COMET SCIENCE WITH GROUND BASED AND SPACE BASED SURVEYS IN THE NEW MILLENNIUM J. M. Bauer

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COMET SCIENCE WITH GROUND BASED AND SPACE

BASED SURVEYS IN THE NEW MILLENNIUM

J. M. Bauer

Dept. of Astronomy, Univ. of Maryland, College Park, MD, USA, 20742-2421

Y. R. Fern´

andez

Dept. of Physics and Florida Space Inst., Univ. of Central Florida, 4000 Central Florida Blvd., Orlando, FL, USA 32816-2385

S. Protopapa

Southwest Research Institute, 1050 Walnut Street, Suite 300, Boulder, CO, USA 80302

L. M. Woodney

California State University, San Bernardino 5500 University Parkway San Bernardino, CA, USA 92407

We summarize the comet science provided by surveys. This includes surveys where the detections

of comets are an advantageous beneﬁt but were not part of the survey’s original intent, as well as some

pointed surveys where comet science was the goal. Many of the surveys are made using astrophysical and

heliophysics assets. The surveys in our scope include those using ground-based as well as space-based

telescope facilities. Emphasis is placed on current or recent surveys, and science that has resulted since the

publication of Comets II, though key advancements made by earlier surveys (e.g. IRAS, COBE, NEAT,

etc.) will be mentioned. The proportionally greater number of discoveries of comets by surveys have

yielded in turn larger samples of comet populations and sub-populations for study, resulting in better deﬁned

evolutionary trends. While providing an array of remarkable discoveries, most of the survey data has been

only cursorily investigated. It is clear that continuing to fund ground- and space-based surveys of large

numbers of comets is vital if we are to address science goals that can give us a population-wide picture of

comet properties.

1. INTRODUCTION

Over the span of the last decade and a half, a more au-

tomated approach to the analysis of data has become com-

mon. This is in part owing to the arrival of data sets which

are so large that each of the observations is not practi-

cally analyzed by human interaction, but rather is conducted

by automated pipeline. Analysis routines are prototyped,

tested, and applied to larger datasets, while outliers and di-

agnostic triggers indicate where special circumstances ap-

ply, and further manipulation, or rejection, of the data are

required. Much of this has been driven by the advent of

the vast quantities of data provided by automated sky sur-

veys. Additionally specialized data sets that are the product

of targeted observations now have a certain expectation of

providing statistically signiﬁcant samples large enough for

outliers to be identiﬁed and trends to be discerned.

Previous generation surveys generally had relatively

small sample sizes. Many of these surveys, demonstra-

bly the space-based surveys, made robust discoveries with

these smaller samples. Lisse et al. (1998) found tempera-

ture excess in dust comae from observations of ﬁve comets

at perihelion distances ∼1au obtained by the Cosmic Mi-

crowave Background Explorer (COBE). R¨

ontgen Satellite

(ROSAT) observations of six (Dennerl et al. 1997), and

later eleven (c.f. Lisse et al. 2004), comets revealed charge

exchange between highly charged heavy ions in the so-

lar wind and cometary neutrals dominated cometary X-ray

emissions. A subsequent survey by Bodewits et al. (2007)

of eight comets with the Chandra observatory found that

the characteristics of observed X-ray spectra mainly reﬂect

the state of the local solar wind. The Infrared Astronomy

Satellite (IRAS) mission data provided the ﬁrst thermal

dust trail measurements from eight identiﬁed comets (Sykes

and Walker 1992). Such surveys had large impacts on the

cometary ﬁeld, but did not employ the more automated

large-sample approaches, such as with astroinformatic tech-

niques (c.f. Borne et al. 2009), now utilized for larger sur-

vey samples.

For the deﬁnition of survey within these pages, we in-

clude sample sizes of 20 or greater, owing to the condi-

tions that even for simple statistical correlation tests, sam-

ple sizes ∼20 or greater are required to achieve 95% con-

ﬁdence values even for strong correlations (c.f. Bonnet

and Wright 2000). Here we concentrate on classical comet

populations (long-period and short-period comets; LPCs

and SPCs, respectively) and their dynamically deﬁned sub-

classiﬁcations (c.f. Levison 1996). SPCs are deﬁned to have

orbital periods <200 years, and LPCs having orbit periods

&200 years. Jupiter Family Comets (JFCs), for example,

arXiv:2210.09400v1 [astro-ph.EP] 17 Oct 2022

are a sub-class of SPCs with orbital periods .20 years and

pro-grade low orbital inclinations .40◦, while dynami-

cally new comets are a sub-class of LPCs with original or-

bital semi-major axis values &104au. Generally speaking,

the source of LPCs is the Oort cloud while the Kuiper belt

feeds the population of SPCs. Notably Halley-type comets

(HTCs) have historically often been lumped with SPCs, but

most of them are likely to be highly-evolved (in the dynam-

ics sense) objects from the Oort Cloud. Thus they are more

closely related to the LPCs. There are also different opin-

ions on the meaning of the term ’Oort Cloud comet’; e.g.,

it may only include dynamically new comets, or it may in-

clude all LPCs and HTCs that were in the Oort Cloud any

time in the past.

Measurements of large populations from single plat-

forms and the same, or similar, instrumentation provide

a basis for comparative samples, in contrast with compi-

lations (c.f. A’Hearn et al. 1995, Lisse et al. 2020 and

A’Hearn et al. 2012). Such samples of cometary physical

properties may be targeted, such as narrow-band ﬁlter sur-

veys (cf. Schleicher and Farnham 2004) or spectroscopic

surveys (cf. Dello Russo et al. 2016), or serendipitous ob-

servations, such as the data obtained with many ground-

based or space-based sky surveys1. These two categories

are signiﬁcantly different in the selection of the objects ob-

served, and how representative the samples are of the back-

ground populations.

In the ﬁrst case of targeted samples, known solar-system

object targets are selected based on their optical brightness,

and were discovered often by sky surveys. They are of-

ten observed at preferred geometries (opposition, for exam-

ple, for ground based telescopic surveys) and detected while

they are most active. As such, there are potential selection

biases in the sample that may skew projection of behavior

or physical properties of the base population. For targeted

observations the observing time can be selected to sample

the points through a comet’s orbit where the expected lev-

els of activity are best matched to the physical property of

interest. For example, optical surveys of comets at aphelion

may provide more accurate absolute magnitude values of

the nucleus, leading to better derived reﬂectances if the size

of the body is known. Alternatively, a more comprehensive

inventory of gas species may be derived at perihelion where

so-called hyper-volatiles and water-related species are re-

leased, and following a comet through its orbit may reveal

when particular species dominate the activity.

1.1. Survey Discoveries of Comets

Prior to the 1990s, comets were generally discovered ei-

ther in large photographic plate exposures or by individuals

that visually scanned the sky, often employing specialized

telescopes or binoculars with fast optics. In the late 1980s

1Here sky survey refers to a survey which covers regions of the inertial

frame, or background, sky with target coordinates ﬁxed in the equatorial,

ecliptic, or galactic coordinate frames, as opposed to moving targets (or

solar system objects).

and early 1990s, digital cameras began to be employed in

regular searches of the sky for solar system objects (cf.

Scotti et al. 1991) with a handful of early comet discoveries.

In addition, astrophysical sky surveys were conceived to

identify transient behavior, like supernova events, in extra-

solar-system objects. With the advent of the earliest digital

sky surveys, the automated surveys began to make signiﬁ-

cant contributions in the number of comet discoveries in the

mid-1990s. These foundational surveys employed Charge-

Coupled Device (CCD) cameras with ﬁelds of view that by

today’s standards would be quite modest, on the order of a

degree on a side (c.f. Pravdo et al. 1999), and rapidly began

to outpace other means of discovery.

The efforts to detect solar system objects have been

largely driven by the intent to discover and characterize

Near Earth Objects (NEOs). Observing cadences, point-

ing strategy, and approaches to analysis were therefore

optimized or prioritized towards these NEO-related goals.

These efforts have been remarkably effective, and discovery

of more than 83% of the known NEOs has been the result of

these efforts (Landis and Johnson 2019). As a means of dis-

covering comets, the NEO search programs have also been

effective, not only with the comets that are a component of

the NEO population, but also with more distant comets.

As of September 30, 2021, approximately 3586 comets

had been discovered, as registered by the Jet Propulsion

Laboratory (JPL) small bodies database.2A summary of

leading discovery platforms is provided in Table 1. Ac-

cording to the database, 41%of the comet discoveries listed

were discovered by the Solar and Heliospheric Observa-

tory (SOHO; with the SWAN and LASCO instruments3)

or the Solar Terrestrial Relations Observatory (STEREO)

spacecraft. In total, including these surveys, over 71% of

comet discoveries up to October 2021 have been made by

sky surveys. It is worth noting that the Minor Planet Cen-

ter count (∼4430 comets as of September 30, 2021), and

future counts in the near term, are likely to be higher, as

a signiﬁcant remainder of the data from the SOHO space-

craft have yet to be processed and the JPL number includes

only those comets that have been observed by other non-

solar-observing platforms in addition. Figure 1 shows the

annual number of discoveries and observations of objects

by sky surveys reported to the MPC and listed in the JPL

database. The drop-off in the discoveries near 2010 coin-

cides with the curtailment of sun-pointing spacecraft survey

data by the MPC, which has been recently resumed (Bat-

tams and Boonplod 2020), though has not yet encompassed

the multi-year backlog (Battams and Knight 2017).

1.2. Survey Observations

Along with a marked increase in the number of comet

discoveries brought through ground-based surveys, the

number of observations of comets has increased as well.

2https://ssd.jpl.nasa.gov/tools/sbdb query.html

3SWAN: the Solar Wind ANisotropy experiment and LASCO: the Large

Angle and Spectrometric COronagraph instrument

Table 1: Comet Discoveries by Selected Sky Surveys

Survey LocationaSPCsbLPCsbTotal

Catalina G96, 703, I52 200 193 393

Pan-STARRS F51, F52 112 142 254

LINEAR 704 91 128 219

NEAT 566, 644 39 16 55

ATLAS T05, T07, T08 16 35 51

NEOWISE C51 16 23 39

Spacewatch 291, 691 16 12 28

LONEOS 699 17 5 22

ZTF/PTF I41 2 16 18

SOHO/SWANc249 12 1466 1478

STEREOcC49 1 8 9

aThe Minor Planet Center Observatory Code contributors.

bShort-period comets (SPCs) with orbital periods <200 years

and Long-period comets (LPCs) with orbital periods ≥200 years.

cSun-looking survey total.

NOTE.—Note that the count of SOHO-discovered comets include

only those contributions with additional non-SOHO observations (see text).

Figure 1 shows that the number of observations closely

tracks the number of objects observed by the surveys.4On

average, an object is observed on the order of 10 times

per year, during its range of detectability, e.g. while the

comet passes through its perihelion. Table 2 lists the num-

ber of observations from each of the leading ﬁve surveys

at 5 year intervals back to 2000. The table shows the num-

ber of comet observations is relatively small compared with

the total observations of small bodies. It also reveals the

slowly changing ranks (in order of total observations) in

the lead surveys. The output of some very active programs

are temporarily diminished (cf. NEAT in the year 2000);

each program either upgrades and incorporates more sites,

or becomes outpaced by competing surveys, in which case

existing survey programs or sites often shift to a priority

from discovery to highly productive follow-up.

Both ground-based and space-based sky surveys have

been used to characterize cometary populations. However,

the full and systematic utilization of the majority of data

obtained by the surveys is in its early stages, with only

a handful of instances of the data being used to quanti-

tatively characterize the comet populations. Much of the

initial exploration of these sky survey datasets are cen-

tered around characterization of particular comets of inter-

est. Dobson et al. (2021) use Asteroid Terrestrial-impact

Last Alert System (ATLAS) data to identify the longevity

of 95P/Chiron’s 2018 onset of activity. Zwicky Transient

Factory (ZTF) survey (Kelley et al. 2021), Transiting Exo-

planet Survey Satellite (TESS) spacecraft (Farnham et al.

4Note that the drop in 2021 in Figure 1 is owing to the tally for that year

being derived from the mid-year numbers.

2019), and NEOWISE survey (Bauer et al. 2021) obser-

vations were used to monitor and characterize the behav-

ior of 46P/Wirtanen during its 2019 perihelion approach.

Investigations of statistically signiﬁcant samples of comet

populations (c.f. Farnham et al. 2021) are likewise facili-

tated by sky surveys, and are beginning to be analyzed using

astroinformatic approaches. Larger surveys that compile

cometary populations to constrain populations statistics are

rarer still. Hicks et al. (2007) reported magnitudes and Afρ

values (c.f. A’Hearn et al. 1984) for 52 comets observed by

the Near Earth Asteroid Telescope (NEAT) between 2001

and 2003, and produced estimates of nucleus size for 25

of the lowest-activity comets in the sample. Searches for

cometary activity among asteroids are more common (see

also Jewitt et al. in this volume). Waszczak et al. (2013)

searched for undiscovered main-belt comets, but identi-

ﬁed 115 comets in the Palomar Transient Factory (PTF)

data taken from 2009 through 2012, listing the maximum

and minimum magnitudes observed in the images. Sonnett

et al. (2011) observed 924 asteroids, and Hsieh et al. (2015)

conducted a large search of main belt objects observed in

Panoramic Survey Telescope and Rapid Response System

(Pan-STARRS) data to ﬁnd cometary activity, while Mar-

tino et al. (2019) and Mommert et al. (2020) searched for

activity amongst asteroids in comet-like orbits.

1.3. Survey Biases

It is abundantly clear from the previous discussion that

sky and sun-pointing surveys have had a remarkable impact

on our statistical understanding of the comet populations.

However, these data possess limitations, according to their

sensitivities, coverage strategies, and cadences. Non-survey

observations remain, therefore, highly valuable to the com-

munity, as demonstrated in the discovery of the second in-

terstellar object (cf. Borisov and Shustov 2021). Figs 2 and

3 are illustrative of the sample biases that can remain even

when short term biases, like those imposed by weather, are

removed or averaged over, and how they can be convolved

with real population features. The SPC inclination features

are mostly real, and are dominated by the JFC population’s

clustering near low-inclination orbits. The outliers in in-

clination, around near-retrograde orbits, have contributions

from the active Centaur and Halley-type comet populations.

Eccentricity is nearly level, but falls off at near zero values,

corresponding to near-circular orbits; the high-eccentricity

outliers on short-period orbits are in part strengthened by

the near sun-grazing comets seen by sun-looking surveys

(SLSs), or higher elongation, or terminator-pointing sur-

veys (TPSs), like NEOWISE.5Comets tend to be most ac-

tive as they approach towards and retreat from their perihe-

lion distance, so the discoveries with the furthest perihelia

are made ﬁrst by the opposition-looking surveys, while the

TPSs make the near-earth perihelion discoveries, and the

5The Near-Earth Object Wide-ﬁeld Infrared Survey Explorer (NEOWISE)

uses the repurposed Wide-ﬁeld Infrared Survey Explorer (WISE) space-

craft to search for NEOs and other solar system bodies.

Fig. 1.— Discoveries and reported observations of comets per year, 1980-2021. Green dashed line indicates discoveries

per year (multiplied by 10) as listed in the JPL small bodies database (but see text for explanation of the 2010 drop off).

Blue solid line indicates the number of comets with observations reported to the MPC. Red dotted line indicates the number

of observations reported to the MPC (divided by 10).

remaining low-perihelion comets are found by SLSs. The

dips near 80 and 270 degrees in the SPC argument of per-

ihelion (ω) distributions roughly correspond to where the

tug of Jupiter disrupts SPC orbits.

For the LPCs, in contrast to the SPCs, the discoveries are

dominated by SLSs, and thus a few high-inclination sun-

grazing comets, particularly the Kreutz family comets. The

NEOWISE weak cluster in inclination, near 105◦, pointed

out in Bauer et al. (2017), has become mildly more pro-

nounced with additional survey data, and the peaks in as-

cending node (Ω) and ωare clustering from the noted

Kreutz family comets. In each survey approach, the success

with particular populations show statistical outliers that can

bias the derived distributions if naively extrapolated from

the observed distributions or not carefully removed.

The large representative samples of comets discovered

and observed by sky surveys facilitates analyses of their to-

tal populations that lead to constraints on their total num-

bers. Such derivations are common among other represen-

tative populations, for example with NEOs (Mainzer et al.

2012) and Centaurs (Jedicke and Herron 1997). Accurate

accounting of factors that affect the survey’s detection ef-

ﬁciency, such as observing cadence, pointing pattern and

viewing geometry, sensitivity, and weather (for ground-

based surveys) are critical to the assessment of the under-

lying population numbers from the observations. Owing

to these factors being intrinsic to each survey (or instru-

ment/telescope combination), they must be considered for

each separate contribution. Comets, however, are different

from other populations in that they require an extra layer of

accounting to derive the ﬁnal total population numbers from

the observed sample; the brightness variations from activity

have to be accounted as well. Comets tend to vary greatly

in their brightness throughout their orbit, usually achieving

peak brightness around, though often not precisely at, their

perihelion. Even surveys with more predictable observing

circumstances, e.g. space-based surveys, have an additional

signiﬁcant level of uncertainty on any derived constraints of

total populations.

The earliest estimates of background populations based

on a modern sky survey was conducted by Francis (2005).

The author used the Lincoln Near-Earth Asteroid Research

(LINEAR) survey to assess the long-period comet popula-

tion. Francis (2005) found a total population of ∼5×1011

comets with a nucleus size of roughly a 1km in diame-

ter, roughly a factor of ∼2.5times that predicted by Oort

(1950). An important detail is that because the small end of

the comet size distribution is difﬁcult to measure, many of

the population estimates are for lower-bounded size ranges.

The difﬁculty in assessing the comet populations with ef-

fective diameters less than a kilometer often results in val-

ues of &1km for the lower bound in size for population

comparisons. The Survey of Ensemble Physical Properties

of Cometary Nuclei (SEPPCoN) (Fern´

andez et al. 2013)

provided constraints on the JFC population between two

and ten thousand objects with diameters of approximately

a kilometer or larger. Bauer et al. (2017), using the NEO-

WISE survey data, arrived at a number that fell within the

lower end of that range, ∼2100 Jupiter Family comets.

Applying a similar technique to the observed LPCs, Bauer

et al. (2017) found a total population of 1.3×1012 Oort

Cloud comets, about twice that of the LINEAR-derived

value by Francis (2005) and also found that the majority

of LPCs, about ∼60%, were already detected by contem-

porary surveys. It is worth noting that since 2015, the rate

of the discovery of non-sun-grazing LPCs has held an av-

erage of 6.2 comets per year with perihelia within 1.5 au

per year. Most recently, the PanSTARRS survey has been

assessed and de-biased to obtain JFC and LPC population

constraints (Boe et al. 2019). The comparative size con-

straints will be discuss in Section 4 , but population totals

for JFC and LPC comets ﬁnd similar numbers, with ∼1012

Oort Cloud objects as the speculative total.

Table 2: Yearly Comet Survey Observationsa

SurveybTotalcComets Comet

DetectionsdObserved Detectionsd

2020

Pan-STARRS 12181991 344 3606

ATLAS 10396137 284 11787

Catalina 10134103 335 4754

NEOWISE 152141 30 324

Spacewatch 70385 13 60

Yearly Total: 32934757 1006 20531

Survey Fraction: 0.18 0.31

2015

Pan-STARRS 7256500 206 2533

Catalina 3950145 176 1566

Spacewatch 512214 51 276

NEOWISE 158595 53 840

ATLAS 104495 189 5708

Yearly Total: 11981950 514 5484

Survey Fraction: 0.10 0.09

2010

Catalina 3296494 128 1119

NEOWISEe2410314 111 1477

LINEAR 2193193 78 1122

Spacewatch 852890 67 462

Pan-STARRS 597563 7 28

Yearly Total: 9350456 391 4208

Survey Fraction: 0.09 0.08

2005

Catalina 2325309 132 1342

LINEAR 2056210 98 1697

Spacewatch 1063276 46 287

NEAT 549313 37 207

LONEOS 803620 66 1513

Yearly Total: 6797728 379 4046

Survey Fraction: 0.11 0.11

2000

Spacewatch 2149917 14 134

LINEAR 2094140 84 1682

LONEOS 456892 50 343

Catalina 48878 7 36

NEAT 29 2 6

Yearly Total: 2814856 157 2201

Survey Fraction: 0.09 0.11

aAnnual totals shown at ﬁve-year intervals.

bNon-solar-pointing surveys and follow-up programs.

cThe total includes asteroids and comets.

dObservations reported to the MPC; more complete

summary available at https://sbnmpc.astro.umd.edu.

eBauer et al. (2017) notes 164 comets observed by WISE/NEOWISE within

the year, many retrieved by stacking. This number represents those

detected by the automated detection pipeline.

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COMETSCIENCEWITHGROUNDBASEDANDSPACEBASEDSURVEYSINTHENEWMILLENNIUMJ.M.BauerDept.ofAstronomy,Univ.ofMaryland,CollegePark,MD,USA,20742-2421Y.R.Fern´andezDept.ofPhysicsandFloridaSpaceInst.,Univ.ofCentralFlorida,4000CentralFloridaBlvd.,Orlando,FL,USA32816-2385S.ProtopapaSouthwestResearchInstitute,1050Wal...

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COMET SCIENCE WITH GROUND BASED AND SPACE BASED SURVEYS IN THE NEW MILLENNIUM J. M. Bauer

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