeroshell and near-assured loss of mission.

EDL↗

Case Study of Solar Wind and IMF Influence on Ionospheric Outflow

We examine ionospheric outflows in the high attitude magnetospheric polar cap during the POLAR satellite's apogee on 04/19/96 using the TIDE instrument. The pass has a fairly constant flux of H+ which is similar to many other passes, but there is a large amount of O+ present. The elevated levels of O+ may be due both to the geophysical conditions during the apogee pass (Kp=5) and prior to the pass. When the outflows for many high altitude polar cap passes are analyzed the O+ density correlates well with the dynamic pressure. There are several aspects of this pass which are interesting besides the abundance of O+ relative to H+. In this pass both the H+ and O+ outflow velocity correlate with both the solar wind speed and Interplanetary Magnetic Field (IMF) Bx. The geophysical conditions are such that the solar wind speed and IMF Bx are highly correlated with each other. For this case the dynamic pressure of the solar wind is fairly constant and has an average value of about 2.5 nPa which is typical for the solar wind, but the average solar wind speed is about 695 km/s which is greater than 450 km/s which is typical for the solar wind at I AU. The ion outflow measurements themselves are interrelated. The H+ density and parallel speed are anticorrelated which results in the constant flux. The 0+ density does not have as large of a anticorrelation with its parallel speed as H+ does with its parallel speed.

Elliott, H. A.↗

NASA Satellites and Data Fusion: A Case Study with Coral Reefs

As the world is experiencing a significant rise in both AI, Climate, and Space start-up companies, we are in a new wave of limitless innovation. NASA's statutory responsibility is to "provide for the widest practicable and appropriate dissemination of information concerning its activities and the results thereof." (51 U.S.C. § 20112) In particular, through machine learning, the public data drawn from NASA’s space assets can provide insights for addressing climate-related problems here on Earth. And many climate start-up companies can benefit from leveraging this data, either for proof of concepts or their own missions. In the Fall of 2021, several scientists from NASA and Coral Vita led a Practicum with the Georgia Institute of Technology Masters in Data Analytics program. The Practicum saw two teams of students develop and implement machine learning models to infer, from CALIPSO satellite imagery, vitality properties upon satellite pass. This kind of capability can lead to real-time mapping of coral health around the world, giving organization an understanding of where to prioritize reef reconstitution.. In this presentation, we will highlight this use case and discuss other concrete applications in which space data is used to solve problems here on Earth.

Earth Sciences↗

Westerly Wind Events in the Eastern Indian Ocean as a Precursor to El Nino: A Case Study for the 2002-03 El Nino

This paper extends the work of our previous study, which showed the potential of using precipitation in the eastern Indian Ocean to predict when an El Nino would begin. The paper begins by showing the successful prediction of the 2002-03 El Nino. However, precipitation is really used as a substitute for wind (storms are usually accompanied by heavy wind), because a popular hypothesis is that winds (especially % winds out of the West) stir up the ocean surface in the western Pacific sending currents of warm waters to the east Pacific where El Ninos form. This paper shows that it is typical for storms that produce strong winds in the western Pacific to have traveled from the Indian Ocean. We begin in the Indian Ocean looking at strong bursts of wind over several days. The number of windy days seems to increase in the months prior to El Nino. We examined these relationships in detail for November 2001 to April 2002, before the recent El Nino, using NASA's TRMM and QuikSCAT data. We found in one case that a warming of the eastern Indian Ocean occurred about 25 days before heavy rainfall formed. As the stormed moved eastward it was followed (6 days later) by strong winds out of the West. The entire storm system (and warming of the sea) moved eastward through a small strip of water between Indonesia and Australia, before reaching the western Pacific. Thus, this paper increases our understanding of the physical processes leading to the formation of El Nino.

Curtis, Scott↗