Shiokawa and Georgieva Progress in Earth and Planetary Science
https://doi.org/10.1186/s40645-021-00410-1(2021) 8:21

REVIEW

Progress in Earth andPlanetary Science

Open AccessA review of the SCOSTEP’s 5-year scientificprogram VarSITI—Variability of the Sun and
Its Terrestrial Impact
Kazuo Shiokawa1*and Katya Georgieva2,3

Abstract
The Sun is a variable active-dynamo star, emitting radiation in all wavelengths and solar-wind plasma to theinterplanetary space. The Earth is immersed in this radiation and solar wind, showing various responses in geospace
and atmosphere. This Sun–Earth connection variates in time scales from milli-seconds to millennia and beyond. The
solar activity, which has a ~11-year periodicity, is gradually declining in recent three solar cycles, suggesting a
possibility of a grand minimum in near future. VarSITI—variability of the Sun and its terrestrial impact—was the 5year program of the scientific committee on solar-terrestrial physics (SCOSTEP) in 2014–2018, focusing on thisvariability of the Sun and its consequences on the Earth. This paper reviews some background of SCOSTEP and its
past programs, achievements of the 5-year VarSITI program, and remaining outstanding questions after VarSITI.
Keywords: VarSITI, Variability of the Sun and its terrestrial impact, Sun, Heliosphere, Inner magnetosphere,
Ionosphere, Thermosphere, Middle atmosphere, Climate change, Space weather

1 Introduction
The Sun, our home star, is a variable star. Its activity is
due to the action of the solar dynamo, maintaining thesolar magnetic field. The solar wind—the everexpanding solar atmosphere—drags the magnetic field
throughout the whole heliosphere and carries transientslike coronal mass ejections and high-speed solar windstreams. The Earth, together with the other planets inthe solar system, is immersed in the solar wind and interacts with the plasma and magnetic fields originatingfrom the Sun. The Sun also emits radiation in all wavelengths, with sporadically superposed contributions bysolar flares, and modulates the flux of galactic cosmic
rays. All these solar agents vary on time-scales frommilli-seconds to millennia and beyond. Consequently,
their impact on the terrestrial system also varies. The
variations of the Sun and the geoeffective solar agents,* Correspondence: shiokawa@nagoya-u.jp
1
Institute for Space-Earth Environmental Research (ISEE), Nagoya University,
Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan
Full list of author information is available at the end of the article

and their varying impacts on the Earth, were studied by
the SCOSTEP’s program VarSITI—Variability of the Sun
and Its Terrestrial Impact.

1.1 What is SCOSTEPSCOSTEP, the Scientific Committee on Solar-Terrestrial
Physics, was originally established as the Inter-Union
Commission on Solar-Terrestrial Physics (IUCSTP) by
the XIth General Assembly of the International Councilof Scientific Unions (ICSU; now the International
Science Council, ISC) in January 1966. At its XIVthGeneral Assembly in September 1972, ICSU reorganized
IUCSTP as a special committee with responsibility forinterdisciplinary solar-terrestrial physics programs of finite duration. The designation of SCOSTEP took effectin September 1973 after the ratification of a new Constitution by the ICSU Executive Board and General Committee. At the XVIIth ICSU General Assembly in
September 1978, SCOSTEP became a Scientific Committee of ICSU charged with the long-term responsibility
to promote international interdisciplinary programs in© The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
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Shiokawa and Georgieva Progress in Earth and Planetary Sciencesolar-terrestrial physics (https://scostep.org/). Under theInternational Science Council (ISC), SCOSTEP is the
only organization to deal with the Sun–Earthconnections.
1.2 Previous SCOSTEP’s programs
1.2.1 Early programs

The early SCOSTEP’s programs were mostly focused on
separate parts of the solar-terrestrial system: International Magnetospheric Study (IMS: 1976–1979), Solar
Maximum Year (SMY: 1979–1981), Middle Atmosphere
Program (MAP: 1982–1985), and three parallel programs during 1998–2002: International Solar Cycle
Study (ISCS), Planetary Scale Mesopause Observing System (PSMOS), and Equatorial Processes Including
Coupling (EPIC). Meanwhile, the first attempts weremade to incorporate all these into an end-to-end program aiming at improving our understanding of thelinked solar–terrestrial system—the Solar–Terrestrial
Energy Program (STEP: 1990–1997), followed by its
continuation STEP—Results, Application and ModelingPhase (S-RAMP) program (1998–2002). (https://scostep.
org/programs/).
Research in the framework of these programs had led
to significant improvements in understanding the physical processes within each of the Sun–Earth domains:
Sun, heliosphere, magnetosphere, thermosphere/ionosphere, middle atmosphere, lower atmosphere, and climate. Some cross-disciplinary progress was alsoachieved during STEP and S-RAMP in understanding
the domain as a whole.
1.2.2 CAWSES (2004–2008)

In 2000, the SCOSTEP’s Long Range Planning Committee was constructed with the purpose to define future research programs. This group came up with a new
approach for solar-terrestrial physics that led to a newparadigm—end-to-end study of scientific “problems”
within the system as a whole on both short and longtime-scales. The program was named CAWSES—Climate and Weather of the Sun–Earth System. This new
program was intended to enable researchers in various
disciplines to work together to understand the effects of
the Sun on the Earth’s environment.
The fundamental problems for CAWSES as formulated by the Planning Committee were (Schmieder et al.
2004):– Can we link the end-to-end processes that produce
geoeffective coronal mass ejections, facilitate theirtransfer through the heliosphere, their interaction
with the magnetosphere, and the production ofgeomagnetic storms that affect the atmosphere?

(2021) 8:21

Page 2 of 43– Can we identify evidence for long-term variations ofsolar luminosity related to solar activity and resultant impacts on global change, compared with otherclimate change mechanisms?
– Can we reconcile apparent responses of the middle
and lower atmosphere to solar activity, identify thephysical mechanisms, in comparison withanthropogenic influences, and estimate future ozone
changes?
– To what extent are the magnetosphere andionosphere-thermosphere systems modulated bysolar activity on long time scales, including the solar
cycle, and how do variations driven by different processes interact with dynamical and radiative forcing
processes from below?
To answer these questions, four projects were definedby the CAWSES Science Steering Group: solar influences on climate, space weather: science and applications, atmospheric coupling processes, and space
climatology.
1.2.2.1 Theme 1: Solar influence on climate The aimof this project was to investigate the effects of solar variability on the climate of the lower and middle atmosphere. Evidences were accumulated that solar activity
indeed influences climate. Using cosmogenic radionuclides which are primarily produced by the galactic cosmic rays whose intensity is modulated by the open solar
magnetic field, the strength of the interplanetary magnetic field (IMF) was reconstructed for the past 10,000
years. The close relationship between the strength of the
IMF and the total solar irradiance (TSI) found during
the modern space era allowed TSI in turn to be reconstructed in the past from the reconstructed IMF. TSI
was compared with selected climate records, and a relationship was found between solar variability and climate(Beer and McCracken 2009). Considerable evidence wasalso found that solar variability on decadal timescales
does influence climate; however, it was noted that thesolar signal is not uniformly distributed over the globe.
Some mechanisms were suggested for the amplificationof the solar signal, as summarized by (Haigh 2009 andthe references therein). Among then, the so called “Bottom-up” mechanism works in the tropical oceans where
there is less cloud and variations of solar irradiance havemore sensible effects. It includes changes in atmosphericcirculation associated with anomalies in horizontal
temperature gradient of the sea surface. The basis of the“Top-down” mechanism connecting the stratosphere to
the underlying tropospheric climate is the spectral solar
irradiance (SSI) variability which is much greater than
the TSI variability. Other possible mechanisms are related to modulation of El Niño by solar activity throughShiokawa and Georgieva Progress in Earth and Planetary Sciencea change in ocean circulations induced by longitudinallyasymmetric changes in sea surface temperatures, etc.
1.2.2.2 Theme 2: Space weather—science andapplications “Space weather” is known as the shortterm variations of the Sun, propagation of energetic
particles, and electro-magnetic emissions through interplanetary space, and their effects in the magnetosphere,
ionosphere, and thermosphere that can influence theperformance and reliability of space-borne and groundbased technological systems and can endanger humanlife or health. The goals of this project were to develop
dependable, robust deterministic end-to-end models thatpredict conditions in geospace from a quantitative understanding of the observed phenomena.
In addition to Interball, Geotail, Cluster, SOHO, ACE
missions, new spacecraft were launched during CAWS
ES like Hinode, RHESSI, Solar-B, and STEREO. They
allowed to study in unprecedented detail processes on
the Sun responsible for solar flares, energetic particles,
and geoeffective transients in the solar wind. The observed properties of CMEs and ICMEs were summarized, with an emphasis on those properties that
determine the ability of CMEs in causing space weather.
On the applied side, special attention was paid to the effects of solar events on satellite missions in near-Earthorbit.
1.2.2.3 Theme 3: Atmospheric coupling processes
Solar and magnetospheric inputs propagate downward
through the atmosphere while tropospheric effects
propagate upward to the thermosphere–ionosphere system. This project sought to gain greater understandingof atmospheric coupling processes by means of observations, theory, and modeling. Global observing campaigns
were conducted to characterize tides and their influence
from the troposphere to the thermosphere, gravity waves
and turbulence, solar and galactic cosmic rays influenceon minor constituents, and layers at the extra-tropicalsummer mesopause. In the framework of the new topic“Equatorial atmosphere coupling processes,” low latitude
ionospheric disturbances associated with geomagnetic
activity and electrodynamic coupling of equatorial F region with conjugate E regions were studied. A project
was dedicated to atmospheric wave interactions with thewinter polar vortices.
1.2.2.4 Theme 4: Space climatology Climatology includes a description and understanding of the average
properties and regular variations of the system and isconcerned with the long-term effects (e.g., longer than
the solar rotation period). The goal of this project was toprovide the data necessary to study the climatology of
the Sun–Earth system with an emphasis on both a(2021) 8:21

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critical review of the original observations and their interpretations. Two composites of total solar irradiancemeasurements (PMOD and ACRIM) were updated, anda third composite (IRMB) was additionally presented(Fröhlich 2009). New geomagnetic indices [e.g., theInter-Hour Variability (IHV), the Inter-Diurnal Variability (IDV), and Polar Cap Potential (PCP)] were devised
from which the long-term variations of the solar windparameters can be derived (Svalgaard and Cliver 2007).
Special attention was paid to the long-term changes andtrends found in the upper atmosphere at heights above
50 km, i.e., in the mesosphere, thermosphere, and ionosphere (Laštovička, Akmaev and Emmert 2009).
A summarizing CAWSES symposium was held in
Kyoto in 2007, and selected papers from the symposium
were gathered in the monograph “Weather of the Sun–
Earth System (CAWSES): Selected papers from the 2007
Kyoto Symposium” (Tsuda et al. 2009) which is freely
availab le o nline at h t t p s : / / w w w .t e r r a p ub . c o . j p /onlineproceedings/ste/CAWSES2007/index.html.
In summary, the first phase of CAWSES led to a significant improvement in our understanding of the solar
influence on climate changes, effects of sporadic solar
events on the terrestrial system and satellite missions innear-Earth orbit, and the coupling of atmospheric layers
through dynamical, electromagnetic, and photochemical processes. It was recognized, however, that
there was still much that needs to be achieved, andtherefore, the SCOSTEP endorsed the continuation of
the CAWSES program as CAWSES II during 2009–2013.
1.2.3 CAWSES II (2009–2013)

CAWSES II had four task groups: solar influences on
Earth’s climate, geospace response to altered climate,short-term solar variability and geospace, and geospace
response to variable inputs from the lower atmosphere.
Additional activities were related to capacity building
and E-science and informatics, including the creation ofscientific databases and their effective utilization insolar–terrestrial physics research. Below is a brief summary of the overview of the achievements by the CAWS
ES II working groups mostly based on Tsuda et al.
(2015).
1.2.3.1 TG1: Solar influences on Earth’s climate An
important contribution of TG1 was the highlighting of
the role of the spectral solar irradiance in the solar influences on climate. Before CAWSES II, the total solar irradiance (TSI) was the only factor considered toquantify the solar influences on climate change. In
addition to the “bottom-up” mechanism relying on theinfluence of the TSI on the tropical sea surface
temperature with resulting changes in the circulation

Shiokawa and Georgieva Progress in Earth and Planetary Science(Meehl et al. 2008), the “top-down” mechanism was proposed highlighting the role of the spectral solar irradiance (SSI) forcing on chemical-dynamical coupling via
its interactions with atmospheric ozone and connecting
the stratosphere to the underlying tropospheric climate(Gray et al. 2010). A major development during the
CAWSES-II period for studies of energetic particle precipitation effects on the middle and upper atmosphere
was the shift of focus from the previously dominant
topic of solar proton events (SPE) to investigations including energetic electron precipitation (EEP). These
two topics together defined as energetic particle precipitation (EPP). In the high latitude atmosphere, the enhanced ionization from EPP leads to the production of
HOx and NOx which have an important role in middle
atmosphere ozone balance, thus providing a potential
link to dynamics and regional climate (Rozanov et al.
2012). Significant advances were also made in the fieldof cosmic rays. An extensive review on the results of
TG1 is given by Seppälä et al. (2014).
Solar influence on climate is now accepted as an important contribution to climate variability, particularly
on regional scales. During CAWSES II, the main focus
has moved not only from TSI towards understanding
SSI variations and their impact, but as well shifting fromthe global responses to more regional responses. Withbetter understanding of SSI, the importance of the topdown stratospheric UV mechanism has been widely accepted. Improved measurements of both TSI and SSI became available leading to more reliable solar cycle
variation estimates, and a new lower value for TSI wasrecommended for the IPCC AR5 climate simulations(Kopp and Lean 2011).
1.2.3.2 TG2: Geospace response to altered climate
The main focus of TG2 was on the effect of anthropogenic emissions of greenhouse gases (GHG) on the geospace—the region of the atmosphere between thestratosphere and several thousand kilometers above
ground where atmosphere-ionosphere-magnetosphereinteractions occur. GHG cause warming in the troposphere but cooling in the upper atmosphere.
GHG are not the only driver of long-term changes andtrends in the upper atmosphere and ionosphere. A regionally important driver is the secular change of themain magnetic field of the Earth. Model simulation
showed that the secular variation of the Earth’s magnetic
field may be the dominant cause of trends in the Atlantic
region ionosphere (Cnossen and Richmond 2013). In themesosphere and lower thermosphere, important additional drivers appear to be stratospheric ozone, changes
in CH4, and mesospheric water vapor concentration,
though the modelled changes are much higher than theobserved (Qian et al. 2011). The poorly known trends in(2021) 8:21

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atmospheric circulation and particularly in atmosphericwave activity with predominantly tropospheric sources(one of potential trend drivers) remained key open question in the upper atmosphere and ionosphere trends (Laštovička et al. 2014).
A sufficient amount of information had made it possible to create a first scenario of global change in themesosphere, thermosphere, and ionosphere (Laštovička
et al. 2006). During CAWSES-II period, this scenario
had been continuously improved and updated (e.g.,
Laštovička et al. 2012; Danilov 2012; Laštovička
2013). The derived trends qualitatively agree withmodel simulations that show that they are the consequences of the enhanced greenhouse gases. However,some of the trends are still controversial or discrepant.
The key challenges now are to improve the accuracy ofvarious parameters and to reduce the differences in trends
between models and observations.
A summary of the CAWSES-II TG2 achievements isgiven by Laštovička et al. (2014).
1.2.3.3 TG3: Short-term solar variability andgeospace Towards the understanding of the origin andemergency of solar magnetism, the development of improved mean field solar dynamo models that take into
account physical ingredients such as mutli-cellular and/or time varying meridional circulation, magnetic pumping, North-South asymmetry, irregularity in the cycles,
or improved source function for the poloidal field, hasbeen accomplished (e.g., Gopalswamy et al. 2015a, b, c).
The first self-consistent models were developed for generation of magnetic wreaths at the base of the convection zone that have become unstable and started to riseto the top (surface) of the numerical domain (Nelson
et al. 2011, 2013, Nelson 2013). Three-dimentional
MHD numerical simulations successfully explained the
dynamics of several CMEs and the associated shockwaves (Shen et al. 2011).
The International Study for Earth-Affecting Solar
Transients (ISEST) program was newly created within
the frame of CAWSES Task Group 3. It continued during the VarSITI program, with the focused objective ofimproving the scientific understanding of the origin andpropagation of solar transients and developing the prediction capacity of these transients’ arrival and potential
impact on the Earth.
1.2.3.4 TG4: Geospace response to variable inputs
from the lower atmosphere The Task Group 4 focusedon the geospace response to variable inputs from thelower atmosphere. This contains atmospheric waves
generated by meteorological disturbances, their interaction with the background mean flow in the middle atmosphere and with the ionospheric plasma, and their

Shiokawa and Georgieva Progress in Earth and Planetary Science

relation to competing disturbances in the thermosphereand ionosphere generated by energy inputs from themagnetosphere. A comprehensive summary of Task
Group 4 is given by Oberheide et al. (2015).
The major scientific findings during CAWSES-II Task
Group 4 are for impacts from lower atmosphere to the
middle and upper atmosphere and ionosphere throughvarious atmospheric waves, i.e., gravity waves with periods from 5 min to a few hours; tides with periods of 6,8, 12, and 24 h; and planetary waves with periods ofdays. Vadas and Crowley (2010) showed the features ofthe penetration of gravity waves generated from convective plume to the middle atmosphere and ionosphere.
Tsugawa et al. (2011) reported clear concentric waves inionospheric total electron content (TEC) map generated
by catastrophic Tohoku earthquake and Tsunami on 11
March 2011. This event provided a strong visual evidence of gravity wave penetration to the ionosphere.
The wavenumber 4 structure observed in the equatorial
ionosphere by Immel et al. (2006) was recognized as aresult of penetration of atmospheric tides to the E- andF-region ionosphere and electromagnetic coupling between E- and F-region ionosphere (e.g., England 2012).
After the discovery of response of ionospheric TEC tothe stratospheric sudden warming (SSW) induced byplanetary wave collapse by Goncharenko and Zhang(2008), many evidences of planetary wave penetration to
the thermosphere and ionosphere have been reported
during the CAWSES-II period.
A summarizing CAWSES-II symposium was held in
Nagoya in 2013, and selected papers from the symposium were gathered in the special issue of Earth Planets
and Space at https://www.springeropen.com/collections/
ICS (overview: Yamamoto et al. 2016). Review papers of
the four task groups and overall CAWAES-II (overview:
Tsuda et al. 2015) were published in the special issue ofProgress in Earth and Planetary Science which is freely
available online at https://www.springeropen.com/
collections/cawses2reviewcollection.

2 VarSITI (2014–2018)
CAWSES coincided with the prolonged period of very
low solar activity between sunspot cycles 23 and 24.
CAWSES II started in 2009, the long-awaited beginningof cycle 24, and covered the rising phase of the cycle. It
was even subtitled “Towards solar maximum.” However,that solar maximum was a surprise to most of thecommunity.
Both CAWSES and CAWSES II were mainly focusedon the Earth’s atmosphere: how it is affected by solar activity on short and long time scales, how anthropogenically induced changes in the atmosphere affect climate,
how the solar effects in the atmosphere depend on a(2021) 8:21

Page 5 of 43changing climate, and how upper atmospheric levels are
influenced by lower levels.
Due to the observed decline in solar activity whichputs an end to the Modern Grand Maximum, as shownin Fig. 1, by the time of the start of the next SCOSTEP’s
scientific program, more attention was directed to theSun: are we facing the next grand minimum in solar activity or will this be just a regular secular minimum? In
either case, what are the most extreme solar events that
we can expect, and how will they affect the Earth’s system and its technological infrastructure? In a period of
low solar activity, what are the characteristics of geoeffective solar agents, and how does the terrestrial system
respond to them?
Basically, all we know about the Sun and the geoeffective solar transients from space-borne and in situ measurements is for the period of the “space era,” coinciding
with the period of the grand maximum of solar activity
in the second half of the twentieth century. The question
arises whether the mechanisms and models based onthese observations will hold true in a period of lower
activity.
The definition of the VarSITI program was a community effort (Gopalswamy 2013). The primary input was aset of nine white papers received from the community
spanning the interests of all the scientific unions andinterdisciplinary bodies of ICSU represented in the SCOSTEP Bureau. Community input was also received during the International Symposium on Solar-Terrestrial
Physics in Pune India in 2012 when a panel discussion
was held on the next scientific program. After a thorough discussion among the Bureau members, a set of 30
experts from the SCOSTEP community was invited to abrainstorming forum organized by the International

Fig. 1 Instrumental sunspot observations: group sunspot number(Hoyt and Schatten 1998)—blue line and international sunspot
number (Clette et al. 2007)—red line. The shaded area indicates the“space era” which started with the launching of the first artificial
satellites of the Earth for in situ measurements in the outer spaceShiokawa and Georgieva Progress in Earth and Planetary Science

Space Science Institute (ISSI) in Bern, Switzerland, during May 7–8, 2013. The participants were the authors of
the white papers, the SCOSTEP Bureau, and international scientists. The 9 white papers and the community input were synthesized into four projects:(i) Solar Evolution and Extrema (SEE)(ii) International Study of Earth-affecting Solar Transients (ISEST/MiniMax24)(iii)Specification and Prediction of the Coupled InnerMagnetospheric Environment (SPeCIMEN)(iv) Role Of the Sun and the Middle atmosphere/
thermosphere/ionosphere In Climate (ROSMIC).
The name VarSITI (Variability of the Sun and Its Terrestrial Impacts) was proposed and accepted at the ISSI
Forum. Further community input was received during
the CAWSES-II Symposium in Nagoya in 2013 and the
VarSITI Town Hall during the AGU 2013 fall meetingin San Francisco.

3 Selected results from VarSITI
3.1 Project SEE: Solar Evolution and Extrema

During CAWSES II, physical models based on thesolar dynamo theory, together with other approaches(statistics, precursors, correlations, neural networks,etc.), were employed for the first time in predicting
the following sunspot cycle 24. A set of predictions of
the amplitude of Solar Cycle 24 accumulated in 2008
ranged from very low to unprecedented high levels of
solar activity (Fig. 2). The predictions formed an almost normal distribution, centered on the average
amplitude of all preceding solar cycles (Pesnell 2012).
The wide range of the predicted amplitudes, even derived using the same methods, demonstrated that at
the time of the completion of CAWSES II, we werestill far from understanding the physics of the solar
cycle.
The goal of the project SEE was to answer the following questions:
1. Are we at the verge of a new grand minimum? If
not, what is the expectation for cycle 25?
2. For the next few decades, what can we expect interms of extreme solar flares and storms, and alsoabsence of activity? Another Carrington event?
What is the largest solar eruption/flare possible?
What is the expectation for periods with absence ofactivity?
3. Does our current best understanding of theevolution of solar irradiance and mass loss resolve
the “Faint Young Sun” problem? What are thealternative solutions?

(2021) 8:21

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3.1.1 Forecasting solar activity

One of the main focuses of VarSITI program was theend of the modern grand maximum of solar activity andwhat we can expect after it. Different approaches are
employed to forecast the future sunspot cycles: extrapolations and statistical relations between some characteristics of the average sunspot cycle and between
consecutive cycles, precursor methods, data-driven fluxtransport simulations, machine learning, neural network,
autoregressive models, etc. All prediction methods canbe generically divided into three broad groups, including
the majority of the above classifications: statistical or extrapolation methods, precursor methods, and modelbased methods. Extensive reviews of the prediction
methods and some early forecasts of cycle 25 are given
by Petrovay (2020).
It should be noted here that a major event occurred
during the VarSITI program though it was not part of it.
After a series of “Sunspot Number Workshops” (http://ssnworkshop.wikia.com/wiki/Home), on July 1, 2015, theSunspot Index Data Center in Brussels terminated themore than 400 years long data series of the International
relative sunspot number RZ and replaced it by a newentirely revised data series SN (Cliver et al. 2013;
Clette et al. 2014). In this revised data series SN, theoverall level of solar activity was significantly increased as compared to RZ. In the future solar activity
forecasts, some authors still use the original RZ series,
others use the new SN series, and the comparison of
the predictions for cycle 25, as well as between cycle
24 and the predictions for cycle 25 is not straightforward. To avoid misunderstanding, for each forecast,
we will indicate which series is used: V1 for the original RZ (Clette et al. 2007) or V2 for the recalibrated
SN (Clette et al. 2014).
The statistical and extrapolation methods include linear regression techniques (e.g., Chae and Kim 2017;
Werner and Guineva 2020), multivariate regression(Sabarinath and Anilkumar 2018), neural networks(Covas et al. 2019), deep learning (Pala and Atici 2019),
and non-linear prediction algorithms (Sarp et al. 2018).
Extrapolation methods can theoretically yield very
long-term predictions. An attempt to make a superlong-term forecast was made by Popova et al. (2018),
where it is stated that two fundamental dependenceswere found for a solar dipole and a quadrupole, on thebasis of which one can make a forecast for many cycles
ahead. This forecast was an example of the methods
based on spectral analysis in which it is assumed thatthe sunspot time series is a superposition of periodicities. This article was criticized by Usoskin (2018), which
the authors disagreed with Zharkova et al. (2018).
Most of the predictions based on statistical and extrapolation methods are for a low cycle 25, similar

Shiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

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Fig. 2 Forecasts of solar cycle 24 (From Pesnell 2012)(possibly somewhat higher of somewhat lower) to cycle
24. Some studies predict a very weak cycle (e.g., Covas
et al. 2019), a cycle stronger than cycle 24 (Sarp et al.
2018), or stronger than both cycles 23 and 24 (Pala andAtici 2019).
In the precursor methods, the future sunspot maximum is predicted using its correlations with otherheliophysical parameters observed before this maximum(“precursors”). Helal and Galal (2013) used a correlation
between the number of spotless days and the upcoming
solar maximum to estimate that Solar Cycle 25 will have
Rz = 118.2 (V1), peaking 4.0 years after the solar minimum. Yoshida (2014) used correlations between Rz before minimum with the upcoming solar maximum, usingShiokawa and Georgieva Progress in Earth and Planetary Science

the symmetries of the even/odd cycles to derive the prediction: Rz = 115.4 ± 11.9 (V1). Based on the empiricalcorrelation between the dipole moment during solar
minimum and the strength of the subsequent cycle,
Cameron et al. (2016) suggest that Cycle 25 will be ofmoderate amplitude, not much higher than cycle 24.
Kirov et al. (2018) show that both the maximum sunspot
number of a solar cycle and the minimum of geomagnetic activity preceding it can be predicted from the
maximum value of the solar dipole magnetic field of theprevious cycle which is observed well before the sunspot
minimum. They estimated that the minimum geomagnetic activity between cycles 24 and 25 as quantified by
the geomagnetic ap-index will be about 5, and the maximum sunspot number for cycle 25 about 50–55 (V1).
Petrovay et al. (2018) focused on the rush–to-the-poles(RTTP) phenomenon in coronal green line emission.
Considering various correlations between properties of
the RTTP with the upcoming solar cycle, they found acorrelation between the rate of the RTTP and the timedelay until the maximum of the next solar cycle. On thebasis of this correlation and the known internal regularities of the sunspot number series, they predict that, following a minimum in 2019, cycle 25 will peak in late 2024
at an amplitude of about 130 (V2). This slightly exceeds
the amplitude of cycle 24, but it would still make cycle 25
a fairly weak cycle. Gopalswamy et al. (2018) used polarand low-latitude brightness temperatures from theNobeyama Radioheliograph at 17 GHz as proxies to thepolar and active region magnetic fields, respectively, andthe locations of prominence eruptions as a proxy to thefilament locations to study their time variation. They
showed that the polar microwave brightness temperature
is highly correlated with the polar magnetic field strengthand the fast solar wind speed, and that the polar microwave brightness in one cycle is correlated with the lowlatitude brightness with a lag of about half a solar cycle.
They used this correlation to predict the strength of thesolar cycle 25: the smoothed sunspot numbers (V2) in thesouthern and northern hemispheres can be predicted as
89 and 59, respectively. These values indicate that cycle 25
will not be too different from cycle 24 in its strength.
Gopalswamy et al. (2018) also combined the rush-to-thepole data from Nobeyama prominences with historical
data going back to 1860 to study the north-south asymmetry of sign reversal at solar poles. They find that the reversal asymmetry has a quasi-periodicity of 3–5 cycles.
The model-based methods are based on the theory ofsolar dynamo. A very recent review of dynamo modelsof the solar cycle is presented by Charbonneau (2020).
The flux-transport mechanism allows predictions by assimilating the observed magnetic field on the surface.
Since the emergence of sunspot groups has random
properties, making it impossible to accurately predict(2021) 8:21

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the solar cycle and strongly limiting the scope of cycle
predictions, Jiang et al. (2018) developed a scheme to investigate the predictability of the solar activity over one
cycle. When a cycle has been ongoing for more than 3
years, the sunspot group emergence can be predicted alongwith its uncertainty during the rest time of the cycle. The
method gives maximum strength of cycle 25 in the range
125 ± 32 (2σ uncertainty range, V2), which is about 10%stronger than cycle 24 based on the mean value. Using an
Advective Flux Transport (AFT) model, Hathaway and
Upton (2016) predicted that cycle 25 will be similar instrength to the cycle 24, with an uncertainty of about 15%.
AFT also predicted that the polar fields in the southernhemisphere would weaken in late 2016 and into 2017 before recovering. After two more years of observations,
Upton and Hathaway (2018) examined the accuracy of the2016 AFT prediction and found that the new observations
track well with AFT’s predictions for the last 2 years. The
updated prediction for cycle 25 was that it will be slightly
weaker than cycle 24, making it the weakest cycle on record in the last hundred years. As weak cycles are precededby long extended minima, we may not reach the cycle24/
25 minimum until 2021. Bhowmik and Nandy (2018)
coupled 2D flux transport model to a 2D kinematic dynamo model and sequentially calculated the polar field of
one cycle and the number of sunspots in the next cycle.
They predicted the maximum of cycle 25 in 2023–2025
with the height of 109–139 (V2).
The general conclusion is that the beginning of thetwentyfirst century will be characterized by one or two
cycles with a fairly low or just low intensity. A more serious, Maunder-type decline of activity cannot be ruledout either, but in the next few decades, the level of solar
activity is expected to be either average (more likely) orof the type of the Dalton minimum (less likely).
A review of the recent results on predicting the futuresolar activity in the framework of VarSITI program isgiven by Nandi et al. (this issue).
3.1.2 Extreme solar events

Extreme can be considered events on the tail of a distribution—for example, a CME with speed or magnetic fieldexceeding certain thresholds that very few observed so far
events have exceeded (Gopalswamy 2018). From the terrestrial point of view, extreme are solar events leading to
disturbances in the terrestrial system that very few observed so far events have caused. It should be noted that
there is no direct correspondence between the two typesof extreme events: extreme geomagnetic storms are nearly
always, but not always, produced by extreme solar events,and extreme solar events do not necessarily cause extreme
geomagnetic storms (Schmieder 2018).
The ability of a solar active region to produce an extreme event depends of the maximum possible magnetic

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of the magnetic potential energy, and of the ability ofthe solar active regions to produce extreme events.
Figure 3 shows the cumulative distribution of the active regions’ areas A for the period 1874–2016(Gopalswamy 2018). The cumulative number decreases slowly until the area reaches ~ 1000 msh (millionths of solar hemisphere) and then decreases
rapidly. The overall distribution can be fit to the Weibull’sfunction, and its high area tail—also to a power law. An
extreme active region (once in 100 years) has an areaof ~ 7000 msh according to the power law and ~6000 msh according to the Weibull function.

Fig. 3 Cumulative number N of active regions’ (sunspot groups’)
areas A from 1874 to 2016. A is expressed in msh (millionths of solar
hemisphere). The left-hand Y-axis gives the total number of active
regions with area > A, and the right-hand Y-axis—the occurrence
rate N per year (taken from Gopalswamy 2018)

potential energy that can be converted into magnetic
kinetic energy. The visual indicators of active regions aresunspots.
The number and area of sunspots reflect the intensityof the solar magnetic fields in the solar active regions(Houtgast and van Sluiters 1948). Therefore, using historical data of active regions’ areas, estimations can bemade of the active regions’ magnetic fields, respectively,

Fig. 4 Cumulative distribution of CME speed (V) from SOHO/LASCO
with the average speeds of the various CME populations (taken from
Gopalswamy 2016)

3.1.2.1 Coronal mass ejections Figure 4 presents the
cumulative distribution of CMEs’ speed from SOHO/LASCO (https://cdaw.gsfc.nasa.gov) with the average
speeds of the various CME populations marked on theplot: metric type II radio bursts (m2); magnetic clouds(MC); ejecta (EJ)—ICMEs lacking flux rope structure;interplanetary shocks (S) detected in the solar wind; geomagnetic storms (GM) caused by CME magnetic field orshock sheath; halo CMEs (Halo) that appear to surroundthe occulting disk of the coronagraph and propagating
Earthward or anti-Earthward; decameter-hectometric(DH) type II bursts indicating electron acceleration by
CME-driven shocks in the interplanetary medium; SEP
events caused by CME-driven shocks; and ground level
enhancement (GLE) in SEP events indicating the acceleration of GeV particles.
The fastest CME observed by SOHO/LASCO occurredon November 10, 2004, with an average speed in thecoronagraph field of view of 3387 km/s, and there arevery few CMEs with speeds exceeding ~ 3000 km/s. Figure 5a illustrates the occurrence frequency of CMEs
with speeds exceeding certain values. From the Weibull
distribution, once in 100 years an event may occur with
V > 3800 km/s, and once in 1000 years—an event with V> 4700 km/s (Gopalswamy 2018).
Figure 5b gives the cumulative distribution and occurrence frequency of the CMEs’ kinetic energy. The oncein 100 years and once in 1000 years events have kinetic
energies 4.4 × 1033 and 9.8 × 1033 erg, respectively,
which are not much higher than the highest reported
values. The CME with the highest kinetic energy of 4.2
× 1033 erg was observed by SOHO/LASCO on September 9, 2005 (Gopalswamy 2018).
3.1.2.2 Flares As in the case of CMEs, the extreme solar
flares are defined as one in 100 years and one in 1000
years events. Figure 6 is the cumulative distribution of
all flares recorded by various GOES satellites since 1969
in the 1–8 A° energy band.
For the flare intensity, the Weibull and the power law
distributions give almost identical results: the 100-year

Shiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

Page 10 of 43

Fig. 5 Cumulative distribution of CME speeds (a) and kinetic energies (b) from SOHO/LASCO catalog (https://cdaw.gsfcs.nasa.gov) for the period
1996–2016 (taken from Gopalswamy 2018)

and 1000-year event sizes are X43.9 and X101, respectively, according to the Weibull distribution, and X42
and X115 according to the power law distribution(Gopalswamy 2018). As mentioned above, the largest
flare during the space age was registered by the GOES
satellite on November 4, 2003, but as the GOES X-ray
sensor saturated at a level of X17.4 for about 12 minduring this event, it was suggested that the flare size
should have been in the range X34–X48, with a mean

Fig. 6 Cumulative distribution of flare sizes between 1969 and 2016.
The flare data are from https://www.ngdc.noaa.gov/stp/solar/
solarflares.html (taken from Gopalswamy 2018)

value of X40 (Brodrick et al. 2005). Therefore, it is about
the size of the 100-year maximum.
The bolometric energy (the energy emitted across thewhole electromagnetic spectrum) corresponding to an
X100 flare is 1033 erg (see e.g., Benz 2017). Flares withbolometric energies > 1033 erg are considered super flares.
There is no agreement about how extreme a solar flare
can be, and how often extreme flares can occur. The
period of instrumental observations of the Sun is only
400 years which is far from good statistics. However, we
can complement these observations with observations ofsolar-like stars. Superflare stars are generally characterized by larger chromospheric emissions than other stars,
including the Sun, but superflare stars with activity levels
lower than, or comparable to, the Sun do exist, suggesting that solar flares and superflares most likely share thesame origin (Karoff et al. 2016). Therefore, if we observe
10,000 solar type stars (slowly rotating G-type main sequence stars with surface temperatures between 5600
and 6000 K) for 1 year, we can get the data similar to thedata obtained from 10,000 years’ observations of theSun. Maehara et al. (2012) using Kepler satellite data,
which include observations of 80,000 solar type stars,
found 365 superflares with total bolometric energy from1033 to 1036 erg on 148 solar type stars. Superflares of1034 erg on Sun-like stars were estimated to occur once
every 800 year, and those of 1035 erg—once every 5000
year. This is much more frequently than implied by Fig. 3
where the tail of the flare-size distribution suggests thatsuper flares (> 1033 erg) can occur on the Sun once in amillennium, and a 1034 erg flare—only once in 125,000
years (Gopalswamy 2018). Besides, historical surveys ofShiokawa and Georgieva Progress in Earth and Planetary Science

bright or oddly colored Sun, short intense heat waves, or
low-latitude auroras indicate that the Sun has likely not
had any superflares in the last two millennia (Schaefer
et al. 2000).
Aulanier et al. (2010, 2013) used a dimensionless numerical 3D MHD simulation for solar eruptions. When themodel is scaled to the strongest measured sunspot group’s
area and magnetic field (6000 msh and 3.5 kG, respectively), it can be used to calculate the size of the sunspot
pair that is required to generate the solar flares of various
energies. Further, observations show that large sunspots
groups are always fragmented into several spots and arenever involved in a given flare as a whole, only one bipole
will be involved in the flare. Aulanier et al. (2013) estimated that only 30% of the area of a given sunspot groupcan be involved in a flare. Figure 7 from Schmieder (2018)illustrates the size of the sunspot group needed to host abipole which can produce a flare of a given size. With
these scalings, a superflare of 1036 erg requires a very large
single pair of spots, whose extent is 48o in longitude/latitude, at the surface of a Sun-like star. Such spots havenever been reported on the Sun (Aulanier et al. 2013).
These scalings resulted in a maximum solar flare energy of∼6 × 1033 erg which is only about six times thatof the strongest-ever directly observed flare of Nov. 4,
2003. Aulanier et al. (2013) argued that superflares of1034 erg are unrealistic for the Sun because of the observed fragmentation of the magnetic flux in the active
regions. However, Toriumi and Takasao (2017) demonstrated that even one of the largest, highly fragmented
sunspot groups, such as the one numbered 14585 by theRoyal Greenwich Observatory (RGO), produced a flare
eruption leaving AR-sized, gigantic flare ribbons (on July25, 1946), which may point to the possibility that even(2021) 8:21

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larger ARs could occur and cause a superflare. For thelargest sunspot group on 1947 April 8, RGO 14886 witha maximum spot area of 6132 msh, Toriumi and Wang(2019) estimated its total flux to be 2.0 × 1023 Mx, leading to a flare with energy 1.5 × 1034 erg. This is morethan twice larger than the maximum possible energy estimated by Aulanier et al. (2013), and in the energy
range of the weak superflares reported by Maehara et al.
(2012) for numerous slowly rotating and isolated Sunlike stars, but is several orders of magnitude smaller thanthat of strong stellar superflares.
An open question is whether the current solar dynamo
can produce much larger sunspot groups as required to
produce stronger flares.
3.1.2.3 Terrestrial perspective From the terrestrial perspective, a crucial question is how extreme geomagnetic
storms the solar extreme events can produce. The Dstindex is available since 1957, and since then, there has
been only one storm with Dst ≤ 500 nT. It had an intensityof Dst = − 589 nT and happened on March 13–14, 1989.
Another very intense magnetic storm, reaching almost thelevel of a superstorm with Dst ≤ 490 nT, occurred on November 20, 2003. Only these two events can qualify as possible superstorms since the Dst-index is available.
Before the Dst-index became available, the geomagnetic storms can be estimated from magnetic field datafrom the Colaba and Alibag Observatories operating
since 1841. The strongest geomagnetic storm since thenis the famous Carrington event on September 1, 1859
(Lakhina and Tsurutani 2018). The depletion of thehorizontal component of the magnetic field measured in
the Colaba observatory in Mumbai, India, was 1600 nT.
The transit time of the ICME from the Sun to the EarthFig. 7 Schematic representation of several modeled sunspot groups on the solar disk, with their corresponding modeled flaw energies
computed with the Aulanier et al. (2013) simulation. A sunspot group consists of several pairs of sunspots. In each group, a pair of sunspots(surrounded by red curve) representing 30% of the sunspot group area is modeled in the simulation (taken from Schmieder 2018)

Shiokawa and Georgieva Progress in Earth and Planetary Science

was 17 h and 40 min, so the average shock transit speed
is found to be 2380 km/s, and the estimated speed at
Earth’s orbit was estimated to have been 1850 km/s.
Based on the empirical relation between the speed andmagnetic field of the ejecta (Gonzalez et al. 1998), themagnetic field magnitude was calculated to have been 90
nT at 1 AU. Finally, from the empirical expression for the
dependence of the Dst-index of the speed and magnetic
field of the ejecta, the Dst-index of the Carrington event
was estimated as − 1760 nT (Tsurutani et al. 2003).
Tsurutani and Lakhina (2014) and Lakhina and Tsurutani(2018) estimated the maximum possible intensity of asuperstorm. They assumed a maximum CME speed close
to the Sun of 3000 km/s, and a 10% decrease on the way to
the Earth, or a speed 2700 km/s at 1 AU. This would give
shock transit time from the Sun to the Earth of ~ 12.0 h(for comparison, the fastest ever recorded event on August
1972 took 14.6 h and the Carrington event 17.6 h). This
would mean Alfvén Mach number of ~ 63 and magnetosonic Mach number of ~ 45. The largest magnetosonic Mach
number of the shock observed so far is ~ 28 and that is forthe shock associated with the extreme ICME of July 23,
2012 (Riley et al. 2016). The ram pressure of the maximum
intensity superstorm downstream of the ICME shock was
calculated to be 244 nPa, which would cause the magnetopause to be pushed inward from its quiet time position of~ 11.9 RE to a new subsolar position at ~ 5.0 RE from thecenter of the Earth, where RE is an Earth radius (6371 km).
So far, the lowest magnetopause position detected is at 5.2
RE for the August 1972 storm. Using the empirical relationship between the speed and magnetic field strength of the
ICME at 1 AU (Gonzalez et al. 1998), the magnetic cloudfield strength of 127 nT was estimated by Tsurutani and
Lakhina (2014). This yields a maximum strength of theinterplanetary electric field of 340 mV/m, and if we accept
a linear dependence of the intensity of all magnetic storms
on the interplanetary electric field (Burton et al. 1975; Echer
et al. 2008), the maximum possible intensity of a superstorm is expected to be twice the intensity of the Carrington storm, that is, Dst ~ 3500 nT.
Figure 8 shows the cumulative distribution of geomagnetic storms with Dst < 100 nT. According to the
Weibull distribution which fits better the data points, a
100-year event has a size of 603 nT, and a 1000-year
event has a size of 845 nT. The 100-year event is consistent with the March 1989 event, while the 1000-year
event is half the estimated size of the Carrington storm.
It should be noted, however, that some authors argue
that the − 1760 nT of the Carrington event is an overestimation and suggest a Dst around − 900 nT as a nominal value for it (Gopalswamy 2018).
Yermolaev et al. (2018), assuming power law, calculated
the tails of distributions in the area of moderate andstrong storms (from − 150 to − 300 nT) where statistics of(2021) 8:21

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Fig. 8 Cumulative distribution of intense geomagnetic storms (Dst <100 nT) and their yearly rates since 1957 (taken from
Gopalswamy 2018)

events are sufficiently high in the period 1963–2015 andthen extrapolated the distributions to the area of extreme
magnetic storms where statistics are poor. They foundthat the most probable waiting times for extreme magnetic storms with Dst ≤ 500, − 1000, and − 1700 nT are
24 years, 250 years, and 1500 years, respectively (with errors 10%, 40%, and 100%). If only the storms caused bymagnetic clouds are considered, the waiting times reduce
to 20, 120, and 500 years, respectively. A detailed review of
the SEE results is given by Nandi et al. (2021).
3.1.3 Highlights of contribution from young scientists to theSEE projectAs has been shown in the highlight of young scientists
in VarSITI Newsletter, several active young scientists
have contributed to the VarSITI/SEE project. Toriumi
et al. (2014) studied solar flux emergence and formationof flare-productive active region on solar surface using
both satellite observation and three-dimentional simulation. Jiang et al. (2014, 2015) studied effects on sunspot
group tilt angles on large-scale magnetic field on thesolar surface, and relation of the solar surface field evolution to the weak solar cycle 24. Pal et al. (2017, 2018)
reported Sun-to-earth analysis of magnetic helicity of
the 2013 March 17–18 interplanetary coronal mass ejection and the dependence of coronal mass ejection properties on their solar source active region characteristics
and associated flare reconnection flux. Holappa et al.
(2014a, b) showed a long-term relationship between
solar wind structures and geomagnetic activities using
new principal component analysis. For solar effect on
the Earth’s atmosphere, Maliniemi et al. (2014, 2016) reported spatial distribution of Northern Hemisphere winter temperatures during different phases of the solar

Shiokawa and Georgieva Progress in Earth and Planetary Science

cycle and the effect of geomagnetic activity on the
Northern Annular Mode in the lower atmosphere.
3.2 Project ISEST/MiniMax24: International Study of Earthaffecting Solar TransientsThe International Study for Earth-Affecting Solar Transients (ISEST) program started already within the framework of CAWSES II Task Group 3 (“Short-term Solar
Variability and Geospace”). The summary of this activity
is given by Gopalswamy et al. (2015a). The project continued during the VarSITI program, focused on the origin and propagation of solar transients, and their impact
on the Earth.
Solar transients are short time-scale (from minutes todays) energetic and/or eruptive events occurring on the
Sun that directly cause transient disturbances in the
Earth’s space environment and possibly impose adverse effects on advanced technological systems of human society.
Solar transient events can be divided in the following
four categories: (1) solar flares, (2) coronal mass ejections(CMEs) including their interplanetary counterparts ICMEs,(3) solar energetic particle (SEP) events, and (4) stream
interaction regions (SIRs) including corotating interaction
regions (CIRs). These four types of Earth-affecting transient events differ in their physical origin or processes, observational appearances, and their geoeffectiveness.
The implementation of the ISEST project was centeredaround seven working groups, which are as follows:(1) Data(2) Theory(3) Simulation(4) Campaign study(5) SEP(6) Bs challenge(7) MiniMax24 campaign.
This overview is a brief summary of the detailed description of the working group activities by Zhang et al. (2021).

(2021) 8:21

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from post-eruptive arcades, flare ribbons, and coronaldimmings measured close to the Sun with magnetic cloudproperties at 1 AU (Qiu et al. 2007; Gopalswamy et al.
2017; Palmerio et al. 2017; James et al. 2017).
The weak solar cycle 24 was one of the main focusesof the VarSITI program. The properties of the transient
events were extensively studied in the framework of
ISEST/MiniMax. The overall rate of CMEs was found tohave increased in solar cycle 24 relative to cycle 23, although the rate of fast and wide CMEs decreased.
Marked changes are observed in the number of intense(Dst ≤ 100 nT) geomagnetic storms (Gopalswamy et al.,2015a, b, c) and high-energy (≥ 500 MeV) SEP events(Gopalswamy et al. 2014; Mewaldt et al. 2015). On theother hand, the number of halo CMEs in cycle 24 did
not decrease significantly (Gopalswamy et al. 2015b). In
fact, the number of halo CMEs as well as the total number of CMEs normalized to the sunspot number is larger
in cycle 24 than in cycle 23.
3.2.2 Theory

Scolini et al. (2019) used proxies of magnetic flux estimates determined from post-flare arcades (Gopalswamy
et al. 2017), flare ribbons (Kazachenko et al. 2017;
Tschernitz et al. 2018), and coronal dimmings (Dissauer
et al., 2018a, b) as initial input for the EUropean Heliospheric FORecasting Information Asset (EUHFORIA)
model, to study the geoeffectiveness of the famous 2017
September events. Good agreement with the observed
Dst profile was found for simulations using the optimized input and including CME-CME interactions.
Recently, there has been substantial development in
the forward modelling of the magnetic structures using
physics-based empirical models. The forward models
typically assume a specific morphology of a magnetic
structure, i.e., flux rope, and evolve it, assuming specificpropagation and expansion (Wood et al. 2017). A stepfurther is to include a specific flux rope magnetic field
topology (e.g., Patsourakos et al. 2016; Isavnin 2016; Kayet al. 2017; Möstl et al. 2015).

3.2.1 Data

In the last decade, a large fleet of spacecraft provided
continuous measurements of the Sun and the interplanetary space. Unprecedented multiple-angle observations
were provided by the Solar Terrestrial Relations Observatory Ahead/Behind (STEREO A/B). Thanks to theseobservations, our knowledge on CME morphologicaland kinematics properties has improved significantly.
Several studies focused on Sun-to-Earth analysis of
CMEs by linking the low coronal behaviour and propertiesof the eruption with its observed in situ signature (D’Huys
et al. 2017; Temmer et al. 2017). A number of studies also
compared magnetic flux rope properties, such as the magnetic flux, the chirality, and its helicity sign determined

3.2.3 Simulation

During the period of the VarSITI/ISEST, the main focus
in the MHD space weather modeling was in the following
areas: the background solar wind, CME initiation andpropagation, interaction between CMEs and solar windstructures (CIR and HCS), and CME-CME interaction.
A detailed review of the recent progress in these areas
is given in Zhang et al. (2021), and the main conclusions
are as follows:
There has been a significant increase in the number of
3-D MHD codes that has been successfully used tosimulate the Sun-to-Earth propagation of CMEs; this has
been the case most notably in Europe with EUHFORIA,

Shiokawa and Georgieva Progress in Earth and Planetary Science

Japan, with SUSANOO and China with IN-TVD MHD.
In addition, a number of existing MHD codes have been
adapted to investigate the heliospheric propagation of
CMEs, including LFM into LFM-Helio and MAS into
MAS-Helio.
Heliospheric codes (starting typically at 0.1 AU) havebeen used with spheromak and/or flux rope CMEs,
which bridges the gap between computationally intensive Sun-to-Earth simulations and heliospheric simulations with code models. These types of simulations may
be used to investigate the magnetic field configuration
inside CMEs as well as their arrival time, and are more
physically consistent when investigating CME-CME
interaction than simulations in which the CMEs do nothave internal magnetic fields.
In parallel, there has been an effort to make the CME
initialization quicker and easier to perform in coronal
codes using out-of-equilibrium flux ropes. This paves theway for future real-time Sun-to-Earth simulations withmagnetized CMEs initiated based on magnetograms, EUV
images, and early coronagraphic images. It is well known
that major changes in the CME properties, including its
speed and orientation, may occur below 0.1 AU where
heliospheric models are initiated. At this time, it is however unclear whether simulations with magnetized CMEs
initiated at 0.1 AU using multi-viewpoints coronagraphic
measurements will perform worse than simulations withmagnetized CMEs initiated at the solar surface, in term ofspace weather forecasting capabilities. The number of
Sun-to-Earth simulations of CMEs initiated at the solar
surface with a realistic model is still relatively low, eventhough there has been effort in presenting the results near
1 AU of more complex initiation mechanisms.
There has been significant new physics included in thesolar wind models, including more advanced thermodynamics treatment and the inclusion of Alfvén waves.
There has not been significant work quantifying how
these new additions affect the CME propagation and theresulting structure near 1 AU.
There has been progress towards coupling timedependent magnetic field models with coronal models andheliospheric models. Initiating CMEs by means of magnetofrictional or other self-consistent models based on solar observations or flux emergence may lead the way to a better
physical understanding of CMEs and is also the only way
space weather forecasting could provide information before
the launch of a CME. Further improvements towards thiscoupling are expected in the next few years.

(2021) 8:21

Page 14 of 43

focus of WG 4 was on why forecasts fail and how we
can improve our predictions. This included analyzing
the complications in linking CMEs to ICMEs, usuallyobserved only in situ at 1 AU.
After examination, WG 4 classified the studied events
into three general categories (Webb and Nitta 2017) as
follows:
1. “Textbook” cases in which the complete chain ofwell-observed events is relatively well understoodfrom its solar source, through its heliosphericpropagation, to its geo-effects. These cases involve
forecasts that are successful in a general way.
2. Cases in which there were problems understanding
the complete chain, but which we think we now
understand it. Thus, something was missing in the
chain of a well-observed event but, in retrospect
after analysis, we now know why. These cases usually involve forecasts that failed because the eventswere not geoeffective or were underestimated.
3. Problem cases in which the chain is not complete,
and we still do not understand why.
Fourteen campaign events were discussed and analyzed
by WG 4 (Table 5-1 in Zhang et al. 2021). Figure 9 is an illustration of the first GLE event observed on September 10,
2017, on two planets: Earth and Mars. A detailed description of the event and the modeled geometry, kinematics,
propagation, and interaction of the three CMEs launchedaround 2017-09-10 from their solar origin to their arrivals
at Mars and Earth are given by Guo et al. (2018).
3.2.5 SEP events

3.2.4 Campaign study

3.2.5.1 SEP origin One of the more unusual solar phenomena is the long-duration gamma-ray flares (LDGR
Fs). The prime characteristic of these events is delayed
and prolonged γ-ray (> 100 MeV) emission after the impulsive phase. Recently, the Fermi Large Area Telescope(LAT) observed dozens of LDGRFs. Share et al. (2018)
characterized and catalogued 30 solar eruptive events
observed by Fermi/LAT from 2008 to 2016, referring tothis emission as “late-phase gamma-ray emission”(LPGRE). In all the events studied, Share et al. (2018)
found that the LPGRE is temporally and spectrally distinct from the impulsive phase emission and concluded
that due to the broad range of the LPGRE characteristics
it is unlikely that the mechanism of acceleration of particles by the CME-driven shock alone is able to accountfor the emission in all of the events under study.

The task of ISEST Working Group 4 (campaign events)
was to integrate theory, simulations, and observations
for better understanding of the chain of activity from the
Sun to the Earth for a few carefully selected events. One

3.2.5.2 SEP acceleration Some studies have provided
new support for a significant contributory or dominantrole for flare acceleration of high-energy protons inShiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

Page 15 of 43

Fig. 9 In situ observations of the 2017-09-10 events at Earth (left panels), Mars (f-h), and STA (i–k). a, i The energy-dependent particle flux
(counts/cm2/sr/MeV/sec) measured by GOES and STA. b Count rate of several ground-based neutron monitors with different cut-off rigidities(each neutron monitor data set is normalized to the average value of the selected time range and shifted apart in y-axis). c, h, and j The solar
wind speed (black, left Y-axis (yl)), proton density (blue, right Y-axis (year)), and temperature (red, year) for Earth (OMNI), Mars (MEX), and STA,
respectively. The ENLIL modeled results at three locations are also plotted as dashed lines. d Plots of the Alfvén Mach number (black, yl), plasma(blue, year), and flow pressure (red, year) estimated at Earth. e, k The vector magnetic fields at Earth/STA in Geocentric Solar Ecliptic (GSE) or
spacecraft Radial-Tangential-Normal (RTN) coordinate and negative ENLIL modeled magnetic field strength (dashed line). f The normalized countrate for downward particles stopping in RAD and penetrating RAD with the former/later approximating protons with energies larger than 175/
288 MeV arriving at Mars. g The dose rate recorded in RAD B (silicon) and E (plastic) detectors. Magenta-highlighted areas are the ICME and/or its
associated shock passage at Earth and Mars. Cyan-highlighted areas are high-speed streams (of two different ones) passing Earth and STA during
this period. Vertical solid lines in a, b, f, g, and i indicate the particle onset time at Earth/Mars/STA (taken from Guo et al. 2018)

gradual SEP events, contrary to the generally accepted scenario favoring shock acceleration (e.g., Dierckxsens et al.
2015; Grechnev et al. 2015). Several other recent studies
support the prevailing shock picture for gradual SEP
events, such as the observation of a prompt SEP event atwidespread locations in conjunction with the longitudinal
propagation of a white-light shock (Lario et al. 2016), theSEP source temperatures (Reames 2015), and the hierarchical relationship between the fluence spectra of gradual SEP events and the kinematics of the CMEs.
3.2.5.3 SEP transport The unprecedented orbits of thetwo-spacecraft STEREO mission provided well-separated
observations at 1 AU and allowed to study the longitudinal distribution of SEPs and especially events withextraordinarily wide particle spreads in great detail. The
STEREO mission has also enabled the identification andstudy of some extreme cases of widespread events with
distributions up to 360° around the Sun.
3.2.5.4 SEP compositional results Measurements ofrelative abundances of heavy elements and their isotopic
and ionic charge state composition in SEP events havebeen used in a wide variety of ways to infer critical information about the origins of the seed populations and thephysical conditions under which these populations areproduced. These seed particles are accelerated by CME
shocks or in solar jets and indicate the conditions of
their transport through the solar corona, the interplanetary medium, and out into the heliosphere (e.g., see
Reames 2015; Desai and Giacalone 2016).
3.2.5.5 Progress in SEP theory and modeling Valuable
insight on particle acceleration at coronal shock waves

Shiokawa and Georgieva Progress in Earth and Planetary Sciencehas been recently obtained by studying the evolution of
CME and shocks in the corona, as well as their interaction with underlying magnetic fields and coronalplasma, both through data-driven or analytical modelling, as well as MHD simulations and combinations ofdifferent approaches. New information has been gathered about the relevant parameters for efficient shock
acceleration (such as the Mach number, compression ratios, and geometry of shock waves), the primary acceleration regions along the shock, the role of coronalmagnetic field configuration, and how these factors are
related to the particle spectra observed in space.
The effect of large-scale streamer-like magnetic configuration on particle acceleration at coronal shocks has been
investigated by considering a CME-driven shock propagating through a streamer-like magnetic field (Kong et al.
2017) or from its flank (Kong et al. 2019), i.e., when thestreamer is rotated with respect to the CME propagation
direction. By numerically solving the Parker transport
equation with both parallel and perpendicular diffusion insuch configuration, Kong et al. (2019) found that the primary sources for particle acceleration are located at different regions and vary significantly as the shock propagatesand expands, depending on the particle energy and time.
The well-separated SEP observations with the STER
EO mission have also lent themselves to study the transport of SEPs in more detail. The comparison of multispacecraft observations with results of 2D or 3D models
solving the focused transport equation allowed to study
not only transport along the mean magnetic field but
also perpendicular to it. It was found that the role of efficient transport perpendicular to the mean magnetic
field can eventually be much stronger than expected(e.g., Dresing et al. 2012) and might play an importantrole, among extended injection and acceleration regions,in the longitudinal spreading of SEPs (e.g., Dröge et al.
2014), but also in creating asymmetries in their longitudinal distribution at 1 AU (He and Wan 2015).
An important step taken in SEP transport modelling is
the inclusion of a realistic solar wind background. Wijsen
et al. (2019) used the data-driven EUHFORIA (Pomoell
and Poedts 2018) to generate a background solar wind fortheir SEP transport code. This allows, on the one hand,the study of the effect of solar wind streams on the SEP
propagation and also on adiabatic energy changes. On theother hand, case studies with a realistic background field
will be possible accounting for the effects of transient
structures leading to non-Parker field configurations.
3.2.6 Stream Interaction Regions/Co-rotating Interaction
Regions (SIRs/CIRs)

The evolution of long-lived coronal holes, closely related
to SIRs/CIRs, can be studied in detail using multiple
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imagery. It was found that coronal holes undergo evolutionary patterns revealing a growing and declining phase
where area increases and decreases again over several
solar rotations (Heinemann et al. 2018, 2019). The coronal hole area is found to be well related to the solar
wind speed measured in-situ at 1 AU (e.g., Vršnak et al.
2007; Rotter et al. 2012). With this well-known areaspeed relation, empirical forecasting tools for the “pure”
background solar wind on the basis of coronal hole area
measurements are performed on a regular basis (Vršnak
et al. 2007; Rotter et al. 2012). By understanding thephotospheric and coronal evolutionary characteristics ofcoronal holes, one can aim to gain a better understanding
and in turn improve the forecast of CIRs (Heinemannet al. 2018). The forecasts are found to be most successful
for periods of low solar activity, as during increased solar
activity transient events, such as CMEs, strongly disturb
the rather stable solar wind outflow for several days
(Temmer et al. 2017). As the high-speed solar windstreams emanate from coronal holes which are low
dynamic structures, CIRs can be forecast with longlead times. Based on that, a variety of persistencemodels were developed. Under the assumption of persistence, in situ measurements of the solar windplasma flow from L1 and varying STEREO vantage point
provide a forecast for Earth position with lead times of up
to 27 days (depending on the exact STEREO spacecraft
position). Implementing the actual changes of coronalhole areas (from EUV data) into such simple forecasting
tools can improve the forecast quality (Temmer et al.
2018). Lead times with about 4.5 days could be achieved
when using data from an instrument permanently locatedat the Lagrangian point L5 (60° behind Earth; ESA preparation for the future L5 mission “Lagrange”).
Forecasting solar wind structures in interplanetary
space serves also as important information for analytical
CME propagation models and space weather models.
Therefore, under the Space Situational Awareness
Program of the European Space Agency, forecasting
services using empirical, and numerical models forthe solar wind are available (see http://swe.ssa.esa.int).
As the forecasting/nowcasting quality is still not sufficient for producing reliable space weather alerts, weneed to better understand and closely monitor SIRs/
CIRs. Main aims for the near future are to verify andevaluate background solar wind models, and with that
improve the input for CME propagation models, topredict periodic and recurrent geomagnetic effects
from CIRs more accurately. In general, single eventsare easier to forecast compared to multiple events
covering CME-CME interactions or interactions of
CMEs with CIRs. By better understanding the physics
behind the coronal hole evolution, we may improvetheir forecasting capability. With that we will also

Shiokawa and Georgieva Progress in Earth and Planetary Science

gain more insight in the ejection and acceleration
processes that define high-speed streams. For this we
can exploit data from the NASA mission Parker Solar
Probe (PSP) measuring the near-Sun space and withthat regions where the solar wind actually getsaccelerated.
Though harder to evaluate and forecast, interaction
events between SIR/CIR and CMEs are of special interest. Interaction events can lead to significant increase ingeomagnetic effects when compared to individual eventsof similar strength (e.g., He et al. 2018).
In a recent paper by Jian et al. (2019), physical properties of a large sample of slow-to-fast SIRs were investigated using STEREO-A and -B data. They identified 518
pristine SIRs, of which more than 50% are associatedwith crossings of the heliospheric current sheet (HCS)
and are of slow speeds but higher densities, and of increased dynamic and total pressure compared to those
without HCS. In that respect, HCS-related SIRs can beclassified as more effective in terms of space weather.
The detection and extraction of reliable coronal holeareas from operational solar observations is extremely
important, not only for solar wind forecasting using thearea-speed relation, but also for investigating the magnetic open flux on the Sun. At present, most extraction
methods focus on EUV observation taken by SDO/AIA,SOHO/EIT, GOES/SUVI, and/or STEREO/EUVI. A
multi-wavelength approach was developed by Garton
et al. (2018) in the form of the multi-thermal emission
recognition algorithm CHIMERA. Recently, with thedawn of machine learning, new methods, utilizing theincreased computational performance have also emerged
to provide an additional tool to identify and extract coronal holes (e.g., Illarionov and Tlatov 2018).
Using various techniques, several coronal hole datasets
were gathered (especially for coronal hole areas) that are
freely available. Automatically created SPOCA boundaries of coronal holes are available via the Heliophysics
Events Knowledgebase (HEK: https://www.lmsal.com/
hek/index.html), and the automated coronal hole detection and extraction using three SDO/AIA wavelengths(171, 193, 211 Å) CHIMERA is available via SolarMonitor (https://www.solarmonitor.org/) and an extensive,
manually checked, coronal hole catalogue covering the
SDO-era (2010-2019) created using CATCH is available
via the VizieR catalog service (http://cdsarc.u-strasbg.fr/
viz-bin/cat/J/other/SoPh/294.144). VizieR, the CDS catalog service, provides the most complete library of published astronomical catalogs (currently, 20391)—tables
and associated data—with verified and enriched data
(DOI: 10.26093/cds/vizier).
To improve solar wind models and to ensure accurate
space weather forecasting, the solar wind models have to
be tested and validated. The validation of solar wind(2021) 8:21

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models is done by comparing the simulation results within situ measurements.
The performance assessment of the EUHFORIA solarwind model was analyzed by Hinterreiter et al. (2019).
The solar wind was modeled rather well for times ofsolar minimum but not during increased solar activity.
In a study by Lee et al. (2009), the heliospheric models
ENLIL/MAS and ENLIL/WSA were compared with insitu measurements from ACE and Wind (time range:
2003–2006). They found that the model results givelower densities for faster solar wind fully agreeing withthe solar wind momentum flux constancy.
3.2.7 Forecasting CMEs

The lack of critical observations (e.g., no routine observations of the magnetic field in the corona) and limitations in theory and models (e.g., idealized initial andboundary conditions) is currently not allowed to predict
when a CME would occur. However, thanks to advancesin our observational knowledge (e.g., new observations
from STEREO, Hinode, SDO, IRIS), and in modeling(e.g., increase of realism in models, data-constrained anddata-driven models) and in analysis and forecasting techniques (e.g., use of advanced statistical tools and machine learning methods) significant progress in our
understanding and eventual prediction of CMEs has
been achieved over the last decade.
Tziotziou et al. (2012) found that helicity and magnetic
free energy thresholds of ~ 2 × 1042 Mx2 and ~ 4 × 1031
erg separate eruptive with non-eruptive ARs. Magnetic
twist (Tw) (i.e., number of turns of field lines around amagnetic axis) of magnetic field lines is another parameterthat is extensively used in CME onset studies. Magnetic
twist is an integral part of magnetic helicity discussed
above, and comparison of its properties/distribution in the
pre-eruptive/eruptive configurations in the solar atmosphere and at 1 AU supplies important physical clues about
CMEs (Wang et al. 2016).
The problem of predicting major CMEs could be mitigated to predicting major flares. Recent reviews on flare
forecasting, including machine-learning schemes, can befound in Leka et al. (2019) and Park et al. (2020). Major
conclusions from their extensive benchmarking of alarge number of methods currently used in flare forecasting are that numerous such methods do better thanclimatology, no method clearly outperforms the others,
and consideration of prior flare history improves thecorresponding skill scores.
Machine learning has been used directly in CME predictions. Bobra and Ilonidis (2016) applied a Support
Vector Machine classification scheme to 18 parameters
derived from HMI vector magnetograms for more than3000 ARs and found that only 6 amongst these parameters are sufficient to separate erupting and non-eruptingShiokawa and Georgieva Progress in Earth and Planetary Science

ARs within 24 h from the corresponding measurements.
These parameters (e.g., mean gradient of the horizontal
magnetic field, mean current helicity, mean twist parameter, etc) are intensive (i.e., do not depend on the AR
size but are spatial averages) and not extensive (i.e.,
dependent on the AR size and corresponding to spatialsums). Guennou et al. (2017) by means of MHD analyzed a set of eruptive and non-eruptive MHD simulations and found, in agreement with Bobra and Ilonidis(2016), that intensive parameters are more relevant toeruptivity.
The availability of multi-viewpoint STEREO imaging
observations allowed to monitor a number of modulations that CMEs experience in the corona and in the
inner heliosphere in terms of deflections and rotations.
CME rotations as well as deflections in the corona aresimultaneously addressed by the ForeCAT model of Kay
et al. (2015). The model has been applied to several
CMEs, and it was able to reproduce the deflections androtations that the CMEs undergone as derived from theanalysis of the corresponding STEREO observations.
The predicted deflections and rotations exhibit significant sensitivity on the input parameters and theemployed background models.
Predicting the magnetic field distribution of CMEs/
ICMEs is of highest importance in heliophysics, as extended intervals of intense southward magnetic fields
are a necessary condition for inducing geomagnetic
storms. A thorough account of the state-of-the art inthis important problem was recently given in Vourlidas
et al. (2019).

(2021) 8:21

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from more than 30 countries. After the end of CAWSESII program, the action transcended from its original 1year-campaign scheme and was included in the new
SCOSTEP program VarSITI as one of the working
groups of the ISEST project.
3.2.9 Highlights of contribution from young scientists to the
ISEST/Minimax24 project

Many young scientists have been glowing to contributeto the ISEST/Minimax24 project. Thalmann et al. (2016)
reported plasma and magnetic environment of a particular flare signature and coronal magnetic field based on
combined SDO, RHESSI, and STEREO data. Chenget al. (2014) made a tracking of magnetic flux rope frominner to outer corona. Sindhuja and Gopalswamy (2020)
investigated properties of flux ropes in CME near theSun. Shen et al. (2014) also investigate evolution of 12
July 2012 CME from Sun to Earth. Kay et al. (2015,2016, 2017) studied global trends of CME deflections,evolution of CME, and predictability of the magnetic
field of earth-impacting CMEs, respectively. Shen et al.
(2017, 2018) investigated geoeffectiveness of interplanetary coronal mass ejection (ICME) statistically from 1995
to 2014 and for a particular ICME event on September
8, 2017. Dumbović et al. (2018) developed an analyticalmodel of Forbush cosmic-ray decreases caused by flux
ropes in the solar wind associated with interplanetary
coronal mass ejection (ICME). Dissauer et al. (2018a, b,2019) extensively investigated coronal dimmings associated with flares and CMEs.

3.2.8 Minimax24 non-flare target

3.3 Project SPeCIMEN: Specification and Prediction of the
Coupled Inner-Magnetospheric Environment

The aim of the ISEST/MiniMax24 non-flare target service is to monitor potentially geoeffective phenomena
which are not related to solar flares and to email alerts.
This service, provided daily by the observer on duty, wasfirst established in the scope of the SCOSTEP/CAWSES
II “MiniMax24 Campaign” in 2013, which was declared
as the year of “MiniMax24” to note that, even though
the Sun is going through activity maximum conditions,the activity is rather low. The goal of the action was tounderstand and explain the current behavior of the Sun
and its potential impact on human society and Earth’s
space environment through year-long scientific and outreach activities. The campaign team counted 37 institutions from 17 countries focused on the solar-terrestrial
observations of solar eruptive events through the MaxMillenium program of solar flare research (http://solar.
physics.montana.edu/max_millennium/) as well as coronal holes, filaments, and CIRs (i.e., non-flare related
phenomena) through the newly established email alert
service. By the end of the year of “MiniMax24,” MiniMax24 email list reached more than 140 participants

The coupled inner-magnetospheric environment has
been focused by the project “Specification and Predictionof the Coupled Inner-Magnetospheric Environment”(SPeCIMEN). The goal and objectives of this project
were the quantitative prediction and specification of the
Earth’s inner magnetospheric environment based on
Sun/solar wind driving inputs. Comprehensive review on
the achievements of this project is provided by Kanekal
and Miyoshi (2021). Here, we briefly review the highlights of the scientific results obtained on this topic.
Figure 10a shows basic configuration of energetic electrons and ions and the waves that interact with theseparticles in the inner magnetosphere around the earth.
The energetic electrons and ions rotate around the Earthdue to curvature and gradient of ambient magnetic fieldwith a time scale of minutes to hours and interact withextremely low frequency (ELF) and very low frequency(VLF) waves (electron cyclotron waves) at frequencies of~kHz, ultra-low frequency (ULF) (Pc1) waves (ion cyclotron waves) at frequencies of ~Hz, and ULF (Pc4-5)
waves at frequencies of ~mHz. These energetic particles

Shiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

Page 19 of 43

Fig. 10 Schematic picture of the energetic electron and ions and waves that interact with these particles in the inner magnetosphere around theearth. a Top view from above the north pole, and b side view from dusk to dawn

and waves propagate along the geomagnetic field line
and cause aurora and ionization of the atmosphere, as
shown in Fig. 10b.
During the VarSITI program, two major satellite projects had been in actively operated to investigate theinner magnetosphere, i.e., Van Allen Probes (also calledas Radiation Belt Storm Probes) (2012–2019, Kirby et al.
2013) and Energization and Radiation in Geospace (ERG,
also called as Arase) (2016-, Miyoshi et al. 2018). The Time
History of Events and Macroscale Interactions during Substorms (THEMIS) satellites (2007-, Angelopoulos 2008)
have also been in operation throughout the VarSITI Program, and Magnetospheric Multiscale (MMS) satellites(2015-, Burch et al. 2016) was newly launched. The THEM
IS and MMS can provide information of the outer magnetosphere, which is the boundary condition of the energization of plasma in the inner magnetosphere. Recently,
Cubesat measurements also contribute to the understanding of radiation belt precipitation at low-Earth orbit (e.g., Li
et al. 2015; Kanekal et al. 2019).
Ground network instruments have been deployed extensively at subauroral latitudes by the PWING projectsince 2016 (Shiokawa et al. 2017). PWING stands forstudy of dynamical variation of Particles and Waves in
the INner magnetosphere using Ground-based network
observations. Modeling efforts to cover the inner magnetosphere has also been made, such as Block-AdaptiveTree-Solar-wind-Roe-Upwind-Scheme with Comprehensive Ring Current Model (BATSRUS/CRCM, Glocer
et al. 2013) and Ring current–Atmosphere interaction
Model (RAM, Jordanova et al. 2010). These extensive

observation networks and advanced modeling efforts
make a golden era of research for the inner magnetosphere during the VarSITI program.
Figure 11 shows an example of 1-year electron flux
variation in 2013 at energies from 46 keV to 1.553 MeV
in the inner magnetosphere observed by the Van Allen
Probes (Reeves et al. 2016). The vertical axis is the Lvalue, which is the radial distance from the Earth with aunit of Earth’s radius. We can see dynamic variation ofelectron fluxes in the inner magnetosphere. The amplitude of the variation reaches a few orders of magnitudes.
The enhancements of electron fluxes clearly correlatedwith solar wind speed enhancements and decreases of
Dst index (geomagnetic storms). The high-flux regions
are separated into two regions around L ~ 4–6 and L <2, forming outer and inner radiation belts, respectively.
Clear differences can be also seen in the electron behavior at different energies and from event to event. Basically, no significant electron fluxes are seen at energies
above 1 MeV in the inner belt at L value less than 3, as
newly found by Fennel et al. (2015), while the inner belt
clearly appears at energies below 459 keV. At further
high energies, Van Allen Probes also discovered sharp
inner boundary for the ultrarelativistic (energies higher
than 5 MeV) electrons in the Earth’s radiation belts(Baker et al. 2014). A comprehensive review of the results obtained by the Van Allen Probes mission has been
provided by Baker et al. (2018).
The ERG satellite was launched in December 2016and has provided several interesting observations particularly related to the wave-particle interactions in theShiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

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Fig. 11 A multi-energy view of flux as a function of L shell (distance from the Earth in unit of Earth radius) and time from the Van Allen Probes
mission for 2013. a–d Background-corrected electron fluxes measured by MagEIS, e electron fluxes measured by HOPE, f solar wind speed, g IMF
Bz, and g Dst index. Clear differences can be seen in radiation belt electron behavior at different energies and from event to event (taken fromReeves et al. 2016)

inner magnetosphere. Figure 12 shows one-to-one correspondence between ELF/VLF chorus wave elements(panel c) that have a time scale of less than 1 s observed
by ERG with electrons at energies of kilo-electronvolts
that causes visible flush aurora observed by ground an
all-sky camera (panels b and f) (Ozaki et al. 2019). ERG
and the ground all-sky camera were nearly on the same
geomagnetic field line. Clear one-to-one correspondence
can be seen at four ELF/VLF chorus wave elements inpanel (c) with the four auroral flashes in panel (f) at ~13:01:28 UT and ~ 13:01:32 UT. This correspondence
indicates that the observed ELF/VLF chorus waves scatter electrons along the magnetic field line to cause precipitation of the electrons and the flash aurora. Kasahara
et al. (2018) did show one-to-one correspondence between ELF/VLF chorus waves and electron fluxes in theloss cone, which is the direct evidence of pitch-angle
scattering of keV-energy electrons by ELF/VLF chorus
waves. On the other hand, Teramoto et al. (2019)provided evidence of wave-particle interaction between
ULF (Pc4-5) waves at frequencies of mHz with energetic
electrons through drift resonance based on multisatellite coordinated observation by the Van Allen
Probes and ERG satellites. More comprehensive results
obtained from the ERG mission have been provided by
two special issues in Earth Planets and Space in 2017and in Geophysical Research Letters in 2018.
In the objectives of SPeCIMEN (specification andprediction), the modeling takes the part of quantitative prediction of the Earth’s inner magnetosphericenvironment. BATSRUS/CRCM model (Glocer et al.
2013) provides global response of the outer and innermagnetosphere to the solar wind. RAM simulation(Jordanova et al. 2010, 2012) provides distribution ofwhistler-mode chorus waves that contribute acceleration and loss of the radiation belt electrons.
Geomagnetic Environment Modeling System for Integrated Studies (GEMSIS)-Ring Current and Radiation

Shiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

Page 21 of 43

Fig. 12 Coordinated ground and ERG (Arase) observations. a Illustration of conjugate observations from the ground network of the PWING
project and the ERG satellite. Earth in panel a is mapped using NASA image. All rights reserved. b All-sky EMCCD snapshot observed at Gakona in
Alaska at 13:01:28 UT, 30 March 2017. Dotted lines indicate the spacing of geographical latitudes and longitudes at 1° and 2° intervals. The yellow
frame indicates the auroral region that is focused on in this study. The green diamond symbol indicates ERG’s footprint at the time ofobservation. c, e The dynamic spectrum, wave-normal angle with respect to the geomagnetic field line, and the waveform of large-amplitude
chorus elements observed by ERG near the magnetic equator. f North to South cross-section (keogram) of auroral emissions with a time shift of− 0.24 s (taken from Ozaki et al. 2019)

Belt models reproduce interaction of Pc5 magnetic
pulsations with relativistic electrons (Kamiya et al.
2018). Not only by these physical models, artificial
intelligence has been introduced for reconstruction of
the inner magnetosphere dynamics. Figure 13 showsneural network reconstruction of the global plasma
density as a function of L and MLT by Bortnik et al.
(2016), using measurements by three THEMIS satellites between 2008 and 2014.
3.3.1 Highlights of contribution from young scientists to the
SPeCIMEN project

More than ten active young scientists contributed to theresearches of the SPeCIMEN project and wrote articles
for highlight of young scientists in the VarSITI newsletter. For studies of whistler mode waves which possibly
accelerate relativistic electrons, Li et al. (2014) haveshown acceleration of radiation belt electrons by chorus
waves during the March 17, 2013, storm based on observations by the Van Allen Probes satellites. Nishimura
et al. (2015) reported chorus intensity modulation driven
by time-varying field-aligned low-energy plasma observed by the Time History of Events and MacroscaleInteractions during Substorms (THEMIS) satellites. Gabrielse et al. (2014) reported statistical characteristics ofparticle injections, which can be a source of the waves,in the equatorial plane of the magnetotail using THEM
IS satellites. Martinez-Calderon et al. (2015a, b, 2016,2019) reported ground and conjugate satellite observations of VLF chorus waves to find their propagation
characteristics from the inner magnetosphere to theground. Douma et al. (2018) showed comparison of relativistic electron microburst activity seen by SAMPEX
with ground-based wave measurements at Halley, Antarctica, and concluded that whistler mode chorus waves
are, most likely, the primary drivers of relativistic electron microbursts. Jones et al. (2017) and Greeley et al.
(2019) reported secular drift of South Atlantic anomaly
during solar cycle 22-24 and quantify the contributionof relativistic electron microbursts to the global electron loss in the radiation belts, based on long-term datafrom the SAMPEX satellite. Shirokov et al. (2017) and
Shirokov (2018) investigated receiving antenna characteristics to measure quasi-static whistler-mode waves
including chorus emissions. An et al. (2019) investigated three seemingly different nonlinear wave structures originated from the same nonlinear electron
trapping process by whistler-mode chorus waves andpointed out that the ratio of the Landau resonant velocity to the electron thermal velocity controls theShiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

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Fig. 13 Neural network reconstruction of the global plasma density as a function of L and MLT. a The SYM-H index relative to 9 March 2008
00:00 UT. The red vertical dashed lines correspond to the times of the snapshots shown in the 12 panels beneath. The common color scale
indicating electron density in electrons per cubic centimeter is shown on the right, and the dashed line in b–m represents the 50 el/cm3
contour. The entire simulation period is outside the training interval (i.e., out of sample) (taken from Bortnik et al. 2016)

generated type of nonlinear wave structures. Píša et al.
(2015, 2016) investigated Langmuir waves observed upstream of Saturn’s foreshock and bow shock observed
by Cassini, which also has some implications on highenergy plasma acceleration in the inner magnetosphere.
For the magnetosphere-ionosphere coupling in the
inner magnetosphere and ionospheric processes,
Thomas et al. (2015, 2016, 2019) investigated magnetic
field variations associated with Pi2 and ionosphericcurrent observed by the CHAMP and Swarm satellites
just above the ionosphere and on the ground to show
their characteristic in and near the ionosphere.

McGranaghan et al. (2015a, b, 2016a, b) extensively investigated high-latitude ionospheric conductivities basedon satellite observations and developed a model of thehigh-latitude ionosphere to reconstruct its electrodynamic variations. Gokani et al. (2015) reported
lightning-associated whistlers at very low latitudes (L =1.08), suggesting ducted mode of propagation of thesewaves near the equator. McCormick et al. (2018) proposed spatial and temporal monitoring of the D-region
ionosphere using lightning-induced broadband sfericmeasurements. These ionospheric topics also havestrong relation with the ROSMIC project.

Shiokawa and Georgieva Progress in Earth and Planetary Science

3.4 Project ROSMIC: Role Of the Sun and the Middle
atmosphere/thermosphere/ionosphere In Climate

The goals and objectives of the Project “Role of the Sun
and the middle atmosphere/thermosphere/ionosphere in
Climate (ROSMIC)” was to understand the impact of
the Sun on the terrestrial middle atmosphere, lower
thermosphere, and ionosphere and Earth’s climate andits importance relative to anthropogenic forcing overvarious time scales from minutes to centuries. A comprehensive review on the achievements of this project isprovided by Ward et al. (2021). Here, we briefly review
the highlights of the scientific results obtained on this
topic during the VarSITI program.
The topic of ROSMIC can be divided to (1) couplingfrom above, (2) coupling from below, and (3) observation of long-term trends. The coupling from above
comes from (1a) solar radiation in various wavelengths
from X-ray, ultraviolet, and visible wavelengths, (1b)solar energetic particles (SEP) or solar proton events(SPE) and (1c) magnetospheric energetic particles(MEP). The effects of (1a) are often divided into total
solar irradiance (TSI) and spectral solar irradiance (SSI).
SEP and MEP are called as energetic particle precipitation (EPP).

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3.4.1 Coupling from above

Figure 14 shows an example of the EPP effect on the middle atmosphere observed by the three different satellites
for three different magnetic storms and in superposed
epoch analysis based on satellite-based measurements by
GOMOS, SABER, and MLS (Andersson et al. 2014). Boththe particular storm events in Fig. 14a–c as well as superposed epoch analysis in Fig. 14d–i, there are significant
ozone depletions at the middle atmosphere with the maximum loss of ozone from 10 to 30 % at altitudes between
70 and 78 km after the storms. This indicates a significant
effect of ozone loss by EPP in the middle atmosphere.
Funke et al. (2014) have shown intrusions of EPP-caused
nitric oxide (NOy) into the stratosphere with a time scaleof several months, based on measurements by Michelson
Interferometer for Passive Atmospheric Sounding (MIPAS) on board the Envisat satellite. This gradual descent of
NOy from the mesosphere to the middle and lower stratosphere contributes to the catalytic destruction of ozone.
Efforts to quantify the total forcing of EPP to the atmosphere have also been made during the VarSITI interval.
Isono et al (2014) reported NO column density enhancement 1–5 days after the commencement of geomagnetic
storms based on ground-based millimeter-wave

Fig. 14 Magnitude of the short-term EEP effects on mesospheric ozone. a–c O3 anomalies (%) for selected EEP events in the Northernhemisphere and in the Southern hemisphere derived from GOMOS (a), SABER (b), and MLS (c) observations. Black dashed lines: EEP event startend end; red dashed lines: SPE event start end; black numbers: daily mean electron count rates (ECRs); red numbers: 410 MeV pfu. d–i
Superposed epoch analysis for EEP events with daily ECR 4150 (counts s1) showing ozone anomalies (%) and ECR (black lines) in the Northernhemisphere (d, f, h) and in the Southern hemisphere (e, g, i). White numbers: O3 loss at different altitudes (taken from Andersson et al. 2014)

Shiokawa and Georgieva Progress in Earth and Planetary Science

spectroscopic radiometer at Syowa Station in
Antarctica.
Together with these new measurements of EPP effects
on the atmosphere, efforts to model the global effects
have also been made. Andersson et al. (2018) combined
the Whole Atmosphere Community Climate Model(WACCM) together with the EPP forcing model developed by van de Kamp et al. (2016) for the 6th phase of
the Coupled Model Intercomparison Project (CMIP6)(Matthes et al. 2017). They concluded that mediumenergy (30 keV–1 MeV) electrons (MEE) can enhance
the stratospheric ozone response to solar activity by afactor of 2. Thus, the EPP forcing can be significant for
the long-term stratospheric ozone variation, implying
their effects on the thermal structure of the middle andlower atmosphere.

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Not only the EPP effect but also understanding of theeffects of irradiance variation of the Sun (total solar
irradiance (TSI) and spectral solar irradiance (SSI)) on
the atmosphere has also been progressed during the
VarSITI interval. This part will be visited in the Section 3.3.3 below.
3.4.2 Coupling from below

During the CAWSES and CAWAES-II interval, penetration of sound waves, gravity waves, tides, and planetary
waves beyond the mesopause region into the thermosphere and their interaction with the ionospheric plasma
had been newly recognized (e.g., Vadas and Crowley
2010; Goncharenko and Zhang 2008; Oberheide et al.
2015). During VarSITI interval, further studies on therole of these waves in the thermosphere and ionosphere

Fig. 15 a Height–latitude section of zonal and diurnal-mean zonal wind obtained by EXP1 (the application of the Lindzen’s gravity-wave
parameterization scheme (only below 100 km height)). Data are averaged from 1 to 30 June. Contour intervals of black lines are 10 ms-1. Negativeand positive values are eastward and westward winds, respectively. b As in a, except for the application of the Yiğit et al. (2008)’s
parameterization scheme in the whole atmosphere (EXP2). c Difference of the zonal wind between EXP1 and EXP2 (EXP2–EXP1). Contour
intervals are 5 ms-1 (taken from Miyoshi and Yigit 2019)

Shiokawa and Georgieva Progress in Earth and Planetary Science

have been made. Yiğit et al. (2016) reviewed the effectsof these waves on the structure of atmosphere, motivated by the IAGA/ICMA/SCOSTEP Workshop on Vertical Coupling in the Atmosphere–Ionosphere System.
Figure 15 shows the height-latitude profiles of zonal
winds without gravity wave forcing above 100 km(Fig. 15a) and with the forcing modeled by Yiğit et al.
(2008) (Fig. 15b) and their differences (Fig. 15c). The
gravity wave dissipation and their forcing to the mean
zonal wind can affect the magnitude of the zonal-mean
zonal wind and provide a deceleration mechanism in themesopause region and lower thermosphere.
New observations have been developed regarding connection from lower to upper atmosphere during the VarSITI program. Gravity wave generation, propagation, anddissipation impact to the atmospheric dynamics have beenreported in the special issue of “ACP (2017) sources,
propagation, dissipation and impact of gravity waves” in
the Atmospheric Chemistory and Phycis (https://acp.
copernicus.org/articles/special_issue899.html) in relation
to the German Role Of the Middle atmosphere In Climate(ROMIC) project (2013–2017). For example, Baumgarten
et al. (2018) reported a 10-day continuous lidar soundingof temporal variability of tidal and gravity waves, indicating the importance of such continuous high-resolution
measurements to detect interaction phenomena between
waves for improving parametrization schemes of gravity
waves in general circulation models. The ROMIC project
has extended in 2018 for additional 3–4 years in Germany.
New Program of the Antarctic Syowa MST/IS radar(PANSY) has been operational (Sato et al. 2014), and Interhemispheric Coupling Study by Observations and Modeling (ICSOM) campaigns (http://pansy.eps.s.u-tokyo.ac.
jp/icsom/) have been carried out in association with VarSITI to understand dynamical variation of the whole atmosphere during stratospheric sudden warming (SSW).
Liu (2016) have shown possible influences of ENSO andQBO in the neutral density variations in the thermosphereusing a 46-year-long dataset of the thermospheric density
during 1967–2012.
Efforts of model extension to the thermosphere andionosphere have also been done. Liu et al. (2018) havedeveloped the NCAR Whole Atmosphere Community
Climate Model with thermosphere and ionosphere extension (WACCM-X). This new model reproduces thermospheric composition, density, and temperature andionospheric plasma density and ExB drifts including prereversal enhancement in the equatorial region. Pedatella
and Liu (2018) noted using the WACCM-X simulations
that the effects of lower atmosphere variability should be
included to accurately capture smaller-scale features of
the upper atmosphere response to geomagnetic storms.
Shinagawa et al. (2017, 2018) successfully reproduced
global distribution of sporadic E layers and daily and(2021) 8:21

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seasonal variation of equatorial spread F, respectively,
based on the Ground-to-topside model of Atmosphereand Ionosphere for Aeronomy (GAIA) model (Jin et al.
2011).
3.4.3 Long-term trend

The long-term trend has been extensively studied under
the working group 3 of the ROSMIC project. Laštovička(2017) provided a review of recent progress in trends inthe upper atmosphere, together with the special issue ofthe long-term changes and trends in the upper atmosphere (https://www.sciencedirect.com/journal/journalof-atmospheric-and-solar-terrestrial-physics/vol/163/
suppl/C). Figure 16 shows linear temperature trends
from the 25-year data set measured by a sodium lidar at
Fort Collins (41° N, 105° W) in the USA reported by She
et al. (2015). By removing strong warming effect by Mt.
Pinatubo eruption in 1991, they concluded a cooling
trend starting from an insignificant value of 0.64 ± 0.99
K/decade at a 85-km altitude, increasing to a maximumof 2.8 ± 0.58 K/decade between 91 and 93 km, and thendecreasing to a warming trend above 103 km. Berger
and Lübken (2015) reported trends in the polar mesospheric clouds (PMCs) which respond to long-termchanges in mesospheric temperatures at northern highlatitudes for the summer in 1961–2013. They suggested
that the thermal conditions near 83 km height, with acooling of − 0.58 ± 0.32 K/decade, mainly determine
trends in the PMCs, whereas cooling at lower heights,
induced by stratospheric ozone, controls to a large extent the long-term behavior of PMC altitudes. Lübken
et al. (2018) used model simulations over 138 years to

Fig. 16 Linear temperature trend from the quarter century data set
with 11- and 7-parameter analyses, respectively, denoted as F11P(90-14_Avg) in black solid circles and F-7P(90-14_Avg) in black
open circles. Shown for comparison are those data published basedon an 18-year data set denoted as F-11P(90-07) in red solid squares
and F-7P(90-07) in open red squares (taken from She et al. 2015)

Shiokawa and Georgieva Progress in Earth and Planetary Sciencestudy the impact of increasing CO2 and H2O on the development of noctilucent clouds (NLCs) on centennial
time scales. They concluded that NLC presumably
existed centuries earlier, but the chance to observe themby the naked eye was extremely small before the twentieth century, whereas it is likely to see several NLC perseason in the modern era.
The above studies of long-term trends are motivatedto identify the anthropogenic effects, i.e., the effect of increasing greenhouse gases, on the mesosphere andthermosphere. On the other hand, solar cycle effects on
the upper atmosphere have also been evaluated during
the VarSITI interval. Yeo et al. (2017) developed a newempirical reconstruction model of total and spectral
solar irradiance (TSI and SSI) variability based on thelinear combination of solar activity indices. Mitchell
et al. (2015) used historical simulations of the CMIP-5
model to evaluate tropospheric signatures of solar cycle
variations through the stratosphere. Thiéblemont et al.
(2015) reported synchronization of solar forcing withdecadal variability in North Atlantic climate, based on
two 145-year experiments of the fully coupled oceanatmosphere model CESM-WACCM3.5 (Marsh et al.
2013) up to a 140-km altitude with interactive chemistry.
Cullens et al. (2016) reported the influence of the 11year solar cycle on gravity waves and the wave-driven
circulation, using the Whole Atmospheric Community
Climate Model (WACCM). The changes in gravity wave
dragged during the solar maximum modify the waveinduced residual circulation and contribute to the warming of ~ 1–4 K in the mesosphere and lower thermosphere. Amorim et al. (2011), Takeo et al. (2017) and
Tsuchiya et al. (2019a, 2019b) reported clear anticorrelation between 11-year solar activity and nighttime
medium-scale traveling ionospheric disturbances (MSTI
Ds) at middle and subauroral latitudes. This anticorrelation can be explained by the linear growth rate ofionospheric Perkins instability, responding to the solarcycle variation of neutral-plasma collision frequency inthe bottom-side ionosphere. This negative correlation ofnighttime MSTIDs at middle latitudes to solar cycle is aclear contrast to the positive correlation of post-sunset
plasma bubbles in the equatorial ionosphere (e.g.,
Nishioka et al. 2008).

(2021) 8:21

Inter-Comparison Project (CMIP5). Wenzel et al. (2016)
reported development of global ionospheric flare detection system (GIFDS) using very low frequency (VLF)
radio transmissions in the northern hemisphere. Yadav
et al. (2016) reported the impact of the St. Patrick’s Day
storm on March 15, 2017, on the evolutionary pattern ofequatorial ionization anomaly over the Indian longitudes
using high-resolution TEC maps. Karan et al. (2016),
Karan and Pallamraju (2017) reported electrodynamic
influence on the diurnal behavior of oxygen dayglow andlongitudinal variations of equatorial thermosphericwaves seen in the dayglow observed from the ground.
rom low to upper atmosphere, Laskar et al. (2014) and
Laskar and Pallamraju (2014) investigated responses ofequatorial electrojet (EEJ) strength, total electron content (TEC), and oxygen dayglow in the Indian sector to
the sudden stratospheric warming and solar activity.
Trinh et al. (2015, 2016, 2018) reported a comprehensive
global observation of gravity waves in the middle atmosphere and thermosphere using several low-altitude satellites, providing evidences of strong vertical couplingfrom lower to middle and upper atmosphere throughgravity waves on global scale. Gao et al. (2015) reported
double-layer structure in hydroxyl (OH) dayglow measured by the Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics (TIMED) satellite. Stober et al.
(2014, 2018), Stober and Chau (2015) investigated neutral density variation using meteor radar echoes in themesosphere and developed novel technique to improvewind measurements in the mesosphere and lower
thermosphere using a multi-static multi-frequency meteor radar.

3.4.4 Highlights of contribution from young scientists to the
ROSMIC project

Many young scientists have been newly joined in thefield of the upper atmosphere during the VarSITI interval and contributed to the ROSMIC project. From space
to the atmosphere, Misios et al. (2015) investigate thetroposphere response to the 11-year solar cycle based on
the ensemble simulations of the twentieth century climate performed in the fifth phase of the Coupled Model

Page 26 of 43

Fig. 17 VarSITI logo designed by Ms. Kadowaki of STEL,
Nagoya University

Shiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

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For the use of GNSS positioning, Macalalad et al.
(2014) evaluated performance of different ionosphericmodels in single-frequency code-based differential GPS
positioning. Seif et al. (2015, 2017, 2018) investigateddaytime ionospheric scintillations at equatorial latitudes
and their relationship with the sporadic E layer and thegradient-drift instability.

Panel 3 of CAWSES-II Symposium in Nagoya, Japan(November 18–22, 2013), was made by Ms. Kadowaki of
STEL, Nagoya University (Fig. 17).
In the following subsections, we describe various implementation activities of VarSITI. Table 1 summarizes
some representative numbers of these activities.

4 Implementation of the VarSITI program
The VarSITI program officially started on January 13,
2014. It was announced in a press release by the SCOSTEP’s Bureau and in information for media in various
countries provided by members of the SCOSTEP community. A video was prepared highlighting the scientificobjectives of VarSITI (https://www.youtube.com/
watch?v=couR4MyxNPY).
A competition was announced for the VarSITI program’s logo. The logo, selected by the voting during the

4.1 Website

The program’s website (http://varsiti.org/) contains information about VarSITI’s projects and members,
VarSITI-related meetings with lots of freely available
presentations, journal articles and books, and links tonumerous resources including real time data, data basesof space-borne and ground-based measurements,
models, visualization, and forecasting tools. After theend of the VarSITI program, the website remains operational. It is maintained by Dimitar Danov from theTable 1 Some representative numbers of the VarSITI implementation activities
VarSITI website (http://varsiti.org/)
number of website visits in 2014-2018~180,000

VarSITI mailing list
category

number of regsitered addresses

number of countries

VarSITI_all

1116

72

SEE

635

63

ISEST/Minimax24

744

67

SPeCIMEN

620

60

ROSMIC824

67

category

number of articles

number of countries

articles60

41highlight of young scientists

49

VarSITI Newsletter (total 21 issues)meeting reports

85

short news

24

VarSITI finantial support
meetings

64

database construction

16

campaign

1

intedisciplinary project

1

VarSITI-related special issues in journals
more than 8 special issues in Journal of Geophysical Research, Earth Planets and Space, Journal of Atmospheric and Solar-Terrestrial Physics, Solar
Physics, and Progress in Earth and Planetary Science
VarSITI-related databases (http://varsiti.org/ → Resources → Databases)
databases

124

data analysis & visualization tools

10

Capacity Building Schools during the VarSITI interval
Schools organized by the VarSITI co-chairs

5 schools at Nigeria (x2), Indonesia (x2), and Russia

schools organized by SCOSTEP

3 schools at Peru, India, and Azerbaijan

Shiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

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Fig. 18 Home page of the VarSITI website

Space Research and Technology Institute at the Bulgarian Academy of Sciences (Fig. 18).
For the duration of the program, the website had been
visited more than 180 thousand times, as shown in
Fig. 19.

1.
2.
3.
4.
5.

SEE: 635 members from 63 countries
ISEST MiniMax24: 744 members from 67 countries
SPeCIMEN: 620 members from 60 countries
ROSMIC: 824 members from 67 countries
The whole VarSITI program: 1116 members from72 countries.

4.2 Mailing lists

Five mailing lists were compiled and regularly updated:for each of the four projects and an integrated list for all
projects. They contained the names and e-mail addressesof the scientists who have expressed their interest to
participate in the program and to whom announcements
were sent related to activities of VarSITI and its
projects. The statistics by the end of the program is
as follows:

4.3 VarSITI newsletter

VarSITI newsletter (Fig. 20) had been published with 4
issues per year: a total of 21 issues until May 2019. The
newsletter had four categories of the articles:
1. Articles on new projects, campaigns, groundobservations, satellite observations, modeling,
workshop/conference/symposium reports, etc.;

Fig. 19 Monthly visits to VarSITI web site: green—total visits; blue—unique visits

Shiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

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Fig. 20 Examples of VarSITI Newsletter issues

2. Highlights on young scientists based on the young
scientist’s own work related to VarSITI;
3. Short news: announcements of campaigns,
workshops, etc.;
4. Meeting schedules.
Since the start of the VarSITI program in January
2014, 60 articles, 49 highlights of young scientists, 85
meeting reports, and 24 short news from 41 countries
were published in these 21 newsletter volumes.
The newsletter was distributed online and in printed
form at international meetings. The full archive is available on VarSITI web site (http://varsiti.org/).

4.4 Financial support

An important tool for implementing VarSITI program was
the SCOSTEP’s financial support provided annually for theorganization of meetings, creation of databases, and campaigns. The grants were distributed by the VarSITI co-chairfollowing recommendations and endorsements by the VarSITI projects’ co-leaders. The grants were associated withthe condition links to materials to be added to the VarSITI
website and to be then freely available to all in the VarSITI
community (e.g., presentations, virtual observatories, press
releases, publications, etc.).
For the 5-year duration of the VarSITI program, we
have organized or supported the following:
1. 64 meetings or sessions, including the three
VarSITI General Symposia: VarSITI2016,
VarSITI2017, and VarSITI2019
2. 16 databases
3. 1 campaign
4. 1 interdisciplinary project

4.5 VarSITI-related special issues in journals

Related to the above meetings organized for VarSITI
and its projects, several topical/special issues have been
published in international journals. The representative
issues are listed as follows.
(1) Special section on “Variability of the Sun and Its
Terrestrial Impact—VarSITI” in Journal ofGeophysical Research—Space Physics (preface: Hu
2015): https://agupubs.onlinelibrary.wiley.com/doi/
toc/10.1002/(ISSN)2169-9402.VarSITI1(2) Special issue on “Global Data Systems for the Studyof Solar-Terrestrial Variability (from SCOSTEPWDS workshop)” in Earth Planets and Space (preface: Watanabe et al. 2017): https://www.
springeropen.com/collections/gdsys(3) Special issue on “Long-term changes and trends inthe upper atmosphere” in Journal of Atmosphericand Solar-Terrestrial Physics (preface: Laštovička
and Lübken 2017): https://www.sciencedirect.com/
journal/journal-of-atmospheric-and-solarterrestrial-physics/vol/163/suppl/C(4) Special issue on “Expected Evolution of Solar Activity in
the Following Decades” in Journal of Atmospheric andSolar-Terrestrial Physics (introductory paper: Obridko
and Georgieva 2018): https://www.sciencedirect.com/
journal/journal-of-atmospheric-and-solar-terrestrialphysics/vol/176/suppl/C(5) Special collection and book on “Earth-affecting
solar transients in Solar Physics” (editorial: Zhang
et al. 2018): Journal:https://link.springer.com/
journal/11207/topicalCollection/AC_74be62d9d035
e23ca163bf5434bd2877
Book: https://www.springer.com/gp/book/9789402415698

Shiokawa and Georgieva Progress in Earth and Planetary Science(6) Special issue of the “VarSITI-2017 symposium” inJournal of Atmospheric and Solar-Terrestrial Physics(preface: Georgieva and Shiokawa 2018): https://www.sciencedirect.com/journal/journal-ofatmospheric-and-solar-terrestrial-physics/vol/180/
suppl/C(7) Special issue of the “VarSITI closing symposium
2019” in Journal of Atmospheric and SolarTerrestrial Physics (under preparation)(8) Special issue of the “VarSITI summarizing
workshop” in Progress in Earth and Planetary
Science (this issue)

4.6 Database collection

The effort to collect VarSITI-related database was initiated after the SCOSTEP - World Data System (WDS)
workshop “Global Data Activities for the Study of SolarTerrestrial Variability” held during 28–30 September
2015 in Tokyo, Japan. VarSITI strives for the international collaboration in data analysis, modelling, andtheory to understand how solar variability affects the
Earth’s environment. The provision and long-term preservation of quality-assessed data are common objectives
for SCOSTEP and the WDS. The development of advanced data systems to enable scientists to perform
multidisciplinary data-analysis are another common target. This workshop marked the beginning of collaborations between SCOSTEP and WDS, and a Letter ofAgreement was signed by both organizations
The principal objective of the workshop was to stimulate interaction among data providers (WDS members,
data centers, data networks, etc.), data scientists, anddata-oriented researchers of the SCOSTEP community.
Data analysis of selected solar-terrestrial events was animportant component of the workshop also, not only todevelop the study of solar-terrestrial variability but also
to establish a mutual feedback loop between “data users”
and data providers.
As an outcome of the discussions during the workshop, it was recommended to have a unified metadata
system that enables users to search for VarSITI data
holdings from a single entry point, for example, a “VarSITI Data Portal.” After the VarSITI co-chairs asked via
the VarSITI mailing list the members to provide links totheir resources, a prototype of such a system has beenrealized in the VarSITI webpage under the title of “VarSITI-related Database Resources” (http://varsiti.org/ →Resources → Databases). It comprises 124 different databases plus 10 data analysis and visualization tools. This
database list can be used for students and young scientists for their easy access to the solar-terrestrial physics
data, allowing interdisciplinary data analysis over thewide area from the Sun to the earth.

(2021) 8:21

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5 Capacity building of SCOSTEP/VarSITIOne of the major tasks of SCOSTEP is the capacity
building of solar-terrestrial physics for students andyoung scientists. During the VarSITI interval in 2014–2018, SCOSTEP has made three large schools in collaboration with International Space Weather Initiative(ISWI) at Lima, Peru, on September 15–24, 2014, at
Sangli Maharashtra, India, on November 7–17, 2016,
and at Baku, Azerbaijan, in October 8–12, 2018.
In addition to these SCOSTEP/ISWI schools, the VarSITI co-chairs organized five schools in Indonesia,
Nigeria, and Russia. The two schools in Nigeria werenamed as the International School on Equatorial and
Low-Latitude Ionosphere (ISELLI) and ISELLI-2. ISELLI
was held at Abuja, Nigeria, on September 14–18, 2015,
and 65 students joined from 7 African countries. ISEL
LI-2 was held at Ota, Nigeria, on September 11–15,
2017, and 38 students joined from 7 African countries.
The two schools in Indonesia were named as the International School on Equatorial and Low-Latitude Ionosphere (ISELION) and ISELION2018. ISELION was heldat Bandung, Indonesia, on March 16–20, 2015, and 39
students joined from 9 Asian countries. ISELION2018
was also held at Bandung, Indonesia, on March 5–9,
2018, and 40 students joined from 7 Asian countries.
The school in Russia was held on July 9–12, 2017, in Irkutsk, Russia, in association with the VarSITI 2017 General Symposium (July 10–15, 2017) at the same venue.
Thirty-five students joined in this school from 5 countries. The database list developed by VarSITI was introduced in these schools to make it available to accessnovel data from latest missions for young scientists andstudents in developing countries (Fig. 21).
6 Future topic for predictability of solar-terrestrial
coupling
As addressed above, there has been great progress during the 5-year VarSITI program on 2014–2018. These
progresses of understanding solar-terrestrial couplingmechanisms make it possible to consider predictabilityof the variable coupling processes more quantitatively.
The expansion of space use for better human life, suchas GNSS positioning and broadcast satellites, requires
more accurate prediction of space weather and hazardous events in space. In addition, threats to Earth’s climate change also requests study of predictability on theeffect of solar variability on Earth’s climate. Under thesecircumstances the SCOSTEP decided to have the next
program as PRESTO—Predictability of variable solarterrestrial coupling for 2020–2024 (http://www.issibj.ac.
cn/Publications/Forum_Reports/201404/W0201906205
92906717714.pdf). The mission of PRESTO is to identify
predictability of the variable solar-terrestrial coupling
performance metrics through modeling, measurements,

Shiokawa and Georgieva Progress in Earth and Planetary Science(2021) 8:21

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Fig. 21 Photo of a VarSITI School on July 2017 at Irkutsk, Russia, with 35 students from 5 countries

and data analysis and to strengthen the communication
between scientists and users. The details of the PRESTO
definition are provided by Daglis et al. (2020).
Figure 22 summarizes challenging scientific topics inthe solar-terrestrial coupling processes that have been
investigated during the VarSITI program, but still needfurther investigation during the PRESTO program. For
short-term variabilities, which are shown in the leftsideof Fig. 22, the following topics will stand even after the
VarSITI interval.

6.1 Short-term variability from Sun to earth
6.1.1 Evolution of sunspot from solar interior to solar
surface

The sunspot evolution in the solar active region is oneof the key processes to understand and predict the solar
flare eruption (e.g., Toriumi and Takasao 2017 and references therein). It is still a difficult part to realisticallymodel this procedure from the solar interior to solar
surface and to use it for prediction of sunspot evolution.

Fig. 22 Black: challenging scientific topics in the solar-terrestrial coupling during and after the VarSITI program. Red: their consequences onhuman life. Short and long-term variabilities are shown in the left and right side of the figure, respectively. CIR corotating interaction region, CME
coronal mass ejection, CR cosmic ray, IMF interplanetary magnetic field, GNSS global navigation satellite system, GW gravity wave, MHD
magnetohydrodynamics, PW planetary wave, UV ultravioletShiokawa and Georgieva Progress in Earth and Planetary Science

6.1.2 Flare/CME prediction at the solar surface

Many progresses and proposals of new models havebeen made for the flare and CME prediction during the
VarSITI program, as summarized by Zhang et al. (2021)
and as shown by e.g., Bamba and Kusano (2018) andKusano et al. (2020). However, this topic is still a challenging key topic during the PRESTO interval.
6.1.3 Accurate measurements and prediction of flare UV
and X-ray spectra to understand ionospheric consequences

In order to understand the effect of solar flares on theionosphere, the spectral information of the solar flare isessential, because the UV and X-ray spectral distribution
provides height distribution of ionization in the ionosphere. In other words, UV and X-ray emissions atshorter (longer) wavelengths cause ionization at lower(higher) altitudes in the ionosphere. The flare spectra
can be different for different flares, even if the flare classdefined by the X-ray intensity is comparable. Recently,
Flare Irradiance Spectral Model (FISM) (Chamberlin
et al. 2008) has been widely used to model the flare effects on the ionosphere. The model provides flare UV
spectra from 0.1 to 190 nm with 1 nm resolution with atime resolution of 60 s, based on the satellite measurements. However, this model does not provide real time
data. Efforts to measure these spectra have been madeduring the VarSITI program (e.g., Woods et al. 2017).
Prediction of the spectra is a further challenging issue.
6.1.4 Measurement and prediction of spectra of Solar
Energetic Particles (SEP)

Similarly to the flare UV/X-ray spectra, the energy distribution of SEP determines the height variation of theionization in the middle atmosphere (e.g., Turunen et al.
2009). Thus, measurement and prediction of the spectral
information of SEP are an essential part to understandSEP effect on the atmosphere.
6.1.5 Accurate IMF-Bz modeling and prediction in the CME

During the VarSITI program, IMF-Bz modeling and prediction in the CME were the topic in a working group of
ISEST/Minimax24 (see Zhang et al. 2021 in details). But
it is still a challenging issue to make accurate predictionof IMF-Bz direction and intensity in the CME, which essentially controls intensity of geomagnetic disturbancesin the Earth’s magnetosphere. For example, Cho et al.
(2017) inspected two abnormal CME-Storm events andsuggested the importance of 3D magnetic field geometryof interplanetary Flux Ropes.
6.1.6 Modeling and prediction of IMF-Bz, speed, and dynamic pressure in the CIR

Another solar wind structure that causes strong geomagnetic disturbances is the CIR, which comes mainly from(2021) 8:21

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solar coronal holes during solar quiet time (e.g., Zhang
et al. 2007). Similarly to the CME, modeling and prediction of IMF-Bz, speed, and dynamic pressure in the CIR
is necessary to predict geomagnetic disturbances in the
Earth’s magnetosphere and ionosphere.
6.1.7 Connection between the outer magnetosphere and theinner magnetosphere

During the VarSITI program, the plasma dynamics in
the inner magnetosphere and acceleration and dissipation of plasma through wave-particle interaction havebeen extensively studied by the SPeCIMEN project(Kanekal and Miyoshi 2021). The connection between
the outer magnetosphere and the inner magnetosphere during storms and substorms provides boundary condition of global energy inputs from daysidemagnetopause and nightside magnetotail to the innermagnetosphere. One issue is that the modeling using
MHD approximation is applicable in the outer magnetosphere, while it is not in the inner magnetosphere
due to significant magnetic gradient and curvatureand strong coupling with the non-MHD ionosphere.
This situation causes a gap of simulation codes used
to describe the outer magnetosphere (MHD simulation) and inner magnetosphere (test particles andmagnetosphere-ionosphere-thermosphere
coupling
codes). Several attempts have been made to connect
these different models smoothly and self-consistently(e.g., Fok et al. 2014; Seki et al. 2018). However, theconnection of these different models is still a challenging issue in the PRESTO program.
6.1.8 Connection between the magnetosphere and theionosphere/thermosphere

Another challenging issue of MHD-non-MHD modelingconnection is the magnetosphere-ionosphere coupling,which is a key process for the energy input from geospace to the Earth’s atmosphere (e.g., Wiltberger et al.
2017; Ebihara and Tanaka 2017). The self-consistentconnection of the magnetosphere and ionosphere including neutral atmosphere is still a challenging issue in
the PRESTO program.
6.1.9 Connection from the high-latitude energy input to thethermospheric dynamics and to the plasma bubble
generation

The plasma convection driven by MHD processes in themagnetosphere can cause associated neutral wind in thethermosphere through ion-neutral collision (e.g., Condeet al. 2001; Xu et al. 2019). The auroral particles and associated Joule heating also cause disturbances in thehigh-latitude thermosphere (e.g., Lu et al. 2016). The resultant neutral wind in the thermosphere further propagates to lower latitudes (e.g., Shiokawa et al. 2007) andShiokawa and Georgieva Progress in Earth and Planetary Sciencecauses westward neutral wind by the disturbance dynamo (Blanc and Richmond 1980), which may suppress
ionospheric instabilities (plasma bubbles) in the equatorial evening terminator (e.g., Carter et al. 2014; Shinagawa
et al. 2018). The prompt penetrating electric field (PPEF)
from the magnetosphere to the equatorial ionosphere isanother major force to control equatorial plasma bubbles during magnetic disturbances (storms and substorms) (e.g., Tulasi Ram et al. 2015). During the
VarSITI program, these global processes have been extensively studied. However, further modeling and observation efforts should be made for accurate prediction ofplasma bubbles, particularly for their day-to-day variability. The equatorial plasma bubbles are one of the mostintense ionospheric disturbances on the Earth that significantly affect GNSS positioning and radiocommunication with satellites.
6.1.10 Connection from the high-latitude energy input tothe composition and dynamics of the atmosphere

During the VarSITI program, growing interest and significant studies have been made on the solar energetic
particles (SEP) and magnetospheric energetic particles(MEP) (Ward et al. 2021 and references therein). These
high-energy (keV-MeV) electrons and protons can causesignificant ozone depletion in the middle atmosphere(e.g., Andersson et al. 2018) which propagates downward
with a seasonal time scale. The challenging part is how
these ozone depletion and associate temperature change
in the middle atmosphere can change the dynamical
coupling between the middle atmosphere andtroposphere.
6.2 Short-term variability from the earth to geospace

From the Earth’s lower atmosphere to the thermosphereand ionosphere, significant dynamical effect can becaused by penetration of acoustic sound waves (periods:
less than minutes), gravity waves (several minutes tohours), tides (6 h to 1 day), and planetary waves (days).
Below are some outstanding topics that will stand evenafter the VarSITI program.
6.2.1 Gravity wave penetration to the thermosphere and its
consequences to the thermospheric dynamics andcirculation

During the CAWSES-II and the VarSITI program, agreat progress has been made on the penetration ofgravity waves into the thermosphere (e.g., Oberheide
et al. 2015; Yiğit 2018). It has been well known that thegravity waves control global circulation of the middle atmosphere through their dissipation in the mesopause region. However, the role of the primary and secondary
gravity waves that penetrate into the thermosphere on
global circulation is still not fully understood. Several(2021) 8:21

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papers during the VarSITI program have suggested thatthe role can be significant (e.g., Miyoshi and Yigit 2019;
Vadas and Becker 2019). However, more comparison
with global observation of the thermosphere and ionosphere will be needed to fully understand the gravity
wave role in the thermospheric dynamics andcirculation.
6.2.2 Gravity wave penetration to the thermosphere and its
consequences to the ionospheric disturbances

Not only the global dynamics, the gravity waves penetrated into the thermosphere can also generate ionospheric disturbances both directly and by seeding
ionospheric plasma instabilities (e.g., Otsuka 2018; Moralet al. 2019; Vadas et al. 2019). Thus, the gravity wave in thethermosphere is one of the key parameters to understandand predict the ionospheric disturbances that can cause
degradation of GNSS positioning accuracy (e.g., Tsugawa
et al. 2018). Further investigation of both modeling andground and satellite measurements should be done.
6.2.3 Variability of pre-reversal enhancement and generation of equatorial plasma bubbles

Pre-reversal enhancement in the evening solar terminator of the ionosphere is another key process that controls the generation of equatorial plasma bubbles. The
equatorial plasma bubble is the strongest disturbance inthe Earth’s ionosphere and significantly affects the GNSS
positioning. Recent global modeling such as by TIEGCM
and GAIA successfully reproduces seasonal variability ofpre-reversal enhancement, and thus, plasma bubbles(e.g., Carter et al. 2014; Shinagawa et al. 2018). However,prediction of day-to-day variability of plasma bubbles isstill a challenging issue. The day-to-day variability ofpre-reversal enhancement can be one of the causes ofthis plasma bubble variability (e.g., Ghosh et al. 2020).
6.2.4 GW/Tide/Planetary wave penetration to thethermosphere and ionosphere and its consequences in theplasmasphereAs cited above, the penetration of these waves with different periods can cause significant effects on thethermosphere (neutral atmosphere) and the ionosphere (plasma). However, their effect to the magnetosphere has not well been understood. For
example, storm enhanced density (SED) in the highlatitude ionosphere corresponds to a plume structurein the plasmasphere around the Earth (Foster et al.
2005). The clear conjugacy of nighttime travelingionospheric disturbances between the northern andsouthern hemispheres (e.g., Otsuka et al. 2004; Narayanan et al. 2018) indicates that these ionosphericdisturbances are mapped between the hemispheres
along geomagnetic field line, including the equatorialShiokawa and Georgieva Progress in Earth and Planetary Scienceplane of the near-Earth magnetosphere. The mapped
density structures in the plasmasphere can contribute ducting and cross-field localization of ULF/ELF/
VLF waves in the magnetosphere that are responsible for acceleration and dissipation of high-energy(radiation belt) plasma particles. Conjugate measurements with satellites in the inner magnetosphere andground instruments will be necessary to see these
possible connections between the ionosphere and themagnetosphere.
6.3 Long-term variability
6.3.1 Solar dynamo evolution and axial dipole moment topredict variability of the 11-year solar cycle

As cited in the above section on Solar Evolution and Extrema, the solar dynamo evolution to predict variabilityof the 11-year solar cycle is still a challenging issue evenafter the great efforts during the VarSITI program. The
solar axial dipole moment during the solar cycle minimum can be an indicator of the activity of next solar
cycle (e.g., Iijima et al. 2017; Jiang et al. 2018). The prediction of the 11-year solar cycle intensity is important
for long-term prediction of the space weather condition
that directly affects spacecraft operation in geospace(Bhowmik and Nandy 2018; Gopalswamy et al. 2018).
6.3.2 Long-term variation of solar total and spectral
irradiance for atmospheric consequences

The long-term variation of solar total and spectral irradiance (TSI and SSI) can be a key parameter to affect the
Earth’s climate change. Various modeling efforts havebeen made during the VarSITI program (e.g., Matthes
et al. 2017). However, quantitative assessment of TSI
and SSI effects on the atmosphere and long-term climatechange is not fully obtained yet. These irradiances also
cause significant variation in atmospheric density in thethermosphere where most of the low-earth orbiting satellites are flying (e.g., Liu et al. 2018). The thermosphericdensity variation controls the lifetime of these satellites
through atmospheric drag.
6.3.3 High-energy plasma effect on the atmosphericvariability, i.e., composition change and its dynamical effectvia ozone concentration

The energetic particle precipitation (EPP) on the atmosphere and subsequent ozone depletion have been observed and modeled in a seasonal time scale during the
VarSITI program (e.g., Funke et al. 2014; Turunen et al.
2016; Andersson et al. 2018). However, their consequences on climate change are the difficult part to approach. As cited before, the key issue is the effect of theozone depletion on the temperature variation in the
middle atmosphere and their connection to the troposphere through various types of atmospheric waves.

(2021) 8:21

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Long-term data analysis and modeling efforts should bedone further during the PRESTO program.
6.3.4 Solar dependence of tropospheric parameters andtheir connecting mechanisms

It is well known that the atmospheric density andtemperature in the thermosphere significantly vary during the 11-year solar cycle. This is clearly due to thevariation of the solar UV emission. We also see solar
variation in the tropospheric parameters, such as a 27day solar rotation in lightning activity (Miyahara et al.
2018) and 11-year solar cycle in Pacific Walker Circulation (Misios et al. 2019). The physical mechanisms thatcreate these solar variations in the troposphere have notbeen quantitatively explained. The variation of solar irradiance in the visible wavelength that reaches thetroposphere seems to be too small (~ 0.1%) to explain
the observed variations. However, the amplitude of variation in solar UV emission is much larger than that invisible wavelength, though the UV emission cannot
reach the troposphere due to absorption in the thermosphere and in the ozone layer in the middle atmosphere.
This reads the idea of atmospheric wave coupling tocause global circulation and tropospheric climate change(e.g., Kodera and Kuroda 2002) as below.
6.3.5 Atmospheric wave coupling to cause global
circulation and tropospheric climate change

The atmospheric waves, i.e., gravity waves, tides, andplanetary waves, can connect the middle atmosphereand the troposphere through dynamical coupling with
global circulation, resulting in climate change in the
troposphere driven by middle atmosphere variation (e.g.,
Kodera and Kuroda 2002; Lu et al. 2017). This process is
one of the key issues to understand possible connection
between the solar variabilities and the Earth’s climate,because the solar UV emission and energetic particles
can cause significant ozone depletion and associatedtemperature variation in the middle atmosphere.
6.3.6 Separation of anthropogenic effect and solar
variability effectThe global warming of the troposphere due to anthropogenic effect, such as CO2 and methane, is more quantitatively understood than that of the solar forcing effect.
However, the actual observation of climate change contains both effects in several different time scales. Modeling efforts have been made to separate these two
mechanisms (e.g., Egorova et al. 2018; Solomon et al.
2019). Comparison of these modeling efforts with longterm observation becomes increasingly important to
identify the mechanisms on solar forcing to climatechange.

Shiokawa and Georgieva Progress in Earth and Planetary Science

6.4 Consequences on human life

The red characters in Fig. 22 indicate the consequenceson human life, which are (a) plasma damage to space/air
vehicles and astronauts by energetic particles from theSun and the magnetosphere; (b) degradation of radio
communication and GNSS positioning by equatorial
plasma instabilities (plasma bubbles), auroras, and traveling ionospheric disturbances; (c) geomagnetically induced
currents (GIC) caused by auroral electrojet currents andflowing through electric supply network and pipelines; (d)satellite orbital change due to atmospheric drag that iscontrolled by solar UV emission and auroral plasma; and(e) climate change possibly caused by energetic particles
and solar UV radiation that changes dynamics of the middle atmosphere through ozone depletion. When we consider these consequences, the parameters used in scientificresearch, such as the sunspot number and the Kp and Dst
indices, may not be useful, and more appropriate parameters, such as temporal and spatial scales and amplitudes ofionospheric plasma variation, radiation dose and its temporal variation, and atmospheric temperature variation,
will be necessary for space users and climate scientists.
Close communication with space users and climate scientists will be necessary for solar-terrestrial physics for space
weather and space climate applications.

7 Summary
To understand variability of the Sun and its consequenceon Earth, communication of different fields and interdisciplinary researches are essential. During the 5-year program of VarSITI, major efforts have been made toencourage more communication between solar andinterplanetary scientists and magnetosphere, ionosphere,
and atmosphere scientists. The efforts were made by
developing mailing lists and websites; by distributing
VarSITI newsletters; by supporting interdisciplinary
meetings, databases, and campaigns; and by creating
database list. More than 1000 scientists in solarterrestrial physics have joined in this program.
Although it is still challenging to predict the intensityof the next solar maximum, several key procedures ofsolar dynamo have been understood during the VarSTII
interval under the SEE project. The interplanetary connection from the solar surface to the Earth’s magnetopause has been investigated in detail by combining
several in situ and remote-sensing satellites and ground
instruments under the ISEST/Minimax24 project. Studyof the inner magnetosphere was in the golden era by the
THEMIS, Van Allen Probes, and ERG satellites as wellas multi-point ground measurements and the global
modeling efforts that connect outer and inner magnetosphere and ionosphere. Coordination efforts have been
done for these inner-magnetosphere data under the SPeCIMEN project. The high-energy plasma input to the(2021) 8:21

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atmosphere and its connection to the climate change inthe middle and lower atmosphere have been extensively
studied, as well as short-term effects from the lower atmosphere to the thermosphere and the ionosphere,
under the ROSMIC project. All these scientific achievements obtained during the VarSITI program allow direction to the quantitative assessment of predictability ofshort- and long-term variation of solar-terrestrial coupling system. However, there are still many challenging issues in all regions from the solar interior to the Earth’s
atmosphere to make prediction of their variability. Increasing the use of space by human beings, such as
GNSS positioning and broadcast satellites, and increasing threat to the Earth’s climate change, are resulting inincreasing requirements for reliable prediction of thevariability of the Sun–Earth system. Under these circumstances, it is quite natural to have the next SCOSTEP
program, PRESTO, to focus on the predictability of variable solar-terrestrial coupling.
Abbreviations
ACE: Advanced Composition Explorer; ACRIM: Active Cavity Radiometer
Irradiance Monitor; AGU: American Geophysical Union; BATSRUS/
CRCM: Block-Adaptive-Tree-Solar-wind-Roe-Upwind-Scheme with
Comprehensive Ring Current Model; CATCH: Collection of Analysis Tools forCoronal Holes; CAWSES: Climate and Weather of the Sun–Earth System;
CDS: Centre de Données astronomiques de Strasbourg (Strasbourg
astronomical Data Cente); CESM: Coupled Ocean-Atmosphere Model;
CHAMP: Challenging Minisatellite Payload; CHIMERA: Coronal Hole
Identification via Multi-thermal Emission Recognition Algorithm;
CIR: Corotating interaction region; CME: Coronal mass ejection; CMIP5: Fifth
Phase of the Coupled Model Inter-Comparison Project; CR: Cosmic ray;
ECR: Electron count rate; EEJ: Equatorial electrojet; EEP: Energetic electron
precipitation; ELF: Extremely low frequency; EMCCD: Electron-multiplying
charge-coupled device; EPIC: Equatorial Processes Including Coupling;
EPP: Energetic particle precipitation; ERG: Energization and radiation in
geospacer; EUHFORIA: EUropean Heliospheric FORecasting Information Asset;
GAIA: Ground-to-topside model of atmosphere and ionosphere foraeronomy; GEMSIS: Geomagnetic Environment Modeling System for
Integrated Studies; GHG: Greenhouse gases; GIC: Geomagnetically induced
current; GNSS: Global navigation satellite system; GOMOS: Global Ozone
Monitoring by Occultation of Stars; GPS: Global Positioning System;
GW: Gravity wave; HCS: Heliospheric current sheet; HOPE: Helium Oxygen
Proton Electron; ICME: Interplanetary coronal mass ejection;
ICSU: International Council of Scientific Union; IMF: Interplanetary magnetic
field; IMS: International Magnetospheric Study; IPCC AR5: Intergovernmental
Panel on Climate Change Fifth Assessment Report; IRMB: Integrated Runoff
Model-F. Bultot; ISC: International Science Council; ISCS: International Solar
Cycle Study; ISELION: International School on Equatorial and Low-Latitude
Ionosphere; ISELLI: International School on Equatorial and Low-Latitude Ionosphere; ISEST: International Study of Earth-affecting Solar Transients;
ISWI: International Space Weather Initiative; IUCSTP: Inter-Union Commission
on Solar-Terrestrial Physics; keV: Kilo electronvolt; LDGRF: Long-duration
gamma-ray flare; LPGRE: Late-phase gamma-ray emission; MagEIS: Magnetic
electron-ion spectrometer; MAP: Middle Atmosphere Program;
MEP: Magnetospheric energetic particles; MeV: Mega electronvolt;
MHD: Magnetohydrodynamics; MLS: Microwave limb sounder; MLT: Magnetic
local time; MMS: Magnetospheric multiscale; PMOD: Physical MeteorologicalObservatory in Davos; PPEF: Prompt penetrating electric field; PRES
TO: Predictability of variable solar-terrestrial coupling; PSMOS: Planetary Scale
Mesopause Observing System; PW: Planetary wave; PWING: Study ofdynamical variation of particles and waves in the inner magnetosphere using
ground-based network; RAM: Ring current–atmosphere interactions model;
RGO: Royal Greenwich Observatory; ROSMIC: Role Of the Sun and the Middle
atmosphere/thermosphere/ionosphere In Climate; SABER: Sounding of theShiokawa and Georgieva Progress in Earth and Planetary Science

Atmosphere using Broadband Emission Radiometry; SAMPEX: Solar
Anomalous and Magnetospheric Particle Explorer; SCOSTEP: ScientificCommittee on Solar-Terrestrial Physics; SDO: Solar Dynamics Observatory;
SED: Storm enhanced density; SEE: Solar Evolution and Extrema; SEP: Solarenergetic particles; SOHO: Solar and Heliospheric Observatory; SPE: Solar
proton events; SPeCIMEN: Specification and Prediction of the Coupled InnerMagnetospheric Environment; SPOCA: Spatial POssibilistic Clustering
Algorithm; S-RAMP: STEP—Results, Application and Modeling Phase;
SSI: Spectral solar irradiance; SSW: Stratospheric sudden warming; STA: Solar
Terrestrial Relations Observatory Ahead; STEL: Solar-Terrestrial Environment
Laboratory; STEP: Solar-Terrestrial Energy Program; STEREO: Solar Terrestrial
Relations Observatory; SUSANOO: Space-Weather-forecast-Usable System
Anchored by Numerical Operations and Observations; TEC: Total electron
content; TG1: Task group 1; TG2: Task group 2; TG3: Task group 3; TG4: Task
group 4; THEMIS: Time History of Events and Macroscale Interactions during
Substorms; TIEGCM: Thermosphere ionosphere electrodynamics generalcirculation model; TIMED: Thermosphere-Ionosphere-Mesosphere Energetics
and Dynamics; TSI: Total solar irradiance; ULF: Ultra low frequency;
UV: Ultraviolet; VarSITI: Variability of the Sun and its Terrestrial Environment;
VLF: Very low frequency; WACCM: Whole Atmosphere Community Climate
Model; WDS: World Data System
Acknowledgements
We are grateful to Dimitar (Mitko) Danov of the Space Research andTechnology Institute, Bulgarian Academy of Sciences, Bulgaria, for his skillfulsupport for construction and maintenance of the VarSITI website. We arealso grateful to the four secretaries, Mai Asakura, Miwa Fukuichi, Megumi
Nakamura, and Ayumi Asai of the Institute for Space-Earth Environmental Research, Nagoya University, for their skillful support to bring out the VarSITI
newsletters.
Authors’ contributions
KS and KG are the two co-chairs of the VarSITI program. Both authors contributed to the writing this article. The authors read and approved the final
manuscript.
Authors’ information
KS and KG are the two co-chairs of the VarSITI program.
Funding
Because VarSITI is the 5-year program of SCOSTEP, the funding of VarSITI has
been provided by SCOSTEP. KS was supported by JSPS KAKENHI Grant Number 15H05815 and 16H06286 and the JSPS Core-to-Core Program, B. AsiaAfrica Science Platforms. The VarSITI Newsletter production has been supported by the Institute for Space-Earth Environmental Research, Nagoya University, Japan. The VarSITI website construction has been supported by theSpace Research and Technology Institute, Bulgarian Academy of Sciences,
Bulgaria.
Availability of data and materials
The dataset in this article is provided by www.varsiti.org except for the
figures taken from other references.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Institute for Space-Earth Environmental Research (ISEE), Nagoya University,
Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan. 2Space Research andTechnology Institute (SRTI), Bulgarian Academy of Sciences, Sofia, Bulgaria.
3
Climate, Atmosphere and Water Research Institute (CAWRI), Bulgarian
Academy of Sciences, Sofia, Bulgaria.
Received: 30 August 2020 Accepted: 25 January 2021

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