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D22303YI ET AL.: DRAINAGE FLOW MODELD22303global carbon and water budgets [Barry, 1993; Schimel etal., 2002], the characterization of drainage flows and theirassociated advective fluxes is especially important.[3] One line of evidence for the occurrence of drainageflows is the within canopy, S-shaped, wind profile that hasbeen widely observed [Fons, 1940; Allen, 1968; Bergen,1971; Oliver, 1971; Landsberg and James, 1971; Shaw,1977; Lalic and Mihailovic, 2002; Turnipseed et al., 2003].The S-shaped profile refers to a second wind maximum thatis often observed within the trunk space of forests and aminimum wind speed in the region of greatest foliagedensity [Shaw, 1977]. The second wind maximum is likelydue to the combined effect of local drainage flows that canachieve relatively high speeds in the lower region ofthe canopy (D.E. Anderson et al., Mean advective fluxof CO 2 in a high elevation subalpine forest duringnocturnal conditions, submitted to Agricultural and ForestMeteorology, 2005, hereinafter referred to as Anderson etal., submitted manuscript, 2005), and resistance to the meanwind flow that can reduce wind speeds in the region of thecanopy with high leaf area density [Massman, 1997;Massman and Weil, 1999; Mohan and Tiwari, 2004; Poggiet al., 2004]. The factors that most determine the potentialfor drainage flows are terrain slope and nocturnal radiativecooling of the slope surface [Fleagle, 1950; Manins andSawford, 1979; Doran and Horst, 1981; Mahrt, 1982].Although past modeling efforts have replicated localdrainage flows across sloped terrain [Mahrt, 1982], to ourknowledge, no analytical mathematical model has yetpredicted the second wind maxima within the context ofthe entire vertical wind profile. It would be of great benefitto have such a model as its use would move us closer tobeing able to close scalar and energy budgets for bothmodeled and measured flux footprints. It would alsoprovide us with even better tools for modeling the processesof scalar and energy fluxes, and thus producing greateraccuracy in our predictions of the effects of environmentalchange on ecosystem biogeochemical cycles.[4] Our past observations of wind flow patterns at theNiwot Ridge Ameriflux site have revealed the presence ofthe secondary wind maximum, especially during nights withhigh atmospheric stability [Turnipseed et al., 2003]. Weinitially attributed the near-surface maximum as being dueto nighttime drainage flows. In a subsequent study, we usedan array of four towers, each with vertical profiling of CO 2and, at least, two-dimensional wind speed to estimate themagnitude and dynamics of horizontal mean advective CO 2fluxes (Anderson et al., submitted manuscript, 2005). In thecurrent study, we continued analysis of the drainage flowpatterns using the four-tower experimental design. Inorder to interpret our observations, we developed a onedimensionalanalytical model that is able to predict theS-shaped wind profile. We constrained the model withobservations of forest canopy structure, including detailedobservations on the vertical distribution of leaf area density,and we validated some of the model predictions using anSF 6 release experiment. Finally, we tested the analyticalmodel against a numerical model developed with computationalfluid dynamics (CFD) techniques; the latter modelrepresents a more detailed, mechanistic model. Overall, ouraim was to provide more insight into the dynamics andcauses of drainage flows in this ecosystem, and prepare ameans of ultimately assessing the effect of bias in the meanhorizontal and vertical flux components on the overall massbalance for CO 2 at the study site.2. Measurements2.1. Study Site[5] The studies were conducted at the Niwot Ridge Amerifluxsite located in a subalpine forest ecosystem in the RockyMountains of Colorado (40°1 0 58 00 N; 105°32 0 47 00 W, 3050 melevation), approximately 25 km west of Boulder and 8 kmeast of the Continental Divide. The terrain of the site has aslope of approximately 5°–7° within 400 m in the east-westdirection. Detailed maps showing the site topography havebeen presented in past papers [Turnipseed et al., 2003,2004]. Predominant winds are from the west [Brazeland Brazel, 1983], flowing downslope. Summertimemeteorology produces valley-mountain airflows, withthermal-induced, near-surface upslope winds from the eastoccurring on many afternoons. Nighttime flow is nearlyalways from the west, and is often katabatic (downslopedrainage). The surrounding subalpine forest is 100 yearsold, having recovered from clear-cut logging. Verylittle understory canopy is present due to the thin, oftendry soils at the site. Other details for the site can befound in Monson et al. [2002] and Turnipseed et al.[2002].2.2. Tower Profile and EddyCovariance Measurements[6] A multiple-tower observing system was employedwhich is capable of measuring eddy fluxes and verticalprofiles of the mixing ratios of CO 2 ,H 2 O, wind speed andwind direction. This system consists of four towers: ET(east tower); WT (west tower); NT (north tower) and ST(south tower) (Anderson et al., submitted manuscript,2005). The ET and WT towers are located 150 m apartand are oriented on a west-east (240°–60°) transect. TheNT and ST towers are 150 m apart along the 330°–150°transect. Thus the four towers form the vertices of adiamond, with the west-east points of the diamond alignedalong the westerly wind vector known to dominate nighttimeflows. Eddy covariance fluxes of CO 2 , water vapor andsensible heat were measured on the two west-to-east alignedtowers. The ET tower measurement height was 21.5 m andthe WT tower measurement height was 33 m. Verticalprofiles of scalar mixing ratios, wind speed and winddirection were measured at five levels on the ET and WTtowers (1, 3, 6, 10, and 21.5 m on ET tower; 1, 3, 6, 10, and33 m on WT tower), and at two levels on the two shortertowers (1, 6 m on NT and ST towers). Wind speedand direction were measured with at least two-dimensional,and at several heights three-dimensional, sonic anemometers.The instrumentation, calibration scheme and fluxcalculation methodology have been described in detailby Anderson et al. (submitted manuscript, 2005) andTurnipseed et al. [2002, 2003, 2004].2.3. Leaf Area Density Measurements[7] Canopy structure was studied in sixteen 10 10 mplots, eight directly east and eight directly west of the ETflux tower. The first plot was established at 50 m east or2of13
D22303YI ET AL.: DRAINAGE FLOW MODELD2230350 m west of the tower, with subsequent plots established at20 m intervals. Each tree greater than 1 m in height wasmeasured in all plots (total of 839 trees) for diameter atbreast height, height to crown and maximum diameter ofcrown (typically at the base of the crown) in the N-S andE-W perpendicular coordinates, and total tree height. Aseparate survey was done of 90 representative trees(30 lodgepole pines, 30 subalpine firs, and 30 Engelmannspruces) in the plots, evaluating diameter at breast heightagainst number of branches in the upper, middle and lowerthird of the trees, using binoculars to count branches. Wefound this approach to be accurate to within 10% whenchecked against a subset of ten trees accessible by canopyaccess towers at the site; the open nature of the forest, andthin nature of the tree crowns also facilitates accurateviewing with binoculars. Linear regression models predicted37–54%, 6–24%, and 1–30% of the variance inbranch number by diameter at breast height in the top,middle and bottom sections of the trees, respectively.Representative branches from the upper, middle and lowerthird of the crown in 30 trees equally distributed amongeach of the three dominant tree species were cut at theirintersection with the bole and measured for total needle drybiomass. Needle mass was converted to needle area using aregression constructed from separate analyses of sun andshade needles in 10 trees from each of the three species.Needle areas were determined with the water immersionmethod described by Chen et al. [1997]. From knowledgeof needle area per branch, branch number per unit bolediameter, average branch length in the top, middle andbottom thirds of the canopy, and total canopy height anddiameter (average diameter of the east-to-west and north-tosouthcrown diameter measurements), we estimated theaverage leaf area index (LAI) in 10 cm, concentric circlesfor each vertical third of the canopy for each of the 839 trees.We assumed that the vertical distribution of LAI in eachthird of the canopy decreased linearly from the bottom tothe top in 1 m thick layers. From these calculations, wewere able to estimate the leaf area density (leaf area per unitvolume) for each 1 m thick vertical layer of the crown ofeach tree. The leaf area density was summed for all trees ina plot for each vertical layer between the ground and 16 m(the maximum height of the canopy) and divided by thetotal area of the plot to provide a vertical profile of leaf areadensity for the entire plot.2.4. SF 6 Experiments[8] Sulfur hexafluoride (SF 6 ) tracer experiments wereconducted in July 2001 and 2002. In 2001, SF 6 was releasedcontinuously at a steady rate from a point source located at0.2 m above the forest floor approximately 50 m upslopefrom the WT tower. In 2002, SF 6 was released from a 200 mline source deployed across the slope at 0.2 m height and50 m upslope from the WT tower. Total release rates werecontrolled with a mass flow controller, and measurementsfrom the individual capillary restrictors (every 3 m along theline) were made from approximately 1/3 of the points duringeach test day. A fast response, continuous SF 6 analyzer wasoperated with the existing CO 2 ambient profiler system tomeasure SF 6 concentrations at 14 locations on the towers(ET, WT, ST, NT) in 2001 and 2002. The profiler sequentiallysamples for 30 s at each position and the measuredconcentrations are combined into 30 minute averages. Theanalyzer was calibrated using certified commercial standards(5% accuracy) during each test day. In this paper we onlyreport the results from a single SF 6 release during August2002; this was a period when all of the release anddetection instruments appeared to functioning at optimallevels, atmospheric stability was high, and the observeddrainage flows were strong.3. Theory[9] For simplicity, the atmosphere is assumed to bestable, incompressible and inviscid. Drainage flow is assumedto develop over a constant slope with angle a. Thecoordinate system used is Cartesian, with x in the directionof the mean downslope wind, and z normal to the slope. Thecanopy structure is assumed to be horizontally uniform butvaries in the vertical coordinate. No vertical motion andhorizontal static pressure gradient are considered, andCoriolis acceleration is neglected. For the steady statecondition, drainage flow is governed by [Wilson and Shaw,1977; Mahrt, 1982]:@u 0 w 0@zg Dq sin a ¼ c D ðÞ‘ z ðÞu z2 ðÞ; zq 0where u 0 w 0 is the average shear stress, g is theacceleration due to gravity, q 0 is the ambient potentialtemperature (in this case taken at 21.5 m height andthe influence of moisture on buoyancy is neglected), Dq =q q 0 is the deficit of potential temperature in thedrainage flow (where q is the potential temperature ofthe drainage flow), ‘(z) is the plant area density facingthe mean wind (defined as the frontal area of individualelements per unit volume of canopy), c D (z) =C D (z)/p(z)is the effective drag coefficient of plant elements subjectto a shelter factor p(z) within the canopy [Massman,1997; Massman and Weil, 1999], C D (z) is the foliage dragcoefficient, and u(z) is the average mean wind velocity.The drag coefficient within the canopy is definedaccording to Mahrt et al. [2000] asc D ðÞ¼ zu2 * ðÞ zu 2 ðÞ z:where u *(z) is the friction velocity within the canopy andis related to the shear stress asu 0 w 0 ¼ u 2 * ðÞ: zAfter substitution, equation (1) becomes@ ðc D ðÞu z2 ðÞ z Þ@zc D ðÞu z2 ðÞ‘ z ðÞ¼g zDq sin a:q 0The cumulative leaf area per unit ground area belowheight z is defined asZ zLz ðÞ¼0‘ ðz 0 Þdz 0 :ð1Þð2Þð3Þð4Þð5Þ3of13
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