Instigators of Future Change in Magnetospheric Research

Michael W. Liemohn,

Amy M. Keesee,

Larry Kepko

, and Mark B. Moldwin

ABSTRACT

This chapter focuses on emerging methods and capabilities ena bling future breakthroughs in magnetospheric

research. That is, it does not focus on magnetospheric research regions and science issues, but on how new trends

in the scientific research is conducted. We specifically cover four topics emerging as techniques/issues that will

likely cause a major upheaval in our approach to magnetosph eric physics. The four topics are: the miniaturization

of spacecraft systems and scientific instrumentation; high-end computing and advanced techniques in code cou-

pling methodologies; storage and handling of large data sets, along with awareness of advanced statistical tech-

niques; and diversity within the magnetospheric physics workforce. We think they are paradigm-shifting

breakthroughs that will revolutionize many research areas within the science, technology, engineering, and math-

ematics umbrella.

47.1. INTRODUCTION

As discussed in all of the previous chapters of this book,

the magnetosphere, not only that around Earth but also

those around every other planet with an intrinsic magnetic

field, are natural laboratories rich in fundamental physi-

cal processes of universal application to many other scien-

tific disciplines. Magnetospheric volumes are vast, yet

some of the relevant physics occurs on a tiny scale. Topics

range from the microscopic proces ses of magnetic recon-

nection and wave–particle interactions to the macroscopic

phenomena like plasma circulation through the system

and pressure balance and magnetic topological distortion

during strong active times.

This final chapter of the book is about the future of

magnetospheric research. That is an extremely broad

topic and one that cannot be covered in just a few pages.

Indeed, earlier chapters in this section cover specific

aspects of this topic, and many recent reviews and com-

mentaries have addressed the open questions in the field.

For instance, there is an entire special section of a journal

on “unsolved problems of magnetospheric physics”

(Denton et al., 2016), covering the topics of the future

of plasmaspheric investigations (Gallagher and Comfort,

2016), current system analysis (Dunlop et al., 2016;

Liemohn et al., 2016), magnetic reconnection (Milan

et al. 2016), and radiation belt physics (Kessel, 2012).

Other works have covered the future of magnetosphere–

ionosphere coupling, noting the nonlinear physics and

feedback inherent in the geospace system (Burch, 2016;

Moore et al., 2016) and the difficulty in knowing even

the spatial connectivity between different parts of geo-

space (Delzanno et al., 2015, 2016). The substorm prob-

lem, of course, is still a point of contention and

ambiguity that requires additional attention (Lui, 2018).

Therefore, this chapter will not focus on magneto-

spheric research regions and science issues but rather on

the emerging methods and capabilities enabling future

breakthroughs in magnetospheric research. Here, we

Department of Climate and Space Sciences and

Engineering, University of Michigan, Ann Arbor, MI, USA

Department of Physics and Space Science Center,

University of New Hampshire, Durham, NH, USA

Space Weather Laboratory, Heliophysics Science Division,

NASA Goddard Space Flight Center, Greenbelt, MD, USA

Space Physics and Aeronomy Collection Volume 2: Magnetospheres in the Solar System, Geophysical Monograph 259, First Edition.

Edited by Romain Maggiolo, Nicolas André, Hiroshi Hasegawa, and Daniel T. Welling.

DOI: 10.1002/9781119815624.ch47

753

specifically cover four topics emerging as techniques that

will probably cause a major upheaval in our approach to

magnetospheric physics. Indeed, we think they are para-

digm-shifting breakthroughs that will revolutionize many

research areas within the science, technology, engineering,

and mathematics (STEM) umbrella.

47.2. TECHNIQUES TO WATCH AND ADOPT

While there are other items that could be in this list, we

will focus on just these four emerging trends in magneto-

spheric physics. The first is the miniaturization of space-

craft systems and scientific instrumentation, allowing

for microsatellites and nanosatellites to become robust

and reliable contributors to the scientific endeavor. The

second is high-end computing and advanced techniques

in code coupling methodologies. This is mostly covered

in an earlier chapter but we wanted to emphasize this

point here. The third is recent developments in data stor-

age and handling, along with awareness of advanced sta-

tistical techniques (i.e., data science and machine

learning). The fourth topic that we will focus on here is

diversity in the workforce, and the burgeoning mindful-

ness that different perspectives in the research community

lead to more creative solutions to problems.

47.2.1. Spacecraft System and Instrumentation

Miniaturization

Both scientific instruments and satellite subsystems

have seen a revolution in the reduction of size, weight,

and power plus cost (SWaP+C) requirements in recent

years. A workshop on Small Satellites for Space Weather

Research and Forecasting was recently held to discuss the

current progress and future opportunities for harnessing

these improvements for research in our field as well as

applications for space weather operations.

The magnetosphere is a large region consisting of inter-

connected pathways of energy and mass transport occur-

ring at multiple concurrent scales. As such, it has long

been recognized that constellatio ns are needed to resolve

spatial and temporal ambiguities, and provide the simul-

taneous, global measurements required to resolve ques-

tions of cross-scale coupling. Yet despite the recognized

need, large constellations have been out of reach, prima-

rily due cost concerns.

There are three key emergent areas that finally enable

these long sought after magnetospheric constellation mis-

sions: (1) instrument miniaturization, for which heliophy-

sics in situ instruments are particularly well suited; (2)

commoditization of spacecraft subsystems components;

and (3) new avenues for access to space. These develop-

ments enable increased usage of small satellites, such as

CubeSats, for small, focused missions accessible to a

broad population in the field, a large mission based on

many small satellites, such as the Magnetospheric Con-

stellation (MagCon) mission concept (Angelopoulos

and Spence, 1999), to make significant progress on unan-

swered questions, and the use of small instruments to be

flown on nondedicated satellites for additional research

and space weather monitoring at greatly reduced costs

when compared to dedicated missions.

As concluded in a National Academies of Sciences

study (National Academies, 2016), CubeSats have

demonstrated their ability to deliver compelling science

on small and economic platforms. Since the publication

of that report, CubeSat technologies, particularly with

respect to instrumentation, have continued to mature,

through such programs as the In-Space Validation of

Earth Science Technologies (INVeST) in Earth Sciences

and the Heliophysics Technology and Instrument Devel-

opment for Science (H-TIDeS) in heliophysics. As noted

by Posner et al. (2014), NASA leadership recognizes the

importance of small spacecraft mission contributions to

our understanding of the Sun–Earth space environment,

most notably for their ability to provide low-cost magne-

tospheric constellations. Note that CubeSat missions are

delivering exceptional science for magnetospheric phys-

ics. For example, the Focus ed Investigations of Relativis-

tic Electron Bursts: Intensity, Range, and Dynamics

(FIREBIRD) CubeSats provided new information about

electron microbursts, including their spatial scale and evi-

dence that discrete whistler mode chorus packets are their

source (Breneman et al., 2017; Crew et al., 2016), and the

Colorado Student Space Weather Experiment (CSSWE)

CubeSat mission, which demonstrated that galactic cos-

mic rays are responsible for inner radiation belt electrons

(Li et al., 2017).

The SmallSat commercial industry is growing in leaps

and bounds. There now exist multiple, low-cost solutions

for spacecraft subsystems, at a fraction of previous costs.

A key enabler for high quality yet cost effective science

missions is to utilize subsystem development efforts and

instrument miniaturization and scale up from CubeSat

platforms to larger small satellites (SmallSats). The relia-

bility of such systems has increased as well, due in part to

government and industry initiatives aimed at reliability,

and the natural progression of the marketplace. Commer-

cial constellations of hundreds to thousands of spacecraft

are now being proposed and built, with per spacecraft

reproduction costs in the range of a few $M (see, e.g., One-

Web Satellites (https://onewebsatellites.com/) or Blue

Canyon Technologies (https://bluecanyontech.com/)).

This is one or two orders of magnitude below the cost

for large spacecraft bus designs, making small satellite

technology affordable for everyone. The reliability of

the mission is increased because the loss of any one space-

craft does not doom the mission. An example of such an

754 MAGNETOSPHERES IN THE SOLAR SYSTEM

approach is the Cyclone Global Navigation Satellite Sys-

tem (CYGNSS) mission that consists of eight identical

spacecraft flying in low-Earth orbit (Ruf et al., 2013),

making breakthrough measurements of ocean winds

(Ruf et al., 2016) and soil moisture content (Kim and

Lakshmi, 2018). Under the hood, the spacecraft bus looks

like a CubeSat, and it was developed for NASA with a

higher acceptance of risk than larger, more traditional

missions.

Designs for several constellation missions have been

studied over the past few decades. In the last Solar and

Space Physics Decadal Survey (NRC, 2013), Magneto-

spheric Constellation (MagCon), and a similar mission,

Magnetospheric Tomography (MagCat), were studied

but deemed too expensive. It is worth quoting directly

from that document (NRC, 2013, pp. 9–42):

“To implement such a constellation (36, 30 kg s/c) requires

development of small satellite systems and instruments

that can be more cheaply manufactured and tested in a

reasonable time frame (2–3 years) with acceptable reliabil-

ity levels.”

It is fair to state that both reliability and spacecraft

manufacturing capability have since increased to the

point that such relatively simple spacecraft can be manu-

factured for such a constellation, with reasonable costs.

Previous approaches to constellation formation relied

on a single, dedicated launch vehicle, and a dispenser ship.

The availability of large launch vehicles with excess

launch capacity, and the potential for smaller launch vehi-

cles (LVs), such as from Electron and Virgin Galactic,

offer an alternative path to constellation formation. It is

no longer necessary to have a dedicated LV; rather, a

smallsat constellation could get to orbit as a rideshare

on an ESPA (Evolved Expendable Launch Vehicle

(EELV) Secondary Payload Adapter) beneath a primary

payload, greatly reducing the cost of the mission to NASA

or other government agency. For a mission such as Mag-

Con, a commercially available propulsive ESPA could

rideshare to geosynchronous transfer orbit, then act as

the dispenser ship to move the spacecraft to the final loca-

tion (Kepko, 2018). For low-Earth orbit (LEO) missions,

the ability to directly launch into LEO is a true game-

changer, as it economically allows multiple spacecraft in

multiple orbit planes, with reduced cost and complexity

compared to a single launch.

Instruments are getting smaller, too, fitting within the

SWaP+C requirements of nanosat form factors. For

instance, miniaturization is possible for particle detectors

(Scime et al., 2016; Clark et al., 2016; Zurbuchen and

Gershman, 2016; Skoug et al., 2016; Desai et al., 2016;

Wieser and Barabash, 2016; Michell et al, 2016), magnetic

and electric field probes (Korth et al., 2016; Miles et al.,

2016; Sheinker and Moldwin, 2016; Regoli et al., 2018),

and even auroral imagers are getting close to fitting Cube-

Sat specifications (Unick et al., 2016; Paxton et al., 2017).

Fennell et al. (2016) conclude that CubeSat versions of

most particle sensors nearly match the performance of

full-sized spaceflight instruments. In addition, the use of

engineering-grade sensors for scientific data products,

such as the magnetometers on the Iridium satellite con-

stellation (Coxon et al., 2018), has significant potential

for rapid growth in space-based instrumentation.

Ground-based sensors hav e also come a long way too,

enabling distributed arrays of small instruments. Several

new miniaturized and low-power sensors have been devel-

oped recently, for example, for magnetometry

(Engebretson and Zesta, 2017), for geocoronal measure-

ments (Gardner et al., 2017), and galactic cosmic ray

monitoring via their byproduct fast neutrons

(Caballero-Lopez, 2016). In addition, the compilation

of ground-based magnetometers from across the globe

into the SuperMAG network (Gjerloev, 2012), with uni-

fied processing and easy accessibility, has provided a

key breakthrough in science studies with these data sets.

47.2.2. High-End Computing and Code Coupling

Advancements

Summit was the world’s fastest supercomputer, brought

online in the summer of 2018. At 200 petaflops, it out-

paced the previously fastest machine by a factor of three.

Are we still on track with Moore’s Law, the observation

that electronic transistor density on a computer chip dou-

bles approximately every two years? Of particular rele-

vance for magnetospheric physics, however, is not

transistor density but rather total computing speed, as

quantified by floating point operations per second

(FLOPS). Figure 47.1 shows the history of FLOPS

increase in the top computers from near the beginning

of the supercomputing age through to the announcement

of the Summit machine. The three curves show the fastest

machine (dotted curve), the 500th fastest machine (dashed

curve), and the sum of computing power for the top-500

machines (solid curve). The growth is a factor of roughly

one million times speed-up (that is, roughly 20 “dou-

blings” of FLOPS) over the past 25 years. Note that yet

another new machine, Fugaku, came online in the sum-

mer of 2020, with a performance 2.8 times faster than

Summit. The amazing speed of Fugaku will surely also

be surpassed some day.

For space physics, this fact of continually-increasing

computational resources means that codes must be

designed to take advantage of efficient parallel processing

algorithms. New codes need to be written with this in

mind and legacy codes need to be updated to exploit

this fact of modern computing. For example, the

INSTIGATORS OF FUTURE CHANGE IN MAGNETOSPHERIC RESEARCH 755

Block-Adaptive-Tree Roe-type Solar wind Upwind

Scheme (BATS-R-US) magnetohydrodynamic model

(Gombosi et al., 2002; Toth et al., 2012) was written with

parallel processing as a cornerstone of its design. Con-

versely, the Rice Convection Model (Harel et al., 1981),

originally written well before the highly-networked super-

computing age, needed to be adapted for parallel calcula-

tion many years after its creation (De Zeeuw et al., 2004).

Some modeling techniques, like test particle codes, are

embarrassingly parallel in that the particle solutions do

not depend on each other, but load balancing becomes

an issue and smart algorithms need to be applied for effi-

cient use of computational resources (Fang et al., 2008).

Code coupling algorithms are also getting better. We

are no longer at the stage of requiring files to be written

by one program and then read by another to transfer

numerical results between codes. While this works well

for one-way coupling, it is inefficient for two-way cou-

pling, in which the codes are run simultaneously on the

same machine. Goodrich et al. (2004) provide a plan

for the code coupling within the Center for Integrated

Space Weather Modeling, detailing the complexity of this

task. Toth et al. (2005, 2012) describe the algorithms

behind the Space Weather Modeling Framework, in par-

ticular the methodology of synchronizing many disparate

code styles into a unified whole. Wiltberger (2015) gives a

review of global magnetospheric modeli ng capabilities,

many of which are coupled code suites. Such coupled code

algorithms are needed for going beyond the magneto-

pause, too, especially space weather simulations from

Sun to the Earth (Merkin et al., 2007; Toth et al.,

2007). This will be especially true as magnetospheric phys-

ics ties in with magnetotelluric modeling to predict geo-

magnetic induced currents (Liemohn et al., 2018b).

The standardization of code input–output will help tre-

mendously with the code-coupling issue. The adoption of

the Space Physics Archive Search and Extract (SPASE)

convention (http://www.spase-group.org/), for both

observational and numerical data sets, provides a proto-

col for information transfer. Development of SPASE-

compliant code requires an initial investment of effor t,

but the future payoff will be highly beneficial for eventual

coupling with other models or allowing SPASE-enab led

websites to find your model results and displa y them, such

as the Virtual Model Repository (http://vmr.engin.umich.

edu/) and the Community Coordinated Modeling Cen-

ter’s Integrated Space Weather Analysis (iSWA) tool

(https://ccmc.gsfc.nasa.gov/iswa/).

The idea of quantum computing, first put forward by

Feynman (1986), has been around for a few decades

(see review by Steane, 1998). The idea is that the informa-

tion is stored in the excited states of single atoms, allowing

an enormous increase in capacity regarding both storage

and processing. A quantum computer is still beyond our

grasp (King, 2018; Yung, 2018). If realized, it will usher

in a new reality of Moore’s Law growth in computing cap-

abilities. This is something to watch for in the coming

years that will revolutionize the way we conduct compu-

tational space physics.

47.2.3. Big Data Storage, Handling, and Data Mining

Techniques

There are several topics that fit within the broad cate-

gory of “big data.” The first is the storage, handling,

and transfer of these large files. While transfers of giga-

bytes are possible across networks, terabyte transfers

are slow, perhaps taking days to complete, and moving

Sum

#500

Top 500 fastest computers

1.E+10

1.E+09

1.E+08

1.E+07

1.E+06

1.E+05

1.E+04

Speed in GFLOPS

1.E+03

1.E+02

1.E+01

1.E+00

1.E–01

Jan-93

Jan-95

Jan-97

Jan-99

Jan-01

Jan-03

Jan-05

Jan-07

Jan-09

Jan-11

Jan-13

Jan-15

Jan-17

Jan-19

Figure 47.1 Peak computing speed in giga-floating-point operations per second (GFLOPS) as a function of time,

from the advent of supercomputers to summer 2018.

756 MAGNETOSPHERES IN THE SOLAR SYSTEM

larger data sets on the petabyte or exabyte scale through

network connections are, at the moment, impractical. It is

often easier to load the data onto a hard drive and ship it

to its destination than wait for bandwidth on the Internet.

Figure 47.2 shows a network of 100 Gb s

−1

nodes devel-

oped by the Department of Energy, the Energy Sciences

Network (Guok et al., 2008). A regional version of this

network is being created within California and eventually

up the coast (https://prp.ucsd.edu/), and an effort is under-

way to create a national big data superhighway (NRP,

2017). NASA is considering these efforts to increase con-

nectivity to this high-end network, allowing space physics

data to flow more rapidly across the country from the data

storage facilities to the researchers analyzing it.

A second aspect of big data is data assimilation – ingesting

observations into model results, changing the values for

the next time step in a simula tion. Data assimilation in

magnetospheric models has been an elusive goal. One

of the first was Garner et al. (1999), with direct replace-

ment of values within the Rice Convection Model.

Because of the high flow speeds and correlation between

neighboring locations, this method is not the optimal

choice for magnetospheric physics studies. When only

one or two satellites are used, assimilation in this manner

does not make for a better, more realistic solution. Better

success has been found with ensemble Kalman filters,

particularly for the radiation belts, when the underlying

model is drift-averaged, so a data stream from a single

spacecraft can influence all local times. This has been

done with several models, like the Versatile Electron

Radiation Belt model (Kondrachev et al., 2011; Shprits

et al., 2013; Kellerman et al., 2014), the Dynamic

Radiation Environment Assimilation Model (Reeves

et al., 2012; Schiller et al., 2012), the Salammbo code

(Maget et al., 2015), and the relativistic electron extension

of the ring current–atmosphere interaction model

(Godinez et al., 2016; Jordanova et al., 2017). Ensemble

Kalman filters have also been used to nudge the

high-latitude electrodynamics solution for global magne-

tospheric models, as done by Merkin et al. (2016).

Another approach that has gained some traction for mag-

netospheric data assimilation is 3DVAR, the three-

dimensional variational assimilation method, which has

been used for plasmaspheric modeling (Nikoukar

et al., 2015).

The new developments mentioned in the earlier sections

will enable data assimilation to become a regular part of

other magnetospheric studies. A constellation of satellites

Seattle, WA

Portland, OR

Eugene, OR

Boise, ID

Reno, NV

Sacramento, CA

Sunnyvale, CA

NERSC

Los Angeles, CA

San Diego, CA

Phoenix, Az

Las Vegas, NV

El Paso, TX

Albuquerque, NM

Dallas, TX

Tulsa, OK

Kansas City, MO

Argonne

National Lab

Goodland, KS

Denver, CO

Ogden, UT

Salt Lake City, UT

Chicago, IL

Cleveland, OH

Buffalo, NY

Syracuse, NY

Albany, NY

Boston, M

New York City, NY

Philadelphia, PA

MANLAN

Pittsburgh, PA

Washington, DC

Indianapolis, IN

Cincinnati, OH

Louisville, KY

Raleigh, NC

Charlotte, NC

Atlanta, GA

Jackson, MS

Houston, TX

San Antonio, TX

Chattanooga, TN

Nashville, TN

St Louis, MO

Oak Ridge

National Lab

Figure 47.2 Department of Energy ESnet data superhighway nodes with ~100 Gb s

−1

throughput. NASA is

proposing to join this effort and expand connections to the system. From the ESnet policy board.

INSTIGATORS OF FUTURE CHANGE IN MAGNETOSPHERIC RESEARCH 757

sprinkled throughout the magnetosphere would be ideal,

providing observations across the vast spatial extent of

geospace for a more uniform nudge of the model results.

Similarly, an extensive array of ground-based sensors

throughout the high-latitude regions in both hemispheres

would be a tremendous data resource for magnetospheric

physics.

The third component of this issue is robustness in data

model comparisons. It is not enough just to do a correla-

tion coefficient or a data model root-mean-square error;

while those are starting calculations that should be done,

there are many more metrics of fit performance and event

detection performance that should be included when com-

paring model output to observations. For instance, Van-

hamäki and Juusola (2018) discuss data methods for

ionospheric electrodynamics, Morley et al. (2018)

describe a method for assessing model results against par-

ticle flux data, which can fluctuate over orders of magni-

tude, and Liemohn et al. (2018a) describe a baseline set for

geomagnetic index model assessment. There is much that

magnetospheric physicists can learn from our counter-

parts in meteorology (see, for example, the many metrics

techniques discussed in Jolliffe and Stephenson, 2011).

A fourth and final topic within the “big data” umbrella

is the adoption of advanced statistical techniques, known

as data science, in particular the idea of machine learning.

McGranaghan et al. (2017) give an excellent overview of

how these new techniques could be used for space physics,

providing examples of how other disciplines have

embraced these methods and offering a strategy for future

research directions that optimize magnetospheric physics

engagement with these tools. Employment of neural net-

works has long been used for geomagnetic index predic-

tion (Lundstedt and Wintoft, 1994; Takalo and

Timonen, 1997; Boberg et al., 2000), but they have only

relatively recently been used for magnetospheric quanti-

ties (Bortnik et al., 2016; Chu et al., 2017a, 2017b).

A workshop entitled “Space Weather: A Multi-

disciplinary Approach” was held to bring together

researchers from the space physics and big data commu-

nities (Camporeale et al., 2018a). This workshop resulted

in a book describing efforts to date and an introduction to

relevant techniques (Camporeale et al., 2018b).

Note that the national Science Foundation (NSF) has

recognized “big data” and the various topics mentioned

above related to it as an area of special attention. In fact,

the NSF is launching a “Ten Big Ideas” initiative, of

which “Harnessing the Data Revolution” is one (https://

www.nsf.gov/news/special_reports/big_ideas/harnessing.

jsp). The NSF intends to heavily invest in this topic over

the next decade; the magnetospheric research community

is poised to be part of this national effort, allowing for

unprecedented advancements in our understanding of

geospace.

47.2.4. Increased Workforce Diversity

At this 2018 Triennial Earth–Sun Summit (TESS) meet-

ing, a plenary session was held on the topic of “Uncon-

scious Bias in Space Physics.” The kick-off presentation

outlined the problem (Richey and Rodgers, 2018), fol-

lowed by a lengthy panel discussion and question period.

This is just one of several conversations taking place in the

space physics community on the topic of creating an inclu-

sive workplace for all scientists. The journal Scientific

American had an entire edition devoted to diversity,

equity, and inclusion, explaining the demographics of

diversity in the scientific workplace (Guterl, 2014a), the

fact that different backgrounds leads to different

approaches towards a problem (Medin et al., 2014), and

how a diverse workforce leads to excellence (Guterl,

2014b). That is, a diverse research community leads to

more creative and open-minded thinking about the pro-

blems being addressed. It is, therefore, good to promote

a diverse workforce, taking this issue into account in

the recruitment of new researchers into the field as well

as helping to make the work environment a more equita-

ble and inclusive place, so that the diverse population will

feel welcome to fully participate.

There is a lon g way to go on this topic, however. Several

studies have examined this issue. For example, our com-

munity’s demographics are changing, albeit very slowly.

A survey of American Geophysical Union (AGU) mem-

bership shows that women comprise only 20% of the

Space Physics and Aeronomy (SPA) section, while a study

by Moldwin and Morrow (2016) of solar and space phys-

ics PhD recipients between 2001 and 2009 showed that

25% were female (of those for whom gender could be iden-

tified, which was 344 of the 416 PhDs). King et al. (2017)

discuss the difficulties in ensuring diversity in the geos-

ciences, Rosen (2017) describes the myriad obstacles that

women face in overcoming sexism to advance their

careers, and Lerback and Hanson (2017) presented data

on how Earth and Space Science journal editors systemat-

ically and disproportionately ask fewer women than men

to review manuscripts. The workplace is not equitable;

there is still work to do to make our resea rch community

fully inclusive and

inviting to all people. Even more insid-

ious and damaging towards diversity, equity, and inclu-

sion is the existence of sexual harassment. A National

Academies report (National Academies, 2018) publicly

exposed the prevalence of sexual harassment in academia.

Several key allies in leadership within our field have

responded by drafting updated Code of Conduct state-

ments for conferences and providing relevant keynote

speakers and training sessions, particularly at the AGU

(https://ethics.agu.org/) and GEM (https://gem.epss.ucla.

edu/mediawiki/index.php/Main_Page#Anti-Harassment_

Policy_for_GEM_Meetings_and_Activities). This is an

758 MAGNETOSPHERES IN THE SOLAR SYSTEM

important step to ensuring an inclusive environment.

Recognition of the achievements of all people in the field

is also important, but has historically not been representa-

tive of the population of the field. Women currently make

up 13% of AGU Fellows within SPA, while being 20% of

the membership. Low numbers of nominations of women

and other underrepresented groups perpetuates this. In the

years 2015–2017, only one of 16, two of 14, and zero of

15 SPA nominations were for women in each of those

years, respectively. In 2016, members of the Earth Science

Women’s Network (ESWN) worked to increase the nomi-

nations of women for AGU Fellow (including the one SPA

nomination mentioned, which was successful). In 2018,

SPA supported a Nomination Task Force (NTF) to delib-

erately address this problem within the section (Jaynes

et al., 2019). Members of the NTF supported the submis-

sion of five nominations for AGU Fellow and one nomina-

tion for AMS Fellow for women and one nomination for

an AGU medal for a member of an underrepresented

group. The AMS Fellow, AGU medal, and one of the

AGU Fellow nominations were successful. The NTF is

continuing this work to sustain the effort.

It should also be noted that magnetospheric physics is a

fundamentally international endeavor. Greenwald (2017)

presents a compelling case that this field has been inher-

ently international from its very beginnings, and details

several of the big initiatives to increase global cooperation

in space research. This cross-border collaboration should

continue, as it is part of the diverse perspective collection

that makes for better and more creative solutions to the

challenges that face the community. Moldwin and Lie-

mohn (2018) also demonstrated that papers with interna-

tional co-authors had higher impact as measured by

citations. It should be noted, however, that there are

obstacles to international collaboration, including visa

policy, travel costs, and technology transfer restrictio ns.

The increased availability and ease of remote communica-

tion methods can overcome some of these obstacles, but

others will be more difficult to address.

47.3. CLOSING COMMENTS

This is an exciting time to be carrying out magneto-

spheric research. We are on the edge of accurate and

meaningful forecasting of space weather and these new

techniques allow for revolutionary advancements in our

understanding of how the magnetosphere works. Further-

more, the demographics of those working in magneto-

spheric research is shifting, bringing new ideas to how

to answer the tough questions we face.

Where will the magnetospheric physics community be

in 10, 20, or 30 years? We foresee that, at some point in

the distance future, it will resemble today’s atmospheric

sciences research community in terms of research initia-

tives yet be something completely different in terms of

workforce interactions. We imagine a robust and distrib-

uted array of measurements contributing to accurate mul-

tiday forecasting of the space environment. We envision

having large-scale community modeling tools open for

all researchers to examine output, conduct their own

simulations, and make code improvements that get

checked back in to the community model. We expect that

there will be full-scale merging of observational and

numerical approaches that allow researchers to probe

not only the microphysical processes but also the sys-

tem-level nonlinearities and large-scale emergent phe-

nomena. We hope that the research community will

look like the general population, that we will be fully

aware of and respectful towards different perspectives

and differing opinions, and that we will embrace this mix-

ture of ideas as the path to the best solutions.

Cassak et al. (2017) and Robinson et al. (2018) note the

importance of the research community in shaping the

future direction of the field. The research community

should be engaged in the planning and implementation

of strategic documents, setting priorities for the research

directions and helping make the plan into reality. The

goals of the National Space Weather Strategy (OSTP ,

2015a) and the Space Weather Action Plan (OSTP,

2015b) are within reach, achieving space weather predic-

tion and forecasting on the level of terrestrial weather

reporting and accuracy. The topics discussed above will

have tremendous impact in helping us achieve that

objective.

ACKNOWLEDGMENTS

The authors would like to thank the sponsors that sup-

ported this work. MWL was partially supported by

NASA through grants 80NSSC17K0015 and

NNX17AB87G and NSF grant 1663770. MBM was par-

tially supported by NSF AGS-1450512 and the NASA

Michigan Space Grant Consortium. The supercomputing

speed data are available at: https://top500.org/statistics/

perfdevel/.

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