November 2011 

NASA/TM–2011-217192 

A State‐of‐the‐Art Experimental Laboratory 

for Cloud and Cloud‐Aerosol Interaction 

Research 

Need for a National Facility to Complement In Situ and Remote 

Field Measurements for Improved Atmospheric Modeling and 

Simulation—Background and Discussion 

Charles M. Fremaux and Dennis M. Bushnell 

Langley Research Center, Hampton, Virginia 
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November 2011 

NASA/TM–2011-217192 

A State‐of‐the‐Art Experimental Laboratory 

for Cloud and Cloud‐Aerosol Interaction 

Research 

Need for a National Facility to Complement In Situ and Remote 

Field Measurements for Improved Atmospheric Modeling and 

Simulation—Background and Discussion 

Charles M. Fremaux and Dennis M. Bushnell 

Langley Research Center, Hampton, Virginia 
Available from: 

NASA Center for AeroSpace Information 

7115 Standard Drive 

Hanover, MD 21076-1320 

443-757-5802 

“The importance of clouds in the climate system cannot be overemphasized”—

Akio Arakawa, 2004 
1

Table of Contents

Acknowledgments 2

Abstract 3

Introduction 4

Background 10

Summary of the State of the Art for Ground‐Based Experimental Laboratories 14

Some High‐Level Facility Requirements for Cloud Research via Ground‐Based

Laboratories 18

A Potential Approach to a Large Chamber for Cloud‐Aerosol Research 22

Next Steps 24

Conclusions 25

References 26

Appendix 31

Partial List of Existing Ground‐Based Aerosol and Cloud Chamber Research					

Facilities and Summary of Capabilities (from Ref. 52) 31
2

Acknowledgments

The	authors	would	like	to	acknowledge	organizations	and	individuals	that	provided	review	

comments	 that	 improved	 the	 final	 version	 of	 this	 report.	 	 From	 NASA	 Langley	 Research	

Center,	 the	 following	organizations	contributed:	Research	Directorate,	Science	Directorate,	

Center	Operations	Directorate,	and	Engineering	Directorate.			Very	helpful	external	reviews	

were	 provided	 by	 Dr.	 James	 D.	 Klett,	 Dr.	 Steven	 Ghan,	 and	 Dr.	 John	 H.	 Helsdon.	 	 Many	

valuable	additional	comments	and	ideas	were	provided	by	individuals	inside	and	outside	of	

NASA	 prior	 to	 and	 during	 the	 writing	 of	 the	 paper.	 	 Special	 thanks	 goes	 to	 Mr.	 Bradley	

Hallier	of	 the	Langley	Aerospace	Research	Summer	Scholars	Program	 for	putting	 together	

the	extensive	list	of	facilities	that	appears	in	the	Appendix	of	this	report.	
3

Abstract

The	 state	 of	 the	 art	 for	 predicting	 future	 climate	 changes	 due	 to	 increasing	 greenhouse	

gasses	in	the	atmosphere	with	high	accuracy	is	problematic,	notably	due	to	need	for	greater	

sophistication	 in	 atmospheric	 modeling.	 	 Confidence	 intervals	 on	 current	 long‐term	

predictions	 (on	 the	 order	 of	 100	 years)	 are	 so	 large	 that	 the	 ability	 to	 make	 informed	

decisions	 with	 regard	 to	 optimum	 strategies	 for	 mitigating	 both	 the	 causes	 of	 climate	

change	and	its	effects	is	in	doubt.		There	is	ample	evidence	in	the	literature	that	large,	if	not	

the	 largest,	 sources	 of	 uncertainty	 in	 current	 climate	 models	 are	 various	 aerosol	 effects,	

with	uncertainty	levels	ranging	from	50%	to	400%	and	greater.		A	significant	deficiency	in	

current	 capabilities	 is	 the	 lack	 of	 high‐fidelity	 mathematical	 models	 for	 cloud‐aerosol	

interactions.		As	exaflop‐class	computational	capability	begins	to	come	on	line	over	the	next	

decade	or	so,	much	better	modeling	of	these	interactions	will	be	needed	to	take	advantage	

of	 significantly	 increased	 computational	 power	 and	 enable	 the	 high	 fidelity	 climate	

predictions	 needed	 by	 policy	 and	 decision	 makers	 in	 government	 and	 industry.	 	 One	

approach	to	furthering	discovery	as	well	as	modeling,	and	verification	and	validation	(V&V)	

for	cloud‐aerosol	interactions	is	use	of	a	"cloud	chamber"	with	a	significantly	larger	volume	

than	is	currently	available.	Such a laboratory facility would be used in a complimentary role

to in‐situ and remote sensing field campaign measurement approaches (e.g., airborne and

spaceborne instruments) to enable improved global climate modeling.		While	it	is	recognized	

that	reproducing	all	of	the	highly	complex	phenomena	associated	with	these	interactions	is	

not	feasible,	it	is	suggested	that	the	physics	of	certain	key	processes	can	be	established	in	a	

laboratory	 setting	 so	 that	 relevant	 fluid‐dynamic	 and	 cloud‐aerosol	 phenomena	 (e.g.,	

turbulent	 many‐phase	 flow,	 convection,	 electrostatics,	 aerosol	 particle	 formation	 and	

growth,	etc.)	can	be	experimentally	simulated	and	studied	in	a	controlled	environment	using	

sophisticated	 instrumentation	 in	 a	 facility	 that	 is	 large	 enough	 so	 that	 wall	 effects	 are	

reduced	 to	acceptable	levels,	and	reasonable‐scale	cloud	dynamics	can	be	simulated.		This	

report	presents	a	high‐level	argument	for	significantly	improved	laboratory	capability,	and	

is	meant	 to	 serve	as	a	 starting	 point	 for	 stimulating	 discussion	within	 the	 climate	 science	

and	 other	 interested	 communities	 with	 regard	 to	 the	 need,	 requirements,	 and	 payoff	 for	

pursuing	 a	 large,	 state‐of‐the‐art	 experimental	 facility	 for	 improving	 prediction	 of	 future	

climate	states.	
4

Introduction

Currently,	 there	is	wide	agreement	within	 the	climate	 science	community	 that	 the	Earth's	

mean	atmospheric	temperature	has	risen	over	the	last	century	relative	to	historical	norms,	

and	 that	 this	 rise	 is	 being	 driven	 primarily	 by	 increased	 concentrations	 of	 natural	 and	

anthropogenic	 greenhouse	 gasses,	 although	 there	 is	 some	 disagreement	 as	 to	 whether	

increased	 greenhouse	 gas	 concentrations	 are	 due	 to	 natural	 cycles	 or	 human‐induced	

activities.	 	 Water	 vapor	 is	 the	 most	 abundant	 greenhouse	 gas	 in	 the	 atmosphere,	 but	

increases	 primarily	in	 carbon	 dioxide	 (CO2),	 but	 also	methane	 (CH4),	 nitrous	 oxide	 (N2O),	

chlorofluorocarbons	 (CFCs),	 	 and	 others	 are	 most	 associated	 with	 the	 rise	 in	 global	

temperature.			

Globally	and	within	the	U.S.,	significant	resources	are	being	expended	on	measurements	of	

atmospheric	phenomena,	and	developing,	testing,	and	refining	climate	models	for	predicting	

climate	 change	 and	 its	 impacts.	 	 Key	 policy‐	 and	 decision‐makers	 in	 government	 and	

industry	require	high‐confidence	projections	of	future	climate	states	in	order	to	make	good	

decisions	 with	 regard	 to	 deployment	 of	 resources	 for	 reducing	 greenhouse	 gas	 sources,	

dealing	 with	impacts	 due	 to	 climate	 change	 such	 as	 sea	level	 rise,	 etc.,	 and	 possibly	 even	

developing	"engineering	solutions"	to	mitigate	undesirable	climate	changes.	

While	analyses	of	historical	climate	data	indicate	with	fairly	high	certainty	that	mean	global	

atmospheric	 temperature	 has	 risen	 since	 the	 late	 nineteenth	 century	 (the	 consensusi

estimate	is	in	the	range	of	0.56	oC	to	0.92	oC	over	the	100	years	between	1906	and	2005	(Fig.	

1)),	and	that	mean	sea	level	has	risen	over	the	same	time	interval	by	approximately	15	cm,	

the	state	of	 the	art	 for	predicting	 future	climate	changes	with	high	accuracy	is	much	more	

problematic.		In	fact,	confidence	intervals	on	current	long‐term	predictions	(e.g.,	by	the	end	

of	 the	 twenty‐first	 century)	 are	 so	large	 that	 the	 ability	 to	make	informed	 decisions	 with	

regard	to	optimum	strategies	for	mitigating	both	the	causes	of	climate	change	and	its	effects	

is	 in	 doubt.	 	 For	 example,	 over	 the	 next	 century,	 IPCC	 best‐estimates1	 for	 global	 surface	

mean	atmospheric	temperature	rise	relative	to	the	last	two	decades	of	the	twentieth	century	

(Table	1)	vary	by	a	factor	greater	than	two	(+1.8	oC	to	+4.0	oC).		If	the	worst‐case	extremes	of	

"likely"	temperature	increase	(where	likely	is	defined	in	Reference	1	as	>66%	probability	of	

occurrence)	are	used,	the	spread	is	nearly	a	factor	of	six	(+1.1	oC	to	+6.4	oC),	as	illustrated	by	

the	gray	 "best	estimate"	 bars	 to	 the	 right	 of	 Figure	 2.	 	Similarly,	 sea‐level	 rise	 predictions	

vary	by	a	factor	of	greater	than	three	(approximately	+18	cm	to	+59	cm).		While	the	reasons	

for	the	spread	in	the	predictions	are	varied	and	complex	(differing	underlying	assumptions,	

uncertainties	 in	 the	 modeled	 values,	 etc.),	 depending	 on	 whether	 the	 outcome	 is	 on	 one	

extreme	of	 the	predictions	or	 the	other,	a	different	(likely	significantly	different)	response	

by	policy‐	and	decision	makers	will	be	required.		Making	the	"wrong"	investments	early	on	

could	have	significant	negative	impact	in	the	long	run,	ranging	from	needless	expenditure	of	
5

valuable	resources	on	one	extreme	to	failure	to	deal	with	the	problem	sufficiently	to	prevent	

major	environmental	consequences	at	the	other	extreme.	

Figure 1. Observed historical change in global average surface temperatures, 

average sea level, and northern hemisphere snow cover (from Ref. 1, Fig. 1.1, p. 31)
6

Table 1. Projected Global Average Surface Warming and Sea Level Rise at the end of the 

21st Century (from Ref. 1, Table 3.1, p. 45) 

Figure 2. Change in average measured (1900-2000) and predicted (2000-2100) 

surface temperature relative to 1980-1999 (from Ref. 2, Fig. SPM.5, Summary 

for Policymakers section, p. 14) 
7

There	is	ample	evidence	in	 the	literature	 (e.g.	 refs.	 2	 ‐	 5,	with	many	 other	examples	 cited	

later)	 that	 large,	 if	 not	 the	 largest,	 sources	 of	 uncertainty	 in	 current	 simulation	 climate	

models	are	various	cloud	and	cloud‐aerosol	effects,	with	values	ranging	from	50%	to	400%	

and	 greater.	 	 A	 significant	 deficiency	 in	 current	 capabilities	 is	 a	 lack	 of	 high‐fidelity	

mathematical	 models	 for	 cloud	 effects	 and	 cloud‐aerosol	 interactions.	 	 The	 following	

excerpt	from	the	2010	Department	of	Energy	(DOE)	Atmospheric	System	Research	Science	

and	Program	Plan6	executive	summary	captures	the	issue	succinctly:	

Current	climate	models	show	a	large	spread	in	the	values	of	projected	climate	

parameters	like	surface	temperature	and	precipitation,	and	this	spread	makes	

it	difficult	 for	policy	makers	 to	use	such	projections	 to	develop	national	and	

international	 energy	 policy.	 The	 spread	 in	 climate	 model	 projections	 arises	

from	 two	 broad	 sources	 of	 uncertainty.	 First,	 scientists	 believe	 that	

anthropogenic	 atmospheric aerosols partially	 offset	 the	 global	 warming	

influence	 due	 to	 enhanced	 greenhouse	 gas	 concentrations,	 but	 because	

climate	models	are	uncertain	how	 to	represent	 the	complex	aerosol	lifecycle	

in	 the	 atmosphere,	 they	 are	 also	 uncertain	 about	 the	 impact	 of	 aerosols	 on	

climate.	 Second,	 clouds are	 a	 large	 source	 of	 uncertainty	 in	 climate	 models,	

particularly	 how	 clouds	 will	 respond	 to	 and	 interact	 with	 changes	 in	

atmospheric	 composition.	 	 Both	 aerosols	 and	 clouds	influence	 radiation and

precipitation,	which	together	largely	drive	the	global	atmospheric	circulation.	

A	 primary	 cause	 of	 current	 high	 levels	 of	 uncertainty	 in	 future	 climate	 prediction	 by	

modeling	 is	 a	 low	 level	 of	 understanding	 of	 the	 underlying	 physical	 processes	 related	 to	

atmospheric	aerosols	and	cloud‐aerosol	interactions	at	 they	pertain	 to	climate	change.		As	

clearly	noted	by	the	IPCC	in	Reference	2:	

Anthropogenic	contributions	to	aerosols	(primarily	sulphate,	organic	carbon,	

black	carbon,	nitrate	and	dust)	together	produce	a	cooling	effect,	with	a	total	

direct	 radiative	 forcing	 of	 –0.5	 [–0.9	 to	 –0.1]	 W	 m–2	 and	 an	 indirect	 cloud	

albedo	 forcing	 of	 –0.7	 [–1.8	 to	 –0.3]	W	 m–2.	 	 These	 forcings	 are	 now	 better	

understood	 than	 at	 the	 time	 of	 the	 TAR	 (i.e.,	 the	 third	 Technical	 Analysis	

Report	produced	 by	 the	 IPCC	in	2001)	due	 to	improved	in situ,	 satellite	and	

ground‐based	measurements	and	more	comprehensive	modeling,	but remain

the dominant uncertainty in radiative forcing	(emphasis	added).		Aerosols	also	

influence	cloud	lifetime	and	precipitation.			

The	 mechanisms	 contributing	 to	 radiative	 forcing	 are	 summarized	 in	 Figure	 3	 from	

Reference	 2.	 	 Note	 that	 the	 total	 (direct	 +	 cloud	 albedo)	 impact	 of	 aerosols	 on	 radiative	

forcing	is	second	only	 to	CO2,	but	 that	 the	uncertainties	on	 these	quantities	are	by	 far	 the

largest	of	any	of	the	components,	and	that	the	"level	of	scientific	understanding"	(LOSU)	is	

"medium	 to	low"	 for	direct	effects,	and	 "low"	 for	 cloud	albdeo	effects.	 	The	clear	 need	 for	

significantly	 better	 understanding	 of	 the	 physical	 mechanisms	 and	 processes	 underlying	
8

atmospheric	 aerosols	 and	 cloud‐aerosol	interactions	 (as	 they	 relate	 to	 climage	 change)	is	

the	impetus	for	proposing	that	highly	controlled	experiments	be	conducted	in	a	state‐of‐the‐

art	laboratory.	 	Only	 when	 the	 relevant	 underlying	 physical	 processes	 related	 to	 aerosols	

and	 cloud‐aerosol	 interactions	 are	 much	 better	 understood,	 and	those	 physical	 processes	

that	 are	 well	 understood	 are	 adequately	 accounted	 for,	 will	 uncertainties	 be	 significantly	

reduced.		As	much	more	powerful	supercomputers	begin	to	come	on	line	

		

over	the	next	decade	or	so	(likely	exaflop‐class	computers,	i.e.,	1018	floating	point	operations	

per	second),	much	better	modeling	of	these	interactions	will	be	needed	to	take	advantage	of	

Figure 3. Anthropogenic and Natural Radiative Forcing Components Important to Climate 

Change (from Ref. 2, Fig. SPM.2, Summary for Policymakers section, p. 4) 
9

significantly	 increased	 computational	 power	 and	 deliver	 the	 high	 fidelity	 climate	

predictions	needed	by	policy	and	decision	makers	in	government	and	industry.	

There	are,	in	addition,	considerable	and	increasing	concerns	regarding	the	potential	impact	

of	"positive	 feedbacks”.		For	example,	warming‐induced	release	of	 the	massive	amounts	of	

fossil	methane	and	methane	clathrates	(methane	ice	or	"fire	ice")	present	in	the	tundra	and	

ocean	 sediments	 could	 have	 a	 major	 impact	 on	 temperature	 rise	 since	 methane	 is	 over	

twenty	 times	 more	 effective	 than	 CO2	 as	 a	 greenhouse	 gas.	 The	 tundra	 and	 oceans	 also	

contain	massive	amounts	of	fossil	CO2	that	is	being	released	as	warming	occurs.		In	addition,	

the	 ability	 of	 the	 oceans	 to	 absorb	 excess	 atmospheric	 CO2	 (i.e.,	 "CO2	 uptake")	 is	 being	

reduced	due	to	temperature	rise,	acidification,	and	reductions	in	algae.		Another	example	of	

a	positive	 feedback	cycle	is	related	 to	the	planet's	albedo,	or	 the	amount	of	solar	radiation	

reflected	 back	 into	 space.	 	 As	 large	 ice	 sheets	 melt,	 albedo	 is	 reduced	 and	 average	

temperature	is	increased.		 Increased	 temperature	results	in	more	water	being	evaporated,	

and	water	 vapor	is	a	 dominant	greenhouse	gas.	 	Taken	 together,	these	 positive	 feedbacks	

could	evidently,	 from	crude	estimates,	greatly	accelerate	the	rate	and	increase	the	impacts	

of	climate	change.		Reference	7	provides	a	discussion	of	the	"cloud	positive	feedback”	that	is	

directly	related	to	cloud‐aerosol	interactions.	

One	approach	 to	 furthering	 discovery	as	well	as	modeling,	and	 verification	and	 validation	

(V&V)	for	cloud‐aerosol	interactions	is	to	use	a	"cloud	chamber"	with	a	significantly	larger	

volume	 than	 is	 currently	 available.	 Such a laboratory facility would be used in a

complimentary role to in‐situ field campaign measurement approaches (e.g., airborne and

spaceborne instruments) to improve the fidelity of atmospheric models for climate change

prediction.	It	is	recognized	that	reproducing	all	of	the	highly	complex	phenomena	associated	

with	these	interactions	in	a	laboratory	setting	is	not	feasible.		However,	it	is	suggested	that	

the	physics	of	certain	key	processes	can	be	established	so	that	important	phenomena	(e.g.,	

turbulent	 many‐phase	 flow,	 convection,	 turbulence,	 electrostatics,	 particle	 formation	 and	

growth,	etc.)	can	be	experimentally	simulated	and	studied	in	a	controlled	environment	using	

sophisticated	 instrumentation	 in	 a	 facility	 that	 is	 large	 enough	 so	 that	 wall	 effects	 are	

reduced	 to	 acceptable	 levels,	 and	 reasonable‐scale	 cloud	 dynamics	 can	 be	 simulated.	 	 As	

discussed	 and	 suggested	 herein,	 controlled	 laboratory	 experiments	 in	 large‐scale	 ground	

facilities	 appear	 to	 be	 a	 "missing	 link"	 in	 the	 quest	 for	 truly	 high	 fidelity	 climate	 change	

predictions	 going	 forward,	 but	 detailed	 analyses	 will	 have	 to	 be	 conducted	 in	 order	 to	

estimate	the	magnitude	of	uncertainty	reduction	that	can	ultimately	be	realized	relative	to	

the	current	field	campaign	state	of	the	art.	

Overall,	it	is	obvious	that	prognostication	of	climate	change	over	the	next	several	decades	to	

a	century	must	be	done	with	as	much	precision	and	accuracy	as	can	be	mustered	due	to	the	

potentially	massive	impacts	going	forward	on	global	econometrics,	human	health,	standards	
10

of	living	and	national	security.		There	is	a	possibility	that	global	co‐operation	whilst	working	

“climate	 change”	 as	 a	 “common	 enemy”	 could	 lead	 to	 greater	 global	 consilience.	 	 NASA	

Langley	Research	Center	is	assessing	the	need	and	requirements	for	a	ground‐based	facility	

to	 experimentally	 simulate,	 both	 for	 discovery	 science	 and	 modeling,	 cloud‐aerosol	

interactions	 with	 application(s)	 to	 their	 effects	 on	 climate	 change.	 	 Such	 a	 facility	 is	

envisioned	 as	 a	 national	 resource	 for	 developing	 critical	 aspects	 of	 climate	 models,	

calibrating	 computational	 methods,	 and	 understanding	 the	 physical	 processes	 underlying	

cloud‐aerosol	interactions	through	the	study	of	meaningful	but	manageable	"unit	problems"	

at	 useful	 scales.	 	 This	 document	 outlines	 the	 impetus	 for	 considering	 the	 need	 for	 better	

understanding	 and	 representation	 of	 cloud‐aerosol	 interactions	 in	 Global	 Climate	 Models	

(GCMs),	 some	 initial	 high‐level	 requirements	 for	 a	 ground‐based	 experimental	 facility,	

possible	conceptual	approaches	to	its	design,	and	the	next	steps	needed	to	assess	the	level	

of	consensus	for	such	a	facility	within	the	climate	science	community.	

Background

A	search	of	the	pertinent	literature	reveals	that,	while	the	mean	predicted	trends	appear	to	

be	 consistent	 (e.g.,	 that	 a	 rise	 in	 mean	 global	 temperature	 over	 a	 time	 scale	 of	 several	

decades	 will	 occur	 due	 to	 increasing	 levels	 of	 greenhouse	 gasses	 from	 a	 combination	 of	

anthropogenic	 and	 natural	 sources)	 there	 is	 wide	 acceptance	 within	 the	 climate	 science	

community	 that	 there	 are	 large	 uncertainties	 in	 these	 projections	 due	 to	 a	 number	 of	

factors.	 	One	 of	 the	largest	 sources	 of	 uncertainty	 appears	 to	be	lack	 of	 sophistication	 for	

representing	 cloud	 feedbacks	 (positive	 and	 negative)	 into	 the	 Earth's	 radiation	 budget	 in	

Global	Climate	Models4,5,	including	 forcing	effects	 of	aerosols	as	 they	interact	with	clouds.		

Large	 Eddy	 Simulations	 (LES)	 and	 other	 computational	 approaches	 use	 modeling	 to	

simulate	complex	atmospheric	physics	and	chemistry,	including	 the	effects	of	aerosols,	 for	

predicting	 climate	 states	 (e.g.,	 Ref.	 8).	 	 These	 aerosol	 (and	 other	 particulate)	 effects	 are	

believed	 to	 be	 the	 source	 of	 phenomena	 ranging	 from	 "global	 dimming"	 (the	 reduction	 of	

direct	 solar	 radiation	 reaching	 the	 Earth's	 surface	 and	 thus	 reducing	 atmospheric	

temperature	 and	 partially	 counteracting	 temperature	 rise	 caused	 by	 greenhouse	 gas	

pollution),	 to	changes	in	 the	global	precipitation	pattern.		The	discretization	scale	of	most	

GCMs	(on	the	order	of	1	degree	of	latitude,	or	roughly	100	km)	is	also	problematic	in	terms	

of	predicting	phenomena	that	are	manifest	at	smaller	scales	such	as	cloud	effects,	and	thus	

their	impacts.		Current	practice	is	to	parameterize	cloud	effects	using	bulk	properties	across	

a	grid	cell,	even	though	the	scale	of	individual	clouds	(and	even	cloud	systems)	can	be	many	

times	 smaller.	 	 While	 necessary	 due	 to	 the	 computational	 intensity	 of	 atmospheric	

simulations	 relative	 to	 current	 computer	 power,	 this	 compromise	 clearly	 introduces	 a	

source	of	uncertainty	into	the	results.		However,	some	recent	simulations	have	been	run	at	

resolutions	as	low	as	100m	in	order	 to	resolve	individual	clouds	with	encouraging	results

(Ref.	9).		Below	are	representative	excerpts	from	a	sampling	of	the	contemporary	literature	
11

with	 regard	 to	 cloud	 and	 cloud‐aerosol	 interactions	 and	 their	 impact	 on	 climate	 change	

predictions:	

 "Estimates	of	Earth's	climate	sensitivity	are	uncertain,	largely	because	of	uncertainty	

in	the	long‐term	cloud	feedback"	‐	(Ref.	10)	

 “Clouds	have	a	strong	influence	on	the	Earth’s	radiative	balance	but	are	poorly	

represented	in	current	climate	models"	‐	(Ref.	11)	

 “Many	of	the	uncertainties	in	Global	Climate	Models	stem	from	poor	representation	

of	cloud	processes	that	operate	at	fine	scales”	‐	(Ref.	6)	

 “We	do	not	know	how	much	warming	due	to	green‐house	gases	has	been	canceled	by	

cooling	due	to	aerosols”	‐	(Ref.	12)	

 "The	uncertainty	in	assessing	anthropogenic	aerosol	impacts	on	climate	must	be	

much	reduced	from	its	current	level	to	allow	meaningful	projections	of	future	

climate"	‐	(Ref.	13)	

 "The	interactions	between	aerosols	and	clouds	is	probably	the	biggest	uncertainty	of	

all	climate	forcing/feedback	processes”	‐	(Ref.	13)	

 	“Modeling	the	cloud	albedo	effect	from	first	principles	has	proven	difficult	because	

the	representation	of	aerosol‐cloud	interactions	and	of	clouds	themselves	in	climate	

models	are	still	crude”	‐	(Ref.	14)	

 “Variations	of	cloudiness	by	5%	translates	to	a	degree	of	temperature	change”‐	(Ref.	

15)	

 “Whether	 anthropogenic	 activity	 actually	 increases	 or	 decreases	 ice	 nuclei	

concentration	is	a	matter	of	debate"	‐	(Ref.	16)	

 “The	uncertainty	in	aerosol	radiative	 forcing	is	 typically	greater	 than	100%	and	 for	

some	aerosol	components	it	is	more	 than	200%.		The	 regional	 scale	 forcing	can	 be	

significantly	 greater	 than	 the	 global	 average,	 as	 can	 the	 associated	 uncertainty”	 ‐	

(Ref.	17)	

 “The	 indirect	 radiative	 effects	 of	 aerosols	 also	 includes	 effects	 on	 ice	 and	 mixed	

phase	clouds	but	the	magnitude	of	any	indirect	effect	associated	with	the	ice	phase	is	

not	known”	‐	(Ref.	3)	

 “Aerosols	 represent	 the	 largest	 uncertainty	 in	 understanding	 how	 humans	 are	

changing	our	climate”	‐	(Ref.	18)	
12

 “Even	small	changes	in	ice	formation	could	have	a	significant	impact	on	the	indirect	

forcing	due	to	aerosols”	‐	(Ref.	3)	

 	“Scientists	 have	 yet	 to	 untangle	 the	 interplay	 between	 pollution,	 clouds,	

precipitation	and	temperature”	‐	(Ref.	19)	

 	“Global	models	suggest	that	sulfate	aerosols	produce	a	direct	forcing	in	the	Northern	

Hemisphere	of	the	same	order	of	magnitude	as	that	from	anthropogenic	green	house	

gases	but	opposite	in	sign.		There	is	substantial	uncertainty	about	the	magnitude	and	

spatial	distribution	of	the	negative	forcing	by	aerosols.		It	is	the	opinion	of	this	panel	

(the	NRC)	that	the	uncertainty	in	the	magnitude	of	the	effects	of	aerosols	on	climate	

is	seriously	hindering	our	ability	to	assess	the	effect	of	anthropogenic	emissions	on	

climate”	‐	(Ref.	20)	

 “Anthropogenic	 aerosols	 have	 the	 potential	 to	 introduce	 complex	 anomalies	 in	 the	

circulation	and	precipitation	climatology	 thereby	creating	hazardous	new	hot	spots	

in	the	water	cycle.”	‐	(Ref.	21)	

 “Quantifying	 the	indirect	 (cloud‐aerosol)	effects	 of	aerosols	is	 highly	 uncertain	and	

remains	one	of	the	largest	uncertainties	in	our	efforts	to	calculate	radiative	forcing”	‐	

(Ref.	23)	

 “The	greatest	uncertainty	about	aerosol	climate	forcing,	indeed	the	largest	of	all	the	

uncertainties	about	global	climate	forcing	–	is	probably	the	indirect	effect	of	aerosols	

on	clouds”	‐	(Ref.	24)	

 "Estimates	of	Earth’s	Climate	sensitivity	are	uncertain	largely	because	of	uncertainty	

in	long	term	cloud	feedback"	‐	(Ref.	10)	

 	“Accurate	representation	of	cirrus	clouds	remains	a	challenge	to	climate	modeling	in	

part	 because	 of	 an	incomplete	 understanding	 of	ice	 formation	mechanisms”	 ‐	 (Ref.	

25)	

 “The	magnitude	of	 the	indirect	effects	 (of	aerosols)	on	clouds	remains	a	mystery”	 ‐	

(Ref.	26)	

 “The	cloud‐aerosol‐precipitation	processes	are	not	taken	into	account	as	they	should	

not	because	we	do	not	recognize	their	importance	but	rather	because	we	know	 too	

little	 on	 how	 to	 quantify	 them	 accurately	 in	 the	 weather	 and	 climate	 models,	 It	

appears	we	cannot	get	the	climate	system	right	without	properly	accounting	for	the	

aerosol‐cloud‐precipitation	 processes,	 the	 dynamic	 response	 of	the	 clouds	 and	 the	

cascade	of	feedbacks”	‐	(Ref.	27)	

 “Aerosols	 and	 clouds	 play	 central	 roles	 in	 atmospheric	 chemistry	 and	 physics,	

climate,	 air	 pollution	 and	 public	 health.	 The	 mechanistic	 understanding	 and	
13

predictability	 of	 aerosol	 and	 cloud	 properties,	 interactions,	 transformations	 and	

effects	are,	however,	still	very	limited”	‐	(Ref.	28)	

 In	Reference	29,	the	issue	that	was	most	uncertain	to	all	fourteen	experts	was	clouds,	

specifically	 whether	 or	 not	 clouds	 would	 exacerbate	 climate	 change	 by	 trapping	

more	heat	or	ameliorate	it	by	reflecting	more	sunlight.	

Based	 on	 recent	 reports	 (e.g.,	Ref.	 2),	 typical	 uncertainties	 for	 various	impacts	 of	aerosols	

upon	 climate	 forcing	 are	in	 the 50%	 to 100%	 range,	 but	 with	 several	 at	much	 greater	

uncertainties	 of	 up	 to	 400%.	 	 The	 current	 state‐of‐the‐art	 for	 developing	 atmospheric	

simulation	models	relies	almost	primarily	on	in situ	and	remote‐sensing	field	measurements	

of	atmospheric	state	using	ground	based,	airborne,	or	spaceborne	instruments.		The	use	of	

highly	 sophisticated	 instruments	 and	 sensing	 techniques	 in	 real‐world	 atmospheric	

measurements	 produces	 very	 high	 quality	 data	 for	 analysis	 and	 modeling.	 	 However,	 the	

information	 produced	 by	 such	 field	 campaigns	 is,	 by	 its	 nature,	 “all	 inclusive”	 and	

“contemporary”,	i.e.,	the	entire	panoply	of	physical	mechanisms	and	interactions	present	in	

the	atmosphere	locally	and	currently	are	represented,	but	the	ability	to	assess	the	impact	of	

particular	 constituents	 or	 processes	 in	 controlled	 and	 repeatable	 ways	 (i.e.,	 as	 in	 a	

laboratory	 setting)	 is	 either	 very	 difficult	 or	 impossible.	 	 Thus,	 potential	 changes	 to	 such	

physics	and	interactions	that	might	be	induced	going	forward	by	various	impacts	of	climate	

change	 are	 not	 accessed.	 	 Without	 accurate,	 valid	 modeling	 of	 the	 requisite	 physics	 writ	

large	 these	 current	 field	 campaigns	 cannot	 be	 projected	 forward	 to	 yield	 what	 is	 really	

required	–	accurate	“predictions”	and	impacts	of	various	mitigation	approaches.		As	noted	in	

Reference	 3:	 	 “Projections	 of	 a	 future	 indirect	 effect	 are	 especially	 uncertain	 because	

empirical	 relationships	 between	 cloud	 droplet	 number	 and	 aerosol	mass	may	 not	 remain	

valid	 for	 possible	 future	 changes	 in	 aerosol	 size	 distributions”.	 	 Although	 the	 empirical	

formulations	 noted	in	Reference	3	 have	 been	 superseded	 by	 those	 that	are	more	 physics‐

based	 in	 the	 current	 generation	 of	 climate	 models	 (as	 noted	 in	 Reference	 4),	 significant	

work	 remains	 to	 be	 done	 before	 the	 all	 of	 the	 relevant	 physics	 are	 captured.	 	 The	 field	

campaigns	 are	 essential	 to	 studying	 the	 factors	 that	 control	 behavior	 of	 the	 current	

atmosphere,	but	are	far	from	what	is	required	to	develop	and	calibrate	high‐fidelity	physical	

models	for	predicting	future	changes.		For	such	modeling,	laboratory	studies	are	required	so	

that	unit	problems	and	discovery	can	be	undertaken	under	controlled	conditions	in	a	cost	

effective	and	expeditious	manner.		"The	key	to	reducing	aerosol	RF	uncertainty	estimates	is	

to	 understand	 the	 contributing	 processes	 well	 enough	 to	 accurately	 reproduce	 them	 in	

models”	 (Ref.	 13).	 	 Currently	in	 the	 U.S.,	 ground‐based	laboratory	 facilities	 (excluding	 the	

ground‐based	atmospheric	measurement	field	campaign	instruments	just	noted)	appear	to	

be	 primarily	 used	 for	 instrument	 calibration	 and	 some	 limited	 science	 for	 understanding	

fundamental	physics	on	a	small	scale,	e.g.,	cloud	microphysics.		Examples	of	some	processes	

that	could	benefit	from	highly	controlled	laboratory	experiments	are	briefly	summarized	in	

a	later	section	of	this	report.	
14

Summary of the State of the Art for Ground-Based Experimental Laboratories 

A	review	of	the	literature	reveals	that	the	state	of	ground‐based	facilities	for	experimentally	

simulating	 and	 studying	 cloud	 phenomena	 (excluding	 those	 for	 instrument	 calibration,	

small‐scale	 experiments,	 and	 educational	 instruction)	 is	 at	 a	 low	 ebb,	 	 far	 more	

conspicuously	 in	 the	 U.S.	 than	 in	 Europe.	 	 The	 appendix	 of	 this	 report	 summarizes	 the	

facilities	 that	 were	 identified	 during	 a	 recent	 literature	 survey.	 	 While	 this	 list	 is	 not	

exhaustive,	it	does	provide	a	good	indication	of	breadth,	location,	and	overall	capabilities	of	

current	facilities.	

In	 the	 U.S.,	 while	 fairly	 large	 facilities	 (e.g.,	 cloud	 chambers)	 were	 in	 use	 during	 past	

decades,	few	if	any	of	these	appear	to	be	operational	today.		In	the	mid	20th	century,	cloud	

chamber	 laboratory	 facilities	 of	 various	 types	 and	 sizes	 were	 relatively	 common,	

contributing	much	to	the	understanding	of	cloud	microphysics.		In	the	later	portions	of	the	

20th	century,	interest	shifted	into	the	emerging	numerical	simulation	arena	as	a	companion	

to	 field	 campaigns	 and,	 in	 the	 U.S.,	 cloud	 chamber	 and	 other	 laboratory	 studies	 were	

deemphasized	and	most	were	decommissioned.		A	workshop	on	“The	Future	of	Laboratory	

Research	 and	 Facilities	 for	 Cloud	 Physics	 and	 Cloud	 Chemistry”	 (Ref.	 30)	 was	 held	 at	

Boulder,	 Colorado	 in	 1985.	 	 The	 report	 from	 that	 workshop	 states	 that	 “...laboratory	

research	over	the	past	two	decades	(i.e.,	since	the	1960s)	has	declined	to	such	an	extent	that	

scientific	 progress	 toward	 understanding	 many	 processes	 occurring	 in	 the	 atmosphere	 is	

being	impeded”.		Additionally	stated	in	that	report	is	the	following	conclusion:	“Triple	(i.e.,	

two	 types	 of	 precipitation	 particles	 and	 cloud)	 and	 triple‐plus	 interactions	 need	 to	 be	

understood	 and	 facilities	 with	 new	 capabilities	 are	 required	 to	 carry	 out	 the	 necessary	

studies;	these	points	are	certain.		Many	of	the	problems	and	costs	involved	in	tackling	triple	

and	triple‐plus	interactions	with	new	equipment	may	demand	a	consolidation	of	resources	

into	a	single	National	Facility,	or	a	set	of	facilities	that	would	be	suitable	for	a	wide	variety	of	

experimental	work	that	cannot	be	undertaken	with	existing	facilities.”		The	report	goes	on	to	

recommend	 facilities	 in	 the	 80m	 to	 120m‐size	 range	 to	 enable	 studies	 of	 cloud‐aerosol	

interactions,	as	illustrated	in	Figure	4.			

More	 recently,	 Reference	 31	 indicates	 that	 10m	 clouds,	 a	 size	 that	 could	 be	 studied	 in	 a	

100m	 facility,	are	of	interest	to	atmospheric	aerosol‐cloud	interaction	dynamics.		Also,	"To	

study	clouds	and	aerosols	one	must	deal	with	processes	occurring	and	interacting	in	more	

than	12	orders	of	magnitude,	changes	on	the	microphysical	clouds	(6m‐10m)	may	produce	

dramatic	changes	on	the	regional	climate	and	whole	hydrological	cycle”	(Ref.	32).	
15

In	the	intervening	twenty‐six	years	since	the	laboratory	workshop	cited	in	Reference	30	was	

held,	 climate	 change	 concerns	 have	 become	 both	 more	 worrisome	 and	 more	 immediate,	

with	concomitant	requirements	for	ever‐more‐accurate	climate	projections	at	the	regional		

and	global	levels.		Also	during	this	timeframe,	cloud	chamber	laboratory	climate	studies	in	

the	 U.S.	 have	 even	 further	 atrophied.	 	 The	 promise	 shown	 by	 advanced	 atmospheric	

simulation	techniques	(both	as	a	predictive	tool,	and	as	a	way	to	make	those	predictions	at	

lower	 cost	 than	 via	 ground‐based	 experiments),	 coupled	 with	 availability	 of	 "current	

atmosphere"	data	from	sophisticated	in	situ	and	remote‐sensing	field	measurements,	was	a	

primary	driver	for	this	shift	in	emphasis.			However,	in	hindsight,	it	is	clear	that	high	fidelity	

climate	 predictions	 must	 rely	 on	 a	 "three	 legged	 stool"	 of	 field	 measurements,	

modeling/simulation,	 and	 sophisticated	 laboratory	 experimentation,	 and	 that	 the	 de‐

emphasis	of	the	latter	over	the	past	few	decades	has	resulted	in	an	"out	of	balance"	situation	

that	is	hampering	predictive	capability	just	when	it	is	needed	most.	

A	 direct	 analogy	 to	 the	 situation	 in	 climate	 prediction	 is	 the	 imminent	 demise	 of	

aerodynamic	 wind	 tunnels	 that	 was	 predicted	 with	 the	 advent	 of	 sophisticated	

computational	 fluid	 dynamic	 (CFD)	 codes	 for	 solving	 the	 Navier‐Stokes	 equations	 that	

began	 in	 the	 1970s	 ("there	 will	 be	 no	 need	 for	 wind	 tunnels	 within	 ten	 years..."),	 and	

continued	in	 the	decades	 that	 followed.		However,	in	 the	 forty	years	since	then,	while	CFD	

has	made	 great	inroads	into	 high‐fidelity	aerodynamic	 prediction	and	many	wind	 tunnels	

have	 closed	 (more	 due	 to	 a	 significant	 reduction	 in	 the	 number	 of	 aircraft	 development	

efforts,	 e.g.,	 due	 to	 the	 end	 of	 the	 Cold	War,	 than	 to	 a	 reduction	 in	 need	 for	 high‐fidelity	

experimental	 data	 in	 any	 given	 project),	 it	 appears	 that	 the	 aerospace	 community	 is	

1

2

Figure 4. Concept for a national cloud and precipitation research facility from 1985 

facilities workshop. 1: diameter 80m, height 120m, 2: diameter 120m, height 60m. (Ref. 30)
16

realizing	that	this	assumption	was	premature	and	shortsighted,	and	that	some	minimum	set	

of	wind	tunnels	will	be	required	for	decades	to	come	for	conducting	controlled	experiments	

for	advanced	aerodynamic	modeling,	validation	and	calibration	of	computational	tools,	and	

database	development	for	configurations	in	flow	regimes	in	which	CFD	is	not	yet	capable	of	

providing	 the	 "final	 answer"	 prior	 to	 flight.	 	 So,	 while	 Boeing	 used	 CFD	 to	 significantly	

reduce	 the	 number	 of	 wing	 sets	 that	 were	 wind	 tunnel	 tested	 for	 the	 787	 Dreamliner	

compared	to	earlier	aircraft,	it	could	not	have	accomplished	the	task	without	the	concurrent	

use	of	high	quality	experimental	data	from	large	wind	tunnels,	both	for	data	generation	and	

for	 computational	 tool	 validation.	 	 Climate	 prediction	methods	 appear	 to	 have	 followed	 a	

path	similar	 to	 that	of	 the	aerospace	community,	but	have	gone	even	 farther	in	 that	 there	

are	few	if	any	large	experimental	facilities	in	operation	today.		

Needless	 to	 say,	 the	 suggested	100m	class	 facilities	called	 for	at	 the	1985	workshop	were	

never	 constructed.	 	 There	 have	 been	 attempts	 to	 secure	 funding	for	 larger	 scale	 facilities	

(i.e.,	 larger	 than	 contemporary	 facilities),	 but	 to‐date	 none	 of	 these	 proposals	 has	 been	

successful	 (Ref.	 33).	 	 Besides	 cloud	 chambers,	 other	 facilities	 such	 as	 specially	 designed	

vertical	 wind	 tunnels	 have	 been	 used	 to	 simulate	 the	 dynamics	 of	 raindrops	 and	 other	

particulates	 in	 the	 atmosphere	 (e.g.,	 Refs.	 34‐36).	 	 While	 not	 emphasized	 in	 this	 report,	

improved	wind	tunnel	capability	for	studying,	e.g.,	aerosol	particle	and	ice	crystal	formation	

and	growth,	should	also	be	considered.	

		

In	 Europe	 the	 situation	 appears	 to	 be	 somewhat	 better	 (Ref.	 37),	 with	 updated	 cloud	

chambers	being	built	and	utilized	for	climate	issues,	but	these	are	far	smaller	than	the	100m	

class	facilities	called	out	in	the	1985	laboratory	workshop.		European	Simulation	Chambers	

for	Investigating	Atmospheric	Processes	(EUROCHAMP‐2)	is	a	highly	integrated	consortium	

of	 sixteen	 chamber	 facilities	 operated	 by	 fourteen	 partner	 organizations	 from	 eight	

European	 countries	 organized	 in	 2009	 as	 a	 follow‐on	 to	 EUROCHAM‐1	 (2004	 ‐	 2009).		

Although	there	are	no	EUROCHAMP	facilities	that	approach	the	scale	of	that	being	discussed	

in	 this	 report,	 there	 are	 some	 relatively	 large	 chambers	 of	 recent	 vintage.	 	 The	 largest	

appears	to	be	Aerosols	Interaction	and	Dynamics	in	the	Atmosphere	(AIDA)37,	38	in	Germany	

for	studying	cloud	dynamics	and	cloud‐aerosol	interactions	on	a	small	scale.		This	chamber	

(Fig.	5)	has	a	volume	of	85	m3,	a	 temperature	range	of	 ‐90	 oC	 to	+50	 oC,	reduced	pressure	

capability,	 can	 introduce	 trace	 gasses,	 and	 has	 highly	 sophisticated	 instrumentation,	

allowing	AIDA	to	carry	out	aerosol	and	cloud	experiments	over	a	full	range	of	tropospheric	

and	stratospheric	temperatures	and	pressures.	

Another	 example	 of	 a	 modern	 facility	 is	 LACIS,	 or	 Leipzig	 Aerosol	 Cloud	 Interaction	

Simulator	operated	by	the	Leibniz	Institute	for	Tropospheric	Research	in	Germany (Ref.	39).		

This	 facility	 is	 highly	 specialized	 to	 study	 cloud‐aerosol	 interactions.	 	 LACIS	 consists	 of	 a	
17

large	 outer	 shell	 containg	 a	 highly	instrumented	 flow	 tube.	 	 The	 exterior	 of	 the	 facility	is	

shown	in	Figure	6.		The	temperature	capabilty	of	the	facility	is	‐60	oC	to	+40	oC.	

 Figure 5. AIDA cloud chamber (Ref. 38, public domain image 

 courtesy of Karlsruhe Institute of Technology) 

Figure 6. LACIS cloud-aerosol interaction facility (Ref. 39, public 

domain image courtesy of Dr. Frank Stratmann/EUROCHAMP) 
18

Some High-Level Facility Requirements for Cloud Research via Ground-Based 

Laboratories 

Clearly,	depending	on	the	intended	use	of	the	facility,	a	"cloud	chamber"	can	take	on	one	of	

several	 incarnations.	 	 For	 example,	 as	 noted	 earlier,	 specialized	 vertical	 wind	 tunnels,	 or	

"cloud	tunnels"	have	been	successfully	used	to	simulate	processes	such	as	rain	drop	and	ice	

crystal	 formation	 and	 dynamics	 within	 clouds.	 	 However,	 a	 ground	 facility	 for	

experimentally	simulating	an	actual	cloud	(even	a	small	one)	would	necessarily	have	to	be	

quite	large.		If	it	is	assumed,	e.g.	as	in	Reference	31,	that	clouds	with	length	scales	as	small	as	

10m	play	an	important	role	in	climate	physics,	then	a	facility	with	dimensions	5	to	10	times	

the	 cloud	 scale	 might	 be	 required	 to	 keep	 wall	 effects	 and	 other	 unwanted	 influences	 to	

acceptable	 levels	 during	 experiments.	 	 Also,	 wall	 temperatures	 would	 likely	 have	 to	 be	

precisely	regulated	in	order	 to	provide	conditions	 for	conducting	meaningful	experiments.		

This	 high	 degree	 of	 temperature	 control	 could	 be	 accomplished	 via	 the	 use	 of	 super‐

insulated	 walls,	 active	 temperature	 regulation,	 or	 a	 combination	 of	 the	 two	 methods.		

Additionally,	 the	 need	 for	 specialized	 instrumentation,	 possibly	 sophisticated	 flow	 (and	

phase)	control,	and	other	considerations	would	have	to	be	taken	into	account.		A	sampling	of	

the	 physical	 mechanisms	 and	 processes	 requiring	 improved	 discovery,	 quantification	 as	

well	as	modeling	and	V&V,	individually	and	in	 various	concert	using	laboratory	chambers	

includes	(but	is	not	limited	to):	

 Gas	phase	photo‐chemical	reactions	of	volatile	organic	compounds,	including	effects	

of	inorganic	 acids	 on	 secondary	 organic	 aerosol	 size	 and	mass,	 and	 heterogeneous	

chemical	reactions	

 Effects	of		innately	anisotropic	turbulence	upon	cloud	condensation	nuclei	(CCN)	and	

ice	 forming	 nuclei	 (IFN),	 i.e.,	 micro‐scale	 turbulence	 accelerates	 cloud	 formation,	

changes	collision	 frequency	and	 triggers	precipitation,	and	 turbulence	causes	 rapid	

growth	in	droplet	size.	

 Dampening	effects	of	aerosols	upon	turbulence	

 Discovery	and	modeling	regarding	 the	physics,	etc.,	associated	with	 the	initiation	of	

precipitation,	especially	for	ice	clouds	

 Ice	 nucleation	 mechanisms,	 including	 the	 inhibiting	 effects	 of	 organic	 content,	 the	

efficiency	of	lead‐containing	particles,	etc.	

 Trace	gas	effects,	including	concentrations	of	nitric	acid	(HNO3)	on	CCN	number	and	

effectiveness,	and	impacts	upon	hygroscopicity	

 Effects	 of	 dynamic	 motions,	 convection,	 and	 shear,	 at	 the	 cloud	 and	 larger	 scales	

upon	 aerosol	 interactions	 and	 behavior,	 including	 coalescence,	 evaporation,	
19

collisions,	 coagulation,	 condensation,	 activation,	 glaciation,	 aggregation	 and	

sedimentation	

 Possibility	 of	 major	 effects	 of	 cosmic	 rays	 and	 ion‐induced	 nucleation	 and	 electro‐

scavenging	 on	 ice	 formation,	 along	 with	 effects	 of	 solar	 radiation	 and	 photo‐

chemistry	

 Effects	of	solar	heating	of	black	carbon	aerosols	upon	their	activation	into	drops	and	

CCN	effectiveness	

 Effects	of	film‐forming	compounds	upon	CCN	effectiveness	

 Atmospheric	and	 self‐induced	electric	 field	effects	 (including	lightning)	 on	collision	

frequency	 and	 ice	 nucleation.	 	 Some	 observations	 indicate	 greatly	 enhanced	 ice	

nucleation.	

 Aerosol	effects	upon	cloud	cellular	convection	

 Aerosol	effects	upon	cloud	formation	mechanisms	(gravity,	Parker‐Jeans,	collisional,	

etc.)	and	turbulence	in	clouds	

 Aerosol	effects	upon	cloud	radiation	influences	,	writ	larg	

 Aerosol	effects	on	cloud	"edge"	dynamics	and	details	

 Effects	of	biologics	on	CCN	including	surface	chemistry,	hygroscopicity,	and	contact	

angle	alterations	

 Methane	influences	on	sulfate	and	production	of	other	aerosols	

The	 major	 cloud‐aerosol	 interaction	 processes	 to	 be	 simulated	 include	 agglomeration,	

coagulation,	 coalescence,	 the	 various	 phase	 changes	 including	 areas	 with	 significant	

knowledge	gaps	such	as	ice	cloud	formation,	nucleation,	deposition,	catalysis,	electrification,	

chemical	changes	writ	large,	and	convection	(including	turbulence	and	precipitation).		The	

independent	 parameter	 spaces	 include	 altitude/pressure,	 temperature,	 moisture,	

convection/turbulence,	 radiation	 (including	 ultraviolet	 and	 cosmic	 rays),	 chemical	

composition(s),	 initial	 aerosol	 compositions/size/geometry/number	 density,	 electrostatic	

fields,	 various	 “bio	 effects”,	 and	 doubtless	 others.	 	 Clearly,	 there	 are	 myriad	 physical	

mechanisms	 and	 processes	 related	to	 clouds,	 precipitation,	 aerosol	 interactions,	 etc.,	 that	

are	not	as	yet	well	understood	which	could	benefit	greatly	 from	study	in	a	highly‐capable,	

well‐designed	laboratory	(why	does	precipitation	occur?	how	do	ice	clouds	form	and	grow?		

do	 we	 fully	 understand	 the	 impact	 of	 the	 biologics,	 e.g.,	 bacteria,	 algae,	 pollen,	 on	

atmospheric	chemistry	and	dynamics?).	
20

In	Reference	40,	it	is	stated	that	“Since	ice	formation	in	clouds	is	not	yet	fully	understood	it	

is	recommended	that	 further	laboratory studies	and	in	situ	measurements	be	conducted	to	

clarify	 the	 nucleation	 mechanisms”	 (emphasis	 added).	 	 Similarly,	 from	 Reference	 18:	

“Obviously	 deconvoluting	 the	 relative	 impact	 of	 each	 property	 on	 CCN	 activation	 is	more

straight forward in well controlled laboratory experiments".	 	 Also,	 “In	 contrast	 to	 field	

observations,	laboratory	 studies	 allow	 one	 to	 examine	 (ice)	 crystal	 growth	 processes	 and	

the	 effect	 of	 each	 environmental	 variable	 under	 controlled	 conditions”	 (Ref.	 41).	 	 And	

“Significant	advances	in	laboratory	data	and	modeling	techniques	are	needed	for	a	number	

of	important	aerosol	systems”	(Ref.	17).		Thus,	laboratory	studies	are	essential	for	providing	

necessary	information	for	input	into	more	detailed	atmospheric	models”.	

In	 their	 2010	 Atmospheric	 System	 Research	 Science	 and	 Program	 Plan	 (Ref.	 6),	 the	 DOE	

Office	of	Science	devoted	significant	attention	to	the	need	for	better	laboratory	facilities	for	

cloud	and	aerosol	studies,	such	as:	“Laboratory	studies	are	essential	to	unraveling	processes	

involving	chemical	reactions	and	composition‐dependent	aerosol	microphysical	properties”	

and	“What	is	clearly	needed	to	advance	understanding	of	cloud	as	well	as	aerosol	formation	

is	a	dedicated	consolidated	laboratory	facility	in	the	U.S.	capable	of	conducting	experiments	

under	 controlled	 conditions....such	 a	 facility	 would	 be	 a	 bold	 breakthrough‐science‐type	

initiative	 that	would	lay	a	 firm	 foundation	 for	 systematically	improving	cloud	and	aerosol	

processes/properties	modules	as	well	as	serve	as	an	incubator	for	the	development	of	new	

cloud	and	aerosol	instruments	designed	for	field	deployment”.	

To	 the	 extent	 that	 the	 various	 scientific	 and	 modeling	 shortfalls	 and	 physical	 issues		

discussed	herein	are	affected	by	cloud‐level	turbulence	and	convection,	a	large‐scale	cloud	

chamber/laboratory	appears	to	be	required	to	conduct	controlled	experiments,	as	noted	in	

Reference	 42:	 	 “One	 principle	 continuing	 difficulty	is	 that	 of	incorporating,	in	a	 physically	

realistic	manner,	the	microphysical	phenomena	in	the	broader	context	of	the	highly	complex	

macrophysical	 environment	 of	 natural	 clouds”.	 	 While	 it	 is	 recognized	 that	 a	 parametric	

approach	 can	 become	 so	 far	 removed	 from	 the	 situation	 of	 interest	 that	 it	 is	 no	 longer	

useful,	the	long	history	of	ground‐based	laboratory	experiments	in	any	number	of	scientific	

disciplines	shows	that	meaningful	results	that	provide	a	better	understanding	of	underlying	

physics	are	obtainable	via	thoughtful	experiment	design.	

The	 motion	 of	 air	 within	 clouds	 is	 in	 general	 turbulent,	 and	 the	 characteristics	 of	 this	

turbulence	 are	 a	 function	 of	 the	 details	 of	 cloud	 formation,	 interactions,	 and	 internal	

dynamics.	 The	 literature	 concerning	 the	 effects	 of	 this	 turbulence	 upon	 cloud‐aerosol	

interactions	indicates	the	following	(refs.	43	to	47):	

 Cloud	turbulence	applicable	to	droplet	scales	is	substantially	

anisotropic	due	to	localized	actions	of	buoyancy	&	evaporation	
21

 Turbulence	affects	particle‐droplet	collision	and	coalescence	processes,	

greatly	changes	localized	relative	velocities,	and	triggers	rain	showers	

 Higher	levels	of	turbulence	result	in	faster	droplet	growth	and	condensation,	where	

the	increases	are	a	function	of	turbulence	amplitude	and	other	detailed	characteristics	

 The	vertical	transport	of	aerosols	can	be	dominated	by	turbulence	

 Turbulence	bridges	droplet	growth	by	condensation	and	coagulation	

 Turbulence	contributes	to	the	formation	of	high	ice	crystal	concentration	

 "Without	turbulence	only	7%	of	the	total	mass	was	observed	in	droplets	

with	sizes	over	100	microns,	while	with	moderate	turbulence	this	increased	

to	79%"	(ref.	43)	

Overall,	the	interactions	between	cloud	microphysics	and	turbulence	have	not	been	studied	

in	detail,	and	would	benefit	from	the	availability	of	a	highly	capable	ground	facility.		Based	

on	existing	techniques	in	current	wind	tunnels	and	other	research	facilities,	it	is	feasible	to	

generate	 and	 control	 air	 turbulence	 of	 varying	 scales,	 frequencies,	 amplitudes,	 etc.,	 for	

parametric	 studies	 in	 a	 cloud	 chamber.	 	 Potential	 techniques	 include	 production	 of	 local	

shear/convection,	 “artifactual”	turbulence	 (i.e.,	 turbulence	 generated	 outside	 the	 chamber	

and	 "injected"),	 and	 utilization	 of	 other	 turbulence	 production	 approaches	 including	

buoyancy,	localized	heating,	chemical	reactions,	and	possibly	application	of	magnetic	fields.	

Turbulence	 is	 generated	 in	 many	 ways	 in	 both	 nature	 and	 by	 technology,	 and	 these	

mechanisms	 should	 be	 studied	 to	 identify	 and	 select	 the	 most	 promising	 candidates	 for	

providing	dynamic	fields	in	the	ranges	required.		A	detailed	study	must	be	conducted	with	

regard	to	the	type(s)	of	turbulence	required	(scale	ranges,	degree	of	anisotropy,	functional	

dependence	on	velocity	and	temperature	fields,	discrete	dynamic	features,	etc.	‐	all	of	which	

have	been	found	to	be	important	for	understanding	cloud‐aerosol	interactions)	and	the	best	

methods	for	generating	such	turbulence	in	a	chamber.		Such	a	study	would	be	a	foundational	

step	toward	realizing	a	large	laboratory	for	cloud‐aerosol	research.	

Clearly,	 the	 literature	 has	 many	 examples	 of	 major	 gaps	 in	 the	 knowledge	 necessary	 to	

adaquately	model	cloud‐aerosol	effects	for	both	regional	and	global	climate	projections.		It	is	

recognized	 that	 no	 single	 ground	 facility	 can	 duplicate	 the	 myriad	 complex	 interactions	

found	in	nature,	or	even	some	of	the	most	difficult	phenomena	individually	(e.g.,	cloud‐top	

radiative	cooling	as	a	driving	mechanism	for	turbulence),	but	with	the	still	ambitous	goal	of	

conducting	high‐fidelity	experiments	 on	 unit	 problems	in	a	large	 chamber,	 there	is	a	 very	

detailed	set	of	capabilities	required,	including	the	capacity	to independently	vary	turbulence	

dynamics	(shear,	level,	scale,	etc.)	and	a	host	of	other	parameters.		Additional	major	“issues”	
22

that	need	to	be	addressed	to	enable	relevant	unit	experiments	include	wall	effects	(thermal,	

radiation,	 convection)	 and	 reconciling	 dynamic	 interactions	 at	 scales	 (Reynolds	 number)	

beyond	those	achieveable	in	even	a	100m	class	chamber.		However,	it	is	worth	noting	that	a	

tremendous	amount	of	 the	requisite	research	regarding	 these	issues	could	be,	and	should,	

be,	conducted	in	small(er)	scale	chambers.	

A Potential Approach to a Large Chamber for Cloud‐Aerosol Research

Although	 a	 ground	 facility	 for	 simulating	 even	 small	 clouds	 could	 be	 massive,	 precedent	

exists	for	the	construction	of	the	basic	shell	of	such	a	facility.		Clearly	wall	effects	(thermal,	

fluid	 boundary,	 etc.)	 would	 need	 to	 be	 minimized.	 	 It	 is	 assumed	 that	 fluid	 boundary	

conditions	can	be	mitigated	both	by	the	scale	of	the	facility	(i.e.,	keeping	the	area	of	interest	

a	 sufficient	 distance	 from	 the	 walls)	 and	 by	 applying	 flow‐control	 technologies	 if	 needed.		

Strict	control	of	heat	transfer	for	establishing	and	maintaining	thermal	boundary	conditions	

might	be	accomplished	via	the	use	of	highly	insulated	walls,	active	temperature	regulation,	

or	a	combination	of	the	two.		

If	 very	 large	 scales	 and	 extremely	 efficient	 insulation	 are	 required	 for	 such	 a	 facility,	 a	

precedent	 exists	 in	 the	 petroleum	 industry,	 which	 has	 been	 constructing	 ever‐larger	

cryogenic	storage	facilities	for	liquefied	natural	gas	(LNG)	since	the	1960s.		Current	state‐of‐

the‐art	 storage	 facilities	 have	 volume	 capacities	 in	 the	 2x105	 m3	 range	 and	 can	 store	

liquefied	methane	at	 ‐160	 oC	at	atmospheric	pressure	with	a	minimum	of	"boil	off"	due	 to	

superb	insulation	characteristics.			Typical	construction	consists	of	a	pre‐stressed	concrete	

outer	 shell,	 a	 high‐performance	 insulation	 blanket,	 and	 an	 inner	 nickel	 alloy	 shell.	 	 An	

example	of	a	one	of	the	largest	 facilities	in	existence	is	El	Paso	Corp.'s	Elba	Island,	Georgia	

facility	with	a	 diameter	 of	 88m	 (similar	 to	 the	 LNG	 tank	 shown	in	 Figure	 7).	 	 Even	larger	

facilities	are	being	proposed,	such	as	a	Japanese	design	for	a	95m‐diameter	tank	shell.	

It	is	difficult	to	determine	how	much	of	the	cost	of	such	an	LNG	storage	facility	is	germane	to	

a	potential	large	cloud	chamber	since	it	is	unknown	how	much	of	the	cost	of	these	facilities	

is	related	to	specific	technical	or	regulatory	requirements,	industry‐specific	equipment,	etc.		

Additionally,	 unit	 cost	 estimates	 for	 existing	 and	 proposed	 facilities	 available	in	 the	 open	

literature	are	scarce.		A	2006	publication (Ref.	48)	states	that	unit	volume	costs	for	an	LNG	

storage	 facility	 is	 in	 the	 $400/m3	 range.	 	 The	 88m‐diameter	 Elba	 Island	 tank	 has	 an	

approximate	 gross	 volume	 of	 2.3x105	 m3,	 resulting	 in	 an	 estimated	 (tank	 only)	 cost	 of	

$92x106.	 	 Conversely,	 a	 smaller	 facility	 (the	 62m	 diameter	 LNG	 tank	 at	 Mt.	 Hayes,	 B.C.,	

Canada,	Ref.	49)	was	completed	in	the	late	2000s	and	has	a	cost	2007	estimate	(couched	as	a	

90%	 confidence	 estimate	 since	 the	 facility	 was	 not	 completely	 finished	 at	 the	 time	 of	 the	

writing	of	the	report)	given	as	$186	x106.		Given	the	spread	of	these	two	figures,	it	is	clear	

that	 significantly	 more	 research	 will	 be	 required	 to	 formulate	 a	 more	 precise	 estimate.		
23

Clearly,	 if	 a	 smaller	 scale	 facility	 with	 less	 extreme	 insulation	 characteristics	 is	 deemed	

adequate,	then	it	follows	that	the	cost	of	the	basic	structure	could	be	lower	than	that	for	the	

LNG	storage	tank	analogy	used	here.	

Beyond	a	suitable	containment	structure,	equipment	 for	producing	 the	desired	 fluid	states	

and	conditions	for	particular	experiments,	and	instrumentation	are	the	most	critical	aspects	

of	the	facility.		While	there	will	be	no	attempt	to	produce	an	exhaustive	list,	it	is	clear	that	a	

large	suite	of	sophisticated	equipment	and	instruments	would	be	 “core”	 to	practically	any	

experiment	that	could	be	envisioned.		As	a	starting	point,	the	descriptions	of	the	European	

facilities	 noted	 above	 (particularly	 Refs.	 38	 and	 39)	 provide	 insight	 for	 the	 beginnings	 of	

such	a	list:	

 Temperature	control	

 Humidity	control	

 Flow	conditioning	(setting	desired	flow	state,	control	of	wall	effects,	generation	and	

control	of	turbulence	scale	and	intensity,	etc.)	

 Aerosol	generation	

 Water	droplet/ice	crystal	injectors/other	particle	injectors	

 Spectrometers	(infrared,	particle,	mass,	etc.)	

Figure 7. Example of Large Cryogenic Storage Tank for Liquified Natural Gas 

(public domain image courtesy of ferc.gov)
24

 Particle	 counters	 and	 sizers	 (condensation	 particle	 counters,	 cloud	 condensation	

nucleus	counters,	etc.)	

 Particle	imagers	and	trackers	

 Differential	mobility	analyzers	

 Gas	chromatagraphs	

 Hygrometers	

 Trace	gas	analyzers/monitors	

Ultimately,	the	user	community	will	drive	sensor	and	instrumentation	requirements,	so	the	

facility	will	have	to	be	designed	with	the	flexibility	to	adapt	other	more	specialized	devices	

on	 an	 as‐needed	 basis.	 	 For	 example,	 in	 such	 a	 large	 facility,	the	 need	 to	 track	 individual	

trajectories	within	large	groups	of	interacting	particles	will	be	a	key	capability.		Equally	as	

important,	sensors	are	poised	 for	a	revolution	in	miniturization,	cost	reduction,	capability,	

and	speed,	making	it	likely	that	by	the	time	a	large	facility	could	be	designed	and	built,	much	

better	 technology	 in	 this	 area	 can	 be	 leveraged	 to	 improve	 the	 scientific	 experiemnts	

conducted.	

Clearly,	a	large,	highly	instrumented	facility	with	many	unique	capabilities	would	have	many	

uses	 other	 than	 direct	 cloud‐aerosol	interaction	 discovery	 and	modeling.	 	 Other	 potential	

uses	in	terrestrial	climate	science	include,	but	are	not	limited	to,	instrumentation	and	sensor	

development	for	field	measurement	campaigns,	direct	validation	and	calibration	numerical	

simulations,	studies	of	 the	impacts	of	aircraft	operations	upon	climate,	 “pollution”	studies,	

and	ideation	of	approaches	to	mitigate	climate	change	including	emissions	designed	to	alter	

hygroscopicity	 to	 enhance	 aerosol	 negative	 feedback	 (as	 one	 example).	 	 Additionally,	

atmospheric	 studies	 of	 planets	 and	 moons,	 free	 space	 optical	 communication	 through	

clouds,	and	many	other	important	and	useful	 technologies	could	be	enabled	in	a	 facility	of	

this	type	if	the	right	disciplene	constituencies are engaged.

Next Steps

This	 report	articulates	 the	 need	and	 high‐level	 requirements	 for	a	large	ground	 facility	 to	

compliment	and	augment	current	and	 future	atmospheric‐science	 field	measurments	with	

the	 goal	 of	 strengthening	 the	 understanding	 of	 clouds	 and	 cloud‐aerosol	 interactions	 and	

their	 impact	 on	 prediction	 of	 climate	 change.	 	 There	 is	 ample	 evidence	 in	 the	 recent	

technical	literature	 that	 there	are	many	major	gaps	in	state‐of‐the‐art	modeling	of	climate	

dynamics	on	regional	and	global	scales,	and	that	these	gaps	are	(and	will	continue)	hobbling	

our	 ability	 to	 predict	 future	 climate	 states	 with	 the	 accuracy	 and	 precision	 needed	 for	

decision	makers	to	optimally	deploy	resources.			
25

A	concensus	among	the	climate	science	experts	needs	to	be	reached	before	further	progress	

can	 be	 made.	 	 A	 workshop,	 along	 the	 lines	 of	 the	 1985	 gathering	 noted	 in	 Reference	 30,	

could	be	convened	to		update	and	refine	both	the	need	and	more	detailed	requirements	for	a	

large	 ground	 facility.	 	 It	is	 suggested	 that	 a	 "virtual	 workshop",	 similar	 to	 that	 used	 for	 a	

recent	modeling	and	simulation	state‐of‐the‐art	assessment	(Ref.	50)	is	an	efficient	way	 to	

gather	 inputs	 from	 a	 large,	 geographically	 dispersed	 group	 of	 participants.	 	 However,	 a	

traditional	"face	to	face"	workshop	can	also	be	accomplished	if	that	approach	is	found	to	be	

preferable.		 If	 the	scientific	community	endorses	a	large	scale	chamber,	next	steps	are	 the	

specification	 of	 the	 capabilities	 and	 parameter	 ranges	 to	 be	 "designed	 in",	 evaluation	 of	

candidate	engineering	approaches,	and	rough	order	of	magnitude	(ROM)	cost	estimates.	

Conclusions

Based	on	a	review	of	the	literature,	it	appears	that	many	researchers	in	the	climate	science	

field	are	in	agreement	that	highly‐fidelity	climate	change	projections	are	highly	dependant	

upon	 cloud‐aerosol	 interactions	 and	 that	 modeling,	 and	 indeed	 even	 understanding,	 such	

interactions	are	at	the	present	time	in	a	grossly	unsatisfactory	state.		There	are	myraid	2,	3,	

and	 4‐phase	 phenomena	 that	 are	 dependent	 upon	 details	 of	 specific	 chemistry,	 radiation,	

and	 numerous	 other	 parameters	 including	 turbulence	 that	 require	 detailed	 study	 and	

understanding.	 	 Such	 detailed	 scientific	 work	 is	 extremely	 difficult	 to	 conduct	 with	 data	

extracted	from	field	campaigns	alone.	

There	is	an	immense	amount	of	laboratory	research	required	to	approach	the	accuracy	and	

precision	needed	 for	believeable	climate	projections	going	 forward.		 It	is	of	interest	 that	a	

large‐scale	 chamber,	 necessary	 to	 begin	 to	 sort	 out	 the	 cloud	 level	 changes	 in	 aerosol	

impacts,	 physics,	 and	 behaviors,	 would	 probably	 take	 the	 better	 part	 of	 a	 decade	 to	

authorize	and	construct.	 In	 that	same	 time	 frame	 the	computing	machines	will	advance	 to	

the	exaflop	stage,	which	is	still	far	less	capability	than	needed	to	ab‐initio	simulate	all	of	the	

multitudinous	 cloud	 and	 aerosol	 issues.	 	 Thus,	 modeling	 will	 be	 required	 for	 decades	 to	

come,	 making	 climate	 change	 prediction	 an	 "experimental	 science".	 	 A	 key	 part	 of	 that	

experimental	 effort	 needs	 to	 be	 a	 resurgence	 of	 serious,	 detailed,	 and	 creative	laboratory	

studies.		It	is	upon	the	need	for	discovery	and	modeling	of	these	cloud‐level	interactions	that	

the	justification	 for	a	100m	class	cloud	chamber	 rests.		The	 overall	justification	 for	cloud‐

aerosol	 interaction	 research,	 for	 both	 discovery	 and	 modeling,	 could	 not	 be	 stronger	 as	

exemplified	 by	 this	 quote	 from	 Reference	 51:	 	 “(The	 study's	 author)	 has	 shown	 that	 in	

model	runs	using	an	AGCM,	the	warming	effect	of	doubling	CO2	concentration	may	be	offset	

by	reducing	an	assumed	(cloud)	droplet	effective	radius	of	10	microns	 to	a	value	between	

7.9	 and	 8.6	 microns”.	 	 In	 other	 words,	 a	 change	 in	 the	 assumed	 magnitude	 of	 an	 cloud	

parameter	in	a	climate	model	of	only	15%	to	20%	has	the	potential	to	mask	the	projected	

impact	 of	large	 changes	in	greenhouse	gas	 concentration.	 	 It	is	 clear	 that	we	 simply	must	
26

significantly	 improve	 the	 modeling	 of	 the	 cloud‐aerosol	 effects.	 	 Coupling	 a	 large,	 high‐

capability	 ground	 facility	 for	 advanced	 model	 development,	 science,	 and	 discovery	 with	

state‐of‐the‐art	 in	 situ	 field	 measurements	 offers	 a	 way	 to	 address	 climate	 change	 in	 a	

rational	manner.		

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Geophysics,	Vol.	27,	2009,	pp.	3989‐4007.	

22. Penner,	J.E.	et	al.:		Model	Intercomparison	of	Indirect	Aerosol	Effects.		Atmospheric

Chemistry and Physics,	Vol.	6,	2006,	pp.	3391‐3405.	
28

23. Lauer,	A.	et	al.:		Simulating	Marine	Boundary	Layer	Clouds	Over	the	Eastern	Pacific	in	

a	Regional	Climate	Model	With	Double‐Moment	Cloud	Microphysics.		Journal of

Geophysical Research	‐	Atmospheres,	Vol.	114,	D21205,	IPRC‐625,	2009.	

			

24. Tao,	W.‐K.	et	al.:		Role	of	Atmospheric	Aerosol	Concentration	On	Deep	Convective	

Percipitation:	Cloud	Resolving	Model	Simulations.		Journal of Geophysical Research	‐	

Atmohpheres,	Vol.	112,	D24S18,	2007.	

25. Abbatt,	J.P.D.	et	al.:		Solid	Ammonium	Sulfate	Aerosols	as	Ice	Nuclei:	A	pathway	For	

Cirrus	Cloud	Formulation.		Science,	Vol.	313,	22	Sept.	2006,	pp.	1770‐1773.	

26. Sassen,	K.,	and	Khvorostyanov,	V.I.:		Cloud	Effects	From	Boreal	Forest	Fire	Smoke:	

Evidence	For	Ice	Nucleation	From	Polarization	Lidar	Data	and	Cloud	Model	

Simulations.		Environmental Research Letters,	Vol.	3,	2008,	025006,	12	pp.	

27. Rosenfeld,	D.:		Aerosol‐Cloud	Interactions	Control	of	Earth	Radiation	and	Latent	Heat	

Release	Budgets.		Space Science Reviews,	2006,	Springer,	Vol.	125,	pp.	149‐157.	

28. Poschl,	U.,	Rudich,	Y.,	and	Ammann,	M.:		Kinetic	Model	Framework	For	Aerosol	and	

Cloud	Surface	Chemistry	and	Gas‐Particle	Interactions	–	Part	1:	General	Equations,	

Parameters	and	Terminology.		Atmos. Chem. Phys,	Vol.	7,	2007,	pp.	5989‐6023.		

29. Biello,	D.:		How	Close	Are	We	to	Catastrophic	Climate	Change?.	 Scientific American	‐	

Observations,	28	June	2010,	

http://www.scientificamerican.com/blog/post.cfm?id=how‐close‐are‐we‐to‐

catastrophic‐cl‐2010‐06‐28.	

30. List,	R.,	Hallett,	J.,	Warner,	J.,	and	Reinking,	R.:		The	Future	of	Laboratory	Research	

and	Facilities	for	Cloud	Physics	and	Cloud	Chemistry	‐	Report	on	a	Technical	

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31. Koren,	I.,	Oreopoulos,	L.,	Feingold,	G.,	Remer,	L.,	and	Altaratz,	O.:		How	Small	is	a	

Cloud?.		Atmospheric Chemistry and Physics,	Vol.	8,	2008,	pp.	3855	‐	3864.	

32. Koren,	Ilan:		"On	the	Link	Between	Cloud	Aerosol	Interaction	and	Climate	Change",	

Environmental	Sciences	and	Energy	Research,	Weizmann	Institute	of	Science,	

http://www.weizmann.ac.il/ESER/People/Ilan/research‐ilan.html.	

33. Helsdon,	J.:		"Re:		Underground	Cloud	Facility",	private	communication	to	D.	Bushnell,	

Sept.	8th,	2010.	

34. Vohl,	O.,	Mitra,	S.	K.,	Wurzler,	S.	C.,	and	Pruppacher,	H.	R.:	A	Wind	Tunnel	Study	of	the	

Effects	of	Turbulence	on	the	Growth	of	Cloud	Drops	by	Collision	and	Coalescence.		

Journal of the Atmospheric Sciences,	Vol.	56,	1999,	pp.	4088	‐	4099.	
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35. Wang,	P.	K.,	and	Pruppacher,	H.	R.:		Acceleration	to	Terminal	Velocity	of	Cloud	and	

Raindrops.		Journal of Applied Meteorology,	Vol.	16,	1977,	pp.	275‐280.	

36. Beard,	K.	V.,	and	Pruppacher,	H.	R.:		A	Wind	Tunnel	Investigation	of	the	Rate	of	

Evaporation	of	Small	Water	Drops	at	Terminal	Velocity	in	Air.		Journal of the

Atmospheric Sciences,	Vol.	28,	pp.	1455‐1464.	

37. Barnes,	I.,	and	Rudzinski,	K.	J.	(eds.):		Environmental Simulation Chambers:		

Application to Atmospheric Chemical Processes.		NATO	Science	Series	IV:		Earth	and	

Environmental	Series	‐	Vol.	62,	Springer,	2006.	

38. Anon.:	"AIDA	Chamber	Description",	http://www.eurochamp.org/chambers/aida/.	

39. Stratmann,	F.:	"Leipzig	Aerosol	Cloud	Interaction	Simulator	(LACIS)",	Leibniz	

Institute	for	Tropospheric	Research,	http://www.eurochamp.org/chambers/lacis/.	

40. Levin,	Z.,	and	Cotton,	W.R.	(eds.):		Aerosol Pollution Impact on Precipitation.		Springer,	

2009,	386	pp.	

41. Song,	N.,	and	Lamb,	D.:		Experimental	Investigations	of	Ice	in	Supercooled	Clouds.		

Part	1:	System	Description	and	Growth	of	Ice	by	Vapor	Deposition.		Journal of the

Atmospheric Sciences,	Vol.	51,	No.1,	Jan.	1994,	pp.	91‐103.	

42. Pruppacher,	H.	R.,	and	Klett,	J.	D.:		Microphysics of Clouds and Precipitation,	Kluwer	

Academic	Publishers,	1997.	

43. Riemer,	N.,	and	Wexler,	A.:		"Growing	Cloud	Droplets	in	Moderate	Turbulence",	BAMS

Vol.	86,	No.	5,	May	2005,	pp.	632‐633.	

44. Pinsky,	M.B.,	Khain,	A.P.:		"Turbulence	Effects	on	Droplet	Growth	and	Size	

Distribution	in	Clouds	‐	A	Review",	J. Aerosol Science,	Vol.	28,	No.	7,	Oct.	1997,	pp.	

1177‐1214.	

45. Gu,	Yu,	and	Liou,	K.N.:		"Interactions	of	Radiation,	Microphysics,	and	Turbulence	in	

the	Evolution	of	Cirrus	Clouds",	J. Atmos. Science,	Vol.	57,	August	2000,	pp.	2463‐

2479.	

46. Duru,	P.,	Koch,	D.L.,	and	Cohen,	C.:	"Experimental	Study	of	Turbulence‐Induced	

Coalescence	in	Aerosols",	International Journal of Multiphase Flows,	Vol.	33,	2007,	pp.	

987‐1005.	

47. Vohl,	O.,	et	al.:		A	Wind	Tunnel	Study	of	the	Effects	of	Turbulence	on	the	Growth	of	

Cloud	Drops	by	Collision	and	Coalescence",	Journal of Atmospheric Science,	Vol.	56,	

1999,	pp.	4088‐4099.	
30

48. Powell,	J.:		Liquefied	Natural	Gas	–	Market	Challenges	and	Opportunities	for	

Innovation.		Hydrocarbon World,	Dec.	2006.	

49. Anon.:		"Mt.	Hayes	LNG	Storage	Facility	‐	Submitted	to	British	Columbia	Utilities	

Commission	by	Terasen	Gas,	Inc.",	June	2007.	

50. Malik,	M.	R.,	and	Bushnell,	D.	M.	(eds.):		Role of Computational Fluid Dynamics and

Wind Tunnels in Aeronautics R&D,	NASA	Technical	Publication	(publication	pending).	

51. Bower,	K.N.,	and	Choularton,	T.W.:		A	Parameterization	of	the	Effective	Radius	of	Ice	

Free	Clouds	For	Use	in	Global	Climate	Models,	Atmospheric Research,	Vol.	27,	1992,	

pp.	305‐339.	

52. Hallier,	B.:		Aerosol	and	Climate	Modeling	‐	A	Summary	of	Existing	Aerosol	and	Cloud	

Chamber	Research	Facilities,	NASA	Langley	internal	white	paper,	July	2010.	
31 

Appendix 

Partial List of Existing Ground-Based Aerosol and Cloud Chamber Research 

Facilities and Summary of Capabilities (from Ref. 52) 

1. DOE Facilities at Pacific Northwest National Lab (PNNL)

Atmospheric Research Chamber

● Aerosol	formation	and	transformation	

● Role	of	aerosols	as	condensation	nuclei	

● Aerosol	processes	associated	with	anthropogenic,	biogenic,	and	biomass	

burning	compounds	

Ice Nucleation Chamber

● Artificial	clouds	under	precisely	controlled	temperature	and	super	saturation	

conditions	

● Isolation	of	particles	from	aerosol	to	study	ice	nucleation	

● Portable	to	study	ambient	aerosols	

2. UC Riverside Atmospheric Process Lab

● Aerosol	formation	and	evolution	in	the	troposphere	

● Consists	of	two	90	m3	reactors	

● No	cloud	process	abilities	

 Supported	by	EPA	

3. DRI Ice Physics Lab

● Static	diffusion	chamber	

● Ice	nucleation	and	electrification	studies	

● Produces	study	on	ice	habits	on	glass	fiber	

 Not	highly	subscribed	

4. DRI Storm Peak Lab

STORMVEx

● Location:	3220	m	high	mountain	in	Colorado	

● Equipment	for	airborne	cloud	research	

● Will	study	situ	cloud	and	precipitation	property	measurements	
32 

ISPA

● Studies	effects	of	pollution	aerosols	on	snow	growth	by	riming	and	snowfall	

amounts	on	the	ground	

● Results	have	implications	for	water	resources	in	the	inner	mountain	west	

 Supported	by	Nevada,	NSF,	DOE	

5. NASA GRC Particulate Aerosol Lab (SE‐11)

● Provided	aerosol	and	ice	particle	measurements	during	recent	ACCRI	tests	

● Flow	through	chamber	(N2)	

● Pressure:	Sea	level	to	50,000	ft	

● Temp:	Ambient	to	‐70C	

● Humidity:		0‐100%	(RHi)	

● Chamber	Velocity:	0.5	to	3	m/s	

● 3	Windows	and	panel	for	probe	insertion	

● Capability	for	exhaust	introduction	

● Studied	effect	of	soot	and	sulfuric	acid	on	ice	formation	

6. Leipzig Aerosol Cloud Interaction Chamber

● Investigates	physical	and	chemical	processes	in	the	polluted	troposphere	

● Flow	through	chamber	

● Flow	tube	1‐10	m	in	length	

● Temp:	‐40C	min	

● Used	for	CCN	studies	

7. AIDA

● Location:	Germany,	Karlsruhe	Institute	of	Technology	

● Size:	4	m	diameter,	7	m	high,	84.5	m3

● Pressure:	0.01	to	1013	hPa	

● Temp:	183K	to	323K	

● Uses	air	as	working	fluid	

● Ice	saturations	achieved	by	expansion	

● Wall	temperature	actively	controlled	

● Used	for	both	IN	and	CCN		studies	

● Many	techniques	for	generating	test	aerosols	

● Capability	for	addition	of	instruments	

8. National Institute of Radiological Sciences

● Location:	Japan	

● Volume:	25	m3
33 

● Radon‐aerosol	chamber	

● Temp:	278‐303K	

● Humidity:		30‐90%	

● Pressure	between	inside	and	outside	of	chamber	can	be	negative	

● Particle	Concentration:	108‐1010	m‐3

9. Institute of Chemistry and Dynamics of the Geosphere (ICG)

● Volume:	260	m3

● Studies	reactions	of	the	surface	of	aerosols	

● Uses	high	resolution	FTIR	spectroscopy	to	track	gas	concentrations	

● Equipped	with	a	scanning	electrostatic	classifier	

				10.		ARM Mobile Facility (AMF)

● Tracks	interaction	between	clouds	and	aerosol	particles	

● Measures	optical,	chemical,	physical,	and	cloud	activation	properties	

● Equipped	with	many	additional	inlets	to	enable	additional	equipment	to	be	

added	

● Condensation	Nuclei	Counter	

● Multiple‐Supersaturation	Cloud	Nuclei	and	Condensation	Nuclei	Counter	

● Particle/Soot	Absorption	Photometer	

					11.		Meteorological Research Institute Cloud Simulation Chamber

● Location:	Tsukuba,	Japan	

● 1	pressure	vessel	and	one	temperature	vessel	

● Volume:	1.4m3

● Pressure:	1000	to	below	30	hPa	

● Temp:		30	to	‐100C	

● Chamber	Velocity:	0	to	30	m/s	

● Studies	cloud	formation	and	ice	properties	

					12.		Colorado State University

● Continuous	Flow	Diffusion	Chamber	

● Studies	ice	formation	on	aerosol	particles	

● Some	funding	from	NASA	

					13.		Energy Research Center of the Netherlands

● Location:	Netherlands	

● Used	to	study	the	cloud	activation	of	ambient	aerosol	

● Very	high	flow	rate	(30m3/min)	
34 

● Uses	forward	scattering	spectrometer	probe	for	measuring	cloud	droplet	

number	concentration	

● Uses	high‐flow	cascade	impactors	for	chemical	characterization	of	aerosol	

● Compared	the	number	of	cloud	droplets	created	in	clean	marine	air	vs.	

polluted	marine	air	

						14.		Vector GmbH Bremen Aerosol Chamber

● Location:	Germany	

● Volume:	9	m3

● Used	to	study	α‐Pinene	ozonolysis	in	the	presence	of	ammonium	sulfate	or	

sulfuric	acid	seed	particles	

						15. Oak Ridge National Lab Environmental Sciences Division

● Mission:	“(1)	investigation	of	particle	behavior	in	the	atmosphere	and	

industrial	workplaces,	(2)	interactions	of	engineered	and	anthropogenic	

pollution	particles	with	biological	systems,	and	(3)	development	of	advanced	

instrumentation	and	measurement	methodology”	

● Relation	to	Jaguar	(largest	existing	supercomputer)	(see	below)

● Funding	sources	include	DOE	and	DOD	

					16.		European Supersites for Atmospheric Aerosol Research (EUSAAR)

Aspvreten Research Station (ASP): 

 Location:	About	80	km	south	of	Stockholm	at	the	Baltic	coast	

 Determines	the	physical	and	chemical	properties	of	the	aerosol	and	contains	

additional	meteorological	instruments	as	well	as	basic	instrumentation	for	

gaseous	compounds	

 Measures	particle	size	distribution	from	10	to	500	nm	

 Particle	mass	in	two	fractions,	PM10	and	PM	2.5

 Particle	mass,	carbonaceous	material	(Organic	Carbon,	Elemental	Carbon)	

 Black	Carbon,	soot	

 Meteorological	conditions	

 Tracks	air	pollution	levels	over	time	

Zeppelin Research Station (ZEP): 

 Location:	Svalbard ́s	west	coast,	474m	above	sea	level	in	an	undisturbed	

Arctic	environment	

 Owned	by	the	Norwegian	Polar	Research	Institute	and	is	used	mostly	by	the	

Norwegian	Institute	for	Atmospheric	Research	
35 

 Performs	studies	on	the	atmosphere,	snow	and	ice	properties,	and	Earth’s	

energy	balance	

BEO Moussala Research Station (BEO): 

 Location:	High	mountain	in	Bulgaria	away	from	pollution	

 Equipped	with	meteorological	instrumentation,	O3	and	NOx	concentration	

equipment,	devices	for	radio	aerosol	research,	X‐ray	florescence	analysis,	

neutron	and	gamma	measurements	

 Run	by	the	Bulgarian	Academy	of	Science	

Cabauw Experimental Site for Atmospheric Research (CBW): 

 Location:	An	agricultural	area	in	the	western	part	of	The	Netherlands	

 Has	a	variety	of	air	masses	around	from	clean	maritime	to	continental	

polluted	

 Measures	land	atmosphere	interaction	and	cloud,	aerosol	and	radiation	

interaction	

 Also	measures	aerosol	properties,	aerosol	optical	depth	using	a	CIMEL	sun	

photometer,	and	aerosol	extinction	and	backscatter	profiles	using	a	

backscatter	lidar	

 Run	by	KIMI	

Finokalia Research Station (FKL): 

 Location:	SE	Mediterranean	away	from	local	sources	of	pollution

 Air	is	representative	of	synoptic	scale	atmospheric	composition

 Equipped	with	in‐situ	meteorological	instrumentation	as	well	as	continuous	

measurements	of	gaseous	(O3,	CO,	NOx,	and	NOy),	particulate	(optical	

properties,	chemical	composition,	mass,	and	mass	size	distribution)	and	wet	

deposition	

 Location	has	frequent	dust	events	which	is	ideal	for	studying	the	interaction	

of	gaseous	compounds	with	heterogeneous	surfaces	(like	dust	and	sea‐salt)	

 Run	by	the	Environmental	Chemical	Processes	Laboratory	

Harwell Research Station (HWL): 

 Location:	Harwell,	United	Kingdom	

 Used	as	a	rural	station	representative	of	large	scale	air	masses	affecting	

Southern	England	

 Equipped	with	in‐situ	meteorological	instrumentation	as	well	as	continuous	

measurements	of	gas	phase	(O3,	NOx,	SO2)	and	particulate	(mass	

concentration,	size	distribution,	chemical	composition)	pollutants	

 Run	by	University	of	Birmingham	
36 

High Altitude Research Station Jungfraujoch (JFJ): 

 Location:	Jungfraujoch,	Switzerland	

 Located	far	from	local	pollution	sources;	well	suited	to	determine	the	

background	above	a	continental	area	

 Equipped	with	a	full	suite	of	gas	phase	components	(measures	both	situ	and	

column	properties),	and	aerosol	measurements	are	performed	by	PSI	

 The	station	is	within	clouds	40%	of	the	time,	making	it	well	suited	for	cloud‐

aerosol	interaction	study	

 Run	by	the	International	Foundation	High	Altitude	Research	Stations	

Jungfraujoch	and	Gornergra	

JRC-Ispra Atmospheric Research Station (JRC): 

 Location:	JRC‐Ispra,	Italy	

 Located	tens	of	kilometers	from	local	sources	of	pollution	and	is	

representative	of	the	regional	polluted	background	

 Equipped	with	in‐situ	meteorological	instrumentation	along	with	continuous	

measurements	of	gaseous,	particulate	(optical	properties,	size	distribution,	

chemical	composition)	species	

 Will	use	LIDAR	in	future	

 Run	by	the	Institute	for	Environment	and	Sustainability	of	the	EC	‐	DG	Joint	

Research	Centre	
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and cloud-aerosol phenomena can be experimentally simulated and studied in a controlled environment. This report presents a high-level argument for 

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