BOREAS: Boreal Ecosystem-Armospnere 5tudy Forrest G. Hall and Piers J. Sellers4

Mike Appi'. Dennis 8a1doccht. Josef Cihlal Barry Goodison". HanJc MargoUI. and Alan Nelso�.

aJ Biospheric Sciences Brtllf:Ch. Cotk 923 Godd4rd Space Flight Center. Greenbelt. Md. 20771 bJ Forestrv Canada. Forestry CaIfIlIiQ. Edmonton. Albena. CatulIi4 c) Natio";'l Oceanic anti Atmospheric AdministrationiARL. Oak Ridge. Tn. dJ Canadian Centre for Remote Sensing. Onawa. Ontario. CatulIi4 e J Canadian Climate Centre. Atmosphere Envir01llMnt Service. Downsview. Ontario. CatulIi4 J) Laval University. Ste-Foy. Quebec. Canada g) University Sciences Research Association. Goddard Space Flight Center. Greenbelt. Md.

BOREAS is a four-year. regional-scale experiment. starting this vear. to studv the forested continental interior of Can­;.tda. The objective �f BOREAS is to improve our understanding of the interaction between the earth' s climate system and the boreal forest at short and intermediate time scales. in order to clarifv their role in global change. BOREAS will focus on bette� understanding the biological and physical interactions between the boreal ecosystem and atmosphere that govern the land-atmosphere exchange of energy. water. carbon and green­house gases. More specifically. BOREAS will address ( i) the biogeochemical cycles underlying lar:d surface-atmosphere in­teractions and ecosystem dynamics (ii) the energy-water cycles underlvin!1: these interactions and their implications for climate -.:han!1:�. t ii i' the i mplications of climate change for boreal ecos�"tem �tucture. function and dynamics. In addition. BOREAS will develop and test satel l i te remote sensing algo­rithms t<l trJ,nsrer nur understandi n g or" the above processes . rom tne '!lcal scale to regIOnal and global scales.

i30RE.-\S \1. til Jeploy rield -.:ampalgns In tne \I. I nter and ,ummer or Il)l/ .. t followed by at least two years or coordinated. interdiSCiplinary analysis of the data. About 75 i nvestigation teams 1.1.111 be funded within BOREAS. including forest ecolo­"ISts and ecopny"iologists. atmospheriC phYSicists. boundar�­iayer meteorologIsts. hydrologIsts. biochemists. atmosphenc -:hemlsts and remote sensIng special ists. BOREAS is beIng led

·,l Intlv bv "i ASA and the Canadian Center tor Remote Sensmg. \l.lIh 'I\!nlti(ant I nvolvement from a number or ()[her l'S and (;.tnadl;n agencies. The LS/Canaoa ulmbmed budget \\.Ii1 :lllai about �.'5 mJilion over [he next tour � ears.

Global Change Fn"d tuel -.:ombustion and deforestanon are almost -':er­

I .. llnl\ the -.:ause or rapidly increasI n g concentranons or atmos-

L.S ",llaonraunl! a.rencles mcluae (he :"allonaj SCIence Foundauon. the

'\�1I0nal Oceanic �no Atmospnenc Admlnt.uallon.theTS Geojo�lcaj Survey. .�� En\lr<lnmental Prolecllon Agencv: Collaborallng C�naalan AgenCies In ..

.. uoe In� "�lIonal S":lence ana En!!1neertn!! Researcn Council. EnVironment .. naoa 1 -\tmo,onenc Environmental Service. Parks C�naaal. h,reslrv Can ..

� .... :, c:ncul[ure I.. "naoa ano Ihe :"allonal Researcn ClunCI!.

March 1993

pheric C02, observed originally by Dave Keeling at Mauna Loa. Continuation of fossil fuel as our primary energy source is projected to double the atmospheric concentrations of C02 by the mid-21st centurY. Gerumt1 circulation models of the aunospbere predict that a doubling of C02 would increase the earth's average surface air temperatUre somewhere between I.S to 4.S °C, and produce wetter winters and dryer summers than present; indeed. because the geographic distribution of these projected cbanges are not uniform. temperature increases for . continental interiors at higher latitudes are projected to be as

high as 10°C. If such warming and drying does occur, it would undoubtedly alter the sttucture and function of terrestrial eco­systems. including forests. croplands. wetlands and deserts. polar ice caps and eventually the oceans.

Our understanding of the coupled Earth system. is integrated and embodied in computer simulation models: atmospheric general circulation models (GeMs). coupled biosphere-atmos­phere models. coupled air-sea interaction models. ecosystem dynamics models. cryospheric process models. atmospheric chemistry and radiation models. These simulation models are continually updated in an attempt to capture the latest scientific knowledge and theoretical developments. Incomplete under­standing of global processes. as well as mathematical and computational constraints. limit our ability to simulate and predict the effects of anthropogenic activities on global change. As modem technological developments have rapidty increased (omputational capacity. model approximations reflecting in­-.:omplete understanding have become a serious factor l imiting

our ability to simulate Earth system processes. and to evaluate the Implicatlons of \'anous envIronmental management and tnltJ gatton ,[rate!!les.

In atmospnenc GC�ts tor example. mathematical and phySICal representations of sub-grid processes (e.g. "urface radiation. energy and mass exchange. c louds. and convection I occurring below 50 to 100 km resolution are very approximate. Realistic modeling or these processes IS important tor cl imate prediction.

,-\nother major uncertaInty In our abi l ity to predict future

dimate. is the uncertaInty in the nux ot carbon among the major :;Iobal pools: [he atmosphere. the oceans. and the vegeta­

tion/soi ls of terrestnal ecosy�tems. How will carbon exchange ..Imong these pools be effected by climate change? .-\re terres .. lnal ecosystems currently net sources or net sinks of CO2') How ..Ire these sources and SInks distnbuted geographically) Ho\l. Jo the source/SInk �trengths depend on climate change!

Earth Systems Science; Quantifying Global Change

In the late 1970·s. as the impl ications of Keeling's dara began to be more Widely appreCIated. groups of scientists ;:uhered to discuss [he state ot sClenuric knowledge and issues �oncerntn g Earth ,vqem ''':Ience. Out ,)[ these meetings

9

emerged several organizations to focus attention on these issues in an international context on an ongoing basis. In 1983 the World Climate Research Program (WCRP) convened a group of scientists to discuss the state of knowledge concerning land surface-atmosphere interactions. and their effect on climate. The group quickly recognized that the state of knowledge concerning such interactions was woefully inadequate to un­derstand the long-term climate implications of Keeling' s find­ings: or for that maner. to accurately predict weather in the short term. The· International Satellite Land Surface Climatology Project ( ISLSCP) was formed to stimulate a series of regional­scale experiments designep to improve the state of knowledge in this area. The first such experiment. the First ISLSCP Field Experiment (RFE) was conducted over a prairie grassland during 1987. involving over 100 scientists: an extensive data set was collected. and analyzed. with results published in a number of papers. culminating most recently in a RFE special l�sue2 . Other important land-surface experiments. included HAPEX ( I 'J861. conducted over agncultural areas in Southern. France and HAPEX Sahel ( 1992).

The nex( logical step in this sequence of field experiments is BOREAS. The boreal ecosystem is a step up in complexity from the prairie grasslands aod it should prove to be an impor­tant player in global change. BOREAS will examine. in addi­tion to land-surface climatology issues. other important issues germane to terrestrial ecology: ecosystem processes underlying energy and water cycles. carbon cycles. biogenic trace gas emissions and ecosystem dynamics at a regional scale. In the �ections to follow we will examine these issues in more detail ,md descnbe the expenmental approach to addressing them.

The Boreal Ecosystem The nnreal. (If c:old northern fnfests. ,ire C:lfcumpo iar In

. tent. .. llu �,:rrentl\ ,[ore ,:Dout a 'I\tn ill Ihe I,mu', ,'f!C:.lnlC: . .;rf)on. h lii\l\\ In!C tne i:.ls( ICC: ;t!Ce I :I.DO() \ cJrs JO!0' the O!lJCl­

.. teu ,1fl:J ill "orth ....... mem:a Ilas Jccumuiated an Jverage !If

.,hOll! IJ.I tl) IJ.2 :,!lgatons ot carbon per year. mostlv 1!1 If'. ,oils.

hut aho 1!1 It> ,tanding vegetation. \Vhile the term "boreal"

_,mnm ne nfet:l�eiy defined. It is a relatively 'Imple et:osyqem.

,narauenzeLi maInly hy 5 dominants: blackiwhlte �pruce. lack rme . . I'pen/birt:h. IJrch and bog!!"n t:()mplexe�. Bogs and fens .. fe pooriv dr:uned . . , Iowly det:. nosmg. nutrient noor areas.

:,UJIl\ C:lI\ erell hy ,phagnum :

The uornmant climatic char:

,e�. i.lrt:h Jno hi �k ,prut:e. 'IStlt: ot the bore:: . lone I� a

-nor! �ro\\ Ing ,eJ�lln. iasnng lro . ..jte .\Ia\ tOla(e ....... ugu,L\\ IIh

<lnl! JJ\' anll 1,)\\ ,olar elevation anglt!, .. l.,nnual oreclOltatlon Jl)mmJ(e, C\ Jporatton. �l) (hat lakes. bogs and fens ..Ire numer­

JUS.

\' . .llUfJI ul,turoance c:ontfOh the t:ornp0'itlon ano ,tfUC(Ure

'I Ihe horeal torest. SuccessIOn or tire-adapted "pecles trom

iJrge. :I�htenmg-mduced burns. determInes the t:ommuntty ,llmpmlllOn and \lructure. Topography and fi re :.tre :.tlso major

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determinants of landscape patch structure. In the natural wil­derness areas of the boreal forest. fire clears a given patCh about once each 100 years. Early successional species such as tire­adapted jack-pine and aspen tend to repopUlate dryer soils in elevated terrain more subject to fire. while more slowly grow­ing black spruce and larch tend to popUlate bogs and fens and borders along river courses. Prior to fire control programs initiated in the nineteen-fifties. fires consumed large areas before they were extinguished naturally by snow or rain: thus. the boreal landscape is characterized by large patch sizes. In fU'e-controlled areas. spruce and fir eventually dominate and replace aspen and jack-pine which are relatively short-lived at about 80 to 100 years.

In the mid-continental boreal forest where the BOREAS study will be conducted. prairies and aspen woodland abut the southern margins. while at the northern margins. conifer forests slowly fade to open forest/tundra. Low moisture is generally believed to be limiting at the southern end. while low tempera­tures determine the northern boundary. As climate warms and dries in this region. it is hypothesized that the southern margins of the boreal forest will move northward. as disturbed areas are replaced by grassland species more adapted to the warmer. dryer climate. At the northern margins. warmer temperature may result in a slow retreat of the tundra and a repopulation by conifers. In addition. the bog/fen complexes should begin' to dry. with accelerated decomposition of the stored peat.

Ecosystem Dynamics and the Global Carbon Cycle

The annual increase in airborne carbon. precisely known from Keeling's and others CO� measurements. is about _�

;;Igawns. This net r:.tte 1)1 increase IS \ ery fapid in comparison :,) hlStoflt:al tluctuatlons: howe\·er.lt I' ralher , mail in comoan­,dn tll the ;;:0" ,ll1nual Jtmospnere-,urtat:e cxcnange r,ll e .

,-,\u mated ,n aDOU( 200 glg:.ttons. But Illr thiS mcre:.tse 1!1 Jlr­

horne t:arbon. the earth' s m:eans and terrestrial ecosytems are lIearly 1!1 neutral cJrbon balance on an annual baSIS. and have ,lpparently heen so tor hundreds or thousands 01 years. What IS the source then. ot this imbalance. Jnd how t:an It be mitigated ·"

The use llt fosstl fuels contnbutes :'.5 glgatons of t:arbon (0

the atmosphere each year. The t:ontnbutlon from deforestation . I' It!ss precl'ieiv known. but IS about (j.n to 2.6 glgatons per year. il)r a total Jtrnosphenc mput of fl. I to II. I :,!lgatons. If only .' :,!Igatons "ta\" alrbornt!. \\here does (he other _; to j gigatons go'

Between In tl) 2...1 ;!lgatons 1\ estlmateo to be :.tbsorbed Jnd ,c4ut!�(eli Into [he oceans by photOSyntheSIS. This leaves U.7 to .\.5

;;Igatons stili unaccounted tor. Is it being absorbed by terrrestnal XOsv(em" J If ,, ). \\ hlt:h nnes J Will Ihe\ L'llntmUe to ,oak UD

..:arbon as the climate warms. or Will they become net sources! Rapid derorestauon m the troptcs make them a net source of

..:arbon. as discussed above. It has been argut!d that annual and latitudinal \:mattons m atmosphenc CO, c:oncentraUons Imply

.1 ma.lo r ,Ink llt t:arbon In (he "orthern hemisphere mid latl­

:uues. \\ Itn (he boreal ecosy'tem posslblv plaYIng a role. If '0.

IEEE Geoscience and Remote Sensing Society New ...... r

the carbon must be accumulating in the shon time scale pools (50 to 100 yrs,. i.e .• the standing woody biomass of the forest. or in the litter. roots or soluable organic compounds in the soil. If this is the case. how will these accumulation rates change with warming? .

Calculations of the long-term carbon storage rates of Nonh American regions glaciated Juring the last ice age. show that soil carbon storage rates probably are no greater than about 0.2 gigatons per year. In fact. the boreal forest soils could become a net source of carbon if the 10°C warming occurs as predicted by atmospheric GeMs. How then. on balance. will the carbon storage rates in the boreal ecosystem change with climate?

Will photosynthesis rates increase faster than litter decom­position rates as warming and drying occur. increasing carbon storage in the shon-term litter pool? Will increased carbon and methane release from increased microbial activity in fens and bogs. large carbon pools within the boreal forest. act as a net ,ource! Wi II warming and drying produce unfavorable climatic

.:onditions for boreal forest species at their southern margins.

decreasing the carbon storage rates as the prairies march nonh­

ward? At the nonhern margins. where productivity is primarily temperature limited. will warming increase carbon storage? Will tire frequency increase as a result of warming and drying. leading to increased disturbance rates. and altered successional patterns! How will this affect carbon storage!

Currently. there are no ecosystem models that can ade­quately address these questions. We do not know if the boreal ecosystem is a net source or sink of carbon. or how rapidly that might change with climate. If we are to answer these questions

we mu\t address the following issues: I I I How Will stored carbon I n the boreal soilS. particularly

:<.:n, anu bogs. be arfected by rapid warming and drvlng !

II F"II()\\ Ing uisturoance. how uoes the rlux Of carbon. I.e.

I;:l f1f1rnan f1f(\UW;llOn [<lr me \ e;:etallon anu ,olis. I.lcpenu <In

_ dillale.llle ( lHnpu,",H lOn l)[ 1n\'aUing - pecles [<lllowlng ulStur­:->ance. a!.!e. and conditIon Of the ,otis!

'1111 How \\ iii the di ... turbance frequencIes themselves de­:'end lIn cilmate. particularly tire frequency . natural mortah ty

.;nU Inse(t Inlestauons,'

I IV I How \\ iii forest ,uccesslon rathway� he altered by

,i Itnate (nange: How \\ III the rei au ve competltl vene ...... <>f the "()feal ,peCle, he alfected relative to each other. ;lnd relative (0 IlOn-poreal 'pecles "

\ I How Joes permarrost control blOme nro(}uctlOn and

'litrogen mlneraiIzauon : What I� [he roie ot ,now melt m the .. ' ;l!er huuge[ ;lnd I iner decompositIOn rates. How \\ Iii perma­: ro�t J I , [n OU liUn be affected by climate change.'

\ I J Hll\\ does [he hyuroroglcai CYCle. Includmg -now.

,now melt. ramfall . and ,urtace hydrology affect the carbon

:lux. ;lnd how \\ iii it be modi tied by clImate change I These rather broad SCIentific issues wli l give flse to many

hvpothese,. ;lnd detine a number of expenments which wtl l be

:l1Plementeu ilver the BOREAS [est ,Ile. In the enu. these �\ Dume,e, \\ I II be tested In the context or coupled cllmate-eco-

March 1993

::.

system computer simulation models. including forest succes­sion models. carbon dynamics models. ",ulricnt cycling mod­els. mesoscale atmospheric circulation models. radiation exchange models etc.

The Energy-Water Cycle Large uncenainties in predicting climate response to atmOS­

pheric COl originate in the assumptions found within surface models used by atmospheric GCMs. Until the early 1980's the effects of biological controls on evapotra.Rspiration. and the effects of heterogeneous landscapes on mesoscale circulation were largely neglected. To calculate the exchange of radiation • heat. moisture and momentum between the land surface and the atmosphere. the models treated the earth' 9 land surface as

a biologically inert. horizontally homogeneous land surface. Water balance was handled with a so-called "bucket" model. in which soil moisture levels were calculated from differences between precipitation.runoff and evaporation: evaporation was

assumed to be independent of the biological properties of the

vegetation covering the surface. These simple assumptions gave rise to large errors. since

much of the solar radiation intercepted by a vegetated surface

is dissipated according to a complex set of physiological con­

trols. in the form of "latent" heat. or evapotranspiration though

the stomatal pores of the plants or by evaporation from the soil. Heat released in this form. cools the surface. releasing the heat into the upper atmosphere in the form of "sensible" heat when it condenses and fonns clouds. Variations in atmospheric water vapor. transparent to visible radiation yet an efficient absorber at thennal wavelengths. and its condensation into highly retlec­t i ve clouds. further complicates the calculation of atmospheric radiatiun balance. High-level ,trarospheric clouds retlect more 'diar raUlalion than they tran. tendmg to coul the atmosphere .

L,mer-Ie\el clouus have the llppo'>lte effect. Thus. t(l unoer­'lano the e rfect or ,urrace healing on atmosphenc clrculauun. It is cruCIal to accurately calculate ,>urt·ace evaporation and its crfects on the global dismbutlon uf atmospheric water vapor.

.-\ number ut sensllivity .,tudies have shown that the overly­,imple '>urface assumptions embedded In most land-,>urface parametenzattons u,>ed in atmosphenc GC\ls result in O\'eres­lImatlon In the ,>urtace evaporatlon rate. The models ignore ". egetatl\ e restriction of evaporauon hy leaf stomata dunng penods or high evaporatlve demand or low mOisture supply,

Other �Imulatlons usmg mesoscale models have shown that honzontal heterogeneity In \ egetatton cover at a landscape ,cale. (;In mduce mesoscale clrculatton paltems. ,imllar [0 "lake effects" [hat can 'Igmricantly enhance surface momen­tum and energy exchange Detween the surtace and the atmo,­phere. Efforts [0 (orrect tor thIS effect mvolved coupling ,ub-grld mesoscale Circulation models [0 the general circula­l Ion models.

ImprO\'ed coupled biosphere/:umosphere models have a key

mle [0 Diay In reducmg these uncertamtles. ,-\ number III ceg lOnai-,..:ale blospnere-atmospnere mudels have been devel-

11

oped to scale existing leaf-level understanding of physiological controls on evapotranSpiration to extant meteorological condi­tions such as photosynthetically active radiation absorbed by the canopy. vapor pressure deficit at the canopy. air tempera­ture. windspeed. root-zone soil moisture etc.

FIFE focused on developing and testing improved bio-_ sphere-atmosphere models. and satellite remote sensing tech­

niques to drive the models. Conducted during 1987 and 1989 over a 15 x 15 km prairie grassland in central Kansas. the scien­tific nndings from FIFE demonstrated three very relevant things: (i) coupled biosphere/atmosphere models can accurately model energy and mass exchange at a regional scale over a homogeneous grassland. (ij) satellite remote sensing can pro­vide accurate parametric inputs to those models. and (iii) the exchange of energy and mass between the atmospheric bound­ary layer (the turbulent layer) and the free atmosphere is twice as large as had been assumed by conventional atmospheric GCMs. These results are already being in corporated into < 'peratlonal weather forecast and large-scale climate models.

With respect to the energy-water cycle. a number of impor­tant additional scientific issues must be addressed for the boreal ecosystem. Among these are:

( i I How do the tenns affecting surface radiation balance depend on community composition and structure: e.g .. albedo. emissivity'! Will the simple two-stream radiation models used in some current biosphere-atmosphere models be adequate to ..:ompute the radiation environment necessary for energy bal­ance modeling!

(ii) How do the open. rough. forested canopies affect the rurouient transfer of heat and moisture' Will the one-dimen­.Innal diffu�ion models u�ed in biosphere-atmo�phere models !'e adequate. or Will more complex do�ure methods he needed'.'

'III How \.\. ill [he mo"es and li..:hens ore\':lIent In horeal i<:q '1.ll1lh .!llI:C[ C: '. ;lOoratlon. "III hl';u 111I\ . •. i:ll alhello'

'. I rio\.\. are leal ono!O�yntnetlc i';l[C� 1 1 r1f..ell [() iL'ar-k\el ·Il ,mala ! ..:omroi and canopy e\'aporatlon In horeai �pecles .' Can .1o�orheJ phot()s� mhetlcally a..:uve r:.lJlatlon hv [he ..:anopy he

�:.lklilateJ lI�lng 'Imple lme-dimenslonal r:.ldlatl\'e [ransler 'l1oJeh )If mu�t more ,nphistlcated moueh .. t..:countlng t<)r ,haJowln',! hy canopy ,upponlng qructure� he emo ioyeJ!

, I C;l11 [he C:.ll1opy- ievel relallon� ue\e/opeu in BOREAS

he ,,;;lled to the regIOnal leI. d. \\ IIh heterogeneous l:.lnds..:aoes .' '. II Ho\ \. h L..lnus..:aoe neterogenell\ Ilnf..ell [ll rne�o'..::.tlt!

.;[mO'Onenc I..'m:uiallon patterns. ;lnu ho\\. 1I0 (he o:.tuerns aiter

·unace energy tlux. ;lnu ..:uupllng t"le[\\een me hounllarv l:.lver .. nu tree :.ltm(hOnere.'

\. II Ho\\. In 'ynoouc and reglOnal":lrculauon O:.l((ern� :.llfect

. de-ie\ ei , urtace 'fluxes 'It <!nergy. \\. ;l[er. ile;lt. �·;lrO()n. ;lnd . f;lce :;;l�e� .'

Biogeochemical Cycles and Trace Gas Emissions

::1..'0\\ ,(em hlogeochC!ml"::.lII..'\ clt!�. \\ IIhIn ;lnll hetweC!n me

�Io\onere ..:nu :.ltmo�onere ;.Ire runuamemal Il) ;l l..'umolC!te lIn-

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derstanding of the links between soils. vegetation and atmos­pheric: dynamics. Many of the biochemical compounds integral to ecophysiological functioning. both above ground and below ground. are also radiati-vely and chemically active in the atmos­phere. affecting both climate and atmospheric chemistry. At­mospheric moisture and temperature. in tum. drive nutriem decompositi�n rates. determine litter quality. thus are inti­mately coupled to ecosystem carbon storage and cycling rates. Below-ground processes. important to carbon storage and allo­cation. as well as trace gas emissions are particularly poorly understood.

Biogenic compounds released from the forest vegetation and soils. will react in the atmosphere along many different pathways to produce thousands of secondary compounds with differing oxidation properties. For example. isoprene and monoterpenes are highly reactive with the hydroxyl radical and thus have several important implications for atmospheric chemis­try. They are capable of generating atmospheric pollutants such as carbon monoxide and ozone in signitlcant quantities. In addition. by reacting with hydroxyl radical. NMHCs can reduce the rate of methane removal from the atmosphere. As the climate warms. the flux of NMHCs into the atmosphere could potentially increase. retarding rates of methane removal. creat­ing a positive feedback in which global warming is accelerated.

Some of the key issues to be addressed by BOREAS are:

(i) What are the key biophysical controls on the production of CH.\. CO and non-methane hydrocarbon (NMHC) fluxes?

( ii) How are canopy demands on carbon. for growth and respiration. linked to NMHC �Ynthesis and emission? How

does leaf-nitrogen concentration. leaf-water potential. and iso­prene syntha�e :.tct ivity affect :"JMHC emissions!

Iliil What :.tre the factors controlling nutrient availabilitv .

e .. j mer de..:()mOO�lllon rates. Imer comOOSllIon Ilignenmmo­o·:n I . .ll1ll '( HI r1l1tr1Cnt tllrn( )\ er f;.l[e:-. .

I \ I \Vhat 1. ;ne fllIe or fire In trace :!:.l� t!mls"lon.'

, \. ) \Vhat :.lre tne lactors ..:ontrolling tne atmo�phenc dynam­t-:� "I ,hon-il\eLi g:.l�es ,u..:h a� 0, �O,. CO and :"JMHC.

I .oprenes. terpenes. ,md o .... vgenated hydrocarbons! \ II What ;.Ire the Imponant phYSical factors controlling the

e ... change pro..:e�ses tor trace gases :.lcro" me �o"-atmosphere hounJary'

Remote Sensing Science .l..Jvances in remme 'ensmg ''':Ience m the past _i() \ ears.

:la\,e produceu the unLierstanlllng :.lnd :.tlgortthms that permit ine computer-.uued pro..:es�mg or dlglt:.ll ,ateilite ImagC!s. tll

Illler ;llmO�pnerH.:. \egetatlve. and ,,)tIs parameters charac­:cnztng e\:O" 'terns Jnd atmo,pnenc processes. Perhaps [he most mature Ci;lSS llr these algorithms are [hose tor mterrtng �ummunJ[y ..:omoosillon :.lnd ,tructural propentes of surrace (OVer: land CO\ er type. Including land-use categones f forest. JesC!rt. gr:.ls�lanJ . ..:roplands. urban I and within [hose hroad ,;Hegones more 'oeellic :ntormallon ,ucn ;.IS torest ,ucces­. iunal �[:.tge. ,�oo t\ pe. etC. The ;.Iigonrhms nave been used to

IEEE Geoscience and Remote Sensing Society Newsletter

produce land-cover maps at both regional and global scales. However. as the global modeling community has progressed. carbon cycling and land-surface climate models have generated the need for even more detailed land cover data - biomass. leaf-area index. stem densities. canopy height. canopy tempera­ture. precipitation: cloudiness. short-wave radiation. long--wave radiation. absorbed photosynthetically active radiation. These requirements push the capability envelop of current remote sensing algorithms.

Beginning in the early 80's NASA recognized the need for an intensified program of research in remote sensing science. and set aside funding for such a program. A little over 10 years later. this program. along with,research funded by other agen­cies. has begun to produce algorithms capable of inferring many of the needed parameters for selected ecosystems at regional. if not global scales. AFE for example. evaluated many of these algorithms over its grassland prairie test area. FIFE results demonstrated that (i) atmospheric corrections and -:alibrauon allzorithms were adequate to estimate surface retlec­tance to I % absolute (5 to 25% relative). using satellite remote �ensinl!: data. (ii) Radiometrically corrected satellite data could be used to estimate incident shortwave radiation with an accu­racy of 8 Wauslm2• and photosynthetically active radiation absorbed by the canopy to about :t 10%. Other biophysical parameters such as leaf area index. canopy albedo. surface soil ;noisture. and canopy temperature could also be estimated to useful but somewhat lower accuracies. (i ii ) These algorithms are for the most pan. scale invariant. and can be used to

Initialize or prescribe land-surface boundary conditions for .itmo�pheric GC\ts using coarse-resolution �atellite data.

'

The remotei�enslng sCience program In BOREAS will build 'n mls t<:chnology, tocuslng l'n the horeai ecosv�tem. <:xamln­

"" me e rrecrs mat rorest .;;;noov "f'UCal f'rooemes and mor­

'nOll)\!\ nave Illl me n::lallon,nlOs nel\\een r<:mote ,enslng llata

,.flll canooy hlophysH.:ai parameters. lnat I':

I I What erfects do wood\ 'tructures. itmbs and tWigs. have

'In these relallonshlps !

ill How does the heterogeneous. ')pen canopy architecture ,r lhe horeai forest and Its aSSOCiated shadOWing effects affect

:ne relallonships.'

Iii I How does the canopy understorv and background affect

':lese relallOnSf1Ips. parucular i\ ,oagnnum moss anu lichen

"acl\\!rounas!

( '�nopy and atmospherIC radlatl\e transrer models wIiI be

:1e t'lacl\bone Ilr algonthm de\elooment erforts. TI1ese models

,\ iiI el!her he used In the ":m'erse" moue to Inter e<.:osy�tem

:-arameters trom remote ,ensmg data. ,lr the understanding

�.!lnell trnm them wlil he lheU to clc\ elop 'Impkr. perhaps

-eml-empmcal algorIthms to Inter e<.:os"tem state . , \Vhile In FIFE there \\as a conslJeraole fOCUS on {)(ISS/I't'

, 'Ollcal and microwave remote sensmg. there was less attention

:'al(j to dCt/l't' optical and microwave, Theorv and expenment

"" :,: L ... :1..lUIJ.n ';!�l\Crnmem I' manmn\! to "liDDon J .:.: ...... Inlt!'n'l\c! !tln�-h:rm

'nll()r1n� J':[:\I(\ ��\"nu dORE,\:-)

March 1993

suggest that the active sensors may be particularly helpful in sorting out canopy structural parameters such as standing biomass. leaf-to-woody-biomass ratios. canopy water content and state. permafrost. and soil moisture. Microwave remote sensing will also play a crucial role in snow hydrology. looking at snow depth and water content. There will also be some attention paid to high-spectral resolution data in terms of their ability to infer snow properties and biochemical properties of vegetation.

BOREAS Experiment Design; Measurement, Models and Algorithms

BOREAS itself is not a long-term monitoring activity. It is not designed to watch the globe actually change.3 Rather. BOREAS will test a number of key hypotheses concerning the fundamen­tal physical. biological and chemical processes underlying global change. then use those hypotheses in a linked way. in computer-simulation models. to predict what changes mIght occur under different management and climate scenarios.

To meet the science objectives of BOREAS. there are three components to the experiment design: tield measurements. process models and remote sensing algorithms. In BOREAS. input and output parameters to the models and algorithms will be measured at or near the surface. at a variety of spatial scales. including the leaf level. plot level. stand level. regional level and mesoscale level. Using these measurements. remote sens­ing algorithms will be developed and evaluated for their ability to both initialize and validate the process models. The remote ,ensing data. along with surface and aircraft measurements will also be used to develop and validate the \ anous process models ,It scales from the stand to the mesoscale level. Once validated. .:nd the lim itations Of the models understood. predictions Il\er

,'n\!er time <ales C:ln he maue to lhell ti) I m estlgate uue,uon,

, .:ntral to �!uDal change.

The approacn to dcslgmng the BOREAS expenment there,

tore differs <.:onsl,derably. and quite conSCIOusly. from the clas­

,IC statistical deSign approach. i.e .. hypotheSIS testing using Jata acqUIred by a factonal desl gn. or probability sample of the

population, .--\s already -;rated. there are \\ ell-defined hypothe­

,es to be te,ted In BORE.\S: however. the hypotheses are

c:mbedded \\ Hhm [he \'anous ecosy\tem models and remote

-<:nslng algorrthms. c()upied In [he comOlex ways \I.e have

Jiscussed. In many ca,es. only the end-[o-cnd chams Of linked

l1vpotheses can he tested. ,lnce many Ilr the Intennediate de­

;:enuent anu Independent \allables are Imoractlcal to measure. -\n examole Ilf ,uch linked hypotheses. I� the leaf and

-:anopy-le\ ei ohotosvnthesls models. which couple hypotheses

"Jncernrng tne relationshIps among iear-Ie\'�i light Intercep' !Ion. carbon aSSImIlation rates. stomatal control by root-zone

mOIsture. temperature. and vapor pressure deficits across leaf­..;tmosphere boundanes. These links become even more con\o­

:uted a! the C:lOOpy and ,tand level where light absorotlon . -:hloroohy i l le\eis. temoerature anu \ :loor pressure orofIle,

,.lrv If1 CllmOlex \\ av, wltn canooy lleOln and stano hetero!!e-

13

neity. While some of these variables can be measured within the canopy using their values to infer canopy level values is problematical. In such cases. tluxes of CO2 and H20 vapor are measured well above the canopy, as are the independent vari­ables such as incident light. and driving meteorological vari­ables. Then. a coupled. computer-simulation model linking the

_ mUltiple hypotheses concerning canopy-level fluxes and can­opy-level meteorological variables is used to compute interme­diate values of the variables. pass them internally from one linked hypothesis to the next. to finally predict canopy or stand-level fluxes. The total. end-to-end model of canopy flux is then tested by comparing stand-level measured to predicted tlux values. The obvious disadvantage of this approach is that if the stand-level model of energy and mass tlux is "falsified", one cannot necessarily say which of the many linked hypothe­ses are false. Converselv, if the model cannot be falsified. one i� not sure of the validity of any of the linked hypotheses. since -::.tncelin!! errors amon!! them could have given rise fortuitously to non-f;lsitication. H�wever. by failing to falsify the models under a wide ran!!e of conditions. and over many replications. �onfidence in the-individual hypothesis can be developed.

Even with this simplified approach. we are faced in BOREAS with enormous logistical difficulties. requiring sig­niticant expense to acqu.ire a complete set of data for hypothesis testing. even for one sample of the total population. To instru­ment a sin!!le site with one vegetation type. requires building roads and �rails. installin!! a meteorological tower extending ,everal meters above the ;anopy. bringing in power to provide ,everal kilowatts of electricity. These requirements can bring the cost of:.t single site to around S 100.000 forrhe inrrastrucrure .done. not �ount1ng the sClentltic personnel.

Til L'(lmoensate. the horeal forest. has \ erv few 'pecles:

',Il\\e\er, ',\ Itnm ea�h \e�eta!lon t\oe there �lre tlltlerent a�e ... ",,:s. .: it terent , .. Ii rertlilty le\'eh. ,:r:.tlOa�t! c !a��e�. ..nu

,:rr'dent L'1 1 Illatt! re!pmes. :;1\ 109 nsc t() lIlan\' !e\eh within the ;'opulauon to he sampled. Thus. \\ie cannot arford the luxury or

-ciecllng a probability sample of sites. ··r.:presentatlve" Ilf the C'nme horeal e(OS\tem. We �annot e\en alford the standard ;\oenrnental pr:lCllce of replIcating sites: thererore. \\e must

:.l�e :;re:lt �:lre 10 extrapolating our exoenmental result to the

.:nme ecosv'aem and carefully calculate the error m domg so. (�\lnceo;ual". :he BOREAS measurement ".:heme \\111 in­

'-:nOe a "hox·· .IDOUt the penmeter or reglOnal-'lled study areas

-.;.,,() I-.. m:

I. '.\ Ith the :ltmo,ohenc m\ er\ Ion ia\ er at the [00 and

. De ['O[[OITI al the lower termmus or' the '(lIi honzon. Dunng -<.:leCleU renou, I,ee Expenment Timmg Jnu Execution I. c:n­

;r�v. \\ ater. r:lJla!lon. and trace g:lS rlux m and out of the box .'. I-I i he mea,ureJ. u,mg :llrcraft and surrac.: flux JevlCes. TIle -urrace ,late ur the \egetatlon will be charactenzed by m ,ItU nea!>urements at ,ejected sample sites . Remote ,ensmg Images

"r rerle(ted ,urrace radiation at \Isible. near mtmred. mid-in­'r:lred. [Dermal mfrared and microwave \\avelengths will be .C:UUlfed. This .'-JlmenslOnai. temooral data \el will be used to

"<'m If1Itlallle unu \ Jildate oroces, models . ..l� I\ell a, remote

14

;:.

sensing algorithms at spatial scales ranging from the leaf to the mesoscale level .

Sample Site Selection Approach To reduce the number of sites to a reasonable level. we have

chosen to sample near the climate. age. and moisture extremes of the boreal population. To sample climate extremes. we have chosen 400 \em:! study areas on the southern and northern "ecotones" i.e •• boundaries. of the boreal forest (see figure. I ). To sample vegetation type we have clustered I x I \em "flux tower" sites of the dominant boreal species within each study area: sites which are large enough to permit gas and energy flux to be observed using aerodynamic techniques. but small enough to be characterized by destructive and non-destructive sampling techniques. and above all. logistically feasible in terms of access and power. To rigorously test the model hy­potheses involved with carbon allocation. we have selected sites that are either "young", i.e. in a state where maintenance respiration is small compared to gross primary production. or "old". i.e. where maintenance respiration would be significant. Finally, to test the biogeochemical aspects of the models, we have chosen to work at the extremes of site productivity. �hoosing sites to be well-drained mineral soils. or in poorly drained organic soils.

With such a sampling strategy, we obviously cannot directly infer regional values of energy, water and biogeochemical tlux by simple aggregation. Rather. by testing the models and algorithms. at the extreme ranges. we hope to demonstrate the models to be robust over the entire range of the response lariable. permitting us to use the models and a�gorithms to calculate values of tluxes over the entire .+00 km- study area. To test the models regIOnally. I\ e \\lil use satellite remme -ensmg Jata tl) Jnve [he modds ;lnd emoinv tlu.x alrcrarr [,'

:lea�ure \'�llUe, Ilr energy. mOISture . .lnu tf:lCe :;:lS rluxe\ el(. ,II <::r the ,tud� area geogr:lphlC le\ei. From pre\lous expenen�e \Ie know that thIS cnmpanson requires at least a .+00 km- "lte to permit \'ahd alrcratt sample of surface gas and energy tlux. Ha\mg \enried the models at the southern and northern mar­:;ms ut the ecosystem. \\ e will have gamed some conridence that they will he robust across the enme range of dimatlc '. anables found m between.

It is :In!l�IO:lted that almost all the i:.tnd-,urtace dimatology.

nutnent cycling. trace gas �hemlstry \\ ofk .. ;.tnd remote sensmg

:lltdatlon \\Iii he Ullne \\lthm the 400 km- ,tudy :lreas. HO\\­':Ier. some ,tudles I" III also he reqUired :.tlong the approxl­:nately 000 km transect that JOins the two study areas. Here . .I � lear ecologlc:.!l ;:radlent ,hould he seen. �orresponding to the -[rong climate grJdlent along the IrJnsec!. This larger bOO I-..m -..:ale IS aiso more (ompauble with evaluation or the atmos-

pheriC GC:--Is. [n order to address these larger mesoscale issues. we wIll place some :.!uxiliary "ltes along the transects ( no tlux :ower 'lies I as well :l� augment the standard meteorological �etwork \'-lIh additional meteorological stations. radioson<le -[;mons . .lnU atmosoherlc ororilers. This network should oermll

IEEE Geoscience and Remote s.n.in9 Saciety New.letter

IIUOSON lAY

1000 1500 2500 3500 G,_"" s._ N_oI .. __ on

_____ 42"F IS.S"CI.

UNITED STATES OF AAlfIllCA

Oegtee-O_: r""_01,,-"_ • 2 eF ICCumutated for ad d..,. of tne QtOW"" ... 1Oft.

Fi{?lIre I. :'U /.:1II.r :'rJ kill BOREAS .I/lId\· areas Oil file lIorThern alld sowhern norell! ecotones.

'ile c,umallon ,It the aovec{!on ano Ji\�r�ence tcrms 'Ir the ",clcllf(ll"\!ICai lluan{![tes lI�ln\! ll�Ha ..l-,'IInIIJllIln "nh �Itmlh­

"lenc i1l1)U<.:i�.

,,, .1U�menl the tower rlux 'lIeS . . \ e ,,\ Iii '"leCt .1 l..lr�e iumher lIr '''luxtiiarY'' 'Ires. hoth tn'ilk (he J()O "m" 'LUOy

.Irea� . ..lllll along the transect. The Juxlilan' 'Ites \\!l1 not have :,miers tnr rnea�unng t1ux. bur II til he i�lr!!e "nou�h ro he : c�ol\ed bv hlgh-"patlal resolution �ar�lllte remore �enstng dO

'11) �lnd 1\ til he characrenzeo tn rams , 'I {heIr hlonhY'Ical .haracrenstlcs and salls phYSIcal properties t 'ee .\Ieasuremenls

,nll \Iea�uremenl StrategIes!. These 'ltc' \\ Iii he ,eiecteo (In ':le hasls or J ,trantieo. 'Jmpie or rhe re�!On. Ilnere ,ltes are ':lnllOn1IV 'elt:creo \1 Ith rhe c()nsrr:.lIn1 lnal Ine\ In! easliv ac­_ ':"Ihle h\ �rouno reams. These 'Ires . '.\ nO't: mt:asured hlo­

:'nv';(cal propt:rtlt:S wlil also he comoart:u to mood Jno . !gOfHhm oreolc[tons. IIIlI thus till in tne rJn!!t: ht:twt:t:n rhe : \treme� uerinell hv the rowt:r "Ites In terms, 'I lear Jrea tnllex.

"'Iomass. ,,)II types. etc.

Sample Site Selecti.on Status Ttl ,t:it:cr rhe ·+00 km- ,rudy areas. I\e '<)!Iuted tnformatlon

',()m ..ireas In C..lnaoa. havtng ,>n!!Otn\! 'lUUIt:�. "nll 'clt:C!t!lI

.:110n\! [nem u,tng a wt:II-t!t:linell 'c! ,,[ 'c::e':(IOn c:rHen�.t: (:ie

March 1993

c:llmatolog� nad {()h� represenlatl ve of the southern or northern �-:Olont:: 'lIe, II ere nOI 'lIDlt:cr It) c\tenSl\ � i'HrgIng (lr f'nliu­

'Ion: tht:y 1\ er� ne�r �Im()rt anu r�a:--onablt: accommouatlon clC.

From ..+:\ pott:ntlal c�nllldatt!s. \1 t: narrowt:d the sdectlon UO\\ n I'l ,IX candidates �nd \ I�lted them on the ground and by �Ir Junng September I t)l)(). FollOWing that. we �dec[ed two study ..lreas_ one nt:ar \:t:ison House - Thompson. \tamtoba. for the

northern t:corone_ �nd ont: nt:ar Prince :-\Ibert Saskatchewan. (\)r the sourht:rn ecotont:.

Since thar tlmt:. wt: have \ Isltt:d the �tudy areas twice yearlv

tnr appnlXlmalel\ thrt:t:-\\et:K Ot:f1mis �nd art: nt:anng comoit:­lion or the 't:lt:Ctlon process tor the tlux tower sites. To t!are. '.\e have iocalt:Ll tour ,ucn Sltt::-- 111 the nortnern studY area: III a !()O-�c�r olt! black ,oruct: 'lIt: 1 111 an xO yt:ar olt! jack pine ,Ile

'Iii) a 25 �t:ar ,lit! lack pine �Ilt:. and 11\'1 a kn .. -\n aspen �Ile .

:Jrge and homogt:nt:ous t:nough to measure canopy-It:\el t1uxes �lluid not ht: [,)und �t the nortnern 'lte \\ here a�pen srands art:

rare. We \\ I il charactenze ,maikr a�pen sites 111 this area ��

.1 part of the Juxdiarv ,ltes. In the ,outhern site. �t:lectlon '" not complete. rut an xO-\ t:ar old aspen �tand has been ,dected as � f1ux towt:r ,lte. ;tnd other candidates have been

!,)cated t'or tne r�malnllt:r. Site 't:It:CtlOn I� planned ro ht: �()moleted rhh \fa\,

IS

E.xpttr ..... nt Timing and Execution The major data collection period for BOREAS is planned

for 1994. To address the many issues defined for BOREAS. we need to have three levels of temporal sampling: (i) retrospec­tive. including historic climate. vegetation cover. and satellite data set. extending as far. back as they arc available (ii) a

...continuous record of meteorological. and satellite data during 1994 and (iii) intensive field measurements during key phe­nological and climatological periods of 1 994.

To address the historic data record. we will go to the archives and compile the relevant ground and satellite data. The Landsat data record goes back to 1972. We have searched that archive and arc ordering the relevant data. The climatological record is much longer. extending back into the 19th century. In addition. we are acquiring other relevant forest cover maps. fire and disturbance history. soils maps. and topography for the study area and intervening transect.

On a periodic basis throughout the 1 994 season. trace gas !lux. �atellite data ( Landsat TM and MSS. SPOT. NOAA .-\ VHRR. GOES etc. ). and meteorological data will be collected within the study areas and intervening transect. as well as biophysical data to characterize significant changes in either the vegetation or soils. The period of such observations will be

. determined by the dynamics of the quantities being observed and modeling requirements. The meteorological measurements will include the standard meteorological parameters. and addi­tionally. snow depth. snow water content. and radiation meas­urements.

Finally. intensive. coordinated measurements involving me­teorological. biophysical. satel lite. aircraft ;md investigator Jata collection. w i l l occur in approxi mately 3-week long peri­"ds called " I ntensive field campaigns" i 1 FC� I. During the I FCs. · :1e tn\eSll�a{Or exoenments wil l be coormnated with weather.

. ' � I i l {e ano am:rarr o\t!roass {() rorm a Il U m Ot!r n l Jetal ied data

- c: h {ll {C�{ me \ anous BOREAS hypotne�t!s anO Issues posed .i{ ,cales ram.!lll!! Trom the leaf level ( c m ' J {O {he n!!!lonai level · : 0- i-- m

: I. T-he IFC:, are planned to occur dUring the different

i'henologlcal and c l i mawlogical periods: W i nter. spnng thaw. ;reenup. peaK photosynthetic activity. ,enescence. The wi nter .1no 'Dring {haw campaigns Will be smal ler tn scope than the ·u mmer campaigns. lllvol ving a l imlteo numoer or investiga­

:llr, Interested in snow hydrology ( Wi nter ! and trace gas dynam­..; , I 'Drtn� thaw I.

These cOOrL1inated mISSIOn plans ( C\lP� I l llvol vlng aircraft. ;no In\es tl gators . w l i l be defined by the BOREAS ,Clentlsts.

.!no coordinated by BOREAS miSSIon managers. C\IP options , I i i he developed prior to the experi ment. Dunng an I Fe.

· I Derat lOns l or the day wtil be decided i n a meeting or BOREAS

,': Ient lsts [he rre\'lous e\'enlnl! based nn weather torecasts,

,\ at iable ll rcr�tt and invesug;tor resources, CvlP pnorlties .. nO weather requIrements ( c lear. cloudy. rammg etc. I . During ; ield ooeratlons. plans can be qUickly modified to meet chang­

n� conOl llons bv rapid communlcatton b\ radio and telephone " etween me m i S S I on manager, l llvesngators ano aircraft. ;\ Ir-

� IJ� ..lnO I t )02111g w l i l be no mOre [han aoout an hour awav

16

from the experimental sites so that aircraft and investigators may rcs�nd quickly to changing conditions.

Mea ............... and Measurement Sha ...... The flux measurement sites will be the lynchpins of the IFCs

and many of the periodic surface studies. These will involve aircraft and tower-mounted cddy-correlation measurements of momentum. C�, latent and sensible heat flux. In addition. measurements of soil heat flux. and net radiation will be ac­quired at each tower to complete the energy budgeL As far as possible. the terrestrial ecology efforts will be coordinated with the flux measurements to ensure the collection of vegetation. litter. soil. nuttienL moisture etc •• to test the various hypotheses linking surface states to process rates.

Biochemical cycling studies will include measurement of soil nutrient turnover rates. and flux measurements ofN20. NO and Cf4. Measurements of ecosystem trace gas fluxes using chambers will include concentrations and flu.xes of NO,. :-.IOv• 0). NMHCs. CO. PAN etc. Operation in the winter will provide an opponunity. to examine NO,IP AN. HNO) storage and indus­trial influences in the high-latitude atmosphere.

For remote sensing studies. fixed-wing'remote sensing air­

craft. equipped with optiCal. thermal and microwave sensors will be utilized to supplement satellite coverage and obtain high-spectral and spatial resolution data. In addition. helicop­ter-mounted radiometer measurements will be made over the tower tlux and auxiliary sites. Ground measurements will be made at ( i) flux tower sites. Oi) auxiliary sites. where remote sensing algorithms will be developed and ( i ii) independent auxiliary sites. where the algorithms wil l be tested. A few of the tlux tower s i tes wil l be "remote sensing super sites" where detailed electromagnetic and morphological properties of the

,tands WI l l be c haracterized for radiative transfer model devei ­

" pment ano va l idation. Once worKlllg canopy radiative transfer

models are val idated. the aux t i iary , l tes W i l l be used to develop

algorithms for I n fernng canopy biophYSical parameters trom remote sensi n g data. and to test such algorithms over a w {de range of conditions.

The histone archive ot satel l ite remote sensing data can then be computer processed uSlllg these algorithms to establish ecosystem state at earlier t i mes dunng the satellite penod of

record. Earl ier \ egetattve ,tates and historic c l imate data can

{hen he used to In t tlal ize and {est the abil ity of ecosystem process model predictions over twenty year periods.

-\tmosphenc optlcai propentes w t l l also be measured during aircraft and sate l l i te (iverpasses to correct tor molecular. aero­

,ols and water \ apor absorption and scattering. An intenSive .:alibratlon act iv i ty w t i l l ink all the alrcratt and ground spectral remote sensing I nstruments to a smgle calibration source .

For hydrolog y , �mall catchments W I l l be gauged within each ,tudy area and hydrometeorological vanables ..:ontinuously monitored - precIpitation. ,oil moisture. �now depth and ,now-water eqUIvalent. Snow interception and melt are clearly ' mponant to the h ydrological processes WIthin the biome and

Xiii be studIed within tne w i n ter and spnng-thaw campaigns.

IEEE Geoscience and Remote Sensing Society News .......

Meteorological data sets will include climatological. air quality. and synoptic data for the two study areas and surround­ing regions. The Atmospheric Environment Service (Can­ada) network will be augmented and assimilation carried out by a number of forecast centers. GOES data will be analyzed to provide data on cloudiness and surface radiation. Atmos­pheric sounding will be carried out using radiosondes. Wind speed and direction. relative humidity and temperature pro­files will be measured. in addition to biogenic hydrocarbon concentrations to provide the link between tower flux and aircraft flux data.

. Ecological studies will bridge the gap between the short­term process related studies of the (FCs and the longer term (seasons to years) ecosystem dynamics processes. These stud­ies will focus on nutrient cycles. canopy biochemistry etc .•

which will be closely linked with the flux and remote sensing measurements. Physiological data will include photosynthesis. ,[Ornata! conductance. leaf and plant water potential. chloro­phyll density. lignenlnitrogen. carboxylase concentration etc. Respiration components will be identified using chambers and porometers.

A number of computer-simulation models will be developed and run to aid in experiment design. These will include remote sensmg algorithms. biophysically based surface-atmosphere models. mesoscale atmospheric circulation models. models of the carbon cycle. and ecological models to s imulate forest biome processes.

BOREAS wil l util ize a staff to acqu ire data common to most i nvestigations: data such as satell ite and aircraft i mages. bio­phYSical characteristics and soils data. and site physiognomic data. �uch a� solis and vegetation maps. �1ore special ized data .. , I I I he acqUired hv the I Ovesugators themselves: ;.urcraft tlux :.Ha. (\ lWef r l u .x data. ecoohys loiog lcai data. t race gas t1ux etc. ' .. :1 l ile uolla I l t l\\. e\'t!r . .. , t i l he ;1\ a l iabk l ( l .l I i I n \'t!�ugaLOrs

' nrougn ;1 , narell data �yqem. Th is I, duclal tn \ leW ot the

i ntenil�cl pl t Oary nature ot BOREAS.

BOREAS Information System (BORIS) ,\s can he ,t!en from the t!xpenment descnption. the tOter­

J lsclpitnary nature of the BOREAS data set Wi l l make it volu­m toous and complex. encompa�stog hundreds ot di fferent .. :tnables Lomposed of many d i fferent types of e,.xpenments. The 'L lence I ,sues [0 be addressed by BOREAS i n vesu gators

.\ I i i requIre re lauvel y rapid and t!asy acct!ss to data acqUired bv : ne other BOREAS i nvesu gators. The t O vesugator W i l l need an , n tormatlon management syqem which acts as a central reposl­' ,lrv tor [he data. and l ists all the data tables as they become , :\ al iable. i n an organized sequence or menus that perm i ts (he

;:asv locatlon ot particular data tables. acqUired on particular Jates tw partlcu iar i nvestigators. The investigator thus should '"'e able to l\uery the database by data type. \'ariable. date. : n vestl gator etc .. Jnd each data type should be documented as I , ) how I t wa� acqUired.

The BORIS w l i l serve other tunctlons : l O geS! sate i l ite (lata.

March 1993

staff and investigator data. help quality check the data. render it to a common format. document the data. and make it available to the investigator community as rapidly as possible. BOREAS will retain a repository of online catalogs. electronic data tables. satellite and image tapes. maps. physiognomiC data. and pro­vide it on request by the investigators. All BOREAS investiga­tors will be linked electronically to the BORIS.

Furthermore. since many models require inputs compatible with theirpanicular spatial ingest grid. the point data and image data inputs to these models. often coll�ted on a different grid spacings from the model (e.g. satellite remote sensing images. or soils maps. or topo data). will have to be combined' in such a way that each model grid element can be associated with the necessary tables of point and image data values. Rather than each modeler doing this individually. it would greatly facilitate the ease and compatibility of modeling analysis if the BOREAS data tables were "gridded". That is. for an arbitrary grid over­lay. data points from all data types could be associated with all elements of the grid. Gridding the data set will require inputs from the modelers. Which of the data should be gridded? How should the data collected at a point (e.g. meteorological data' or tower flux data) be associated with a grid element: Krieging. contouring. aggregation? What time averaging is involved? How should the image data at one spatial resolution be aver­aged or aggregated to a different resolution? How should missing data be handled?

A data system satisfying similar requirements was . con­structed and successfully used during FIFE. The GSFC BORIS staff will b u i ld on that experience. As currently planned. BORIS will be implemented at the GSFC on a V AX duster. and staffed by a knowledgeable user support office. BORIS 'taff wi II work with investigators at workshops and be avat iable

I n [he tield to tact i i tute the �UDmISSlOn and retrIeval of data.

Experiment Status :\s of this date. tormal agreements are i n place between the

respective governments tovolved in BOREAS. a science plan Jeveloped. ol Joint US/Canada solicitation tor investigations ,ent out. proposals recei ved and evaluated by a peer renew panel. and a �ekct1on made. Some tower t1ux sites have been ,elected. and roads. trails. and towers are being constructed . .-\

workshop was held i n December ot 1 992 at the GSFC. i l1 \ olv-

109 all funded BOREAS i nvestlgators. and a number ot eXPen­ment deS i g n ,,�ues defined t o r resolution in the ne.xt kw

months . . .l. field \ I'itt and workshop I� 'Lheduled tor \Iay I l t 1 993 to fina l i ze �lte selection and complete the next leg 01 [ht!

experimen t deS ign . . .l. tie ld V I s i t to planned in August [0 (est ,orne o t the c oncepts pnor to gO tog 10(0 [he field in 1 '-)44 ,

Acknowledgements This paper' I S based i n part on the prel immary B0REAS

c! x penment plan and I O put t rom several SClentltic workshops

I nvolvl O g \ anous dements or the sC ience commun ity .

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